Annex E. Epidemiologic Studies 

E.1.Short-Term Exposure and Cardiovascular Outcomes 

E.1.1. Cardiovascular Morbidity Studies 

Table E-1 Short-term exposure – cardiovascular morbidity outcomes: PM10

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Baccarelli et al. (2007, 

091310)

Period of Study: Jan 1995-Aug 2005 

Location: Lombardia region, Italy 

Outcome: Fasting and postmethionineload total homocysteine (tHcy) 

Age Groups: 11-84 yr

Study Design: Cross-sectional / Panel 

N: 1,213 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: Age, sex, BMI, smoking, 

alcohol, hormone use, temperature, day 

of the yr, and long-term trends 

Season: Adjusted for long-term trends 

to account for season 

Dose-response Investigated? No 

Statistical Package: R v2.2.1 

Lags Considered: 1-day, 7-day ma. 

Pollutant: PM10 (some TSP measures 

used to predict PM10) 

Averaging Time: 24 h 

Mean (SD): NR 

Percentiles: 

25th: 20.1 

50th: 34.1 

75th: 52.6 

Max: 390.0 

Monitoring Stations: 53 

Copollutant: CO, NO2, SO2, O3

PM Increment: IQR 

Percent Change: [Lower CI, Upper 

CI]: Homocysteine, fasting: 0.4 (-2.4, 

3.3) 

Homocysteine, postmethionine-load: 

1.1 (-1.5, 3.7) 

Percent Change: per 25.7m3 

increase in 7-day ma of PM10

Homocysteine, fasting: 1.0 (-1.9, 3.9) 

Homocysteine, postmethionine-load: 

2.0 (-0.6, 4.7) 

Percent Change: on fasting 

homocysteine per IQR increase in 

24-h PM10 levels

Among smokers: 6.2 (0.0, 12.7) 

Among non-smokers: -1.6 (-5.5, 2.5) 

Percent Change: on postmethionineload homocysteine per IQR increase 

in 24-h PM10 levels: Among smokers: 

6.0 (0.5, 11.8) 

Among non-smokers: -0.1 (-3.6, 3.5) 

December 2009 E-1 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Baccarelli et al. (2007, 

090733) 

Period of Study: Jan 1995-Aug 2005 

Location: Lombardia region, Italy 

Outcome: Prothrombin time (PT) 

Activated partial thromboplastin time 

(APTT) 

Fibrinogen 

Functional antithrombin 

Functional protein C 

Protein C, antigen 

Functional protein S 

Free protein S 

Age Groups: 11-84 yr

Study Design: Cross-sectional / Panel 

N: 1,218 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: Age, sex, BMI, smoking, 

alcohol, hormone use, temperature, day 

of the yr, and long-term trends 

Season: Adjusted for long-term trends 

to account for season 

Dose-response Investigated? No 

Statistical Package: R software v2.2.1 

Pollutant: PM10 (some TSP measures 

used to predict PM10) 

Averaging Time: Hourly concentrations 

used to calculate lags of same day, 7-

day, 30-day, and h 0-6

Mean (SD): NR 

Percentiles: 

Sep-Nov: 

5th: 33.1 

50th: 51.2 

75th: 76.5 

Max: 148.9 

Dec-Feb: 

25th: 47.9 

50th: 68.5 

75th: 95.3 

Max: 238.3 

Mar-May: 

25th: 30.0 

50th: 64.1 

75th: 64.8 

Max: 158.5 

Jun-Aug: 

25th: 28.0 

50th: 44.3 

75th: 61.3 

Max: 94.7 

Monitoring Stations: 53 sites 

Copollutant: CO, NO2 , SO2, O3

PM Increment: SD 

Effect Estimate [Lower CI, Upper CI]: 

Estimated changes in endpoint 

PT (international normalized ratio): 

At time of blood sample: -0.06 (-0.12, 

0.00) 

Avg levels 7 days prior: -0.03 (-0.10, 

0.04) 

Avg levels 30 days prior: -0.08 (-0.14, -

0.01) 

(Hourly ma presented in Fig 2) 

APTT (ratio to reference plasma): 

At time of blood sample: 0.02 (-0.04, 

0.08) 

Avg levels 7 days prior: 0.00 (-0.07, 

0.06) 

Avg levels 30 days prior: 0.01 (-0.06, 

0.08) 

Fibrinogen: 

At time of blood sample: 0.01 (-0.05, 

0.07) 

Avg levels 7 days prior: -0.03 (-0.09, 

0.04) 

Avg levels 30 days prior: -0.02 (-0.09, 

0.05) 

Functional antithrombin: 

At time of blood sample: -0.02 (-0.09, 

0.04) 

Avg levels 7 days prior: -0.06 (-0.13, 

0.01) 

Avg levels 30 days prior: -0.06 (-0.13, 

0.02) 

Functional protein C: 

At time of blood sample: 0.00 (-0.06, 

6.1) 

Avg levels 7 days prior: -0.06 (-0.12, 

0.01) 

Avg levels 30 days prior: -0.06 (-0.14, 

0.01) 

Protein C, antigen: 

At time of blood sample: 0.00 (-0.06, 

6.0) 

Avg levels 7 days prior: -0.04 (-0.10, 

0.03) 

Avg levels 30 days prior: -0.06 (-0.14, 

0.01) 

Functional protein S: 

At time of blood sample: 0.04 (-0.03, 

0.10) 

Avg levels 7 days prior: -0.03 (-0.11, 

0.06) 

Avg levels 30 days prior: -0.14 (-0.23, 

-0.05) 

Free protein S: 

At time of blood sample: 0.05 (-0.01, 

0.10) 

Avg levels 7 days prior: 0.01 (-0.05, 

0.07) 

Avg levels 30 days prior: -0.01 (-0.08, 

0.06) 

December 2009 E-2 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Barclay et al.

(2009, 179935) 

Period of Study: Jan 2003-May 2005 

Location: Aberdeen, Scotland 

Outcome: Haematological outcomes, 

Heart Rhythm outcomes, & Heart Rate 

Variability outcomes 

Age Groups: 70.4 (8.9)

Study Design: Panel 

N: 132 patients w/ chronic heart failure 

Statistical Analyses: Linear & Mixed 

Effects Regression Model 

Covariates: Age, temperature, 

humidity, pressure 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: Lags 0-2 day 

Pollutant: PM10

Averaging Time: daily 

Mean (SD): 20.25

Min: 7.375 

Max: 68.3 

Monitoring Stations: 1 

Copollutant: PM2.5, PNC, NO2

Co-pollutant Correlation: 

NO2 city: 0.294 

NO city: 0.112 

NO2 personal: 0.055 

PNC DEOM: 0.241 

PM2.5 total: 0.476* 

PM2.5 traffic: 0.882* 

PNC total: 0.125 

PNC traffic: 0.190 

*Correlations based on 3-day avg 

concentrations 

PM Increment: NR 

Beta (Lower CI, Upper CI): 

Haemoglobin: 0.136 (-0.274, 0.546) 

Mean corpuscular haemoglobin: 0.030 

(-0.232, 0.291) 

Platelets: 0.096 (-0.923, 1.115) 

Haematocrit: 0.131 (-0.289, 0.551) 

White blood cells: 0.034 (-1.175, 1.244)

C reactive protein: -4.872 (-12.094, 

2.351) 

IL-6: 2.207 (-4.995, 9.410) 

von Willebrand factor: 0.660 (-2.651, 

3.970) 

E-selectin: -0.536 (-2.528, 1.457) 

Fibrinogen: -0.432 (-2.470, 1.607) 

Factor VII: 0.990 (-1.265, 3.245) 

day-dimer: -1.225 (-4.505, 2.055) 

All arrhythmias: -3.447 (-11.521, 4.627)

Ventricular ectopic beats: -2.110 (-

12.135, 7.915) 

Ventricular couplets: -1.561 (-10.811, 

7.689) 

Ventricular runs: -0.709 (-6.677, 5.259)

Supraventricular ectopic beats: 0.033 

(-9.242, 9.308) 

Supraventricular couplets: 0.006 

(-8.618, 8.629) 

Supraventricular runs: 3.710 (-2.847, 

10.266) 

Avg HR: 0.321 (-0.197, 0.838) 

24 h SDNN: 1.040 (-0.415, 2.494) 

24 h SDANN: 1.195 (-0.473, 2.863) 

24 h RMSSD: 0.321 (-0.197, 0.838) 

24 h PNN: 2.837 (-3.791, 9.465) 

24 h LF power: 0583 (-3.622, 4.787) 

24 h LF normalized: -3.137 (-5.540, 

-0.733)* 

24 h HF power: 0.872 (-4.649, 6.392) 

24 h HF normalized: -2.223 (-4.952, 

0.505) 

24 h LF/HF ratio: -0.296 (-3.832, 3.240)

*p < 0.05 

Notes: LF= low frequency 

HF= high frequency 

Reference: Briet et al. (2007, 093049) 

Period of Study: NR 

Location: Paris, France 

Outcome: Endothelial Function 

Age Groups: 20-40 yr

Study Design: Panel 

N: 40 white male nonsmokers 

Statistical Analyses: Multiple Robust 

Regrssion 

Covariates: R53R/R53H genotype, 

diet, subject factor, visit, temperature 

Dose-response Investigated? No 

Statistical Package: NCSS 

Lags Considered: 0-5 day 

Pollutant: PM10

Averaging Time: 24 h 

5 day Mean (SD): 43 (10) 

Monitoring Stations: NR 

Co-pollutant: PM2.5, SO2, NO, NO2, CO

Co-pollutant Correlation: N/A 

PM Increment: 1 SD 

Beta (Lower CI, Upper CI), P, R2: 

Flow-mediated brachial artery dilation: 

0.07 (-0.62, 0.76), NS, 0.03 

Reactive hyperemia: 

15.91 (7.74, 24.0), <0.001, 0.16 

December 2009 E-3 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Choi et al. (2007, 093196)

Period of Study: 2001-2003 

Location: Incheon, South Korea 

Outcome: Blood pressure 

Study Design: Cross-sectional 

N: 10459 subjects with a hospital health 

examination 

Statistical Analyses: Linear regression

Covariates: Season: Effect 

modification by season 

Pollutant: PM10

Averaging Time: Measured hourly and 

calculated 24-h means

Percentiles: 

Warm season: Median: 36.7 

Cold season: Median: 45.7 

Monitoring Stations: 9 stations 

Copollutant: NO2, SO2

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Estimate (p-value) for the relationship 

between systolic blood pressure (SBP) 

and diastolic blood pressure (DBP) and 

an increase in PM10 on lag day 1 

SBP: Warm season: 0.0798 (p < 0.001) 

DBP: Warm season: 0.0240 (p < 0.001) 

Note: No evidence of associations 

between PM10 and BP during the cold 

season

Reference: Chuang et al. (2007, 

091063) 

Period of Study: 

Between Apr-Jun 2004 or 2005 

Location: Taipei, Taiwan 

Outcome: High-sensitivity C-reactive 

protein (hs-CRP) 

Fibrinogen, plasminogen activator 

fibrinogen inhibitor-1 (PAI-1), tissuetype plasminogen activator (tPA), 8-

hydroxy-2’-deoxyguanosine (8-OHdG), 

and log-transformed HRV indices 

(SDNN = standard deviation of NN 

intervals, r-MSSD = square root of the 

mean of the sum of the squares of 

differences between adjacent NN 

intervals, LF = low frequency [0.04-

0.15Hz], and HF = high frequency 

[0.15-0.40Hz]) 

Age Groups: 18-25 yr 

Study Design: Panel (cross-sectional) 

N: 76 students 

Statistical Analyses: Linear mixedeffects models 

Covariates: Age, sex, BMI, weekday, 

temperature of previous day, relative 

humidity 

Season: Only 1 season of data 

collection 

Dose-response Investigated? No

Statistical Package: NR 

Pollutant: PM10

Averaging Time: Hourly data used to 

calculate avg over 1- to 3-day periods 

Mean (SD): 1-day avg: 49.2 (18.0) 

2-day avg: 55.3 (18.6) 

3-day avg: 54.9 (18.2) 

Range (Min, Max): 

1-day avg: 29.5, 83.4 

2-day avg: 25.5, 85.1 

3-day avg: 22.2, 87.2 

Monitoring Stations: 2 sites (each 

pollutant measured at one site only) 

Copollutant: PM2.5, Sulfate, Nitrate, 

OC, EC, NO2, CO, SO2, O3

PM Increment: IQR (1-day avg: 32.7 

2-day avg: 34.5 

3-day avg: 26.0) 

Effect Estimate [Lower CI, Upper CI]: 

% change in health endpoint per 

increase in IQR of PM10 (1-3 day 

averaging period 

single pollutant models)

hs-CRP: 1-day: 135.8 (1.8, 269.7) 

2-day: 108.2 (-10.9, 227.3) 

3-day: 109.6 (2.5, 216.7) 

8-OHdG: 1-day: -9.2 (-21.5, 3.2) 

2-day: -6.1 (-17.0, 4.8) 

3-day: -5.6 (-13.8, 2.6) 

PAI-1: 1-day: 30.0 (12.4, 47.7) 

2-day: 19.1 (3.6, 34.7) 

3-day: 21.2 (9.7, 32.8) 

tPA: 1-day: 16.0 (-4.1, 36.2) 

2-day: 10.4 (-6.3, 27.2) 

3-day: 8.8 (-2.8, 20.5) 

Fibrinogen: 1-day: 5.3 (1.5, 15.2) 

2-day: 1.5 (-4.4, 7.5) 

3-day: 3.3 (-1.1, 7.7) 

Heart Rate Variability 

SDNN: 1-day: -4.9 (-7.8, -2.1) 

2-day: -4.0 (-6.6, -1.4) 

3-day: -4.1 (-6.1, -2.2) 

r-MSSD: 1-day: -4.8 (-12.3, 2.7) 

2-day: -2.2 (-9.0, 4.7) 

3-day: -4.0 (-9.0, 0.9) 

LF: 1-day: -6.1 (-10.1, -2.1) 

2-day: -3.0 (-7.2, 1.2) 

3-day: -4.3 (-7.0, -1.6) 

HF: 1-day: -5.5 (-13.0, 2.1) 

2-day: -2.7 (-9.5, 4.1) 

3-day: -2.0 (-7.2, 3.2) 

December 2009 E-4 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ebelt et al. (2005, 056907) 

Period of Study: Summer of 1998 

Location: Vancouver, Canada 

Outcome: CVD 

Age Groups: Range from 54-86 yr 

mean age= 74 yr 

Study Design: Extended analysis of a 

repeated-measures panel study 

N: 16 persons with COPD 

Statistical Analyses: 

Earlier analysis expanded by 

developing mixed-effect regression 

models and by evaluating additional 

exposure indicators 

Dose-response Investigated? No 

Statistical Package: SAS V8 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Ambient PM10: 17 ± 6 

Exposure to ambient PM10: 10.3 ± 4.6 

Range (Min, Max): 

Ambient PM10-2.5: 7-36 

Exposure to ambient PM10-2.5: 

1.5-23.8 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient concentrations and exposure 

to ambient PM were highly correlated 

for each respective metric: r ≥ 0.71 

PM10-2.5: r ≥ 0.72 

PM2.5: r ≥ 0.92 

Note: Total personal fine particle 

exposure (T) were dominated by 

exposures to non ambient particles 

which were not correlated with ambient 

fine particle exposure (A) or ambient 

concentrations (C). Results for each of 

these metrics are listed. 

Effect estimates and 95% CI for IQR 

range increases in exposure 

Increment: C10: IQR = 7 μg/m3 

SBP (mm Hg): -2.2 (-4.78-0.38) 

DBP (mm Hg): -0.78 (-2.65-1.09) 

Ln-SVE (bph): 0.16 (-0.07-0.40) 

HR (bpm): 1.02 (-0.79-2.82) 

SDNN (ms): -2.14 (-6.94-2.65) 

R-MSSD (ms): -2.24 (-4.27-0.21) 

Increment: A10: IQR = 6.5μg/m3

SBP (mm Hg): -2.81 (-5.67-0.05) 

DBP (mm Hg): -0.59 (-2.79-1.62) 

Ln-SVE (bph): 0.27 (0.03-0.52) 

HR (bpm): 0.86 (-1.61-3.33) 

SDNN (ms): -3.91 (-9.73-1.91) 

R-MSSD (ms): -0.81 (-4.94-3.31) 

Reference: Folino et al. (2009, 191902) 

Period of Study: Jun 2006-May 2007 

Location: Padua, Italy 

Outcome: HRV & Inflammatory 

Markers 

Age Groups: 45-65 yr

Study Design: Panel 

N: 39 patients w/ myocardial infarction 

Statistical Analyses: Linear 

Regression Model, ANOVA 

Covariates: Temperature, relative 

humidity, atmospheric pressure, betablocker, aspirin, or nitrate consumption, 

smoking habit 

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: NR 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Summer: 46.4 (16.1) 

Winter: 73.0 (30.9) 

Spring: 38.3 (15.4) 

Monitoring Stations: NR 

Copollutant: PM2.5, PM0.25

Co-pollutant Correlation: NR 

PM Increment: 1 μg/m3

Beta (SE), p-value: 

SDNN: 0.115 (0.093), 0.218 

SDANN: 0.138 (0.103), 0.182 

RMSSD: 0.049 (0.034), 0.146 

pH: 0.002 (0.001), 0.033 

LTB4: 0.427 (0.0279), 0.126 

eNO: 0.000 (0.002), 0.851 

PTX3: -0.003 (0.001), 0.033 

C-reactive protein: -0.006 (0.004), 

0.161 

CC16: -0.002 (0.002), 0.280 

IL-8: 0.000 (0.003), 0.895 

Reference: Forbes et al. (2009, 

190351) 

Period of Study: 1994, 1998, 2003 

Location: England 

Outcome: Inflammation markers 

Age Groups: 16+ yr

Study Design: Cross-sectional 

N: 25,000 white adults w/ fibrinogen 

measurements & 17,000 white adults w/ 

C-reactive protein measurements 

Statistical Analyses: Multilevel Linear 

Regression Models 

Covariates: Age, sex, BMI, social 

class, region, cigarette smoking 

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: NR 

Pollutant: PM10

Averaging Time: Yearly 

1994 

Median: 19.5 

Range: 12.5-36.1 

IQR: 3.7 

1998 

Median: 17.9 

Range: 12.6-27.0 

IQR: 2.7 

2003 

Median: 16.2 

Range: 11.0-22.7 

IQR: 2.6 

Monitoring Stations: NR 

Copollutant: NO2, SO2, O3

Co-pollutant Correlation: N/A 

PM Increment: 1 μg/m3

Percent Change (Lower CI, Upper 

CI): 

Fibrinogen 

1994 Crude: -0.068 (-0.367, 0.231) 

1994 Adjusted: 0.080 (-0.164, 0.326) 

1998 Crude: -0.592 (-0.902, -0.280) 

1998 Adjusted: -0.388 (-0.727, -0.047) 

2003 Crude: -0.339 (-0.696, 0.019) 

2003 Adjusted: -0.069 (-0.458, 0.322) 

Combined: -0.077 (-0.254, 0.100) 

C-reactive protein 

1998 Crude: -0.914 (-2.206, 0.395) 

1998 Adjusted: -0.266 (-1.782, 1.274) 

2003 Crude: 0.286 (-1.327, 1.925) 

2003 Adjusted: 0.661(-1.068, 2.421) 

Combined: 0.140 (-1.003, 1.296) 

December 2009 E-5 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kaufman (1987, 190960) 

Period of Study: Nov 2004-2005 

Location: Isfahan, Iran 

Outcome: Inflammation 

Age Groups: 10-18 yr

Study Design: Panel 

N: 374 children 

Statistical Analyses: Linear 

Regression, Logistic Regression 

Covariates: Age, gender, BMI, waist 

circumference, healthy eating index, 

physical activity level 

Dose-response Investigated? No 

Statistical Package: SPSS 

Lags Considered: 0- to 7-day avg 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 122.08 (33.63) 

0th: 11.00 

25th: 86.50 

50th: 153.0 

75th: 191.00 

Monitoring Stations: 3 

Copollutant: O3, SO2, NO2, CO 

Co-pollutant Correlation: NR 

PM Increment: NR 

Beta (SE): 

CRP: 1.5 (0.2) 

Ox-LDL: 1.4 (0.1) 

MDA: 1.3 (0.1) 

CDE: 1.1 (0.1) 

HOMA-IR: 1.1 (0.3) 

Reference: Liao et al. (2004, 056590) 

Period of Study: 1996-1998 

Location: ARIC study cohort 

(Washington County, MD 

Forsyth County, NC 

and selected suburbs of Minneapolis, 

MN). 

The 4th quarter of the ARIC cohort was 

sampled exclusively from black 

residents of Jackson, MS. 

Outcome: 5-min HR, HRV indices (HF, 

LF, SDNN) 

Study Design: Cross-sectional

Statistical Analyses: Linear regression

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 24.3 (11.5) 

Copollutant: 

O3

CO 

SO2

NO2

PM Increment: SD

Effect Estimate [Lower CI, Upper CI]: 

Estimate (SE) 

HF: -0.06 ms2 (0.018) 

SDNN: -1.03 ms (0.31) 

H: 0.32 beats/min (0.158) 

Reference: Liao et al. (2005, 088677) 

Period of Study: 1987-1989 baseline 

health exam 

Location: 3 centers in the U.S. 

(Forsyth County, NC 

suburbs of Minneapolis, MN 

black residents of Jackson, MS) 

Outcome: Fibrinogen, factor VIII coagulant activity (VIII-C), von Willebrand 

factor (vWF), white blood cell count 

(WBC), and serum albumin 

Age Groups: 45-64 yr

Study Design: Cross-sectional 

N: 10,208 participants (7705 for PM) 

Statistical Analyses: Multiple linear 

regression 

Covariates: Age, sex, ethnicity-center, 

education, smoking, drinking status, 

BMI, history of chronic respiratory 

disease, humidity, season, cloud cover, 

and temperature 

Dose-response Investigated? 

Yes, examined higher-ordered terms for 

each pollutant 

Statistical Package: SAS v8.2 

Pollutant: PM10

Averaging Time: 24-h avg (1, 2, and 3 

days prior to the exam) 

Mean (SD): 29.9 (29.9) 

Mean (SD) within Quartiles: 

Q1-3: 24.0 (6.96) 

Q4: 47.3 (10.11) 

Copollutant: 

CO, SO2, NO2, O3

PM Increment: 1 SD (12.8 μg/m3)

Effect Estimate: Adjusted regression 

coefficient (SE): Fibrinogen (mg/dl): 

0.163 (0.755) 

Factor VIII-C (%): Non-linear 

association: β (PM10) = -5.30, p < 0.01 

β (PM10)2 = 0.80, p < 0.05 

vWF (%): Diabetics: 3.93 (1.80) 

Nondiabetics: -0.54 (0.58) 

Albumin (g/dl): CVD: -0.006 (0.003) 

Non-CVD: 0.029 (0.017) 

p < 0.05 

December 2009 E-6 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Liao et al. (2007, 180272) 

Period of Study: 1999-2004 

Location: 24 U.S. states 

Outcome: Ectopy 

Age Groups: Women 50-79 yr

Study Design: Panel 

N: 57,422 

Statistical Analyses: Logistic 

regression & random effects modeling 

Covariates: Age, race, center, 

education, history of CVD/chronic lung 

disease, rel. humidity, temperature, 

smoking 

Dose-response Investigated? No 

Statistical Package: SAS, Stata 

Lags Considered: Lags 0-365 day 

‡ Monitors used in model for spatial 

interpolation of daily PM values. 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD)*: 

All: 27.5 (12.1) 

No Ectopy: 27.5 (12.1) 

Any Ectopy: 27.5 (11.9) 

5th, 95th percentile*: 

All: 12.2, 48.9 

No Ectopy: 12.3, 48.8 

Any Ectopy: 11.8, 49.3 

Monitoring Stations: NR‡ 

Copollutant: PM2.5 

Co-pollutant Correlation: NR 

*Lag 1 

PM Increment: 10 μg/m3

Percent Change (Lower CI, Upper 

CI): 

All Ventricular Ectopy 

Lag 0: 1.01 (0.95, 1.07) 

Lag 1: 1.02 (0.96, 1.09) 

Lag 2: 0.99 (0.93, 1.06) 

Current Smoker Ventricular Ectopy 

Lag 0: 1.21 (0.96, 1.53) 

Lag 1: 1.32 (1.07, 1.65) 

Lag 2: 1.22 (0.95, 1.56) 

Nonsmoker Ventricular Ectopy 

Lag 0: 1 (0.93, 1.06) 

Lag 1: 1.01 (0.94, 1.07) 

Lag 2: 0.98 (0.92, 1.05) 

All Supraventricular Ectopy 

Lag 0: 1 (0.95, 1.06) 

Lag 1: 1 (0.95, 1.05) 

Lag 2: 0.99 (0.94, 1.04) 

All Ventricular or Supraventricular 

Ectopy 

Lag 0: 1 (0.95, 1.04) 

Lag 1: 1 (0.96, 1.04) 

Lag 2: 0.98 (0.94, 1.02) 

Reference: Liu et al. (2007, 156705) 

Period of Study: 

May 2005-Jul 2005 

Location: Windsor, Ontario, Canada 

Outcome: Heart rate, blood pressure, 

brachial arterial diameter, flow-mediated 

vasodilatation (FMD), plasma cytokines, 

and thiobarbituric acid reactive 

substances (TBARS) 

Age Groups: 18-65 yr

Study Design: Panel 

N: 24 nonsmoking subjects with type I 

or II diabetes over a 7 week period (2-

14 visits for subjects) 

170 total vascular measurements and 

134 total blood samples collected 

Statistical Analyses: Mixed effects 

regression models 

Covariates: (Time-dependent 

covariates) Daily temperature, relative 

humidity, blood glucose level, also 

checked for confounding by ambient air 

pollutant concentrations (controlled for 

ambient PM2.5) 

Season: No adjustment since testing 

was completed within a 7-wk period 

during early summer 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Pollutant: PM10 (personal) 

Averaging Time: Real-time monitor 

measured exposure during 24-h period 

prior to clinic measures

Median (5th-95th percentile): 

0-24 h: 25.5 (9.8-133.0) 

0-6 h: 15.3 (5.3-83.2) 

7-12 h: 17.0 (7.1-186.3) 

13-18 h: 28.5 (11.4-167.0) 

19-24 h: 30.5 (10.1-148.2)

Monitoring Stations: 

Personal monitoring 

Copollutant (correlation): 

Ambient PM2.5 (r = 0.34) 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

**p < 0.05 

*p < 0.10. Regression coefficients (SE) 

End-diastolic basal diameter (μm): All 

subjects (n=24): -2.52 (3.27) 

subjects not taking vasoactive meds 

(n=17): -3.93 (3.66) 

subjects w/BMI ≤ 29kg/m2 (n=14): 8.85 

(5.85) 

End-systolic basal diameter (μm): All 

subjects (n=24): -9.02 (3.58)** 

subjects not taking vasoactive meds 

(n=17): -10.59 (4.36)** 

subjects w/BMI ≤29kg/m2 (n=14): 3.85 

(5.49) 

End-diastolic FMD (%): All subjects 

(n=24): 0.20 (0.08)** 

subjects not taking vasoactive meds 

(n=17): 0.23 (0.09)** 

subjects w/BMI ≤29kg/m2 (n=14): 0.12 

(0.05)** 

End-systolic FMD (%): All subjects 

(n=24): 0.38 (0.18)** 

subjects not taking vasoactive meds 

(n=17): 0.51 (0.22)** 

subjects w/BMI ≤ 29kg/m2 (n=14): 0.18 

(0.10)* 

Flow (cm/s): All subjects (n=24): -0.16 

(0.19) 

subjects not taking vasoactive meds 

(n=17): -0.48 (0.21)** 

subjects w/BMI ≤ 29kg/m2 (n=14): -0.39 

(0.23)* 

Heart rate (bpm): All subjects (n=24): 

0.01 (0.11) 

subjects not taking vasoactive meds 

(n=17): -0.06 (0.12) 

subjects w/BMI ≤ 29kg/m2 (n=14): 0.15 

(0.12) 

Diastolic blood pressure (mm Hg): All 

subjects (n=24): 0.19 (0.16) 

subjects not taking vasoactive meds 

December 2009 E-7 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

(n=17): 0.40 (0.18)** 

subjects w/BMI ≤ 29kg/m2 (n=14): 0.27 

(0.21) 

Systolic blood pressure (mm Hg): All 

subjects (n=24): 0.17 (0.19) 

subjects not taking vasoactive meds 

(n=17): 0.43 (0.24)* 

subjects w/ BMI ≤ 29kg/m2 (n=14): 0.38 

(0.24) 

CRP (μg/mL): All subjects (n=24): 0.11 

(0.07) 

subjects not taking vasoactive meds 

(n=17): 0.10 (0.09) 

subjects w/ BMI ≤ 29kg/m2 (n=14): 0.02 

(0.03) 

ET-1 (pg/mL): All subjects (n=24): 0.00 

(0.00) 

subjects not taking vasoactive meds 

(n=17): 0.00 (0.00) 

subjects w/BMI ≤ 29kg/m2 (n=14): 0.00 

(0.01) 

IL-6 (pg/mL): All subjects (n=24): 0.00 

(0.05) 

subjects not taking vasoactive meds 

(n=17): 0.01 (0.05) 

subjects w/BMI ≤ 29kg/m2 (n=14): -0.00 

(0.03) 

TNFα (pg/mL): All subjects (n=24): 

0.03 (0.05) 

subjects not taking vasoactive meds 

(n=17): 0.02 (0.05) 

subjects w/ BMI ≤ 29kg/m2 (n=14): 0.03 

(0.08) 

TBARS (pmol/mL) All subjects (n=24): 

16.12 (4.00)** 

subjects not taking vasoactive meds 

(n=17): 8.10 (9.18) 

subjects w/ BMI ≤ 29kg/m2 (n=14): -

0.28 (6.60)

regression coefficients (SE) among 

subjects not taking vasoactive 

medications, with lag time 

End-diastolic basal diameter (μm): 0-

6 h: 29.91 (10.64)**

7-12 h: 0.72 (3.95)

13-18 h: -3.62 (2.80)

19-24 h: -0.57 (1.7)

End-systolic basal diameter (μm): 0-6 

h: 28.88 (11.22)**

7-12 h: -0.78 (4.58) 

13-18 h: -7.70 (3.30)**

19-24 h: -2.87 (2.05) 

End-diastolic FMD (%): 0-6 h: -0.12 

(0.10)

7-12 h: 0.04 (0.05)

13-18 h: 0.11 (0.03)**

19-24 h: 0.12 (0.04)**

End-systolic FMD (%): 0-6 h: 0.36 

(0.08)**

7-12 h: 0.48 (0.32)

13-18 h: 0.19 (0.06)**

19-24 h: 0.34 (0.13)**

Flow (cm/s): 0-6 h: -0.34 (0.22)

7-12 h: -0.26 (0.27 

13-18 h: -0.27 (0.15)*

19-24 h: -0.30 (0.11)**

Heart rate (bpm): 0-6 h: 0.31 (0.13)**

7-12 h: 0.26 (0.12)**

December 2009 E-8 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

13-18 h: 0.01 (0.09)

19-24 h: -0.08 (0.05)

Diastolic blood pressure (mm Hg): 0-

6 h: -0.29 (0.12)**

7-12 h: 0.24 (0.12)**

13-18 h: 0.46 (0.17)**

19-24 h: 0.18 (0.14)

Systolic blood pressure (mm Hg): 0-

6 h: -0.65 (0.18)** 

7-12 h: 0.17 (0.19)

13-18 h: 0.86 (0.24)**

19-24 h: 0.11 (0.10)

CRP (μg/mL): 0-6 h: 0.15 (0.13)

7-12 h: 0.15 (0.13)

13-18 h: 0.03 (0.06)

19-24 h: 0.04 (0.03)

ET-1 (pg/mL): 0-6 h: 0.02 (0.00)**: 7-12 

h: -0.00 (0.00)

13-18 h: -0.00 (0.00)

19-24 h: 0.00 (0.00)

IL-6 (pg/mL): 0-6 h: 0.03 (0.06)

7-12 h: 0.00 (0.06)

13-18 h: 0.02 (0.03)

19-24 h: 0.00 (0.02)

TNF-α (pg/mL): 0-6 h: 0.01 (0.07)

7-12 h: 0.09 (0.04)**

13-18 h: 0.01 (0.04)

19-24 h: -0.00 (0.03)

TBARS (pmol/mL): 0-6 h: -4.44 (6.72)

7-12 h: 11.94 (5.08)**

13-18 h: 5.06 (4.03)

19-24 h: 1.06 (4.64)

Note: Adding ambient PM2.5 data as a 

covariate in the model yielded similar 

regression coefficients for personal 

PM10

Reference: Lipsett et al. (2006, 

088753) 

Period of Study: Feb-May 2000

Location: Coachella Valley, CA 

Outcome: HRV parameters: SDNN, 

SDANN, r-MSSD, LF, HF, total power, 

triangular index (TRII).

Study Design: Panel study

N: 19 non-smoking adults with coronary 

artery disease

Statistical Analysis: Mixed linear regression models with random effects 

parameters 

Pollutant: PM10

Averaging Time: 2 h

Mean (range): 

Indio: 23.2 (6.3-90.4)

Palm Springs: 14 (4.7-52)

Monitoring Stations: 2

Copollutant: O3

PM Increment: SE*1000

Effect Estimate (change in HRV per 

unit increase in PM concentration): 

SDNN: -0.71 msec (SE = 0.268)

Notes: Weekly ambulatory 24 h ECG 

recordings (once per week for up to 12 

wk), using Holter monitors, were made.

Subjects’ residences were within 5 

miles of 1 of 2 PM monitoring sites.

Regressed HRV parameters against 18: 

00-20: 00 mean particulate pollution. 

December 2009 E-9 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ljungman et al. (2008, 

180266) 

Period of Study: Aug 2001-Dec 2006 

Location: Gothenburg & Stockholm, 

Sweden 

Outcome: Ventricular Arrhythmia 

Age Groups: 28-85 yr

Study Design: Case-crossover 

N: 88 patients w/ implantable 

cardioverter defibrillators 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, humidity, 

pressure, ischemic heart disease, 

ejection fraction, heart disease, 

diabetes, use of beta-blockers, age, 

BMI, location at time of arrhythmia, 

distance from air pollution monitor 

Dose-response Investigated? No 

Statistical Package: Stata, S-plus 

Lags Considered: Lags 2-24 h 

Pollutant: PM10

Averaging Time: Hourly 

Gothenburg, Stockholm 

Median: 

2h: 18.95, 14.62 

24 h: 19.92, 15.23 

Min: 

2h: 0.00, 0.33 

24 h: 2.13, 3.96 

Max: 

2h: 203.75, 159.79 

24 h: 78.01, 90.50 

IQR: 

2h: 14.16, 11.59 

24 h: 11.49, 9.59 

Monitoring Stations: 2 

Copollutant: PM2.5, NO2

Co-pollutant Correlation 

2 h NO2: 0.36 

24 h NO2: 0.29 

PM Increment: Interquartile Range 

Odds Ratio (Lower CI, Upper CI): 

2 h: 1.31 (1.00, 1.72) 

24 h: 1.24 (0.87, 1.76) 

Notes: OR of ventricular arrhythmia for 

an IQR increase of air pollutants in 

different subgroups (Fig 2) 

Reference: Ljungman et al. (2009, 

191983) 

Period of Study: May 2003-Jul 2004 

Location: 

Athens, Greece 

Helsinki, Finland 

Ausburg, Germany 

Barcelona, Spain 

Rome, Italy 

Stokholm, Sweeden 

Outcome: Interleukin-6 Response 

Age Groups: 35-80 yr 

Study Design: Panel 

N: 955 male myocardial infarction 

survivors 

Statistical Analyses: Additive Mixed 

Models 

Covariates: Age, sex, BMI, city, 

HDL/total cholesterol, smoking, 

alcohol intake, HbA1c, NT-proBNP, 

history of MI, heart failure, or 

diabetes, phlegm 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1 day 

Pollutant: PM10

Averaging Time: 24 h 

Mean: 31.6 

25th: 21.1 

75th: 38.4 

Monitoring Stations: NR 

Copollutant: CO, NO2, PNC, PM2.5

Co-pollutant Correlation 

PM2.5: 0.81 

PM Increment: Interquartile Range 

(17.4 μg/m3) 

Change of IL-6 (Lower CI, Upper CI), 

p-value: 

0.0 (-1.3, 1.3), 1.0 

Reference: Mar et al. (2005, 087566) 

Period of Study: 1999-2001

Location: Seattle, WA 

Outcome: Change in arterial O2 saturation, heart rate, and blood pressure 

(SBP and DBP) 

Age Groups: >75 yr

Study Design: Panel study

N: 88 elderly subjects

Statistical Analysis: GEE 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 

Indoor: 12.6 (7.8)

Outdoor: 14.5 (7.0) 

PM Increment: 10 μg/m3

Unit change in measure(95% CI): 

Among all subjects: 

Each increase in outdoor same day 

PM10 was associated with: SBP: -0.10 

mmHg (95% CI: -1.37, 1.18) 

DBP: -0.03 mmHg (95% CI: -0.79, 0.73)

HR: -0.48 beats/min (95% CI: -1.03, 

0.06)

Each increase in indoor same day 

PM2.5was associated with: SBP: 0.92 

mmHg (95% CI: -0.95, 2.78) 

DBP: 0.63 mmHg (95% CI: -0.29, 1.56) 

HR: 0.02 beats/min (95% CI: -0.54, 

0.58) 

Notes: Results by health status 

presented in Fig 1. Used 2 sessions 

that each were 10 consecutive days of 

measurement. Used personal, indoor, 

and outdoor measures of PM2.5

December 2009 E-10 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Metzger et al. (2007, 

092856) 

Period of Study: Jan 1993-Dec 2002 

Location: Atlanta, GA 

Outcome: Days with any event 

recorded by the ICD, days with ICD 

shocks/defibrillation and days with 

either cardiac pacing or defibrillation 

Study Design: Repeated measures 

N: 884 subjects 

Statistical Analysis: Logistic 

regression with GEE to account for 

residual autocorrelation within subjects 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 28.0 (12.2) 

Median: 26.4 

Copollutant: 

O3, NO2, CO, SO2. Aug1998-Dec2002: 

Oxygenated hydrocarbons 

PM Increment: OR (95% CI): 

Outcome = Any event recorded by ICD

OR = 1.00 (95% CI: 0.97, 1.03) 

Reference: Min et al. (2008, 191901) 

Period of Study: Dec 2003-Jan 2004 

Location: Taein Isalnd, South Korea 

Outcome: Heart Rate Variability 

Age Mean (SD): 44.3 (21.9) 

Study Design: Panel 

N: 1.349 participants 

Statistical Analyses: Linear 

Regression 

Covariates: Age, sex, BMI, smoking 

Dose-response Investigated? No 

Statistical Package: SAS, R 

Lags Considered: 0-72 h 

Pollutant: PM10 

Averaging Time: 1 h 

Mean (SD): 33.244 (19.017) 

Percentiles: 

25th: 18.000 

50th: 26.000 

75th: 41.000 

Range: 187.000. 16.000 

Monitoring Stations: 1 

Copollutant: NO2, SO2

PM Increment: 1 SD (19 μg/m3) 

Percent Change: [Lower CI, Upper 

CI]: 

SDNN 

6-h avg: -4.34 (-7.99, -0.55)** 

9-h avg: -5.48 (-9.61, -1.17)**h^ 

12-h avg: -6.23 (-10.47, -1.79)*** 

24-h-avg: -4.73 (-9.73, 0.56)- 

48-h avg: -1.25 (-5.59, 3.29) 

72-h avg: -0.85 (-5.35, 3.86) 

LF 

6-h avg: -10.32 (-18.05, -1.86)** 

9-h avg: -13.79 (-22.26, -4.39)*** 

12-h avg: -14.48 (-23.18, -4.80)*** 

24-h-avg: -13.15 (-23.36, -1.57)** 

48-h avg: -0.10 (-9.99, 10.87) 

72-h avg: -7.61 (-17.04, 2.88) 

HF 

6-h avg: -1.07 (-10.43, 9.28) 

9-h avg: -3.28 (-13.72, 8.43) 

12-h avg: -4.06 (-14.77, 8.00) 

24-h-avg: -1.22 (-13.96, 13.41) 

48-h avg: -3.55 (-14.01, 8.18) 

72-h avg: -3.88 (-14.64, 8.23) 

Notes: Percent change in HRV for air 

pollution children, adults, and the 

elderly (Fig 2) 

Percent change in HRV for PM10

exposure in all ages (Fig 3) 

December 2009 E-11 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peters et al. (2009, 

191992) 

Period of Study: May 2003-Jul 2004 

Location: 

Helsinki, Finland 

Ausburg, Germany 

Barcelona, Spain 

Rome, Italy 

Stokholm, Sweeden 

Outcome: Plasma Fibrinogen 

Age Groups: 37-81 

Study Design: Panel 

N: 854 adults 

Statistical Analyses: Additive Mixed 

Models 

Covariates: Age, sex, BMI, city, 

HDL/total cholesterol, smoking, 

HbA1c, NT-proBNP, history of 

arrhythmia, asthma, arthrosis, stroke, 

bronchitis, season, apparent 

temperature, relative humidity, 

weekday, hour of visit 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0- to 5-day avg 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 30.3 

Min: 0 

Max: 194 

Monitoring Stations: NR 

Copollutant: PM2.5, PM10-2.5

Co-pollutant Correlation: NR 

PM Increment: 13.5 μg/m3

Change (Lower CI, Upper CI): 

Genotype 1 1 

rs2070006: 1.22 (0.47, 1.96) 

rs2070011: 1.16 (0.41, 1.90) 

rs1800790: 0.27 (-0.36, 0.91) 

rs2227399: 0.27 (-0.36, 0.91) 

rs6056: 0.19 (-0.45, 0.83) 

rs4220: 0.19 (-0.45, 0.83) 

Haplotype in cluster 2: 0.09 (-0.53, 

0.76) 

rs1800791: 0.18 (0.21, 1.40) 

Genotype 1 2 

rs2070006: 0.5 (-0.19, 2.15) 

rs2070011: 0.42 (-0.28, 1.13) 

rs1800790: 1.28 (0.54, 2.01) 

rs2227399: 1.28 (0.55, 2.02) 

rs6056: 1.26 (0.49, 2.04) 

rs4220: 1.27 (0.49, 2.04) 

Haplotype in cluster 2: 1.17 (0.35, 1.99)

rs1800791: 0.40 (-0.48, 1.28) 

Genotype 2 2 

rs2070006: 0.11 (-1.94, 2.15) 

rs2070011: 0.08 (-2.08, 2.24) 

rs1800790: 2.15 (0.71, 3.60) 

s2227399: 2.18 (0.73, 3.63) 

s6056: 2.24 (0.72, 3.77) 

s4220: 2.25 (0.73, 3.78) 

Haplotype in cluster 2: 2.16 (0.61, 3.71)

rs1800791: -0.13 (-1.84, 1.58) 

Reference: Rosenlund et al. (2007, 

114679) 

Period of Study: 1985-1996 

Location: Stockholm County 

Outcome: Myocardial Infarction 

Age Groups: 15-79 yr

Study Design: Case-control 

N: 24,387 first event of myocardial 

infarction cases and 276,926 population 

based controls 

Statistical Analyses: Logistic 

Regression 

Covariates: Age, sex, calendar yr, SES

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: 5 yr 

Pollutant: PM10

Averaging Time: 5 yr 

Median: 2.4 

5th-95th: 0.3-6.2 

Median: 2.2 

5th-95th: 0.3-6.0 

Monitoring Stations: NR 

Copollutant: NO2, CO 

Co-pollutant Correlation: HNR 

PM Increment: 

5th-95th percentile (5μg/m3) 

Odds Ratio (Lower CI, Upper CI): 

All Subjects 

Controls: 1.0 

All Cases: 1.04 (1.00, 1.09) 

Nonfatal Cases: 0.98 (0.963, 1.03) 

Fatal Cases: 1.16 (1.09, 1.24) 

In-hospital death: 1.05 (0.95, 1.17) 

Out-of-hospital death: 1.23 (1.14, 1.33) 

Subjects who did not move b/t 

population censuses 

Controls: 1.0 

All Cases: 1.11 (1.02, 1.21) 

Nonfatal Cases: 1.05 (0.96, 1.15) 

Fatal Cases: 1.56 (1.28, 1.91) 

In-hospital death: 1.58 (1.13, 2.19) 

Out-of-hospital death: 1.56 (1.22, 1.98) 

December 2009 E-12 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2007, 

156931) 

Period of Study: May 2003-Jul 2004 

Location: Athens, Augsburg, 

Barcelona, Helsinki, Rome, and 

Stockholm 

Outcome: Interleukin-6 (IL-6), 

fibrinogen, C-reactive protein (CRP) 

Age Groups: 35-80 yr

Study Design: Repeated measures/ 

longitudinal 

N: 1003 MI survivors 

Statistical Analyses: Mixed-effect 

models 

Covariates: City-specific confounders 

(age, sex, BMI) long-term time trend 

and apparent temperature RH, time of 

day, day of week included if adjustment 

improved model fit 

Season: Long-term time trend 

Dose-response Investigated? Used psplines to allow for nonparametric 

exposure-response functions 

Statistical Package: SAS v9.1 

Pollutant: PM10

Averaging Time: Hourly and 24 h (lag 

0-4, mean of lags 0-4, mean of lags 0-1, 

mean of lags 2-3, means of lags 0-3) 

Mean (SD): Presented by city only 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: Central 

monitoring sites in each city 

Copollutant: 

SO2

O3

NO 

NO2

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

% change in mean blood markers per 

increase in IQR increase of air pollutant.

IL-6: Lag (IQR): % change in GM 

(95%CI) 

Lag 0 (17.4): -0.34 (-1.66, 0.99) 

Lag 1 (17.4): -0.69 (-1.95, 0.58) 

Lag 2 (17.4): -1.59 (-3.99, 0.88) 

5-day avg (13.5): -0.87 (-2.28, 0.55) 

Fibrinogen: Lag (IQR): % change in 

AM (95%CI) 

Lag 0 (17.4): 0.06 (-0.43, 0.55) 

Lag 1 (17.4): 0.14 (-0.35, 0.63) 

Lag 2 (17.4): 0.24 (-0.24, 0.72) 

5-day avg (13.5): 0.60 (0.10, 1.09) 

CRP: Lag (IQR): % change in GM 

(95%CI) 

Lag 0 (17.4): -0.71 (-2.75, 1.37) 

Lag 1 (17.4): -0.63 (-2.61, 1.39) 

Lag 2 (17.4): -1.42 (-4.23, 1.47) 

5-day avg (13.5): -1.35 (-3.45, 0.79) 

December 2009 E-13 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2006, 

088754) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: C-reactive protein (CRP) 

serum amyloid A (SAA) 

E-selectin 

vWF 

intercellular adhesion molecule-1 

(ICAM-1) 

fibrinogen 

Factor VII 

prothrombin fragment 1+2 

D-dimer 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear and logistic regression models

Covariates: Models adjusted for different factors based on health endpoint 

CRP: RH, temperature, trend, ID 

ICAM-1: temperature, trend, ID 

vWF: air pressure, RH, temperature, 

trend, ID 

FVII: air pressure, RH, temperature, 

trend, ID, weekday 

Season: Time trend as covariate 

Dose-response Investigated? Sensitivity analyses examined nonlinear 

exposure-response functions 

Statistical Package: SAS v8.2 and 

S-Plus v6.0 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 20.0 (13.0) 

Percentiles: 

25th: 10.8 

50th: 15.6 

75th: 26.0 

Range (Min, Max): 5.4, 74.5 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5

PM10

OC 

EC 

NO2

CO 

PM Increment: IQR (15.2 

5-day avg: 12.8)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as OR (95%CI) for an 

increase in the blood marker above the 

90th percentile per increase in IQR air 

pollutant.

CRP: Time before draw: 0-23 h: 1.2 

(0.8, 1.9) 

24-47 h: 2.0 (1.1, 3.6) 

48-71 h: 2.2 (1.2, 3.8) 

5-day mean: 2.0 (1.2, 3.7) 

ICAM-1: Time before draw: 0-23 h: 1.3 

(0.9, 1.8) 

24-47 h: 3.1 (2.0, 4.8) 

48-71 h: 3.4 (2.2, 5.2) 

5-day mean: 3.4 (2.2, 5.3) 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

vWF: Time before draw: 0-23 h: 4.0 

(-0.6, 8.5) 

24-47 h: 6.0 (0.6, 11.5) 

48-71 h: 1.1 (-4.9, 7.0) 

5-day mean: 6.1 (-0.6, 12.8) 

FVII: Time before draw: 0-23 h: -6.6 

(-10.4--2.5) 

24-47 h: -8.4 (-12.3--4.3) 

48-71 h: -5.9 (-9.6, -2.0) 

5-day mean: -8.0 (-12.4, -3.4) 

Note: Summary of results presented in 

figures. SAA results indicate increases 

in association with PM (not as strong 

and consistent as with CRP) 

No association observed between Eselectin and PM 

An increase in prothrombin fragment 

1+2 was consistently observed, 

particularly with lag 4 

Fibrinogen results revealed few 

significant associations, potentially due 

to chance 

D-dimer results revealed null 

associations in linear and logistic 

analyses 

December 2009 E-14 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2007, 

091379) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: Soluble CD40 ligand 

(sCD40L), platelets, leukocytes, 

erythrocytes, hemoglobin 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear regression models

Covariates: Long-term time trend, 

weekday of the visit, temperature, RH, 

barometric pressure 

Season: Time trend as covariate 

Dose-response Investigated? No 

Statistical Package: SAS v8.2 and 

S-Plus v6.0 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 20.0 (13.0) 

Percentiles: 

25th: 10.8 

50th: 15.6 

75th: 26.0 

Range (Min, Max): 5.4, 74.5 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5 

PM10 

NO 

PM Increment: IQR (15.2 

5-day avg: 12.8)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

sCD40L, % change GM (pg/mL): lag0: 

1.6 (-3.5, 7.0) 

lag 1: 1.1 (-5.4, 7.9) 

lag 2: -3.5 (-8.9, 2.2) 

lag 3: -1.4 (-6.0, 3.4) 

5-day mean: -1.2 (-7.8, 5.8) 

Platelets, % change mean (103/μl): 

lag 0: -0.4 (-1.9, 1.0) 

lag 1: 0.4 (-1.4, 2.3) 

lag 2: 0.5 (-1.4, 2.3) 

lag 3: -0.1 (-1.6, 1.4) 

5-day mean: 0.0 (2.1, 0.0) 

Leukocytes, % change in mean 

(103/μl): lag0: -1.1 (-2.8, 0.7) 

lag 1: -0.5 (-2.6, 1.5) 

lag 2: 0.1 (-2.1, 2.4) 

lag 3: -0.7 (-2.6, 1.2) 

5-day mean: -1.1 (-3.6, 1.4) 

Erythrocytes, % change mean 

(106/μl): lag0: 0.0 (-0.4, 0.5) 

lag 1: -0.4 (-1.0, 0.1) 

lag 2: -0.7 (-1.2, -0.2) 

lag 3: -0.4 (-0.8, 0.0) 

5-day mean: -0.6 (-1.2, -0.1) 

Hemoglobin, % change mean (g/dl): 

lag 0: -0.1 (-0.7, 0.6) 

lag 1: -0.4 (-1.2, 0.3) 

lag 2: -0.7 (-1.3, 0.0) 

lag 3: -0.3 (-0.9, 0.2) 

5-day mean: -0.7 (-1.5, 0.1) 

Reference: Steinvil et al. (2008, 

188893) 

Period of Study: 2003-2006 

Location: Tel-Aviv, Israel 

Outcome: Inflammation 

Age Groups: 

Mean (SD): 46 (12) yr 

Study Design: Panel 

N: 3659 

Statistical Analyses: Linear 

Regression 

Covariates: Age, waist circumference, 

BMI, HDL, OLDL, triglycerides, diastolic 

& systolic BP, alcohol consumption, 

sports intensity, medications, smoking 

status, family history of CHD, 

temperature, humidity, precipitation, 

season, & yr 

Dose-response Investigated? No 

Statistical Package: SPSS 

Lags Considered: 0-7 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

64 (100.8) 

25th: 33.1 

50th: 43.0 

75th: 60.7 

Monitoring Stations: NR 

Copollutant: SO2, NO2, O3, CO 

Co-pollutant Correlation: 

SO2: 0.043 

NO2: 0.082 

O3: -0.113 

CO: 0.075 

PM Increment: Interquartile Range 

(27.6 μg/m3

) 

hs-CRP Relative % Change (Lower 

CI, Upper CI): 

Men: 

Lag 0: -1 (-2, 1) 

Lag 1: 0 (-1, 1); Lag 2: -1 (-2, 1) 

Lag 3: -1 (-2, 0) 

Lag 4: 0 (-1, 1) 

Lag 5: 0 (-1, 2) 

Lag 6: 1 (0, 2) 

Lag 7: 1 (0, 1) 

0-7 avg: -2 (-5, 1) 

Women: 

Lag 0: 0 (-2, 2) 

Lag 1: 0 (-1, 2) 

Lag 2: 1 (0, 2) 

Lag 3: 0 (-1, 1) 

Lag 4: 0 (-1, 2) 

Lag 5: 0 (-1, 2) 

Lag 6: -1 (-3, 1) 

Lag 7: 0 (-2, 1) 

0-7 avg: 1 (-2, 4) 

Fibrinogen Absolute % Change 

(Lower CI, Upper CI): 

Men: 

Lag0: 0.7(0.0,1.5); Lag1: 0.4(-0.2, 0.9); 

Lag2: -0.1(-0.9, 0.6) 

Lag3: -0.1(-0.7, 0.6); Lag4: 0.0(-0.7, 

0.7); Lag5: 0.1(-0.7, 1.0) 

Lag6: 0.6(-0.1, 1.3); Lag7: 0.4(0.0, 0.8); 

December 2009 E-15 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0-7 avg: -0.4(-1.9, 1.0) 

Women: 

Lag0: 0.3(-0.6, 1.2); Lag1: -0.1(-0.8, 

0.7); Lag2: -0.3(-0.9, 0.3) 

Lag3: -0.1(-0.7, 0.5); Lag4: 0.2(-0.4, 

0.9); Lag5: 0.2(-0.7, 1.2) 

Lag6: -0.3(-1.4, 0.8); Lag7: 0.7(-0.1, 

1.5); 0-7 avg: 0.0(-1.5, 1.5) 

WBC Absolute Change (Lower CI, 

Upper CI): 

Men: 

Lag0: 2 (-22, 27) 

Lag1: 3 (-14, 19) 

Lag2: 1 (-22, 24) 

Lag3: -7 (-28, 14) 

Lag4: -22 (-44, -1) 

Lag5: -20 (-46, 7) 

Lag6: -5 (-27, 16) 

Lag7: -4(-16, 9) 

0-7avg: -11(-58, 36) 

Women: 

Lag 0: 20 (-6, 46) 

Reference: Su et al. (2006, 157022) 

Period of Study: Feb-Apr 2002 

Location: Taipei, Taiwan 

Outcome: Total cholesterol, HDL, 

tryglycerides, LDL, hs-CRP, IL-6, TNFα, tPA, PAI-1, and fibrinogen 

Age Groups: 40-75 yr

Study Design: Panel study 

N: 49 subjects (31 males and 18 

females) with coronary heart disease or 

multiple risk factors for CHD 

Statistical Analysis: Linear mixed 

effects regression 

Pollutant: PM10

Averaging Time: 1 h 

(High pollution day = PM10 from 08: 

00-18: 00 >100) 

Copollutant: O3

PM Increment: High vs.. Low pollution 

days 

Effect Estimate [Lower CI, Upper CI]: 

CHD patients (n = 23): P-value for 

paired t-test comparing health endpoint 

means on high and low pollution days

hs-CRP: p = 0.568 

IL-6: p = 0.856 

TNF-α: p = 0.246 

PAI-1: p = 0.008 

tPA: p = 0.322 

Fibrinogen: p = 0.189 

P-value for health endpoint in mixedeffects models 

PAI-1: p = 0.010 

tPA: p = 0.329 

Fibrinogen: p = 0.747 

Patients with multiple CHD risk 

factors (n = 26): P-value for paired ttest comparing health endpoint means 

on high and low pollution days 

hs-CRP: p = 0.475 

IL-6: p = 0.561 

TNF-α: p = 0.572 

PAI-1: p = 0.098 

tPA: p = 0.260 

Fibrinogen: p = 0.087 

P-value for health endpoint in mixedeffects models 

PAI-1: p = 0.891 

tPA: p = 0.789 

Fibrinogen: p = 0.923

Notes: Subjects had paired fasting 

blood samples taken during high and 

low air pollution days. 

December 2009 E-16 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Vedal et al., (2004, 055630) 

Period of Study: 1997-2000 

Location: Vancouver, British Columbia 

Outcome: Implantable cardioverter 

defibrillator (ICD) discharge 

Age Groups: All 

Study Design: Time series 

(Retrospective, longitudinal panel study)

N: 50 ICD patients with 1+ discharges 

(40,328 person-days and 257 

arrhythmia event days) 

Statistical Analyses: Multiple logistic 

regression with GEE 

Covariates: Temperature, relative 

humidity, barometric pressure, rainfall, 

wind direction and speed 

Season: Summer (May-Sep) and winter 

(Oct-Apr) 

Dose-response Investigated: No 

Statistical Package: NR 

Lags Considered: -3 day 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 12.9 (3.8-49.3) 

SD = 5.6 

Monitoring Stations: 8 

Copollutant (correlation): 

O3: r = 0.11 

SO2: r = 0.70 

NO2: r = 0.49 

CO: r = 0.43 

Other variables: 

Temp: r = 0.43 

Humidity: r = -0.35 

Baro Pressure: r = 0.26 

Rain: r = -0.63 

Wind: r = -0.53 

PM Increment: 5.6 μg/m3 (SD) 

Percent Change [CI]: Values NR 

Notes: The author states that significant 

negative associations were found for 

ICD discharge with same-day lag, and 

also for 3-day lag with more arrhythmiaprone patients. All other non-significant 

percent change estimates are shown in 

Fig 3 and 4.

Reference: Vedal et al. (2004, 055630) 

Period of Study: 1997-2000

Location: Vancouver, British Columbia, 

Canada 

Outcome: ICD discharges 

(arrhythmias) 

N: 150 patients w/ICD, 4 yr 

Statistical Analysis: Logistic 

regression, GEE 

Covariates: Temporal trends, 

temperature, relative humidity, wind 

speed, rain 

Season: Summer, winter 

Dose-response Investigated? No 

Lags Considered: 0, 1, 2, and 3 days 

Pollutant: PM10

Mean: 12.9 (SD = 5.6)

Copollutant): O3, SO2, NO2, CO 

Increment: 1 SD 

Effect Estimates, e.g., % change in the 

rate of arrhythmia, were presented in 

Fig 3. No association with PM10 was 

observed while SO2 was associated 

with an increase in the rate of 

arrhythmia among 16 patients with at 

least 2 discharges per yr. 

December 2009 E-17 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Whitsel et al. (2009, 

191980) 

Period of Study: 1993-2004 

Location: U.S. 

Outcome: Heart Rate Variability 

Age Groups: 50-79 yr 

Study Design: Panel 

N: 4,295 women 

Statistical Analyses: Random Effects 

Model 

Covariates: Temperature, humidity 

Dose-response Investigated? No 

Statistical Package: SUDAAN 

Lags Considered: 0 

Pollutant: PM10

Averaging Time: 24 h 

Amsterdam 

Mean: 20.0 

Min: 3.8 

25th: 10.4

50th: 16.9 

75th: 23.9 

Max: 82.2 

Erfurt 

Mean: 23.1 

Min: 4.5 

25th: 10.5 

50th: 16.3 

75th: 27.4 

Max: 118.1 

Helsinki 

Mean: 12.7 

Min: 3.1 

25th: 8.1 

50th: 10.6 

75th: 16.0 

Max: 39.8 

Monitoring Stations: 3

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: 10 μg/m3

Beta (Lower CI, Upper CI): 

Supine Position, Amsterdam 

Lag 0: -0.06 (-0.95, 0.84) 

Lag 1: 0.18 (-0.74, 1.10) 

Lag 2: 0.93 (0.01, 1.85) 

5-day avg: 0.49 (-0.74, 1.72) 

Supine Position, Erfurt 

Lag 0: -0.36 (-0.83, 0.11) 

Lag 1: -0.40 (-0.91, 0.11) 

Lag 2: -0.68 (-1.20, -0.17) 

5-day avg: -0.68 (-1.44, 0.09) 

Supine Position, Helsinki 

Lag 0: -0.44 (-2.27, 1.40) 

Lag 1: -0.17 (-1.69, 1.3.5) 

Lag 2: -1.14 (-2.51, 0.23) 

5-day avg: -0.59 (-3.08, 1.90) 

Supine Position, Pooled 

Lag 0: -0.30 (-0.71, 0.11) 

Lag 1: -0.25 (-0.68, 0.18) 

Lag 2: -0.26 (-1.22, 0.70)* 

5-day avg: -0.36 (-0.99, 0.27) 

Standing Position, Amsterdam 

Lag 0: -0.44 (-1.6, 0.72) 

Lag 1: -0.61 (-1.8, 0.59) 

Lag 2: 0.32 (-0.88, 1.51) 

5-day avg: -0.55 (-2.15, 1.04) 

Standing Position, Erfurt 

Lag 0: -0.59 (-1.24, 0.06) 

Lag 1: -0.70 (-1.42, 0.03) 

Lag 2: -0.65 (-1.37, 0.07) 

5-day avg: -0.68 (-1.74, 0.39) 

Standing Position, Helsinki 

Lag 0: 1.17 (-1.46, 3.80) 

Lag 1: 0.01 (-2.17, 2.19) 

Lag 2: -0.63 (-2.60, 1.34) 

5-day avg: -1.96 (-5.51, 1.60) 

Standing Position, Pooled 

Lag 0: -0.48 (-1.03, 0.07) 

Lag 1: -0.62 (-1.21, -0.03) 

Lag 2: -0.41 (-1.00, 0.17) 

5-day avg: -0.72 (-1.57, 0.14) 

*p < 0.1 

Reference: Yeatts et al. (2007, 091266) 

Period of Study: 

12-wk period b/t Sep 2003-Jul 2004 

Location: Chapel Hill, NC 

Outcome: Heart Rate Variability 

Age Groups: 21-50 yr 

Study Design: Panel 

N: 12 asthmatics 

Statistical Analyses: Linear Mixed 

Model 

Covariates: Temperature, humidity, 

pressure 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 1 day 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 17.5 (7.8)

Min: 1.4 

Max: 45.6 

Monitoring Stations: 1 

Copollutant: PM2.5, PM10-2.5

Co-pollutant Correlation 

PM2.5 = 0.90* 

PM10-2.5 = 0.73* 

*p < 0.01 

PM Increment: 1 μg/m3

Beta, SE, p-value (Lower CI, Upper 

CI): NR 

1

All units expressed in μg/m3 unless otherwise specified.

December 2009 E-18 
Table E-2. Short-term exposure - cardiovascular morbidity studies: PM10-2.5. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chuang et al. (2007, 

091063) 

Period of Study: Nov 2002-Mar 2003 

Location: Taipei, Taiwan 

Outcome: Heart Rate Variability 

Age Groups: 52-76 yr 

Study Design: Panel 

N: 10 CHD & 16 Hypertensive Patients 

Statistical Analyses: Linear Mixed 

Effects Model 

Covariates: Age, sex, BMI, time of day, 

temperature, humidity, pressure, HRV 

Dose-response Investigated? No 

Statistical Package: S-PLUS 

Lags Considered: 1- to 4-h ma 

Pollutant: PM10-2.5 

Averaging Time: 1 h 

among CHD, among hypertensive 

Mean (SD): 16.4 (10.7), 14.0 (11.1)

IQR: 14.8, 11.9 

Min: 0.7, 0.3 

Max: 59.6, 66.5 

Monitoring Stations: 1 personal 

monitor each 

Copollutant: PM1.0-2.5, PM0.3-1.0

Co-pollutant Correlation: 

NR 

PM Increment: Interquartile range 

Percent Change (Lower CI, Upper 

CI): 

Cardiac Patients- SDNN 

1h moving: -1.73 (-3.53, 0.08) 

2h moving: -1.97 (-4.43, 0.49) 

3h moving: -1.70 (-4.39, 0.89) 

4h moving: -1.75 (-5.42, 1.92) 

Cardiac Patients- r-MSSD 

1h moving: -4.39 (-9.54, 0.03) 

2h moving: -4.36 (-8.99, 0.27) 

3h moving: -4.20 (-9.02, 0.61) 

4h moving: -2.70 (-9.24, 3.84) 

Cardiac Patients- LF 

1h moving: -1.85 (-4.33, 0.62) 

2h moving: -3.87 (-8.22, 0.47 

3h moving: -2.98 (-6.65, 0.69) 

4h moving: -3.11 (-8.22, 1.99) 

Cardiac Patients- HF 

1h moving: -4.46 (-9.23, 0.32) 

2h moving: -4.41 (-9.55, 0.72) 

3h moving: -3.80 (-9.12, 1.53) 

4h moving: -3.39 (-10.62, 3.84) 

Cardiac Patients- LF: HF ratio 

1h moving: 8.45 (-3.48, 20.38) 

2h moving: 1.66 (-15.22, 18.55) 

3h moving: 11.69 (-7.27, 30.64) 

4h moving: 8.18 (-17.22, 33.57) 

Hypertensive Patients- SDNN 

1h moving: -2.64 (-3.93, 0.55 

2h moving: -3.51 (-7.87, 0.85) 

3h moving: -2.74 (-6.22, 0.74) 

4h moving: -2.49 (-6.13, 1.15) 

Hypertensive Patients- r-MSSD 

1h moving: -2.53 (-5.10, 0.04) 

2h moving: -5.42 (-10.92, 0.09) 

3h moving: -3.15 (-6.32, 0.03) 

4h moving: -4.23 (-8.88, 0.42) 

Hypertensive Patients- LF 

1h moving: -4.38 (-8.78, 0.03) 

2h moving: -5.23 (-10.95, 0.05) 

3h moving: -3.34 (-1.72, 0.04) 

4h moving: -2.96 (-6.63, 0.71) 

Hypertensive Patients- HF 

1h moving: -4.92 (-9.94, 0.10) 

2h moving: -6.07 (-12.28, 0.13) 

3h moving: -1.94 (-5.44, 1.55) 

4h moving: -2.78 (-6.78, 1.21) 

Hypertensive Patients- LF: HF ratio 

1h moving: 5.94 (-3.27, 15.15) 

2h moving: 10.70 (-2.19, 23.59) 

3h moving: -1.51 (-17.02, 14.00) 

4h moving: 3.41 (-16.91, 23.74) 

*p < 0.05 

December 2009 E-19 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ebelt et al. (2005, 056907) 

Period of Study: Summer of 1998 

Location: Vancouver, Canada 

Outcome: CVD 

Age Groups: range from 54-86 yr 

mean age= 74 yr 

Study Design: extended analysis of a 

repeated-measures panel study 

N: 16 persons with COPD 

Statistical Analyses: 

Earlier analysis expanded by 

developing mixed-effect regression 

models and by evaluating additional 

exposure indicators 

Dose-response Investigated? No 

Statistical Package: SAS V8 

Pollutant: PM10-2.5

Averaging Time: 24 h 

Mean (SD): 

Ambient PM10-2.5: 5.6 (3.0) 

Exposure to ambient PM10-2.5: 2.4 (1.7) 

Range (Min, Max): 

Ambient PM10-2.5: (-1.2-11.9) 

Exposure to ambient PM10-2.5: (-0.4-7.2) 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient concentrations and exposure 

to ambient PM were highly correlated 

for each respective metric: r ≥ 0.71 

Note: Total personal fine particle 

exposure (T) were dominated by 

exposures to non ambient particles 

which were not correlated with ambient 

fine particle exposure (A) or ambient 

concentrations (C). Results for each of 

these metrics are listed. 

PM Increment: 

Increment: C10-2.5: IQR = 4.5 μg/m3

SBP (mm Hg): -2.12 (-5.07-0.82) 

DBP (mm Hg): -0.92 (-3.37-0.36) 

Ln-SVE (bph): 0.06 (-0.24-0.36) 

HR (bpm): 1.09 (-0.69-2.86) 

SDNN (ms): 2.64 (-2.85-8.13) 

R-MSSD (ms): -0.33 (-4.49-3.82) 

Increment: A10-2.5: IQR = 2.4 μg/m3

SBP (mm Hg): -2.55 (-6.15-1.05) 

DBP (mm Hg): -0.75 (-3.50-2.01) 

Ln-SVE (bph): 0.26 (-0.07-0.58) 

HR (bpm): 1.04 (-0.95-3.03) 

SDNN (ms): 0.68 (-3.07-4.42) 

R-MSSD (ms): 1.10 (-3.08-5.28) 

Reference: Lipsett et al. (2006, 

088753) 

Period of Study: Feb-May 2000 

Location: Coachella Valley, CA 

Outcome: HRV parameters, specifically 

SDNN, SDANN, r-MSSD, LF, HF, total 

power, triangular index (TRII). 

Study Design: Panel study 

N: 19 non-smoking adults with coronary 

artery disease 

Statistical Analysis: Mixed linear 

regression models with random effects 

parameters 

Pollutant: PM10-2.5 

Averaging Time: 2 h 

Monitoring Stations: 2 

Copollutant: O3

PM Increment: SE*1000

Effect Estimate (change in HRV per 

unit increase in PM concentration): 

SDNN: -0.72 msec (SE = 0.296) 

Notes: PM10-2.5 calculated by 

subtracting PM2.5 concentration from 

PM10 concentration. Weekly ambulatory 

24-h ECG recordings (once per wk for 

up to 12 wk), using Holter monitors, 

were made. Subjects’ residences were 

within 5 mi of 1 of 2 PM monitoring 

sites. Regressed HRV parameters 

against 18: 00-20: 00 mean particulate 

pollution 

Reference: Metzger et al. (2007, 

092856) 

Period of Study: Aug 1998-Dec 2002 

Location: Atlanta, GA 

Outcome: Days with any event 

recorded by the ICD, days with ICD 

shocks/defibrillation and days with 

either cardiac pacing or defibrillation 

Study Design: Repeated measures 

N: 884 subjects between 1993 and 

2002 

Statistical Analysis: Logistic 

regression with GEE to account for 

residual autocorrelation within subjects 

Pollutant: PM10-2.5 (n/cm3) 

Averaging Time: 24 h 

Mean (SD): 9.6 (5.4) 

Median: 8.7 

Copollutant: 

O3, NO2, CO, SO2, oxygenated 

hydrocarbons 

PM Increment: OR (95% CI): 

OR = 1.03 (95% CI: 1.00, 1.07)

Reference: Pekkanen et al. (2002, 

035050) 

Period of Study: Winter 1998-1999 

Location: Helsinki, Finland 

Outcome: ST Segment Depression 

(>0.1mV) 

Study Design: Panel of ULTRA Study 

participants 

N: 45 subjects, 342 biweekly 

submaximal exercise tests, 72 exercise 

induced ST Segment Depressions 

Statistical Analysis: Logistic 

regression / GAM 

Pollutant: PM10-2.5 (n/cm3) 

Averaging Time: 24 h 

Median: 4.8 

IQR: 5.5 

Monitoring Stations: 1 

Copollutant: NO2, CO, PM2.5, PM1, 

ACP, ultrafine 

PM Increment: IQR 

Effect Estimate(s): PM10-2.5: OR = 1.99 

(0.70, 5.67), lag 2

Notes: The effect was strongest for 

ACP and PM2.5, which in 2 pollutant 

models appeared independent. 

Increases in NO2 and CO were also 

associated with increased risk of ST 

segment depression, but not with 

coarse particles. 

Reference: Timonen et al. (2006, 

088747) 

Period of Study: 1998-1999 

Location: Amsterdam, Netherlands 

Erfurt, Germany 

Helsinki, Finland 

Outcome: HRV measurements: [LF, 

HF, LFHFR, NN interval, SDNN, rMSSD] 

Study Design: Panel study 

N: 131 elderly subjects with stable 

coronary heart disease 

Statistical Analysis: Linear mixed 

models 

Pollutant: PM10-2.5 

Means: 

Amsterdam: 15.3 

Erfurt: 3.7 

Helsinki: 6.7 

Copollutant: NO2, CO 

PM Increment: 10 μg/m3

Effect Estimate: SDNN 

0.69ms (95% CI: -1.24, 2.63) 

HF: 2.9% (95% CI: -7.3, 13.1) 

LFHFR: -3.3 (95% CI: -12.7, 6.1) 

Notes: Followed for 6 mo with biweekly 

clinic visits 

2-day lag. ULTRA Study 

December 2009 E-20 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yeatts et al. (2007, 091266) 

Period of Study: 

12-wk period b/t Sep 2003-Jul 2004 

Location: Chapel Hill, NC 

Outcome: Heart Rate Variability 

Age Groups: 21-50 yr 

Study Design: Panel 

N: 12 asthmatics 

Statistical Analyses: Linear Mixed 

Model 

Covariates: Temperature, humidity, 

pressure 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 1 day 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean (SD): 5.3 (2.8)

Min: 0 

Max: 14.6 

Monitoring Stations: 1 

Copollutant: PM2.5, PM10

Co-pollutant Correlation: 

PM2.5 = 0.46* 

PM10 = NR 

*p < 0.01 

PM Increment: 1 μg/m3. 

Beta, SE (Lower CI, Upper CI), pvalue 

HRV 

Max Heart Rate: -1.95, 0.88 (-3.67, -

0.23), 0.03 

ASDNN5: -0.77, 0.37 (-1.580, -0.04), 

0.05 

SDANN5: -3.76, 1.53 (-6.76, -0.76), 

0.02 

SDNN24HR(mesc): -3.36, 1.38 (-6.06, -

0.65), 0.02 

rMSSD: -0.75, 0.53 (-1.79, 0.28), 0.16 

pNN50_24hr: -0.50, 0.27 (-1.03, 0.03), 

0.07 

pNN50_7min: -1.88, 0.55 (-2.95, -0.81), 

0.07 

Low-frequency power: -0.19, 0.42 (-

1.01, 0.63), 0.65 

Percent low frequency: 0.57, 1.08 (-

1.55, 2.69), 0.60 

High-frequency power: -0.46, 0.17 (-

0.79, -0.14), 0.01 

Percent high frequency: -2.14, 0.94 (-

3.98, -0.30), 0.03 

Blood Lipids 

Triglycerides: 4.78, 2.02 (0.81, 8.74), 

0.02 

VLDL: 1.15, 0.44 (0.29, 2.02), 0.01 

Total cholesterol: 0.78, 0.54 (-0.28, 

1.84), 0.15 

Hematologic Factors 

Circulating eosinophils: 0.16, 0.06 

(0.04, 0.28), 0.01 

Platelets: -1.71, 1.11 (-3.89, 0.47), 0.13 

Circulating Proteins 

Plasminogen: -0.01, 0.01 (-0.02, 0.00), 

0.08 

Fibrenogen: -0.04, 0.02 (-0.08, 0.00), 

0.07 

Von Willibrand factor: -1.23, 0.66 (-2.53, 

0.06), 0.07 

Factor VII: -0.90, 0.85 (-2.58, 0.77), 

0.29 

1

All units expressed in μg/m3 unless otherwise specified. 

Table E-3. Short-term exposure - cardiovascular morbidity studies: PM2.5 (including PM 

components/sources). 

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Adar et al. (2007, 001458) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, Missouri 

Outcome: Heart rate variability: heart 

rate, standard deviation of all normal-tonormal intervals (SDNN), square root of 

the mean squared difference between 

adjacent normal-to-normal intervals 

(rMSSD), percentage of adjacent 

normal-to-normal intervals that differed 

by more than 50 ms (pNN50), high 

frequency power (HF in the range of 

0.15-0.4Hz), low frequency power (LF, in 

the range of 0.04-0.15Hz), and the ratio 

of LF/HF 

Age Groups: ≥ 60 yr

Study Design: Panel (4 planned 

repeated measures surrounding bus 

Pollutant: PM2.5 (μg/m3) 

Averaging Time: Measurements 

collected over 48 h period surrounding 

the bus trip (during which health 

endpoints were measured) used to 

calculate 5-, 30-, 60-min, 4-h, 24-h ma 

Median (IQR): 

All: 7.7 (6.8) 

Facility: 6.8 (5.1) 

Bus: 17.2 (10.3) 

Activity: 8.2 (16.1) 

Lunch: 11.2 (5.9) 

Monitoring Stations: 2 portable carts 

Copollutant: 

PM Increment: IQR 

Effect Estimate [Lower CI, Upper CI]: 

% change (95%CI) in HRV per IQR in 

the 24-h ma of the microenvironmental 

pollutant (IQr = 4.5 μg/m3

)

Single-pollutant models: 

SDNN: -5.5 (-6.3, -4.8) 

rMSSD: -9.1 (-9.8, -8.4) 

pNN50 + 1: -12.2 (-13.3, -11.1). LF: -

10.8 (-12.3, -9.3) 

HF: -15.1 (-16.7, -13.7) 

LF/HF: 5.1 (3.9, 6.4) 

H: 1.0 (0.9, 1.2) 

Two-pollutant models (with particle 

December 2009 E-21 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

trips with a total of 158 person-trips, 35 

participating in all 4 trips) 

N: 44 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: Subject, weekday, time, 

apparent temperature, trip type, activity, 

medications, and autoregressive terms 

Season: Limited data collection period 

Dose-response Investigated? No 

Statistical Package: SAS v8.02, R 

v2.0.1 

PM2.5

BC 

Fine particle counts 

coarse particle counts 

Correlation notes: 24-h mean PM2.5, 

BC, and fine particle count concentrations ranged from 0.80-0.98 

r = 0.76-0.97 when limited to time spent 

on the bus 

r = 0.55-0.86 when comparing bus 

concentrations to 24-h ma 

r = -0.003-0.51 when comparing 5-min 

avg and 24-h ma 

Poor correlations found between coarse 

particle count concentrations and all fine 

particulate measures during all times 

periods 

number count coarse): 

SDNN: -5.7 (-6.5, -4.9) 

rMSSD: -9.4(-10.1, -8.6) 

pNN50+1: -13.1(-14.3, -11.9). 

LF: -10.7(-12.4, -9.1) 

HF: -14.9(-16.5, -13.3); LF/HF: 4.9 (3.6, 

6.2)’ H: 0.9 (0.7,1.1) 

Independent short- and medium-term 

associations with HRV across all time 

periods 

% change per IQR (95%CI) 

IQR 5-min means = 6.8 μg/m3

 and 23: 

55-h means = 4.2 μg/m3

SDNN: 5-min mean: -0.5 (-0.8, -0.1) 

23: 55-h mean: -4.6 (-5.3, -4.0) 

rMSSD: 5-min mean: -0.9 (-1.3, -0.5) 

23: 55-h mean: -7.5 (-8.1 to -6.8) 

pNN50 + 1 

5-min mean: -1.1 (-1.7 to -0.5) 

23: 55-h mean: -9.9 (-10.9 to -8.9). LF 

5-min mean: 0.4 (-0.5, 1.2) 

23: 55-h mean: -10.0 (-11.4 to -8.6) 

HF 

5-min mean: -1.5 (-2.3 to -0.6) 

23: 55-h mean: -12.9 (-14.2 to -11.5) 

LF/HF 

5-min mean: 1.9 (1.3, 2.4) 

23: 55-h mean: 3.2 (2.1, 4.3) 

H: 5-min mean: 0.1 (0.1, 0.2) 

23: 55-h mean: 0.8 (0.7, 0.9) 

Independent associations of short-term 

avg (5-min means) of PM with HRV by 

bus and nonbus periods 

IQR for bus = 10 μg/m3

) and 

nonbus = 5.6 μg/m3

) 

% change (95%CI) 

p-value of interaction 

SDNN 

Bus: -5.0 (-6.3 to -3.7) 

Nonbus: -0.5 (-0.9 to -0.2) 

p-value for interaction: <0.0001. rMSSD 

Bus: -4.8 (-6.2 to -3.5) 

Nonbus: -0.7 (-1.1 to -0.4. p-value for 

interaction: <0.0001 

pNN50 + 1 

Bus: -6.3 (-8.4 to -4.2) 

Nonbus: -0.8 (-1.4 to -0.3) 

p-value for interaction: <0.0001 

LF: Bus: -7.0 (-9.8 to -4.1) Nonbus: 0.6 

(-0.1, 1.4) 

p-value for interaction: <0.0001. HF: 

Bus: -10.7 (-13.5 to -7.9)’ Nonbus: -0.7 

(-1.5, 0.04) p-value for interaction: 

<0.0001. LF/HF: Bus: 3.9 (1.7, 6.0) 

Nonbus: 1.4 (0.8, 1.9) 

p-value for interaction: 0.39. H: Bus: 0.7 

(0.5, 1.0) 

Nonbus: -0.01 (-0.08, 0.1) 

p-value for interaction: <0.0001 

Note: Exposure to health associations 

by all lag periods presented in Fig 2 

(magnitude of associations increased 

with averaging period, with the largest 

associations consistently found for 24-h 

ma) 

December 2009 E-22 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Adar et al. (2007, 001458) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, Missouri 

Outcome: Heart rate variability: heart 

rate, standard deviation of all normal-tonormal intervals (SDNN), square root of 

the mean squared difference between 

adjacent normal-to-normal intervals 

(rMSSD), percentage of adjacent 

normal-to-normal intervals that differed 

by more than 50 ms (pNN50), high 

frequency power (HF 

in the range of 0.15-0.4Hz), low 

frequency power (LF, in the range of 

0.04-0.15Hz), and the ratio of LF/HF 

Age Groups: ≥ 60 yr

Study Design: Panel (4 planned 

repeated measures with a total of 158 

person-trips 

35 participating in all 4 trips) 

N: 44 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: Subject, weekday, time, 

apparent temperature, trip type, activity, 

medications, and autoregressive terms 

Season: Limited data collection period 

Dose-response Investigated? No 

Statistical Package: SAS v8.02, R 

v2.0.1 

Pollutant: BC (ng/m3) 

Averaging Time: Measurements 

collected over 48 h period surrounding 

the bus trip (during which health 

endpoints were measured) used to 

calculate 5-, 30-, 60-min, 4-h, 24-h ma 

Median (IQR): All: 330 (337) 

Facility: 285 (270) 

Bus: 2911 (2464) 

Activity: 482 (1168) 

Lunch: 434 (276) 

Monitoring Stations: 2 portable carts 

Copollutant: PM2.5

BC 

Fine particle counts 

Coarse particle counts 

Correlation notes: 24-h mean PM2.5, 

BC, and fine particle count 

concentrations ranged from 0.80 to 0.98 

r = 0.76 to 0.97 when limited to time 

spent on the bus 

r = 0.55 to 0.86 when comparing bus 

concentrations to 24-h ma 

r = -0.003 to 0.51 when comparing 5-min 

avg and 24-h ma

Poor correlations found between coarse 

particle count concentrations and all fine 

particulate measures during all times 

periods 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

% change (95%CI) in HRV per IQR in 

the 24-h ma of the microenvironmental 

pollutant (IQr = 459 ng/m3

) 

Single-pollutant models 

SDNN: -5.3 (-6.5 to -4.1) 

rMSSD: -10.7 (-11.9 to -9.5) 

pNN50 + 1: -13.2 (-15.0 to -11.4) 

LF: -11.3 (-13.7 to -8.8) 

HF: -18.8 (-21.1 to -16.5) 

LF/HF: 9.3 (7.2, 11.4) 

H: 1.0 (0.8, 1.3) 

Independent short- and medium-term 

associations with HRV across all time 

periods 

% change per IQR (95%CI) 

IQR 5-min means = 337 ng/m3

 and 23: 

55-h means = 490 ng/m3

) 

SDNN: 5-min mean: -0.3 (-0.5 to -0.1) 

23: 55-h mean: -4.7 (-5.9 to -3.5) 

rMSSD: 5-min mean: -0.3 (-0.5 to -0.1) 

23: 55-h mean: -9.3 (-10.5 to -8.1) 

pNN50 + 1: 5-min mean: -0.3 (-0.6 to -

0.1) 

23: 55-h mean: -10.5 (-12.3 to -8.7) 

LF: 5-min mean: -0.5 (-0.9 to -0.1) 

23: 55-h mean: -9.8 (-12.4 to -7.2) 

HF: 5-min mean: -0.9 (-1.2 to -0.5) 

23: 55-h mean: -15.4 (-17.8 to -12.9) 

LF/HF: 5-min mean: 0.3 (0.1, 0.6) 

23: 55-h mean: 6.5 (4.5, 8.6) 

H: 5-min mean: 0.1 (0.1, 0.2) 

23: 55-h mean: 0.4 (0.2, 0.7) 

Independent associations of short-term 

avg (5-min means) of PM with HRV by 

bus and nonbus periods 

IQR for bus = 2.6 μg/m3

) and 

nonbus = 0.27 μg/m3

) 

% change (95%CI) 

p-value of interaction 

SDNN: Bus: -4.6 (-6.1 to -3.0)’ Nonbus: -

0.1 (-0.3, 0.1) 

p-value for interaction: <0.0001 

rMSSD: Bus: -2.6 (-4.2 to -0.9): Nonbus: 

-0.3 (-0.5 to -0.1) 

p-value for interaction: 0.64 

pNN50 + 1: Bus: -2.0 (-4.5, 0.5): 

Nonbus: -0.5 (-0.8 to -0.1) 

p-value for interaction: 0.34 

LF: Bus: -6.0 (-9.3 to -2.5): Nonbus: -0.2 

(-0.7, 0.3) 

p-value for interaction: 0.028 

HF: Bus: -5.8 (-9.1 to -2.3) 

Nonbus: -0.9 (-1.4 to -0.4) 

p-value for interaction: 0.50 

LF/HF: Bus: -0.8 (-3.1, 1.7) 

Nonbus: 0.8 (0.5, 1.1) 

p-value for interaction: <0.0001 

H: Bus: -0.5 (-0.8 to -0.2) 

Nonbus: 0.3 (0.26, 0.34) 

p-value for interaction: <0.0001 

Note: Exposure to health associations 

by all lag periods presented in Fig 2 

(magnitude of associations increased 

with averaging period, with the largest 

associations consistently found for 24-h 

ma) 

Reference: Auchincloss et al. (2008, 

156234) 

Outcome: Blood pressure: Systolic 

(SBP), diastolic (DBP), mean arterial 

Pollutant: PM2.5 PM Increment: 10 μg/m3 (approx. 

equivalent to difference between 90th 

December 2009 E-23 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Period of Study: Jul 2000-Aug 2002 

Location: 

6 U.S. communities (Baltimore City and 

Baltimore County, Maryland 

Chicago, Illinois 

Forsyth County, North Carolina 

Los Angeles, California 

Northern Manhattan and the Bronx, New 

York and St. Paul, Minnesota) 

Part of MESA (Multi-ethnic Study of 

Atherosclerosis) 

(MAP), pulse pressure (PP) 

Avg of 2nd and 3rd BP measurement 

used for analyses

Age Groups: 45-84 yr 

Study Design: Cross-sectional (MultiEthnic Study of Atherosclerosis baseline 

examination) 

N: 5,112 persons (free of clinically 

apparent cardiovascular disease) 

Statistical Analyses: Linear regression

secondary analyses used log binomial 

models to fit a binary hypertension 

outcome 

Covariates: Age, sex, race/ ethnicity, 

per capita family income, education, 

BMI, diabetes status, cigarette smoking 

status, exposure to ETS, high alcohol 

use, physical activity, BP medication 

use, meteorology variables, and 

copollutants 

Examined site as a potential confounder 

and effect modifier 

Heterogeneity of effects also examined 

by traffic-related exposures, age, sex, 

type 2 diabetes, hypertensive status, 

cigarette use, by levels of SO2 and CO, 

and for weather variables 

Season: Adjusted for temperature and 

barometric pressure to adjust for 

seasonality (because seasons vary by 

the study sites) 

Also performed sensitivity analyses 

adjusting for season to examine the 

potential for residual confounding not 

accounted for by weather variables 

Dose-response Investigated? 

Assessed nonlinear relationships-no 

evidence of strong threshold/nonlinear 

effects for PM2.5

Statistical Package: NR 

Averaging Time: 5 exposure metrics 

constructed: prior day, avg of prior 

2 days, prior 7 days, prior 30 days, and 

prior 60 days 

Mean (SD): 

Prior day: 17.0 (10.5) 

Prior 2 days: 16.8 (9.3) 

Prior 7 days: 17.0 (6.9) 

Prior 30 days: 16.8 (5.0) 

Prior 60 days: 16.7 (4.4) 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: Used monitor 

nearest the participant’s residence to 

calculate exposure metrics 

Copollutant: 

SO2

NO2

CO 

Traffic-related exposures (straight-line 

distance to a highway total road length 

around a residence) 

Correlations with PM2.5 averaged 

over prior 30 days: 

O3

Cool: r = -0.67 

Moderate: r = -0.30 

Warm: r = 0.23 

CO 

Cool: r = 0.20 

Moderate: r = 0.71 

Warm: r = 0.23 

SO2

Cool: r = 0.36 

Moderate: r = -0.17 

Warm: r = -0.11 

NO2

Cool: r = 0.55 

Moderate: r = 0.66 

Warm: 0.32 

and 10th percentile for prior 30 day 

mean) 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted mean difference (95% CI) in 

PP and SBP (mmHg) per 10 μg/m3

increase in PM2.5 (avgd for the prior 30 

days) 

Pulse Pressure 

(PM2.5 avgd for prior 30 days) 

Adjustment variables: 

Person-level Covariates: 1.04 (0.25, 

1.84), p = 0.010 

Person-level cov., weather: 1.12 (0.28, 

1.97), p = 0.009 

Person-level cov., weather, gaseous 

copollutants: 2.66 (1.61, 3.71), p = 0.000

Person-level cov., study site: 0.93 (-0.04, 

1.90), p = 0.060 

Person-level cov., study site, weather: 

1.11 (0.01, 2.22), p = 0.049 

Person-level cov., study site, weather, 

gaseous copollutants: 1.34 (0.10, 2.59) , 

p = 0.035 

Systolic Blood Pressure 

Adjustment variables: 

Person-level Covariates: 0.66 (-0.41, 

1.74) , p = 0.226 

Person-level cov., weather: 0.99 (-0.15, 

2.13) , p = 0.089 

Person-level cov., weather, gaseous 

copollutants: 2.8 (1.38, 4.22) , p = 0.000 

Person-level cov., study site: 0.86 (-0.45, 

2.17) , p = 0.200 

Person-level cov., study site, weather: 

1.32 (-0.18, 2.82) , p = 0.085 

Person-level cov., study site, weather, 

gaseous copollutants: 1.52 (-0.16, 3.21) 

, p = 0.077 

Additional results: Associations 

became stronger with longer averaging 

periods up to 30 days. For example: 

Adjusted (personal covariates and 

weather) mean differences in PP: Prior 

day: -0.38 (-0.76, 0.00) 

Prior 2 days: -0.22 (-0.65, 0.21) 

Prior 7 days: 0.52 (-0.08, 1.11) 

Prior 30 days: 1.12 (0.28, 1.97) 

Prior 60 days: 1.08 (0.11, 2.05) 

(Pattern held for additional adjustments 

and for SBP results 

therefore, only results for 30-day mean 

differences were presented) 

Additional results (not presented): 

None of DBP results were statistically 

significant 

Results for MAP were similar to SBP, 

though weaker and generally not 

significant

Effect modification: Associations 

between PM2.5 and BP were stronger for 

persons taking medications, with 

hypertension, during warmer weather, in 

the presence of high NO2, residing ≤

300m from a highway, and surrounded 

by a high density of roads (Fig 1) 

associations were not modified by age, 

sex, diabetes, cigarette smoking, study 

site, high levels of CO or SO2, season , 

nor residence ≤ 400m fro a highway 

December 2009 E-24 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Note: Supplementary material available 

on-line shows results for DBP and MAP, 

among others 

Reference: Baccarelli et al. (2009, 

188183) 

Period of Study: Nov 2000-Jun 2005 

Location: Boston, Mass 

Outcome: Heart rate variability 

Age Groups: Elderly 

Study Design: Panel 

N: 549 men 

Statistical Analyses: Mixed-effects 

model 

Covariates: Age, past/current CHD, 

BMI, mean arterial pressure, fasting 

blood glucose, smoking, alcohol 

consumption, use of beta-blockers, CA 

channel blockers, angiotensinconverting enzyme inhibitors, room 

temperature, season, apparent 

temperature 

Season: No 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM2.5

Averaging Time: 48-h ma 

Geometric Mean (95%CI): 

All Visits: 10.5 (10.0, 10.9) 

Visits w/ Genotype Data: 10.4 (9.9, 11.0)

Visits w/o Genotype Data: 10.5 (9.8, 

11.4) 

Monitoring Stations: 1 

Copollutant: NR 

Correlation: N/A 

PM Increment: 10 μg/m3

Percent Change [Lower CI, Upper CI], 

P: 

All Subjects w/ Genotype Data 

SDNN: -6.0 (-13.5, 2.0), 0.14 

HF: -17.1 (-32.3, 1.6), 0.07 

LF: -8.2 (-22.1, 8.2), 0.31 

All Subjects 

SDNN: -7.1 (-13.2, -0.6), 0.03 

HF: -18.7 (-31.1, -4.0), 0.01 

LF: -11.8 (-23.2, -1.3), 0.08 

December 2009 E-25 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Barclay et al. (2007, 

192229) 

Period of Study: Jan 2003-May 2005 

Location: Aberdeen, Scotland 

Outcome: Haematological outcomes, 

Heart Rhythm outcomes, & Heart Rate 

Variability outcomes 

Age Groups: 70.4 (8.9)

Study Design: Panel 

N: 132 patients w/ chronic heart failure 

Statistical Analyses: Linear & Mixed 

Effects Regression Model 

Covariates: Age, temperature, humidity, 

pressure 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: Lags 0-2 day 

Pollutant: PM2.5

Averaging Time: Daily 

Mean: 7.454 

Min: 1.092 

Max: 21.97 

Monitoring Stations: 0 

Copollutant: PM10, PNC, NO2

Co-pollutant Correlation 

NO2 city: 0.164 

NO city: 0.048 

PM10 city: 0.476* 

NO2 personal: 0.169 

PNC DEOM: 0.115 

PM2.5 traffic: 0.522* 

PNC total: 0.367* 

PNC traffic: 0.234 

*correlations based on 3-day avg 

concentrations 

Notes: PM2.5 values model predicted 

PM Increment: NR 

Beta (Lower CI, Upper CI): 

Haemoglobin: -0.509 (-1.560, 0.542) 

Mean corpuscular haemoglobin: 0.188 (-

0.481, 0.857) 

Platelets: 3.022 (0.403, 5.642) 

Haematocrit: -0.813 (-1.892, 0.267) 

White blood cells: -1.652 (-4.727, 1.424)

C reactive protein: 4.924 (-13.022, 

22.869) 

IL-6: -5.980 (-23.649, 11.690) 

von Willebrand factor: 1.363 (-6.561, 

9.287) 

E-selectin: 2.136 (-2.946, 7.217) 

Fibrinogen: -5.579 (-10.403, -0.755)* 

Factor VII: 3.747 (-1.959, 9.452) 

day-dimer: 5.211 (-2.974, 13.397) 

All arrhythmias: -7.082 (-28.789, 14.626)

Ventricular ectopic beats: -12.203 (-

39.021, 14.615) 

Ventricular couplets: -1.255 (-25.678, 

23.168) 

Ventricular runs: -2.548 (-17.448, 

12.351) 

Supraventricular ectopic beats: 4.898 (-

19.772, 29.568) 

Supraventricular couplets: 6.138 (-

16.242, 28.518) 

Supraventricular runs: -0.545 (-17.577, 

16.487) 

Avg HR: 0.617 (-0.782, 2.016) 

24 h SDNN: 3.645 (-0.227, 7.517) 

24 h SDANN: 4.437 (0.030, 8.844)* 

24 h RMSSD: 0.617 (-0.782, 2.016) 

24 h PNN 50%: 11.247 (-6.228, 28.722)

24 h LF power: 4.439 (-6.823, 15.701) 

24 h LF normalized: -5.659 (-11.815, 

0.497) 

24 h HF power: 3.800 (-10.863, 18.464)

24 h HF normalized: -6.597 (-13.724, 

0.531) 

24 h LF/HF ratio: 1.033 (-8.355, 10.414) 

*p < 0.05 

Notes: Estimates also available for 

PM2.5 traffic

LF= low frequency 

HF= high frequency 

Reference: Briet et al. (2007, 093049) 

Period of Study: NR 

Location: Paris, France 

Outcome: Endothelial Function 

Age Groups: 20-40 yr

Study Design: Panel 

N: 40 white male nonsmokers 

Statistical Analyses: Multiple Robust 

Regrssion 

Covariates: R53R/R53H genotype, diet, 

subject factor, visit, temperature 

Dose-response Investigated? No 

Statistical Package: NCSS 

Lags Considered: 0-5 days 

Pollutant: PM2.5

Averaging Time: 24 h 

5 day Mean (SD): 28 (6) 

Monitoring Stations: NR 

Co-pollutant: PM10, SO2, NO, NO2, CO 

Co-pollutant Correlation: N/A 

PM Increment: 1 SD 

Beta (Lower CI, Upper CI), P, R2: 

Flow-mediated brachial artery dilation: 

-0.32 (-1.10, 0.46), NS, 0.04 

Reactive hyperemia: 

15.68 (7.11, 23.30), <0.0001, 0.24 

Changes in Endothelial function b/t 

visits: 

1.98 (0.67, 3.259), 0.004, 0.44 

December 2009 E-26 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Cárdenas et al. (2008, 

191900) 

Period of Study: NR 

Location: Mexico City, Mexico 

Outcome: Heart Rate Variability 

Age Groups: 20-40 yr

Study Design: Panel 

N: 54 subjects 

Statistical Analyses: Linear GEE 

models 

Covariates: Localization, supine 

position, gender, age, humidity, heart 

rate, orthostatic position, head-up tilt test 

result 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: NR 

Pollutant: PM2.5

Averaging Time: NR 

25th, 50th, 75th percentile: 

Indoor: 14.8, 28.3, 47.9 

Outdoor: 6.4, 10.8, 16.8 

Monitoring Stations: NR 

Co-pollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: NR 

Mean Difference (Lower CI, Upper CI), 

lag: 

Ln low frequency 

Indoors: -0.028 (-0.0423, -0.0138) 

Outdoors: -0.194 (-0.4509, 0.0627) 

Ln high frequency 

Indoors: -0.019 (-0.0338, -0.0044) 

Outdoors: -0.298 (-0.5553, -0.0401) 

Ln LF/HF ratio 

Indoors: -0.017 (-0.0330, -0.0007) 

Outdoors: -0.278 (-0.5540, 0.0030) 

Reference: Cavallari et al. (2007, 

157425) 

Period of Study: 1999-2006 

Location: Massachusetts 

Outcome: Heart Rate Variability 

Age Groups: 22-63

Study Design: Panel 

N: 36 males 

Statistical Analyses: Mixed Effects 

Regression Model 

Covariates: Age, smoking, heart rate at 

work 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Lags 0-14 h 

Pollutant: PM2.5

Averaging Time: Hourly 

Mean (SD): 1.12 (0.76) 

Min: 0.12 

Max: 3.99 

Monitoring Stations: NR 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM 1 mg Increment: m3

Beta (Lower CI, Upper CI): 

Model 1 

Lag 1 h: -1.44 (-7.75, 4.87) 

Lag 2 h: -5.33 (-10.97, 0.31)* 

Lag 3 h: -6.86 (-11.91, -1.81)‡ 

Lag 4 h: -2.17 (-9.33, 4.99) 

Lag 5 h: -4.73 (-11.99, 2.53) 

Lag 6 h: -3.52 (-9.89, 2.84) 

Lag 7 h: -1.59 (-7.53, 4.35) 

Lag 8 h: -0.72 (-7.63, 6.20) 

Lag 9 h: -5.55 (-10.65, -0.45)‡ 

Lag 10 h: -3.66 (-8.85, 1.53) 

Lag 11 h: -8.60 (-17.45, 0.24)* 

Lag 12 h: -5.98 (-14.67, 2.70) 

Lag 13 h: -8.27 (-17.00, 0.46)* 

Lag 14 h: -4.19 (-12.71, 4.33) 

Model 2 

Lag 1 h: 4.10 (-0.39, 8.60)* 

Lag 2 h: -3.21, (-8.78, 2.37) 

Lag 3 h: -6.45 (-11.59, -1.31)‡ 

Lag 4 h: -0.01 (-6.96, 6.94) 

Lag 5 h: -2.03 (-8.27, 4.22) 

Lag 6 h: -1.99 (-8.46, 4.48) 

Lag 7 h: -0.34 (-6.22, 5.54) 

Lag 8 h: 0.72 (-6.35, 7.78) 

Lag 9 h: -5.26 (-10.62, 0.11)* 

Lag 10 h: -3.68 (-9.17, 1.80) 

Lag 11 h: -9.41 (-18.60, -0.23)‡ 

Lag 12 h: -6.45 (-15.62, 2.72) 

Lag 13 h: -7.33 (-16.55, 1.89) 

Lag 14 h: -4.75 (-13.81, 4.32) 

*p < 0.05, ‡p < 0.10 

Notes: Model 1 adjusted for smoking 

status and age only. Model 2 adjusted 

for smoking status, age, and heart rate 

during work. 

December 2009 E-27 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chahine et al. (2007, 

156327) 

Period of Study: Jan 2000-Jun 2005 

Location: Boston, MA 

Outcome: Heart Rate Variability 

Age Groups: Mean 72.8(6.6) yr 

Study Design: Panel 

N: 539 white males 

Statistical Analyses: Mixed Effects 

Model 

Covariates: Age, BMI, mean arterial 

pressure, fasting blood glucose, 

smoking, alcohol consumption, use of 

beta-blockers, calcium channel blockers, 

ACE inhibitors, room temperature, 

season, outdoor temperature 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0- to 2-day ma 

Pollutant: PM2.5

Averaging Time: 1 h 

Mean (SD): 11.7 (7.8) 

Monitoring Stations: 1 

Copollutant: PM1.0

Co-pollutant Correlation: N/A 

PM Increment: 10 μg/m3

Percent Change (Lower CI, Upper CI), 

p-value: 

log10 SDNN 

Total: -6.8 (-12.9, -0.2), 0.0436 

GSTM1 wildtype: -2.0 (-11.3, 8.3), 

0.6908 

GSTM1 null: -10.5 (-18.2, -2.2), 0.0150 

HMOX-1 <25 repeats: 7.4 (-8.7, 26.2), 

0.3891 

HMOX-1 ≥25 repeats: -8.5 (-14.8, -1.8), 

0.0137 

log10 HF 

Total: -17.3 (-30.0, -2.3), 0.0263 

GSTM1 wildtype: -4.0 (-24.8, 22.6), 

0.7442 

GSTM1 null: -24.2 (-39.2, -5.5), 0.0139 

HMOX-1 <25 repeats: 8.9 (-27.1, 62.8), 

0.6759 

HMOX-1 ≥25 repeats: -20.1 (-32.9, -5.0), 

0.0115 

log10 LF 

Total: -11.2 (-22.8, 2.2), 0.0986 

GSTM1 wildtype: -0.6 (-19.0, 22.0), 

0.9545 

GSTM1 null: -17.0 (-31.0, -0.2), 0.0478 

HMOX-1 <25 repeats: 14.0 (-18.6, 59.5), 

0.4465 

HMOX-1 ≥25 repeats: -14.0 (-25.7, -0.5), 

0.0430 

Reference: Chen and Schwartz (2008, 

190106) 

Period of Study: 1989-1991 

Location: U.S. 

Outcome: White Blood Cell count 

Age Groups: 20-89 yr

Study Design: Panel 

N: 2,978 participants 

Statistical Analyses: Mixed Effects 

Models 

Covariates: Age, sex, race, SES, 

smoking, alcohol consumption, MS 

abnormalities, indoor air pollutants, 

exercise 

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: NR 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 36.8 (13.0) Median(range) 

for

Q1: 23.1(14.6-27.8) 

Q2: 31.2 (27.9-34.3) 

Q3: 38.8 (34.3-43.3) 

Q4: 53.7 (43.3-78.5) 

Monitoring Stations: NR 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: Quartile, 1yr avg (36.8 

μg/m3

) 

Avg WBC count(SE) by PM quartile: 

Q1: 6760 (79) 

Q2: 6942 (99) 

Q3: 6895 (84) 

Q4: 7109 (61) 

Beta(Lower CI, Upper CI), p-value: 

Crude: 239 (58, 420), 0.01 

Model 1: 145 (10, 281), 0.035 

Model 2: 141 (6, 277), 0.041 

Model 3: 138 (2, 273), 0.046 

Model 1: Age, sex, race, SES, smoking, 

alcohol consumption, MS abnormalities. 

Model 2: Model 1 plus indoor air 

pollutants, exercise. Model 3: Clean 

areas (Q1) vs.. other more polluted 

areas 

December 2009 E-28 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chuang et al. (Chuang et 

al., 2007, 091063) 

Period of Study: Between Apr-Jun 

2004 or 2005 

Location: Taipei, Taiwan 

Outcome: High-sensitivity C-reactive 

protein (hs-CRP) 

Fibrinogen, plasminogen activator 

fibrinogen inhibitor-1 (PAI-1), tissue-type 

plasminogen activator (tPA), 8-hydroxy2’-deoxyguanosine (8-OHdG), and logtransformed HRV indices 

(SDNN = standard deviation of NN 

intervals, r-MSSD = square root of the 

mean of the sum of the squares of 

differences between adjacent NN 

intervals, LF = low frequency [0.04-

0.15Hz], and HF = high frequency[0.15-

0.40Hz]) 

Age Groups: 18-25 yr 

Study Design: Panel (cross-sectional) 

N: 76 students 

Statistical Analyses: Linear mixedeffects models 

Covariates: Age, sex, BMI, weekday, 

temperature of previous day, relative 

humidity 

Season: Only 1 season of data 

collection 

Dose-response Investigated? No

Statistical Package: NR 

Pollutant: PM10, nitrate, sulfate 

Averaging Time: Hourly data used to 

calculate avg over 1- to 3-day periods 

Mean (SD): 

1-day avg: 31.8 (10.6) 

2-day avg: 36.4 (12.6) 

3-day avg: 36.5 (12.6) 

Range (Min, Max): 

1-day avg: 16.2, 50.1 

2-day avg: 15.0, 53.4 

3-day avg: 12.7, 59.5 

Monitoring Stations: 2 sites (each 

pollutant measured at 1 site only) 

Copollutant: PM10

Sulfate 

Nitrate 

OC 

EC 

NO2

CO 

SO2

O3

PM2.5 Increment: IQR 

(1-day avg: 20.4 

2-day avg: 25.2 

3-day avg: 20.0) 

Effect Estimate [Lower CI, Upper CI]: 

% change in health endpoint per 

increase in IQR of PM2.5 (1-3 day 

averaging period 

single pollutant models) 

hs-CRP: 

1-day: 90.2 (-10.2, 190.1) 

2-day: 99.1 (-26.1, 224.3) 

3-day: 100.4 (-2.9, 203.7) 

8-OHdG: 

1-day: -5.0 (-14.3, 4.4) 

2-day: -5.5 (-15.6, 4.6) 

3-day: -5.6 (-13.8, 2.6) 

PAI-1: 

1-day: 20.4 (17.3, 33.5) 

2-day: 16.2 (1.9, 30.5) 

3-day: 20.0 (18.5, 31.5) 

tPA: 

1-day: 12.0 (-2.4, 26.3) 

2-day: 12.0 (-2.9, 26.9); 

3-day: 12.0 (-2.7, 26.6) 

Fibrinogen: 

1-day: 2.6 (-2.7, 7.8) 

2-day: 1.5 (-4.1, 7.1); 

3-day: 3.6 (-0.8, 8.1) 

Heart Rate Variability 

SDNN: 

1-day: -4.0 (-6.1 to -1.9) 

2-day: -2.5 (-4.6 to -0.4) 

3-day: -3.0 (-5.0 to -1.1) 

r-MSSD: 

1-day: -3.0 (-8.7, 2.7) 

2-day: -2.0 (-8.4, 4.4); 

3-day: -3.6 (-8.8, 1.6) 

LF: 

1-day: -3.1 (-6.1 to -0.1) 

2-day: -3.2 (-4.6, 0.1); 

3-day: -3.4 (-6.1 to -0.6) 

HF: 

1-day: -3.7 (-9.4, 2.1) 

2-day: -2.1 (-8.4, 4.3); 

3-day: -4.0 (-9.3, 1.2) 

December 2009 E-29 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chuang et al. (2007, 

091063) 

Period of Study: Between Apr-Jun 

2004 or 2005 

Location: Taipei, Taiwan 

Outcome: High-sensitivity C-reactive 

protein (hs-CRP) 

Fibrinogen, plasminogen activator 

fibrinogen inhibitor-1 (PAI-1), tissue-type 

plasminogen activator (tPA), 8-hydroxy2’-deoxyguanosine (8-OHdG), and logtransformed HRV indices 

(SDNN = standard deviation of NN 

intervals, r-MSSD = square root of the 

mean of the sum of the squares of 

differences between adjacent NN 

intervals, LF = low frequency [0.04-

0.15Hz], and HF = high frequency[0.15-

0.40Hz]) 

Age Groups: 18-25 yr 

Study Design: Panel (cross-sectional) 

N: 76 students 

Statistical Analyses: Linear mixedeffects models 

Covariates: Age, sex, BMI, weekday, 

temperature of previous day, relative 

humidity 

Season: Only 1 season of data 

collection 

Dose-response Investigated? No

Statistical Package: NR 

Pollutant: Nitrate 

Averaging Time: Hourly data used to 

calculate avg over 1-3 day periods 

Mean (SD): 1-day avg: 4.5 (2.7) 

2-day avg: 4.7 (2.4) 

3-day avg: 4.4 (2.2) 

Range (Min, Max): 1-day avg: 0.7, 10.6

2-day avg: 0.7, 8.9 

3-day avg: 0.8, 7.5 

Monitoring Stations: 2 sites (each 

pollutant measured at 1 site only) 

Copollutant: PM10

Sulfate 

PM2.5

OC 

EC 

NO2

CO 

SO2

O3

Nitrate Increment: IQR (1-day avg: 2.5

2-day avg: 4.0 

3-day avg: 3.4) 

Effect Estimate [Lower CI, Upper CI]: 

% change in health endpoint per 

increase in IQR of nitrate (1-3 day 

averaging period 

single pollutant models) 

hs-CRP: 1-day: -2.1 (-21.9, 17.8) 

2-day: -11.6 (-58.6, 35.5) 

3-day: -18.7 (-69.9, 32.5) 

8-OHdG: 1-day: 9.0 (4.0, 14.1) 

2-day: 15.1 (5.9, 24.3) 

3-day: 15.0 (4.9, 25.0) 

PAI-1: 1-day: 4.0 (-2.5, 10.4) 

2-day: 11.6 (0.1, 23.1) 

3-day: 16.9 (4.3, 29.4) 

tPA: 1-day: 2.0 (-6.2, 10.3) 

2-day: 12.9 (-1.6, 27.5) 

3-day: 10.0 (-5.8, 25.8) 

Fibrinogen: 1-day: 1.6 (-1.3, 4.5) 

2-day: 1.3 (-3.9, 6.5) 

3-day: 1.0 (-4.6, 6.6) 

Heart Rate Variability 

SDNN: 1-day: -1.5 (-2.6 to -0.3) 

2-day: -2.6 (-4.7 to -0.5) 

3-day: -3.0 (-5.3 to -0.7) 

r-MSSD: 1-day: -5.5 (-8.7 to -2.2) 

2-day: -7.1 (-14.0 to -0.2) 

3-day: -8.1 (-14.5 to -1.8) 

LF: 1-day: -1.0 (-1.6 to -0.5) 

2-day: -2.0 (-5.6, 1.6) 

3-day: -2.0 (-5.2, 1.2) 

HF: 1-day: -2.0 (-5.3, 14[potential typo, 

possibly 1.4]) 

2-day: -4.9 (-10.9, 0.9) 

3-day: -6.9 (-13.4 to -0.3) 

December 2009 E-30 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chuang et al. (2007, 

091063) 

Period of Study: Between Apr-Jun 

2004 or 2005 

Location: Taipei, Taiwan 

Outcome: High-sensitivity C-reactive 

protein (hs-CRP) 

Fibrinogen, plasminogen activator 

fibrinogen inhibitor-1 (PAI-1), tissue-type 

plasminogen activator (tPA), 8-hydroxy2’-deoxyguanosine (8-OHdG), and logtransformed HRV indices 

(SDNN = standard deviation of NN 

intervals, r-MSSD = square root of the 

mean of the sum of the squares of 

differences between adjacent NN 

intervals, LF = low frequency [0.04-

0.15Hz], and HF = high frequency[0.15-

0.40Hz]) 

Age Groups: 18-25 yr 

Study Design: Panel (cross-sectional) 

N: 76 students 

Statistical Analyses: Linear mixedeffects models 

Covariates: Age, sex, BMI, weekday, 

temperature of previous day, relative 

humidity 

Season: Only 1 season of data 

collection 

Dose-response Investigated? No

Statistical Package: NR 

Pollutant: Sulfate 

Averaging Time: Hourly data used to 

calculate avg over 1- to 3-day periods 

Mean (SD): 1-day avg: 4.1 (3.6) 

2-day avg: 4.1 (3.7) 

3-day avg: 3.9 (3.5) 

Range (Min, Max): 1-day avg: 0.4, 10.9

2-day avg: 0.4, 11.9 

3-day avg: 0.4, 11.5 

Monitoring Stations: 2 sites (each 

pollutant measured at 1 site only) 

Copollutant: PM10

PM2.5

Nitrate 

OC 

EC 

NO2

CO 

SO2

O3

Sulfate Increment: IQR 

(1-day avg: 3.9 

2-day avg: 4.3 

3-day avg: 3.8) 

Effect Estimate [Lower CI, Upper CI]: 

% change in health endpoint per 

increase in IQR of sulfate (1-3 day 

averaging period 

single pollutant models) 

hs-CRP: 

1-day: 80.0 (9.8, 150.2) 

2-day: 87.1 (14.9, 159.4) 

3-day: 71.1 (13.0, 129.2) 

8-OHdG: 

1-day: 1.0 (0.3, 1.3) 

2-day: -0.4 (-5.4, 4.7) 

3-day: -0.3 (-4.3, 3.7) 

PAI-1: 

1-day: 12.0 (5.4, 18.7) 

2-day: 13.3 (6.6, 19.9) 

3-day: 11.2 (5.7, 16.6) 

tPA: 

1-day: 2.0 (-4.6, 8.7) 

2-day: 3.8 (-2.8, 10.3) 

3-day: 3.0 (-2.3, 8.2) 

Fibrinogen: 

1-day: 2.9 (0.2, 5.5) 

2-day: 2.8 (0.1, 5.5) 

3-day: 2.2 (0.4, 4.7) 

Heart Rate Variability 

SDNN: 

1-day: -3.1 (-4.1 to -2.1) 

2-day: -4.1 (-5.2 to -3.1) 

3-day: -2.0 (-2.9 to -1.2) 

r-MSSD: 

1-day: -5.0 (-8.0 to -2.0) 

2-day: -6.0 (-8.9 to -2.9) 

3-day: -5.7 (-8.2 to -3.2) 

LF: 

1-day: -3.4 (-4.9 to -1.8) 

2-day: -3.0 (-4.5 to -1.5) 

3-day: -3.0 (-4.3 to -1.7) 

HF: 

1-day: -3.5 (-6.5 to -0.4) 

2-day: -3.9 (-7.0 to -0.8) 

3-day: -3.0 (-5.5 to -0.5) 

December 2009 E-31 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chuang et al. (2007, 

098629) 

Period of Study: NR 

Location: Boston, MA 

Outcome: ST Segment Depression 

Age Groups: 43-75 yr

Study Design: Panel 

N: 48 coronary artery disease patients 

Statistical Analyses: Linear & Mixed 

Logistic Regression models 

Covariates: Participant, day of week, 

order of visit, visit date, hour of day, 

hourly temperature 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: Lags 1-72 h 

Pollutant: PM2.5 

Averaging Time: Hourly 

25th, 50th, 75th percentile: 

12-h avg: 6.18, 8.91, 13.18 

24-h avg: 6.38, 9.20, 13.31 

Max: 

12-h avg: 37.13 

24-h avg: 40.38 

Monitoring Stations: 1 

Co-pollutant: BC, CO, O3, NO2, SO2

Co-pollutant Correlation 

BC: 0.56 

O3: 0.20 

NO2: 0.38 

SO2: 0.25 

PM Increment: Interquartile Increase 

Change (Lower CI, Upper CI): 

12-h mean 

PM2.5: -0.022 (-0.032, -0.012) 

PM2.5+ NO2: -0.023 (-0.034, -0.012) 

PM2.5+ SO2: -0.009 (-0.02, 0.001) 

PM2.5+ BC: -0.011 (-0.023, 0.001) 

24-h mean 

PM2.5: -0.026 (-0.037, -0.015) 

PM2.5+ NO2: -0.017 (-0.029, 0.004) 

PM2.5+ SO2: -0.014 (-0.025, -0.002) 

PM2.5+ BC: -0.012 (-0.026, 0.003) 

Relative Risk (Lower CI, Upper CI): 

12-h mean 

PM2.5: 1.02 (0.86, 1.21) 

PM2.5+ NO2: 0.99 (0.82, 1.21) 

PM2.5+ SO2: 0.87 (0.71, 1.05) 

PM2.5+ BC: 0.92 (0.74, 1.14) 

24-h mean 

PM2.5: 1.22 (0.99, 1.50) 

PM2.5+ NO2: 1.00 (0.80, 1.25) 

PM2.5+ SO2: 1.04 (0.83, 1.30) 

PM2.5+ BC: 0.87 (0.65, 1.17) 

Mean (Lower CI, Upper CI): 

12-h mean 

Myocardial Infarction: -0.042 (-0.057, -

0.026) 

No Myocardial Infarction: -0.012 (-0.023, 

0.00) 

p- for interaction: 0.002 

Visit 1: -0.102 (-0.12, -0.085) 

Visits 2-4: 0.006 (-0.005, 0.017) 

p- for interaction: <0.001 

Diabetic: -0.097 (-0.119, -0.074) 

Non-diabetic: -0.009 (-0.019, 0.002) 

p- for interaction: <0.001 

Diurnal daytime pattern: -0.032 (-0.043, -

0.021) 

Diurnal nighttime pattern: -0.006 (-0.018, 

0.006) 

p- for interaction: <0.001 

24-h mean 

Myocardial Infarction: -0.027 (-0.043, -

0.012) 

No Myocardial Infarction: -0.025 (-0.038, 

0.011) 

p- for interaction: 0.787 

Visit 1: -0.127 (-0.148, -0.105) 

Visits 2-4: 0.001 (-0.011, 0.013) 

p- for interaction: <0.001 

Diabetic: -0.118 (-0.144, -0.091) 

Non-diabetic: -0.13 (-0.024, -0.002) 

p- for interaction: <0.001 

Diurnal daytime pattern: -0.031 (-0.043, -

0.020) 

Diurnal nighttime pattern: -0.018 (-0.030, 

-0.005) 

p- for interaction: 0.233 

Notes: The effects of PM on half-h St 

segment levels (Fig 1)

December 2009 E-32 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dales et al. (2007, 155743) 

Period of Study: NR 

Location: Ottawa, Canada 

Outcome: Vascular Reactivity 

Age Groups: 18-50 yr 

Study Design: Panel 

N: 39 volunteers 

Statistical Analyses: Mixed Effects 

Model 

Covariates: Temperature, humidity, 

wind speed, time of day testing was 

done, site 

Dose-response Investigated? No 

Statistical Package: S-PLUS 

Lags Considered: NR 

Pollutant: PM2.5

Averaging Time: 2 h 

Mean (SD): 

Downtown: 40 (20) 

Tunney’s Pasture: 10 (10) 

p-value 0.000 

Monitoring Stations: NR 

Copollutant: PM1.0 

Co-pollutant Correlation 

N/A 

PM Increment: Interquartile Range 

(27.02 μg/m3

) 

Beta (SE), p-value: 

Flow mediated vasodilation (%): -0.016 

(0.0072) p=0.03 

Heart Rate (beats/min): 0.081 (0.135) 

p=0.55 

Diastolic blood pressure (mmHg): 0.088 

(0.088) p=0.32 

Systolic blood pressure (mmHg): -0.108 

(0.006) p=0.48 

Reference: de Hartog et al. (2009, 

191904) 

Period of Study: 1998-1999 

Location: 

Amsterdam, The Netherlands 

Erfurt, Germany 

and Helsinki, Finland 

Outcome: Heart Rate Variability 

Age Groups: 50+

Study Design: Panel 

N: 122 coronary heart disease patients 

Statistical Analyses: Linear Regression

Covariates: Time trend, temperature, 

humidity, pressure 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Lags 0-3 days 

Pollutant: PM2.5

Averaging Time: Daily 

p25, p50, p75. p95: 

Amsterdam: 10.4, 16.7, 23.9, 47.0 

Erfurt: 10.8, 16.3, 26.7, 62.3 

Helsinki: 8.3, 10.6, 15.9, 25.8 

Monitoring Stations: NR 

Copollutant: PM <0.1, PM0.1-1.0, NO2, 

SO2

Co-pollutant Correlation 

NR 

Note: Correlations are provided for 

source-specific PM2.5 & elements 

PM Increment: 1 μg/m3

Beta (Lower CI, Upper CI): 

SDNN 

Local traffic: -0.12 (-0.36, 0.12) 

Long-range transport: -0.04 (-0.14, 0.06)

Oil combustion: -0.29 (-1.04, 0.45) 

Industry: 0.03 (-0.12, 0.19) 

Crustal: 0.11 (-0.35, 0.56) 

Salt: -0.19 (-1.92, 1.55) 

HF 

Local traffic: 0.43 (-0.91, 1.79) 

Long-range transport: 0.19 (-0.38, 0.77)

Oil combustion: 1.05 (-2.70, 4.94) 

Industry: 0.62 (-0.34, 1.59) 

Crustal: 1.57 (-1.28, 4.50) 

Salt: -1.43 (-9.86, 7.78) 

SDNN 

ABS: -0.52 (-1.39, 0.31) 

S: -0.51 (-1.36, 0.33) 

V: -0.66 (-1.73, 0.41) 

Zn: 0.12 (-0.55, 0.79) 

Ca: 0.27 (-0.58, 1.11) 

Cl: 0.14 (-0.39, 0.67) 

Fe: 0.15 (-1.00, 1.30) 

Cu: -0.08 (-0.74, 0.57) 

SDNN 

ABS: 2.91 (-2.54, 8.67) 

S: 0.25 (-4.42, 5.14) 

V: 0.73 (-4.74, 6.53) 

Zn: 3.85 (-0.26, 8.13) 

Ca: 3.39 (-1.80, 8.86) 

Cl: 1.13 (-1.48, 3.81) 

Fe: 6.69 (0.11, 13.69) 

Cu: 3.00 (-0.85, 7.00) 

Notes: Estimates provided are for all 

subjects at lag 1, estimates are also 

available at lags 0, 2, and 3, as well as 

for subjects w/o beta-blockers at lags 

0-3. 

December 2009 E-33 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: DeMeo et al. (2004, 

087346) 

Period of Study: Jul-Aug 1999 

Location: Boston, MA 

Outcome: Oxygen saturation 

Age Groups: 60.4-89.2 yr 

Study Design: Cross-sectional study 

N: 28 adult participants 

Statistical Analyses: GLM, Natural 

Spline Smoothing, Regression Analysis, 

Random-effects model 

Covariates: Mean temperature, Dew 

point temperature, Barometric pressure, 

Medication use 

Season: Summer 

Dose-response Investigated? No 

Statistical Package: 

S-PLUS, SAS 

Lags Considered: Hourly lags between 

2 and 7 h 

Pollutant: PM2.5

Averaging Time: 6 h, 12 h, 24 h, 48 h 

PM Increment: IQR (13.42 μg/m3) 

increase 

6 h: 13.42 μg/m3

12 h: 10.81 μg/m3

24 h: 10.26μg/m3

48: 10.57 μg/m3

Overall: 0.172% (-0.313, 0.031) 

decrease 

6 h: -0.769% (-1.21 to -0.327) decrease 

B-blocker users: -0.062% (-0.248, 0.123)

Rest: 6 h: -0.173 (-0.345 to -0.001) 

12 h: -0.160 (-0.308 to -0.012) 

24 h: -0.169 (-0.316 to -0.022) 

48 h: -0.153 (-0.304, 0.002) 

Exercise: 6 h: -0.005 (-0.215, 0.205) 

12 h: -0.014 (-0.196, 0.168) 

24 h: 0.001 (-0.180, 0.182) 

48 h: -0.011 (-0.196, 0.174) 

Post exercise Rest: 6 h: -0.173 (-0.332 

to -0.014) 

12 h: -0.128 (-0.266, 0.010) 

4 h: -0.113 (-0.250, 0.023) 

48 h: -0.157 (-295 to -0.019) 

Paced breathing: 6 h: -0.142 (-0.292, 

0.007) 

12 h: -0.139 (-0.269 to -0.010) 

24 h: -0.121 (-0.248, 0.007) 

48 h: -0.082 (0.211, 0.047) 

Summary over protocol 

6 h: -0.131 (-0.247 to -0.015) 

12 h: -0.120 (-0.221, 0.020) 

24 h: -0.112 (-0.212 to -0.013) 

Notes: Fig of the variation in oxygen 

saturation during the first rest period vs.. 

individual hourly lag measurements for 

PM2.5 

Reference: Diez-Roux et al. (2006, 

156400) 

Period of Study: Baseline data 

collected Jun 2000-Aug 2002 

Location: 

USA 

6 field centers: 

Baltimore, MD 

Chicago, IL 

Forsyth Co, NC 

Los Angeles, CA 

New York, NY 

St. Paul, MN 

Outcome: C-reactive protein (CRP) 

assessed continuously and as a 

dichotomous variable (cutpoint, 3 mg/L) 

interleukin-6 (IL-6) 

Age Groups: 45-84 yr

Study Design: Cross-sectional 

N: 5634 persons 

Statistical Analyses: Linear regression 

& logistic regression 

Covariates: Age, sex, race/ethnicity, 

general health status, BMI, diabetes, 

cigarette status, secondhand smoke, 

physical activity, arthritis flare in last 2 

wk, medications, infections in last 2 wk 

(also ran models including site, 

copollutants, and weather) 

Season: Examined seasonal patterns in 

the residuals of fully adjusted models 

stratified by season 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM2.5 

Averaging Time: Prior day, prior 2 days, 

prior wk, prior 30 days, and prior 60 

days 

Mean (SD): Presented in Fig 1 by site 

Percentiles: Presented in Fig 1 by site 

Range: NR 

Monitoring Stations: NR 

Long-term exposure to PM estimated 

based on residential history reported 

retrospectively 

All addresses geocoded 

Ambient AP obtained from U.S. EPA 

Copollutant: 

SO2

NO2

CO 

O3

PM Increment: 10 μg/m3 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted (all personal-level covariates) 

relative difference in CRP (mg/L) per 

10 μg/m3 increase in PM2.5

Prior day: 0.99 (0.96, 1.01) 

Prior 2 days: 0.99 (0.96, 1.01) 

Prior 7 days: 1.00 (0.96, 1.04) 

Prior 30 days: 1.03 (0.98, 1.10) 

Prior 60 days: 1.04 (0.97, 1.11) 

Odds Ratios of CRP of ≥ 3 mg/L per 

10 μg/m3

 increase in PM2.5 (adjusted for 

all personal-level covariates) 

Prior day: 0.98 (0.92, 1.04) 

Prior 2 days: 0.99 (0.93, 1.06) 

Prior 7 days: 1.05 (0.96, 1.15) 

Prior 30 days: 1.12 (0.98, 1.29) 

Prior 60 days: 1.12 (0.96, 1.32) 

December 2009 E-34 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dubowsky et al. (2006, 

088750) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, Missouri 

Outcome: White blood cells (WBC), 

C-reactive protein (CRP), interleukin-6 

(IL-6) 

Age Groups: ≥ 60 yr

Study Design: Panel (4 planned 

repeated measures 

n = 35 participated in 4 trips) 

N: 44 participants 

Statistical Analyses: Linear mixed 

models 

Covariates: Sex, obesity, diabetes, 

smoking history, time-varying 

parameters (apparent temperature, h, 

day, trip, residence, mold, pollen, illness, 

and juice intake), medication and vitamin 

consumption (day of blood draw) 

Season: Limited data collection period 

Dose-response Investigated? No 

Statistical Package: SAS v8.02 

Pollutant: PM2.5 (ambient) 

Averaging Time: Hourly data used to 

calculate avg concentrations over 1-7 

days preceding the blood draw (ambient 

PM2.5) 

Microenvironmental PM2.5 measures 

were avgd over the 1-2 days preceding 

the blood draw 

Mean (SD) (1-day): 16 (6.0) 

Percentiles (1-day): 0: 6.5 

25th: 12 

75th: 22 

100th: 28 

Monitoring Stations: 1 ambient monitor

Copollutant: 

PM2.5 (ambient) 

BC (ambient) 

PM2.5 (microenvironment) 

CO 

NO2

SO2

O3

PM Increment: 6.1 μg/m3 (5-day mean)

Effect Estimate [Lower CI, Upper CI]: 

Note: Most results presented in figures. 

Selected result in abstract text: % 

change in WBC per increase in IQR 

(5.4 μg/m3

) of PM2.5 avgd over the 

previous week: 5.5 (0.1, 11) 

Associations (% changes and 95%CI) 

between 5-day mean ambient 

concentrations and markers of 

inflammation per increase (IQR) in 

pollutant. 

CRP: All participants: 14 (-5.4, 37) 

Among those with all 3 conditions 

(diabetes, obesity, and hypertension): 81 

(21, 172) 

Among those with at least 2 of the 

conditions: 11 (-7.3, 33) 

IL-6: All participants: -2.1 (-13, 11) 

Among those with all 3 conditions 

(diabetes, obesity, and hypertension): 23 

(-5.3, 59) 

Among those with at least 2 of the 

conditions: -3.1 (-14, 9.7) 

WBC (x109/L): All participants: 3.4 (-1.8, 

8.9) 

Among those with all 3 conditions 

(diabetes, obesity, and hypertension): 

0.4 (-8.8, 11) 

Among those with at least 2 of the 

conditions: 3.6 (-1.7, 9.1) 

Reference: Dubowsky et al. (2006, 

088750) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, Missouri 

Outcome: White blood cells (WBC), 

C-reactive protein (CRP), interleukin-6 

(IL-6) 

Age Groups: ≥ 60 yr

Study Design: Panel (4 planned 

repeated measures 

n = 35 participated in 4 trips) 

N: 44 participants 

Statistical Analyses: Linear mixed 

models 

Covariates: Sex, obesity, diabetes, 

smoking history, time-varying 

parameters (apparent temperature, h, 

day, trip, residence, mold, pollen, illness, 

and juice intake), medication and vitamin 

consumption (day of blood draw) 

Season: Limited data collection period 

Dose-response Investigated? No 

Statistical Package: SAS v8.02 

Pollutant: BC (ng/m3) (ambient) 

Averaging Time: Hourly data used to 

calculate avg concentrations over 1-7 

days preceding the blood draw (ambient 

PM) 

microenvironmental PM2.5 measures 

were avgd over the 1-2 days preceding 

the blood draw 

Mean (SD) (1-day): 900 (280) 

Percentiles (1-day): 0: 290 

25th: 730 

75th: 1,100 

100th: 1,400 

Monitoring Stations: 1 ambient monitor

Copollutant: 

PM2.5 (ambient) 

BC (ambient) 

PM2.5 (microenvironment) 

CO 

NO2

SO2

O3

PM Increment: 230 ng/m3 (5-day mean)

Effect Estimate [Lower CI, Upper CI]: 

Note: Most results presented in figures. 

Associations (% changes and 95%CI) 

between 5-day mean ambient 

concentrations and markers of 

inflammation per increase (IQR) in 

pollutant. 

CRP: All participants: 13 (-0.34, 28) 

Among those with all 3 conditions 

(diabetes, obesity, and hypertension): 49 

(16, 90) 

Among those with at least 2 of the 

conditions: 9.0 (-3.8, 24) 

IL-6: All participants: -0.8 (-8.9, 8.0) 

Among those with all 3 conditions 

(diabetes, obesity, and hypertension): 15 

(-2.2, 35) 

Among those with at least 2 of the 

conditions: -2.7 (-11, 6.2) 

WBC (x109/L): All participants: 1.3 (-2.1, 

4.8) 

Among those with all 3 conditions 

(diabetes, obesity, and hypertension): 

0.05 (-5.9, 6.3) 

Among those with at least 2 of the 

conditions: 1.5 (-2.0, 5.1) 

December 2009 E-35 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ebelt et al. (2005, 056907) 

Period of Study: Summer of 1998 

Location: Vancouver, Canada 

Outcome: CVD 

Age Groups: Range from 54-86 yr 

mean age= 74 yr 

Study Design: Extended analysis of a 

repeated-measures panel study 

N: 16 persons with COPD 

Statistical Analyses: Earlier analysis 

expanded by developing mixed-effect 

regression models and by evaluating 

additional exposure indicators 

Dose-response Investigated? No 

Statistical Package: SAS V8 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Ambient PM2.5: 11.4 ± 4.6 

Exposure to ambient PM2.5: 7.9 ± 3.7 

Range (Min, Max): 

Ambient PM2.5: 4.2-28.7 

Exposure to ambient PM2.5: 0.9-21.3 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient concentrations and exposure to 

ambient PM were highly correlated for 

each respective metric: r ≥ 0.71 

PM Increment: 

Increment: C2.5: IQR = 5.8 

SBP (mm Hg): -1.70 (-3.48-0.08) 

DBP (mm Hg): -0.58 (-2.02-0.85) 

Ln-SVE (bph): 0.20 (0.00-0.40) 

HR (bpm): 0.93 (-0.90-2.75) 

SDNN (ms): -4.37 (-9.40-0.65) 

R-MSSD (ms): -2.79 (-6.16-0.57) 

Increment: NS_C2.5: IQR = 4.2 

SBP (mm Hg): -1.52 (-2.94- -0.09) 

DBP (mm Hg): -0.77 (-1.87-0.32) 

Ln-SVE (bph): 0.19 (-0.01-0.38) 

HR (bpm): 1.03 (-0.43-2.48) 

SDNN (ms): -3.83 (-7.77-0.11) 

R-MSSD (ms): -2.90 (-5.55- -0.25) 

Increment: S_C2.5: IQR = 1.5 

SBP (mm Hg): -1.10 (-3.48-1.28) 

DBP (mm Hg): 0.76 (-1.15-2.68) 

Ln-SVE (bph): 0.09 (-0.05-0.23) 

HR (bpm): -0.42 (-2.28-1.44) 

SDNN (ms): -3.14 (-9.73-3.45) 

R-MSSD (ms): 0.24 (-5.14-5.63) 

Increment: A2.5: IQR = 4.4 

SBP (mm Hg): -1.90 (-3.66- -0.14) 

DBP (mm Hg): -0.33 (-1.72-1.06) 

Ln-SVE (bph): 0.20 (0.02-0.37) 

HR (bpm): 0.57 (-1.34-2.47) 

SDNN (ms): -3.91 (-8.79-0.97) 

R-MSSD (ms): -1.05 (-4.79-2.17) 

Increment: NS_A2.5: IQR = 3.4 

SBP (mm Hg): -1.70 (-3.27- -0.14) 

DBP (mm Hg): -0.51 (-1.71-0.70) 

Ln-SVE (bph): 0.20 (0.02-0.37) 

HR (bpm): 0.69 (-0.96-2.35) 

SDNN (ms): -4.18 (-8.51-0.15) 

R-MSSD (ms): -1.40 (-4.40-1.60) 

Increment: S_T2.5: IQR = 0.9 

SBP (mm Hg): -1.55 (-3.35-0.26) 

DBP (mm Hg): 0.49 (-0.91-1.90) 

Ln-SVE (bph): 0.08 (-0.14-0.19) 

HR (bpm): -0.24 (-1.75-1.26) 

SDNN (ms): -0.68 (-4.74-3.38) 

R-MSSD (ms): 0.91 (-3.51-5.33) 

Increment: T2.5: IQR = 10.1 

SBP (mm Hg): -1.26 (-2.60-0.08) 

DBP (mm Hg): 0.34 (-1.26-1.94) 

Ln-SVE (bph): 0.01 (-0.10-0.11) 

HR (bpm): -0.23 (-1.09-0.63) 

SDNN (ms): -2.11 (-4.90-0.68) 

R-MSSD (ms): -0.83 (-3.60-1.94) 

Increment: N2.5: IQR = 8.9 

SBP (mm Hg): -0.81 (-2.15-0.53) 

DBP (mm Hg): 0.40 (-1.19-1.98) 

Ln-SVE (bph): -0.04 (-0.18-0.10) 

HR (bpm): -0.35 (-0.85-0.14) 

SDNN (ms): -1.10 (-3.10-0.90) 

R-MSSD (ms): -0.54 (-2.54-1.46) 

Note: Total personal fine particle 

exposure (T) were dominated by 

exposures to non ambient particles 

which were not correlated with ambient 

fine particle exposure (A) or ambient 

concentrations (C). Results for each of 

these metrics are listed. 

December 2009 E-36 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Fan et al. (2008, 191979) 

Period of Study: Feb-May 2005 

Location: Paterson, New Jersey 

Outcome: Cardiopulmonary Health 

(FEV, FVC, PEF, SDNN, HR) 

Age Groups: 61.2 (13.7) 

Study Design: Panel 

N: 11 

Statistical Analyses: Mixed Effects 

models, Linear Regression models 

Covariates: Temperature, humidity 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0 

Pollutant: PM2.5 

Averaging Time: Daily 

Mean (SD): | 

∆PM2.5 avg 

Morning: 35.2 (25.9) 

Afternoon: 24.1 (22.1) 

∆PM2.5 peak 

Morning: 71.3 (56.1) 

Afternoon: 64.3 (43.5) 

Range: 

∆PM2.5 avg 

Morning: 1.1 - 87 

Afternoon: 1.2 - 98 

∆PM2.5 peak 

Morning: 4.0 - 278 

Afternoon: 3.0 - 150 

Monitoring Stations: NR 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: 10 μg/m3

Beta (SE), p-value: 

∆SDNN

Morning, ∆PM2.5 avg 

15min: -14.5 (6.9), 0.06 

2h: -18.9 (4.2), 0.0002 

4h: -2.5 (8.6), 0.78 

Morning, ∆PM2.5 peak 

15min: -9.2 (11.2), 0.43 

2h: -5.1 (13.8), 0.72 

4h: -7.4 (12.0), 0.55 

Afternoon, ∆PM2.5 avg 

15min: -2.4 (7.6), 0.77 

2h: -20.2 (10.8), 0.10 

4h: -0.7 (11.2), 0.95 

Afternoon, ∆PM2.5 peak 

15min: 0.6 (8.9), 0.95 

2h: 19.2 (14.6), 0.23 

4h: -6.8 (14.1), 0.64 

∆ HR 

Morning, ∆PM2.5 avg 

15min: 1.2 (3.1), 0.71 

2h: -5.5 (2.9), 0.08 

4h: -3.1 (4.6), 0.51 

Morning, ∆PM2.5 peak 

15min: 0.8 (4.4), 0.86 

2h: -7.2 (4.2), 0.11 

4h: -7.1 (6.3), 0.28 

Afternoon, ∆PM2.5 avg 

15min: -2.0 (4.0), 0.62 

2h: 0.9 (5.4), 0.87 

4h: 8.2 (5.2), 0.14 

Afternoon, ∆PM2.5 peak 

15min: -5.6 (5.3), 0.31 

2h: 3.1 (8.1), 0.71 

4h: 11.1 (8.1), 0.20 

∆ FEV1

Morning, ∆PM2.5 avg: 0.02 (0.04), 0.68 

Morning, ∆PM2.5 peak: -0.13 (0.08), 0.16 

∆ FVC 

Morning, ∆PM2.5 avg: -0.10 (0.09), 0.31 

Morning, ∆PM2.5 peak: -0.12 (0.17), 0.51

∆ PEF 

Morning, ∆PM2.5 avg: -0.54 (0.62), 0.42 

Morning, ∆PM2.5 peak: -1.46 (1.12), 0.24

Notes: Estimates relative to increases in 

the avg and peak PM2.5 concentrations 

Reference: Folino et al. (2009, 191902) 

Period of Study: Jun 2006-May 2007 

Location: Padua, Italy 

Outcome: HRV & Inflammatory Markers

Age Groups: 45-65 yr

Study Design: Panel 

N: 39 patients w/ myocardial infarction 

Statistical Analyses: Linear Regression 

Model, ANOVA 

Covariates: Temperature, relative 

humidity, atmospheric pressure, betablocker, aspirin, or nitrate consumption, 

smoking habit 

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: NR 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 

Summer: 33.9 (12.7) 

Winter: 62.1 (27.9) 

Spring: 30.8 (14.0) 

Monitoring Stations: NR 

Copollutant: PM10, PM0.25

Co-pollutant Correlation: NR 

PM Increment: 1 μg/m3

Beta (SE), p-value: 

SDNN: 0.109 (0.115), 0.345 

SDANN: 0.127 (0.126), 0.314 

RMSSD: 0.045 (0.040), 0.256 

pH: 0.002 (0.001), 0.041 

LTB4: 0.590 (0.324), 0.069 

eNO: -0.002 (0.003), 0.503 

PTX3: -0.004 (0.002), 0.013 

C-reactive protein: -0.008 (0.005), 0.115

CC16: -0.002 (0.002), 0.410 

IL-8: 0.000 (0.003), 0.989 

December 2009 E-37 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Folino et al. (2009, 191902) 

Period of Study: Jun 2006-May 2007 

Location: Padua, Italy 

Outcome: HRV & Inflammatory Markers

Age Groups: 45-65 yr

Study Design: Panel 

N: 39 patients w/ myocardial infarction 

Statistical Analyses: Linear Regression 

Model, ANOVA 

Covariates: Temperature, relative 

humidity, atmospheric pressure, betablocker, aspirin, or nitrate consumption, 

smoking habit 

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: NR 

Pollutant: PM0.25 

Averaging Time: 24 h 

Mean (SD): 

Summer: 17.6 (7.5) 

Winter: 30.5 (17.4) 

Spring: 18.8 (10.8) 

Monitoring Stations: NR 

Copollutant: PM10, PM2.5

Co-pollutant Correlation: NR 

PM Increment: 1 μg/m3

Beta (SE), p-value: 

SDNN: 0.214 (0.204), 0.295 

SDANN: 0.214 (0.214), 0.316 

RMSSD: 0.081 (0.077), 0.291 

pH: 0.005 (0.002), 0.004 

LTB4: 0.835 (0.533), 0.117 

eNO: -0.006 (0.005), 0.182 

PTX3: -0.006 (0.003), 0.071 

C-reactive protein: -0.011 (0.007), 0.104

CC16: 0.001 (0.004), 0.890 

IL-8: -0.004 (0.006), 0.527 

Reference: Goldberg et al. (2008, 

180380) 

Period of Study: Jul 2002-Oct 2003 

Location: Montreal, Canada 

Outcome: Oxygen saturation & pulse 

rate 

Age Groups: 50-85 yr

Study Design: Panel 

N: 31 

Statistical Analyses: Mixed Random 

Effects Model 

Covariates: Body temperature, 

consumption of salt, intake of fluids, 

being ill the day before, ambient 

temperature, relative humidity, 

barometric pressure 

Dose-response Investigated? No 

Statistical Package: Splus 

Lags Considered: lags 1 day; 0- to 

2-day avg 

Pollutant: PM2.5 

Averaging Time: Daily 

IQR: 7.3 

Monitoring Stations: 8 

Co-pollutant: CO, NO2, SO2, O3

Co-pollutant Correlation 

CO: 0.72 

NO2: 0.62 

PM Increment: Interquartile Range 

(7.3 μg/m3

) 

Mean Difference (Lower CI, Upper CI), 

lag: 

Oxygen Saturation 

Unadjusted: 

-0.087 (-0.143, -0.031), lag 0 

Unadjusted: 

-0.058 (-0.114, -0.002), lag 1 

Unadjusted: 

 -0.083 (-0.155, -0.010), lag 0-2-day avg

Adjusted: -0.056 (-0.117, 0.005), lag 0 

Adjusted: -0.019 (-0.079, 0.041), lag 1 

Adjusted: -0.039 (-0.118, 0.039), lag 0-

2-day avg 

Pulse Rate 

Unadjusted: 0.226 (-0.037, 0.489), lag 0

Unadjusted: 0.288 (0.022, 0.554), lag 1

Unadjusted: 0.420 (0.067, 0.772), lag 0-

2-day avg 

Adjusted: 0.158 (-0.136, 0.451), lag 0 

Adjusted: 0.246 (-0.040, 0.531), lag 1 

Adjusted: 0.353 (-0.034, 0.740), lag 0-

2-day avg 

December 2009 E-38 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Goldberg et al. (2008, 

180380) 

Period of Study: Jul 2002-Oct 2003 

Location: Montreal, Canada 

Outcome: Shortness of Breath & 

General health 

Age Groups: 50-85 yr

Study Design: Panel 

N: 31 

Statistical Analyses: Mixed Random 

Effects Model 

Covariates: Body temperature, 

consumption of salt, intake of fluids, 

being ill the day before, ambient 

temperature, relative humidity, 

barometric pressure 

Dose-response Investigated? No 

Statistical Package: Splus 

Lags Considered: lags 0-4 days; 0- to 

2-day avg 

Pollutant: PM2.5 

Averaging Time: Daily 

Mean: 9.5 

Median: 7.0 

Min: 0.8 

Max: 50.2 

IQR: 7.3 

Monitoring Stations: 8 

Co-pollutant: CO, NO2, SO2, O3

Co-pollutant Correlation 

CO: 0.66 

NO2: 0.54 

O3: 0.32 

SO2: 0.50

PM Increment: Interquartile Range 

(7.3 μg/m3

) 

Mean Difference (Lower CI, Upper CI), 

lag: 

General Health 

Unadjusted: -0.317 (-0.699, 0.064), lag 0

Unadjusted: -0.284 (-0.670, 0.103), lag 1

Unadjusted: -0.048 (-0.427, 0.332), lag 2

Unadjusted: -0.241 (-0.620, 0.139), lag 3

Unadjusted: -0.010 (-0.390, 0.370), lag 4

Unadjusted: -0.482 (-1.053, 0.090), lag 

0-2-day avg 

Adjusted: -0.125 (-0.545, 0.295), lag 0 

Adjusted: -0.167 (-0.568, 0.234), lag 1 

Adjusted: -0.081 (-0.464, 0.302), lag 2 

Adjusted: -0.222 (-0.602, 0.157), lag 3 

Adjusted: 0.016 (-0.364, 0.396), lag 4 

Adjusted: -0.281 (-0.886, 0.325), lag 

0-2-day avg 

Shortness of breath at night 

Unadjusted: -0.421 (-0.847, 0.006), lag 0

Unadjusted: -0.278 (-0.711, 0.155), lag 1

Unadjusted: -0.100 (-0.526, 0.327), lag 2

Unadjusted: -0.220 (-0.645, 0.206), lag 3

Unadjusted: -0.206 (-0.632, 0.220), lag 4

Unadjusted: -0.555 (-1.172, 0.063), lag 

0-2-day avg 

Adjusted: -0.171 (-0.639, 0.297), lag 0 

Adjusted: -0.130 (-0.579, 0.319), lag 1 

Adjusted: -0.127 (-0.553, 0.299), lag 2 

Adjusted: -0.192 (-0.616, 0.231), lag 3 

Adjusted: -0.171 (-0.594, 0.253), lag 4 

Adjusted: -0.301 (-0.952, 0.350), lag 

0-2-day avg 

Reference: Ibald-Mulli et al. (2004, 

087415) 

Period of Study: Winter 1998-1999 

Location: 

Helsinki, Finland 

Erfurt, Germany 

Amsterdam, the Netherlands 

Outcome: Blood Pressure & Heart Rate 

Age Groups: 40-84 

Study Design: Panel 

N: 131 adults w/ CHD 

Statistical Analyses: Linear Regression 

Covariates: Trend, day of week, 

temperature, barometric pressure, 

relative humidity, medication use 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2, 5-day avg 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 

Downtown: 40 (20) 

Tunney’s Pasture: 10 (10) 

p-value 0.000 

Monitoring Stations: NR 

Copollutant: PM1.0 

Co-pollutant Correlation: N/A 

PM Increment: Interquartile Range 

(27.02 μg/m3

) 

Beta (SE), p-value: 

Flow mediated vasodilation (%): 

-0.016 (0.0072) p=0.03 

Heart Rate (beats/min): 

0.081 (0.135) p=0.55 

Diastolic blood pressure (mmHg): 

0.088 (0.088) p=0.32 

Systolic blood pressure (mmHg): 

-0.108 (0.006) p=0.48 

Reference: Langrish et al. (2009, 

191908) 

Period of Study: Aug 2008 

Location: Beijing, China 

Outcome: Cardiovascular Effects 

Age Groups: Median 28 yr 

Study Design: Panel 

N: 15 

Statistical Analyses: NR 

Covariates: NR 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: NR 

Pollutant: PM2.5 

Averaging Time: NR 

Mean: 

W/o mask: 86 

W/ mask: 140 

Monitoring Stations: NR 

Co-pollutant: CO, SO2, NO2

Co-pollutant Correlation: N/A 

PM Increment: NR 

Mean (Lower CI, Upper CI): 

W/o Mask (Day) 

SBP: 100 (104, 116) 

DBP: 73 (69, 76) 

MAP: 85 (81, 88) 

Heart Rate: 79 (74, 84) 

Avg NN interval: 829 (789, 869) 

pNN50: 15.9 (10.7, 21.0) 

RMSSD: 35.1 (29.2, 41.0) 

SDNN: 61.2 (54.9, 67.5) 

Triangular index: 12.9 (11.9, 13.9) 

LF power: 816 (628, 1004) 

HF power: 460 (325, 595) 

LFn: 62.8 (56.7, 68.9) 

HFn: 29.2 (25.5, 32.8) 

HF/LF ratio: 0.738 (0.507, 0.970) 

W/ Mask (Day) 

SBP: 109 (104, 114) 

DBP: 73 (70-76) 

MAP: 85 (81, 89) 

December 2009 E-39 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Heart Rate: 78 (73, 82) 

Avg NN interval: 850 (805, 896) 

pNN50: 17.9 (14.2, 21.6) 

RMSSD: 37.1 (32.2, 42.0) 

SDNN: 65.5 (59.0, 72.2)* 

Triangular index: 13.8 (13.0, 14.5) 

LF power: 919 (717, 1122)* 

HF power: 485 (400, 569) 

LFn: 64.5 (60.6, 68.4) 

HFn: 30.0 (27.0, 33.1) 

HF/LF ratio: 0.680 (0.519, 0.842) 

W/o Mask (During Walk) 

SBP: 121 (115, 127) 

DBP: 81 (75-87) 

MAP: 94 (89, 99) 

Heart Rate: 88 (82, 94) 

Avg NN interval: 594 (562, 627) 

pNN50: 3.3 (0.8, 5.7) 

RMSSD: 17.2 (13.4, 21.0) 

SDNN: 45.8 (36.8, 54.8) 

Triangular index: 10.7 (9.1, 12.4) 

LF power: 313 (170, 455) 

HF power: 76.5 (33.6, 120.0) 

LFn: 68.2 (60.9, 75.5) 

HFn: 16.1 (11.9, 20.3) 

HF/LF ratio: 0.259 (0.173, 0.344) 

W/ Mask (During Walk) 

SBP: 114 (108, 120) 

DBP: 79 (74, 83) 

MAP: 90 (86, 94) 

Heart Rate: 91 (85, 97) 

Avg NN interval: 613 (571, 655) 

pNN50: 2.1 (-0.1, -4.4) 

RMSSD: 20.0 (15.5, 24.6) 

SDNN: 54.8 (42.5, 67.0) 

Triangular index: 11.4 (9.4, 13.3) 

W/ Mask (During Walk) 

LF power: 414 (233, 595) 

HF power: 116.8 (52.6, 181.0) 

LFn: 67.9 (61.9, 73.9) 

HFn: 16.0 (12.5, 19.4) 

HF/LF ratio: 0.247 (0.180, 0.314) 

Mean (SD): 

W/o Mask (After Walk) 

Headache: 2.53 (5.55) 

Dizziness: 1.07 (2.22) 

Tiredness: 8.47 (12.14) 

Sickness: 1.07 (2.22) 

Cough: 1.80 (4.80) 

Difficulty Breathing: 0.67 (0.90) 

Eye irritation: 1.40 (3.60) 

Throat irritation: 1.47 (4.07) 

Nose irritation: 1.53 (3.78) 

Unpleasant Smell: 0.93 (1.22) 

Bad taste: 0.73 (0.96) 

Difficulty walking: 12.53 (13.24) 

Perception of Pollution: 19.80 (18.37) 

W/ Mask (After Walk) 

Headache: 0.73 (1.03) 

Dizziness: 0.80 (1.57 

Tiredness: 7.40 (9.37) 

Sickness: 0.87 (1.51) 

Cough: 1.00 (1.73) 

Difficulty Breathing: 3.80 (8.10) 

Eye irritation: 1.67 (3.27) 

Throat irritation: 1.07 (2.63) 

Nose irritation: 1.07 (1.91) 

Unpleasant Smell: 0.60 (0.91) 

Bad taste: 0.60 (1.18) 

Difficulty walking: 15.13 (11.51) 

Perception of Pollution: 11.60 (10.44) 

*p < 0.05 

Notes: Estimates also available for 24 h, 

night, before walk, and 24 h after walk. 

December 2009 E-40 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lanki et al. (2006, 088412) 

Period of Study: Fall 1998-spring 1999 

Location: Helsinki, Finland 

Outcome: ST segment depressions (2 

endpoints: >0.1mV regardless of the 

direction of the ST slope and >0.1mV 

with horizontal or downward slope 

[stricter criteria]) 

Age Groups: Mean = 68.2 (6.5) yr

Study Design: Panel 

N: 45 elderly nonsmoking persons with 

stable coronary heart disease 

342 total exercise tests for analyses 

Statistical Analyses: Generalized 

additive models with penalized splines 

(logistic regression) 

principal components analysis and linear 

regression of 13 measured elements 

used to apportion PM2.5 mass between 

different sources 

Covariates: Subject, linear terms for 

time trend, temperature, relative 

humidity, penalized spline for change in 

heart rate during the exercise test 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-plus 2000 and R

Pollutant: PM2.5 (Analyses conducted 

for source specific PM2.5) 

Averaging Time: Daily filter samples

Mean: 

Crustal: 0.6 

Long-range transported: 6.4 

Oil combustion: 1.6 

Salt: 0.9 

Local traffic: 2.9 

Total: 12.8 

Percentiles: Crustal 

25: 0.0 

50: 0.4 

75: 1.1; 

Max: 5.3 

Long-range transported 

25: 2.2 

50: 5.5 

75: 9.8; 

Max: 26.5 

Oil combustion 

25: 0.6 

50: 1.3 

75: 2.3; 

Max: 12.2 

Salt 

25: 0.3 

50: 0.8 

75: 1.2; 

Max: 5.9 

Local traffic 

25: 1.7 

50: 2.5 

75: 3.4; 

Max: 12.0 

Total 

25: 8.3 

50: 10.6 

75: 15.9; 

Max: 39.8 

Monitoring Stations: 1 monitor 

Copollutant (correlation): 

Correlations with PM2.5: 

Crustal: r = -0.01 

Long-range transported: r = 0.82 

Oil combustion: r = 0.35 

Salt: r = 0.19 

Local traffic: r = 0.26 

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Adjusted ORs between daily sourcespecific PM2.5 concentrations and 

ST-segment depressions. ST-segment 

depression defined as >0.1 mV (n = 62) 

Crustal

Lag 0: 0.80 (0.47, 1.36) 

Lag 1: 0.66 (0.40, 1.10) 

Lag 2: 1.18 (0.68, 2.06) 

Lag 3: 1.87 (0.85, 4.09) 

Long-range transport 

Lag 0: 0.94 (0.84, 1.05) 

Lag 1: 1.00 (0.92, 1.08) 

Lag 2: 1.11 (1.02, 1.20) 

Lag 3: 1.06 (0.95, 1.18) 

Oil combustion 

Lag 0: 0.87 (0.57, 1.32) 

Lag 1: 1.04 (0.75, 1.45) 

Lag 2: 1.10 (0.83, 1.46) 

Lag 3: 1.12 (0.79, 1.58) 

Salt 

Lag0: 1.03 (0.57, 1.85) 

Lag1: 0.72 (0.37, 1.40) 

Lag2: 0.66 (0.31, 1.40) 

Lag3: 1.55 (0.83, 2.89) 

Local traffic 

Lag 0: 0.91 (0.69, 1.21) 

Lag 1: 1.22 (0.88, 1.69) 

Lag 2: 1.53 (1.19, 1.97) 

Lag 3: 0.98 (0.78, 1.23) 

ST-segment depression defined as >0.1 

mV with horizontal or downward slope 

(n = 46) 

Crustal 

Lag0: 0.76 (0.42, 1.35) 

Lag1: 0.41 (0.22, 0.79) 

Lag2: 1.17 (0.65, 2.09) 

Lag3: 1.60 (0.72, 3.59) 

Long-range transport 

Lag 0: 0.98 (0.86, 1.10) 

Lag 1: 1.03 (0.95, 1.12) 

Lag 2: 1.11 (1.02, 1.21) 

Lag 3: 1.02 (0.95, 1.10) 

Oil combustion 

Lag 0: 0.95 (0.61, 1.49) 

Lag 1: 1.13 (0.76, 1.68) 

Lag 2: 1.33 (0.98, 1.80) 

Lag 3: 1.29 (0.90, 1.86) 

Salt 

Lag 0: 1.15 (0.56, 2.38) 

Lag 1: 0.90 (0.44, 1.81) 

Lag 2: 1.39 (0.63, 3.08) 

Lag 3: 1.93 (1.00, 3.72) 

Local traffic 

Lag 0: 0.89 (0.64, 1.23) 

Lag 1: 1.21 (0.86, 1.71) 

Lag 2: 1.37 (1.03, 1.83) 

Lag 3: 1.03 (0.80, 1.32) 

Adjusted ORs for the association of 

indicator elements of PM2.5 sources and 

ST-segment depressions in 

multipollutant models (models include all 

5 indicator elements). ST-segment 

depression defined as >0.1 mV (n = 62) 

Si (Crustal) 

Lag0: 0.73 (0.39, 1.38) 

December 2009 E-41 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Lag1: 0.48 (0.25, 0.93) 

Lag2: 0.78 (0.35, 1.71) 

Lag3: 1.95 (0.69, 5.48) 

S (Long-range transport) 

Lag0: 0.70 (0.25, 1.95) 

Lag1: 0.58 (0.23, 1.47) 

Lag2: 1.08 (0.44, 2.63) 

Lag3: 1.60 (0.73, 3.48) 

Ni (Oil combustion) 

Lag0: 0.78 (0.30, 2.04) 

Lag1: 1.20 (0.58, 2.46) 

Lag2: 1.15 (0.61, 2.18) 

Lag3: 1.02 (0.41, 2.54) 

Cl (Salt) 

Lag0: 1.03 (0.79, 1.34) 

Lag1: 0.88 (0.56, 1.38) 

Lag2: 1.02 (0.62, 1.69) 

Lag3: 1.27 (0.85, 1.91) 

ABS (Local traffic) 

Lag0: 0.92 (0.36, 2.37) 

Lag1: 1.83 (0.73, 4.59) 

Lag2: 4.46 (1.69, 11.79) 

Lag3: 0.92 (0.40, 2.12) 

ST-segment depression defined as >0.1 

mV with horizontal or downward slope 

(n = 46) 

Si (Crustal) 

Lag0: 0.67 (0.33, 1.36) 

Lag1: 0.34 (0.15, 0.81) 

Lag2: 0.81 (0.33, 2.00) 

Lag3: 1.90 (0.64, 5.65) 

S (Long-range transport) 

Lag0: 0.84 (0.29, 2.47) 

Lag1: 0.89 (0.34, 2.32) 

Lag2: 1.36 (0.54, 3.45) 

Lag3: 1.12 (0.53, 2.40) 

Ni (Oil combustion) 

Lag0: 1.10 (0.36, 3.37) 

Lag1: 1.16 (0.45, 2.96) 

Lag2: 1.64 (0.84, 3.20) 

Lag3: 1.63 (0.64, 4.14) 

Cl (Salt) 

Lag0: 1.13 (0.80, 1.62) 

Lag1: 0.99 (0.58, 1.68) 

Lag2: 1.55 (0.87, 2.76) 

Lag3: 1.45 (0.94, 2.25) 

ABS (Local traffic) 

Lag0: 0.74 (0.25, 2.23) 

Lag1: 1.76 (0.62, 5.00) 

Lag2: 4.86 (1.55, 15.26) 

Lag3: 0.97 (0.39, 2.41) 

December 2009 E-42 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lanki et al. (2008, 191984) 

Period of Study: Jan 1999-Apr 1999 

Location: Helsinki, Finland 

Outcome: ST Segment Depressions 

>0.1 mV 

Age Groups: 50+

Study Design: Panel 

N: 41 elderly people w/ CHD 

Statistical Analyses: Logistic 

Regression Model 

Covariates: Long-term time trend, 

temperature, humidity, change in heart 

rate following exercise test 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: lags 0-24 h 

Pollutant: PM2.5 

Averaging Time: Hourly 

25th, 50th, 75th, Max: 

Personal PM2.5

1h: 6.9, 11.2, 15.8, 41.5 

4h: 5.9, 10.0, 14.6, 41.3 

8h: 5.0, 7.9, 13.0, 34.9 

12h: 5.2, 7.8, 12.1, 28.8 

22h: 6.6, 9.3, 13.0, 30.2 

Outdoor PM2.5

1h: 8.9, 12.9, 17.8, 42.9 

4h: 8.8, 12.5, 17.6, 40.8 

8h: 8.3, 12.1, 17.2, 39.2 

12h: 8.3, 11.9, 17.0, 37.0 

24 h: 9.0, 12.5, 17.7, 30.5 

Monitoring Stations: 1 

Co-pollutant: PM<0.1 

Co-pollutant Correlation 

Personal & Outdoor PM2.5

1 h & 1 h: 0.70 

4 h & 4 h: 0.54 

8 h & 8 h: 0.60 

12 h & 12 h: 0.50 

22 h & 24 h: 0.80 

Notes: 1-22 h pollutant averaging times. 

Correlations also available for personalpersonal and outdoor-outdoor. 

PM Increment: 10 μg/m3

Odds Ratio (Lower CI, Upper CI): 

Personal PM2.5

1-h avg: 3.26 (1.07, 9.99)* 

4-h avg: 2.42 (0.75, 7.83) 

8-h avg: 1.57 (0.49, 5.09) 

12-h avg: 1.96 (0.44, 8.64) 

22-h avg: 2.06 (0.30, 14.10) 

Outdoor PM2.5

1-h avg: 1.77 (0.87, 3.58) 

4-h avg: 2.47 (1.05, 5.85)* 

8-h avg: 1.83 (0.80, 4.20) 

12-h avg: 1.90 (0.77, 4.65) 

24-h avg: 1.60 (0.59, 4.39) 

*p < 0.05 

Reference: Liao et al. (2007, 180272) 

Period of Study: 1999-2004 

Location: 24 U.S. States 

Outcome: Ectopy 

Age Groups: women 50-79 yr

Study Design: Panel 

N: 57,422 

Statistical Analyses: logistic regression 

& random effects modeling 

Covariates: Age, race, center, 

education, history of CVD/chronic lung 

disease, rel. humidity, temperature, 

smoking 

Dose-response Investigated? No 

Statistical Package: SAS, Stata 

Lags Considered: lags 0-365 days 

Pollutant: PM2.5 

Averaging Time: Daily 

Mean (SD)*: 

All: 13.8 (79) 

No Ectopy: 13.8 (7.9) 

Any Ectopy: 13.8 (7.6) 

5th, 95th percentile*: 

All: 5, 29.1 

No Ectopy: 5, 29.2 

Any Ectopy: 5.06, 28.5 

Monitoring Stations: NR‡ 

Copollutant: PM10 

Co-pollutant Correlation: NR 

*Lag 1 

‡Monitors used in model for spatial 

interpolation of daily PM values. 

PM Increment: 10 μg/m3

Percent Change (Lower CI, Upper CI): 

All Ventricular Ectopy 

Lag 0: 1.01 (0.91, 1.13) 

Lag 1: 1.07 (0.96, 1.20) 

Lag 2: 1.09 (0.98, 1.21) 

Current Smoker Ventricular Ectopy 

Lag 0: 1.52 (1.04, 2.24) 

Lag 1: 2 (1.32, 3.03) 

Lag 2: 1.59 (0.99, 2.55) 

Nonsmoker Ventricular Ectopy 

Lag 0: 0.99 (0.89, 1.11) 

Lag 1: 1.05 (0.94, 1.17) 

Lag 2: 1.08 (0.97, 1.21) 

All Supraventricular Ectopy 

Lag 0: 1.04 (0.96, 1.13) 

Lag 1: 1.01 (0.93, 1.10) 

Lag 2: 0.96 (0.87, 1.05) 

All Ventricular or Supraventricular 

Ectopy 

Lag 0: 1.03 (0.96, 1.11) 

Lag 1: 1.04 (0.97, 1.11) 

Lag 2: 1 (0.94, 1.07) 

Reference: Lipsett et al. (2006, 088753) 

Period of Study: Feb-May 2000 

Location: Coachella Valley, CA 

Outcome: HRV parameters, specifically 

SDNN, SDANN, r-MSSD, LF, HF, total 

power, triangular index (TRII). 

Study Design: Panel study 

N: 19 non-smoking adults with coronary 

artery disease 

Statistical Analysis: Mixed linear 

regression models with random effects 

parameters 

Pollutant: PM2.5 

Averaging Time: 2 h 

Mean (range) 

Indio: 23.2 (6.3-90.4) 

Palm Springs: 14 (4.7-52) 

Monitoring Stations: 2 

Copollutant: O3

PM Increment: SE*100

Effect Estimate (change in HRV per 

unit increase in PM concentration): 

SDNN: -0.37 msec (SE = 1.01) 

Notes: Weekly ambulatory 24 h ECG 

recordings (once per week for up to 12 

wk), using Holter monitors, were made. 

Subjects’ residences were within 5 mi of 

1 of 2 PM monitoring sites. Decreased 

HRV was associated with PM2.5, but 

these effects were not statistically 

significant. Regressed HRV parameters 

against 18: 00-20: 00 mean particulate 

pollution. 

December 2009 E-43 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ljungman et al. (2008, 

180266) 

Period of Study: Aug 2001-Dec 2006 

Location: Stockholm, Sweden 

Outcome: Ventricular Arrhythmia 

Age Groups: 28-85 yr

Study Design: Case-crossover 

N: 88 patients w/ implantable 

cardioverter defibrillators 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, humidity, 

pressure, ischemic heart disease, 

ejection fraction, heart disease, 

diabetes, use of beta-blockers, age, 

BMI, location at time of arrhythmia, 

distance from air pollution monitor 

Dose-response Investigated? No 

Statistical Package: Stata, S-plus 

Lags Considered: lags 2-24 h 

Pollutant: PM2.5

Averaging Time: Hourly 

Median: 

2 h: 9.17 

24 h: 9.49 

Min: 

2 h: 0.15 

24 h: 2.97 

Max: 

2 h: 99.25 

24 h: 47.07 

IQR: 

2 h: 6.69 

24 h: 5.27 

Monitoring Stations: 1 

Copollutant: PM10, NO2

Co-pollutant Correlation: NR 

PM Increment: Interquartile Range 

Odds Ratio (Lower CI, Upper CI): 

2 h: 1.23 (0.84, 1.80) 

24 h: 1.28 (0.90, 1.84) 

Notes: OR of ventricular arrhythmia for 

an IQR increase of air pollutants in 

different subgroups (Fig 2) 

Reference: Ljungman et al. (2009, 

191983) 

Period of Study: May 2003-Jul 2004 

Location: Athens, Greece 

Helsinki, Finland 

Ausburg, Germany 

Barcelona, Spain 

Rome, Italy 

Stokholm, Sweeden 

Outcome: Interleukin-6 Response 

Age Groups: 35-80 yr 

Study Design: Panel 

N: 955 male myocardial infarction 

survivors 

Statistical Analyses: Additive Mixed 

Models 

Covariates: Age, sex, BMI, city, 

HDL/total cholesterol, smoking, alcohol 

intake, HbA1c, NT-proBNP, history of MI, 

heart failure, or diabetes, phlegm 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1 day 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean: 17.7 

25th: 10.9 

75th: 21.9 

Monitoring Stations: NR 

Copollutant: CO, NO2, PNC, PM2.5

Co-pollutant Correlation: 

PM10: 0.81 

PM Increment: Interquartile Range 

(11.0 μg/m3

) 

Change of IL-6 (Lower CI, Upper CI), 

p-value: 

0.6 (-0.8, 2.0), 0.40 

Reference: Luttman-Gibson et al. 

(2006, 089794) 

Period of Study: Jun-Dec 2000 

Location: Steubenville, OH 

Outcome: Heart rate variability 

Age Groups: 

Study Design: Panel study 

N: 32 participants 

Statistical Analysis: Linear mixed 

models 

Pollutant: PM2.5 

Averaging Time: 

1 h 

24 h 

Mean (IQR) 

PM2.5: 20.0 (15.2) 

Sulfate: 6.9 (5.1) 

EC: 1.1 (0.6) 

Copollutant: NO2, SO2, O3

PM Increment: IQR

Percent change (95% CI): Each 

13.4 μg/m3

 increase in 24 h mean PM2.5

concentration was associated with: 

SDNN: -4.0% (95% CI: -7.0% to -0.9%) 

r-MSSD: -6.5% (95% CI: -12.1% to 

-0.6%) 

HF: -11.4% (95% CI: -21.5% to -0.1%)

Each 5.1 μg/m3 increase in sulfates on 

the previous day was associated with: 

SDNN: -3.3% (95% CI: -6.0% to -0.5%) 

r-MSSD: -5.6% (95% CI: -10.7%, 0.2%) 

HF: -10.3% (95% CI: -19.5% to -0.1%) 

Notes: The authors conclude that 

increases in both traffic related particles 

and sulfates may adversely effect 

autonomic function.

December 2009 E-44 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mar et al. (2005, 087566) 

Period of Study: 1999-2001 

Location: Seattle, WA 

Outcome: Change in arterial O2

saturation, heart rate, and blood 

pressure (SBP and DBP) 

Age Groups: >75 yr 

Study Design: Panel study 

N: 88 elderly subjects 

Statistical Analysis: GEE 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 

Personal: 9.3(8.4) 

Indoor: 7.4 (4.8) 

Outdoor: 9.0 (4.6) 

PM Increment: 10 μg/m3

Unit change in measure (95% CI): 

Among all subjects: Each increase in 

outdoor same day PM2.5 was associated 

with: SBP: -0.81 mmHg (95% CI: -2.34, 

0.73) 

DBP: -0.46 mmHg (95% CI: -1.49 to 

0.57) 

H: -0.75 beats/min (95% CI: -1.42 to 

-0.07)

Each increase in indoor same day PM2.5

was associated with: SBP: 0.92 mmHg 

(95% CI: -2.04 to 3.87) 

DBP: 0.38 mmHg (95% CI: -1.43 to 

2.20) 

H: 0.22 beats/min (95% CI: -0.71 to 

1.16) 

Each increase in personal same day 

PM2.5 was associated with: SBP: 0.37 

mmHg (95% CI: -0.93 to 1.67) 

DBP: -0.20 mmHg (95% CI: -0.85 to 

0.46) 

H: 0.44 beats/min (95% CI: 0.04 to 0.84) 

Notes: Results by health status 

presented in Fig 1 

Used 2 sessions that each were 10 

consecutive days of measurements 

Used personal, indoor, and outdoor 

measures of PM2.5

Reference: Metzger et al. (2007, 

092856) 

Period of Study: Aug 1998-Dec 2002 

Location: Atlanta, GA 

Outcome: Days with any event 

recorded by the ICD, days with ICD 

shocks/defibrillation and days with either 

cardiac pacing or defibrillation 

Study Design: Repeated measures 

N: 884 subjects between 1993 and 2002

Statistical Analysis: Logistic regression 

with GEE to account for residual 

autocorrelation within subjects 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 

PM2.5: 17.8 (8.6) 

PM2.5 sulfates: 5.0 (3.4) 

PM2.5 EC: 1.7 (1.2) 

PM2.5 OC: 4.4 (2.4) 

PM2.5 water-soluble metals: 0.029 

(0.024) 

Percentiles: 

PM2.5: Median: 16.2 

PM2.5 sulfates: Median: 4.1 

PM2.5 EC: Median: 1.4 

PM2.5 OC: Median: 3.9 

PM2.5 water-soluble metals: 

Median: 0.022 

Copollutant: 

O3

NO2

CO 

SO2

Oxygenated hydrocarbons 

PM Increment: OR (95% CI): 

Outcome = Any event recorded by ICD 

PM2.5

OR = 1.00 

(95% CI: 0.95, 1.04) 

PM2.5 EC 

OR = 1.01 

(95% CI: 0.98, 1.05) 

PM2.5 OC 

OR = 1.01 

(95% CI: 0.98, 1.03) 

PM2.5 Sulfates 

OR = 0.99 

(95% CI: 0.93, 1.06) 

PM2.5 Water soluble metals 

OR = 0.95 

(95% CI: 0.90, 1.00 

Reference: O'Neill et al. (2007, 091362) 

Period of Study: May 1998-Dec 2002 

Location: Boston, MA 

Outcome: Soluble intercellular adhesion 

molecule 1 (ICAM-1) 

Vascular cell adhesion molecule 1 

(VCAM-1) 

von Willebrand factor (vWF) 

Age Groups: Mean (SD): 56.6 (10.6) 

Study Design: Cross-sectional 

N: 92 participants (type 2 diabetic 

patients) 

Pollutant: PM2.5 

Averaging Time: 24 h (lagged ma of 

days 0 to 1, 2, 3, 4, and 5) 

Mean (SD): 11.4 (5.9) 

Descriptive statistics represent entire 

study period 

Percentiles: IQR range: 7.6 

Range (Min, Max): 0.07, 33.7) 

PM Increment: IQR (specific to lag 

period)

Effect Estimate [Lower CI, Upper CI]: 

% change per IQR of PM2.5

ICAM-1 - All subjects 

Lag 0: 2.87 (-4.63, 10.95) 

2 dma: 2.25 (-5.15, 10.22) 

3 dma: 1.48 (-5.63, 9.11) 

4 dma: 1.80 (-4.98, 9.07) 

5 dma: 1.51 (-5.30, 8.80) 

6 dma: 2.12 (-4.23, 8.89) 

December 2009 E-45 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Statistical Analyses: linear regression 

Covariates: Apparent temperature, 

season, age, race, sex, glycosylated 

hemoglobin, cholesterol, smoking 

history, BMI 

Dose-response Investigated? No 

Statistical Package: NR 

Monitoring Stations: 1 site 

Copollutant: 

PM2.5

BC 

SO4

2–

Subjects not known to be taking 

statins

Lag 0: 5.47 (-3.74, 15.57) 

2 dma: 5.70 (-3.70, 16.01) 

3 dma: 4.57 (-4.31, 14.27) 

4 dma: 4.57 (-4.27, 14.23) 

5 dma: 3.80 (-4.84, 13.22) 

6 dma: 3.79 (-4.49, 12.80) 

Subjects who report smoking in the 

past (but not within 6 mo)

Lag 0: 0.9 (-9.56, 12.66) 

2 dma: 0.40 (-12.08, 14.65) 

3 dma: 1.34 (-9.23, 13.14) 

4 dma: 2.29 (-6.84, 12.30) 

5 dma: 1.09 (-8.30, 11.44) 

6 dma: 3.08 (-6.30, 13.40); 

Subjects who did not report smoking 

in the past 

Lag 0: 0.46 (-8.23, 9.97) 

2 dma: 1.37 (-7.96, 11.65) 

3 dma: -0.96 (-10.01, 9.00) 

4 dma: -1.34 (-10.35, 8.58) 

5 dma: -0.87 (-10.17, 9.40) 

6 dma: -1.78 (-10.64, 7.94) 

VCAM-1 - All subjects 

Lag 0: 6.88 (-2.88, 17.62) 

2 dma: 8.18 (-1.43, 18.72) 

3 dma: 6.92 (-1.66, 16.25) 

4 dma: 6.46 (-1.16, 14.66) 

5 dma: 8.57 (0.05, 17.80) 

6 dma: 11.76 (3.48, 20.70) 

Subjects not known to be taking 

statins

Lag 0: 10.26 (-0.64, 22.35) 

2 dma: 15.02 (3.76, 27.49) 

3 dma: 14.59 (3.94, 26.34) 

4 dma: 15.15 (4.54, 26.84) 

5 dma: 16.16 (5.77, 27.58) 

6 dma: 17.66 (7.77, 28.45) 

Subjects who report smoking in the 

past (but not within 6 mo) 

Lag 0: 13.2 (-1.30, 29.72) 

2 dma: 18.4 (0.69, 39.33) 

3 dma: 15.7 (1.19, 32.30) 

4 dma: 13.1 (0.88, 26.78) 

5 dma: 13.2 (0.49, 27.58) 

6 dma: 16.2 (3.76, 30.10) 

Subjects who did not report smoking 

in the past

Lag 0: -3.12 (-12.41, 7.17) 

2 dma: -0.34 (-10.57, 11.05) 

3 dma: -1.09 (-11.15, 10.12) 

4 dma: -0.81 (-10.91, 10.43) 

5 dma: 2.07 (-8.59, 13.96) 

6 dma: 4.89 (-5.56, 16.50) 

vWF - All subjects 

Lag 0: 15.16 (-9.79, 47.01) 

2 dma: 12.57 (-9.19, 39.55) 

3 dma: 25.14 (-9.87, 73.74) 

4 dma: 23.42 (-9.47, 68.25) 

5 dma: 17.92 (-10.22, 54.87) 

6 dma: 20.48 (-8.82, 59.22) 

Subjects not known to be taking 

statins

Lag 0: 7.40 (-19.82, 43.88) 

2 dma: 7.10 (-19.09, 41.76) 

3 dma: 10.78 (-17.92, 49.52) 

4 dma: 11.61 (-16.64, 49.42) 

5 dma: 9.15 (-20.32, 49.53) 

6 dma: 7.91 (-20.70, 46.85) 

Subjects who report smoking in the 

December 2009 E-46 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

past (but not within 6 mo) 

Lag 0: 19.23 (-24.29, 87.77) 

2 dma: 19.92 (-29.65,104.41) 

3 dma: 29.54 (-17.24, 102.76) 

4 dma: 41.98 (-6.95, 116.63) 

5 dma: 44.05 (-1.23, 110.07) 

6 dma: 50.39 (9.35, 106.82) 

Subjects who did not report smoking 

in the past 

 Lag 0: -14.21 (-53.20, 57.24) 

2 dma: -20.66 (-63.14, 70.77) 

3 dma: -28.89 (-68.43, 60.19) 

4 dma: -23.51 (-55.11, 30.34) 

5 dma: -29.18 (-60.08, 25.66) 

6 dma: -30.68 (-55.95, 9.08) 

Reference: O'Neill et al. (2007, 091362) 

Period of Study: May 1998-Dec 2002 

Location: Boston, MA 

Outcome: Soluble intercellular adhesion 

molecule 1 (ICAM-1) 

Vascular cell adhesion molecule 1 

(VCAM-1) 

von Willebrand factor (vWF) 

Age Groups: Mean (SD): 56.6 (10.6) 

Study Design: Cross-sectional 

N: 92 participants (type 2 diabetic 

patients) 

Statistical Analyses: Linear regression 

Covariates: Apparent temperature, 

season, age, race, sex, glycosylated 

hemoglobin, cholesterol, smoking 

history, BMI 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: BC 

Averaging Time: 24 h (lagged ma of 

days 0 to 1, 2, 3, 4, and 5) 

Mean (SD): 1.1 (0.8) 

descriptive statistics represent entire 

study period 

Percentiles: IQR range: 0.8 

Range (Min, Max): 0.2, 5.8 

Monitoring Stations: 1 site 

Copollutant: 

PM2.5

BC 

SO4

2–

PM Increment: IQR (specific to lag 

period)

Effect Estimate [Lower CI, Upper CI]: 

% change per IQR of BC 

ICAM-1- -All subjects 

Lag 0: 5.09 (-2.37, 13.11) 

2 dma: 3.97 (-10.24, 20.42) 

3 dma: 5.10 (-10.17, 22.96) 

4 dma: 8.38 (-6.46, 25.56) 

5 dma: 10.09 (-7.36, 30.83) 

6 dma: 10.58 (-5.34, 29.18)

Subjects not known to be taking 

statins 

Lag 0: 5.77 (-3.92, 16.44) 

2 dma: 2.39 (-7.65, 13.52) 

3 dma: 0.84 (-8.16, 10.73) 

4 dma: 1.67 (-6.71, 10.80) 

5 dma: 1.55 (-6.46, 10.24) 

6 dma: 2.20 (-6.47, 11.68) 

Subjects who report smoking in the 

past (but not within 6 mo) 

Lag 0: 5.84 (0.87, 11.05) 

2 dma: 5.08 (-2.34, 13.07) 

3 dma: 4.44 (-2.70, 12.11) 

4 dma: 5.02 (-1.78, 12.29) 

5 dma: 5.89 (-2.14, 14.58) 

6 dma: 6.73 (-1.54, 15.70) 

Subjects who did not report smoking 

in the past 

Lag 0: 6.04 (0.87, 11.48) 

2 dma: 6.54 (-1.64, 15.39) 

3 dma: 5.86 (-1.90, 14.22) 

4 dma: 6.11 (-1.18, 13.94) 

5 dma: 6.89 (-1.42, 15.89) 

6 dma: 7.86 (-1.35, 17.94) 

VCAM-1 - All subjects 

Lag 0: 9.26 (2.98, 15.91) 

2 dma: 10.18 (1.93, 19.10) 

3 dma: 15.45 (2.70, 29.78) 

4 dma: 17.97 (3.63, 34.30) 

5 dma: 23.83 (8.41, 41.44) 

6 dma: 27.51 (11.96, 45.21)

Subjects not known to be taking 

statins 

Lag 0: 9.19 (3.23, 15.49) 

2 dma: 14.64 (5.02, 25.14) 

3 dma: 14.39 (5.30, 24.28) 

4 dma: 14.19 (5.71, 23.36) 

5 dma: 19.11 (9.44, 29.65) 

6 dma: 22.60 (11.79, 34.45) 

Subjects who report smoking in the 

past (but not within 6 mo)

Lag 0: 12.4 (2.77, 22.92) 

2 dma: 28.5 (8.38, 52.24) 

3 dma: 25.14 (3.50, 51.30) 

4 dma: 23.1 (2.70, 47.58) 

December 2009 E-47 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

5 dma: 32.0 (7.29, 62.30) 

6 dma: 31.8 (9.74, 58.26) 

Subjects who did not report smoking 

in the past 

Lag 0: 5.15 (-5.63, 17.17) 

2 dma: 2.09 (-9.07 ,14.61) 

3 dma: 3.90 (-6.38, 15.31) 

4 dma: 4.92 (-4.63, 15.43) 

5 dma: 7.89 (-1.31, 17.95) 

6 dma: 10.97 (0.98, 21.96) 

vWF- All subjects 

Lag 0: 7.96 (-4.34, 21.84) 

2 dma: 14.87 (-2.85, 35.82) 

3 dma: 15.34 (-3.22, 37.45) 

4 dma: 15.47 (-7.60, 44.31) 

5 dma: 19.50 (-8.89, 56.74) 

6 dma: 20.53 (-9.80, 61.05)

Subjects not known to be taking 

statins 

Lag 0: 3.23 (-8.91, 17.00) 

2 dma: 9.82 (-8.39, 31.66) 

3 dma: 17.79 (-16.03, 65.21) 

4 dma: 13.14 (-18.71, 57.47) 

5 dma: 16.14 (-20.43, 69.52) 

6 dma: 13.25 (-22.09, 64.62) 

Subjects who report smoking in the 

past (but not within 6 mo)

Lag 0: 7.63 (-17.01, 39.58) 

2 dma: 37.64 (-7.18, 104.10) 

3 dma: 75.41 (6.16, 189.85) 

4 dma: 72.05 (-3.34, 206.22) 

5 dma: 73.14 (6.94, 180.32) 

6 dma: 71.23 (14.00, 157.19) 

Subjects who did not report smoking 

in the past 

Lag 0: 10.22 (-23.14, 58.04) 

2 dma: 17.07 (-18.86, 68.91) 

3 dma: 6.56 (-42.75, 98.36) 

4 dma: -9.20 (-65.79, 140.99) 

5 dma: -23.86 (-71.05, 100.29) 

6 dma: -48.69 (-77.75, 18.29) 

Reference: O'Neill et al. (2005, 088423)

Period of Study: 

Baseline period: May 1998-Jan 2000 

Time trial: 2000-2002 

Location: Boston, MA 

Outcome: Changes in vascular 

reactivity, specifically percent change in 

brachial artery diameter (flow-mediated 

and nitroglycerin-mediated)

N: 270 patients with diabetes or at risk of 

diabetes, who participated in non-air 

pollution related studies at the Joselyn 

Diabetes Center in Boston 

Statistical Analysis: Linear regression 

Pollutant: PM2.5

Mean (SD): 11.5 (6.4) 

Range: 1.1-40.0 

Monitoring Stations: 1 

Copollutant: 

Sulfates 

BC 

Ultrafine particle counts 

PM Increment: IQR (value not given)

Percent change (95% CI): PM2.5 6-day 

ma 

Nitroglycerin-mediated reactivity: -7.6% 

(95% CI: 12.8% to -2.1%) 

Notes: PM2.5 was positively associated 

with nitroglycerin-mediated reactivity 

an association was also reported with 

ultrafine particles. Effect estimates were 

larger in type II than type I diabetes. BC 

and sulfate increases were associated 

with decreased flow-mediated reactivity 

among those with diabetes. Although the 

largest associations were with the 6-day 

ma, similar patterns and quantitatively 

similar results appear in the other lags.

December 2009 E-48 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: O'Neill et al. (2007, 091362) 

Period of Study: May 1998-Dec 2002 

Location: Boston, MA 

Outcome: soluble intercellular adhesion 

molecule 1 (ICAM-1) 

vascular cell adhesion molecule 1 

(VCAM-1) 

von Willebrand factor (vWF) 

Mean Age: 56.6 (10.6) 

Study Design: Cross-sectional 

N: 92 participants (type 2 diabetic 

patients) 

Statistical Analyses: Linear regression 

Covariates: Apparent temperature, 

season, age, race, sex, glycosylated 

hemoglobin, cholesterol, smoking 

history, BMI 

Dose-response Investigated? No 

Statistical Package: NR

Pollutant: SO4

2– 

Averaging Time: 24 h (lagged ma of 

days 0 to 1, 2, 3, 4, and 5) 

Mean (SD): 3.0 (2.0) 

descriptive statistics represent entire 

study period 

Percentiles: IQR range: 2.2 

Range (Min, Max): 0.5, 9.6) 

Monitoring Stations: 1 site 

Copollutant: PM2.5, BC, SO4

2–

PM Increment: IQR (specific to lag 

period)

Effect Estimate [Lower CI, Upper CI]: 

% change per IQR of PM2.5

ICAM-1 All subjects 

Lag 0: 5.30 (-2.60, 13.83) 

2 dma: 4.02 (-3.26, 11.85) 

3 dma: 4.03 (-5.34, 14.34) 

4 dma: -0.79 (-7.30, 6.18) 

5 dma: 1.06 (-7.10, 9.93) 

6 dma: 3.15 (-5.66, 12.78) 

Subjects not known to be taking 

statins 

Lag 0: 10.14 (0.44, 20.77) 

2 dma: 9.39 (-1.28, 21.20) 

3 dma: 10.93 (-2.23, 25.85) 

4 dma: -0.24 (-9.66, 10.16) 

5 dma: 4.03 (-8.66, 18.47) 

6 dma: 5.66 (-7.52, 20.72) 

Subjects who report smoking in the 

past (but not within 6 mo)

Lag 0: -4.00 (-24.79, 22.52) 

2 dma: -4.82 (-18.01, 10.48) 

3 dma: -7.19 (-23.66, 12.83) 

4 dma: -9.8 (-27.96, 12.97) 

5 dma: -10.4 (-29.92, 14.44) 

6 dma: -6.8 (-25.72, 17.03) 

Subjects who did not report smoking 

in the past

Lag 0: 6.67 (-4.34, 18.94) 

2 dma: 5.65 (-4.67, 17.10) 

3 dma: 10.21 (-5.83, 28.99) 

4 dma: 0.80 (-9.94, 12.83) 

5 dma: 2.80 (-10.85, 18.54) 

6 dma: 5.15 (-7.78, 19.89) 

VCAM-1 All subjects 

Lag 0: -0.04 (-3.75, 3.80) 

2 dma: 0.94 (-4.79, 7.01) 

3 dma: -0.87 (-3.50, 1.82) 

4 dma: 0.13 (-2.02, 2.34) 

5 dma: -0.47 (-2.67, 1.78) 

6 dma: -0.46 (-1.99, 1.09) 

Subjects not known to be taking 

statins

Lag 0: -1.34 (-11.23, 9.66) 

2 dma: -0.19 (-11.13, 12.09) 

3 dma: -2.84 (-13.90, 9.64) 

4 dma: 4.28 (-6.18, 15.90) 

5 dma: -0.26 (-13.44, 14.93) 

6 dma: -3.44 (-16.51, 11.67) 

Subjects who report smoking in the 

past (but not within 6 mo)

Lag 0: 0.07 (-23.40, 30.73) 

2 dma: -5.62 (-20.77, 12.43) 

3 dma: -26.92 (-33.31 to -19.91) 

4 dma: -3.06 (-28.01,30.56) 

5 dma: -6.42 (-30.75, 26.47) 

6 dma: -6.46 (-28.55, 22.47) 

Subjects who did not report smoking 

in the past 

Lag 0: -3.28 (-12.66, 7.12) 

2 dma: -3.17 (-11.75, 6.23) 

3 dma: -9.67 (-22.07, 4.70) 

4 dma: -5.51 (-14.28, 4.15) 

5 dma: -12.17 (-22.05 to -1.05) 

6 dma: -11.77 (-20.95 to -1.52) 

vWF (sulfate measures not available) 

December 2009 E-49 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Park et al. (2008, 156845) 

Period of Study: Jan 1995-Jun 2005 

Location: Greater Boston area, MA 

Outcome: Total homocysteine (tHcy) 

Mean Age: 73.6 ± 6.9 yr

Study Design: Cross-sectional and 

longitudinal analyses performed 

N: 960 men 

Statistical Analyses: Generalized 

additive models (also hierarchical mixedeffects regression models to assess 

repeated measures of tHcy) 

Covariates: Model 1: season, age, longterm trend, apparent temperature 

Model 2: further adjustment for BMI, 

systolic blood pressure, smoking status, 

pack yr of cigarettes, alcohol consumption 

Model 3: further adjustment for serum 

creatinine, plasma folate, vitamin B6, 

and vitamin B12 

Dose-response Investigated? Modeled 

continuous covariates as penalized 

splines to determine if association with 

tHcy was linear 

Statistical Package: R software 

Pollutant: PM2.5 

Averaging Time: 24 h (ma up to 7 days 

prior to blood collection) 

Mean (SD): 12.0 (6.6) 

Median: 10.6 

Range (Min, Max): 2.0, 62.0 

Monitoring Stations: 1 site 

Copollutant: 

PM2.5 

BC (r = 0.51) 

OC (r = 0.51) 

SO4

2– (r = 0.85) 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

Estimated % change in tHcy per IQR 

increase in pollutant. 

Lag model 

Concurrent day. IQR: 7.66 

Model 1: 1.32 (-0.83, 3.52) 

Model 2: 1.55 (-0.77, 3.91) 

Model 3: 1.57 (-0.38, 3.56) 

1-day previous. IQR: 6.91 

Model 1: -1.43 (-3.51, 0.69) 

Model 2: -1.41 (-3.53, 0.76) 

Model 3: -1.28 (-3.12, 0.60) 

2-day ma. IQR: 6.47 

Model 1: 0.04 (-2.13, 2.26) 

Model 2: -0.07 (-2.26, 2.17) 

Model 3: 0.25 (-1.69, 2.22) 

3-day ma. IQR: 5.83 

Model 1: -0.64 (-2.92, 1.69) 

Model 2: -0.74 (-3.04, 1.61) 

Model 3: -0.59 (-2.63, 1.49) 

4-day ma. IQR: 5.21 

Model 1: -0.63 (-2.94, 1.72) 

Model 2: -0.86 (-3.19, 1.52) 

Model 3: -0.73 (-2.78, 1.37) 

5-day ma. IQR: 4.68 

Model 1: -0.51 (-2.79, 1.83) 

Model 2: -0.82 (-3.13, 1.54) 

Model 3: -0.84 (-2.85, 1.22) 

6-day ma. IQR: 4.50 

Model 1: -0.91 (-3.32, 1.56) 

Model 2: -1.32 (-3.76, 1.17) 

Model 3: -1.44 (-3.58, 0.74) 

7-day ma. IQR: 4.20 

Model 1: -0.84 (-3.27, 1.64) 

Model 2: -1.19 (-3.64, 1.33) 

Model 3: -1.69 (-3.84, 0.51) 

Stratified analyses: No significant 

difference in effect of PM2.5 among those 

with high and low levels of vitamins 

December 2009 E-50 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Park et al. (2008, 156845) 

Period of Study: Jan 1995-Jun 2005 

Location: Greater Boston area, MA 

Outcome: Total homocysteine (tHcy) 

Mean Age: 73.6 ± 6.9 yr

Study Design: cross-sectional and 

longitudinal analyses performed 

N: 960 men 

Statistical Analyses: Generalized 

additive models (also hierarchical mixedeffects regression models to assess 

repeated measures of tHcy) 

Covariates: Model 1: season, age, longterm trend, apparent temperature 

Model 2: further adjustment for BMI, 

systolic blood pressure, smoking status, 

pack yr of cigarettes, alcohol 

consumption 

Model 3: further adjustment for serum 

creatinine, plasma folate, vitamin B6, 

and vitamin B12 

Dose-response Investigated? Modeled 

continuous covariates as penalized 

splines to determine if association with 

tHcy was linear 

Statistical Package: R software 

Pollutant: BC 

Averaging Time: 24 h (ma up to 7 days 

prior to blood collection) 

Mean (SD): 0.99 (0.56) 

Median: 0.87 

Range (Min, Max): 0.07, 3.7 

Monitoring Stations: 1 site 

Copollutant 

(correlation): 

PM2.5 (r = 0.51) 

BC 

OC (r = 0.0.51) 

SO4

2– (r = 0.50) 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

Estimated % change in tHcy per IQR 

increase in pollutant. 

Lag model Concurrent day. IQR: 0.66 

Model 1: 2.64 (-0.12, 5.48) 

Model 2: 2.62 (-0.17, 5.48) 

Model 3: 3.13 (0.76, 5.55) 

1-day previous. IQR: 0.66 

Model 1: 1.46 (-0.98, 3.96) 

Model 2: 1.32 (-1.14, 3.85) 

Model 3: 0.95 (-1.12, 3.05) 

2-day ma. IQR: 0.60 

Model 1: 2.75 (-0.18, 5.76) 

Model 2: 2.63 (-0.33, 5.67) 

Model 3: 2.59 (0.10, 5.14) 

3-day ma. IQR: 0.57 

Model 1: 2.95 (-0.44, 6.46) 

Model 2: 2.97 (-0.46, 6.51) 

Model 3: 3.12 (0.21, 6.11) 

4-day ma. IQR: 0.52 

Model 1: 3.94 (0.24, 7.78) 

Model 2: 3.76 (0.02, 7.64) 

Model 3: 3.00 (-0.13, 6.22) 

5-day ma. IQR: 0.49 

Model 1: 3.26 (-0.60, 7.27) 

Model 2: 2.64 (-1.23, 6.67) 

Model 3: 2.38 (-0.89, 5.77) 

6-day ma IQR: 0.44 

Model 1: 1.63 (-1.99, 5.38) 

Model 2: 1.03 (-2.62, 4.80) 

Model 3: 0.93 (-2.15, 4.11) 

7-day ma. IQR: 0.44 

Model 1: 1.38 (-2.45, 5.36) 

Model 2: 0.69 (-3.16, 4.70) 

Model 3: 0.45 (-2.81, 3.83) 

% change in tHcy per IQR increase in 

BC, 24-h avg 

Among those with low folate: 5.31 (2.26, 

8.42) 

Among those with low B12: 5.06 (2.03, 

8.17) 

nearly null associations among those 

with high levels 

December 2009 E-51 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Park et al. (2008, 156845) 

Period of Study: Jan 1995-Jun 2005 

Location: Greater Boston area, MA 

Outcome: Total homocysteine (tHcy) 

Mean Age: 73.6 ± 6.9 yr

Study Design: Cross-sectional and 

longitudinal analyses performed 

N: 960 men 

Statistical Analyses: Generalized 

additive models (also hierarchical mixedeffects regression models to assess 

repeated measures of tHcy) 

Covariates: Model 1: season, age, longterm trend, apparent temperature 

Model 2: further adjustment for BMI, systolic blood pressure, smoking status, 

pack yr of cigarettes, alcohol consumption 

Model 3: further adjustment for serum 

creatinine, plasma folate, vitamin B6, 

and vitamin B12 

Dose-response Investigated? Modeled 

continuous covariates as penalized 

splines to determine if association with 

tHcy was linear 

Statistical Package: R software 

Pollutant: OC 

Averaging Time: 24 h (ma up to 7 days 

prior to blood collection) 

Mean (SD): 3.5 (1.8) 

Median: 3.1 

Range (Min, Max): 0.29, 11.8 

Monitoring Stations: 1 site 

Copollutant (correlation): 

PM2.5 (r = 0.51) 

BC (r = 0.51) 

OC 

SO4

2– (r = 0.41) 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

Estimated % change in tHcy per IQR 

increase in pollutant. 

Lag model 

Concurrent day. IQR: NA 

Model 1: NA 

Model 2: NA 

Model 3: NA 

1-day previous. IQR: 2.00 

Model 1: 2.12 (-0.98, 5.31) 

Model 2: 1.69 (-1.51, 5.00) 

Model 3: 1.87 (-0.81, 4.62) 

2-day ma. IQR: 1.93 

Model 1: -0.39 (-3.67, 3.01) 

Model 2: -0.88 (-4.26, 2.61) 

Model 3: 1.05 (-1.86, 4.06) 

3-day ma. IQR: 1.68 

Model 1: 0.53 (-2.66, 3.83) 

Model 2: 0.14 (-3.15, 3.54) 

Model 3: 1.32 (-1.44, 4.16) 

4-day ma. IQR: 1.64 

Model 1: 1.57 (-1.89, 5.15) 

Model 2: 1.42 (-2.14, 5.12) 

Model 3: 1.89 (-1.15, 5.03) 

5-day ma, IQR: 1.60 

Model 1: 2.27 (-1.49, 6.16) 

Model 2: 2.11 (-1.77, 6.15) 

Model 3: 2.12 (-1.29, 5.65) 

6-day ma. IQR: 1.43 

Model 1: 2.83 (-0.74, 6.52) 

Model 2: 2.78 (-0.90, 6.60) 

Model 3: 2.53 (-0.59, 5.74) 

7-day ma. IQR: 1.23 

Model 1: 2.75 (-0.41, 6.02) 

Model 2: 2.55 (-0.71, 5.92) 

Model 3: 2.55 (-0.21, 5.39) 

% change in tHcy per IQR increase in 

OC, 7-day avg. 

Among those with low B12: 5.23 (1.59, 

9.01) 

Nearly null associations among those 

with high levels 

December 2009 E-52 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Park et al. (2005, 057331) 

Period of Study: Nov 2000-Oct 2003 

Location: Greater Boston area, MA 

Outcome: Change in HRV (SDNN, HF, 

LF, LFHFR) 

Mean age: 72.7 yr

Study Design: Cross-sectional 

N: 497 adult males living in the Greater 

Boston, MA area 

Pollutant: PM2.5 

Averaging Time: 

4 h 

24 h 

48 h 

Mean (SD): 11.4 (8.0) 

Range: 6.45-62.9 

Copollutant: 

O3, Particle number count, BC, NO2, 

SO2, CO 

PM Increment: 8 μg/m3

Percent change (95% CI): 48h mean 

PM2.5: 20.8% decrease in HF (95% CI: 

4.6%, 34.2%) 

18.6% increase in LFHFR (4.1%, 

35.2%). 

Notes: Subjects were monitored during 

a 4-min rest period between 8 a.m. and 

1 p.m. Modifying effects of hypertension, 

IHD, diabetes, and use of cardiac/antihypertensive medications also 

examined. Linear regression analyses. 

This subject group is from the VA 

Normative Aging Study. The 4-h 

averaging period was most strongly 

associated with HRV indices. The PM 

effect was robust in models including O3. 

The HRV change per IQR increase in 

PM2.5 were larger in subjects with 

hypertension (n = 335) IHD (n = 142), 

and diabetes (n = 72). In addition, those 

who did not use calcium-channel 

blockers had a greater decline in LF 

associated with each IQR increase in 

PM2.5 than did those who did use 

calcium channel blockers. IQR increases 

in 48h mean BC concentration were also 

associated with adverse changes in 

HRV, suggesting traffic pollution may be 

particularly toxic. 

Reference: Park et al. (2006, 091245) 

Period of Study: Nov 2000-Dec 2004 

Location: Greater Boston area, MA 

Outcome: Change in HF 

Study Design: Cross-sectional 

N: Statistical Analysis: Linear 

regression models 

Pollutant: PM2.5 

Averaging Time: 48 h 

Mean (SD): 

PM2.5: 11.7 (7.8) 

Sulfates: 3.3 (3.3) 

BC: 0.92 (0.46) 

Copollutant: O3

PM Increment: 10 μg/m3

Percent change (95% CI): Wild-type 

HFE genotype: 31.7% (95% CI: 10.3, 

48.1) 

Among those with either of the 2 HFE 

variants, there was no association 

between 48h PM2.5 and HF (shown in a 

graph, ~10% non-significant increase). 

Notes: Normative Aging Study. 

Examining association between PM and 

HF among those with and without the 

wild-type HFE genotype. 

Reference: Pekkanen et al. (2002, 

035050) 

Period of Study: Winter 1998-1999 

Location: Helsinki, Finland 

Outcome: ST-Segment Depression 

(>0.1mV) 

Study Design: Panel of ULTRA Study 

participants 

N: 45 Subjects, n = 342 biweekly 

submaximal exercise tests, 72 exercise 

induced ST Segment Depressions 

Statistical Analysis: Logistic regression 

/ GAM 

Pollutant: PM2.5 

Averaging Time: 24 h 

Median: 10.6 

IQR: 7.9 

Pollutant: PM1 

Median: 7.0 

IQR: 5.6 

Pollutant: ACP (100 to 1000nm) (n/cm3)

Median: 1200 

IQR: 760 

Copollutant: NO2, CO, PM10-2.5, ultrafine

PM Increment: IQR 

Effect Estimate(s): ACP: OR = 3.29 

(1.57, 6.92), lag 2 

PM1: OR = 4.56 (1.73, 12.03), lag 2 

PM2.5: OR = 2.84 (1.42, 5.66), lag 2 

Notes: The effect was strongest for ACP 

and PM2.5, which in 2 pollutant models 

appeared independent. Increases in NO2

and CO were also associated with 

increased risk of ST-segment 

depression, but not with coarse particles.

December 2009 E-53 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Park et al. (2008, 156845) 

Period of Study: Jan 1995-Jun 2005 

Location: Greater Boston area, MA 

Outcome: Total homocysteine (tHcy) 

Mean Age: 73.6 ± 6.9 yr

Study Design: Cross-sectional and 

longitudinal analyses performed 

N: 960 men 

Statistical Analyses: Generalized 

additive models (also hierarchical mixedeffects regression models to assess 

repeated measures of tHcy) 

Covariates: Model 1: season, age, longterm trend, apparent temperature 

Model 2: further adjustment for BMI, 

systolic blood pressure, smoking status, 

pack yr of cigarettes, alcohol consumption 

Model 3: further adjustment for serum 

creatinine, plasma folate, vitamin B6, 

and vitamin B12 

Dose-response Investigated? Modeled 

continuous covariates as penalized 

splines to determine if association with 

tHcy was linear 

Statistical Package: R software 

Pollutant: SO4

2–

Averaging Time: 24 h (ma up to 7 days 

prior to blood collection) 

Mean (SD): 3.2 (3.0) 

Median: 2.4 

Range (Min, Max): 0.39, 29.0 

Monitoring Stations: 1 site 

Copollutant (correlation): 

PM2.5 (r = 0.85) 

BC (r = 0.50) 

OC (r = 0.41) 

SO4

2– 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

Estimated % change in tHcy per IQR 

increase in pollutant. 

Lag model 

Concurrent day: IQR: NA 

Model 1: NA 

Model 2: NA 

Model 3: NA 

1-day previous: IQR: 2.61 

Model 1: 0.91 (-0.77, 2.62) 

Model 2: 0.99 (-0.94, 2.95) 

Model 3: 0.91 (-0.72, 2.57) 

2-day ma: IQR: 2.10 

Model 1: -0.25 (-2.07, 1.60) 

Model 2: -0.29 (-2.35, 1.82) 

Model 3: 0.05 (-1.74, 1.86) 

3-day ma: IQR: 1.73 

Model 1: -0.15 (-1.97, 1.69) 

Model 2: -0.17 (-2.23, 1.93) 

Model 3: -0.01 (-1.78, 1.80) 

4-day ma: IQR: 1.64 

Model 1: -0.69 (-2.74, 1.41) 

Model 2: -0.60 (-2.95, 1.81) 

Model 3: -0.58 (-2.63, 1.51) 

5-day ma: IQR: 1.60 

Model 1: -1.14 (-3.53, 1.30) 

Model 2: -0.90 (-3.64, 1.92) 

Model 3: -1.09 (-3.48, 1.36) 

6-day ma; ’ IQR: 1.40 

Model 1: 0.00 (-2.39, 2.44) 

Model 2: 0.36 (-2.36, 3.16) 

Model 3: 0.41 (-2.01, 2.89) 

7-day ma 

IQR: 1.30 

Model 1: -0.16 (-2.51, 2.24) 

Model 2: 0.30 (-2.37, 3.04) 

Model 3: 0.07 (-2.25, 2.43) 

Stratified analyses: No significant 

difference in effect of SO4

2– among those 

with high and low levels of vitamins 

Reference: Peters et al. (2005, 095747) 

Also Peters et al. (2005, 156859) 

Period of Study: Feb 1999-Jul 2001 

Location: Augsburg, Germany 

Outcome: Myocardial infarction 

Study Design: Case-crossover 

N: 691 myocardial infarction patients 

Statistical Analysis: Conditional logistic 

regression 

Dose-response Investigated? No 

Pollutant: PM2.5 

Averaging Time: 

1 h: Median = 14.5 

IQR: 9.1 

24-h: Median = 14.9 

IQR: 7.7 

Copollutant: NO2, SO2, CO 

Effect Estimate: 2-h lag: OR = 0.93 

95% CI: 0,83, 1.04 

24-h mean, 2-day lag: OR = 1.18 

95% CI: 1.03, 1.34 

Notes: Examined triggering for MI at 

various lags before MI onset (up to 6 h 

before MI, up to 5 days before MI). PM2.5

levels 2 days before MI onset were 

associated with increased risk of MI, but 

not on the concurrent day, or lags 1, 3, 

4, or 5. These findings are consistent 

with the prior Boston MI study for a 1- to 

2-day lagged effect of PM2.5. 

December 2009 E-54 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Pope et al. (2004, 055238) 

Period of Study: Winter 1999-2000 (in 

Wasatch Front, UT). Summer 2000 (in 

Hawthorne, UT). 

Winter 2000-2001 (in Bountiful, UT and 

Lindon, UT) 

Location: Utah: Wasatch Front, 

Hawthorne, Bountiful, and Lindon 

Outcome: Change in autonomic 

function (measured by changes in HRV), 

C-reactive protein (CRP), blood cell 

counts, platelets, and blood viscosity 

associated with short-term changes in 

PM2.5

Age Groups: Elderly (specific age range 

not given)

Study Design: Panel study 

N: 88 elderly subjects 

Statistical Analysis: Linear regression 

Season: Winter, summer 

Dose-response Investigated? No 

Pollutant: PM2.5 (TEOM) 

Averaging Time: 24 h 

Mean (SD): 18.9 (13.4) 

Copollutant: None 

PM Increment: 100 μg/m3

Effect Estimate: Each 100 μg/m3

increase associated with: -35 (SE = 8) 

msec decline in SDNN 

0.81 (SE 0.17) mg/dL increase in CRP 

0.31 (SE 9.34) k/μL increase in platelets

0.07 (SE 0.21) cP increase in blood 

viscosity 

Notes: The study observed small but 

statistically significant adverse 

associations between daily mean PM2.5

and HRV and C-reactive protein (CRP). 

The authors point out, however, that 

most of the variability in the temporal 

deviation of these physiological 

endpoints was not explained by PM2.5. 

These observations therefore suggest 

that PM2.5 may be 1 of multiple factors 

that influence HRV and CRP. 

Reference: Pope et al. (2006, 091246) 

Period of Study: 1994-2004 

Location: Wasatch Front, Utah 

Outcome: Acute ischemic heart disease

Study Design: Case-crossover study 

(time-stratified control selection) 

N: Statistical Analysis: Conditional 

logistic regression 

Pollutant: PM2.5 (FRM) 

Averaging Time: 24 h 

Mean (SD): Site 1: 10.1 

Site 2: 10.8 

Site 3: 11.3 

Monitoring Stations: 3 

Copollutant: PM10 (FRM) measured at 

4 monitoring sites 

PM Increment: 10 μg/m3

Effect Estimate: For same-day increase 

in PM2.5: OR = 1.045 

95% CI: 1.011, 1.080 

Notes: Case-crossover study (timestratified control selection) triggering of 

acute ischemic heart disease by ambient 

PM2.5 concentrations on the same and 

previous 3 days. PM2.5 measured at 3 

sites and estimated for missing days. 

Effect estimates were larger for those 

with angiographically demonstrated 

coronary artery disease. 

Reference: Pope et al. (2004, 055238) 

Period of Study: 1999-2001 

Location: Wasatch Front, Utah 

Outcome: Heart rate variability (HRV) 

C-reactive protein (CRP) 

Blood cell counts, whole blood viscosity 

Age Groups: 54-89 yr 

Study Design: Panel study 

N: 88 participants 

Statistical Analyses: Linear regression 

Covariates: Subject-specific fixed 

effects 

Interactive spline smooths for temp, RH 

(partial control for H) 

Season: Temperature as covariate 

Dose-response Investigated? 

Yes, also assessed PM by including 

cubic smoothing splines with 3 df 

Statistical Package: SAS 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 23.7 (20.2) 

Range (Min, Max): 1.7, 74.0 

Monitoring Stations: NR 

Copollutant: None 

PM Increment: 100 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Regression coefficients (SE) for 

associations with concurrent day 

pollutant: Mean H: -4.49 (1.73) 

SDNN: -34.94 (8.32) 

SDANN: -18.98 (8.67) 

r-MSSD: -42.25 (10.90) 

CRP: 0.81 (0.18) 

Whole blood viscosity: 0.07 (0.21) 

WBC: -0.07 (0.38) 

Granulocytes: 0.02 (0.37) 

Lymphocytes: -0.07 (0.14) 

Monocytes: 0.12 (0.04) 

Basophils: -0.01 (0.01) 

Eosinophils: -0.01 (0.02) 

RBC: 0.03 (0.06) 

Platelets: 0.31 (9.34) 

Reference: Rich et al. (2005, 079620) 

Period of Study: Jul 1995-Jul 2002 

Location: Eastern Massachusetts, USA 

Outcome: Confirmed ventricular 

arrhythmias 

Study Design: Case-crossover (timestratified control selection) 

N: 203 patients with implantable 

cardioverter defibrillators 

Statistical Analysis: Conditional logistic 

regression 

Pollutant: PM2.5 (TEOM) 

Averaging Time: 1-h avg 

24-h avg 

Median (IQR): 

1-h avg: Median = 9.2 μg/m3

24-h avg: Median = 9.8 μg/m3

IQr = 7.8 

Copollutant: O3, BC, CO, NO2, SO2

PM Increment: 7.8 μg/m3

Effect Estimate: For mean PM2.5 in the 

24 h before ventricular arrhythmia: OR 

= 1.19 

95% CI: 1.02, 1.38 

Notes: 794 ventricular arrhythmias 

among 84 subjects. 

Lag h: 0-2, 0-6, 0-23, 0-47 

December 2009 E-55 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rich et al. (2006, 088427) 

Period of Study: Jul 1995-Jul 2002 

Location: Eastern Massachusetts, USA 

Outcome: Confirmed episodes of 

paroxysmal atrial fibrillation 

Study Design: Case-crossover (timestratified control selection) 

N: 203 patients with implantable 

cardioverter defibrillators 

Statistical Analysis: Conditional logistic 

regression 

Pollutant: PM2.5 (TEOM) 

Averaging Time: 1-h avg 

24-h avg 

Median (IQR): 

1-h avg: Median = 9.2 μg/m3

24-h avg: Median = 9.8 μg/m3

IQr = 7.8 

Copollutant: O3, BC, CO, NO2, SO2

PM Increment: 9.4 μg/m3

Effect Estimate: 0-h lag: OR 1.41 (0.82, 

2.42) 

Notes: 91 paroxysmal atrial fibrillation 

(PAF) episodes among 29 subjects. 

Lag h: 0, 0-23 

Positive, but not significant increases in 

the relative odds of PAF associated with 

PM2.5 concentrations in the same h and 

24-h before PAF episode onset. Authors 

note reduced statistical power for PM2.5

analyses due to missing data. 

Reference: Rich et al. (2006, 088427) 

Period of Study: Jul 1995-Jul 2002 

Location: Eastern Massachusetts, USA 

Outcome: Confirmed episodes of 

paroxysmal atrial fibrillation 

Study Design: Case-crossover (timestratified control selection) 

N: 203 patients with implantable 

cardioverter defibrillators 

Statistical Analysis: Conditional logistic 

regression 

Pollutant: BC 

Averaging Time: 1-h avg, 24-h avg 

Median (IQR): IQR: 0.91μg/m3 

Copollutant: O3, PM2.5, CO, NO2, SO2

PM Increment: 0.91μg/m3 (IQR) 

Effect Estimate: 0- to 23-h lag period: 

OR 1.46 (95% CI: 0.67, 3.17) 

Notes: 91 paroxysmal atrial fibrillation 

(PAF) episodes among 29 subjects. 

Lag h: 0, 0-23

Positive, but not significant increases in 

the relative odds of PAF associated with 

BC concentrations in the same h and 24 

h before PAF episode onset. Authors 

note reduced statistical power for BC 

analyses due to missing data. 

Reference: Rich et al. (2006, 089814) 

Period of Study: May 2001-Dec 2002 

Location: St. Louis, MO metropolitan 

area 

Outcome: Confirmed ventricular 

arrhythmia 

Study Design: Case-crossover design 

(time-stratified control selection) 

Dose-response Investigated? No 

Pollutant: PM2.5 (CAMM) 

Averaging Time: 24 h 

Median (IQR): 16.2 μg/m3 (IQr = 9.7) 

Copollutant: NO2, SO2, CO, O3, EC, OC

PM Increment: 9.7 μg/m3 (IQR) 

Effect Estimate: OR (PM2.5) = 0.95 

(95% CI: 0.72, 1.27) 

OR (SO2) = OR = 1.24 (95% CI: 1.07, 

1.44) 

Notes: 139 confirmed ventricular 

arrhythmia episodes among 56 subjects. 

Lags: 0-2h, 0-6h, 0-11h, 0-23h, 0-47h 

Authors did not find increased relative 

odds of VA associated with each IQR 

increase in 24-h mean PM2.5, but did find 

non-significantly increased relative odds 

of VA associated with 24-h EC. Shorter 

and longer lag times’ relative odds 

estimates provided no evidence of 

immediate ventricular arrhythmic effects 

of air pollution. 

Reference: Rich et al. (2004, 055631) 

Period of Study: Feb-Dec 2000 

Location: Vancouver, British Columbia, 

Canada 

Outcome: ICD discharges (as a proxy 

for VT/VF) 

Age Groups: 15-85 yr 

Study Design: Case-crossover design 

(ambidirectional control selection ± 7 

days) 

N: 34 patients with implantable 

cardioverter defibrillators 

Statistical Analysis: Conditional logistic 

regression 

Dose-response Investigated? No 

Pollutant: PM2.5 (Partisol) 

Averaging Time: 1 h 

Mean (SD), IQR: 

Mean: : 8.2 μg/m3 (SD = 10.7) 

IQr = 5.2 

Copollutant: O3, EC, OC, SO4

2–, CO, 

NO2, SO2, PM10

PM10: Mean: : 13.3 μg/m3

 

(SD = 4.9) 

IQr = 7.4 

PM Increment: Effect Estimate: Odds 

ratios were less than 1.0 at all lags (0, 1, 

2, 3) for PM2.5. 

No consistent association between any 

of the air pollutants and implantable 

cardioverter defibrillators discharges. 

Notes: Same study as Vedal et al. 

(2004, 055630), except Rich (2004) 

used data from a shorter time period so 

as to estimate relative odds of ICD 

discharge associated with acute 

increases in more pollutants than Vedal 

(2004, 055630).

December 2009 E-56 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rich et al. (2008, 156910) 

Period of Study: NR 

Location: New Jersey 

Outcome: Pulmonary Artery and Right 

Ventricular Pressures 

Age Groups: 25-68 

Study Design: Panel 

N: 11 subjects 

Statistical Analyses: Repeated 

Measures 

Covariates: Long-term trends, calendar 

month, weekday, apparent temperature 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-6d 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): NR 

Monitoring Stations: NR 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: 11.62μg/m3

Change (Lower CI, Upper CI), p-value: 

ePAD: 0.19 (0.05, 0.33), 0.01 

RV diastolic pressure: 0.23 (0.11, 0.34), 

<0.001 

RV systolic pressure: 0.12 (-0.07, 0.31), 

0.23 

MPAP: 0.12 (-0.05, 0.28), 0.16/ 

Reference: Riediker et al. (2004, 

091261) 

Period of Study: Fall 2001 

Location: Wake County, North Carolina 

Outcome: Heart rate variability 

(measured 10 h after shift): mean cycle 

length of normal R-R intervals (MCL), 

the standard deviation of normal R-R 

intervals (SDNN), and percentage of 

normal R-R interval differences greater 

than 50 msec (PNN50), low frequency 

(0.04-0.15Hz), high frequency (0.15-

0.40Hz), the ratio of low to high 

frequency. 

Blood analysis (measured 15 h after 

shift): Uric acid, blood urea nitrogen, 

gamma glutamyl transpeptidase, white 

blood cell count, red blood cell count, 

hematocrit, hemoglobin, mean red blood 

cell volume (MCV), neutronphils (count 

and %), lymphocytes (count and %), Creactive protein, plasminogen, 

plasminogen activator inhibitor type 1, 

von Willebrand factor (vWF), endovthzelin-1, protein C, and interleukin-6 

Age Groups: 23-30 yr

Study Design: Panel 

N: 9 healthy male troopers, repeated 

measures (36 person-days) 

Statistical Analyses: Mixed effects 

regression models (principal factor 

analysis for classification of exposure) 

Covariates: Potential confounders: 

temperature, relative humidity, number 

of law-enforcement activities during the 

shift and the avg speed during the shift 

Controlling had no effect on effect estimates for “crustal” and “speed-change” 

factors 

However, confounder inclusion in the 

“speed change” and blood urea nitrogen 

and vWF reduced the effect estimate 

and the CI included zero 

Season: Only 1 season included 

Dose-response Investigated? No 

Statistical Package: S-Plus 6.1 

Pollutant: In-vehicle PM2.5 components 

identified with factor analysis (crustal 

material, wear of steel automotive 

components, gasoline combustion, 

speed-changing traffic with engine 

emissions and brake wear 

Averaging Time: Exposure assessed 

during 3 p.m. to 12 a.m. work shifts

Mean: PM2.5mass = 23.0 μg/m3

Monitoring Stations: Per vehicle 

Copollutant (correlation): Correlation 

to PM2.5Mass 

Benzene: r = 0.50 

Aldehydes: r = 0.34 

CO: r = 0.52 

Aluminum: r = 0.58 

Silicon: r = 0.66 

Sulfur: r = 0.58 

Calcium: r = 0.37 

Titanium: r = 0.41 

Chromium: r = 0.51 

Iron: r = 0.71 

Copper: r = 0.16 

Selenium: r = 0.38 

Tungsten: r = 0.37 

PM2.Lightscatter: r = 0.71 

PM Increment: 1 SD change in source 

factor 

Effect Estimate: % change in the health 

outcome per 1 SD change in the “speed 

change” factor 

MCL: 7% 

HRV: 16% 

supraventricular ectopic beats: 39% 

% Neutrophils: 7% 

% lymphocytes: -10% 

red blood cell volume MCV: 1% 

vWF: 9% 

blood urea nitrogen: 7% 

protein C: -11% 

% change in the health outcome per 1 

SD change in the “crustal” factor 

MCL: 3% serum uric acid 

concentrations: 5% 

Note: Results (including CIs) are 

reported in figures 2 & 3. 

December 2009 E-57 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Riojas-Rodriguez et al. 

(2006, 156913) 

Period of Study: Dec 2001-Apr 2002 

Location: Mexico City metropolitan area 

Outcome: Heart rate variability (5-

minute periods) 

Study Design: Panel study 

N: 30 patients from the outpatient clinic 

of the National Institute of Cardiology of 

Mexico, where each subject had existing 

ischemic heart disease. 

Statistical Analysis: Mixed models 

Pollutant: PM2.5 (nephelometry) 

Averaging Time: 5 min 

Mean (SD), Range: 

46.8 μg/m3 (SD = 1.82) 

Range: 0-483 μg/m3

Copollutant: CO 

PM Increment: 10 μg/m3 

Effect Estimate: Each 20 μg/m3

increase in 5 min PM2.5 was associated 

with a: -0.008 decrease in the 

ln(HF)(95% CI: -0.015, 0.0004 

Notes: Population of subjects with 

known ischemic heart disease (25 men 

and 5 women who had at least 1 prior MI 

[not in last 6 mo]) 

Each 10 μg/m3

 increase in 5-min mean 

PM2.5 was associated with nonsignificantly decreased HF, and with 

similar, but smaller changes in LF and 

VLF. 

Reference: Romieu et al. (2005, 

086297) 

Period of Study: 2000-2001 

Location: Mexico City, Mexico 

Outcome: Heart rate variability (HF, LF, 

VLF, PNN50, SDNN, r-MSSD) 

Age Groups: >60 yr of age 

Study Design: Double blind randomized 

controlled trial 

N: 50 elderly residents of a Mexico City 

nursing home 

Pollutant: PM2.5 

Averaging Time: 24 h 

Copollutant: O3, NO2, SO2, PM10

PM Increment: 8 μg/m3 

Effect Estimate: In the group receiving 

the fish oil supplement, each 8 μg/m3

change in 24-h mean total exposure 

PM2.5 was associated with a: a) 54% 

reduction (95% CI: -72% to -24%) in HF 

(log transformed) in the presupplementation phase 

b) 7% reduction (95% CI: -20%, 7%) in 

the supplementation phase. 

Changes in other HRV parameters were 

also smaller in the supplementation 

phase. In the group receiving soy oil 

supplementation, the % reduction in HF 

was also smaller in the supplementation 

phase, but the differences were smaller 

and not statistically significant. 

Notes: Study of the effect of omega-3-

fatty acid supplementation (2 g/day of 

fish oil vs.. 2 g/day of soy oil) to mitigate 

the effect of ambient PM2.5 on HRV. 

Subjects had no cardiac arrhythmias, 

cardiac pacemakers, allergies to omega3 fatty acids or fish, treatment with oral 

anticoagulants, or history of bleeding 

diathesis. PM2.5 was measured and 

estimated indoors, outdoors, and with 

regards to total exposure (the same as 

Holguin et al. (2003)). 

December 2009 E-58 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Romieu et al. (2008, 

156922) 

Period of Study: Sep 2001-Apr 2002 

Location: Mexico City, Mexico 

Outcome: Copper/zinc superoxide 

dismutase activity (Cu/Zn SOD) 

Lipoperoxidation (LPO) 

Reduced glutathione (GSH) 

Age Groups: 60-96 yr

Study Design: Intervention (randomly 

assigned fish oil or soy oil) 

N: 52 participants 

Statistical Analyses: Linear mixed 

models 

Covariates: Time 

Dose-response Investigated? 

Assessed possible nonlinearity using 

generalized additive mixed models with 

p-splines 

Statistical Package: STATA v8.2 and 

SAS v9.1 

Pollutant: PM2.5 (indoor) 

Averaging Time: 24 h (same day) 

Mean (SD): 38.7 (14.7) 

Percentiles: 

25th: 30.62 

50th: 35.11 

75th: 41.10 

Range (Min, Max): 14.8, 70.9 

Monitoring Stations: Indoor measured 

inside nursing home 

Copollutant: O3

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Regression coefficient (SE 

p-value): 

Cu/Zn SOD: -0.05 (0.02 

0.001) 

LPO (square root transformed): 0.08 

(0.09 

0.381) 

GSH (log-transformed 

quadratic term for PM): -0.05 (0.01 

0.002) 

Regression coefficient (SE 

p-value) by supplementation groups 

(same transformations as above): Cu/Zn 

SOD 

Soy Oil: -0.06 (0.02, <0.001) 

Fish Oil: * 0.04 (0.02, 0.009) 

LPO 

Soy Oil: -0.02 (0.14, 0.904) 

Fish Oil: * 0.16 (0.07, 0.024) 

GSH 

Soy Oil: -0.03 (0.04, 0.406) 

Fish Oil: -0.09 (0.04, 0.017) 

*Quadratic term for PM 

Reference: Ruckerl et al. (2007, 

156931) 

Period of Study: May 2003-Jul 2004 

Location: 

Athens, Augsburg, Barcelona, Helsinki, 

Rome, and Stockholm 

Outcome: Interleukin-6 (IL-6), 

fibrinogen, C-reactive protein (CRP) 

Age Groups: 35-80 yr

Study Design: Repeated measures / 

longitudinal 

N: 1003 MI survivors 

Statistical Analyses: Mixed-effect 

models 

Covariates: City-specific confounders 

(age, sex, BMI) 

Long-term time trend and apparent 

temperature 

RH, time of day, day of week included if 

adjustment improved model fit 

Season: Long-term time trend 

Dose-response Investigated? Used psplines to allow for nonparametric 

exposure-response functions 

Statistical Package: SAS v9.1 

Pollutant: PM2.5 

Averaging Time: Hourly and 24-h (lag 

0-4, mean of lags 0-4, mean of lags 0-1, 

mean of lags 2-3, means of lags 0-3) 

Mean (SD): Presented by city only 

Monitoring Stations: Central 

monitoring sites in each city 

Copollutant: 

SO2

O3

NO 

NO2

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

% change in mean blood markers per 

increase in IQR of air pollutant. 

IL-6 

Lag (IQR): % change in GM (95%CI) 

Lag 0 (11.0): 0.46 (-0.89, 1.83) 

Lag 1 (11.0): -0.39 (-1.69, 0.93) 

Lag 2 (11.0): -0.23 (-1.53, 1.07) 

5-day avg (8.6): 0.05 (-1.37, 1.50) 

Fibrinogen 

Lag (IQR): % change in AM (95%CI) 

Lag 0 (11.0): 0.05 (-0.48, 0.58) 

Lag 1 (11.0): 0.17 (-0.35, 0.69) 

Lag 2 (11.0): 0.20 (-0.32, 0.71) 

5-day avg (8.6): 0.38 (-0.21, 0.96) 

CRP 

Lag (IQR): % change in GM (95%CI) 

Lag 0 (11.0): 0.11 (-1.95, 2.21) 

Lag 1 (11.0): -0.06 (-1.98, 1.90) 

Lag 2 (11.0): 0.11 (-1.80, 2.06) 

5-day avg (8.6): -0.13 (-2.15, 1.92) 

December 2009 E-59 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2006, 

088754) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: C-reactive protein (CRP) 

serum amyloid A (SAA) 

E-selectin 

von Willebrand Factor (vWF) 

intercellular adhesion molecule-1 (ICAM1) 

fibrinogen 

Factor VII 

prothrombin fragment 1+2 

D-dimer 

Age Groups: 50+ 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear and logistic regression models

Covariates: Models adjusted for 

different factors based on health 

endpoint 

CRP: RH, temperature, trend, ID 

ICAM-1: temperature, trend, ID 

vWF: air pressure, RH, temperature, 

trend, ID 

FVII: air pressure, RH, temperature, 

trend, ID, weekday 

Season: Time trend as covariate 

Dose-response Investigated? 

Sensitivity analyses examined nonlinear 

exposure-response functions 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 20.0 (15.0) 

Percentiles: 

25th: 9.7 

50th: 14.9 

75th: 26.1 

Range (Min, Max): 2.6, 83.7 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5

PM10

OC 

EC 

NO2

CO 

PM Increment: IQR (16.4 

5-day avg: 12.2)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as OR (95%CI) for an 

increase in the blood marker above the 

90th percentile per increase in IQR air 

pollutant. 

CRP 

Time before draw: 0 to 23 h: 1.1 (0.7, 

1.8) 

24-47 h: 1.5 (0.9, 2.5) 

48-71 h: 1.2 (0.8, 1.9) 

5-day mean: 1.4 (0.9, 2.3) 

ICAM-1 

Time before draw: 0-23 h: 0.7 (0.4, 0.9)

24-47 h: 1.3 (0.8, 1.8) 

48-71 h: 1.8 (1.2, 2.7) 

5-day mean: 1.1 (0.8, 1.5) 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

vWF 

Time before draw: 0-23 h: 3.9 (-0.3, 8.1)

24-47 h: 3.1 (-1.6, 7.8) 

48-71 h: 3.6 (-1.1, 8.3) 

5-day mean: 5.6 (0.5, 10.8) 

FVII 

Time before draw: 0-23 h: -2.5 (-6.2 to 

1.4) 

24-47 h: -2.8 (-6.1 to 0.6) 

48-71 h: -2.3 (-5.0 to 0.6) 

5-day mean: -3.5 (-6.4 to -0.4) 

Note: Summary of results presented in 

figures. SAA results indicate increase in 

association with PM (not as strong and 

consistent as with CRP) 

No association observed between Eselectin and PM 

An increase in prothrombin fragment 

1+2 was consistently observed, 

particularly with lag 4 

Fibrinogen results revealed few 

significant associations, potentially due 

to chance 

D-dimer results revealed null 

associations in linear and logistic 

analyses 

December 2009 E-60 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2006, 

088754) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: C-reactive protein (CRP) 

serum amyloid A (SAA) 

E-selectin 

von Willebrand Factor (vWF) 

intercellular adhesion molecule-1 

(ICAM-1) 

fibrinogen 

Factor VII 

prothrombin fragment 1+2 

D-dimer 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear and logistic regression models

Covariates: Models adjusted for 

different factors based on health 

endpoint 

CRP: RH, temperature, trend, ID 

ICAM-1: temperature, trend, ID 

vWF: air pressure, RH, temperature, 

trend, ID 

FVII: air pressure, RH, temperature, 

trend, ID, weekday 

Season: Time trend as covariate 

Dose-response Investigated? 

Sensitivity analyses examined nonlinear 

exposure-response functions 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: EC 

Averaging Time: 24 h 

Mean (SD): 2.6 (2.4) 

Percentiles: 

25th: 1.0 

50th: 1.8 

75th: 3.2 

Range (Min, Max): 0.2, 12.4 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5

PM10

OC 

EC 

NO2

CO 

PM Increment: IQR (2.3 

5-day avg: 1.8)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as OR (95%CI) for an 

increase in the blood marker above the 

90th percentile per increase in IQR air 

pollutant. 

CRP 

Time before draw: 0-23 h: 1.2 (0.7, 2.0)

24-47 h: 1.3 (0.7, 2.4) 

48-71 h: 1.6 (0.9, 2.7) 

5-day mean: 1.2 (0.7, 2.1) 

ICAM-1 

Time before draw: 0-23 h: 1.0 (0.7, 1.6) 

24-47 h: 2.6 (1.7, 3.8) 

48-71 h: 4.0 (2.5, 6.1) 

5-day mean: 2.2 (1.4, 3.3) 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

vWF 

Time before draw: 0-23 h: 5.0 (0.0, 10.1)

24-47 h: 7.6 (1.4, 13.7) 

48-71 h: 1.1 (-5.2, 7.4) 

5-day mean: 5.7 (-0.5, 12.0) 

FVII 

Time before draw: 0-23 h: -5.7 (-10.5 to -

0.7) 

24-47 h: -6.9 (-11.2 to -2.3) 

48-71 h: -4.2 (-8.4, 0.2) 

5-day mean: -6.0 (-10.5 to -1.2) 

Note: Summary of results presented in 

figures. SAA results indicate increase in 

association with PM (not as strong and 

consistent as with CRP) 

No association observed between 

E-selectin and PM 

An increase in prothrombin fragment 

1+2 was consistently observed, 

particularly with lag 4 

Fibrinogen results revealed few 

significant associations, potentially due 

to chance 

D-dimer results revealed null 

associations in linear and logistic 

analyses 

December 2009 E-61 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2006, 

088754) 

Period of Study: 

Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome (ICD9 and ICD10): C-reactive 

protein (CRP) 

Serum amyloid A (SAA) 

E-selectin 

von Willebrand Factor (vWF) 

intercellular adhesion molecule-1 (ICAM1) 

Fibrinogen 

Factor VII 

Prothrombin fragment 1+2 

D-dimer 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear and logistic regression models

Covariates: Models adjusted for 

different factors based on health 

endpoint 

CRP: RH, temperature, trend, ID 

ICAM-1: temperature, trend, ID 

vWF: air pressure, RH, temperature, 

trend, ID 

FVII: air pressure, RH, temperature, 

trend, ID, weekday 

Season: Time trend as covariate 

Dose-response Investigated? 

Sensitivity analyses examined nonlinear 

exposure-response functions 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: OC 

Averaging Time: 24 h 

Mean (SD): 1.5 (0.6) 

Percentiles: 

25th: 1.1 

50th: 1.4 

75th: 1.8 

Range (Min, Max): 0.3, 3.4 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5

PM10

OC 

EC 

NO2

CO 

PM Increment: IQR (0.7 

5-day avg: 0.5)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as OR (95%CI) for an 

increase in the blood marker above the 

90th percentile per increase in IQR air 

pollutant. 

CRP 

Time before draw: 0-23 h: 1.2 (0.7, 1.9)

24-47 h: 1.3 (0.8, 2.1) 

48-71 h: 1.4 (0.8, 2.4) 

5-day mean: 1.2 (0.7, 1.8) 

ICAM-1 

Time before draw: 0-23 h: 0.9 (0.6, 1.3)

24-47 h: 2.0 (1.3, 3.2) 

48-71 h: 3.0 (1.8, 4.8) 

5-day mean: 1.3 (0.8, 2.0) 

 Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

vWF 

Time before draw: 0-23 h: 5.5 (0.2, 10.8)

24-47 h: 8.0 (2.1, 13.9) 

48-71 h: 3.5 (-2.6, 9.6) 

5-day mean: 7.4 (2.0, 12.8) 

FVII 

Time before draw: 0-23 h: -6.1 (-10.6 to -

1.4) 

24-47 h: -7.2 (-11.4 to -2.8) 

48-71 h: -3.8 (-8.2, 0.9) 

5-day mean: -5.6 (-9.8 to -1.1) 

Note: Summary of results presented in 

figures. SAA results indicate increase in 

association with PM (not as strong and 

consistent as with CRP) 

No association observed between Eselectin and PM 

An increase in prothrombin fragment 

1+2 was consistently observed, 

particularly with lag 4 

Fibrinogen results revealed few 

significant associations, potentially due 

to chance 

D-dimer results revealed null 

associations in linear and logistic 

analyses 

December 2009 E-62 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2007, 

091379) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: Soluble CD40 ligand 

(sCD40L), platelets, leukocytes, 

erythrocytes, hemoglobin 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear regression models

Covariates: Long-term time trend, 

weekday of the visit, temperature, RH, 

barometric pressure 

Season: Time trend as covariate 

Dose-response Investigated? No 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 20.0 (15.0) 

Percentiles: 

25th: 9.7 

50th: 14.9 

75th: 26.1 

Range (Min, Max): 2.6, 83.7 

Monitoring Stations: 1 site 

Copollutants: 

UFPs 

AP 

PM2.5

PM10

NO 

PM Increment: IQR (16.4 

5-day avg: 12.2)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

sCD40L, % change GM (pg/mL) 

lag0: 1.5 (-4.0, 7.3) 

Lag1: 0.2 (-5.4, 6.2) 

Lag2: -2.6 (-8.0, 3.1) 

Lag3: 0.5 (-3.9, 5.0) 

5-day mean: 0.2 (-5.4, 6.2) 

Platelets, % change mean (103/μl) 

Lag0: -0.6 (-1.9, 0.7) 

Lag1: 0.1 (-1.3, 1.5) 

Lag2: 0.5 (-0.9, 1.9) 

Lag3: 0.2 (-1.1, 1.5) 

5-day mean: -0.4 (-1.9, 1.2) 

Leukocytes, % change in mean 

(103/μl) 

Lag0: -1.6 (-3.2, 0.0) 

Lag1: -0.4 (-2.2, 1.4) 

Lag2: -0.2 (-2.1, 1.7) 

Lag3: -0.8 (-2.4, 0.7) 

5-day mean: -1.6 (-3.5, 0.3) 

Erythrocytes, % change mean (106/μl)

Lag0: -0.1 (-0.5, 0.3) 

Lag1: -0.3 (-0.7, 0.2) 

Lag2: -0.4 (-0.8, 0.0) 

Lag3: -0.2 (-0.5, 0.1) 

5-day mean: -0.4 (-0.8, 0.0) 

Hemoglobin, % change mean (g/dl) 

Lag0: 0.0 (-0.6, 0.5) 

Lag1: -0.2 (-0.8, 0.3) 

Lag2: -0.5 (-1.1, 0.0) 

Lag3: -0.2 (-0.7, 0.2) 

5-day mean: -0.5 (-1.0, 0.1) 

Reference: Sarnat et al. (2006, 090489) 

Period of Study: Summer and fall 2000 

Location: Steubenville, OH 

Outcome: Supraventricular ectopy 

(SVE) or ventricular ectopy (VE) 

N: 32 nonsmoking older adults 

Statistical Analysis: Logistic mixed 

effects regression 

Season: Summer and fall 

Dose-response Investigated? No 

Pollutant: PM2.5 

Averaging Time: 5 days 

Median (IQR): PM2.5: Median: 19.0 

μg/m3

 

IQr = 10.0 

Sulfate: Median: 6.1. IQR: 4.2 

EC: Median: 0.9. IQR: 0.5 

Copollutants: O3, NO2, SO2

PM Increment: IQR 

Effect Estimate: PM2.5: SVE: OR = 1.42 

(95% CI: 0.99, 2.04) 

VE: OR = 1.02 (95% CI: 0.63-1.65) 

Sulfate: SVE: OR = 1.70 (95% CI: 1.12, 

2.57) 

VE: OR = 1.08 (95% CI: 0.65, 1.80) 

EC: SVE: OR = 1.15 (95% CI: 0.73, 

1.81) 

VE: OR = 1.00 (95% CI: 0.57, 1.75) 

Notes: Longitudinal study of 32 

nonsmoking older adults who had ECG 

measurements made every week for 24 

wk. PM measured within 1 mile of 

subjects’ residences, and central site 

pollutant measurements were also 

made.

December 2009 E-63 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Schneider et al. (2008, 

191985) 

Period of Study: Nov 2004-Dec 2005 

Location: Chapel Hill, NC 

Outcome: Endothelial Function 

Parameters 

Age Groups: 48-80 yr

Study Design: Panel 

N: 22 diabetics 

Statistical Analyses: Mixed Models 

Covariates: Season, day of the week, 

temperature, relative humidity, 

barometric pressure 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-4 days; 5-day ma 

Pollutant: PM2.5 

Averaging Time: Daily 

Mean (SD): 13.6 (7.0)

Min: 2.0 

Max: 38.9 

Monitoring Stations: 2 

Copollutant: NR 

PM Increment: 10 μg/m3

Percent Change: (Lower CI, Upper 

CI), lag: 

FMD: ^l 

-17.3 (-34.6, 0.0), lag 0 

-4.4 (-24.6, 15.8), lag 1 

-18.6 (-44.8, 7.6), lag 2 

1.6 (-23.6, 26.9), lag 3 

18.4 (-3.5, 40.3), lag 4 

-19.4 (-62.6, 23.8), 5-day ma 

NTGMD: 

2.5 (-9.0, 13.9), lag 0 

-13.6 (-24.5, -2.6), lag 1* 

-10.2 (-23.5, 3.0), lag 2 

-8.0 (-22.4, 6.4), lag 3 

3.6 (-7.9, 15.0), lag 4 

-19.4 (-44.3, 5.5), 5-day ma 

LAEI: 

0.4 (-4.2, 5.0), lag 0 

-0.3 (-6.0, 5.4), lag 1 

2.5 (-4.3, 9.4), lag 2 

-7.3 (-13.5, -1.1), lag 3* 

-2.3 (-8.0, 3.3), lag 4 

-4.6 (-15.3, 6.1), 5-day ma 

SAEI: 

-3.0 (-13.0, 7.0), lag 0 

-17.0 (-27.5, -6.4), lag 1** 

-9.7 (-23.5, 4.2), lag 2 

-15.1 (-29.3, -0.9)*, lag 3 

-2.1 (-14.0, 9.7), lag 4 

-25.4 (-45.4, -5.3), 5-day ma* 

SVR: 

-1.6 (-3.7, 0.4), lag 0 

1.6 (-0.9, 4.1), lag 1 

3.5 (0.5, 6.5), lag 2 

2.4 (-0.5, 5.3), lag 3 

3.2 (0.7, 5.6), lag 4* 

4.5 (-0.3, 9.2), 5-day ma 

*p < 0.05, ** p < 0.01 

Notes: Percent change (95% CI) per 

10 μg/m3 PM2.5 by GSTM1 genotype 

(Fig 3) 

Reference: Schwartz et al. (2005, 

074317) 

Period of Study: 12 wk during the 

summer of 1999 

Location: Boston, MA 

Outcome: Heart rate variability (HRV), 

(SDNN, 

r-MSSD, PNN50, LFHFR) 

Age Groups: 61-89 yr

Study Design: Panel study 

N: 28 elderly subjects 

Statistical Analysis: Mixed models. To 

examine heterogeneity of effects, 

hierarchical modeling was used. 

Season: Summer 

Dose-response Investigated? No 

Pollutant: PM2.5 

Averaging Time: 1 h, 24 h 

Median: 24-h: 10 μg/m3

Monitoring Stations: 1

Copollutant: BC, O3, CO, SO2, NO2

PM Increment: IQR (not given) 

Effect Estimate: 24 h: 2.6 ms decrease 

in SDNN (95% CI: 0.8 to -6.0) 

10.1 ms decrease in r-MSSD (95% CI: -

2.8 to -16.9). 

1 h: 3.4 ms decrease in SDNN (95% CI: 

0.6 to -7.3) 

7.4 ms decrease in r-MSSD (95% CI: 

1.6 to -15.5). 

Notes: Various log-transformed HRV 

parameters were measured for 30 

minutes once a week. The random 

effects model indicated that the negative 

effect of BC on HRV was not restricted 

to a few subjects. 

Same study population as Gold et al. 

(2005). Boston Elders Study 

For each pollutant/averaging time, 

similarly sized changes were observed 

for PNN50 (%) and LFHFR. 

December 2009 E-64 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Schwartz et al. (2005, 

074317) 

Period of Study: 12 wk during the 

summer of 1999 

Location: Boston, MA 

Outcome: Heart rate variability (HRV), 

(SDNN, r-MSSD, PNN50, LFHFR) 

Age Groups: 61-89 yr 

Study Design: Panel study 

N: 28 elderly subjects 

Statistical Analysis: Mixed models. To 

examine heterogeneity of effects, 

hierarchical modeling was used. 

Season: Summer 

Dose-response Investigated? No 

Pollutant: BC 

Averaging Time: 24 h 

Median: 1.0 μg/m3

Monitoring Stations: 1

Copollutant: PM2.5, O3, CO, SO2, NO2

PM Increment: IQR 

Effect Estimate: 5.1 ms decrease in 

SDNN (-1.5 to -8.6) 

10.1 ms decrease in r-MSSD (-2.4 to -

17.2). 

Notes: Various log-transformed HRV 

parameters were measured for 30 

minutes once a week. The random 

effects model indicated that the negative 

effect of BC on HRV was not restricted 

to a few subjects. Same study 

population as Gold et al. (2005). Boston 

Elders Study. Subjects with a prior MI 

experienced greater declines in BC 

associated HRV. For each 

pollutant/averaging time, similarly sized 

changes were observed for PNN50 (%) 

and LFHFR.

Reference: Schwartz et al. (2005, 

074317) 

Period of Study: 2000 

Location: Boston, Massachusetts 

Outcome: HF (high frequency 

component of heart rate variability) 

Study Design: Cross-sectional 

N: 497 subjects 

Statistical Analysis: Linear regression, 

controlling for covariates 

Pollutant: PM2.5 

Averaging Time: 48 h 

Mean (SD): 11.4 μg/m3 (8.0) 

Copollutant: None 

PM Increment: 10 μg/m3

Effect Estimate: 34% decrease in HF 

(95% CI: -9% to -52%) in subjects 

without the GSTM1 allele. In subjects 

with the allele, no effect was noted. 

Similar findings for obese subjects and 

those with high neutrophil counts. 

Notes: Study population: Normative 

Aging Study. 

Effects of PM2.5 appear to be mediated 

by ROS. 

Reference: Sorensen et al. (2005, 

089428) 

Period of Study: Nov 1999-Aug 2000 

Location: Copenhagen, Denmark 

Outcome: 7-Hydro-8-Oxo-2’-

Deoxyguanosine (8-oxodG) (measured 

in lymphocytes and urine) 

Age Groups: 20-33 yr

Study Design: Panel (repeated 

measures) 

N: 49 students living and studying in 

central Copenhagen 

50 students examined each season (66 

subjects total 

32 participated in each season 

total of 98 measurements) 

Statistical Analyses: Mixed models 

repeated measures 

Covariates: PM2.5, season, subject 

(random factor) 

Dose-response Investigated? No 

Statistical Package: SAS v8e 

Pollutant: PM2.5 

Averaging Time: 48 h 

Mean (SD): Fall: 20.7 

Summer: 12.6 

Percentiles: IQR Fall: 13.1-27.7 

IQR summer: 9.4-24.3 

Range (Min, Max): NR 

Monitoring Stations: NA (personal 

assessment) 

Copollutant (correlation): 

Spearman correlations with PM2.5 mass: 

chromium (r = 0.22) 

copper (r = 0.33) 

iron (r = 0.29) 

vanadium (p>0.5) 

nickel (p>0.5) 

platinum (p>0.5) 

PM Increment: see below

Effect Estimate [Lower CI, Upper CI]: 

Association between 8-oxodG in 

lymphocytes and personal exposure to 

transition metals in PM2.5.

% increase in 8-oxodG per increase in 

metal concentration indicated 

Vanadium: 1.9% per 1 μg/L (0.6, 3.3) 

Chromium: 2.2% per 1 μg/L (0.8, 3.5) 

Platinum: 6.1% per 1 ng/L (-0.6, 13.2) 

Nickel: 0.8% per 10 μg/L (-2.1, 3.7) 

Copper: -0.8% per 10 μg/L (-2.7, 1.0) 

Iron: 0.6% per 10 μg/L (-1.4, 2.6) 

Note: PM2.5 mass was independently 

associated with 8-oxodG in 5 of 6 

transition metal models (p < 0.02 in 

models with vanadium, chromium, 

nickel, copper, and iron 

p = 0.07 in platinum model). No 

transition metals were associated with 8-

oxodG measured in urine 

December 2009 E-65 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sorensen et al. (2003, 

042700) 

Period of Study: Nov 1999-Aug 2000 

Location: Copenhagen, Denmark 

Outcome: RBC count, hemoglobin, 

platelet count, fibrinogen, PLAAS (2-

aminoadipic semialdehyde in plasma 

proteins), HBGGS (γ-glutamyl 

semialdehyde in hemoglobin), HBAAS 

(2-aminoadipic semialdehyde in 

hemoglobin), MDA (malondialdehyde) 

Age Groups: 20-33 yr

Study Design: Panel (repeated 

measures) 

N: 50 students living and studying in 

central Copenhagen 

50 students examined each season (68 

subjects total 

31 participated in each season 

total of 195 measurements) 

Statistical Analyses: Mixed model 

repeated-measures analysis 

Covariates: Season, avg outdoor 

temperature, and sex 

Season: Repeated measures 4 times 

(once per season) 

Dose-response Investigated? No 

Statistical Package: SAS v8e 

Pollutant: PM2.5 (personal) 

Averaging Time: 48 h 

Median: 16.1 μg/m3 

Percentiles: Q25-Q75: 10.0-24.5 

Copollutant: 

Urban background PM2.5

Personal PM2.5

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Relationship between exposure and 

biomarkers 

Estimate (p-value): Platelet count (x 

106/g protein): 0.0008 (0.37) 

Fibrinogen (nmol/g protein): 0.0006 

(0.69) 

PLAAS (pmol/mg protein): 0.0016 

(0.061) 

HBGGS (pmol/mg protein): 0.0001 

(0.94) 

HBAAS (pmol/mg protein): 0.0006 (0.64)

Increase (95%CI) in biomarkers per 10 

μg/m3

 increase in PM2.5

RBC 

Men: 0% (-1.6, 1.6) 

Women: 2.3% (0.5, 4.1) 

Hemoglobin 

Men: 0.0% (-1.7, 1.5) 

Women: 2.6% (0.8, 4.5) 

Reference: Sorensen et al. (2003, 

042700) 

Period of Study: Nov 1999-Aug 2000 

Location: Copenhagen, Denmark 

Outcome: RBC count, hemoglobin, 

platelet count, fibrinogen, PLAAS (2-

aminoadipic semialdehyde in plasma 

proteins), HBGGS (γ-glutamyl semialdehyde in hemoglobin), HBAAS (2-

aminoadipic semialdehyde in 

hemoglobin), MDA (malondialdehyde) 

Age Groups: 20-33 yr

Study Design: Panel (repeated 

measures) 

N: 50 students living and studying in 

central Copenhagen 

50 students examined each season (68 

subjects total 

31 participated in each season 

total of 195 measurements) 

Statistical Analyses: Mixed model 

repeated-measures analysis 

Covariates: Season, avg outdoor 

temperature, and sex 

Season: Repeated measures 4 times 

(once per season) 

Dose-response Investigated? No 

Statistical Package: SAS v8e 

Pollutant: Personal exposure to black 

carbon (10-6/m) 

Averaging Time: 48 h 

Median: 8.1 

Percentiles: Q25-Q75: 5.0-13.2 

Copollutant: 

Urban background PM2.5

Personal PM2.5 

PM Increment: 10-6/m 

Effect Estimate [Lower CI, Upper CI]: 

Relationship between exposure and 

biomarkers 

Estimate (p-value): RBC count (x 109/g 

protein): 0.0003 (0.75) 

Hemoglobin (μmol/g protein): 0.0004 

(0.65) 

Platelet count (x 106/g protein): 0.0009 

(0.51) 

Fibrinogen (nmol/g protein): -0.0027 

(0.29) 

PLAAS (pmol/mg protein): 0.0041 

(0.0009) 

HBGGS (pmol/mg protein): 0.0024 

(0.25) 

HBAAS (pmol/mg protein): 0.0022 (0.20)

MDA (pmol/mg protein): 0.0018 (0.30) 

December 2009 E-66 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sorensen et al. (2003, 

042700) 

Period of Study: Nov 1999-Aug 2000 

Location: Copenhagen, Denmark 

Outcome: RBC count, hemoglobin, 

platelet count, fibrinogen, PLAAS (2-

aminoadipic semialdehyde in plasma 

proteins), HBGGS (γ-glutamyl 

semialdehyde in hemoglobin), HBAAS 

(2-aminoadipic semialdehyde in 

hemoglobin), MDA (malondialdehyde) 

Age Groups: 20-33 yr

Study Design: Panel (repeated 

measures) 

N: 50 students living and studying in 

central Copenhagen 

50 students examined each season (68 

subjects total 

31 participated in each season 

total of 195 measurements) 

Statistical Analyses: Mixed model 

repeated-measures analysis 

Covariates: Season, avg outdoor 

temperature, and sex 

Season: Repeated measures 4 times 

(once per season) 

Dose-response Investigated? No 

Statistical Package: SAS v8e 

Pollutant: PM2.5 (urban background 

concentration) 

Averaging Time: 48 h 

Median: 9.2 μg/m3 

Percentiles: Q25-Q75: 5.3-14.8 

Copollutant: 

Urban background PM2.5

Personal carbon black 

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Relationship between exposure and 

biomarkers 

Estimate (p-value): RBC count (x 109/g 

protein): 0.0008 (0.36) 

Hemoglobin (μmol/g protein): 0.0005 

(0.53) 

Platelet count (x 106/g protein): -0.0008 

(0.49) 

Fibrinogen (nmol/g protein): 0.0004 

(0.84) 

PLAAS (pmol/mg protein): 0.0004 (0.76) 

HBGGS (pmol/mg protein): -0.0020 

(0.39) 

HBAAS (pmol/mg protein): -0.0021 

(0.29) 

MDA (pmol/mg protein): 0.0012 (0.52) 

Reference: Sullivan et al. (2007, 

100083) 

Period of Study: Feb 2000-Mar 2002 

Location: Seattle, Washington, USA 

Outcome: Blood CRP, fibrinogen, Ddimer 

Age Groups: >55 yr of age

Study Design: Panel study 

N: 47 elderly subjects 

Pollutant: PM2.5 

Averaging Time: 24 h 

Median (IQR): 7.7 μg/m3 (6.4)

Monitoring Stations: 1

Copollutant: Indoor PM2.5

PM Increment: 10 μg/m3

Effect Estimate: Among those with 

CVD, PM2.5 1 day earlier: CRP: 1.25 

(95% CI: 0.97, 1.58) 

Fibrinogen: 1.01 (95% CI: 0.97, 1.05) 

D-dimer: 1.04 (95% CI: 0.93, 1.15) 

With COPD: CRP: 0.69 (95% CI: 0.34, 

1.42) 

Fibrinogen: 1.05 (95% CI: 0.97, 1.13) 

D-dimer: 1.10 (95% CI: 0.95, 1.28) 

Healthy: CRP: 1.01 (95% CI: 0.85, 1.19) 

Fibrinogen: 0.88 (95% CI: 0.81, 0.95) 

D-dimer: 1.10 (95% CI: 0.75, 1.58)

Notes: Out of 47 subjects, n = 23 with 

CVD and n = 24 (n = 16 COPD and 8 

healthy) without CVD. Blood markers 

were measured on 2-3 morning over a 

5-10 day period, and outdoor PM2.5 was 

measured at a central monitoring site. 

These findings are not consistent with 

and effect of fine PM on markers of 

inflammation and thrombosis in the 

elderly. 

December 2009 E-67 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sullivan et al. (2005, 

109418) 

Period of Study: Feb 2000-Mar 2002 

Location: Seattle, Washington, USA 

Outcome: Heart rate variability (H, LF, 

HF, r-MSSD, SDNN) 

Study Design: Panel study 

N: 34 elderly subjects with (n = 21) and 

without (n = 13) CVD. 

Statistical Analysis: Linear mixed 

effects regression 

Pollutant: PM2.5 

Averaging Time: 1 h 

Median (IQR): 10.7 (7.6) 

Copollutant: CO, NO2

PM Increment: 10 μg/m3

Effect Estimate: 1 h: 

With CVD: HF: (3% increase, 95% CI: 

-19, 32) 

Without CVD: HF(5% decrease, 95% CI: 

-34, 36) 

Similarly, no association was found for 

4-h or 24-h mean PM2.5 concentrations. 

Notes: 285 daily 20 min HRV measures 

were made in the homes of study 

subjects over a 10-day period. 

December 2009 E-68 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sullivan et al. (2005, 

109418) 

Period of Study: Feb 2000-Mar 2002 

Location: Seattle area, WA 

Outcome (ICD9 and ICD10): Highsensitivity C-reactive protein (hs-CRP) 

fibrinogen 

D-dimer 

Endothelin-1 (ET-1) 

Interleukin-6 (IL-6 

Interleukin-6 receptor (IL-6r) 

Tumor necrosis factor-α (TNF-8- α) 

Tumor necrosis factor-receptors (p55, 

p75) 

Monocyte chemoattractant protein-1 

(MCP-1) 

Age Groups: ≥ 55 yr

Study Design: Panel (repeated 

measures) 

N: 47 participants with (23) and without 

(10 COPD and 8 healthy) CVD 

Statistical Analyses: Mixed models 

Covariates: Age, gender, medication 

use, meteorological variables 

(temperature and RH) 

Dose-response Investigated? No 

Statistical Package: SAS v8.02 

Pollutant: PM2.5 

Averaging Time: 24 h 

(0-day and 1-day lags) 

Mean (SD): NR 

Percentiles: For all subject-days: 

25th: 5.2 

50th: 7.7 

75th: 11.5 

90th: 19.9 

Range (Min, Max): 1.3, 33.9 

Monitoring Stations: NA, measured at 

participant’s residence 

Copollutant: None 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Multiplicative change in mean outcome 

associated with 10 μg/m3

 increase in PM 

Among those with different disease 

status. 

CRP Fold-rise (95%CI) 

CV 

0-day lag: 1.21 (0.86, 1.70) 

CV 

1-day lag: 1.25 (0.97, 1.58); 

COPD 

0-day lag: 0.93 (0.48, 1.80) 

COPD 

1-day lag: 0.69 (0.33, 1.46) 

Healthy 

0-day lag: 0.98 (0.88, 1.08) 

Healthy 

1-day lag: 1.01 (0.84 1.21) 

Fibrinogen Fold-rise (95%CI) 

CV 

0-day lag: 1.02 (0.98, 1.06) 

CV 

1-day lag: 1.0 (0.97, 1.03); 

COPD 

0-day lag: 1.0 (0.91, 1.09) 

COPD 

1-day lag: 1.08 (0.99, 1.17) 

Healthy 

0-day lag: 0.94 (0.87, 1.01) 

Healthy 

1-day lag: 0.99 (0.88, 1.17) 

D-dimer Fold-rise (95%CI) 

CV 

0-day lag: 1.02 (0.88, 1.17) 

CV 

1-day lag: 1.03 (0.93, 1.15); 

COPD 

0-day lag: 1.04 (0.93, 1.16) 

COPD 

1-day lag: 1.09 (0.94, 1.27) 

Healthy 

0-day lag: 0.95 (0.79, 1.14) 

Healthy 

1-day lag: 0.97 (0.71, 1.31) 

Among those with cardiovascular 

disease 

MCP-1 Fold-rise (95%CI) 

0-day lag: 1.3 (1.1, 1.7) 

1-day lag: 1.0 (0.9, 1.3) 

ET-1 Fold-rise (95%CI) 

0-day lag: 1.1 (0.8, 1.2) 

1-day lag: 1.1 (0.9, 1.2) 

Note: TNF-α and IL-6 measures were 

below the limit of detection of assays 

Reference: Timonen et al. (2006, 

088747) 

Period of Study: 1998-1999 

Location: Amsterdam, Netherlands 

Erfurt, Germany 

Helsinki, Finland 

Outcome: Heart variability (HRV) 

measurements: [LF, HF, LFHFR, NN 

interval, SDNN, r-MSSD] 

Study Design: Panel study 

N: 131 elderly subjects with stable 

coronary heart disease 

Statistical Analysis: Linear mixed 

models 

Pollutant: PM2.5 

Means: 

Amsterdam: 20.0 

Erfurt: 23.3 

Helsinki: 12.7 

Copollutant: NO2, CO 

PM Increment: 10 μg/m3

Effect Estimate: SDNN 

-0.33ms (95% CI: -1.05, 0.38) 

HF: -0.3% (95% CI: -10.6, 5.4) 

LFHFR: -1.4 (95% CI: -5.9, 8.7) 

Notes: Followed for 6 mo with biweekly 

clinic visits 

2-day lag. ULTRA Study 

December 2009 E-69 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Vallejo et al. (2006, 157081) 

Period of Study: Apr-Aug 2002 

Location: Mexico City metropolitan area 

Outcome: Heart rate variability 

measures (SDNN, pNN50) 

Age Groups: Mean age 27 yr

Study Design: Panel study 

N: 40 young healthy participants (nonsmokers, no meds or history of CVD, 

respiratory, neurological, or endocrine 

disease) 

Statistical Analysis: Linear mixed 

effects models 

Pollutant: PM2.5 

(pDR nephelometric method-DataRAM) 

Copollutant: None 

PM Increment: 30 μg/m3

Effect Estimate: pNN50: 

0 h lag: -0.01% (95% CI: -0.03, 0.01) 

1 h: -0.01% (95% CI: -0.04, 0.02) 

2 h: -0.05% (95% CI: -0.09, 0.00) 

3 h: -0.07% (95% CI: -0.13 to -0.02) 

4 h: -0.08% (95% CI: -0.14 to -0.01) 

5 h: -0.06% (95% CI: -0.13, 0.02) 

6 h: -0.05% (95% CI: -0.13, 0.04) 

SDNN: 

0 h: 0.00% (95% CI: 0.00, 0.01) 

1 h: 0.00% (95% CI: -0.01, 0.01) 

2 h: 0.00% (95% CI: -0.02, 0.01) 

3 h: -0.01% (95% CI: -0.02, 0.00) 

4 h: -0.01% (95% CI: -0.02, 0.01) 

5 h: -0.01% (95% CI: -0.02, 0.01) 

6 h: 0.00% (95% CI: -0.02, 0.02) 

Notes: Subjects underwent 13 h of ECG 

monitoring and personal PM2.5

measurement. HRV measures were 

regressed against different lags of PM2.5

concentration.

Reference: Van Hee et al. (2009, 

192110) 

Period of Study: Jul 2000-Aug 2002 

Location: Baltimore, Maryland 

Chicago, Illinois 

Winston-Salem, North Carolina 

St. Paul 

Minnesota 

New York, New York 

Los Angeles, California 

Outcome: Left Ventricular Mass Index 

and Ejection Fraction 

Age Groups: 45-84 yr

Study Design: Cross-sectional 

N: 3,827 participants 

Statistical Analyses: Linear Regression 

Models 

Covariates: Age, race, income, sex, 

education, medication use, LDL, HDL, 

physical activity, alcohol consumption, 

smoking, diabetes, systolic BP, diastolic 

BP 

Dose-response Investigated? No 

Statistical Package: Stata 

Lags Considered: NR 

Pollutant: PM2.5

Averaging Time: NR 

Mean (SD): Fig only 

Monitoring Stations: N/A 

Interpolation used 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: 10 μg/m3

Difference (Lower CI, Upper CI), pvalue: 

Left Ventricular Mass Index 

Unadjusted: -6.0 (-7.8, -4.2), <0.0001 

All covariates except center, BP: -6.1 (-

7.8, -4.4), <0.0001 

All covariates except BP: 3.7 (-6.0, 

13.4), 0.46 

Full model: 4.6 (-4.7, 13.9), 0.33 

Full model plus center/race interaction: 

3.8 (-6.1, 13.7), 0.45 

Left Ventricular Ejection Fraction 

Unadjusted: 3.0 (2.2, 3.8), <0.0001 

All covariates except center, BP: 1.4 

(0.5, 2.2), 0.001 

All covariates except BP: -1.1(-5.8, 3.7), 

0.66 

Full model: -1.3 (-6.0, 3.5), 0.60 

Full model plus center/race interaction: -

3.0 (-8.0, 2.0), 0.24 

Reference: Wellenius et al. (2007, 

092830) 

Period of Study: Feb 2002-Mar 2003 

Location: Boston, Massachusetts, USA 

Outcome: Circulating levels of B-type 

natriuretic peptide (BNP 

Measured in whole blood at 0, 6, 12 wk) 

Study Design: Panel study 

N: 28 subjects (each with chronic stable 

HF and impaired systolic function) 

Statistical Analysis: Linear mixed 

effects models 

Pollutant: PM2.5 

Copollutant: NO2, SO2, O3, CO, BC 

PM Increment: 10 μg/m3

Effect Estimate: Same day PM2.5: 0.8% 

increase in BNP (95% CI: -16.4, 21.5) 

Notes: The study found no association 

between any pollutant and measures of 

BNP at any lag. Further, the within 

subject coefficient of variation was large 

suggesting the magnitude of effected air 

pollutant health effects are small in 

relation to within subject variability in 

BNP. 

December 2009 E-70 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Wellenius et al. (2007, 

092830) 

Period of Study: Feb 2002-Mar 2003 

Location: Boston, Massachusetts 

Outcome (ICD9 and ICD10): B-type 

natriuretic peptide (BNP) (natural-log 

transformed) 

Age Groups: 33-88 yr

Study Design: Panel (blood collected at 

0, 6, and 12 wk) 

N: 28 patients with chronic stable heart 

failure and impaired systolic function 

Statistical Analyses: Linear mixedeffects models 

Covariates: Temperature, dew point, 

mean dew point over the past 3 days, 

calendar month of blood draw, measurement occasion, treatment 

assignment, measurement occasion by 

treatment assignment interaction 

Season: Adjusted for calendar month 

Dose-response Investigated? No 

Statistical Package: SAS v9.1 

Pollutant: PM2.5 

Averaging Time: Daily (assessed lags 

of 0-3 days)

Mean (SD): 10.9 (8.4) 

Percentiles: 50th: 8.0 μg/m3

Range (Min, Max): 0.7-50.9 μg/m3 

Monitoring Stations: 1 monitor 

Copollutant (correlation): 

CO (r = 0.35) 

NO2 (r = 0.31) 

SO2 (r = 0.18) 

O3 (r = 0.35) 

BC(r = 0.68) 

PM Increment: IQr = 8.1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

% change in BNP per IQR increase in 

PM2.5

Lag0: 1.5 (-18.7, 19.2) 

Lag1: 2.1 (-20.0, 30.3) 

Lag2: 1.3 (12.3, 17.1) 

Lag3: 5.6 (-16.8, 34.0) 

Note: No significant associations 

observed between any pollutant and 

BNP levels at any lags (presented in 

Fig 2) 

Reference: Wheeler et al. (2006, 

088453) 

Period of Study: Fall 1999 and spring 

2000 

Location: Atlanta, GA 

Outcome: Heart rate variability 

Age Groups: 49-76 yr

N: 18 subjects with COPD and 12 

subjects with a recent MI 

Statistical Analysis: Linear-mixed 

effect model 

Season: Fall and spring 

Pollutant: PM2.5

Averaging Time: 

1 h 

4 h 

24 h 

Mean: 24-h: 17.8 μg/m3

Copollutant: O3, CO, SO2, NO2

PM Increment: 11.65 μg/m3 (IQR) in 4 h 

PM2.5

Effect Estimate: Among COPD 

patients: 8.3% increase in SDNN (95% 

CI: 1.7, 15.3) 

Among MI patients: 2.9% decrease in 

SDNN (95% CI: -7.8, 2.3) 

Results for 1-h and 24-h averaging times 

were similar. 

Notes: Data was collected on 7 days in 

the fall of 1999 or spring of 2000. 

Effects were modified by medication 

use, baseline pulmonary function, and 

health status.

December 2009 E-71 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yeatts et al. (2007, 091266) 

Period of Study: 12-wk period b/t 

Sep 2003-Jul 2004 

Location: Chapel Hill, NC 

Outcome: Heart Rate Variability 

Age Groups: 21-50 yr 

Study Design: Panel 

N: 12 asthmatics 

Statistical Analyses: Linear Mixed 

Model 

Covariates: Temperature, humidity, 

pressure 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 1 day 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 12.5 (6.0)

Min: 0.6 

Max: 37.1 

Monitoring Stations: 1 

Copollutant: PM10-2.5, PM10

Co-pollutant Correlation: 

PM10-2.5 = 0.46* 

PM10 = NR 

*p < 0.01 

PM Increment: 1 μg/m3

Beta, SE (Lower CI, Upper CI), pvalue: 

HRV 

Max Heart Rate: 0.40, 0.43 (-0.45, 1.24), 

0.36 

ASDNN5: -0.07, 0.15 (-0.37, 0.22), 0.63 

SDANN5: 1.66, 0.65 (0.39, 2.93), 0.02 

SDNN24HR(mesc): 1.16, 0.58 (0.02, 

2.29), 0.06 

rMSSD: 0.53, 0.20 (0.14, 0.91), 0.01 

pNN50_24hr: -0.06, 0.11 (-0.27, 0.15), 

0.58 

pNN50_7min: 0.47, 0.42 (-0.35, 1.29), 

0.27 

Low-frequency power: -0.23, 0.14 (-0.51, 

0.05), 0.11 

Percent low frequency: -0.78, 0.41 (-

1.59, 0.03), 0.07 

High-frequency power: 0.14, 0.07 (-0.01, 

0.28), 0.07 

Percent high frequency: 0.64, 0.36 (-

0.07, 1.34), 0.09 

Blood Lipids 

Triglycerides: -0.63, 0.84 (-2.29, 1.02), 

0.46 

VLDL: -0.17, 0.22 (-0.61, 0.26), 0.44 

Total cholesterol: -0.06, 0.22 (-0.49, 

0.36), 0.77 

Hematologic Factor 

Circulating eosinophils: -0.02, 0.00 (-

0.02, -0.02), 0.27 

Platelets: -0.01, 0.45 (-0.88, 0.86), 0.98 

Circulating Proteins 

Plasminogen: 0.00, 0.00 (-0.01, 0.00), 

0.82 

Fibrenogen: 0.00, 0.01 (-0.01, 0.02), 

0.59 

Von Willibrand factor: -0.31, 0.29 (-0.87, 

0.25), 0.28 

Factor VII: -0.65, 0.33 (-1.29, -0.01), 

0.05 

December 2009 E-72 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yue et al. (2007, 097968) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: QT interval and T-wave 

amplitude for ECG recordings, and vWF, 

CRP from blood samples 

Study Design: Panel study 

N: 56 patients (male CAD patients with 

12 clinical visits) 

Statistical Analysis: Linear and logistic 

regression models 

Dose-response Investigated? No 

Pollutant: PM2.5, PNC (n/cm3) 

Averaging Time: Mean: 

Mass concentrations of PNC 

(0.1-2.84 n/cm3

) 

Monitoring Stations: 1 

Copollutant: None 

PM Increment: . IQR 

Effect Estimate: Each IQR increase in 

0-23 h mean traffic particle concentration 

was associated with: QT interval: 0.6% 

(95% CI: -0.3, 1.4) 

T wave amplitude: -1.6% (95% CI: -3.3, 

0.1) 

vWF: 3.2% (95% CI: -0.5, 7.0) 

CRP: (OR = 1.5 

95% CI 1.0-2.3) 

Each IQR increase in 0-23 h mean 

combustion-generated particle 

concentration was associated with: QT 

interval: 0.1%(-0.3, 0.6) 

T wave amplitude: -0.2% (-1.2, 0.7) 

vWF: 2.8% (0.8, 4.8) 

CRP (OR = 1.0 

0.8, 1.2) 

Notes: Five sources of particles were 

identified (airborne soil, local trafficrelated ultrafine particles, combustiongenerated aerosols, diesel traffic-related 

particles, and secondary aerosols).

Reference: Yue et al. (2007, 097968) 

Period of Study: 

Oct 12, 2000-Apr 27, 2001 

Location: Erfurt, Germany 

Outcome: QT interval, T wave 

amplitude, von Willebrand factor (vWF), 

C-reactive protein (CRP above 90th 

percentile compared to below) 

Age Groups: >50 yr 

Study Design: Panel (12 visits 

625 observations for repolarization 

parameters and 578 observations for 

inflammatory markers) 

N: 57 male coronary artery disease 

patients 

Statistical Analyses: Linear and logistic 

fixed-effects regression models 

(generalized additive models) 

Covariates: Trend, weekday, and 

meteorological variables (temperature, 

relative humidity, barometric pressure) 

Dose-response Investigated? No 

Statistical Package: SAS v9.1 and SPlus v6.0 

Pollutant: Five particle source factors 

(airborne soil, local traffic-related 

ultrafine particles, combustion-generated 

aerosols, diesel traffic-related particles, 

and secondary aerosols); see below for 

size fractions (factor scores) 

Averaging Time: Used daily factor 

scores in analyses

Mean (SD): 

Factor 1: particles from airborne soil 

(1.0-2.8 μm): 2390 (1696) 

Factor 2: ultrafine particles from local 

traffic (0.01-0.1 μm): 9931 (5858) 

Factor 3: secondary aerosols from local 

fuel combustion (0.1-0.5 μm): 3770 

(6129) 

Factor 4: particles from traffic (0.01-

0.5 μm): 6865 (5689) 

Factor 5: secondary aerosols from 

multiple sources (0.2-1.0 μm): 4732 

(3890) 

Median: 

Factor 1: 2053 

Factor 2: 8531 

Factor 3: 1348 

Factor 4: 5045 

Factor 5: 3752 

IQR (5-day avg): 

Factor 1: 1110 

Factor 2: 5749 

Factor 3: 4124 

Factor 4: 5000 

Factor 5: 3393 

Range (Min, Max): 

Factor 1: 284, 12960 

Factor 2: 866, 26632 

Factor 3: 139, 39097 

Factor 4: 283, 27605 

Factor 5: 67, 20129 

Monitoring Stations: 1 monitor 

PM Increment: IQR 

Effect Estimate [Lower CI, Upper CI]: 

QT interval, % change (95%CI) 

Factor 1: 

0-5 h: -0.1 (-0.6, 0.6) 

6-11 h: -0.5 (-1.1, 0.2) 

12-17 h: 0.1 (-0.4, 0.4) 

18-23 h: -0.2 (-0.7, 0.2) 

0-23 h: -0.2 (-0.9, 0.4) 

1 day: -0.1 (-0.7, 0.6) 

2 day: -0.3 (-0.9, 0.4) 

3 day: -0.7 (-1.4, 0.1) 

4 day: -0.2 (-0.9, 0.5) 

0-4 day avg: -0.7 (-1.8, 0.3) 

Factor 2: 

0-5 h: 0.2 (-0.4, 0.8) 

6-11h: 0.8 (-0.0, 1.7) 

12-17 h: 0.6 (-0.2, 1.4) 

18-23 h: 0.5 (-0.4, 1.4) 

0-23 h: 0.9 (-0.1, 2.0) 

1 day: 1.5 (0.3, 2.7) 

2 day: -0.4 (-1.7, 1.0) 

3 day: 0.5 (-0.9, 1.9) 

4 day: 0.1 (-1.2, 1.4) 

0-4 day avg: 1.6 (-0.1, 3.3) 

Factor 3: 

0-5 h: 0.1 (-0.3, 0.5) 

6-11 h: 0.2 (-0.3, 0.6) 

12-17 h: 0.2 (-0.3, 0.6) 

18-23 h: 0.1 (-0.3, 0.4) 

0-23 h: 0.1 (-0.3, 0.6) 

1 day: 0.1 (-0.3, 0.4) 

2 day: -0.1 (-0.4, 0.3) 

3 day: -0.2 (-0.5, 0.2) 

4 day: -0.1 (-0.5, 0.2) 

0-4 day avg: -0.1 (-0.7, 0.6) 

Factor 4: 

0-5 h: 0.2 (-0.4, 0.8) 

6-11 h: 0.8 (0.0, 1.6) 

12-17 h: 0.5 (-0.2, 1.3) 

18-23 h: 0.5 (-0.2, 1.2) 

0-23 h: 0.6 (-0.3, 1.4) 

1 day: -0.4 (-1.5, 0.7) 

2 day: -0.9 (-2.0, 0.1) 

3 day: -0.5 (-1.4, 0.5) 

December 2009 E-73 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Copollutant: NA 4 day: -0.5 (-1.3, 0.2) 

0-4 day avg: -0.3 (-1.7, 1.1) 

Factor 5: 

n0-5 h: 1.0 (-0.1, 2.1) 

6-11 h: 0.9 (-0.2, 2.0) 

12-17 h: 0.3 (-0.7, 1.4) 

18-23 h: -0.1 (-1.2, 1.0) 

0-23h: 0.7 (-0.6, 1.9) 

1 day: 0.1 (-1.1, 1.3) 

2 day: -0.2 (-1.5, 1.1) 

3 day: -0.6 (-1.9, 0.8) 

4 day: -0.9 (-2.0, 0.2) 

0-4 day avg: -0.4 (-1.9, 1.2) 

T wave amplitude, % change (95%CI)

Factor 1: 

0-5 h: -0.3 (-1.5, 0.9) 

6-11 h: -0.6 (-1.9, 0.7) 

12-17 h: 0.1 (-0.8, 0.9) 

18-23 h: -0.6 (-1.5, 0.4) 

0-23 h: -0.5 (-1.8, 0.9) 

1 day: 0.4 (-0.9, 1.7) 

2 day: 1.2 (-0.3, 2.7) 

3 day: 0.2 (-1.2, 1.7) 

4 day: -0.2 (-1.3, 1.0) 

0-4 day avg: 0.8 (-1.1, 2.6) 

Factor 2: 

0-5 h: -1.7 (-3.0 to -0.4) 

6-11 h: -2.6 (-4.5 to -0.6) 

12-17 h: -1.0 (-2.6, 0.7) 

18-23 h: -1.1 (-2.8, 0.7) 

0-23 h: -3.1 (-5.3 to -0.9) 

1 day: -0.3 (-2.9, 2.2) 

2 day: -1.2 (-4.1, 1.7) 

3 day: -0.5 (-3.2, 2.1) 

4 day: -3.4 (-9.9, 3.1) 

0-4 day avg: -1.5 (-4.4, 1.5) 

Factor 3: 

0-5 h: -0.3 (-1.1, 0.6) 

6-11 h: -0.1 (-0.9, 0.9) 

12-17 h: 0.1 (-0.9, 1.0) 

18-23 h: -0.4 (-1.2, 0.4) 

0-23 h: -0.2 (-1.2, 0.7) 

1 day: 0.1 (-0.7, 0.8) 

2 day: -0.1 (-0.7, 0.7) 

3 day: 0.4 (-0.3, 1.1) 

4 day: 0.1 (-0.7, 0.7) 

0-4 day avg: 0.3 (-0.9, 1.5) 

Factor 4: 

0-5 h: -1.5 (-2.8 to -0.2) 

6-11 h: -1.3 (-3.0, 0.3) 

12-17 h: -1.1 (-2.7, 0.4) 

18-23 h: -0.9 (-2.4, 0.6) 

0-23 h: -1.6 (-3.3, 0.1) 

1 day: -1.2 (-3.3, 0.9) 

2 day: -1.0 (-3.2, 1.2) 

3 day: 0.2 (-1.5, 1.9) 

4 day: 0.5 (-1.0, 2.0) 

0-4 day avg: -1.7 (-4.1, 0.7) 

Factor 5: 

0-5 h: -1.6 (-3.6, 0.4) 

6-11 h: -0.1 (-2.1, 2.0) 

12-17 h: -0.2 (-2.2, 1.8) 

18-23 h: -1.8 (-3.8, 0.2) 

0-23 h: -1.2 (-3.4, 1.0) 

1 day: -1.8 (-4.2, 0.6) 

2 day: -0.7 (-3.5, 2.1) 

3 day: 0.8 (-1.5, 3.2) 

4 day: 0.5 (-1.5, 2.5) 

0-4 day avg: -1.4 (-4.0, 1.2) 

vWF, % change (95%CI)Factor 1: 

0-5 h: 1.1 (-1.5, 3.6) 

6-11 h: 1.6 (-1.2, 4.5) 

12-17 h: 0.4 (-1.4, 2.1) 

18-23 h: 1.4 (-0.6, 3.5) 

0-23 h: 1.6 (-1.3, 4.4) 

1 day: -1.0 (-3.9, 1.9) 

2 day: -1.8 (-4.8, 1.2) 

December 2009 E-74 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

3 day: -2.5 (-5.8, 0.9) 

4 day: 0.5 (-2.9, 3.9) 

0-4 day avg: -2.5 (-7.1, 2.2) 

Factor 2: 

0-5 h: 0.4 (-2.4, 3.2) 

6-11 h: -0.4 (-4.3, 3.4) 

12-17 h: 2.1 (-1.4, 5.7) 

18-23 h: 2.3 (-1.4, 5.9) 

0-23 h: 1.9 (-2.8, 6.6) 

1 day: 2.8 (-2.8, 8.3) 

2 day: 5.1 (-0.8, 11.1) 

3 day: 11.4 (5.3, 17.6) 

4 day: 6.6 (0.0, 13.1) 

0-4 day avg: 11.4 (3.7, 19.1) 

Factor 3: 

0-5 h: 1.8 (0.1, 3.6) 

6-11 h: 1.7 (-0.3, 3.7) 

12-17 h: 2.2 (0.3, 4.2) 

18-23 h: 2.8 (1.1, 4.5) 

0-23 h: 2.8 (0.8, 4.8) 

1 day: 2.7 (1.0, 4.4) 

2 day: 3.4 (1.8, 5.0) 

3 day: 2.3 (0.8, 3.8) 

4 day: 1.4 (-0.2, 2.9) 

0-4 day avg: 4.8 (2.0, 7.6) 

Factor 4: 

0-5h: 1.5 (-1.4, 4.3) 

6-11h: 2.0 (-1.7, 5.6) 

12-17h: 2.6 (-0.8, 5.9) 

18-23h: 3.5 (0.4, 6.6) 

0-23h: 3.2 (-0.5, 7.0) 

1 day: 5.4 (0.6, 10.2) 

2 day: 4.5 (-0.6, 9.5) 

3 day: 3.8 (-0.6, 8.1) 

4 day: 3.0 (-0.6, 6.6) 

0-4d avg: 11.3 (5.0, 17.6) 

Factor 5: 

0-5 h: 1.9 (-2.8, 6.6) 

6-11 h: 3.2 (-1.6, 8.0) 

12-17 h: 2.4 (-2.3, 7.1) 

18-23 h: 1.6 (-3.1, 6.2) 

0-23 h: 2.9 (-2.5, 8.2) 

1 day: -2.2 (-7.6, 3.2) 

2 day: -1.3 (-7.4, 4.9) 

3 day: 1.1 (-4.8, 7.1) 

4 day: 1.3 (-4.2, 6.7) 

0-4 day avg: 3.3 (-4.1, 10.6) 

CRP, Odds Ratio (95%CI) 

Factor 1

0-5 h: 0.9 (0.7, 1.1) 

6-11 h: 1.4 (1.1, 1.8) 

12-17 h: 1.2 (1.0, 1.4) 

18-23 h: 1.0 (0.8, 1.3) 

0-23 h: 1.1 (0.9, 1.5) 

1 day: 1.4 (1.1, 1.8) 

2 day: 1.3 (1.0, 1.7) 

3 day: 1.0 (0.7, 1.4) 

4 day: 1.1 (0.9, 1.5) 

0-4 day avg: 1.6 (1.1, 2.2) 

Factor 2

0-5h: 0.8 (0.6, 1.0) 

6-11h: 1.0 (0.7, 1.4) 

12-17h: 1.1 (0.8, 1.5) 

18-23h: 1.0 (0.8, 1.4) 

0-23h: 0.9 (0.6, 1.4) 

1 day: 0.9 (0.6, 1.5) 

2 day: 2.1 (1.3, 3.3) 

3 day: 1.9 (1.0, 3.6) 

4 day: 1.4 (0.8, 2.3) 

0-4d avg: 1.4 (0.8, 2.6) 

Factor 3

0-5 h: 1.0 (0.8, 1.1) 

6-11 h: 0.9 (0.8, 1.1) 

12-17 h: 1.0 (0.9, 1.2) 

18-23 h: 1.0 (0.8, 1.2) 

0-23 h: 1.0 (0.8, 1.2) 

1 day: 1.1 (1.0, 1.3) 

December 2009 E-75 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

2 day: 1.0 (0.9, 1.2) 

3 day: 1.2 (1.1, 1.4) 

4 day: 1.1 (1.0, 1.3) 

0-4 dY avg: 1.2 (1.0, 1.5) 

Factor 4

0-5 h: 0.8 (0.6, 1.1) 

6-11 h: 0.8 (0.6, 1.1) 

12-17 h: 1.3 (1.0, 1.8) 

18-23 h: 1.1 (0.8, 1.5) 

0-23 h: 1.0 (0.7, 1.4) 

1 day: 1.5 (1.0, 2.3) 

2 day: 2.0 (1.3, 3.2) 

3 day: 1.5 (0.9, 2.3) 

4 day: 1.3 (0.9, 1.8) 

0-4 day avg: 1.7 (1.0, 2.9) 

Factor 5

0-5 h: 0.7 (0.5, 1.1) 

6-11 h: 1.4 (0.9, 2.1) 

12-17 h: 1.9 (1.3, 2.8) 

18-23 h: 1.4 (1.0, 2.0) 

0-23 h: 1.4 (0.9, 2.2) 

1 day: 1.6 (1.0, 2.6) 

2 day: 1.6 (0.9, 2.6) 

3 day: 2.3 (1.3, 4.1) 

4 day: 1.6 (0.9, 2.8) 

0-4 day avg: 2.1 (1.2, 3.8) 

Reference: Zanobetti et al. (2004, 

087489) 

Period of Study: 1999-2001 

Location: Boston, Massachusetts, USA 

Outcome: Blood pressure (systolic 

blood pressure, diastolic blood pressure, 

mean arterial blood pressure) 

Age Groups: Elderly

Study Design: Panel study 

N: 62 elderly subjects with n = 631 

repeated visits for cardiac rehabilitation 

Statistical Analysis: Linear mixed 

effects models 

Pollutant: PM2.5

Averaging Time: 24 h 

Median (10th-90th percentile) 

Median: 8.8 μg/m3

10th-90th: 13.4 

Monitoring Stations: 1

Copollutant: SO2, O3, CO, NO2, BC 

120-h avg 

Median: 0.651 

10th-90th: 0.376 

PM Increment: .10.4 μg/m3 for 5-day 

mean, 13.9 μg/m3 for 2-day mean 

Effect Estimate: Each 10.4 μg/m3

increase in 5-day mean PM2.5

concentration was associated with: 

Systolic BP: 2.8mmHg (95% CI: 0.1, 5.5)

Diastolic BP: 2.7mmHg (95% CI: 1.2, 

4.3) 

Mean arterial BP: 2.7mmHg (95% CI: 

1.0, 4.5) 

Each 13.9 μg/m3

 increase in 2-day mean 

PM2.5, during exercise in person with 

H.70bpm 

Diastolic: 7.0mmHg (95% CI: 2.3, 12.1) 

Mean arterial BP: 4.7mmHg (95% CI: 

0.5, 9.1) 

December 2009 E-76 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zeka et al. (2006, 157177) 

Period of Study: Nov 2000-Dec 2004 

Location: Greater Boston area 

(Massachusetts) 

Outcome: White blood cells (WBC), Creactive protein (CRP), sediment rate, 

fibrinogen 

Age Groups: Mean age (SD) = 73.0 

(6.7)

Study Design: Cross-sectional 

N: 710 subjects 

Statistical Analyses: Linear regression 

Covariates: Age, BMI, season (also 

assessed potential for confounding by 

temperature, RH, barometric pressure, 

hypertensive or cardiac medications, 

hypertension, smoking, alcohol, and 

fasting glucose levels) 

Dose-response Investigated? No 

Pollutant: BC 

Averaging Time: Hourly (PN, BC, 

PM2.5) and 24-h (SO4

2–) measurements 

used to create 48-h, 1-wk, and 4-wk ma 

Mean (SD): 0.77 (0.63) 

Percentiles: 50th: 0.61 

75th: 1.00 

90th: 1.51 

Monitoring Stations: 2 sites 

Units: ng/m3

Copollutant (correlation): 

PM2.5 (r = 0.52) 

BC 

PN (r = 0.30) 

SO4

2– (r = 0.30) 

PM Increment: 1 SD increase

Effect Estimate [Lower CI, Upper CI]: 

% increase (95%CI) in biomarker per 1 

SD increase in pollutant.

Fibrinogen

48 h: 0.84 (-0.63, 2.31) 

1 wk: 0.60 (-0.95, 2.15) 

4 wk: 1.78 (0.19, 3.36) 

CRP

48 h: 4.51 (-2.03, 11.06) 

1 wk: 1.07 (-5.55, 7.68) 

4 wk: 5.41 (-1.00, 11.81) 

Sediment rate

48 h: -4.56 (-25.55, 16.43) 

1 wk: 1.98 (-18.15, 22.11) 

4 wk: 21.65 (1.48, 41.82) 

WBC count

48 h: -0.63 (-2.45, 1.19) 

1 wk: -0.13 (-1.87, 1.60) 

4 wk: -0.55 (-2.36, 1.26) 

Note: No statistically significant 

difference was reported for any category 

of effect modifiers (age, obesity, 

medications, homozygous for the 

deletion of GSTM1-null, hypertension) 

However, results suggested almost all 

the effect of BC on sediment rate was 

among the younger group (<78 yr) 

There was a 4-fold difference for the 

association between BC and CRP in the 

presence of obesity 

Also evidence for effect modification by 

obesity of the association between BC 

and sediment rate 

There was a suggestive greater effect of 

BC on CRP among GSTM1-null subjects 

(9.73% [1.48, 17.98]) vs.. GSTM1-

present subjects (-2.97% [-14.05, 8.10] 

for concentrations 4-wk prior) 

A stronger effect of BC on sediment rate 

was seen among non-users of statins 

(36.01% [13.88, 58.13]) vs.. users 

(-12.29% [39.13, 14.55]) 

Reference: Zeka et al. (2006, 157177) 

Period of Study: Nov 2000-Dec 2004 

Location: Greater Boston area 

(Massachusetts) 

Outcome: White blood cells (WBC), Creactive protein (CRP), sediment rate, 

fibrinogen 

Age Groups: Mean age (SD) = 73.0 

(6.7)

Study Design: Cross-sectional 

N: 710 subjects 

Statistical Analyses: Linear regression 

Covariates: Age, BMI, season (also 

assessed potential for confounding by 

temperature, RH, barometric pressure, 

hypertensive or cardiac medications, 

hypertension, smoking, alcohol, and 

fasting glucose levels) 

Dose-response Investigated? No 

Pollutant: SO4

2– 

Averaging Time: Hourly (PN, BC, 

PM2.5) and 24-h (SO4

2–) measurements 

used to create 48-h, 1-wk, and 4-wk ma 

Mean (SD): 2.29 (1.62) 

Percentiles: 

50th: 1.84 

75th: 2.81 

90th: 4.10 

Monitoring Stations: 2 sites 

Copollutant (correlation): 

PM2.5 (r = 0.50) 

BC (r = 0.30) 

PN (r = -0.15) 

SO4

2– 

PM Increment: 1 SD increase

Effect Estimate [Lower CI, Upper CI]: 

% increase (95%CI) in biomarker per 1 

SD increase in pollutant. 

Fibrinogen: 

48 h: 0.60 (-1.23, 2.42) 

1 wk: 0.03 (-1.93, 1.99) 

4 wk: 1.12 (-0.52, 2.77) 

CRP: 

48 h: 1.57 (-7.13, 10.27) 

1 wk: 0.21 (-8.27, 8.69) 

4 wk: 5.29 (-1.91, 12.49) 

Sediment rate: 

48 h: 4.05 (-23.26, 31.36) 

1 wk: -5.87 (-32.39, 20.64) 

4 wk: -1.60 (-25.24, 22.04) 

WBC count: 

48 h: -0.12 (-2.35, 2.11) 

1 wk: -0.48 (-2.87, 1.90) 

4 wk: 0.75 (-1.30, 2.80) 

Note: No statistically significant 

difference was reported for any category 

of effect modifiers (age, obesity, 

medications, homozygous for the 

deletion of GSTM1-null, hypertension) 

December 2009 E-77 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zeka et al. (2006, 157177) 

Period of Study: Nov 2000-Dec 2004 

Location: Greater Boston area 

(Massachusetts) 

Outcome (ICD9 and ICD10): White 

blood cells (WBC), C-reactive protein 

(CRP), sediment rate, fibrinogen 

Age Groups: Mean age (SD) = 73.0 

(6.7)

Study Design: Cross-sectional 

N: 710 subjects 

Statistical Analyses: Linear regression 

Covariates: Age, BMI, season (also 

assessed potential for confounding by 

temperature, RH, barometric pressure, 

hypertensive or cardiac medications, 

hypertension, smoking, alcohol, and 

fasting glucose levels) 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM2.5

Averaging Time: Hourly (PN, BC, 

PM2.5) and 24-h (SO4

2–) measurements 

used to create 48-h, 1-wk, and 4-wk ma 

Mean (SD): 11.16 (7.95) 

Percentiles: 

50th: 9.39 

75th: 14.57 

90th: 21.48 

Monitoring Stations: 2 sites 

Copollutant (correlation): 

PM2.5 

BC (r = 0.52) 

PN (r = -0.02) 

SO4

2– (r = 0.50) 

PM Increment: 1 SD increase

Effect Estimate [Lower CI, Upper CI]: 

% increase (95%CI) in biomarker per 1 

SD increase in pollutant. 

Fibrinogen: 48 h: -0.18 (-1.93, 1.57) 

1 wk: -1.39 (-3.46, 0.67) 

4 wk: 1.14 (-0.60, 2.88) 

CRP: 48 h: -4.88 (-13.29, 3.53) 

1 wk: -1.37 (-10.44, 7.71) 

4 wk: 4.36 (-3.25, 11.96) 

Sediment rate: 48 h: -16.91 (-43.66, 

9.84) 

1 wk: -18.89 (-47.48, 9.70) 

4 wk: 24.93 (0.68, 49.18) 

WBC count: 48 h: -3.18 (-5.39 to -0.97) 

1 wk: -0.51 (-3.02, 2.00) 

4 wk: -0.03 (-2.17, 2.10) 

Note: No statistically significant 

difference was reported for any category 

of effect modifiers (age, obesity, 

medications, homozygous for the 

deletion of GSTM1-null, hypertension) 

Reference: Zhang et al. (2009, 191970) 

Period of Study: 1999-2003 

Location: U.S. 

Outcome: Myocardial Ischemia 

Age Groups: 52-90

Study Design: Panel 

N: 55,529 

Statistical Analyses: Logistic & Linear 

Regression 

Covariates: 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, season 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-5-day 

Pollutant: PM2.5 

Averaging Time: NR 

Mean (SD): 

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: 13.9 (7) 

Monitoring Stations: NR‡ 

Co-pollutant: NR 

‡ Monitors used in model for spatial 

interpolation of daily PM values. 

PM Increment: 10 μg/m3

Odds Ratio (Lower CI, Upper CI), lag: 

Minnesota Codes* 

MC4: 1.04 (0.97, 1.10), lag 0-2 

MC4: 1.04 (0.98, 1.11), lag 3-5 

MC5: 1.05 (1.00, 1.09), lag 0-2 

MC5: 1.04 (1.00, 1.08), lag 3-5 

MC 4 or 5: 1.04 (1.00, 1.09), lag 0-2 

MC 4 or 5: 1.03 (0.99, 1.07), lag 3-5 

Change (Lower CI, Upper CI), lag: 

ST-segment amplitude 

Lead I: -0.07 (-0.36, 0.21), lag 0-2 

Lead I: 0.18 (-0.10, 0.46), lag 3-5 

Lead II: -0.12 (-0.47, 0.23), lag 0-2 

Lead II: 0.16 (-0.18, 0.50), lag 3-5 

Lead aVL: -0.01 (-0.25, 0.23), lag 0-2 

Lead aVL: 0.11 (-0.12, 0.34 ), lag 3-5 

Lead V1: -0.02 (-0.39, 0.35), lag 0-2 

Lead V1: -0.22 (-0.58, 0.14), lag 3-5 

Lead V2: 0.07 (-0.57, 0.70), lag 0-2 

Lead V2: -0.01 (-0.61, 0.62), lag 3-5 

Lead V3: -0.11 (-0.68, 0.47), lag 0-2 

Lead V3: -0.02 (-0.58, 0.54), lag 3-5 

Lead V4: -0.0.3 (-0.51, 0.45), lag 0-2 

Lead V4: 0.24 (-0.23, 0.71), lag 3-5 

Lead V5: -0.01 (-0.41, 0.39), lag 0-2 

Lead V5: 0.35 (-0.04, 0.74), lag 3-5 

Lead V6: 0.02 (-0.30, 0.33), lag 0-2 

Lead V6: 0.35 (0.04, 0.65), lag 3-5 

T-wave amplitude 

Lead I: -1.60 (-3.07, -0.13), lag 0-2 

Lead I: -0.31 (-1.73, 1.11), lag 3-5 

Lead II: -0.54 (-1.99, 0.92), lag 0-2 

Lead II: 0.71 (-0.70, 2.13), lag 3-5 

Lead aVL: -1.21 (-2.50, 0.10), lag 0-2 

Lead aVL: -0.55 (-1.18, 0.71), lag 3-5 

Lead V1: 1.45 (-0.16, 3.06), lag 0-2 

Lead V1: 0.03 (-1.53, 1.59), lag 3-5 

Lead V2: -0.18 (-2.96, 2.60), lag 0-2 

Lead V2: 0.57 (-2.12, 3.27), lag 3-5 

Lead V3: -2.33 (-5.15, 0.49), lag 0-2 

Lead V3: -0.13 (-2.87, 2.60), lag 3-5 

Lead V4: -2.03 (-4.69, 0.63), lag 0-2 

Lead V4: 0.64 (-1.94, 3.22), lag 3-5 

Lead V5: -1.92 (-4.22, 0.38), lag 0-2 

Lead V5: 0.55 (-1.69, 2.78), lag 3-5 

Lead V6: -0.63 (-2.36, 1.10), lag 0-2 

Lead V6: 0.82 (-0.86, 2.49), lag 3-5 

QRS/T angles and heart rate (change) 

December 2009 E-78 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

QRS/T angle-spatial (°): 0.19 (-0.21, 

0.59), lag 0-2 

QRS/T angle-spatial (°): -0.20 (-0.59, 

0.19), lag 3-5 

QRS/T angle-frontal (°): 0.13 (-0.24, 

0.50), lag 0-2 

QRS/T angle-frontal (°): 0.35 (-0.01, 

0.71), lag 3-5 

Heart Rate (beats/min): 0.16 (0.02, 

0.30), lag 0-2 

Heart Rate (beats/min): 0.04 (-0.10, 

0.18), lag 3-5 

*Any ST abnormality (MC 4.1-4.4) 

Any T abnormality (MC 5.1-5.4) 

1

All units expressed in μg/m3 unless otherwise specified. 

Table E-4. Short-term exposure-cardiovascular morbidity studies: Other size fractions. 

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Adar et al. (2007, 001458) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, Missouri 

Outcome: Heart rate variability: heart 

rate, standard deviation of all normal-tonormal intervals (SDNN), square root of 

the mean squared difference between 

adjacent normal-to-normal intervals 

(rMSSD), percentage of adjacent 

normal-to-normal intervals that differed 

by more than 50 ms (pNN50), high 

frequency power (HF in the range of 

0.15-0.4Hz), low frequency power (LF, 

in the range of 0.04-0.15Hz), and the 

ratio of LF/HF 

Age Groups: ≥ 60 yr

Study Design: Panel (4 planned 

repeated measures with a total of 158 

person-trips 35 participating in all 4 

trips) 

N: 44 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: Subject, weekday, time, 

apparent temperature, trip type, activity, 

medications, and autoregressive terms 

Season: Limited data collection period 

Dose-response Investigated? No 

Statistical Package: SAS v8.02, R 

v2.0.1 

Pollutant: Particle count fine (PC fine) 

(particles/cm3

) 

Averaging Time: Measurements 

collected over 48-h period surrounding 

the bus trip (during which health 

endpoints were measured) used to 

calculate 5-, 30-, 60-min, 4-h, 24-h ma 

Median (IQR): 

All: 42 (57) 

Facility: 36 (45) 

Bus: 105 (96) 

Activity: 50 (133) 

Lunch: 69 (48) 

Monitoring Stations: 2 portable carts 

Copollutant: 

PM2.5 

BC 

Fine particle counts 

Coarse particle counts 

Correlation notes: 24-h mean PM2.5, 

BC, and fine particle count 

concentrations ranged from 0.80 to 0.98

r = 0.76 to 0.97 when limited to time 

spent on the bus 

r = 0.55 to 0.86 when comparing bus 

concentrations to 24-h ma 

r = -0.003 to 0.51 when comparing 5-

min avg and 24-h ma. Poor correlations 

found between coarse particle count 

concentrations and all fine particulate 

measures during all times periods 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

% change (95%CI) in HRV per IQR in 

the 24-h ma of the microenvironmental 

pollutant (IQr = 39 pt/cm3) 

Single-pollutant models

SDNN: -5.1 (-5.8 to -4.4) 

rMSSD: -8.0 (-8.7 to -7.2) 

pNN50 + 1: -10.2 (-11.3 to -9.0) 

LF: -9.9 (-11.4 to -8.4) 

HF: -13.7 (-15.1 to -12.2) 

LF/HF: 4.3 (3.1, 5.5) 

H: 0.9 (0.8, 1.1) 

Note: Exposure to health associations 

by all lag periods presented in Fig 2 

(magnitude of associations increased 

with averaging period, with the largest 

associations consistently found for 24-h 

ma) 

December 2009 E-79 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Adar et al. (Adar et al., 

2007, 001458) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, Missouri 

Outcome: Heart rate variability: heart 

rate, standard deviation of all normal-tonormal intervals (SDNN), square root of 

the mean squared difference between 

adjacent normal-to-normal intervals 

(rMSSD), percentage of adjacent 

normal-to-normal intervals that differed 

by more than 50 ms (pNN50), high 

frequency power (HF in the range of 

0.15-0.4Hz), low frequency power (LF, 

in the range of 0.04-0.15Hz), and the 

ratio of LF/HF 

Age Groups: ≥ 60 yr

Study Design: Panel (4 planned 

repeated measures with a total of 158 

person-trips 

35 participating in all 4 trips) 

N: 44 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: Subject, weekday, time, 

apparent temperature, trip type, activity, 

medications, and autoregressive terms 

Season: Limited data collection period 

Dose-response Investigated? No 

Statistical Package: SAS v8.02, R 

v2.0.1 

Pollutant: Particle count coarse (PT 

coarse) (pt/cm3

) 

Averaging Time: Measurements 

collected over 48-h period surrounding 

the bus trip (during which health 

endpoints were measured) used to 

calculate 5-, 30-, 60-min, 4-h, and 24-h 

ma 

Median (IQR): 

All: 0.02 (0.11) 

Facility: 0.01 (0.04) 

Bus: 0.16 (0.13) 

Activity: 0.29 (0.26) 

Lunch: 0.16 (0.36) 

Monitoring Stations: 2 portable carts 

Copollutant: 

PM2.5

BC 

Fine particle counts 

Coarse particle counts 

Correlation notes: 24-h mean PM2.5, 

BC, and fine particle count 

concentrations ranged from 0.80 to 0.98

r = 0.76 to 0.97 when limited to time 

spent on the bus 

r = 0.55 to 0.86 when comparing bus 

concentrations to 24-h ma 

r = -0.003 to 0.51 when comparing 5-

min avg and 24-h ma. Poor correlations 

found between coarse particle count 

concentrations and all fine particulate 

measures during all times periods 

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

% change (95%CI) in HRV per IQR in 

the 24-h ma of the microenvironmental 

pollutant (IQr = 0.066 pt/cm3

) 

Single-pollutant models

SDNN: 2.4 (1.3, 3.6) 

rMSSD: 3.9 (2.6, 5.1) 

pNN50 + 1: 2.9 (1.0, 4.9) 

LF: 6.4 (3.7, 9.1) 

HF: 10.2 (7.4, 13.1) 

LF/HF: -3.3 (-5.0 to -1.6) 

H: -1.1 (-1.3 to -0.8) 

Two-pollutant models (with PM2.5): 

SDNN: -0.7 (-1.9, 0.6) 

rMSSD: -1.3 (-2.6 to -0.05) 

pNN50 + 1: -4.3 (-6.3 to -2.4) 

LF: 0.2 (-2.5, 3.0) 

HF: 1.3 (-1.5, 4.1) 

LF/HF: -0.9 (-2.7, 1.0) 

H: -0.6 (-0.9 to -0.4) 

Note: Exposure to health associations 

by all lag periods presented in Fig 2 

(magnitude of associations increased 

with averaging period, with the largest 

associations consistently found for 24-h 

ma) 

Reference: Delfino et al. (2008, 

156390) 

Period of Study: 2005-2006 

Location: Los Angeles, California, air 

basin 

Outcome: C-reactive protein (CRP) 

Fibrinogen, tumor necrosis factor-α

(TNF-α) and its soluble receptor-II 

(TNF-RII) 

Interleukin-6 (IL-6) and its soluble 

receptor (IL-6sR) 

Fibrin D-dimer 

Soluble platelet selectin (sP-selectin) 

Soluble vascular cell adhesion molecule-1 (sVCAM-1) 

Intracellular adhesion molecule-1 

(sICAM-1) and myeloperoxidase (MPO) 

Erythrocyte lysates for glutathione 

peroxidase-1 (GPx-1) 

Copper-zinc superoxide dismutase (cu, 

Zn-SOD) 

Age Groups: ≥ 65 yr 

Study Design: Panel (biomarkers 

measured weekly 12 times) 

N: 29 participants (nonsmoking with 

history of coronary artery disease) 

Statistical Analyses: Mixed models 

Covariates: temperature (infectious 

illnesses were excluded by excluding 

weeks with such observations) 

Season: Collected 6 wk of data during 

warm period and 6 wk of data during 

Pollutant: PM (multiple size fractions 

and components) 

Averaging Time: 24-h avg preceding 

the blood draw (lag 0) and cumulative 

avg up to 5 days preceding the draw

Outdoor hourly PM: EC: Mean (SD): 

1.61 (0.62) 

Median: 1.56 

IQR: 0.92 

Min, Max: 0.24, 3.94 

OC: Mean (SD): 5.94 (2.11) 

Median: 5.58 

IQR: 2.79 

Min-Max: 2.51, 13.60 

BC: Mean (SD): 2.00 (0.77) 

Median: 1.89 

IQR: 0.96 

Min-Max: 0.58, 5.11 

OCpri: Mean (SD): 3.37 (1.21) 

Median: 3.21 

IQR: 1.63 

Min-Max: 0.99, 7.11 

Secondary OC: Mean (SD): 2.49 (1.50) 

Median: 2.10 

IQR: 1.86 

Min-Max: 0, 8.10 

PN (p/cm3

): Mean (SD): 16,043 (5886) 

Median: 13,968 

IQR: 7,386 

Min-Max: 6837, 31263 

Indoor hourly PM EC: Mean (SD): 

1.31 (0.52) 

Median: 1.30 

IQR: 0.70 

Min-Max: 0.19, 2.89 

PM Increment: IQR 

Effect Estimate [Lower CI, Upper CI]: 

Note: Nearly all results presented in 

figures 

Results: The authors found significant 

positive associations for CRP, IL-6, 

sTNF-RII, and sP-selectin with outdoor 

and/or indoor concentrations of quasiultrafine PM ≤ 0.25 μm in diameter, EC, 

OCpri, BC, PN, CO, and nitrogen 

dioxide from the current-day and 

multiday avg. There were consistent 

positive but largely nonsignificant 

coefficients for TNF-α, sVCAM-1, and 

sICAM-1, but not fibrinogen, IL-6sR, or 

D-dimer. The authors found inverse 

associations for erythrocyte Cu, ZnSOD with these pollutants and other PM 

size fractions (0.25-2.5 and 2.5-10 μm). 

Inverse associations of GPx-1 and MPO 

with pollutants were largely 

nonsignificant. Indoor associations were 

often stronger for estimated indoor EC, 

OCpri, and PN of outdoor origin than for 

uncharacterized indoor measurements. 

There was no evidence for positive 

associations with SOA. 

December 2009 E-80 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

cool period 

Dose-response Investigated? No 

Statistical Package: NR 

EC of outdoor origin: Mean (SD): 1.11 

(0.39) 

Median: 1.06 

IQR: 0.51 

Min-Max: 0.41, 2.97 

OC: Mean (SD): 5.69 (1.51) 

Median: 5.60 

IQR: 1.96 

Min-Max: 2.34, 10.79 

OCpri of outdoor origin: Mean (SD): 

2.18 (0.82) 

Median: 2.15 

IQR: 1.07 

Min-Max: 0.32, 5.21 

Secondary OC of outdoor origin: Mean 

(SD): 2.08 (1.26) 

Median: 1.75 

IQR: 1.45 

Min-Max: 0, 6.87 

PN (particles/cm3

): Mean (SD): 14,494 

(6770) 

Median: 12,341 

IQR: 7,337 

Min-Max: 1016, 43027 

PN of outdoor origin (p/cm3

): Mean 

(SD): 10,108 (3108) 

Median: 9,580 

IQR: 3,684 

Min-Max: 1016, 17700 

Outdoor PM mass PM0.25: Mean 

(SD): 9.47 (2.97) 

Median: 9.4 

IQR: 4.2 

Min-Max: 3.31, 18.75 

PM0.25-2.5: Mean (SD): 13.53 (10.67) 

Median: 11.7 

IQR: 11.5 

Min-Max: 1.29, 66.77 

PM10-2.5: Mean (SD): 10.04 (4.07) 

Median: 9.9 

IQR: 5.9 

Min-Max: 1.76, 22.38 

Indoor PM mass PM0.25: Mean (SD): 

10.45 (6.77) 

Median: 9.5 

IQR: 4.5 

Min-Max: 1.42, 69.86 

PM0.25-2.5 (μg/m3

): Mean (SD): 7.36 

(4.57) 

Median: 6.5 

IQR: 5.7 

Min-Max: 0.77, 30.86 

PM10-2.5: Mean (SD): 4.12 (4.76) 

Median: 2.8 

IQR: 3.5 

Min-Max: 0.12, 37.63 

Copollutant: Outdoor hourly gases 

(NO2, CO, O3) and indoor hourly gases 

(NO2, CO) 

Reference: Pekkanen et al. (2002, 

035050) 

Period of Study: Winter 1998-1999 

Location: Helsinki, Finland 

Outcome: ST Segment Depression 

(>0.1mV) 

Study Design: Panel of ULTRA Study 

participants 

N: 45 Subjects, n = 342 biweekly 

submaximal exercise tests, 72 exercise 

induced ST Segment Depressions 

Statistical Analysis: Logistic 

regression / GAM 

Pollutant: Ultrafine NC0.01-0.1 μm 

(n/cm3) 

Averaging Time: 24 h 

Median: 14,890 

IQR: 9830 

Monitoring Stations: 1 

Copollutant: NO2, CO, PM2.5, PM10-2.5, 

PM1, ACP 

PM Increment: IQR 

Effect Estimate(s): NC0.01-0.1: OR 

= 3.14 (1.56, 6.32), lag 2 

Notes: The effect was strongest for 

ACP and PM2.5, which in 2 pollutant 

models appeared independent. 

Increases in NO2 and CO were also 

associated with increased risk of ST 

segment depression, but not with 

coarse particles. 

December 2009 E-81 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peters et al. (2005, 

095747) 

Also Peters et al, 2005 (2005, 156859) 

Period of Study: Feb 1999-Jul 2001 

Location: Augsburg, Germany 

Outcome: Myocardial infarction 

Study Design: Case-crossover 

N: 691 myocardial infarction patients 

Statistical Analysis: Conditional 

logistic regression 

Dose-response investigated 

(yes/no)? No 

Pollutant: Ultrafine (TNC) (n/cm3) 

Averaging Time: 

1 h: Median = 10,001 

IQR: 7919 

24 h: Median = 10,934 

IQR: 6276 

Copollutant: NO2, SO2, CO 

PM Increment: Effect Estimate: 2-h 

lag: OR = 0.95 

95% CI: 0.84, 1.06 

24-h mean, 2-day lag: OR = 1.04 

95% CI: 0.90, 1.20 

Notes: Examined triggering for MI at 

various lags before MI onset (up to 6 h 

before MI, up to 5 days before MI). No 

statistically significant increases in 

lagged ultrafine particle concentration 

were found. 

Reference: Ruckerl et al. (2006, 

088754) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome (ICD9 and ICD10): 

C-reactive protein (CRP) 

Serum amyloid A (SAA) 

E-selectin 

von Willebrand Factor (vWF) 

Intercellular adhesion molecule-1 

(ICAM-1) 

Fibrinogen 

Factor VII 

Prothrombin fragment 1+2 

D-dimer 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear and logistic regression models

Covariates: Models adjusted for 

different factors based on health 

endpoint 

CRP: RH, temperature, trend, ID 

ICAM-1: temperature, trend, ID 

vWF: air pressure, RH, temperature, 

trend, ID 

FVII: air pressure, RH, temperature, 

trend, ID, weekday 

Season: Time trend as covariate 

Dose-response Investigated? 

Sensitivity analyses examined nonlinear 

exposure-response functions 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: AP (n/cm3) 

Averaging Time: 24 h 

Mean (SD): 1593 (1034) 

Percentiles: 

25: 821 

50: 1238 

75: 2120 

Range (Min, Max): 328, 4908 

Unit (i.e. μg/m3): n/cm3 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5

PM10

OC 

EC 

NO2

CO 

PM Increment: IQR (1299 

5-day avg: 1127)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as OR (95%CI) for an 

increase in the blood marker above the 

90th percentile per increase in IQR air 

pollutant. 

CRP 

Time before draw: 

0 to 23 h: 0.7 (0.5, 1.2) 

24 to 47 h: 1.5 (0.9, 2.6) 

48 to 71 h: 3.2 (1.7, 6.0) 

5-day mean: 1.5 (0.8, 3.0) 

ICAM-1 

Time before draw: 

0 to 23 h: 0.6 (0.4, 0.9) 

24 to 47 h: 1.8 (1.2, 2.8) 

48 to 71 h: 1.6 (1.0, 2.5) 

5-day mean: 0.9 (0.6, 1.5) 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

vWF 

Time before draw: 

0 to 23 h: 4.8 (0.2, 9.3) 

24 to 47 h: 5.9 (0.4, 11.5) 

48 to 71 h: 7.0 (0.7, 13.4) 

5-day mean: 13.5 (6.3, 20.6) 

FVII 

Time before draw: 

0 to 23 h: 0.0 (-2.9, 3.0) 

24 to 47 h: -2.9 (-6.1, 0.4) 

48 to 71 h: -3.6 (-6.8 to -0.3) 

5-day mean: -4.1 (-7.9 to -0.3) 

Note: Summary of results presented in 

figures. 

SAA results indicate increase in 

association with PM (not as strong and 

consistent as with CRP) 

No association observed between Eselectin and PM 

An increase in prothrombin fragment 

1+2 was consistently observed, 

particularly with lag 4 

Fibrinogen results revealed few 

significant associations, potentially due 

to chance 

D-dimer results revealed null 

associations in linear and logistic 

analyses 

December 2009 E-82 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ruckerl et al. (2006, 

088754) 

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome: Soluble CD40 ligand 

(sCD40L), platelets, leukocytes, 

erythrocytes, hemoglobin 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear regression models 

Covariates: Long-term time trend, 

weekday of the visit, temperature, RH, 

barometric pressure 

Season: Time trend as covariate 

Dose-response Investigated? No 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: AP (n/cm3) 

Averaging Time: 24 h 

Mean (SD): 1593 (1034) 

Percentiles: 

25th: 821 

50th: 1238 

75th: 2120 

Range (Min, Max): 328, 4908 

Monitoring Stations: 1 site 

Copollutant: 

UFPs 

AP 

PM2.5

PM10

NO 

PM Increment: IQR (1299 

5-day avg: 1127)

Effect Estimate [Lower CI, Upper CI]: 

Effects of air pollution on blood markers 

presented as % change from the 

mean/GM in the blood marker per 

increase in IQR air pollutant. 

sCD40L, % change GM (pg/mL) 

lag0: 6.9 (0.5, 13.8) 

lag1: -1.1 (-8.0, 6.4) 

lag2: -4.9 (-11.9, 2.7) 

lag3: -3.8 (-10.3, 3.2) 

5-day mean: -1.3 (-9.9, 8.1) 

Platelets, % change mean (103/μl) 

lag0: -1.0 (-2.5, 0.5) 

lag1: -0.4 (-2.1, 1.6) 

lag2: 0.8 (-1.0, 2.4) 

lag3: 0.0 (-1.8, 1.7) 

5-day mean: -0.9 (-3.0, 1.3) 

Leukocytes, % change in mean 

(103/μl) 

lag0: -1.9 (-3.8 to -0.1) 

lag1: -0.6 (-2.9, 1.6) 

lag2: -0.6 (-3.2, 2.0) 

lag3: -2.3 (-4.6, 0.1) 

5-day mean: -2.7 (-5.5, 0.1) 

Erythrocytes, % change mean 

(106/μl) 

lag0: -0.1 (-0.5, 0.3) 

lag1: -0.4 (-0.9, 0.2) 

lag2: -0.4 (-0.9, 0.2) 

lag3: -0.4 (-0.6, 0.3) 

5-day mean: -0.4 (-1.0, 0.2) 

Hemoglobin, % change mean (g/dl) 

lag0: -0.2 (-0.7, 0.4) 

lag1: -0.3 (-1.0, 0.4) 

lag2: -0.1 (-0.9, 0.7) 

lag3: -0.1 (-0.8, 0.6) 

5-day mean: -0.2 (-1.1, 0.6) 

Reference: Ruckerl et al. (2007, 

156931) 

Period of Study: May 2003-Jul 2004 

Location: Athens, Augsburg, 

Barcelona, Helsinki, Rome, and 

Stockholm 

Outcome: Interleukin-6 

(IL-6), fibrinogen, C-reactive protein 

(CRP) 

Age Groups: 35-80 yr

Study Design: Repeated measures / 

longitudinal 

N: 1003 MI survivors 

Statistical Analyses: Mixed-effect 

models 

Covariates: City-specific confounders 

(age, sex, BMI) 

Long-term time trend and apparent 

temperature 

RH, time of day, day of week included if 

adjustment improved model fit 

Season: Long-term time trend 

Dose-response Investigated? Used psplines to allow for nonparametric 

exposure-response functions 

Statistical Package: SAS v9.1 

Pollutant: UFP (n/cm3) 

Averaging Time: Hourly and 24 h (lag 

0-4, mean of lags 0-4, mean of lags 0-1, 

mean of lags2-3, means of lags 0-3) 

Mean (SD): Presented by city only 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: Central 

monitoring sites in each city 

Copollutant: 

SO2

O3

NO 

NO2

PM Increment: IQR

Effect Estimate [Lower CI, Upper CI]: 

% change in mean blood markers per 

increase in IQR of air pollutant. 

IL-6 

Lag (IQR): % change in GM (95%CI) 

Lag 0 (11852): 1.88 (-0.16, 3.97) 

Lag 1 (11852): -0.67 (-2.56, 1.25) 

Lag 2 (11852): -2.12 (-4.03 to -0.17) 

5-day avg (11003): -0.93 (-3.37, 1.56) 

Fibrinogen 

Lag (IQR): % change in AM (95%CI) 

Lag 0 (11852): 0.40 (-0.40, 1.19) 

Lag 1 (11852): 0.11 (-0.69, 0.91) 

Lag 2 (11852): 0.09 (-0.71, 0.90) 

5-day avg (11003): 0.50 (-2.20, 3.20) 

CRP 

Lag (IQR): % change in GM (95%CI) 

Lag 0 (11852): 1.33 (-3.05, 5.90) 

Lag 1 (11852): -1.52 (-4.39, 1.45) 

Lag 2 (11852): -1.63 (-6.70, 3.71) 

5-day avg (11003): -0.08 (-3.78, 3.75) 

December 2009 E-83 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Pekkanen et al. (2002, 

035050) 

Period of Study: Winter 1998-1999 

Location: Helsinki, Finland 

Outcome: ST Segment Depression 

(>0.1mV) 

Age Groups: Study Design: Panel of 

ULTRA Study participants 

N: 45 Subjects, n = 342 biweekly 

submaximal exercise tests, 72 exercise 

induced ST Segment Depressions 

Statistical Analysis: Logistic 

regression / GAM 

Pollutant: Ultrafine NC0.01-0.1 μm 

(n/cm3

) 

Averaging Time: 24 h 

Median: 14,890 

IQR: 9830 

Monitoring Stations: 1 

Copollutant: NO2, CO, PM2.5, PM10-2.5, 

PM1, ACP 

PM Increment: IQR 

Effect Estimate(s): NC0.01-0.1: OR 

= 3.14 (1.56, 6.32), lag 2 

Notes: The effect was strongest for 

ACP and PM2.5, which in 2 pollutant 

models appeared independent. 

Increases in NO2 and CO were also 

associated with increased risk of ST 

segment depression, but not with 

coarse particles. 

Reference: Peters et al. (2005, 

095747) 

Also Peters et al, 2005 (2005, 156859) 

Period of Study: Feb 1999-Jul 2001 

Location: Augsburg, Germany 

Outcome: Myocardial infarction 

Study Design: Case-crossover 

N: 691 myocardial infarction patients 

Statistical Analysis: Conditional 

logistic regression 

Dose-response Investigated? No 

Pollutant: Ultrafine (TNC) (n/cm3) 

Averaging Time: 1 h: Median = 10,001 

IQR: 7919 

24-h: Median = 10,934 

IQR: 6276 

Copollutant: NO2, SO2, CO 

PM Increment: Effect Estimate: 

2-h lag: OR = 0.95 

95% CI: 0.84, 1.06 

24-h mean, 2-day lag: OR = 1.04 

95% CI: 0.90, 1.20 

Notes: Examined triggering for MI at 

various lags before MI onset (up to 6 h 

before MI, up to 5 days before MI). No 

statistically significant increases in 

lagged ultrafine particle concentration 

were found. 

Reference: Ruckerl et al. (2007, 

091379)

Period of Study: Oct 2000-Apr 2001 

Location: Erfurt, Germany 

Outcome (ICD9 and ICD10): Soluble 

CD40 ligand (sCD40L), platelets, 

leukocytes, erythrocytes, hemoglobin 

Age Groups: 50+ yr 

Study Design: Panel (12 repeated 

measures at 2-wk intervals) 

N: 57 male subjects with coronary 

disease 

Statistical Analyses: Fixed effects 

linear regression models 

Covariates: Long-term time trend, 

weekday of the visit, temperature, RH, 

barometric pressure 

Season: Time trend as covariate 

Dose-response Investigated? No 

Statistical Package: SAS v8.2 and SPlus v6.0 

Pollutant: UFP 

Averaging Time: 24 h 

Mean (SD): 12,602 (6455) 

Percentiles: 

25th: 7326 

50th: 11,444 

75th: 17,332 

Range (Min, Max): 328, 4908 

Monitoring Stations: 1 site 

Copollutant: 

AP 

PM2.5

PM10 

NO 

PM Increment: IQR (10,005 

5-day avg: 6,821)

Effect Estimate [Lower CI, Upper CI]: 

sCD40L, % change GM (pg/mL) 

lag 0: 7.1 (0.1, 14.5) 

lag 1: 0.3 (-6.6, 8.6) 

lag 2: 0.6 (-5.9, 8.6) 

lag 3: -8.5 (-15.8, -0.5) 

5-day mean: -0.7 (-7.6, 6.8) 

Platelets, % change mean (103/μl) 

lag 0: -1.8 (-3.4, -0.2) 

lag 1: -1.1 (-2.9, 0.6) 

lag 2: 1.0 (-2.9, 0.8) 

lag 3: -2.4(4.5, -0.3) 

5-day mean: -2.2 (-4.0, -0.3) 

Leukocytes, [103/μl]

lag 0: -2.4 (-4.5, -0.2) 

lag 1: -2.1 (-4.4, 0.2) 

lag 2: -0.2 (-2.4, 2.8) 

lag 3: -1.5 (-4.4, 1.4) 

5-day mean: -1.6 (-4.1, 0.8) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-84 
E.1.2. Cardiovascular Emergency Department Visits and Hospital 

Admissions 

Table E-5. Short-term exposure-cardiovascular: ED/HA PM10

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Anderson et al. (2003, 

054820) 

Period of Study: 1992-1994 

Location: London, U.K. 

Outcome: Ischemic Heart Disease

Age Groups: 0-15, 15-64, 65-74, 75+ 

Study Design: Time series 

N: NR 

Statistical Analyses: NR 

Covariates: NR 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): NR

Monitoring Stations: NR 

Copollutant: NR 

PM Increment: 10th-90th percentile 

% Change in Daily IHD Admissions 

by Age [CI]: 0-15 yr: NR 

15-64 yr: 2.6 [0.3,5] 

65-74 yr: 2.5 [0.1,4.9] 

75+ yr: 2.2 [0.2,4.6] 

Notes: RRs are presented in graph 

form showing little change with 

increasing age (PM increment of 

10 μg/m3

). This article is primarily a 

systematic literature review of other 

studies.

Reference: Andersen et al. (2008, 

189651) 

Period of Study: May 2001-Dec 2004 

Location: Copenhagen, Denmark 

Outcome (ICD-10): CVD, including 

angina pectoris (I20), myocardial 

infarction (I21-22), other acute ischemic 

heart diseases (I24), chronic ischemic 

heart disease (I25), pulmonary 

embolism (I26), cardiac arrest (I46), 

cardiac arrhythmias (I48-48), and heart 

failure (I50). 

Age Groups: >65 yr (CVD and RD), 

5-18 yr (asthma) 

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAM 

Covariates: Temperature, dew-point 

temperature, long-term trend, 

seasonality, influenza, day of the week, 

public holidays. 

Season: NR 

Dose-response Investigated: No 

Statistical Package: R (gam 

procedure, mgcv package) 

Lags Considered: Lag 0 -5 days, 4-

day pollutant avg (lag 0 -3) for CVD. 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 24(14)

Median: 21

IQR: 16-28

99th percentile): 72 

Monitoring Stations: 1 

Copollutant (correlation): 

NCtot: r = 0.39 

NC100: r = 0.28 

NCa12: r = 0.02 

NCa23: r = -0.12 

NCa57: r = 0.45 

NCa212: r = 0.63 

PM2.5: r = 0.80 

CO: r = 0.37 

NO2: r = 0.35 

NOX: r = 0.32 

NOX curbside: r = 0.18 

O3: r = -0.21 

Other variables: 

Temperature: r = 0.12 

Relative humidity: r = 0.05 

PM Increment: 13 μg/m3 (IQR) 

Relative risk (RR) Estimate [CI]: 

CVD hospital admissions 

(4-day avg, lag 0 -3), age 65+: 

One-pollutant model: 1.03 [1.01-1.05] 

Adj for NCtot: 1.04 [1.02-1.06] 

Adj for NCa212: 1.05 [1.01-1.09] 

RD hospital admissions 

(5-day avg, lag 0 -4), age 65+: 

One-pollutant model: 1.06 [1.02-1.09] 

Adj for NCtot: 1.05 [1.01-1.10] 

Adj for NCa212: 1.04 [0.98-1.11] 

Asthma hospital admissions 

(6-day avg lag 0-5), age 5 - 18: 

One-pollutant model: 1.02 [0.93-1.12] 

Adj for NCtot: 1.01 [0.91-1.12] 

Adj for NCa212: 0.94 [0.81-1.09] 

Estimates for individual day lags 

reported only in Fig form (see notes): 

Notes: Fig 2: Relative risks and 95% 

confidence intervals per IQR in single 

day concentration (0- to 5-day lag). 

Summary of Fig 2: CVD: Positive, 

marginally or statistically significant 

associations at Lag 0-Lag 2. 

December 2009 E-85 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Anderson et al. (2007, 

156214) 

Period of Study: January 

1999-December 2004 

Location: Copenhagen, Denmark

Outcome (ICD10): Hospital Admission, 

CVD, including angina pectoris (I20), 

myocardial infarction (I21-22), other 

acute ischemic heart diseases (I24), 

chronic ischaemic heart disease (I25), 

pulmonary embolism (I26), cardiac 

arrest (I46), cardiac arrhythmias 

(I48-48), and heart failure (I50). 

Age Groups Analyzed: Age >65 

Study Design: Time series 

N: 2192 days, 9 Hospitals 

Statistical Analyses: Principal 

Component Analysis and Constrained 

Physical Receptor Model (COPREM), 

Poisson regression, GAM, 

Covariates: Season, day of the wk, 

public holidays, influenza epidemics 

and meteorology 

Season: All yr 

Dose-response Investigated? No 

Statistical package: R, gam/mgcv 

package 

Lags Considered: 0-6 days 

Pollutant: Source specific PM10

components 

Averaging Time: 24 h 

Mean (SD): Percentiles: 

25th: 16 

50th (Median): NR 

75th: 30 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10: 

Biomass: r = 0.53 

Secondary: r = 0.73 

Oil: r = 0.57 

Crustal: r = 0.37 

Sea salt: r = 0.04 

Vehicle: r = 0.02 

Notes: Correlations between source 

specific PM10 components presented in 

paper 

PM Increment: IQR 

RR Estimate 

Respiratory disease (age >65) 

Single pollutant model: 

PM10: 1.027 (1.013, 1.042), IQR=14 

PM10 (other 5 sources): 1.045 (1.016, 

1.074), IQR=13 

Biomass: 1.040 (0.009, 1.072), IQR=5.4

Secondary: 1.050 (1.021, 1.081), 

IQR=6.1 

Oil: 1.035 (1.006, 1.065), IQR=2.8 

Crustal: 1.054 (1.028, 1.081), IQR=1.8 

Sea salt: 0.98 (0.947, 1.017), IQR=2.2 

Vehicle: 0.989 (0.949, 1.032), IQR=0.6 

Notes: 2 pollutant model results for 

PM10 with source specific components 

and gases also presented in 

manuscript. 

Reference: Baccarelli et al. (2007, 

091310)

Period of Study: Jan 1995-Aug 2005 

Location: Lombardia region, Italy 

Outcome (ICD9 and ICD10): Fasting 

and postmethionine-load total 

homocysteine (tHcy) 

Age Groups: 11-84 yr

Study Design: Cross-sectional/Panel 

N: 1,213 participants 

Statistical Analyses: Generalized 

additive models 

Covariates: age, sex, BMI, smoking, 

alcohol, hormone use, temperature, day 

of the yr, and long-term trends 

Season: Adjusted for long-term trends 

to account for season 

Dose-response Investigated? No 

Statistical Package: R software v2.2.1 

Pollutant: PM10 (some TSP measures 

used to predict PM10) 

Averaging Time: Hourly concentrations 

used to calculate 24-h ma and 7-day 

ma

Mean (SD): NR 

Percentiles: 

25th: 20.1 

50th: 34.1 

75th: 52.6 

Range (Min, Max): Max: 390.0

Monitoring Stations: 53 sites 

Copollutant: 

CO 

NO2 

SO2 

O3

PM Increment: IQR 

Effect Estimate [Lower CI, Upper CI]: 

Estimates (%) per 32.5 μg/m3 increase 

in 24-h ma of PM10

Homocysteine, fasting: 0.4 (-2.4, 3.3) 

Homocysteine, postmethionine-load: 

(-1.5, 3.7) 

Estimates (%) per 25.7m3

 increase in 7-

day ma of PM10

Homocysteine, fasting: 1.0 (-1.9, 3.9) 

Homocysteine, postmethionine-load: 

2.0 (-0.6, 4.7) 

Estimates of effect (%) on fasting 

homocysteine per IQR increase in 24-h 

PM10 levels 

Among smokers: 6.2 (0.0, 12.7) 

Among non-smokers: -1.6 (-5.5, 2.5) 

Estimates of effect (%) on 

postmethionine-load homocysteine per 

IQR increase in 24-h PM10 levels 

Among smokers: 6.0 (0.5, 11.8) 

Among non-smokers: -0.1 (-3.6, 3.5) 

December 2009 E-86 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ballester et al. (2006, 

088746) 

Period of Study: 1995-1999 

Location: 5 Spanish cities: Granada, 

Huelva, Madrid, Seville, Zaragoza 

Outcome (ICD-9): All cardiovascular 

disease (390-459), including all heart 

diseases (410-414, 427, 428)

Age Groups: All ages 

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAMs 

Covariates: Dily temp, barometric 

pressure relative humidity 

Daily influenza incidence, day of the 

week, holidays, unusual events (ex. 

medical strikes), seasonal variation, 

trend 

Dose-response Investigated: No 

Statistical Package: S-Plus GAM 

function 

Lags Considered: lag 0-3 days, lag 

0-1 avg 

Pollutant: PM10

Averaging Time: 24 h 

Mean (10-90th percentile): overall 

mean NR. 

City specific means 

Granada: 43.2 (24.8, 62.6) 

Huelva: 38.6 (23.1, 57.3) 

Madrid: 35.7 (21.4, 54.4) 

Seville: 41.9 (27.3, 57.6) 

Zaragoza: 32.8 (17.3, 50.3) 

Monitoring Stations: At least three 

stations/city (15+) 

Copollutant (correlation): Summary of 

the correlation coefficients between 

each pair of pollutants within cities: 

BS: r = 0.48 

TSP: N/A 

NO2: from r = 0.13 to r = 0.62 

(median r = 0.40) 

SO2: from r = 0.20 to r = 0.51 

(median r = 0.46) 

CO: from r = 0.34 to r = 0.45 

(median r = 0.37) 

O3: from r = -0.07 to r = 0.16 

(median r = 0.11) 

PM Increment: 10 μg/m3 

Relative risk [CI]: Relative risks are 

expressed only in the form of figures 

(see notes). 

Percentage change in risk [CI]: All 

cardiovascular diseases (avg of lags 0 -

1): 0.91% [0.35, 1.47] 

Heart disease (avg of lags 0 -1) 

1.56% [0.82, 2.31] 

Notes: Relative risks for the single 

pollutant models are expressed in 

Fig 2. 

Fig 2: Time sequence of the combined 

association between PM10 and hospital 

admissions for all CVD (A) and heart 

disease (B). 

Summary of results: Significant, positive 

association of PM10 with both overall 

CVD and heart disease hospitalizations 

at Lag 0 and Lag 1. 

Relative risks for 2 pollutant models 

are expressed in Fig 3: Fig 3: 

Combined estimates of the association 

between hospital admissions for heart 

diseases and air pollutants (avg of lags 

0-1 

Adjusted for CO, NO2, O3, or SO2) 

Summary of results: Significant, positive 

association remains after adjusting for 

pollutants. 

December 2009 E-87 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bell et al. (2008, 091268) 

Period of Study: 1995-2002 

Location: Taipei, Taiwan 

Outcome (ICD-9): Hospital admissions 

for ischemic heart disease (410 , 411, 

414), cerebrovascular disease 

(430-437). 

Age Groups: All 

Study Design: Time series 

N: 6,909 hospital admissions for 

ischaemic heart diseases, 11,466 for 

cerebrovascular disease. 

Statistical Analyses: Poisson 

regression 

Covariates: Day of the week, time, 

apparent temperature, long-term trends, 

seasonality 

Season: All 

Dose-response Investigated: No 

Statistical Package: NR 

Lags Considered: lags 0-3 days, avg 

of lags 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean (range 

IQR): 

49.1 (12.7-215.5 

27.6) 

Monitoring Stations: Taipei area: 13 

monitors 

Taipei City: 5 monitors 

Monitors with correlations of 0.75 + for 

PM10: 12 monitors 

Copollutant: NR 

PM Increment: 28 μg/m3 (near IQR) 

Percentage increase estimate [95% 

CI]: Ischemic heart disease: Taipei 

area (13 monitors): L0: 1.91 (-1.25, 

5.17) 

L1: 0.39 (-2.73, 3.61) 

L2: 1.80 (-1.33, 5.04) 

L3: 2.01 (-1.14, 5.26) 

L03: 2.91 (-1.52, 7.55) 

Taipei City (5 monitors): L0: 2.08 (-1.04, 

5.30) 

L1: 0.43 (-2.64, 3.60) 

L2: 2.17 (-0.92, 5.36) 

L3: 2.16 (-0.94, 5.36) 

L03: 3.40 (-1.19, 8.20) 

Monitors with > = 0.75 between monitor 

correlations (12 monitors): L0: 1.82 

(-1.29, 5.03) 

L1: 0.35 (-2.72, 3.52) 

L2: 1.93 (-1.15, 5.10) 

L3: 1.93 (-1.16, 5.12) 

L03: 2.86 (-1.63, 7.54) 

Cerebrovascular disease: Taipei area 

(13 monitors): L0: -1.41 (-3.80, 1.04) 

L1: -1.95 (4.31, 0.48) 

L2: 0.77 (-1.62, 3.23) 

L3: 2.64 (0.21, 5.12) 

L03: 0.01 (-3.33, 3.47) 

Taipei City (5 monitors): L0: -1.27 

(-3.64, 1.16) 

L1: -2.13 (-4.47, 0.27) 

L2: 0.85 (-1.52, 3.28) 

L3: 2.52 (0.13, 4.97) 

L03: -0.07 (-3.53, 3.51) 

Monitors with > = 0.75 between monitor 

correlations (12 monitors): L0: -1.34 

(-3.70, 1.07) 

L1: -1.98 (-4.31, 0.40) 

L2: 0.80 (-1.56, 3.22) 

L3: 2.61 (0.22, 5.05) 

L03: -0.02 (-3.40, 3.49)

Reference: Chan et al. (2007, 147787) 

Period of Study: Apr 1997-Dec 2002 

Location: Boston, MA 

Outcome: Cerebrovascular Emergency 

Admissions 

Age Groups: 50+ yr 

Study Design: Tme series 

Statistical Analyses: GAM Poisosn 

Regression 

Covariates: Yr, mo, day of wk, 

temperature, dew point 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 50.2 (22.1) 

Min: 16.0 

Max: 325.4 

IQR: 25.4 

Monitoring Stations: 16 

Copollutant: O3, CO, SO2, NO2, PM2.5

Co-pollutant Correlation: 

O3: 0.43

CO: 0.47 

SO2: 0.59 

NO2: 0.64 

PM2.5: 0.61 

PM Increment: Interquartile Range 

(25.4 μg/m3) 

Percent Change (Lower CI, Upper CI), 

p-value: 

Cerebrovascular Disease 

Lag 0: 1.001 (0.969, 1.033) 

Lag 1: 0.999 (0.9787, 1.020) 

Lag 2: 1.023 (0.989, 1.057) 

Lag 3: 1.030 (1.011, 1.049) 

Lag 3 + O3: 1.018 (0.987, 1.049) 

Lag 3 + CO: 1.019 (0.988, 1.050) 

Lag 3 + O3 + CO: 1.015 (0.985, 1.045) 

Stroke 

Lag 0: 0.969 (0.897, 1.041) 

Lag 1: 0.992 (0.918, 1.066) 

Lag 2: 1.004 (0.993, 1.015) 

Lag 3: 1.009 (0.988, 1.030) 

Ischaemic stroke 

Lag 0: 0.984 (0.932, 1.036) 

Lag 1: 0.993 (0.939, 1.047) 

Lag 2: 0.989 (0.927, 1.041) 

Lag 3: 1.042 (0.981, 1.103) 

Haemorrhagic stroke 

Lag 0: 0.966 (0.884, 1.048) 

Lag 1: 0.990 (0.908, 1.072) 

Lag 2: 1.002 (0.920, 1.084) 

Lag 3: 0.974 (0.902, 1.046) 

December 2009 E-88 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chan et al. (2008, 093297) 

Period of Study: 1995-2002 

Location: Taipei Metropolitan area, 

Taiwan 

Outcome (ICD-9): Emergency visits for 

ischaemic heart diseases (410-411, 

414), cerebrovascular diseases 

(430-437), and COPD (493, 496)

Age Groups: All 

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson 

regression models 

Covariates: Yr, mo, day of wk,

temperature, dew point temperature, 

PM2.5, NO2

Season: All 

Dose-response Investigated: No 

Statistical Package: SAS version 8.0 

Lags Considered: 0- to 7-day lags 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): High dust events: Pre-dust 

periods: 45.5 (17.6) 

Asian dust events: 122.7 (24.4) 

Low dust events: Pre-dust periods: 59.4 

(31.0) 

Asian dust events: 61.1 (17.8) 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: 25.4 μg/m3 (IQR) 

OR [95% CI]: In environmental 

conditions without dust storms (results 

only shown for best-fitting model) 

Lag 3 days: 1.023 (1.003, 1.041)

Reference: Chang et al. (2007, 

147621) 

Period of Study: 1997-2001 

Location: Taipei, Taiwan 

Outcome: CVD HA 

Age Groups: NR 

Study Design: Case-crossover 

Statistical Analyses: Conditional 

Logistic Regression 

Covariates: Temperature, humidity 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean: 48.32 

Min: 14.44 

25th: 32.65 

50th: 42.80 

75th: 57.16 

Max: 234.91 

Monitoring Stations: 6 

Copollutant: O3, CO, SO2, NO2

Co-pollutant Correlation: NR 

PM Increment: Interquartile Range 

(24.51 μg/m3

) 

Odds Ratio (Lower CI, Upper CI): 

≥20°C 

PM10: 1.085 (1.061, 1.110) 

PM10+ SO2: 1.131 (1.103, 1.161) 

PM10+ NO2: 10.977 (0.950, 1.006) 

PM10+ CO: 1.025 (0.999, 1.052) 

PM10+ O3: 1.064 (1.039, 1.090) 

<20°C 

PM10: 1.142 (1.105, 1.180) 

PM10+ SO2: 1.235 (1.184, 1.288) 

PM10+ NO2: 1.148 (1.103, 1.194) 

PM10+ CO: 1.165 (1.121, 1.212) 

PM10+ O3: 1.142 (1.105, 1.180) 

Reference: D'Ippoliti et al. (2003, 

074311) 

Period of Study: Jan 1995-Jun 1997 

Location: Rome, Italy 

Outcome: Myocardial Infarction HA 

Age Groups: 18+ yr 

Study Design: Case-crossover 

Statistical Analyses: Conditional 

Logistic Regression 

Covariates: Temperature, humidity 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-4 days 

Pollutant: TSP 

Averaging Time: 24 h 

Mean (SD): 66.9 (19.7) 

25th: 54.7 

50th: 66.4 

75th: 78.4 

IQR: 23.7 

Monitoring Stations: 3 

Copollutant: CO, SO2, NO2

Co-pollutant Correlation: 

CO: 0.35 

SO2: 0.29 

NO2: 0.38 

PM Increment: Quartiles 

Odds Ratio (Lower CI, Upper CI): 

Lag 0-2-day avg 

QI: 1.0 (ref) 

QII: 1.048 (0.957, 1.148) 

QIII: 1.105 (1.007, 1.214) 

QIV: 1.132 (1.023, 1.253) 

Various Lags 

Lag 0: 1.023 (1.004, 1.042) 

Lag 1: 1.015 (0.996, 1.034) 

Lag 2: 1.017 (0.999, 1.035) 

Lag 3: 0.989 (0.974, 1.003) 

Lag 4: 1.001 (0.987, 1.016) 

December 2009 E-89 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Fung et al., (2005, 093262) 

Period of Study: 

Nov 1995-Dec 2000 

Location: London, Ontario 

Outcome (ICD-9): Cardiovascular 

diseases 

(410-414, 427-428) 

Age Groups: <65 yr, 65+ yr 

Study Design: Time series 

N: 12,947 CVD admissions 

Statistical Analyses: GAM with locally 

weighted regression smoothers 

(LOESS) 

Covariates: Maximum and minimum 

temp, humidity, day of the week, 

seasonal cycles, secular trends 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: Current to 3-day 

mean 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 38.0 (5-248) 

SD = 23.5 

Monitoring Stations: 4 

Copollutant (correlation): 

NO2: r = 0.30 

SO2: r = 0.24 

CO: r = 0.21 

O3: r = 0.53 

COH: r = 0.29 

PM Increment: 26 μg/m3

% Change in Daily Admission [CI]: 

Age <65 

Current day mean: 2.6 [-2.3,7.7] 

2-day mean: -1.2 [-7.2,5.1] 

3-day mean: -3 [-9.6,4] 

Age 65+ 

Current day mean: 0.9 [-2.3,4.2] 

2-day mean: -0.9 [-4.8,3.2] 

3-day mean: -0.1 [-4.4,4.5]

Reference: Hanigan et al. (2008, 

156518) 

Period of Study: 1996-2005 

(Apr-Nov of each yr) 

Location: Darwin, Australia 

Outcome: Daily emergency hospital 

admissions for total cardiovascular 

(ICD-9: 390-459 

ICD-10: I00-I99), ischemic heart 

disease (ICD-9: 410-414 

ICD-10: I20-I25). 

Age Groups: All 

Study Design: Time series 

N: 8,279 hospital admissions 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Indigenous status, time in 

days, temperature, relative humidity, 

day of the week, influenza epidemics, 

change between ICD editions, holidays, 

yrly population 

Season: Apr-Nov (corresponding to the 

dry season) 

Dose-response Investigated? No 

Statistical Package: R version 2.3.1 

Lags Considered: 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD 

range): 21.2 (8.2 

55.2) 

Monitoring Stations: N/A (see notes) 

Copollutant: NR 

PM Increment: 10 μg/m3 

Percent change [95% CI]: Overall 

CVD: Lag 0 (indigenous): -3.78 [-13.4, 

6.91] 

Lag 0 (non-indigenous): -3.43 [-9.00, 

2.49] 

All unstratified associations either 

negative or zero and not statistically 

significant. 

All other results of stratified analysis (by 

indigenous status) reported in a Fig 

(see notes). 

Notes: Fig 3: Associations between 

hospitalizations for non-indigenous and 

indigenous people with estimated 

ambient PM10. Summary: Confidence 

intervals were wide, but indigenous 

people generally had stronger 

associations with PM10 than nonindigenous people. Daily PM10 exposure 

levels were estimated for the population 

of the city from visibility data using a 

previously validated models. 

December 2009 E-90 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hanigan et al. (2008, 

156518) 

Period of Study: 1996-2005 

(Apr-Nov of each yr) 

Location: Darwin, Australia 

Outcome: Cardiorespiratory Disease 

HA (ICD 9: 390-519 

ICD 10: I00-99 & J00-99) 

Age Groups: NR

Study Design: Time series 

N: 8279 events 

Statistical Analyses: poisson 

regression 

Covariates: Indigenous status, time in 

days, temperature, relative humidity, 

day of the week, influenza epidemics, 

change between ICD editions, holidays, 

yearly population 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: lags 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 21.2 (8.2)

Range: 55.2 

Monitoring Stations: 2 (monitored & 

modeled) 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: 10 μg/m3

Percent Change (Lower CI, Upper CI), 

lag: 

Tot. Cardiovascular, Indigenous: -3.43 (-

9.00, 2.49), lag 0 

Tot Cardiovascular, Non-Indigenous: -

3.78 (-13.4, 6.91), lag 0 

*Fig 3. percent change in hospital 

admissions per 10 μg/m3

 increase in 

PM10 

Reference: Henrotin et al. (2007, 

093270) 

Period of Study: Mar 1994-Dec 2004 

Location: Dijon, France 

Outcome: Ischemic and hemorrhagic 

strokes 

Age Groups: All 

Study Design: Bi-directional casecrossover 

N: 1487 (ischemic) and 220 

(hemorrhagic) stroke patients 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, relative 

humidity, influenza epidemics, holidays 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: STATA software v. 

8.2 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

21.1 (2-103) 

SD = 11.3 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: 10 μg/m3 

OR Estimate [CI]: Ischemic stroke 

Same-day lag: 1.009 [0.930,1.094] 

1-day lag: 1.011 [0.998,1.094] 

2-day lag: 0.960 [0.889,1.036] 

3-day lag: 0.990 [0.919,1.066] 

Hemorrhagic stroke 

Same-day lag: 0.901 [0.730,1.111] 

1-day lag: 1.014 [0.828,1.241] 

2-day lag: 1.100 [0.903,1.339] 

3-day lag: 0.991 [0.881,1.212] 

Notes: Ischemic stroke ORs were also 

categorized into male and female, 

yielding similar results (none were 

significant for any lag days).

Reference: Issever et al. (2005, 

097736) 

Period of Study: 

Jan 1997-Dec 2001 

Location: Istanbul, Turkey 

Outcome: Acute coronary syndrome 

(ACS) 

Age Groups: All 

Study Design: Time series 

N: 2889 ACS admissions 

Statistical Analyses: Multiple stepwise 

regression, Pearson correlation 

Covariates: Humidity, temperature, 

pressure 

Season: NR 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 24 h 

Mean: NR 

Monitoring Stations: 1 

Copollutant (correlation): 

ACS: r = 0.37 (p = 0.003) 

ACS controlled for temp: r = 0.29 

(p = 0.02) 

PM Increment: NR 

RR Estimate [CI]: NR 

Notes: This study focused more on the 

seasonal change in acute coronary 

syndrome admissions.

December 2009 E-91 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Jalaludin et al. (2006, 

189416) 

Period of Study: Jan 1997-Dec 2001 

Location: Sydney, Australia 

Outcome (ICD-9): Cardiovascular 

disease (390-459), cardiac disease 

(390-429), ischemic heart disease 

(410-413) and cerebrovascular disease 

or stroke (430-438) 

Age Groups: 65+ yr 

Study Design: Time series 

N: NR 

Statistical Analyses: GAM, GLM 

Covariates: Temperature, humidity 

Season: Warm (Nov-Apr) and cool 

(May-Oct) 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 16.8 (3.8-103.9) 

SD = 7.2 

Monitoring Stations: 14 

Copollutant (correlation): 

Warm 

BSP: r = 0.82 

PM2.5: r = 0.89 

O3: r = 0.59 

NO2: r = 0.44; 

CO: r = 0.31 

SO2: r = 0.37 

Cool 

BSP: r = 0.75 

PM2.5: r = 0.88 

O3: r = 0.22 

NO2: r = 0.67 

CO: r = 0.48 

SO2: r = 0.46 

Other variables: 

Warm 

Temp: r = 0.36 

Rel humidity: r = -0.25 

Cool 

Temp: r = 0.13 

Rel humidity: r = 0.05 

PM Increment: 7.8 μg/m3 (IQR) 

Percent Change Estimate [CI]: 

All CVD 

Same-day lag: 0.72 [-0.14,1.60] 

Avg 0-1 day lag: 0.25 

[-0.61,1.12] 

Cool (same-day lag): 1.34 [0.08,2.61] 

Warm (same-day lag): 0.33 [-0.83,1.50] 

Cardiac disease 

Same-day lag: 1.15 [0.14,2.18] 

Avg 0-1 day lag: 0.97 

[-0.07,2.02] 

Cool (same-day lag): 1.35 [-0.16,2.89] 

Warm (same-day lag): 1.12 [-0.23,2.48] 

Ischemic heart disease 

Same-day lag: 0.59 [-0.95,2.17] 

Avg 0-1 day lag: 0.61 

[-0.95,2.20] 

Cool (same-day lag): 0.33 [-2.00,2.72] 

Warm (same-day lag): 0.79 [-1.23,2.85] 

Stroke 

Same-day lag: -1.66 [-3.48,0.20] 

Avg 0-1 day lag: -2.05 

[-3.88,-0.20] 

Cool (same-day lag): 0.46 [-2.17,3.17] 

Warm (same-day lag): -3.49 [-5.97,-

0.95] 

Notes: All other lag-day ORs were 

provided, yet none were significant. 

Percent change in ED attendance was 

also reported graphically 

(Fig 1-5).

Reference: Johnston et al. (2007, 

155882) 

Period of Study: 2000, 2004, 2005 

(Apr-Nov of each yr) 

Location: Darwin, Australia 

Outcome (ICD-10): All cardiovascular 

conditions (I00-I99), including ischemic 

heart disease (I20-I25). 

Age Groups: All 

Study Design: Case-crossover 

N: 2466 emergency admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Weekly influenza rates, 

temperature, humidity, days with rainfall 

>5mm, public holidays, school holiday 

periods (for respiratory conditions only) 

Season: Apr-Nov (dry season) 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Median: 17.4 

IQR: 13.6-22.3 

10-90th Percentile: 10.3-27.7 

Range: 1.1-70.0

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: 10 μg/m3 

OR Estimate [95% CI]: All respiratory 

conditions: Ischemic heart disease: 

Lag 0: 0.82 [0.68-0.98] 

Lag 0 (non-indigenous): 0.75 

[0.61-0.93] 

Lag 3 (indigenous): 1.71 [1.14-2.55] 

Notes: 

Fig 5: OR and 95% CI for hospital 

admissions for cardiovascular 

conditions. 

Summary: Negative associations in 

overall study population and in nonindigenous people. Positive 

associations in Indigenous people at 

Lag 1, Lag 2, and Lag 3. 

Fig 6: OR and 95% CI for hospital 

admissions for ischaemic heart disease.

Summary: Negative associations in 

overall study population and nonindigenous people. Positive association 

in indigenous people.

December 2009 E-92 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Koken et al. (2003, 

049466) 

Period of Study: Jul and Aug, 

1993-1997 

Location: Denver, Colorado 

Outcome (ICD-9): Acute myocardial 

infarction (410.00-410.92), pulmonary 

heart disease (416.0-416.9), cardiac 

dysrhythmias (427.0-427.9), congestive 

heart failure (428.0)

Age Groups: 65+ yr 

Study Design: Time series 

N: 298 days 

Statistical Analyses: GLM, GEE 

Covariates: Maximum temp and dew 

point temp 

Season: NR 

Dose-response Investigated: Yes 

Statistical Package: SAS (PROC 

GENMOD) 

Lags Considered: 0-4 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 24.2 (7.0-51.6) 

SD = 6.25 

Monitoring Stations: 3 

Copollutant (correlation): 

NO2: r = 0.56 

SO2: r = 0.36 

O3: r = 0.03 

CO: r = 0.25 

Other variables: Max temp: r = 0.38 

Dew point temp: r = -0.24 

PM Increment: 8.0 μg/m3 (IQR) 

Percent Change Estimate [CI]: No PM 

data reported

Reference: Lanki et al., (2006, 089788) 

Period of Study: 1992-2000 

Location: 

Augsburg, Barcelona, Helsinki, Rome, 

and Stockholm 

Outcome (ICD-9): Acute myocardial 

infarction 

(410 

ICD-10: I21, I22)

Age Groups: 35+ yr, <75 yr, 75+ yr 

Study Design: Time series 

N: 26,854 hospitalizations 

Statistical Analyses: GAM 

Covariates: Temperature, barometric 

pressure 

Season: Warm (Apr-Sep) and cold 

(Oct-Mar) 

Dose-response Investigated: No

Statistical Package: R package mgcv 

0.9-5 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Median: 

Augsburg: 43.5 

Barcelona: 57.4 

Helsinki: 21.0 

Rome: 48.5 

Stockholm: 12.5 

Copollutant (correlation): 

Augsburg 

PNC: r = 0.53 

CO: r = 0.56 

NO2: r = 0.64 

O3: r = 0.43 

Barcelona: PNC: r = 0.38 

CO: r = 0.44 

NO2: r = 0.48 

O3: r = 0.01 

Helsinki: PNC: r = 0.45 

CO: r = 0.21 

NO2: r = 0.40 

O3: r = 0.40 

Rome: PNC: r = 0.32 

CO: r = 0.41 

NO2: r = 0.29 

O3: r = 0.59 

Stockholm: PNC: r = 0.06 

CO: r = 0.41 

NO2: r = 0.29 

O3: r = 0.59 

PM Increment: 10 μg/m3 

Pooled Rate Ratio [CI]: 

All 5 cities (35+ yr) 

Same-day lag: 1.003 [0.995,1.011] 

1-day lag: 1.001 [0.990,1.011] 

2-day lag: 1.002 [0.994,1.010] 

3-day lag: 1.002 [0.991,1.013] 

3 cities with hospital discharge register 

(35+ yr) 

Same-day lag: 1.003 [0.994,1.012] 

1-day lag: 0.997 [0.988,1.006] 

2-day lag: 1.003 [0.995,1.012] 

3-day lag: 1.003 [0.986,1.020] 

Warm season (35+ yr) 

Same-day lag: 1.006 [0.990,1.022] 

1-day lag: 1.000 [0.985,1.016] 

2-day lag: 1.005 [0.990,1.020] 

3-day lag: 1.010 [0.995,1.025] 

Cold season (35+ yr) 

Same-day lag: 1.001 [0.991,1.012] 

1-day lag: 0.998 [0.987,1.009] 

2-day lag: 1.001 [0.991,1.012] 

3-day lag: 0.991 [0.981,1.002] 

Age >75 

Non-fatal 

Same-day lag: 1.012 [0.995,1.029] 

1-day lag: 1.000 [0.983,1.017] 

2-day lag: 0.999 [0.982,1.017] 

3-day lag: 1.001 [0.984,1.018] 

Fatal 

Same-day lag: 1.009 [0.985,1.034] 

1-day lag: 0.998 [0.974,1.023] 

2-day lag: 1.003 [0.978,1.028] 

3-day lag: 1.018 [0.975,1.063] 

Notes: Pooled rate ratios were also 

provided for groups <75 yielding similar 

results to the overall 3-city data.

December 2009 E-93 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lee et al. (2003, 095552) 

Period of Study: 

Dec 1997-Dec 1999 

Location: Seoul, Korea 

Outcome (ICD-10): Angina pectoris 

(I20), acute/subsequent myocardial 

infarction (I21-I23), other acute 

ischemic heart diseases (I24) 

Age Groups: All ages, 64+ yr 

Study Design: Time series 

N: 822 days 

Statistical Analyses: GAM with 

LOESS, Pearson correlation 

Covariates: Temperature, relative 

humidity, day of the week 

Season: Summer (Jun-Aug) and winter 

Dose-response Investigated: Yes 

Statistical Package: NR 

Lags Considered: 0-6 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 64.0 (31.8) 

Monitoring Stations: 27 

Copollutant (correlation): 

All yr 

SO2: r = 0.59 

NO2: r = 0.74 

O3: r = 0.11 

CO: r = 0.60 

Temp: r = -0.07 

Humidity: r = 0.02 

Summer 

SO2: r = 0.61 

NO2: r = 0.73 

O3: r = 0.64 

CO: r = 0.55 

Temp: r = -0.01 

Humidity: r = -0.11 

PM Increment: 40.4 μg/m3 (IQR) 

RR Estimate [CI]: All yr

All ages: 0.99 [0.96,1.01] 

64+ yr: 1.05 [1.01,1.10] 

Summer

All ages: 1.03 [0.97,1.09] 

64+ yr: 1.09 [1.00,1.19] 

Two-pollutant model

CO (1 ppm IQI): 1.04 [0.98,1.11] 

O3 (21.7 ppb IQI): 1.07 [1.03,1.11] 

NO2 (14.6 ppb IQI): 1.09 [1.02,1.16] 

SO2 (4.4 ppb): 0.98 [0.94,1.03] 

Reference: Lee et al. (2008, 192076) 

Period of Study: 1996-2005 

Location: Taipei, Taiwan 

Outcome: Congestive Heart Failure HA 

(ICD 9: 428) 

Age Groups: NR

Study Design: Case-crossover 

N: 18593 events 

Statistical Analyses: conditional 

logistic regression 

Covariates: Temperature, humidity 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Lags 0-2 

Pollutant: PM10

Averaging Time: 24 h 

Mean: 49.94

Min: 11.33 

25th: 33.37 

50th: 45.05 

75th: 60.82 

Max: 234.92 

Monitoring Stations: 6 

Copollutant: SO2, CO, NO2, O3

Co-pollutant Correlation 

SO2: 0.52 

CO: 0.67 

NO2: 0.35 

O3: 0.39 

PM Increment: Interquartile Range 

(27.45 μg/m3

) 

Odds Ratio (Lower CI, Upper CI): 

W/ Hypertension: 1.23 (1.15, 1.32) 

W/o Hypertension: 1.20 (1.15, 1.25) 

W/ Diabetes: 1.20 (1.12, 1.40) 

W/o Diabetes: 1.21 (1.15, 1.26) 

W/ Dysrhythmia: 1.17 (1.08, 1.27) 

W/o Dysrhythmia: 1.22 (1.17, 1.27) 

W/ COPD: 1.21 (1.07, 1.36) 

W/o COPD: 1.21 (1.16, 1.25) 

Reference: Larrieu et al. (2007, 

093031) 

Period of Study: 1998-2003 

Location: 

8 French urban area: Bordeaux, Le 

Havre, Lille, Lyon, Marseille, Paris, 

Rouen, and Toulouse 

Outcome (ICD-10): Hospital 

admissions for cardiovascular disease 

(I00-I99), cardiac disease (I00-I52), 

ischemic heart disease (I20-I25), and 

stroke (cerebrovascular disease: I60-64 

and transient ischemic attack: 

G45-G46). 

Age Groups: All, and 65 + 

Study Design: Time series

N: Statistical Analyses: generalized 

additive Poisson regression 

Covariates: Temperature, holidays, 

influenza epidemic periods, long-term 

trend, season, day of the week, 

Season: NR 

Dose-response Investigated: No 

Statistical Package: R 2.2.1 

Lags Considered: 0 –to 1-day lag 

(mean) 

Pollutant: PM10

Averaging Time: 24 h 

Mean: Bordeaux: 21.0 

Le Havre: 21.7 

Lille: 22.1 

Lyon: 24.6 

Marseille: 28.9 

Paris: 23.1 

Rouen: 21.2 

Toulouse: 21.8 

Monitoring Stations: 32 

Copollutant: NR 

PM Increment: 10 μg/m3

ERR [95% CI]: 

CVD: All ages: 0.7 [0.1, 1.2] 

65+ yr: 1.1 [0.5, 1.7] 

Cardiac diseases: All ages: 0.8 [0.2, 

1.4] 

65+ yr: 1.5 [0.7, 2.2] 

Ischemic heart diseases: All ages: 1.9 

[0.8, 3.0] 

65+ yr: 2.9 [1.5, 4.3] 

Strokes: All ages: 0.2 [-1.6, 1.9] 

65+ yr: 0.8 [-0.9, 2.5]

December 2009 E-94 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Le Tertre et al. (2002, 

023746) 

Period of Study: 1990-1997 

Location: 

Barcelona, Birmingham, London, Milan, 

the Netherlands, Paris, Rome, and 

Stockholm 

Outcome (ICD-9): Cardiac diseases 

(390-429), ischemic heart disease (410-

413), and stroke (430-438) 

Age Groups: <65 yr, 65+ yr 

Study Design: Time series 

N: NR 

Statistical Analyses: GAM 

Covariates: Long term trend, season, 

days of the week, holidays, influenza 

epidemics, temperature, and humidity 

Season: NR 

Dose-response Investigated: No 

Statistical Package: S-Plus 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Barcelona: 55.7 (18.4) 

Birmingham: 24.8 (13.1) 

London: 28.4 (12.3) 

Milan: 51.5 (22.7) 

Netherlands: 39.5 (19.9) 

Paris: 22.7 (10.8) 

Rome: 52.5 (12.9) 

Stockholm: 15.5 (7.2) 

Monitoring Stations: 1-12 

Copollutant: NR 

PM Increment: 10 μg/m3 

Pooled Percent Increase [CI]: Cardiac 

(all ages) 

Fixed: 0.5 [0.3,0.7] 

Random: 0.5 [0.2,0.8] 

Cardiac (over 65) 

Fixed: 0.7 [0.4,1.0] 

Random: 0.7 [0.4,1.0] 

IHD (<65) 

Fixed: 0.3 [-0.1,0.6] 

Random: 0.3 [-0.2,0.7] 

IHD (over 65) 

Fixed: 0.6 [0.3,0.8]; Random: 0.8 

[0.3,1.2] 

Stroke (over 65) 

Fixed: 0.0 [-0.3,0.3]; Random: 0.0 [-

0.3,0.3] 

Deaths: Cardiac: 0.5 [0.2,0.8]; Cardiac 

(65+): 0.7 [0.4,1.0] 

IHD (65+): 0.8 [0.3,1.2] 

Notes: Estimated percentage increases 

are also provided by city for cardiac 

admissions and ischemic heart disease 

in Fig 1-3.

Reference: Mann et al. (2002, 036723) 

Period of Study: 1988-1995 

Location: South Coast Air Basin, 

California 

Outcome (ICD-9): Ischemic heart 

disease (410-414), secondary 

congestive heart failure (sCHF) (428), 

and secondary arrhythmia (sARR) (426, 

427) 

Age Groups: All, 40-59 yr, >60 yr 

Study Design: Time series 

N: 54,863 IHD admissions 

Statistical Analyses: GAM 

Covariates: Temperature, day of the 

week, relative humidity 

Season: NR 

Dose-response Investigated: No 

Statistical Package: S-Plus 

Lags Considered: 0-5 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 43.7 (0.22-251) 

SD = 27.7 

Monitoring Stations: 20 

Copollutant (correlation): 

Region 1: 

CO: r = 0.28

O3: r = 0.20 

NO2: r = 0.36 

Region 2: 

CO: r = 0.15 

O3: r = 0.57 

NO2: r = 0.53 

Region 3: 

CO: r = 0.36 

O3: r = 0.30 

NO2: r = 0.46 

Region 4: 

CO: r = 0.27 

O3: r = 0.33 

NO2: r = 0.50 

Region 5: 

CO: r = 0.40 

O3: r = 0.43 

NO2: r = 0.53 

Region 6: 

CO: r = 0.33 

O3: r = 0.20 

NO2: r = 0.42 

Region 7: 

CO: r = 0.28 

O3: r = 0.48 

NO2: r = 0.60 

PM Increment: 10 μg/m3 

Percent Change in IHD Admissions 

[CI]: Secondary ARR 

Same-day lag: 0.59 [-0.71,1.91] 

1-day lag: 0.46 [-0.86,1.80] 

2-day lag: -0.04 [-1.37,1.31] 

Secondary CHF 

Same-day lag: -0.62 [-1.77,0.55] 

1-day lag: -0.45 [-1.60,0.71] 

2-day lag: -0.36 [-1.52,0.82] 

No secondary diagnosis 

Same-day lag: -0.25 [-1.23,0.75] 

1-day lag: 0.04 [-0.97,1.06] 

2-day lag: 0.18 [-0.82,1.20] 

All IHD admissions: 0.19 [-0.576,0.955] 

MI admissions: -0.10 [-1.33,1.12] 

Other acute IHD admissions: 0.36 [-

0.87,1.60]

December 2009 E-95 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Metzger et al. (2004, 

044222) 

Period of Study: Aug 1993-Aug 2000 

Location: Atlanta Metropolitan area 

(Georgia) 

Outcome (ICD-9): Emergency visits for 

ischemic heart disease (410-414), 

cardiac dysrhythmias (427), cardiac 

arrest (427.5), congestive heart failure 

(428), peripheral vascular and 

cerebrovascular disease (433-437, 440, 

443-444, 451-453), atherosclerosis 

(440), and stroke (436). 

Age Groups: All 

Study Design: Time series 

N: 4,407,535 emergency department 

visits 

Statistical Analyses: Poisson 

generalized linear modeling 

Covariates: Day of the wk, hospital 

entry and exit indicator variables, 

federally observed holidays, temporal 

trends, temperature, dew point 

temperature 

Season: All 

Dose-response Investigated: No 

Statistical Package: SAS 

Lags Considered: 3-day ma, lags 0 -7 

Pollutant: PM10

Averaging Time: 24 h 

Median (10% - 90% range): 26.3 (13.2, 

44.7)

Monitoring Stations: NR 

Copollutant (correlation): 

O3: r = 0.59 

NO2: r = 0.49 

CO: r = 0.47 

SO2: r = 0.20 

PM2.5: r = 0.84 

PM10-2.5: r = 0.59 

UFP: r = -0.13 

PM2.5 water-sol 

metals: r = 0.74 

PM2.5 sulfates: r = 0.74 

PM2.5 acidity: r = 0.68 

PM2.5 OC: r = 0.69 

PM2.5 EC: r = 0.56 

oxygenated hydrocarbon: r = 0.58 

Other variables: Temperature: r = 0.58 

Dew point: r = 0.44 

PM Increment: 10 μg/m3

(approximately 1 SD) 

RR [95% CI]: For 3-day ma: All CVD: 

1.009 [0.998, 1.019] 

Dysrhythmia: 1.008 [0.989, 1.029] 

Congestive heart failure: 0.992 

[0.968-1.016] 

Ischemic heart disease: 1.011 

[0.992-1.030] 

Peripheral vascular and 

cerebrovascular disease: 1.020 

[0.999-1.043] 

Notes: Results for Lags 0-7 expressed 

in figures 

Fig 1: RR (95% CI) for single-day lag 

models for the association of ER visits 

for CVD with daily ambient PM10. 

Summary: Statistically significant 

association at Lag 0. Positive but not 

statistically significant association at 

Lag 1. Negative, statistically significant 

association at Lag 7, and negative 

associations at Lag 2 through Lag 6. 

Reference: Middleton et al. (2008, 

156760) 

Period of Study: 1995-1998, 

2000-2004 

Location: Nicosia, Cyprus 

Outcome: Hospital admissions for all 

cardiovascular disease (ICD-10: 

I00-I52). 

Age Groups: All, also stratified by age 

(<15 vs.. >15 yr) 

Study Design: Time series

Statistical Analyses: Generalized 

additive Poisson models 

Covariates: Seasonality, day of the 

week, long- and short-term trend, 

temperature, relative humidity 

Dose-response Investigated: No 

Statistical Package: STATA SE 9.0, R 

2.2.0 

Lags Considered: Lag 0 -2 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD median 5% - 95% range): 

Cold: 57.6 (52.5 

50.8 

20.0-103.0 

5.0-1370.6)

Warm: 53.4 (50.5 

30.7 

32.0-77.6 

18.4-933.5) 

Monitoring Stations: 2 

Copollutant: NR 

PM Increment: 10 μg/m3, and across 

quartiles of increasing levels of PM10

Percentage increase estimate [CI]: 

All age/sex groups (Lag 0): All 

admissions: 0.85 (0.55, 1.15) 

Cardiovascular: 1.18 (-0.01, 2.37) 

Nicosia residents (Lag 0): 

Cardiovascular: 0.73 (-0.62, 2.09) 

Males (Lag 0): All admissions: 0.96 

(0.54, 1.39) 

Cardiovascular: 1.27 (-0.15, 2.72) 

Females (Lag 0): All admissions: 0.74 

(0.31, 1.18) 

Cardiovascular: 0.99 (-1.11, 3.14) 

Aged <15 yr (Lag 0): All admissions: 

0.47 (-0.13, 1.08) 

Aged >15 yr (Lag 0): All admissions: 

0.98 (0.63, 1.33)

December 2009 E-96 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peel et al. (2007, 090442) 

Period of Study: Jan 1993-Aug 2000 

Location: Atlanta, GA 

Outcome (ICD-9): Ischemic heart 

disease (410-414), dysrhythmia (427), 

congestive heart failure (428), 

peripheral vascular and 

cerebrovascular disease (433-437, 440, 

443, 444, 451-453) 

Age Groups: All 

Study Design: Case-crossover 

N: 4,407,535 ED visits 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Avg temp and dew point 

temp 

Season: NR 

Dose-response Investigated: No 

Statistical Package: SAS v. 9.1 

Lags Considered: 0-2 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): Daily levels: 27.9 (12.3) 

Diff in case and control-day avg: 9.1 

(7.5) 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: 10 μg/m3

OR Estimate [CI]: All CVD: 1.010 

[1.000,1.020] 

IHD: 1.009 [0.991,1.027] 

Dysrhythmia: 1.011 [0.991, 1.031] 

Peripheral/Cerebrovascular disease: 

1.017 [0.996,1.039] 

CHF: 1.001 [0.978,1.024] 

With comorbid hypertension 

IHD: 1.003 [0.973,1.034] 

Dysrhythmia: 1.037 [0.988,1.089] 

Peripheral/Cerebrovascular disease: 

1.024 [0.990,1.060] 

CHF: 1.041 [0.999,1.084] 

No comorbid hypertension 

IHD: 1.013 [0.991,1.036] 

Dysrhythmia: 1.006 [0.985,1.028] 

Peripheral/Cerebrovascular disease: 

1.013 [0.987,1.040] 

CHF: 0.982 [0.955,1.010] 

With comorbid diabetes 

IHD: 1.022 [0.979,1.067] 

Dysrhythmia: 1.049 [0.968,1.137] 

Peripheral/Cerebrovascular disease: 

1.016 [0.965,1.069] 

CHF: 1.029 [0.982,1.078] 

No comorbid diabetes 

IHD: 1.006 [0.987,1.026] 

Dysrhythmia: 1.009 [0.989,1.029] 

Peripheral/Cerebrovascular disease: 

1.018 [0.995,1.042] 

CHF: 0.992 [0.966,1.019] 

With comorbid COPD 

IHD: 0.981 [0.921,1.044] 

Dysrhythmia: 0.984 [0.889,1.088] 

Peripheral/Cerebrovascular disease: 

1.086 [0.998,1.181] 

CHF: 1.010 [0.954,1.069] 

No comorbid COPD 

IHD: 1.012 [0.993,1.031] 

Dysrhythmia: 1.012 [0.992,1.032] 

Peripheral/Cerebrovascular disease: 

1.013 [0.991,1.035] 

CHF: 0.999 [0.974,1.025]

Reference: Pope et al., (2006, 091246) 

Period of Study: 1994-2004 

Location: Wasatch Front area, Utah 

Outcome: Myocardial infarction or 

unstable angina (ICD codes not 

reported) 

Age Groups: All 

Study Design: Case-crossover 

N: 12,865 patients who underwent 

coronary arteriography 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and dew 

point temperature 

Season: NR 

Dose-response Investigated: No 

Statistical Package: NR 

Lags Considered: 0- to 3-day lag, 2- to 

4-day lagged ma 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD maximum): 

Ogden: 28.5 (16.5 

163) 

SLC Hawthorne: 27.7 (17.4 

162) 

Provo/Orem, Lindom: 32.7 (21.1 

240) 

SLC AMC: 35.9 (20.4 

161) 

SLC North: 45.1 (25.1 

199) 

Monitoring Stations: 5 

Copollutant: NR 

PM Increment: 10 μg/m3 

Percent increase in risk [95% CI]: 

Results summarized in Fig (see notes). 

Notes: Fig 1: Percent increase in risk 

(and 95% CI) of acute coronary events 

associated with 10 μg/m3

 of PM10 for 

different lag structures. 

Summary of Fig 1: Positive, statistically 

significant or marginally significant 

associations between association seen 

for Lag 0, Lag 1 and 2-, 3-, and 4-day 

ma. Non-statistically significant 

associations

December 2009 E-97 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Santos et al. (2008, 

192004) 

Period of Study: Jan 1998-Aug 1999 

Location: Sao Paulo, Bazil 

Outcome: Cardiac Arrhythmia ER Visits 

(ICD 10: I45-I49) 

Age Groups: 17+ yr

Study Design: Time series 

N: 3251 ER visits 

Statistical Analyses: Poisson 

Covariates: Temperature, humidity, 

seasonality 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 

Lags Considered: Lags 0-13 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 48.64 (20.34)

Min: 18.68 

Max: 137.76 

Monitoring Stations: 14 

Copollutant: SO2, CO, NO2, O3

Co-pollutant Correlation: 

SO2: 0.675* 

CO: 0.580* 

NO2: 0.781* 

O3: 0.438* 

*p < 0.01 

PM Increment: Interquartile Range 

(22.2 μg/m3

) 

Percent Increase (Lower CI, Upper 

CI): 

PM10+ NO2,CO: -5.6 (-12.7, 2.1) 

PM10+ CO: -1.1 (-7.0, 5.1) 

PM10+ NO2: -2.4 (-9.4, 5.1) 

Fig 1. PM10 effects, reported as percent 

increase, on arrhythmia ER visits 

caused by interquartile range increases, 

lags 0-6. 

Fig 2. Relative risks and 95% CI for 

arrhythmia ER visits according to the 

division of air pollutant daily 

concentrations in quintiles. 

Reference: Tolbert et al. (2007, 

090316) 

Period of Study: 1993-2004 

Location: Atlanta Metropolitan area, 

Georgia 

Outcome (ICD-9): Combined CVD 

group, including: Ischemic heart 

disease (410-414), cardiac 

dysrhythmias (427), congestive heart 

failure (428), and peripheral vascular 

and cardiovascular disease (433-437, 

440, 443-445, and 451-453).

Age Groups: All 

Study Design: Time series 

N: 10,234,490 ER visits (283,360 and 

1,072,429 visits included in the CVD 

and RD groups, respectively) 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Long-term temporal trends, 

season (for RD outcome), temperature, 

dew point, days of week, federal 

holidays, hospital entry and exit 

Season: All 

Dose-response Investigated: No 

Statistical Package: SAS version 9.1 

Lags Considered: 3-day ma (lag 0-2) 

Pollutant: PM10

Averaging Time: 24 h 

Mean (median 

IQR, range, 10th-90th percentiles): 

26.6 (24.8 

17.5-33.8 

0.5-98.4 

12.3-42.8) 

Monitoring Stations: NR 

Copollutant (correlation): 

O3: r = 0.59 

NO2: r = 0.53 

CO: r = 0.51 

SO2: r = 0.21 

Coarse PM: r = 0.67 

PM2.5: r = 0.84 

PM2.5 SO4: r = 0.69 

PM2.5 EC: r = 0.61 

PM2.5 OC: r = 0.65 

PM2.5 TC: r = 0.67 

PM2.5 water-sol metals: r = 0.73 

OHC: r = 0.53 

PM Increment: 16.30 μg/m3 (IQR) 

Risk ratio [95% CI]: Single pollutant 

models: CVD: 1.008 (0.997-1.020) 

Reference: Tsai et al. (2003, 080133) 

Period of Study: 1997-2000 

Location: Kaohsiung, Taiwan 

Outcome (ICD-9): Cerebrovascular 

diseases (430-438), subarachnoid 

hemorrhagic stroke (430), primary 

intracerebral hemorrhage (431-432), 

ischemic stroke (433-435), and others 

(436-438) 

Age Groups: All 

Study Design: Case-crossover 

N: 23,179 admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and humidity 

Season: NR 

Dose-response Investigated: No 

Statistical Package: SAS 

Lags Considered: Cumulative 0-2 

days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 78.82 (20.50-217.33) 

Monitoring Stations: 6 

Copollutant: NR 

PM Increment: 66.33 μg/m3 (IQR) 

OR Estimate [CI]: Two-pollutant 

model (all stroke admissions)

Primary intracerebral hemorrhage (PIH) 

Adj for SO2: 1.55 [1.31,1.83] 

Adj for NO2: 1.28 [1.01,1.61]; 

Adj for CO: 1.45 [1.20,1.74] 

Adj for O3: 1.56 [1.27,1.91] 

Ischemic stroke (IS) 

Adj for SO2: 1.46 [1.32,1.61] 

Adj for NO2: 1.16 [1.01,1.34] 

Adj for CO: 1.35 [1.21,1.51] 

Adj for O3: 1.51 [1.34,1.71] 

Single-pollutant model 

Temp >20oC 

PIH: 1.54 [1.31,1.81] 

IS: 1.46 [1.32,1.61] 

Temp <20oC 

PIH: 0.82 [0.48,1.40] 

IS: 0.97 [0.65,1.44] 

December 2009 E-98 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ulirsch et al. (2007, 

091332) 

Period of Study: Nov 1994-Mar 2000 

Location: 

Pocatello, Idaho and Chubbuck, Idaho 

Outcome (ICD-9): CVD (390-429). 

Age Groups: 65 + 

Study Design: Time series

N: 39,347 admissions/visits 

Statistical Analyses: Log-linear 

generalized linear models 

Covariates: Time, temperature, relative 

humidity, influenza, day of the week 

Season: All, and separate analyses 

were performed for the all-age group for 

cool months (Oct-Mar) vs.. warm 

months (Apr-Sep). 

Dose-response Investigated: No 

Statistical Package: S-plus version 6.1 

Lags Considered: 0- to 4-day lags, 

and mean of days 0 -4 

Pollutant: PM10

Averaging Time: 24 h 

Mean (range 10th - 90th percentiles): 

24.2 (3.0-183.0 

10.5-40.7) 

Monitoring Stations: 4 

Copollutant (correlation): 

NO2: r = 0.47 

Other variables: Correlation for PM10

between monitors: r = 0.42-0.87 

PM Increment: 50 μg/m3 , and 

24.3 μg/m3

 (mean increase in PM10) 

Mean percent of change (% change 

in the mean number of daily 

admissions and visits) [95% CI]: 

For 24.3 μg/m3

 increase in PM10: 

All-age RD/CVD: 3.7 [1.3, 6.3] 

All-age CVD (Lag 0): -0.02 [-5.9, 6.3] 

All-age CVD (Lag 1): 1.9 [-4.1, 8.4] 

All-age CVD (Lag 2): -3.1 [-9.1, 3.4] 

All-age CVD (Lag 3): 0.5 [-5.6, 6.9] 

All-age CVD (Lag 4): -1.7 [-4.3, 0.9] 

Lag 0-4 days: -0.5 [-8.0, 7.6] 

For 50 μg/m3 increase in PM10 

(single pollutant models, CIs not 

given): 

All-age respiratory disease: 8.4 

All-age RD/CVD: 7.9 

18-64 yr RD: 7.2 

All-age CVD (Lag 3): 1.0 

All-age CVD (Lag 4): -3.6 

All-age CVD (Lag 0 -4): -1.1 

Notes: Included urgent care visits as 

well as emergency department visits 

and hospital admissions. 

Reference: Yang et al. (2007, 092847) 

Period of Study: 1996-2005 

Location: Taipei, Taiwan 

Outcome: Congestive Heart Failure HA 

(ICD 9: 428) 

Age Groups: NR 

Study Design: case-crossover 

N: 24,240 events 

Statistical Analyses: Poisson 

Covariates: Temperature, humidity 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: lags 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean: 49.47

Min: 14.42 

25th: 33.08 

50th: 44.71 

75th: 60.10 

Max: 234.91 

Monitoring Stations: 6 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: Interquartile Range 

(27.02 μg/m3

) 

Odds Ratio (Lower CI, Upper CI): 

Temp ≥20°C 

PM10: 1.15 (1.10-1.21)* 

PM10+ SO2: 1.23 (1.17, 1.30)* 

PM10+ NO2: 1.03 (0.97, 1.10) 

PM10+ CO2: 1.09 (1.03, 1.15)* 

PM10+ O3: 1.10 (1.04, 1.15)* 

Temp <20°C 

PM10: 0.99 (0.93, 1.05) 

PM10+ SO2: 0.96 (0.89, 1.03) 

PM10+ NO2: 0.97 (0.90, 1.04) 

PM10+ CO2: 0.96 (0.90, 1.03) 

PM10+ O3: 1.00 (0.94, 1.05) 

*p < 0.05 

Reference: Yang et al. (2007, 092847) 

Period of Study: 1996-2001 

Location: Taipei, Taiwan 

Outcome: Congestive Heart Failure HA

Age Groups: NR 

Study Design: case-crossover 

N: NR 

Statistical Analyses: Poisson 

Covariates: NR 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Lags 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Index days: 111.68 (38.32) 

Comparison days: 55.43 (24.66) 

Monitoring Stations: 7 

Copollutant: NR 

Co-pollutant Correlation: N/A 

PM Increment: Index (>125 μg/m3) vs.. 

Comparison (≤125 μg/m3

) 

Relative Risk (Lower CI, Upper CI), 

lag: 

0.915 (0.805, 1.041), lag 0 

1.114 (0.993, 1.250), lag 1 

0.983 (0.873, 1.106), lag 2 

0.974 (0.870, 1.090), lag 3 

December 2009 E-99 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Villeneuve et al. (2006, 

090191) 

Period of Study: Apr 1992-Mar 2002

Location: Edmonton, Canada 

Outcome (ICD-9): Stroke (430-438), 

including ischemic stroke (434-436), 

hemorrhagic stroke (430,432), and 

transient ischemic attacks (TIA) (435). 

Age Groups: 65+ yr

Study Design: Case-crossover 

N: 12,422 visits 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and relative 

humidity 

Season: summer (Apr-Sep), winter 

(Oct-Mar)

Dose-response Investigated: No

Statistical Package: SAS (PHREG) 

Lags Considered: 0, 1, and 3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

All yr: 

24.2 (14.8) 

Summer: 25.9 (16.4) 

Winter: 22.6 (12.9) 

Monitoring Stations: 3 

Copollutant (correlation): 

All yr 

SO2: r = 0.19 

NO2: r = 0.34; 

CO: r = 0.30 

O3-mean: r = 0.07; 

O3-max: r = 0.22 

PM2.5: r = 0.79 

Summer 

SO2: r = 0.18 

NO2: r = 0.57; 

CO: r = 0.38 

O3-mean: r = 0.20; 

O3-max: r = 0.40 

PM2.5: r = 0.85 

Winter 

SO2: r = 0.27 

NO2: r = 0.48; 

CO: r = 0.53 

O3-mean: r = -0.26; 

O3-max: r = -0.09 

PM2.5: r = 0.70 

PM Increment: μg/m3 (IQR) 

All yr: 16.0 

Summer: 17.5 

Winter: 16.0 

Adjusted OR Estimate [CI]: Acute 

ischemic stroke 

All yr 

Same-day lag: 0.98 [0.94,1.03] 

1-day lag: 1.00 [0.96,1.05] 

3-day lag: 0.99 [.93,1.05] 

summer 

Same-day lag: 0.93 [0.87,1.00] 

1-day lag: 1.01 [0.94,1.08] 

3-day lag: 0.96 [0.88,1.04] 

Winter 

Same-day lag: 1.04 [0.97,1.11] 

1-day lag: 1.00 [0.94,1.06]; 

3-day lag: 1.05 [0.95,1.15] 

Hemorrhagic stroke 

All yr 

Same-day lag: 1.01 [0.90,1.12] 

1-day lag: 1.03 [0.93,1.15] 

3-day lag: 1.13 [0.98,1.30] 

summer 

Same-day lag: 1.02 [0.88,1.20] 

1-day lag: 1.07 [0.91,1.26] 

3-day lag: 1.20 [0.98,1.46] 

Winter 

Same-day lag: 1.05 [0.90,1.22] 

1-day lag: 1.04 [0.91,1.19] 

3-day lag: 1.11 [0.90,1.37] 

Transient cerebral ischemic attack 

All yr 

Same-day lag: 0.96 [0.90,1.02] 

1-day lag: 0.99 [0.94,1.05] 

3-day lag: 0.94 [0.87,1.01] 

summer 

Same-day lag: 0.97 [0.89,1.09] 

1-day lag: 0.99 [0.91,1.08] 

3-day lag: 0.94 [0.84,1.04] 

Winter 

Same-day lag: 0.95 [0.87,1.04] 

1-day lag: 0.99 [0.92,1.07] 

3-day lag: 0.93 [0.83,1.05] 

Notes: Adjusted ORs are provided for 

an IQR increase in the 3-day mean in 

Fig 1-4 for single and two-pollutant 

models. 

December 2009 E-100 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: von Klot et al. (2005, 

088070) 

Period of Study: 1992-2001

Location: 

Augsburg, Germany 

Barcelona, Spain 

Helsinki, Finland 

Rome, Italy 

Stockholm, Sweden 

Outcome (ICD-9): Acute myocardial 

infarction (410 

ICD-10: I21-I22), angina pectoris (411, 

413 

ICD-10: I20, I24), dysrhythmia (427 

ICD-10: I46.0, 46.9, I47-I49, R00.1, 

R00.8), heart failure (428 

ICD-10: 150) 

Age Groups: 35+ yr

Study Design: Cohort 

N: 22,006 MI survivors 

Statistical Analyses: GAM, Spearman 

correlation 

Covariates: Temperature, dew point 

temp, avg barometric pressure, relative 

humidity 

Season: NR

Dose-response Investigated: No

Statistical Package: R 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (5th-95th percentile): 

Augsburg: 44.7 (16.8-81.4) 

Barcelona: 52.2 (25.3-89.2) 

Helsinki: 25.3 (9.5-57.6) 

Rome: 51.1 (23.3-89.4) 

Stockholm: 14.6 (6.4-30.0) 

Monitoring Stations: NR 

Copollutant (correlation): 

Augsburg 

PNC: r = 0.52 

CO: r = 0.57; 

NO2: r = 0.64 

O3: r = -0.32 

Barcelona 

PNC: r = 0.29 

CO: r = 0.39; 

NO2: r = 0.36 

O3: r = -0.14 

Helsinki 

PNC: r = 0.46 

CO: r = 0.21; 

NO2: r = 0.40 

O3: r = 0.02 

Rome 

PNC: r = 0.33 

CO: r = 0.31; 

NO2: r = 0.48 

O3: r = -0.22 

Stockholm 

PNC: r = 0.06 

CO: r = 0.38; 

NO2: r = 0.29 

O3: r = 0.15 

PM Increment: 10 μg/m3 

Pooled RR Estimate [CI]: 

All cardiac admissions: 1.021 

[1.005,1.048] 

Myocardial infarction: 1.026 

[0.995,1.058] 

Angina pectoris: 1.008 [0.986,1.032] 

Notes: Rate ratios for 0-3 day lags are 

provided in graphical form (Fig 1). 

Same-day levels were significantly 

associated with cardiac readmissions. 

Reference: Wellenius et al. (2005, 

087483) 

Period of Study: Jan 1987-Nov 1999

Location: Pittsburgh, Pennsylvania 

Outcome (ICD-9): Congestive heart 

failure (428.0-428.1) 

Age Groups: 65+ yr

Study Design: Case-crossover 

N: 55,019 patients 

Statistical Analyses: Conditional 

logistic regression, Pearson’s pairwise 

correlation 

Covariates: Temperature, barometric 

pressure, dew point 

Season: NR

Dose-response Investigated: No

Statistical Package: SAS 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (5th-95th percentile): 

31.06 (8.89-70.49) 

SD = 20.10 

Monitoring Stations: 17 

Copollutant (correlation): 

CO: r = 0.57 

NO2: r = 0.64 

O3: r = 0.29 

SO2: r = 0.51 

PM Increment: 24 μg/m3 (IQR) 

Percent Increase [CI]: Single-pollutant: 

3.07 [1.59,4.57] 

Adj. for CO: -1.10 [-3.02,0.86] 

Adj. for NO2: 0.52 [-1.46,2.53] 

Adj. for O3: 2.80 [1.29,4.33] 

Adj. for SO2: 2.18 [0.37,4.02] 

Percent Increase (with 10 μg/m3

increment) 

1.27 [0.66,1.88] 

December 2009 E-101 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Wellenius et al. (2005, 

088685) 

Period of Study: 

Jan 1986-Nov 1999

Location: 

Birmingham, Chicago, Cleveland, 

Detroit, Minneapolis, New Haven, 

Pittsburgh, Salt Lake City, Seattle 

Outcome (ICD-NR): Ischemic stroke 

and hemorrhagic stroke 

Age Groups: 65+ yr

Study Design: Case-crossover (timestratified) 

N: 115,503 hospital admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and humidity 

Season: NR

Dose-response Investigated: No

Statistical Package: SAS (v.9) and Rstatistical package 

Lags Considered: 0-2 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 32.69 (19.75) 

Monitoring Stations: NR 

(data obtained from the U.S. EPA) 

Copollutant (correlation): 

CO: r = 0.43 

NO2: r = 0.53 

SO2: r = 0.39 

Other variables: Temp: r = 0.22 

PM Increment: 22.96 μg/m3 (IQR) 

Percent Increase [CI]: Ischemic (sameday lag): 1.03 [0.04,2.04] 

Hemorrhagic: -0.58 [-5.48,4.58] 

Notes: Percent increase in rate for 

ischemic and hemorrhagic stroke are 

provided for each city in graphical form 

(Fig A and B). 

Reference: Wellenius et al.,(2006, 

088748) 

Period of Study: 

Jan 1986-Nov 1999

Location: 

Birmingham, Chicago, Cleveland, 

Detroit, Minneapolis, New Haven, 

Pittsburgh, Salt Lake City, Seattle 

Outcome (ICD-9): Congestive heart 

failure (428) 

Age Groups: 65+ yr

Study Design: Case-crossover (timestratified) 

N: 292,918 admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and 

barometric pressure 

Season: NR

Dose-response Investigated: No

Statistical Package: SAS (v.9) and Rstatistical package 

Lags Considered: 0-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Median: Overall: 28.3 

Birmingham: 33.0 

Chicago: 31.5 

Cleveland: 34.5 

Detroit: 29.5 

Minneapolis: 24.0 

New Haven: 22. 

Seattle: 25.8 

Monitoring Stations: NR 

(data obtained from the U.S. EPA) 

Copollutant: NR 

PM Increment: 10 μg/m3 

Percent Increase [CI]: Same-day lag: 

0.72 [0.35,1.10] 

p-value = 0.0002 

Notes: City-specific percent increases 

are graphed in Fig 1 for same-day lag 

showing a significant association in 

Chicago, Detroit, Seattle, and the 

summary values. 

Percent increase in admission rate s 

are provided for lag 0-3 days in Fig 2 

where same-day lag showed a 

significant association. 

Reference: Yang et al. (2004, 094376) 

Period of Study: 1997-2000

Location: Kaohsiung, Taiwan 

Outcome (ICD-9): Cardiovascular 

diseases (410-429) 

Age Groups: All

Study Design: Case-crossover 

N: 29,661 admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and humidity 

Season: NR

Dose-response Investigated: No

Statistical Package: SAS 

Lags Considered: Cumulative 0-2 

days 

Pollutant: PM10

Averaging Time: 24 h 

Median (min-max): 78.82 (20.50-

217.33) 

Monitoring Stations: 6 

Copollutant: NR 

PM Increment: 66.33 μg/m3 (IQR) 

OR Estimate [CI]: Temp >25oC: 1.439 

[1.316,1.573] 

Temp <25oC: 1.568 [1.433,1.715] 

Adj for SO2

Temp >25oC: 1.460 [1.333,1.599] 

Temp <25oC: 1.543 [1.404,1.696] 

Adj for NO2 

Temp >25oC: 1.306 [1.154,1.478] 

Temp <25oC: 0.912 [0.809,1.028] 

Adj for CO 

Temp >25oC: 1.260 [1.144,1.388] 

Temp <25oC: 1.259 [1.128,1.406] 

Adj for O3 Temp >25oC: 1.086 [0.967,1.220] 

Temp <25oC: 1.703 [1.541,1.883] 

December 2009 E-102 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yang et al. (2008, 157160) 

Period of Study: 1996-2004

Location: Taipei, Taiwan 

Outcome (ICD-9): Congestive heart 

failure (428) 

Age Groups: All

Study Design: Case-crossover 

N: 24,240 CHF hospital admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: temperature, humidity 

Season: All

Dose-response Investigated: No

Statistical Package: SAS 

Lags Considered: Cumulative lag 0-2 

days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (median, range, IQR): 

49.47 (44.71, 14.42-234.91, 

33.08-44.71) 

Monitoring Stations: 6 

Copollutant: NR 

PM Increment: 27.02 μg/m3 (IQR) 

OR [95% CI]: 

Single pollutant models: >20 °C: 1.15 

[1.10-1.21] 

<20 °C: 0.99 [0.93-1.05] 

Adjusted for SO2: ≥ 20 °C: 1.23 

[1.17-1.30] 

<20 °C: 0.96 [0.89-1.03] 

Adjusted for NO2: ≥ 20 °C: 1.03 

[0.97-1.10] 

<20 °C: 0.97 [0.90-1.04] 

Adjusted for CO: ≥ 20 °C: 1.09 

[1.03-1.15] 

<20 °C: 0.96 [0.90-1.03] 

Adjusted for O3: ≥ 20 °C: 1.10 

[1.04-1.15] 

<20 °C: 1.00 [0.94-1.05]

Reference: Zanobetti and Schwartz 

(2002, 034821) 

Period of Study: 1988-1994

Location: 

Cook county (Chicago), Illinois 

Wayne county (Detroit), Michigan 

Allegheny county (Pittsburgh), 

Pennsylvania 

and King county (Seattle), Washington 

Outcome (ICD-9): Cardiovascular 

disease (390-429) with/without diabetes 

(250) 

Age Groups: 65-74 and 75+ yr with 

diabetes, 65-74 and 75+ yr without 

diabetes

Study Design: Time series 

N: NR 

Statistical Analyses: GAM, metaregression 

Covariates: Temperature, prior day’s 

temperature, relative humidity, 

barometric pressure, day of the week 

Season: NR

Dose-response Investigated: No 

Pollutant: PM10

Averaging Time: 24 h 

Median (25-75th percentile): 

Chicago: 33 (23-46) 

Detroit: 32 (21-49) 

Pittsburgh: 30 (19-47) 

Seattle: 27 (18-39) 

Monitoring Stations: NR (obtained 

from USEPA Aerometric Information 

Retrieval System) 

Copollutant: NR 

PM Increment: 10 μg/m3 

Percent Change [CI]: 

All 4 cities 

<75 (w/ diabetes): 1.6 [1.2,2.0] 

75+ (w/ diabetes): 2.0 [1.6,2.4] 

<75 (w/o diabetes): 0.9 [0.6,1.1] 

75+ (w/o diabetes): 1.3 [1.0,1.5] 

Chicago 

<75 (w/ diabetes): 1.9 [1.1,2.7] 

75+ (w/ diabetes): 2.0 [1.1,3.0] 

<75 (w/o diabetes): 0.7 [0.2,1.2] 

75+ (w/o diabetes): 1.2 [0.8,1.7] 

Detroit 

<75 (w/ diabetes): 1.3 [0.5,2.2] 

75+ (w/ diabetes): 2.1 [1.0,3.1] 

<75 (w/o diabetes): 1.2 [0.7,1.7] 

75+ (w/o diabetes): 1.2 [0.7,1.6] 

Pittsburgh 

<75 (w/ diabetes): 1.8 [0.9,2.7] 

75+ (w/ diabetes): 0.9 [-0.2,2.0] 

<75 (w/o diabetes): 0.6 [0.1,1.2] 

75+ (w/o diabetes): 1.6 [1.2,2.1] 

Seattle 

<75 (w/ diabetes): 1.9 [0.1,3.7] 

75+ (w/ diabetes): 2.7 [0.7,4.8] 

<75 (w/o diabetes): 0.8 [0.0,1.6] 

75+ (w/o diabetes): 0.9 [0.2,1.6] 

Notes: Overall percent increases were 

also provided for each city, yielding 

similar results.

December 2009 E-103 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zanobetti and Schwartz 

(2005, 088069) 

Period of Study: 1985-1999

Location: 

21 U.S. cities (Birmingham, Alabama 

Boulder, Colorado 

Canton, Ohio 

Chicago, Illinois 

Cincinnati, Ohio 

Cleveland, Ohio 

Colorado Springs, Colorado 

Detroit, Michigan 

Honolulu, Hawaii 

Houston, Texas 

Minneapolis-St. Paul, Minnesota 

Nashville, Tennessee 

New Haven, Connecticut 

Pittsburgh, Pennsylvania 

Provo-Orem, Utah 

Salt Lake City, Utah 

Seattle, Washington 

Steubenville, Ohio 

Youngstown, Ohio) 

Outcome (ICD-9): Myocardial infarction 

(410) 

Age Groups: >65 yr

Study Design: Case-crossover 

N: 302,453 admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature 

Season: NR

Dose-response Investigated: Yes

Statistical Package: SAS (PROC 

PHREG) 

Lags Considered: 0-2 days 

Pollutant: PM10

Averaging Time: 24 h 

Median: Ranged from 15.5-34.1Avg 

across all cities = 27 

Monitoring Stations: 1+ (data obtained 

from USEPA’s Aerometric Information 

Retrieval System) 

Copollutant: NR 

PM Increment: 10 μg/m3 

Percent Increase [CI]: MI only: 0.65 

[0.3,1] 

Previous COPD admission: 1.3 [-

0.1,2.8] 

Secondary pneumonia diagnosis: 1.4 [-

0.8,3.6] 

Notes: Fig 1 presents percent change 

in MI per lag day, showing same-day 

lag to be significant. Fig 2 shows 

percent change with/without other comorbidities. 

1

All units expressed in μg/m3 unless otherwise specified.

Table E-6. Short-term exposure-cardiovascular-ED/HA - PM10-2.5. 

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Halonen et al. (2009, 

180379) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome: Cardiovascular 

Hospitalizations & Mortality (ICD 10: 

I00-99) 

Age Groups: 65+ yr

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson, GAM 

Covariates: Temperature, humidity, 

influenza epidemics, high pollen 

episodes, holidays 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: lags 0-3 days; 5-day 

(0-4) mean 

Pollutant: PM10-2.5

Averaging Time: Daily 

Mean (SD): NR

Min: 0.0 

25th percentile: 4.9 

50th percentile: 7.5 

75th percentile: 12.1 

Max: 101.4

Monitoring Stations: NR 

Copollutant: 

PM<0.03, PM0.03-0.1, PM<0.1, 

PM<0.10.29, PM2.5, CO, NO2

Co-pollutant Correlation 

PM<0.03: 0.14 

PM0.03-0.1: 0.28 

PM<0.1: 0.24 

PM<0.10.29: 0.20 

PM2.5: 0.25 

PM Increment: Interquartile Range 

Percent Change (Lower CI, Upper 

CI): 

All Cardiovascular Morality 

Lag 0: -0.01 (-1.52, 1.53) 

Lag 1: -0.26 (-1.69, 1.18) 

Lag 2: -0.61 (-2.03, 0.83) 

Lag 3: -0.57 (-1.98, 0.85) 

5-day mean: -0.70 (-2.56, 1.20) 

Coronary Heart Disease HA 

Lag 0: 1.12 (-0.28, 2.55) 

Lag 1: -0.38 (-1.68, 0.94) 

Lag 2: 0.01 (-1.33, 1.37) 

Lag 3: -0.53 (-1.82, 0.78) 

5-day mean: 0.23 (-0.29, 0.75) 

Stroke HA 

Lag 0: -1.33 (-3.26, 0.63) 

Lag 1: -1.90 (-3.82, 0.07) ‡ 

Lag 2: -1.09 (-3.04, 0.89) 

Lag 3: -0.51 (-2.40, 1.43) 

5-day mean: -2.21 (-4.75, 0.39) 

Arrhythmia HA 

Lag 0: 0.57 (-1.33, 2.49) 

Lag 1: -0.65 (-2.55, 1.29) 

Lag 2: 0.02 (-1.93, 2.00) 

Lag 3: -1.34 (-3.26, 0.62) 

5-day mean: -1.11 (-3.68, 1.53) 

*p < 0.05, ‡p < 0.10 

December 2009 E-104 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Host et al. (2008, 

155852)(Host et al., 2008, 155852) 

Period of Study: 2000-2003

Location: Six French cities: Le Havre, 

Lille, Marseille, Paris, Rouen, and 

Toulouse 

Outcome (ICD-10): Daily 

hospitalizations for all cardiovascular 

(I00-I99), cardiac (I00-I52), and 

ischemic heart diseases (I20-I25). 

Age Groups: For cardiovascular 

diseases: All ages, and restricted to ≥

65 yr 

Study Design: Time series 

N: NR (Total population of cities: 

approximately 10 million) 

Statistical Analyses: Poisson 

regression 

Covariates: Seasons, days of the 

week, holidays, influenza epidemics, 

pollen counts, temperature, and 

temporal trends

Dose-response Investigated: No

Statistical Package: MGCV package in 

R software (R 2.1.1) 

Lags Considered: Avg of 0-1 days 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean μg/m3 (5th -95th percentile): 

Le Havre: 7.3 (2.5-14.0) 

Lille: 7.9 (2.2-13.7) 

Marseille: 11.0 (4.5-21.0) 

Paris: 8.3 (3.2-15.9) 

Rouen: 7.0 (3.0-12.5) 

Toulouse: 7.7 (3.0-15.0) 

Monitoring Stations: 

13 total: 

1 in Toulouse 

4 in Paris 

2 each in other cities 

Copollutant (correlation): PM2.5: 

Overall: r>0.6 

Ranged between r = 0.28 and r = 0.73 

across the six cities. 

PM Increment: 10 μg/m3 , and an 

18.8 μg/m3

 increase (corresponding to 

an increase in pollutant levels between 

the lowest of the 5th percentiles and the 

highest of the 95th percentiles of the 

cities’ distributions) 

ERR (excess relative risk) Estimate [CI]: 

For all cardiovascular diseases 

(10 μg/m3

 increase): All ages: 0.5% [-

1.2, 2.3] 

≥ 65 yr: 1.0% [-1.0, 3.0] 

For all cardiovascular diseases 

(18 μg/m3

 increase): All ages: 1.0% [-

2.3, 4.3] 

≥ 65 yr: 1.9% [-2.0, 5.9] 

For cardiac diseases (10 μg/m3

increase): All ages: 0.1% [-1.9, 2.1] 

≥ 65 yr: 1.6% [-0.8, 4.1] 

For cardiac diseases (18.8 μg/m3

increase): All ages: 0.1% [-3.6, 4.0] 

≥ 65 yr: 3.1% [-1.5, 7.9] 

For ischemic heart diseases (10 μg/m3

increase): All ages: 2.8% [-0.8, 6.6] 

≥ 65 yr: 6.4% [1.6, 11.4] 

For ischemic heart diseases (18 μg/m3

increase): All ages: 5.4% [-1.5, 12.8] 

≥ 65 yr: 12.4 [3.1, 22.6] 

Reference: Metzger et al. (2004, 

044222) 

Period of Study: Aug 1998-Aug 2000

Location: Atlanta Metropolitan area 

(Georgia) 

Outcome (ICD-9): Emergency visits for 

ischemic heart disease (410-414), 

cardiac dysrhythmias (427), cardiac 

arrest (427.5), congestive heart failure 

(428), peripheral vascular and 

cerebrovascular disease (433-437, 440, 

443-444, 451-453), atherosclerosis 

(440), and stroke (436). 

Age Groups: All

Study Design: Time series 

N: 4,407,535 emergency department 

visits between 1993-2000 (data not 

reported for 1998 - 2000) 

Statistical Analyses: Poisson 

generalized linear modeling 

Covariates: Day of the wk, hospital 

entry and exit indicator variables, 

federally observed holidays, temporal 

trends, temperature, dew point 

temperature 

Season: All

Dose-response Investigated: No

Statistical Package: SAS 

Lags Considered: 3-day ma; lags 0 -7 

Pollutant: PM10 -2.5 

Averaging Time: 24 h 

Median μg/m3 (10% - 90% range): 

9.1 (4.4, 16.2) 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10: r = 0.59 

O3: r = 0.35 

NO2: r = 0.46 

CO: r = 0.32 

SO2: r = 0.21 

PM2.5: r = 0.43 

UFP: r = 0.13 

PM2.5 water 

soluble metals: r = 0.47 

PM2.5 sulfates: r = 0.26 

PM2.5 acidity: r = 0.23 

PM2.5 OC: r = 0.51 

PM2.5 EC: r = 0.48 

PM2.5 oxygenated hydrocarbon: r = 0.31

Other variables: Temperature: r = 0.20 

Dew point: r = 0.00 

PM Increment: 5 μg/m3 (approximately 

1 SD) 

RR [95% CI]: For 3 day ma: All CVD: 

1.012 [0.985, 1.040] 

Dysrhythmia: 1.021 [0.974, 1.070] 

Congestive heart failure: 1.020 

[0.964-1.079] 

Ischemic heart disease: 0.994 

[0.946-1.045] 

Peripheral vascular and 

cerebrovascular disease: 1.022 

[0.972-1.074]] 

Results for Lags 0-7 expressed in 

figures (see notes). 

Notes: Fig 1: RR (95% CI) for singleday lag models for the association of 

ER visits for CVD with daily ambient 

PM10-2.5. 

Summary of Fig 1 results: Positive 

association at Lag 0. 

December 2009 E-105 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peng et al. (2008, 156850) 

Period of Study: Jan 1999-Dec 2005

Location: 108 U.S. counties in the 

following states: Alabama, Arizona, 

California, Colorado, Connecticut, 

District of Columbia, Florida, Georgia, 

Idaho, Illinois, Indiana, Kentucky, 

Louisiana, Maine, Maryland, 

Massachusetts, Michigan, Minnesota, 

Missouri, Nevada, New Hampshire, 

New Jersey, New Mexico, New York, 

North Carolina, Ohio, Oklahoma, 

Oregon, Pennsylvania, Rhode Island, 

South Carolina, Tennessee, Texas, 

Utah, Virginia, Washington, West 

Virginia, Wisconsin 

Outcome (ICD-9): Emergency 

hospitalizations for: Cardiovascular 

disease, including heart failure (428), 

heart rhythm disturbances (426-427), 

cerebrovascular events (430-438), 

ischemic heart disease (410-414, 429), 

and peripheral vascular disease 

(440-448). 

Age Groups: 65 + yr, 65-74, 75+

Study Design: Time series 

N: approximately 12 million Medicare 

enrollees (3.7 million CVD and 1.4 

million RD admissions) 

Statistical Analyses: Two-stage 

Bayesian hierarchical models: 

Overdispersed Poisson models for 

county-specific data. Bayesian 

hierarchical models to obtain national 

avg estimate 

Covariates: Day of the wk, age-specific 

intercept, temperature, dew point 

temperature, calendar time, indicator for 

age of 75 yr or older. Some models 

were adjusted for PM2.5. 

Dose-response Investigated: No

Statistical Package: R version 2.6.2 

Lags Considered: 0-2 days 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean μg/m3 (IQR): 

All counties assessed: 9.8 (6.9-15.0) 

Counties in Eastern U.S.: 9.1 (6.6-13.1) 

Counties in Western U.S.: 15.4 

(10.3-21.8) 

Monitoring Stations: At least 1 pair of 

co-located monitors (physically located 

in the same place) for PM10 and PM2.5

per county 

Copollutant (correlation): 

PM2.5: r = 0.12 

PM10: r = 0.75 

Other variables: Median within-county 

correlations between monitors: r = 0.60 

PM Increment: 10 μg/m3 

Percentage change [95% CI]: CVD: Lag 

0 (unadjusted for PM2.5): 0.36 [0.05, 

0.68] 

Lag 0 (adjusted for PM2.5): 0.25 [-0.11, 

0.60] 

Notes: Effect estimates for PM10-2.5 (0-2 

day lags) are showing in Fig 2-5. 

Fig 2: Percentage change in emergency 

hospital admissions for CVD per 

10 μg/m3

 increase in PM (single 

pollutant model and model adjusted for 

PM2.5 concentration) 

Fig 4: Percentage change in emergency 

hospital admissions rate for CVD and 

RD per a 10 μg/m3

 increase in PM10-2.5

(0-2 day lags, Eastern vs.. Western 

USA) 

Fig 5: County-specific log relative risks 

of emergency hospital admissions for 

CVD per 10 μg/m3

 increase in PM10-2.5

at Lag 0 (unadjusted for PM2.5 and 

plotted vs.. percentage of urbanicity) 

No significant associations between 

PM10-2.5 and cause-specific 

cardiovascular disease. 

Reference: Tolbert et al. (2007, 

090316) 

Period of Study: Aug 1998-Dec 2004

Location: Atlanta Metropolitan area, 

Georgia 

Outcome (ICD-9): Combined CVD 

group, including: Ischemic heart 

disease (410-414), cardiac 

dysrhythmias (427), congestive heart 

failure (428), and peripheral vascular 

and cardiovascular disease (433-437, 

440, 443-445, and 451-453) 

Age Groups: All

Study Design: Time series 

N: NR for 1998-2004. For 1993-2004: 

10,234,490 ER visits (283,360 visits). 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Long-term temporal trends, 

temperature, dew point, days of week, 

federal holidays, hospital entry and exit 

Season: All

Dose-response Investigated: No

Statistical Package: SAS version 9.1 

Lags Considered: 3-day ma (lag 0-2) 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean (μg/m3) (median IQR, range, 

10th-90th percentiles): 

9.0 (8.2 

5.6-11.5 

0.5-50.3 

3.6-15.1) 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10: r = 0.67 

O3: r = 0.36 

NO2: r = 0.48 

CO: r = 0.38SO2: r = 0.16 

PM2.5: r = 0.47 

PM2.5 SO4: r = 0.32 

PM2.5 EC: r = 0.49 

PM2.5 OC: r = 0.49 

PM2.5 TC: r = 0.51 

PM2.5 water-sol metals: r = 0.50 

OHC: r = 0.41 

PM Increment: 5.89 μg/m3 (IQR) 

Risk ratio [95% CI]: CVD: 1.004 

(0.990-1.019) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-106 
Table E-7. Short-term exposure – cardiovascular: ED/HA PM2.5 (including PM components/sources) 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Andersen et al. (2008, 

189651) 

Period of Study: May 2001-Dec 2004

Location: Copenhagen, Denmark 

Outcome (ICD-10): CVD, including 

angina pectoris (I20), myocardial 

infarction (I21-22), other acute ischemic 

heart diseases (I24), chronic ischaemic 

heart disease (I25), pulmonary 

embolism (I26), cardiac arrest (I46), 

cardiac arrhythmias (I48-48), and heart 

failure (I50). RD, including chronic 

bronchitis (J41-42), emphysema (J43), 

other chronic obstructive pulmonary 

disease (J44), asthma (J45), and status 

asthmaticus (J46). Pediatric hospital 

admissions for asthma (J45) and status 

asthmaticus (J46). 

Age Groups: > 65 yr (CVD and RD), 

5-18 yr (asthma)

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAM 

Covariates: Temperature, dew-point 

temperature, long-term trend, 

seasonality, influenza, day of the week, 

public holidays, school holidays (only 

for 5-18 yr olds), pollen (only for 

pediatric asthma outcome) 

Season: NR

Dose-response Investigated: No

Statistical Package: R statistical 

software (gam procedure, mgcv 

package) 

Lags Considered: Lag 0-5 days, 4-day 

pollutant avg (lag 0-3) for CVD, 5-day 

avg (lag 0-4) for RD, and a 6-day avg 

(lag 0-5) for asthma. 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean μgm3 (SD): 10(5)

Median: 9

IQR: 7-12

99th percentile): 28 

Monitoring Stations: 1 

Copollutant (correlation): 

NCtot: r = 0.40 

NC100: r = 0.29 

NCa12: r = 0.07 

Nca23: r = -0.25 

NCa57: r = 0.51 

NCa212: r = 0.82 

PM10: r = 0.80 

CO: r = 0.46 

NO2: r = 0.42 

NOX: r = 0.40 

 curbside: r = 0.28 

O3: r = -0.20 

Other variables: 

Temperature: r = -0.01 

Relative humidity: r = 0.21 

PM Increment: 5 μg/m3 (IQR) 

Relative risk (RR) Estimate [CI]: CVD 

hospital admissions (4-day avg, lag 0 -

3), age 65+: One-pollutant model: 1.03 

[1.01-1.06] 

Adj for NCtot: 1.03 [1.01-1.06] 

RD hospital admissions (5-day avg, lag 

0 -4), age 65+: 

One-pollutant model: 1.00 [0.95-1.00] 

Adj for NCtot: 1.00 [0.95-1.06] 

Asthma hospital admissions (6-day avg 

lag 0-5), age 5 - 18: 

One-pollutant model: 1.15 [1.00-1.32] 

Adj for NCtot: 1.13 [0.98-1.32] 

Estimates for individual day lags 

reported only in Fig form (see notes): 

Notes: Fig 2: Relative risks and 95% 

confidence intervals per IQR in single 

day concentration (0-5 day lag). 

Summary: CVD: Marginally significant 

association at Lag 0. RD: No 

statistically or marginally significant 

associations. Positive associations at 

Lag 4-5.Asthma: Wide confidence 

intervals make interpretation difficult. 

Positive associations at Lag 1, 2, 3. 

December 2009 E-107 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ballester et al. (2006, 

088746) 

Period of Study: 1995-1999

Location: 6 Spanish cities: Barcelona, 

Bilbao, Pamplona, Valencia, Vigo, 

Zaragoza 

Outcome (ICD-9): The number of daily 

emergency admissions with primary 

diagnosis for all cardiovascular disease 

(390-459) and heart diseases (410-414, 

427, 428) 

Age Groups: All ages

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAMs 

Covariates: Daily temperature, 

barometric pressure, and relative 

humidity 

Daily influenza incidence, day of the 

week, holidays, unusual events (ex. 

medical strikes), seasonal variation, 

trend of the series 

Season: NR

Dose-response Investigated: No

Statistical Package: S-Plus GAM 

function 

Lags Considered: 0-3 days, 0- to 

1-day avg 

Pollutant: Black smoke (BS) 

Averaging Time: 24 h 

Mean μg/m3 (10-90th percentile): 

Overall mean NR. 

City specific means 

Barcelona: 35.0 (19.4, 53.0) 

Bilbao: 18.5 (8.8, 31.0) 

Pamplona: 7.4 (2.3, 13.0) 

Valencia: 40.3 (20.3, 66.4) 

Vigo: 79.4 (43.9, 122.3) 

Zaragoza: 40.4 (23.8, 61.3) 

Monitoring Stations: NR 

(at least 3 stations per city) 

Copollutant (correlation): Summary of 

the correlation coefficients between 

each pair of pollutants within cities: 

PM10: r = 0.48 

TSP: from r = 0.16 to r = 0.69 

(median r = 0.43) 

NO2: from r = 0.23 to r = 0.69 

(median r = 0.48) 

SO2: from r = 0.09 to r = 0.59 

(median r = 0.24) 

CO: from r = 0.62 to r = 0.69 

(median r = 0.69) 

O3: from r = -0.43 to r = -0.06 

(median r = -0.16) 

PM Increment: 10 μg/m3 

Relative risk [CI]: Relative risks are 

expressed only in the form of figures 

(see notes). 

Percentage change in risk [CI]: All 

cardiovascular diseases (avg of lags 0 -

1) 0.24% [-0.18, 0.67] 

Heart disease (avg of lags 0 -1) 0.71% 

[0.13, 1.29] 

Notes: Relative risks for the single 

pollutant models are expressed in Fig 2. 

Fig 2: Time sequence of the combined 

association between BS and hospital 

admissions for all CVD (A) and heart 

disease (B). Summary: Significant, 

positive association of TSP with both 

overall CVD and heart disease 

hospitalizations at Lag 0. 

Relative risks for 2 pollutant models are 

expressed in Fig 3: Combined 

estimates of the association between 

hospital admissions for heart diseases 

and air pollutants (avg of lags 0-1 

Adjusted for CO, NO2, O3, or SO2 ). 

Summary: Significant, positive 

association remains after adjusting for 

NO2, O3, and SO2. Association remains 

positive but becomes marginally 

significant after adjusting for CO. 

Reference: Ballester et al. (2006, 

088746) 

Period of Study: 1993-1999

Location: 7 Spanish cities: Barcelona, 

Bilbao, Cartagena, Castellon, Gijon, 

Oviedo, Valencia 

Outcome (ICD-9): The number of daily 

emergency admissions with primary 

diagnosis for all cardiovascular disease 

(390-459) and heart diseases (410-414, 

427, 428) 

Age Groups: All ages

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAMs 

Covariates: Daily temperature, 

barometric pressure, and relative 

humidity 

Daily influenza incidence, day of the 

week, holidays, unusual events (ex. 

medical strikes), seasonal variation, 

trend of the series 

Season: NR

Dose-response Investigated: No

Statistical Package: S-Plus GAM 

function 

Lags Considered: 0-3 days, 0- to 

1-day avg 

Pollutant: TSP 

Averaging Time: 24 h 

Mean μg/m3 (10-90th percentile): 

Overall mean NR. 

City specific means 

Barcelona: 51.8 (29.4, 78.8) 

Bilbao: 58.3 (30.3, 92.3) 

Cartagena: 54.9 (32.5, 79.9) 

Castellon: 60.4 (32.0, 92.1) 

Gijon: 77.4 (47.4, 118.3) 

Oviedo: 76.0 (48.3, 111.8) 

Valencia: 61.0 (44.1, 80.7) 

Monitoring Stations: NR (at least 

three stations per city) 

Copollutant (correlation): Summary of 

the correlation coefficients between 

each pair of pollutants within cities: 

BS: from r = 0.16 to r = 0.69 

(median r = 0.43) 

PM10: NA 

NO2: from r = -0.13 to r = 0.65 

(median r = 0.48) 

SO2: from r = 0.06 to r = 0.69 

(median r = 0.31) 

CO: from r = 0.06 to r = 0.59 

(median r = 0.47) 

O3: from r = -0.27 to r = 0.07 

(median r = -0.03) 

PM Increment: 10 μg/m3 

Relative risk [CI]: Relative risks are 

expressed only in the form of figures 

(see notes). 

Percentage change in risk [CI]: All 

cardiovascular diseases: 0.07% [-0.23, 

0.36] 

Heart disease 0.45% [0.04, 0.86] 

Notes: Relative risks for the single 

pollutant models are expressed in Fig 2.

Fig 2: Time sequence of the combined 

association between TSP and hospital 

admissions for all CVD (A) and heart 

disease (B). 

Summary of results: Positive, marginally 

significant association of TSP with 

overall CVD at Lag 0. Positive, 

statistically significant relation between 

TSP and heart disease hospitalizations 

at Lag 0. 

Relative risks for 2 pollutant models are 

expressed in Fig 3: 

Fig 3: Combined estimates of the 

association between hospital 

admissions for heart diseases and air 

pollutants (avg of lags 0-1 adjusted for 

CO, NO2, O3, or SO2 ). 

Summary of results: Small positive 

significant or marginally significant 

associations between TSP and general 

CVD and heart disease hospitalizations 

remain constant after adjustment for 

CO, NO2, O3, or SO2. 

December 2009 E-108 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bell et al. (2008, 091268) 

Period of Study: 1995-2002

Location: Taipei, Taiwan 

Outcome (ICD-9): Hospital admissions 

for ischemic heart disease (410, 411, 

414), cerebrovascular disease 

(430-437), asthma (493), and 

pneumonia (486). 

Age Groups: All

Study Design: Time series 

N: 6,909 hospital admissions for 

ischaemic heart diseases, 11,466 for 

cerebrovascular disease, 19,966 for 

pneumonia, and 10,231 for asthma 

Statistical Analyses: Poisson 

regression 

Covariates: Day of the week, time, 

apparent temperature, long-term trends, 

seasonality 

Season: All

Dose-response Investigated: No

Statistical Package: NR 

Lags Considered: lags 0-3 days, mean 

of lags 0-3 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean μg/m3 (range IQR): 31.6 (0.50-355.0 20.2) 

Monitoring Stations: 2 

Copollutant (correlation): NR 

PM Increment: 20 μg/m3 (near IQR) 

Percentage increase estimate [95% CI]: 

Ischemic heart disease: L0: 3.48 (-0.39, 

7.51) 

L1: 3.55 (-0.30, 7.56) 

L2: 3.32 (-0.50, 7.29) 

L3: 2.80 (-1.04, 6.79) 

L03: 8.38 (2.28, 14.84) 

Cerebrovascular disease: L0: -2.22 (-

50.2, 0.67) 

L1: -1.30 (-4.08, 1.55) 

L2: 0.24 (-2.49, 3.040 

L3: 1.21 (-1.41, 3.90) 

L03: -1.45 (-5.58, 2.87) 

Asthma: L0: 0.46 (-2.41, 3.42) 

L1: -1.36 (-4.33, 1.71) 

L2: -0.83 (-3.67, 2.10) 

L3: -0.78 (-3.63, 2.16) 

L03: -1.75 (-6.21, 2.92) 

Pneumonia: L0: 0.06 (-2.74, 2.94) 

L1: 0.34 (-2.446, 3.20) 

L2: -0.59 (-3.38, 2.29) 

L3: -0.44 (-3.22, 2.41) 

L03: -0.61 (-4.87, 3.85) 

Reference: Bell et al. (2008, 091268) 

Period of Study: 1999-2005

Location: 202 U.S. counties 

Outcome (ICD-9): Heart failure (428), 

heart rhythm disturbances (426-427), 

cerebrovascular events (430-438), 

ischemic heart disease (410-414, 429), 

peripheral vascular disease (440-449), 

COPD (490-492), respiratory tract 

infections (464 - 466, 480 - 487) 

Age Groups: 65+

Study Design: Time series 

N: NR 

Statistical Analyses: Two-stage 

Bayesian hierarchical model to find 

national avg 

First stage: Poisson regression (countyspecific) 

Covariates: Day of the week, 

temperature, dew point temperature, 

temporal trends, indicator for persons 

75+ yr, population size 

Season: All, Jun-Aug (Summer), 

Sep-Nov (Fall), Dec-Feb (Winter), 

Mar-May (Spring)

Dose-response Investigated: No

Statistical Package: NR 

Lags Considered: 0- to 2-day lags 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (μg/m3): Descriptive information 

presented in Fig S2 (boxplots): 

IQR: 8.7 μg/m3

Monitoring Stations: NR 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3 

Percent increase [95% PI]: 

Cardiovascular admissions: 

Lag 0 (all seasons): 0.80 [0.59-1.01] 

Lag 0 (winter, national): 1.49 [1.09-1.89]

Lag 0 (winter, northeast): 2.01 

[1.39-2.63] 

Lag 0 (winter, southeast): 1.06 

[-0.07-2.21] 

Lag 0 (winter, northwest): 0.85 

[-4.11-6.07] 

Lag 0 (winter, southwest): 0.76 

[-0.25-1.79] 

Lag 0 (spring, national): 0.91 

[0.47-1.35] 

Lag 0 (spring, northeast) 

0.95 [0.32-1.58] 

Lag 0 (spring, southeast): 0.75 

[-0.26-1.78] 

Lag 0 (spring, northwest): -0.07 

[-12.40-13.98] 

Lag 0 (spring, southwest): 1.78 

[-0.87-4.51] 

Lag 0 (summer, national): 0.18 

[-0.23-0.58] 

Lag 0 (summer, northeast): 0.55 

[0.08-1.02] 

Lag 0 (summer, southeast): -0.67 

[-1.60-0.26] 

Lag 0 (summer, northwest): -1.55 

[-15.22-14.31] 

Lag 0 (summer, southwest): -1.20 

[-4.90-2.65] 

Lag 0 (fall, national): 0.68 [0.29-1.07] 

Lag 0 (fall, northeast): 1.03 [0.48-1.58] 

Lag 0 (fall, southeast): 0.17 [-0.72-1.07] 

Lag 0 (fall, northwest): -0.67 

[-6.96-6.05] 

Lag 0 (fall, southwest): 0.30 [-0.98-1.59]

Lag 1 (all seasons): 0.07 [-0.12-0.26] 

Lag 1 (winter): 0.56 [0.16-0.96] 

Lag 1 (spring): -0.10 [-0.58-0.39] 

Lag 1 (summer): -0.16 [-0.54-0.22] 

Lag 1 (fall): 0.04 [-0.28-0.35] 

Lag2 (all seasons): [0.06 [-0.12-0.23] 

Lag 2 (winter): 0.27 [-0.12-0.65] 

Lag 2 (spring): 0.19 [-0.23-0.60] 

December 2009 E-109 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Lag 2 (summer): -0.12 [-0.50-0.26] 

Lag 2 (fall): 0.02 [-0.30-0.34] 

Respiratory admissions: Lag 0 (all 

seasons): 0.22 [-0.12-0.56] 

Lag 0 (winter, national): 1.05 [0.29-1.82]

Lag 0 (winter, northeast): 1.76 

[0.60-2.93] 

Lag 0 (winter, southeast): 0.59 

[-1.35-2.58] 

Lag 0 (winter, northwest): -0.07 

[-6.74-7.08] 

Lag 0 (winter, southwest): 0.03 

[-1.25-1.34] 

Lag 0 (spring, national): 0.31 

[-0.47-1.11] 

Lag 0 (spring, northeast): 0.34 

[-0.66-1.34] 

Lag 0 (spring, southeast): -0.06 

[-1.77-1.68] 

Lag 0 (spring, northwest): -8.52 

[-25.62-12.51] 

Lag 0 (spring, southwest): 1.87 

[-2.00-5.90] 

Lag 0 (summer, national): -0.62 

[-1.33-0.09] 

Lag 0 (summer, northeast): -0.8 

[-1.65-0.07] 

Lag 0 (summer, southeast): -0.15 

[-1.88-1.61] 

Lag 0 (summer, northwest): 0.25 

[-21.46-27.96] 

Lag 0 (summer, southwest): 0.64 

[-5.38-7.04] 

Lag 0 (fall, national): 0.02 [-0.63-0.67] 

Lag 0 (fall, northeast): -0.01 [-0.87-0.85]

Lag 0 (fall, southeast): -0.58 

[-2.06-0.91] 

Lag 0 (fall, northwest): -1.38 

[-11.84-10.32] 

Lag 0 (fall, southwest): 1.77 [-0.73-4.33]

Lag 1 (all seasons): 0.05 [-0.29-0.39] 

Lag 1 (winter): 0.50 [-0.27-1.27] 

Lag 1 (spring): -0.24 [-1.01-0.53] 

Lag 1 (summer): 0.28 [-0.39-0.95] 

Lag 1 (fall): 0.15 [-0.49-0.79 

Lag 2 (all seasons): 0.41 [0.09-0.74] 

Lag 2 (winter, national): 0.72 [0.01-1.43]

Lag 2 (winter, northeast): 0.79 

[-0.21-1.80] 

Lag 2 (winter, southeast): 0.4 [-1.45, 

2.27] 

Lag 2 (winter, northwest): -0.06 

[-6.52-6.85] 

Lag 2 (winter, southwest): 1.2 

[-0.10-2.52] 

Lag 2 (spring, national): 0.35 

[-0.29-0.99] 

Lag 2 (spring, northeast): 0.04 

[-0.88-0.97] 

Lag 2 (spring, southeast): 0.75 

[-0.82-2.34] 

Lag 2 (spring, northwest): 2.29 

[-14.26-22.03] 

Lag 2 (spring, southwest): 1.05 

[-2.18-4.39] 

Lag 2 (summer, national): 0.57 

[-0.07-1.23] 

Lag 2 (summer, northeast): 0.77 

[-0.01-1.56] 

|Lag 2 (summer, southeast): -0.52 

[-2.07-1.06] 

Lag 2 (summer, northwest): 0.74 

[-18.73-24.86] 

Lag 2 (summer, southwest): 2.41 

[-2.61-7.69] 

Lag 2 (fall, national): 0.39 [-0.22-1.01] 

Lag 2 (fall, northeast): 0.12 [-0.82-1.07] 

Lag 2 (fall, southeast): 0.14 [-1.29-1.59] 

December 2009 E-110 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Lag 2 (fall, northwest): -0.74 

[-10.08-9.58] 

Lag 2 (fall, southwest): 0.97[-1.36-3.36]

Reference: Bell et al. (2009, 191007) 

Period of Study: 1999-2005 

Location: 168 U.S. Counties 

Outcome: CVD hospital admissions 

Study Design: Retrospective Cohort 

Covariates: Socio-economic 

conditions, long term temperature 

Statistical Analysis: Bayesian 

hierarchical model 

Age Groups: ≥ 65 yr 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD) Unit: NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 20% of the population 

acquiring air conditioning 

Percent Change (95% CI) in 

community-specific PM health effect 

estimates for CVD hospital 

admissions 

Any AC, including window units 

Yearly health effect: -4.3 (-72.7 to 4.2) 

Summer health effect: -148 (-327 to 

31.1) 

Winter health effect: -80.0 (-182 to 22.0)

Central AC 

Yearly health effect: -42.5(-63.4-21.6) 

Summer health effect: -79.5 (-143 to 

15.7) 

Winter health effect: -41.9 (-124 to 40.0)

Reference: Bell et al. (2009, 191997) 

Period of Study: 1999-2005 

Location: U.S. 

Outcome: Cardiovascular HA 

Age Groups: 65+

Study Design: time series 

N: NR 

Statistical Analyses: Bayesian 

Hierarchical Regression 

Covariates: time trend, day of week, 

seasonality, dew point, temperature 

Statistical Package: NR 

Lags Considered: 0-2 

Pollutant: PM2.5 

Averaging Time: Daily 

Mean: 

EC: 0.715 

Ni: 0.002 

V: 0.003 

Min: 

EC: 0.309 

Ni: 0.003 

V: 0.001 

Max: 

EC: 1.73 

Ni: 0.021 

V: 0.010 

Interquartile Range: 

EC: 0.245 

Ni: 0.001 

V: 0.001 

Interquartile Range of Percents: 

EC: 1.7 

Ni: 0.01 

V: 0.01 

Monitoring Stations: NR 

Copollutant: Al, NH4+, As, Ca, Cl, Cu, 

EC, OMC, Fe, Pb, Mg. Ni, NO3-, K, Si, 

Na+, SO4=, Ti, V, Zn 

Co-pollutant Correlation:

Ni, V: 0.48 

V, EC: 0.33 

Ni, EC: 0.30 

Note: Pollutant concentrations available 

for all fractions of PM2.5

PM Increment: Interquartile Range in 

the fraction of PM2.5

Percent Increase in PM Health Effect 

(Lower CI, Upper CI), lag

EC: 25.8 (4.4, 47.2), lag 0 

EC + Ni: 14.0 (-7.6, 35.5), lag 0 

EC + V: 14.9 (-7.8, 37.6), lag 0 

EC+ V, HS education: 15.0 (3.3, 26.8), 

lag 0 

EC+ V, median income: 15.8 (4.1, 27.5), 

lag 0 

EC+ V, racial composition: 14.2 (2.8, 

25.6), lag 0 

EC+ V, percent living in urban area: 

14.7 (3.1, 26.3), lag 0 

EC+ V, population: 13.6 (2.2, 25.0), lag 

0 

EC + Ni, V: 11.9 (-10.4, 43.2), lag 0 

Ni: 19.0 (9.9, 28.2), lag 0 

Ni + EC: 17.3 (7.7, 26.9), lag 0 

Ni + V: 15.5 (4.1, 26.9), lag 0 

Ni + EC, V: 14.9 (3.4, 26.4), lag 0 

V: 27.5 (10.6, 44.4), lag 0 

V + EC: 23.1 (4.9, 41.4), lag 0 

V+ Ni: 10.9 (-9.6, 31.5), lag 0 

V + EC, Ni: 8.1 (-13.3, 29.5), lag 0 

EC: 11.8 (-69.2, 92.8), lag 1 

EC: 21.0 (-46.6, 88.6), lag 2 

Ni: 20.6 (-15.5, 56.7), lag 1 

Ni: -2.3 (-32.5, 27.9), lag 2 

V: 34.0 (-31.2, 99.1), lag 1 

V: 8.0 (-46.8, 62.7), lag 2 

Percent HS education: -17.4 (-46.8, 

11.9), lag 0 

Median income: 21.3 (-20.0, 62.5), lag 0

Percent black: 26.9 (-15.8, 69.6), lag 0 

Percent living in urban area: 34.4 (-

29.0, 97.8), lag0 

Population: -4.3 (-13.3, 4.8), lag 0 

Notes: Interquartile ranges in percent 

HS education, median income, percent 

black, percent living in urban area, and 

population are 5.2 %, $9,223, 17.3%, 

11.0%, and 549,283 respectively. 

December 2009 E-111 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chan et al. (2007, 147787) 

Period of Study: Apr 1997-Dec 2002 

Location: Boston, MA 

Outcome: Cerebrovascular Emergency 

Admissions 

Age Groups: 50+ yr 

Study Design: Time series 

Statistical Analyses: GAM Poisosn 

Regression 

Covariates: Yr, mo, day of wk, 

temperature, dew point 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-3 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 31.5 (16.0) 

Min: 15.6 

Max: 200.6 

IQR: 19.7 

Monitoring Stations: 16 

Copollutant: O3, CO, SO2, NO2, PM10

Co-pollutant Correlation

O3: 0.33 

CO: 0.44 

SO2: 0.51 

NO2: 0.50 

PM10: 0.61 

PM Increment: Interquartile Range 

(19.7 μg/m3

) 

Percent Change (Lower CI, Upper CI), 

p-value: 

Cerebrovascular Disease 

Lag 0: 1.006 (0.993, 1.019) 

Lag 1: 1.002 (0.990, 1.014) 

Lag 2: 1.015 (0.978, 1.052) 

Lag 3: 1.021 (1.005, 1.037) 

Lag 3 + O3: 1.009 (0.987, 1.031) 

Lag 3 + CO: 1.014 (0.993, 1.035) 

Lag 3 + O3 + CO: 1.009 (0.987, 1.031) 

Stroke 

Lag 0: 0.931 (0.831, 1.031) 

Lag 1: 0.936 (0.845, 1.027) 

Lag 2: 0.931 (0.820, 1.042) 

Lag 3: 0.991 (0.969, 1.013) 

Ischaemic stroke 

Lag 0: 0.981 (0.907, 1.055) 

Lag 1: 0.994 (0.920, 1.078) 

Lag 2: 0.960 (0.885, 1.035) 

Lag 3: 1.059 (0.984, 1.134) 

Haemorrhagic stroke 

Lag 0: 0.870 (0.740, 1.010) 

Lag 1: 0.882 (0.761, 1.003) 

Lag 2: 0.909 (0.810, 1.008) 

Lag 3: 0.921 (0.830, 1.012) 

Reference: Chan et al. (2008, 093297) 

Period of Study: 1995-2002

Location: Taipei Metropolitan area, 

Taiwan 

Outcome (ICD-9): Emergency visits for 

ischaemic heart diseases (410-411, 

414), cerebrovascular diseases (430-

437), and COPD (493, 496) 

Age Groups: All

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson 

regression 

Covariates: Yr, mo, day of wk, 

temperature, dewpoint temperature, 

PM10, NO2 

Season: All

Dose-response Investigated: No

Statistical Package: SAS version 8.0 

Lags Considered: 0- to 7-day lags 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean μg/m3 (SD): NR 

Monitoring Stations: 1 

Copollutant (correlation): NR 

PM Increment: 19.7 μg/m3 (IQR) 

OR [95% CI]: In environmental 

conditions without dust storms (results 

only given for best-fitting model) 

Lag 6 days: 1.024 (1.004, 1.044)

Reference: Delfino et al, (2008, 

156390) 

Period of Study: October 

2001-2003-November 2003 

Location: Southern California 

Outcome: Cardiovascular hospital 

admissions 

Study Design: Time series 

Statistical Analysis: Poisson 

regression with GEE 

Age Groups: All 

Pollutant: PM2.5

Averaging Time: Hourly 

Mean (SD) Unit by county: 

Los Angeles 

Before Fires: 27.2 (12.4) μg/m3

During Fires: 54.1 (21.0) μg/m3

After Fires: 15.9 (5.5) μg/m3

Orange

Before Fires: 23.2 (9.6) μg/m3

During Fires: 64.3 (26.5) μg/m3

After Fires: 15.5 (10.2) μg/m3

Riverside

Before Fires: 32.7 (14.7) μg/m3

During Fires: 42.1 (25.5) μg/m3

After Fires: 16.9 (10.2) μg/m3

San Bernadino

Before Fires: 35.7 (16.6) μg/m3

During Fires: 45.3 (28.7) μg/m3

After Fires: 18.5 (8.3) μg/m3

San Diego

Before Fires: 18.5 (6.7) μg/m3

Increment: 10 μg/m3

Relative Rate (Min CI, Max CI)

All Cardiovascular

All Periods: 0.996 (0.989-1.003)

Pre-Wildfire: 0.992 (0.976-1.009)

Wildfire: 1.008 (0.999-1.018), p = 0.104

Post-Wildfire: 0.991 (0.964-1.019), 

p = 0.955 

Ischaemic Heart Disease

All Periods: 0.991 (0.980-1.003)

Pre-Wildfire: 0.990 (0.963-1.017)

Wildfire: 0.117 (0.990-1.024), p = 0.313

Post-Wildfire: 0.989 (0.950-1.030), 

p = 0.976 

Congestive Heart Failure

All Periods: 0.989 (0.974-1.004)

Pre-Wildfire: 0.978 (0.942-1.015)

Wildfire: 1.016 (0.933-1.039), p = 0.096

Post-Wildfire: 0.969 (0.914-1.027), 

p = 0.791 

December 2009 E-112 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

During Fires: 76.1 (66.6) μg/m3

After Fires: 14.2 (7.2) μg/m3

Ventura 

Before Fires: 18.4 (8.3) μg/m3

During Fires: 50.1 (50.5) μg/m3

After Fires: 12.9 (4.3) μg/m3

Copollutant (correlation): NR 

Cardiac Dysrhythmia

All Periods: 0.980 (0.962-0.998)

Pre-Wildfire: 0.979 (0.935-1.025)

Wildfire: 0.989 (0.961-1.017), p = 0.721

Post-Wildfire: 0.976 (0.912-1.044), 

p = 0.934 

Cerebrovascular Disease and Stroke

All Periods: 1.019 (1.004-1.035)

Pre-Wildfire: 1.015 (0.980-1.052)

Wildfire: 1.016 (0.997-1.036), p = 0.971

Post-Wildfire: 1.044 (0.987-1.104), 

p = 0.379 

Relative Rate (Min CI, Max CI) in 

relation to pre-wildfire period (1)

All Cardiovascular: Wildfire, unadjusted 

for PM2.5: 0.958 (0.920-0.997)

Wildfire, adjusted for PM2.5: 0.947 

(0.902-0.994)

Post-wildfire, unadjusted for PM2.5: 

1.061 (1.006-1.119) 

Post-wildfire, adjusted for PM2.5: 1.053 

(0.994-1.114) 

Ischaemic Heart Disease: Wildfire, 

unadjusted for PM2.5: 0.913 (0.852-

0.978)

Wildfire, adjusted for PM2.5: 0.905 

(0.832-0.985)

Post-wildfire, unadjusted for PM2.5: 

1.029 (0.943-1.123) 

Post-wildfire, adjusted for PM2.5: 1.029 

(0.936-1.131) 

Congestive Heart Failure: Wildfire, 

unadjusted for PM2.5: 0.981 (0.817-

0.972)

Wildfire, adjusted for PM2.5: 0.911 

(0.819-1.014)

Post-wildfire, unadjusted for PM2.5: 

1.113 (0.997-1.242) 

Post-wildfire, adjusted for PM2.5: 1.105 

(0.982-1.244) 

Cardiac Dysrhythmia: Wildfire, 

unadjusted for PM2.5: 0.968 (0.874-

1.072)

Wildfire, adjusted for PM2.5: 0.964 

(0.851-1.093)

Post-wildfire, unadjusted for PM2.5: 

1.089 (0.949-1.251) 

Post-wildfire, adjusted for PM2.5: 1.057 

(0.914-1.223) 

Cerebrovascular Disease and Stroke: 

Wildfire, unadjusted for PM2.5: 1.066 

(0.981-1.159)

Wildfire, adjusted for PM2.5: 1.017 

(0.922-1.123)

Post-wildfire, unadjusted for PM2.5: 

1.013 (0.907-1.132) 

Post-wildfire, adjusted for PM2.5: 1.013 

(0.902-1.138) 

Reference: Dominici et al. (2006, 

088398) 

Period of Study: 1999-2002

Location: 204 U.S. counties, located 

in: Alabama, Alaska, Arizona, Arkansas, 

California, Colorado, Connecticut, 

Delaware, District of Columbia, Florida, 

Georgia, Hawaii, Idaho, Illinois, Indiana, 

Iowa, Kansas, Kentucky, Louisiana, 

Maine, Maryland, Massachusetts, 

Michigan, Minnesota, Mississippi, 

Missouri, Nevada, New Hampshire, 

New Jersey, New Mexico, New York, 

North Carolina, Ohio, Oklahoma, 

Oregon, Pennsylvania, Rhode Island, 

South Carolina, Tennessee, Texas, 

Outcome (ICD-9): Daily counts of 

hospital admissions for primary 

diagnosis of heart failure (428), heart 

rhythm disturbances (426-427), 

cerebrovascular events (430-438), 

ischemic heart disease (410-414, 429), 

peripheral vascular disease (440-448), 

chronic obstructive pulmonary disease 

(490-492), and respiratory tract 

infections (464-466, 480-487). 

Age Groups: >65 yr 

Study Design: Time series 

N: 11.5 million Medicare enrollees 

Statistical Analyses: Bayesian 2-stage 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (μg/m3

 ) (IQR): 13.4 (11.3-15.2) 

Monitoring Stations: NR 

Copollutant (correlation): NR 

Other variables: Median of pairwise 

correlations among PM2.5 monitors 

within the same county for 2000: r = 

0.91 (IQR: 0.81-0.95) 

PM Increment: 10 μg/m3 (Results in 

figures; see notes) 

Percent increase in risk [95% PI]: 

Cerebrovascular disease (Lag 0): 

Age 65+: 0.81 [0.30, 1.32] 

Age 65-74: 0.91 [0.01, 1.82] 

Age 75+: 0.80 [0.21, 1.38] 

Peripheral vascular disease (Lag 0): 

Age 65+: 0.86 [-0.06, 1.79] 

Age 65-74: 1.21 [-0.26, 2.67] 

Age 75+: 0.86 [-0.39, 2.11] 

Ischemic heart disease (Lag 2): 

Age 65+: 0.44 [0.02, 0.86] 

Age 65-74: 0.37 [-0.22, 0.96] 

Age 75+: 0.52 [-0.01, 1.04] 

December 2009 E-113 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Utah, Virginia, Washington, West 

Virginia, Wisconsin 

hierarchical models. 

First stage: Poisson regression (countyspecific) 

Second stage: Bayesian hierarchical 

models, to produce a national avg 

estimate 

Covariates: Day of the week, 

seasonality, temperature, dew point 

temperature, long-term trends 

Season: NR 

Dose-response Investigated: No

Statistical Package: R statistical 

software version 2.2.0 

Lags Considered: 0-2 days, avg of 

days 0-2 

Heart rhythm disturbances (Lag 0): 

Age 65+: 0.57 [-0.01, 1.15] 

Age 65-74: 0.46 [-0.63, 1.54] 

Age 75+: 0.72 [0.02, 1.42] 

Heart failure (Lag 0): 

Age 65+: 1.28 [0.78, 1.78] 

Age 65-74: 1.21 [0.35, 2.07] 

Age 75+: 1.36 [0.78, 1.94] 

COPD (Lag 0): 

Age 65 +: 0.91 [0.91, 1.64] 

Age 65-74: 0.42 [-0.64, 1.48] 

Age 75+: 1.47 [0.54, 2.40] 

Respiratory tract infection: 

Age 65+: 0.92 [0.41, 1.43] 

Age 65-74: 0.93 [0.04, 1.82] 

Age 75+: 0.92 [0.32, 1.53] 

Annual reduction in admissions 

attributable to a 10 μg/m3

 reduction in 

daily PM2.5 level (95% PI): 

Cerebrovascular disease: Annual 

number of admissions: 226,641 

Annual reduction in admissions: 1836 

[680, 2992] 

Peripheral vascular disease: Annual 

number of admissions: 70,061 

Annual reduction in admissions: 602 [-

42, 1254] 

Ischemic heart disease: Annual number 

of admissions: 346,082 

Annual reduction in admissions: 1523 

[69, 2976] 

Heart rhythm disturbances: Annual 

number of admissions: 169,627 

Annual reduction in admissions: 967 [-

17, 1951] 

Heart failure: Annual number of 

admissions: 246,598 

Annual reduction in admissions: 3156 

[1923, 4389] 

COPD: Annual number of admissions: 

108,812 

Annual reduction in admissions: 990 

[196, 1785] 

Respiratory tract infections: Annual 

number of admissions: 226,620 

Annual reduction in admissions: 2085 

[929, 3241] 

Notes: Fig 2: Point estimates and 95% 

posterior intervals of the % change in 

admissions rates per 10 μg/m3

 (national 

avg relative rates) for single lag (0, 1, 

and 2 days) and distributed lag models 

for 0 to 2 days (total) for all outcomes. 

Summary: Positive significant or 

marginally significant associations 

between PM2.5 and cerebrovascular 

disease at Lag 0 

Peripheral vascular disease at Lags 0 

and 2 

Ischemic heart disease at Lag 2 

Heart rhythm disturbances at Lag 0 

December 2009 E-114 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Heart failure at Lag 0, Lag 2, and Lags 

0 -2 

COPD at Lag 0, Lag 1, and Lags 0-2 

and respiratory tract infections at Lag 2 

and Lags 0-2. 

Fig 3: Point estimates and 95% 

posterior intervals of the % change in 

admission rates per 10 μg/m3

 (regional 

relative rates). Summary: For 

cardiovascular diseases, all estimates 

in the Midwestern, Northeastern, and 

Southern regions were positive, while 

estimates in the other regions (South, 

West, Central, Northwest) were close to 

0. For respiratory disease, there were 

larger effects in the Central, 

Southeastern, Southern, and Western 

regions than in the other regions. 

Fig 4: Point estimates and 95% 

posterior intervals of the % change in 

admission per 10 μg/m3

 (Eastern vs.. 

Western regions): Summary: All 

estimates for cardiovascular outcomes 

were positive in the U.S. Eastern region 

but not in the U.S. Western region. The 

estimates for respiratory tract infections 

were larger in the Western region than 

in the Eastern region. The estimates for 

CCPD were positive in the both regions. 

Reference: Halonen et al. (2009, 

180379) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome: Cardiovascular 

Hospitalizations & Mortality (ICD 10: 

I00-99) 

Age Groups: 65+ yr

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson, GAM 

Covariates: Temperature, humidity, 

influenza epidemics, high pollen 

episodes, holidays 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: lags 0-3 days; 5-day 

(0-4) mean 

Pollutant: PM2.5 

Averaging Time: Daily 

Mean (SD): NR

Min: 1.1 

25th percentile: 5.5 

50th percentile: 9.5 

75th percentile: 11.7 

Max: 69.5 

Monitoring Stations: NR 

Copollutant: 

PM<0.03, PM0.03-0.1, PM<0.1, 

PM<0.10.29, PM10-2.5, CO, NO2

Co-pollutant Correlation 

PM<0.03: 0.14 

PM0.03-0.1: 0.48 

PM<0.1: 0.35 

PM<0.10.29: 0.88 

PM10-2.5: 0.25 

PM Increment: Interquartile Range 

Percent Change (Lower CI, Upper 

CI): 

All Cardiovascular Morality 

Lag 0: 0.73 (-0.66, 2.13) 

Lag 1: 0.74 (-0.63, 2.13) 

Lag 2: 0.74 (-0.62, 2.11) 

Lag 3: 0.06 (-1.29, 1.43) 

5-day mean: 0.87 (-0.94, 2.70) 

Coronary Heart Disease HA 

Lag 0: -0.17 (-1.5.0, 1.18) 

Lag 1: -0.03 (-1.31, 1.26) 

Lag 2: -0.63 (-1.87, 0.62) 

Lag 3: 0.48 (-0.78, 1.76) 

5-day mean: 0.80 (-0.94, 2.58) 

Stroke HA 

Lag 0: -0.99 (-2.78, 0.84) 

Lag 1: 0.02 (-1.74, 1.82) 

Lag 2: -1.38 (-3.13, 0.40) 

Lag 3: -0.17 (-1.92, 1.61) 

5-day mean: -0.78 (-3.10, 1.60) 

Arrhythmia HA 

Lag 0: 0.82 (-1.03, 2.68) 

Lag 1: 0.18 (-1.58, 1.97) 

Lag 2: -0.09 (-1.82, 1.67) 

Lag 3: -0.48 (-2.22, 1.29) 

5-day mean: 0.16 (-2.16, 2.54) 

*p < 0.05, ‡p < 0.10 

December 2009 E-115 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Host et al. (2008, 155852) 

Period of Study: 2000-2003

Location: Six French cities: Le Havre, 

Lille, Marseille, Paris, Rouen, and 

Toulouse 

Outcome (ICD-10): Daily 

hospitalizations for all cardiovascular 

(I00-I99), cardiac (I00-I52), and 

ischemic heart diseases (I20-I25), all 

respiratory diseases (J00-J99), 

respiratory infections (J10-J22). 

Age Groups: For cardiovascular 

diseases: All ages, and restricted to ≥

65 yr. For all respiratory diseases: 0-14 

yr, 15-64 yr, and ≥ 65 yr. For respiratory 

infections: All ages

Study Design: Time series 

N: NR (Total population of cities: 

approximately 10 million) 

Statistical Analyses: Poisson 

regression 

Covariates: Seasons, days of the wk, 

holidays, influenza epidemics, pollen 

counts, temperature, and temporal 

trends 

Season: NR

Dose-response Investigated: No

Statistical Package: MGCV package in 

R software (R 2.1.1) 

Lags Considered: Avg of 0-1 days 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (5th -95th percentile):

Le Havre: 13.8 (6.0-30.5) 

Lille: 15.9 (6.9-26.3) 

Marseille: 18.8 (8.0-33.0) 

Paris: 14.7 (6.5-28.8) 

Rouen: 14.4 (7.5-28.0) 

Toulouse: 13.8 (6.0-25.0) 

Monitoring Stations: 

13 total: 1 in Toulouse 

4 in Paris 

2 each in other cities 

Copollutant (correlation): 

PM10-2.5: Overall: r > 0.6 

Ranged between r = 0.28 and 

r = 0.73 across the six cities. 

PM Increment: 10 μg/m3 increase, and 

a 27 μg/m3

 increase (corresponding to 

the difference between the lowest of the 

5th percentiles and the highest of the 

95th percentiles of the cities’ 

distributions) 

ERR (excess relative risk) Estimate [CI]: 

For all cardiovascular diseases (10 

μg/m3

 increase): All ages: 0.9% [0.1, 

1.8] 

≥ 65 yr: 1.9% [0.9, 3.0] 

For all cardiovascular diseases (27 

μg/m3

 increase): All ages: 2.5% [0.2, 

4.9] 

≥ 65 yr: 5.3% [2.6, 8.2] 

For ischemic heart diseases (27 μg/m3

increase): All ages: 5.2% [-0.6, 11.3] 

≥ 65 yr: 12.7% [6.3, 19.5] 

For cardiac diseases (10 μg/m3

increase): All ages: 0.9% [-0.1, 2.0] 

≥ 65 yr: 2.4% [1.2, 3.7] 

For cardiac diseases (27 μg/m3

increase): All ages: 2.5% [-0.3, 5.4] 

≥ 65 yr: 6.8% [3.3, 10.3] 

For ischemic heart diseases (10 μg/m3

increase): All ages: 1.9 % [-0.2, 4.0] 

≥ 65 yr: 4.5% [2.3, 6.8] 

For all respiratory diseases (10 μg/m3

increase): 0-14 yr: 0.4% [-1.2, 2.0] 

15-64 yr: 0.8% [-0.7, 2.3]; 

≥ 65 yr: 0.5% [-2.0, 3.0] 

For all respiratory diseases (27 μg/m3

increase): 0-14 yr: 1.1% [-3.1, 5.5] 

15-64 yr: 2.2% [-1.8, 6.4]; 

≥ 65 yr: 1.3% [-5.3, 8.2] 

For respiratory infections (10 μg/m3

increase): All ages: 2.5% [0.1, 4.8] 

For respiratory infections (27 μg/m3

increase): All ages: 7.0% [0.7, 13.6] 

December 2009 E-116 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Jalaludin et al. (2006, 

189416) 

Period of Study: Jan 1997-Dec 2001

Location: Sydney, Australia 

Outcome (ICD-9): Cardiovascular 

disease (390-459), cardiac disease 

(390-429), ischemic heart disease (410-

413) and cerebrovascular disease or 

stroke (430-438) 

Age Groups: 65+ yr

Study Design: Time series 

N: NR 

Statistical Analyses: GAM, GLM 

Covariates: Temperature, humidity 

Season: Warm (Nov-Apr) and cool 

(May-Oct)

Dose-response Investigated: No

Statistical Package: S-Plus 

Lags Considered: 0-3 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (min-max): 9.5 (2.4-82.1) 

SD = 5.1 

Monitoring Stations: 14 

Copollutant (correlation): 

Warm 

BSP: r = 0.93 

PM10: r = 0.89 

O3: r = 0.57 

NO2: r = 0.45 

CO: r = 0.35 

SO2: r = 0.27 

Cool 

BSP: r = 0.90 

PM10: r = 0.88 

O3: r = 0.05 

NO2: r = 0.68 

CO: r = 0.60 

SO2: r = 0.46 

Other variables: 

Warm 

Temp: r = 0.24 

Rel humidity: r = -0.15 

Cool 

Temp: r = -0.04 

Rel humidity: r = 0.20 

PM Increment: 4.8 μg/m3 (IQR) 

Percent Change Estimate [CI]: All CVD 

Same-day lag: 1.26 [0.56,1.96] 

Avg 0-1 day lag: 0.85 [0.18,1.52] 

Cool (same-day lag): 2.23 [0.98,3.50] 

Warm (same-day lag): 0.73 [-0.05,1.52] 

Cardiac disease 

Same-day lag: 1.55 [0.74,2.38] 

Avg 0-1 day lag: 1.33 [0.54,2.13] 

Cool (same-day lag): 2.37 [0.87,3.89] 

Warm (same-day lag): 1.13 [0.22,2.04] 

Ischemic heart disease 

Same-day lag: 1.17 [-0.08,2.44] 

Avg 0-1 day lag: 1.24 [0.04,2.45] 

Cool (same-day lag): 0.57 [-1.74,2.94] 

Warm (same-day lag): 1.31 [-0.04,2.68] 

Stroke 

Same-day lag: -0.89 [-2.41,0.65] 

Avg 0-1 day lag: -1.08 [-2.54,0.41] 

Cool (same-day lag): 1.45 [-1.17,4.15] 

Warm (same-day lag): -2.19 

[-4.00,-0.36] 

Notes: All other lag-day ORs were 

provided, yet none were significant. 

Percent change in ED attendance was 

also reported graphically (Fig 1-5).

Reference: Jalaludin et al. (2006, 

189416) 

Period of Study: Jan 1997-Dec 2001

Location: Sydney, Australia 

Outcome (ICD-9): Cardiovascular 

disease (390-459), cardiac disease 

(390-429), ischemic heart disease (410-

413) and cerebrovascular disease or 

stroke (430-438) 

Age Groups: 65+ yr

Study Design: Time series 

N: NR 

Statistical Analyses: GAM, GLM 

Covariates: Temperature, humidity 

Season: 

Warm (Nov-Apr) and cool (May-Oct)

Dose-response Investigated: No

Statistical Package: S-Plus 

Lags Considered: 0-3 days 

Pollutant: BS,P 

Averaging Time: 24 h 

Mean/104/m (min-max): 

0.26 (0.04-3.37) 

SD = 0.22 

Monitoring Stations: 14 

Copollutant (correlation): 

Warm 

PM2.5: r = 0.93 

PM10: r = 0.82 

O3: r = 0.48 

NO2: r = 0.35 

CO: r = 0.33 

SO2: r = 0.21 

 

Cool 

PM2.5: r = 0.90 

PM10: r = 0.75 

O3: r = -0.08 

NO2: r = 0.59 

CO: r = 0.62 

SO2: r = 0.48 

Other variables: 

Warm 

Temp: r = 0.23 

Rel humidity: r = -0.04 

Cool 

Temp: r = -0.09 

Rel humidity: r = 0.36 

PM Increment: 0.18/ 104/m (IQR) 

Percent Change Estimate [CI]: 

All CVD 

Same-day lag: 1.05 [0.44,1.66] 

Avg 0-1 day lag: 0.79 [0.20,1.38]; 

Cool (same-day lag): 2.38 [1.15,3.62] 

Warm (same-day lag): 0.45 [-0.18,1.09] 

Cardiac disease 

Same-day lag: 1.34 [0.63,2.05] 

Avg 0-1 day lag: 1.13 [0.44,1.82]; 

Cool (same-day lag): 2.50 [1.04,3.98] 

Warm (same-day lag): 0.80 [0.07,1.54] 

Ischemic heart disease 

Same-day lag: 0.91 [-0.17,2.02] 

Avg 0-1 day lag: 0.90 [-0.14,1.95]; 

Cool (same-day lag): 0.52 [-1.74,2.83] 

Warm (same-day lag): 0.93 [-0.15,2.03] 

Stroke 

Same-day lag: -0.93 [-2.27,0.42] 

Avg 0-1 day lag: -0.82 [-2.11,0.49]; 

Cool (same-day lag): 1.38 [-1.19,4.01]; 

Warm (same-day lag): -1.85 

[-3.31,-0.36] 

Notes: All other lag-day ORs were 

provided, yet none were significant. 

Percent change in ED attendance was 

also reported graphically (Fig 1-5).

December 2009 E-117 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lisabeth et al. (2008, 

155939) 

Period of Study: 2001-2005

Location: Nueces County, Texas 

Outcome: Ischemic stroke and 

transient ischemic attacks (ICD codes 

not reported). 

Age Groups: 45+ yr

Study Design: Time series

N: 3,508 stroke/TIAs (2,350 strokes, 

and 1,158 TIAs) 

Statistical Analyses: Poisson 

regression 

Covariates: Temperature, day of week, 

temporal trends 

Season: All, but looked at potential 

effect modification by season (Summer: 

Jun-Sep; Non-summer: Oct-May)

Dose-response Investigated: No

Statistical Package: S-plus 7.0 

Lags Considered: Lags 0-5 days, and 

avg lag effect (0-5 days) 

Pollutant: PM2.5

Averaging Time: 24 h 

Median μg/m3 (IQR): 7.0 (4.8-10.0) 

Monitoring Stations: 6 

Copollutant (correlation): NR 

PM Increment: 5.1 μg/m3 (IQR) 

RR Estimate [CI]: Lag 0: 1.03 (0.99, 

1.07) 

Lag 1: 1.03 (1.00-1.07) 

All other lags and avg (lag 0-5) were not 

statistically or marginally significant. 

Adjusted for O3: Lag 0: 1.03 (0.99, 1.07)

Lag 1: 1.03 (0.99-1.06) 

All other lags and avg (lag 0-5) were not 

statistically or marginally significant. 

Notes: Fig 3: % change in stroke/TIA 

risk associated with an IQR increase in 

PM2.5

Reference: Metzger et al. (2004, 

044222) 

Period of Study: Aug 1998-Aug 2000

Location: Atlanta Metropolitan area 

(Georgia) 

Outcome (ICD-9): Emergency visits for 

ischemic heart disease (410-414), 

cardiac dysrhythmias (427), cardiac 

arrest (427.5), congestive heart failure 

(428), peripheral vascular and 

cerebrovascular disease (433-437, 440, 

443-444, 451-453), atherosclerosis 

(440), and stroke (436). 

Age Groups: All

Study Design: Time series

N: 4,407,535 emergency department 

visits for 1993-2000 (data not reported 

for 1998-2000) 

Statistical Analyses: Poisson 

generalized linear modeling 

Covariates: Day of the wk, hospital 

entry and exit indicator variables, 

federally observed holidays, temporal 

trends, temperature, dew point 

temperature 

Season: All

Dose-response Investigated: No

Statistical Package: SAS 

Lags Considered: 3-day ma, lags 0 -7 

Pollutant: PM2.5

Averaging Time: 24 h 

Median μg/m3 (10%-90% range):

PM2.5: 17.8 (8.9, 32.3) 

PM2.5 water soluble metals: 0.021 

(0.006-0.061) 

PM2.5 acidity: 4.5 (1.9-1.07) 

PM2.5 OC: 0.010 

(-0.001-0.045) 

PM2.5 EC: 4.1 (2.2-7.1) 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10: r = 0.84 

O3: r = 0.65 

NO2: r = 0.46 

CO: r = 0.44 

SO2: r = 0.17 

PM10-2.5: r = .43 

UFP: r = -0.16 

PM2.5 water-sol metals: r = 0.70 

PM2.5 sulfates: r = 0.77 

PM2.5 acidity: r = 0.58 

PM2.5 OC: r = 0.51 

PM2.5 EC: r = 0.48 

oxygenated hydrocarbon: r = 31 

Other variables: 

Temperature: r = 0.20 

Dew point: r = 0.00 

PM Increment: Approximately 1 SD 

increase: PM2.5: 10 μg/m3

 

PM2.5 water-sol metals: 0.03 μg/m3

 

PM2.5 sulfates: 5 μg/m3 

PM2.5 acidity: 0.02 μequ/m3

 

PM2.5 OC: 2 μg/m3

 

PM2.5 EC: 1 μg/m3 

RR [95% CI]: PM2.5 (3-day ma): 

All CVD: 1.033 [1.010, 1.056] 

Dysrhythmia: 1.015 [0.976, 1.055] 

Congestive heart failure: 

1.055 [1.006-1.105] 

Ischemic heart disease: 

1.023 [0.983-1.064] 

Peripheral vascular and 

cerebrovascular disease: 

1.050 [1.008-1.093] 

PM2.5 water soluble metals (3-day 

ma): 

All CVD: 1.027[0.998, 1.056] 

Dysrhythmia: 1.031 [0.982, 1.082] 

Congestive heart failure: 1.040 

[0.981-1.103] 

Ischemic heart disease: 1.000 

[0.951-1.051] 

Peripheral vascular and 

cerebrovascular disease: 1.043 

[0.991-1.098] 

PM2.5 sulfates (3-day ma): 

All CVD: 1.003 [0.968, 1.039] 

Dysrhythmia: 0.986 [0.926, 1.048] 

Congestive heart failure: 1.009 

[0.938-1.085] 

Ischemic heart disease: 0.997 

[0.936-1.062] 

Peripheral vascular and 

cerebrovascular disease: 1.025 

[0.964-1.090] 

PM2.5 acidity (3-day ma): 

December 2009 E-118 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

All CVD: 0.994 [0.966, 1.022] 

Dysrhythmia: 0.991 [0.942, 1.043] 

Congestive heart failure: 0.989 

[0.930-1.052] 

Ischemic heart disease: 0.992 

[0.944-1.043] 

Peripheral vascular and 

cerebrovascular disease: 1.004 

[0.955-1.056] 

PM2.5 OC (3-day ma): 

All CVD: 1.026 [1.006, 1.046] 

Dysrhythmia: 1.008 [0.975, 1.044] 

Congestive heart failure: 1.048 

[1.007-1.091] 

Ischemic heart disease: 1.028 

[0.994-1.064] 

Peripheral vascular and 

cerebrovascular disease: 

1.026 [0.990-1.062] 

hydrocarbons simultaneously. 

PM2.5 OC (3-day ma): 

All CVD: 1.020 [1.005, 1.036] 

Dysrhythmia: 1.011 [0.985, 1.037] 

Congestive heart failure: 1.035 

[1.003-1.068] 

Ischemic heart disease: 1.019 

[0.992-1.046] 

Peripheral vascular and 

cerebrovascular disease: 1.021 

[0.994-1.049] 

Results for Lags 0-7 expressed in 

figures (see notes). 

Notes: Fig 1: RR (95% CI) for singleday lag models for the association of 

ER visits for CVD with daily ambient 

PM2.5 and associated components. 

Summary of Fig 1 results: Statistically 

significant positive associations at Lag 

0 and Lag 1 for PM2.5, at Lag 0 for PM2.5

water soluble metals (inverse 

association at Lag 7), at Lag 0, Lag 1, 

and Lag 3 for organic and EC (inverse 

association at Lag 7). 

Fig 2: RR (95%) of multipollutant 

models for the association of ER visits 

for CVD with daily ambient air quality 

measurements. 

Summary of Fig 2 results: Positive 

association after adjustment for NO2, 

CO, and oxygenated hydrocarbons, but 

attenuated when adjusted for total 

carbon and null when adjusted for NO2, 

CO, total carbon, and oxygenated

December 2009 E-119 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peng et al. (2008, 156850) 

Period of Study: Jan 1999-Dec 2005

Location: 108 U.S. counties in the 

following states: Alabama, Arizona, 

California, Colorado, Connecticut, 

District of Columbia, Florida, Georgia, 

Idaho, Illinois, Indiana, Kentucky, 

Louisiana, Maine, Maryland, 

Massachusetts, Michigan, Minnesota, 

Missouri, Nevada, New Hampshire, 

New Jersey, New Mexico, New York, 

North Carolina, Ohio, Oklahoma, 

Oregon, Pennsylvania, Rhode Island, 

South Carolina, Tennessee, Texas, 

Utah, Virginia, Washington, West 

Virginia, Wisconsin 

Outcome (ICD-9): Emergency 

hospitalizations for: Cardiovascular 

disease, including heart failure (428), 

heart rhythm disturbances (426-427), 

cerebrovascular events (430-438), 

ischemic heart disease (410-414, 429), 

and peripheral vascular disease 

(440-448). Respiratory disease, 

including COPD (490-492) and 

respiratory tract infections (464-466, 

480-487) 

Age Groups: 65 + yr, 65-74, ,75 +

Study Design: Time series

N: ~12 million Medicare enrollees (3.7 

million CVD and 1.4 million RD 

admissions) 

Statistical Analyses: Two-stage 

Bayesian hierarchical models: 

Overdispersed Poisson models for 

county-specific data 

Bayesian hierarchical models to obtain 

national avg estimate 

Covariates: Day of the week, agespecific intercept, temperature, dew 

point temperature, calendar time, 

indicator for age of 75 yr or older. Some 

models were adjusted for PM10-2.5. 

Season: NR

Dose-response Investigated: No

Statistical Package: R version 2.6.2 

Lags Considered: 0-2 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean μg/m3 (IQR): All counties assessed: 13.5 (11.1-15.8) 

Counties in Eastern U.S.: 

13.8 (12.3-15.8) 

Counties in Western U.S.: 

11.1 (10.1-14.3) 

Monitoring Stations: At least 1 pair of 

co-located monitors (physically located 

in the same place) for PM10 and PM2.5

per county 

Other variables: Median within-county 

correlations between monitors: r = 0.92 

PM Increment: 10 μg/m3

Percentage change [95% CI]: CVD and 

RD (unadjusted for PM10-25): Lag 0: 

0.71 [0.45, 0.96] 

Lag 2: 0.44 [0.06, 0.82] 

Most values NR (see note) 

Notes: Effect estimates for PM10-2.5 (0-2 

day lags) are showing in Fig 2-5. 

Fig 2: Percentage change in emergency 

hospital admissions for CVD per 10 

μg/m3

 increase in PM2.5 (single pollutant 

model and model adjusted for PM10-2.5

concentration) 

Fig 3: Percentage change in emergency 

hospital admissions for RD per 10 

μg/m3

 increase in PM2.5 (single pollutant 

model and model adjusted for PM10-2.5

concentration) 

No significant associations between 

PM2.5 and cause-specific cardiovascular 

disease. 

Reference: Peters et al. (2005, 

156859) 

Period of Study: Feb 1999-Jul 31, 

2001

Location: Germany: City of Augsburg, 

County Augsburg, and County AichachFriedlberg 

Outcome: Transmural or 

nontransmural acute MI 

Age Groups: NR

Study Design: Case-crossover and 

time series

N: 851 MI survivors 

Statistical Analyses: Conditional 

logistic regression for case-crossover 

element. Poisson regression for time 

series element. 

Covariates: Case-crossover: Season, 

temperature, day of the week, time 

series: trend, season, influenza, 

weather, and day of the week 

Season: All 

Dose-response Investigated: No

Statistical Package: 

SAS, version 8.2 

Poisson: R, version 1.7.1 

Lags Considered: Lags 0-6 h, 0-5 

days 

Poisson: Single lagged days, 5-day, 

15-day, 30-day, and 45-day ma 

Pollutant: PM2.5

Averaging Time: 1 h and 24 h 

Mean μg/m3 (range IQR/ median 

IQR): 

1-h avg: 16.3 (-6.9-355.2 

10.7-19.8 

14.5) 

24-h avg: 16.3 (6.1-58.5 

11.6-19.3 

14.9) 

Monitoring Stations: 1 

Copollutant (correlation): 

24-h avg: 

TNC: r = 0.37 

TSP: r = 0.89 

PM10: r= 0.92 

CO: r = 0.57 

NO2: r = 0.67 

NO: r = 0.59 

SO2: r = 0.58 

O3: r = -0.24 

1hr avg: 

TNC: r = 0.42 

CO: r = 0.52 

NO2: r = 0.58 

NO: r = 0.50 

SO2: r = 0.48 

O3: r = -0.35 

Other variables: 

24-h avg: Temperature: r = 0.05 

1-h avg: Temperature: r = -0.01 

PM Increment: 1-h avg: 9.1 μg/m3

(IQR) 

24-h avg: 7.7 μg/m3

 (IQR) 

OR [95% CI]: Case-Crossover (control 

selection method (unidirectional with 

three control periods): 

1-h avg: Lag 0: 0.98 (0.88, 1.10) 

Lag 1: 0.97 (0.87, 1.09) 

Lag 2: 0.93 (0.83, 1.04) 

Lag 3: 0.98 (0.88, 1.09) 

Lag 4: 0.96 (0.86, 1.07) 

Lag 5: 0.94 (0.84, 1.05) 

Lag 6: 0.90 (0.80, 1.01). 

24-h avg: Lag 0: 0.95 (0.83, 1.080) 

Lag 1: 1.10 (0.96, 1.25) 

Lag 2: 1.18 (1.03, 1.34) 

Lag 3: 1.07 (0.94, 1.22) 

Lag 4: 0.94 (0.83, 1.07) 

Lag 5: 0.90 (0.79, 1.02) 

Case-Crossover (control selection 

method: bidirectional with 16 control 

periods): 

24-h avg: Lag 0: 1.03 (0.94, 1.12) 

Lag 1: 1.07 (0.98, 1.16) 

Lag 2: 1.08 (0.99, 1.17) 

Lag 3: 1.01 (0.92, 1.10) 

Lag 4: 0.96 (0.88, 1.04) 

Lag 5: 0.93 (0.85, 1.02) 

Lag 0 -4 (IQR = 5.8): 1.03 (0.94, 1.14) 

Unidirectional: Model 1 (unadjusted): 

1.175 (1.033, 1.337) 

Model 2 (adjusted for day of week using 

indicator variables): 1.179 (1.035, 

December 2009 E-120 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

1.343) 

Model 3 (adjusted for temperaturequadratic, linear air pressure): 1.170 

(1.028, 1.333) 

Model 4 (adjusted for temperaturequadratic, linear air pressure, day of 

week): 1.176 (1.031, 1.341) 

Model 5 (temperature-quadratic, air 

pressure-quadratic, relative humidityquadratic, day of week using indicator 

variables): 1.170 (1.026, 1.336) 

Model 6 (temperature-penalized spline, 

4.4 df, linear air pressure, day of week 

using indicator variables): 1.175 (1.030, 

1.340 

Model 7 (temperature-penalized spline, 

4.4 df, linear air pressure, relative 

humidity-penalized spline, 7.8 df, day of 

week using indicator variables: 1.177 

(1.030, 1.344) 

Bidirectional (16 control periods): Model 

1 (unadjusted): 1.077 (0.988, 1.174) 

Model 2 (adjusted for day of the week 

using indicator variables): 1.078 (0.988, 

1.175) 

Model 3 (adjusted for temperaturequadratic, linear air pressure): 1.060 

(0.970, 1.160) 

Model 4 (adjusted for temperaturequadratic, linear air pressure, day of the 

week): 1.060 (0.969, 1.160) 

Model 5 

 (temperature-quadratic, air pressurequadratic, relative humidity-quadratic, 

day of the week using indicator 

variables): 1.065 (0.973, 1.166) 

Model 6 (temperature-penalized spline, 

4.4 df, linear air pressure, day of the 

week using indicator variables): 1.068 

(0.976, 1.168) 

Model 7 (temperature-penalized spline, 

4.4 df, linear air pressure, relative 

humidity-penalized spline, 7.8 df, day of 

the week using indicator variables: 

1.077 (0.983, 1.179) 

Bidirectional (4 control periods): Model 

1 (unadjusted): NR 

Model 2 (adjusted for day of the week 

by design): 1.049 (0.964, 1.141) 

Model 3 (adjusted for temperaturequadratic, linear air pressure): NR 

Model 4 (adjusted for temperaturequadratic, linear air pressure, day of the 

week): 1.032 (0.944, 1.128) 

Model 5 (temperature-quadratic, air 

pressure-quadratic, relative humidityquadratic, day of the week by design): 

1.033 (0.945, 1.130) 

Model 6 (temperature-penalized spline, 

4.4 df, linear air pressure, day of the 

week by design): 1.036 (0.947, 1.132) 

Model 7 (temperature-penalized spline, 

4.4 df, linear air pressure, relative 

December 2009 E-121 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

humidity-penalized spline, 7.8 df, day of 

the week by design): 1.039 (0.950, 

1.136) 

Stratified: Model 1 (unadjusted): NR 

Model 2 (adjusted for day of week by 

design): 1.059 (0.972, 1.154) 

Model 3 (adjusted for temperaturequadratic, linear air pressure): NR 

Model 4 (adjusted for temperaturequadratic, linear air pressure, day of 

week): 1.047 (0.957, 1.145) 

Model 5 (temperature-quadratic, air 

pressure-quadratic, relative humidityquadratic, day of week by design): 

1.045 (0.954, 1.144) 

Model 6 (temperature-penalized spline, 

4.4 df, linear air pressure, day of week 

by design): 1.054 (0.964, 1.153odel 7 

(temperature-penalized spline, 4.4 df, 

linear air pressure, relative 

humidity-penalized spline, 7.8 df, day of 

week by design): 1.056 (0.965, 1.156) 

RR (95% CI): Time series (24 h avg): 

Lag 0: 0.97 (0.89, 1.07) 

Lag 1: 1.04 (0.96, 1.13) 

Lag 2: 1.07 (0.98, 1.15) 

Lag 3: 1.03 (0.95, 1.11) 

Lag 4: 0.98 (0.90, 1.07) 

Lag 5: 0.98 (0.90, 1.06) 

Lag 0-4: 1.03 (0.94, 1.12) 

Lag 0-14: 1.03 (0.95, 1.13) 

Lag 0-29: 1.09 (1.01, 1.18) 

Lag 0-44: 1.08 (1.00, 1.17) 

Time series (OR [95% CI]): Model 1 

(unadjusted): 1.059 (0.981, 1.142) 

Model 2 (adjusted for day of week using 

indicator variables): 1.056 (0.979, 

1.140) 

Model 3 (adjusted for temperaturequadratic, linear air pressure): 1.062 

(0.982, 1.148) 

Model 4 (adjusted for temperaturequadratic, linear air pressure, day of 

week): 1.059 (0.979, 1.146) 

Model 5 (temperature-quadratic, air 

pressure-quadratic, relative humidityquadratic, day of week using indicator 

variables): 1.063 (0.981, 1.151) 

Model 6 (temperature-penalized spline, 

4.4 df, linear air pressure, day of week 

using indicator variables): 1.065 (0.985, 

1.153) 

Model 7 (temperature-penalized spline, 

4.4 df, linear air pressure, relative 

humidity-penalized spline, 7.8 df, day of 

week using indicator variables: 1.069 

(0.988, 1.157) 

December 2009 E-122 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Pope et al.(2006, 091246) 

Period of Study: 1994-2004

Location: Wasatch Front area, Utah 

Outcome: Myocardial infarction or 

unstable angina (ICD codes not 

reported) 

Age Groups: All, <65, 65+

Study Design: Case-crossover

N: 12,865 patients who underwent 

coronary arteriography 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and dew 

point temperature 

Season: NR

Dose-response Investigated: No

Statistical Package: NR 

Lags Considered: 0- to 3-day lag, 2- to 

4-day lagged ma 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (μg/m3) (SD maximum): Ogden: 10.8 (10.6 

108) 

SLC Hawthorne: 11.3 (11.9 

94) 

Provo/Orem, Lindom: 10.1 (9.8 

82) 

Monitoring Stations: 3 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3 

Percent increase in risk [95% CI]: 

Same-day increase in PM2.5 (Lag 0): 

Index MI and unstable angina: 4.81 

[0.98-8.79] 

Subsequent MI: 3.23 [-3.87, 10.85] 

All acute coronary events: 4.46 

[1.07-7.97] 

All acute coronary events excluding 

observations using imputed PM2.5 data: 

4.24 [0.33-8.31] 

Stable presentation: -2.57 [-5.39, 0.34] 

Remaining results summarized in 

figures (see notes). 

Notes: Fig 1: Percent increase in risk 

(and 95% CI) of acute coronary events 

associated with 10 μg/m3

 of PM2.5 for 

different lag structures. 

Summary of Fig 1: Positive, statistically 

significant association seen for Lag 0, 

Lag 1 and 2, 3, and 4 day ma. Positive 

but non-statistically significant 

associations seen for Lags 2 and 3. 

Fig 2: Percent increase in risk (and 95% 

CI) of acute coronary events associated 

with 10 μg/m3

 of PM2.5 stratified by 

various characteristics.

Reference: Pope et al. (2008, 191969) 

Period of Study: 1994-2006 

Location: Ogden, Salt Lake City, & 

Provo/Orem, Utah 

Outcome: Heart Failure 

Hospitalizations 

Age Groups: NR

Study Design: Case-crossover 

N: 2,618 

Statistical Analyses: Conditional 

Logistic Regression 

Covariates: Age, sex, length of stay, 

temperature, pressure, clearing index, 

day of the week, seasonality, and longterm trends 

Season: Adjusted for long-term trends 

to account for season 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0- to 28-day ma. 

Pollutant: PM2.5 

Averaging Time: NR 

Mean (SD): 

Ogden: 10.6(9.9) 

SLC, Hawthorne: 11.1 (11.2) 

Provo/Orem, Lindon: 10.1 (9.3) 

Max: 

Ogden: 108 

SLC, Hawthorne: 94 

Provo/Orem, Lindon: 82 

Monitoring Stations: NR 

Copollutant: PM10

PM Increment: 10 μg/m3

Percent Increase: (Lower CI, Upper 

CI): 

All HF Admissions 

All: 13.1 (1.3, 26.2)* 

Men: 13.4 (-1.7, 30.7)‡ 

Women: 12.7 (-5.1, 33.9) 

Age <65 yr: 3.5 (-13.5, 23.8) 

Age ≥65 yr: 19.6 (4.0, 37.5)* 

Length of stay 0-2 days: 

24.4 (-0.8, 56.0) ‡ 

Length of stay 3-7 days: 

10.8 (-4.6, 28.7) 

Length of stay 8+ days: 

6.5 (-15.9, 34.8) 

First HF Admissions: 2.1 (-11.3, 17.5) 

Subsequent HF Admits: 32.4 (10.7, 

58.4) † 

All HF Admissions 

All: 32.4 (10.7, 58.4) † 

Men: 29.2 (2.7, 62.6)* 

Women: 41.5 (5.4, 89.9)* 

Age <65 yr: -3.1 (-26.5, 27.8) 

Age ≥65 yr: 64.1 (28.6, 109) † 

Length of stay 0-2 days: 

68.9 (12.5, 154)* 

Length of stay 3-7 days: 

35.7 (5.9, 73.9)* 

Length of stay 8+ days: 

2.6 (-28.5, 47.1) 

*p < 0.05, † p < 0.01, ‡p < 0.10 

December 2009 E-123 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sarnat et al. (2008, 

097972) 

Period of Study: Nov 1998-Dec 2002

Location: Atlanta (Georgia) 

metropolitan area 

Outcome (ICD-9): Cardiovascular 

disease ED visits: Ischemic heart 

disease (410-414), cardiac 

dysrhythmias (427), congestive heart 

failure (428), and peripheral vascular 

and cerebrovascular disease (433-437, 

440, 443-444, 451-453) 

Age Groups: All

Study Design: Time series

N: >4.5 million emergency department 

visits 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Day of the week, holidays, 

hospital, long-term trends, temperature, 

dew point temperature 

Season: All, warm season (Apr 15-Oct 

14), and cool season (Oct 15-Apr 14). 

Dose-response Investigated: No

Statistical Package: NR 

Lags Considered: 0-day lag 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (μg/m3) (median 10th-90th 

percentile): 

Total PM2.5: 

Cool season: 15.8 (14.3 

7.5-25.5). 

Warm season: 18.2 (17.0 

9.1-29.0) 

PM2.5 EC: 

Cool: 1.7 (1.4 

0.6-3.3). 

Warm: 1.4 (1.3 

0.6-2.5) 

PM2.5 Zn (ng/m3

): 

Cool: 15.7 (11.7 

4.6-30.2) 

Warm: 10.9 (8.5 

3.3-20.2) 

PM2.5 K (ng/m3

): 

Cool: 63.0 (53.9 

24.3-114.2) 

Warm: 52.7 (43.3 

23.2-93.5) 

PM2.5 Si (ng/m3

): 

Cool: 67.7 (54.1 

24.3-123.5). 

Warm: 110.9 (89.0 

32.9-186.3) 

PM2.5 SO4

2–: 

Cool: 3.4 (0.6 

1.5-5.8). 

Warm: 6.0 (5.2 

2.3-10.8) 

PM2.5 NO3-: 

Cool: 1.4 (1.2 

0.5-2.6). 

Warm: 0.7 (2.9 

0.3-1.2) 

PM2.5 Se (ng/m3

): 

Cool: 1.4 (1.1 

0.4-3.0). 

Warm: 1.2 (0.9 

0.4-2.7) 

PM2.5 OC: 

Cool: 4.6 (3.9 

1.9-8.0) 

Warm: 4.0 (3.7 

2.1-6.4) 

Monitoring Stations: 1 

Copollutants: NR 

PM Increment: IQR (specific values not 

given) 

Risk ratio [95% CI]: CVD (Lag 0): All 

seasons: Total PM2.5: 1.022 [1.007, 

1.038] 

PM2.5 EC: 1.02 [1.013-1.037] 

PM2.5 zinc: 1.013 [1.005-1.022] 

PM2.5 potassium: 1.030 [1.018-1.042] 

PM2.5 silicon: 1.008 [1.00-1.016] 

PM2.5 sulfate: 1.007 [0.994-1.019] 

PM2.5 nitrate: 1.002 [0.990-1.014] 

PM2.5 selenium: 1.002 [0.991-1.012] 

PM2.5 OC: 1.024 [1.013-1.035] 

Cool season: Total PM2.5: 1.028 

[1.012-1.044] 

PM2.5 EC: 1.029 [1.015-1.044] 

PM2.5 Zinc: 1.012 [1.002-1.022] 

PM2.5 K: 1.037 [1.021-1.054] 

PM2.5 Si: 1.022 [1.002-1.043] 

PM2.5 sulfate: 1.014 [0.991-1.037] 

PM2.5 nitrate: 1.006 [0.993-1.019] 

PM2.5 Se: 1.012 [0.997-1.027] 

PM2.5 OC: 1.027 [1.013-1.040] 

Warm season: Total PM2.5: 1.006 

[0.990-1.022] 

PM2.5 EC: 1.021 [1.000-1.043] 

PM2.5 Zinc: 1.017 [1.002-1.033] 

PM2.5 K: 1.024 [1.007-1.041] 

PM2.5 Si: 1.005 [0.996-1.014] 

PM2.5 sulfate: 1.001 [0.988-1.015] 

PM2.5 nitrate: 1.000 [0.969-1.033] 

PM2.5 Se: 0.996 [0.981-1.011] 

PM2.5 OC: 1.027 [1.004-1.051]

December 2009 E-124 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Schreuder et al. (2006, 

097959) 

Period of Study: Sep 1995-May 2002 

Location: Spokane, WA 

Outcome: Cardiac HA 

Age Groups: NR 

Study Design: Time series 

Statistical Analyses: GAM Poisosn 

Regression 

Covariates: Season, temperature, 

relative humidity, day of week 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0-1 day 

Pollutant: PM2.5 (ng/m3) 

Averaging Time: 24 h 

Arithmetic Mean: 10,580 

Geometric Mean: 8,790 

Min: 930 

Max: 43,230 

IQR: 

Entire period: 7.7 μg/m3

Heating season: 10.1μg/m3

Non-heating season: 5.5μg/m3

Monitoring Stations: NR 

Copollutant: NR 

Co-pollutant Correlation: NR 

PM Increment: Interquartile Range 

Relative Risk (Lower CI, Upper CI): 

Entire Period, Lag 0: 1.008 (0.985, 

1.032) 

Entire Period, Lag 1: 1.000 (0.978, 

1.023) 

Heating Season, Lag 1: 1.015 (0.968, 

1.063) 

Non-Heating Season, Lag 1: 0.995 

(0.969, 1.021) 

December 2009 E-125 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sullivan et al. (2005, 

109418) 

Period of Study: 1988-1994

Location: King County, Washington 

Outcome: Acute MI 

Age Groups: All, <50, 50-59, 70+ 

Study Design: Case-crossover

N: 5793 cases of acute MI (5793 case 

days and 20,134 referent exposure 

days from these case individuals) 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Relative humidity, 

temperature, season, day of week 

Season: All, and also conducted 

stratified analysis by season of event 

(heating season: Nov-Feb 

nonheating season: Mar-Oct)

Dose-response Investigated: No

Statistical Package: SAS version 8.0 

and SPSS version 10 

Lags Considered: Lag 1 and Lag 2 for 

24-h avg 

Pollutant: PM2.5 

Averaging Time: 

1 h, 2 h, 4 h, and 24 h 

Summary of PM2.5 1 h before MI onset: 

Mean (μg/m3) (median IQR, 90th 

percentile range): 

12.8 (8.6 

5.3-15.9 

27.3 

2.0-147) 

Monitoring Stations: 3 

Copollutant (correlation): 

1-h avg: 

PM10: r = 0.78 

CO: r = 0.47 

SO2: r = 0.16 

PM Increment: 10 μg/m3 

Odds ratio [95% CI]: 

1-h Averaging Time: 1.01 [0.98, 1.05] 

2-h Averaging Time: 1.01 [0.97, 1.05] 

4-h Averaging Time: 1.02 [0.98, 1.04] 

24-h Averaging Time: 1.02 [0.98, 1.07]

Association between PM2.5 (24 h) 

lagged 1 or 2 days non-significant (data 

not shown) 

Season (1-h avg): Heating: 1.01 

[0.98-1.05] 

Nonheating: 0.99 [0.91-1.09] 

Age (1-h avg): <50 yr: 1.04 [0.95, 1.14] 

50-60 yr: 0.99 [0.94, 1.05] 

70+ yr: 1.03 [0.98, 1.08] 

Age (24-h avg): <50 yr: 1.07 [0.98, 1.19]

50-69 yr: 0.99 [0.93, 1.06] 

70+ yr: 1.04 [0.99, 1.11] 

Sex (1-h avg): Men: 1.02 [0.98, 1.06] 

Women: 1.00 [0.95, 1.06] 

Sex (24-h avg): Men: 1.03 [0.99, 1.08] 

Women: 1.00 [0.94, 1.07] 

Race (1-h avg): White: 1.01 [0.97, 1.04] 

Nonwhite: 1.06 [0.97, 1.17] 

Race (24-h avg): White: 1.01 [0.97, 

1.06] 

Nonwhite: 1.10 [0.99, 1.23] 

Smoking status (1-h avg): Current: 0.99 

[0.93, 1.06] 

Nonsmoker: 1.03 [0.97, 1.08] 

Smoking status (24-h avg): Current: 

0.99 [0.95, 1.14] 

Nonsmoker: 1.03 [0.98, 1.09] 

Survivor of MI * (1-h avg): Yes: 1.02 

[0.98, 1.06]; No: 0.96 [0.86, 1.08] 

Survivor of MI * (24-h avg): Yes: 1.03 

[0.98, 1.07]; No: 0.97 [0.85, 1.10] 

Previous congestive heart failure (1 h 

avg): Yes: 1.06 [0.97, 1.16]; No: 1.00 

[0.97, 1.04] 

Previous congestive heart failure (24-h 

avg): Yes: 1.08 [0.97, 1.2]; No: 1.00 

[0.97, 1.04] 

Previous MI (1-h avg): Yes: 1.03 [0.97, 

1.1]; No: 1.01 [0.96, 1.06] 

Previous MI (24-h avg): Yes: 1.04 [0.97, 

1.17]; No: 1.02 [0.98, 1.08] 

Hypertension (1-h avg): Yes: 1.02 [0.97, 

1.07]; No: 1.01 [0.96, 1.06] 

Hypertension (24-h avg): Yes: 1.02 

[0.97, 1.07]; No: 1.02 [0.97, 1.08] 

Diabetes mellitus (1-h avg): Yes: 1.06 

[0.98, 1.14]; No: 1.01 [0.97, 1.05] 

Diabetes mellitus (24-h avg): Yes: 1.04 

[0.95, 1.14]; No: 1.01 [0.97, 1.06] 

*Compares those who survive 

hospitalization (yes) with those who 

died in hospital from complications of 

MI. 

December 2009 E-126 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Symons et al. (2006, 

091258) 

Period of Study: Apr-Dec 2002

Location: Baltimore, Maryland 

Outcome: Congestive heart failure 

Age Groups: All

Study Design: Case-crossover

N: 125 patients 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and humidity 

Season: NR

Dose-response Investigated: Yes

Statistical Package: SAS and S-Plus 

Lags Considered: 0-3 days (single and 

cumulative) 

Pollutant: PM2.5

Averaging Time: 8 h & 24 h 

Mean (min-max): 

8 h 

17.0 (0.1-111.9) 

SD = 12.7 

24 h 

16.0 (3.5-69.2) 

SD = 10.0 

Monitoring Stations: 8 

Copollutant (correlation): NR 

PM Increment: 9.2 μg/m3 (IQR) 

RR Estimate [CI]: 

8 h (participant’s onset period) 

Same-day lag: 0.87 [0.69,1.09] 

1-day lag: 0.96 [0.78,1.18] 

2-day lag: 1.09 [0.91,1.30] 

3-day lag: 0.99 [0.79,1.23] 

Cumulative 1-day lag: 0.89 [0.67,1.16] 

Cumulative 2-day lag: 0.99 [0.74,1.33] 

Cumulative 3-day lag: 0.98 [0.70,1.36] 

24 h avg 

Same-day lag: 0.81 [0.65,1.01] 

1-day lag: 0.90 [0.74,1.11] 

2-day lag: 0.85 [0.68,1.07] 

3-day lag: 0.86 [0.70,1.05] 

Cumulative 1-day lag: 0.82 [0.64,1.04] 

Cumulative 2-day lag: 0.76 [0.57,1.01] 

Cumulative 3-day lag: 0.70 [0.51,0.97] 

Notes: β coefficients presented in Fig 5

Reference: Tolbert et al. (2007, 

090316) 

Period of Study: Aug 1998-Dec 2004

Location: Atlanta Metropolitan area, 

Georgia 

Outcome (ICD-9): 

Combined CVD group, including: 

Ischemic heart disease (410-414), 

cardiac dysrhythmias (427), congestive 

heart failure (428), and peripheral 

vascular and cardiovascular disease 

(433-437, 440, 443-445, and 451-453) 

Age Groups: All

Study Design: Time series

N: NR for 1998-2004. 

For 1993-2004: 10,234,490 ER visits 

(283,360 and 1,072,429 visits included 

in the CVD and RD groups, 

respectively) 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Long-term temporal trends, 

season (for RD outcome), temperature, 

dew point, days of week, federal 

holidays, hospital entry and exit 

Season: All

Dose-response Investigated: No

Statistical Package: SAS version 9.1 

Lags Considered: 3-day ma(lag 0 -2) 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (μg/m3) (median IQR, range, 

10th -90th percentiles): 

PM2.5: 17.1 (15.6 

11.0-21.9 

0.8-65.8 

7.9-28.8). 

PM2.5 sulfate: 4.9 (3.9 

2.4-6.2 

0.5-21.9 

1.7-9.5). 

PM2.5 OC: 4.4 (3.8 

2.7-5.3 

0.4-25.9 

2.1-7.2). 

PM2.5 EC: 1.6 (1.3 

0.9-2.0 

0.1-11.9 

0.6-3.0). 

PM2.5 water-soluble metals: 0.030 

(0.023 

0.014-0.039 

0.003-0.202 

0.009-0.059) 

Monitoring Stations: 1 

Copollutant (correlation): 

Between PM2.5 and: 

PM10: r = 0.84 

O3: r = 0.62 

NO2: r = 0.47 

CO: r = 0.47 

SO2: r = 0.17 

PM10-2.5: r = 0.47 

PM2.5 SO4: r = 0.76 

PM2.5 EC: r = 0.65 

PM2.5 OC: r = 0.70 

PM2.5 TC: r = 0.71 

PM2.5 water-sol metals: r = 0.69 

OHC: r = 0.50 

Between PM2.5 SO4 and: PM10: r = 0.69 

O3: r = 0.56 

NO2: r = 0.14 

CO: r = 0.14 

SO2: r = 0.09 

PM10-2.5: r = 0.32 

PM2.5: r = 0.76 

PM2.5 EC: r = 0.32 

PM2.5 OC: r = 0.33 

PM Increment: 

PM2.5: 10.96 μg/m3

 (IQR) 

PM2.5 sulfate: 3.82 μg/m3

 (IQR) 

PM2.5 total carbon: 3.63 μg/m3

 (IQR) 

PM2.5 OC: 2.61 μg/m3 (IQR) 

PM2.5 EC: 1.15 μg/m3

 (IQR) 

PM2.5 water-soluble metals: 0.03 μg/m3

(IQR) 

Risk ratio [95% CI] (single pollutant 

models): 

PM2.5: 

CVD: 1.005 [0.993-1.017] 

PM2.5 sulfate: 

CVD: 0.999 [0.987-1.011] 

PM2.5 total carbon: 

CVD: 1.016 [1.005-1.026] 

PM2.5 OC: 

CVD: 1.015 [1.005-1.026] 

PM2.5 EC: 

CVD: 1.015 [1.005-1.025] 

PM2.5 water-soluble metals: 

CVD: 1.009 [0.997-1.021] 

Notes: Results of selected multipollutant models for cardiovascular 

disease are presented in Fig 1. 

 Fig 1: PM2.5 total carbon adjusted for 

CO, NO2, or NO2+CO 

Summary of results: PM2.5 total carbon 

continued to have a positive, statistically 

significant association with CVD after 

adjustment for NO2 but not after 

adjustment

December 2009 E-127 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

PM2.5 TC: r = 0.34 

PM2.5 water-sol metals: r = 0.65 

OHC: r = 0.47 

Between PM2.5 EC and: 

PM10: r = 0.61 

O3: r = 0.40 

NO2: r = 0.64 

CO: r = 0.66 

SO2: r = 0.22 

PM10-2.5: r = 0.49 

PM2.5: r = 0.65PM2.5

SO4: r = 0.32 

PM2.5 OC: r = 0.82 

PM2.5 TC: r = 0.91 

PM2.5 water-sol metals: r = 0.52 

OHC: r = 0.35 

Between PM2.5 OC and: 

PM10: r = 0.65 

O3: r = 0.54 

NO2: r = 0.62 

CO: r = 0.59 

SO2: r = 0.17 

PM10-2.5: r = 0.49 

PM2.5: r = 0.70 

PM2.5 SO4: r = 0.33 

PM2.5 EC: r = 0.82 

PM2.5 TC: r = 0.98 

PM2.5 water-sol metals: r = 0.49 

OHC: r = 0.37 

Between PM2.5 total carbon and: 

PM10: r = 0.67 

O3: r = 0.52 

NO2: r = 0.65 

CO: r = 0.63 

SO2: r = 0.19 

PM10-2.5: r = 0.51 

PM2.5: r = 0.71 

PM2.5 SO4: r = 0.34 

PM2.5 EC: r = 0.91 

PM2.5 OC: r = 0.98 

PM2.5 water-sol metals: r = 0.52 

OHC: r = 0.38 

Between PM2.5 water-soluble metals 

and: PM10: r = 0.73 

O3: r = 0.43 

NO2: r = 0.32 

CO: r = 0.35 

SO2: r = 0.06 

PM10-2.5: r = 0.50 

PM2.5: r = 0.69 

PM2.5 SO4: r = 0.65 

PM2.5 EC: r = 0.52 

PM2.5 OC: r = 0.49 

PM2.5 TC: r = 0.52 

December 2009 E-128 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Villeneuve et al. (2006, 

090191) 

Period of Study: Apr 1992-Mar 2002

Location: Edmonton, Canada 

Outcome (ICD-9): Stroke (430-438), 

including ischemic stroke (434-436), 

hemorrhagic stroke (430,432), and 

transient ischemic attacks (TIA) (435). 

Age Groups: 65+ yr

Study Design: Case-crossover

N: 12,422 visits 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and relative 

humidity 

Season: Summer (Apr-Sep), winter 

(Oct-Mar)

Dose-response Investigated: No

Statistical Package: SAS (PHREG) 

Lags Considered: 0, 1, and 3 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean μg/m3 (SD): 

All yr: 8.5 (6.2) 

Summer: 8.7 (7.1) 

Winter: 8.3 (5.2) 

Monitoring Stations: 3 

Copollutant (correlation): 

All yr 

SO2: r = 0.22 

NO2: r = 0.41 

CO: r = 0.43 

O3-mean: r = -0.07 

O3-max: r = 0.07 

PM10: r = 0.79 

Summer 

SO2: r = 0.20 

NO2: r = 0.52 

CO: r = 0.42 

O3-mean: r = 0.11 

O3-max: r = 0.34 

PM10: r = 0.85 

Winter 

SO2: r = 0.28 

NO2: r = 0.57 

CO: r = 0.71 

O3-mean: r = -0.45 

O3-max: r = -0.35 

PM10: r = 0.70 

PM Increment: μg/m3 (IQR) 

All yr: 6.3 

Summer: 6.5 

Winter: 6.0 

Adjusted OR Estimate [CI]: 

Acute ischemic stroke 

All yr: Same-day lag: 1.00 [0.96,1.04] 

1-day lag: 1.00 [0.96,1.05] 

3-day lag: 1.01 [0.96,1.06] 

Summer: Same-day lag: 0.96 

[0.90,1.03] 

1-day lag: 1.01 [0.94,1.07] 

3-day lag: 0.98 [0.89 [1.07] 

Winter: Same-day lag: 1.04 [0.99,1.10] 

1-day lag: 1.01 [0.96,1.07] 

3-day lag: 1.05 [0.98,1.13] 

Hemorrhagic stroke 

All yr: Same-day lag: 0.99 [0.90,1.08] 

1-day lag: 1.07 [0.98,1.16] 

3-day lag: 1.05 [0.93,1.19] 

Summer: Same-day lag: 0.99 

[0.86,1.15] 

1-day lag: 1.12 [0.97,1.30] 

3-day lag: 1.08 [0.88,1.31] 

Winter: Same-day lag: 1.04 [0.92,1.18] 

1-day lag: 1.08 [0.97,1.20] 

3-day lag: 1.11 [0.94,1.31] 

Transient cerebral ischemic attack 

All yr: Same-day lag: 0.98 [0.93,1.03] 

1-day lag: 0.99 [0.95,1.04] 

3-day lag: 0.96 [0.90,1.03] 

Summer: Same-day lag: 1.00 

[0.92,1.08] 

1-day lag: 1.03 [0.95,1.12] 

3-day lag: 0.98 [0.88,1.09] 

Winter: Same-day lag: 0.97 [0.90,1.05] 

1-day lag: 0.97 [0.91,1.04] 

3-day lag: 0.94 [0.86,1.03] 

Notes: Adjusted ORs are provided for 

an IQR increase in the 3-day mean in 

Fig 1-4 for single and two-pollutant 

models. 

Reference: Zanobetti and Schwartz 

(2006, 090195) 

Period of Study: 1995-1999

Location: Boston Metropolitan area 

Outcome (ICD-9): Myocardial infarction 

(410) or pneumonia (480-487) 

Age Groups: 65+ yr

Study Design: Case-crossover

N: 15,578 patients admitted for MI and 

25,857 admitted for pneumonia 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, day of the 

week. 

Season: All, and also tested for 

interaction by warm (Apr-Sep) vs.. cold 

season

Dose-response Investigated: No

Statistical Package: SAS version 8.2 

(PROC PHREG) 

Lags Considered: Lag 0 , and mean of 

lags 0 -1 

Pollutant: PM2.5

Averaging Time: 24 h 

Median (μg/m3) (IQR 5th-95th 

percentile): 

11.1 (7.23-16.14 

3.87-26.31) 

Monitoring Stations: 1 

Copollutant (correlation): 

BC: r = 0.66 

NO2: r = 0.55 

CO: r = 0.52 

O3: r = 0.20 

PM non-traffic: r = 0.74 

PM Increment: Difference between the 

90th and 10th percentile for PM2.5 

Myocardial infarction cohort (Lag 0): 

17.17 μg/m3

 

Myocardial infarction cohort (Lag 0-1): 

16.32 μg/m3

 

Pneumonia cohort (Lag 0): 17.14 μg/m3

Pneumonia cohort (Lag 0): 16.32 μg/m3

Percentage (%) increase in risk [95% 

CI]: 

Myocardial infarction cohort: 

Lag 0: 8.50 (1.89-14.43) 

Lag 0-1: 8.65 (1.22-15.38) 

Pneumonia cohort: 

Lag 0: 6.48 (1.13-11.43) 

Lag 0-1: 5.56 (-0.45, 11.27) 

Notes: Assessed for effect modification 

by season. Results are reported in Fig 

2. Summary of results: PM2.5 is 

associated with pneumonia 

hospitalization in the cold season but 

not the hot season. PM2.5 is associated 

with MI hospitalization in the hot season 

but not the cold season. 

December 2009 E-129 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zanobetti and Schwartz 

(2006, 090195) 

Period of Study: 1995-1999

Location: Boston Metropolitan area 

Outcome (ICD-9): Myocardial infarction 

(410) or pneumonia (480-487)

Age Groups: 65 + yr

Study Design: Case-crossover

N: 15,578 patients admitted for MI and 

25,857 admitted for pneumonia 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, day of the 

week. 

Season: All, and also assessed for 

interaction by hot (Apr-Sep) vs.. cold 

season

Dose-response Investigated: No

Statistical Package: SAS Software 

Release 8.2 

Lags Considered: Lag 0 , and mean of 

lags 0 -1 

Pollutant: BC 

Averaging Time: 24 h 

Median (μg/m3) (IQR 5th-95th 

percentiles): 

1.15 (0.74-1.72 

0.42-2.83)

Monitoring Stations: 1 

Copollutant (correlation): 

PM2.5: r = 0.66 

NO2: r = 0.70 

CO: r = 0.82 

O3: r = -0.25 

PM non-traffic: r = -0.01 

PM Increment: Difference between the 

90th and 10th percentile for BC 

Myocardial infarction cohort (Lag 0): 

2.01 μg/m3

 

Myocardial infarction cohort (Lag 0-1): 

1.69 μg/m3

 

Pneumonia cohort (Lag 0): 2.05 μg/m3

 

Pneumonia cohort (Lag 0 -1): 

1.69 μg/m3

 

Percentage (%) increase in risk [95% 

CI]: 

Myocardial infarction cohort: 

Lag 0: 6.98 (-0.27-13.76) 

Lag 0-1: 8.34 (0.21-15.82) 

Pneumonia cohort: 

|Lag 0: 10.76 (4.54-15.89) 

Lag 0-1: 11.71 (4.79, 17.36) 

Notes: Assessed for effect modification 

by season. Results are reported in Fig 

2. Summary of results: PM2.BC is 

associated with pneumonia 

hospitalization in the cold season but 

not the hot season. BC had a stronger 

positive association with MI 

hospitalization in the cold season, but 

the confidence interval was wide. 

1

All units expressed in μg/m3 unless otherwise specified.

Table E-8. Short-term exposure-cardiovascular-ED/HA-other size fractions. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Andersen et al, (2008, 

189651) 

Period of Study: May 2001-Dec 2004

Location: Copenhagen, Denmark 

Outcome (ICD-10): CVD, including 

angina pectoris (I20), myocardial 

infarction (I21-22), other acute ischemic 

heart diseases (I24), chronic ischaemic 

heart disease (I25), pulmonary 

embolism (I26), cardiac arrest (I46), 

cardiac arrhythmias (I48-48), and heart 

failure (I50). 

RD, including chronic bronchitis 

(J41-42), emphysema (J43), other 

chronic obstructive pulmonary disease 

(J44), asthma (J45), and status 

asthmaticus (J46). 

Pediatric hospital admissions for 

asthma (J45) and status asthmaticus 

(J46). 

Age Groups: >65 yr (CVD and RD), 

5-18 yr (asthma)

Study Design: Time series

N: NR 

Statistical Analyses: Poisson GAM 

Covariates: Temperature, dew-point 

temperature, long-term trend, 

seasonality, influenza, day of the week, 

public holidays, school holidays (only 

for 5-18 yr olds), pollen (only for 

pediatric asthma outcome) 

Season: NR

Pollutant: Total number concentration 

of ultrafine and accumulation mode 

particles (NCtot) (particles/cm3

) 

Averaging Time: 24 h 

NCtotal 

Mean (SD): 8,116 (3502) 

Median: 7,358

IQR: 5,738-9,645

99th Percentile: 19,895

NCa12 

Mean (SD): 493 (315)

Median: 463

IQR: 308-650

99th Percentile: 1,263

NCa23 

Mean (SD): 2,253 (1,364)

Median: 2,057

IQR: 1,280-3,066

99th Percentile: 6,096

NCa57 

Mean (SD): 5,104 (2,687)

Median: 4,562

IQR: 3,248-6,274

99th Percentile: 14,410

NCa100 

Mean (SD): 6,847 (2,846)

Median: 6,243

IQR: 4,959-8,218

99th Percentile: 16,189

NCa212 

PM Increment: IQR increase in 

pollutant level: Nctot: 3907 particles/cm3

(IQR) 

Nca12: 342 particles/cm3

 (IQR) 

Nca23: 1786 particles/cm3

 (IQR) 

Nca57: 3026 particles/cm3 (IQR) 

NC100: 3259 particles/cm3

 (IQR) 

Nca212: 495 particles/cm3

 (IQR) 

Relative risk (RR) Estimate [CI]: CVD 

hospital admissions (4-day avg, lag 0 -

3), age 65+ 

One-pollutant model (NCtot): 

1.00 [0.99-1.02] 

Adj for PM10: 0.98 [0.96-1.01] 

Adj for PM2.5: 0.99 [0.95-1.03] 

Adj for CO: 0.99 [0.97-1.02] 

Adj for NO2: 1.01 [0.98-1.03] 

Adj for O3: 1.01 [0.96-1.06] 

One-pollutant model (NC100): 

1.00 [0.98-1.02] 

One pollutant model (Nca12): 

0.99 [.97-1.01] 

Adj for other size fractions: 

0.99 [0.97-1.02] 

One pollutant model (Nca23): 

0.99 [0.96-1.01] 

Adj for other size fractions: 

0.99 [0.96-1.02] 

One pollutant model (NCa57): 

1.01 [0.98-1.02] 

Adj for other size fractions: 

0.99 [0.97-1.02] 

One pollutant model (Nca212): 

1.02 [1.00-1.04] 

December 2009 E-130 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Dose-response Investigated: No

Statistical Package: R statistical 

software (gam procedure, mgcv 

package) 

Lags Considered: Lag 0 -5 days, 4-

day pollutant avg (lag 0 -3) for CVD, 5-

day avg (lag 0-4) for RD, and a 6-day 

avg (lag 0-5) for asthma. 

Mean (SD): 392 (441)

Median: 246

IQR: 89-584

99th Percentile: 2,248

*NC, number concentration tot, total (all 

particles 6-700 in diameter) a12, size 

mode with mean diameter of 12 nm 

a23, size mode with median diameter of 

23 nm 

a57, size mode with median diameter of 

57 nm a212 size mode with median 

diameter of 212 nm 

NC100 = a12+a23+0.797*a57+0.084*a

212. 

Monitoring Stations: 1 

Copollutant (correlation): 

Correlation of NCtot with: 

PM10: r = 0.39 

PM2.5: r = 0.40 

NO2: r = 0.68 

: r = 0.66 

NC100: r = 0.98 

NCa12: r = 0.31 

NCa23: r = 0.57 

NCa57: r = 0.87 

NCa212: r = 0.29 

CO: r = 0.54 

NOX curbside: r = 0.36 

O3: r = -0.12 

Other variables: 

Temperature: r = -0.06 

Relative humidity: r = -0.04 

Adj for other size fractions: 

1.02 [1.00-1.05] 

Adj for PM10: 0.98 [0.95-1.01] 

RD hospital admissions (5-day avg, lag 

0 -4), age 65+: One-pollutant model: 

1.04 [1.00-1.07] 

Adj for PM10: 1.00 [0.96-1.05] 

Adj for PM2.5: 0.97 [0.89-1.05] 

Adj for CO: 1.03 [0.98-1.07] 

Adj for NO2: 1.00 [0.95-1.05] 

Adj for O3: 0.95 [0.87-1.04] 

One pollutant model (NC100): 

1.03 [0.99-1.07] 

One pollutant model (Nca12): 

1.01 [0.98-1.05] 

Adj for other size fractions: 

1.01 [0.97-1.05] 

One pollutant model (Nca23): 

0.99 [0.94-1.03] 

Adj for other size fractions: 

0.98 [0.94-1.03] 

One pollutant model (Nca57): 

1.04 [1.00-1.08] 

Adj for other size fractions: 

1.02 [0.97-1.06] 

One pollutant model (Nca212): 

1.04 [1.01-1.08] 

Adj for other size fractions: 

 1.03 [0.99-1.07] 

Adj for PM10: 1.01 [0.96-1.07] 

Asthma hospital admissions (6-day avg 

lag 0-5), age 5-18: One-pollutant model: 

1.07 [0.98-1.17] 

Adj for PM10: 1.03 [0.92-1.15] 

Adj for PM2.5: 1.04 [0.85-1.28] 

Adj for CO: 1.09 [0.99-1.21] 

Adj for NO2: 1.07 [0.96-1.19] 

Adj for O3: 1.08 [0.87-1.35] 

One pollutant model (NC100): 

1.06 [0.97-1.16] 

One pollutant model (Nca212): 

1.08 [0.99-1.18] 

Adj for other size fractions: 

1.07 [0.97-1.19] 

One pollutant model (Nca23): 

1.09 [0.98-1.21] 

Adj for other size fractions: 

1.08 [0.97-1.21] 

One pollutant model (Nca57): 

1.02 [0.94-1.12] 

Adj for other size fractions: 

0.93 [0.83-1.04] 

One pollutant model (Nca212): 

1.08 [1.00-1.17] 

Adj for other size fractions: 1.12 

[1.02-1.23] 

Adj for PM10: 1.10 [0.96-1.13] 

Notes: Fig 2: Relative risks and 95% 

confidence intervals per IQR in single 

day concentration (0-5 day lag). 

Summary of Fig 2: CVD: Positive, 

marginally or statistically significant 

associations at Lag 2 (Nctot, Nca57, 

Nca212), Lag 3 (Nca212), and Lag 1 

(Nca212). RD: Positive, statistically or 

marginally significant associations at 

Lag 4 (Nctot, Nca57, NCa212) and Lag 

5 (Nctot, Nca57, Nca212), and to a 

lesser extent Lag 2 (Nctot, Nca212) and 

Lag 3 (Nctot, Nca212). Asthma: Wide 

confidence intervals make interpretation 

difficult. Positive, significant association 

for Nca212 at Lag 1.

December 2009 E-131 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lanki et al. (2006, 089788) 

Period of Study: 1992-2000

Location: Augsburg, Barcelona, 

Helsinki, Rome, and Stockholm 

Outcome (ICD-9): Acute myocardial 

infarction (410 

ICD-10: I21, I22) 

Age Groups: 35+ yr, <75 yr, 75+ yr

Study Design: Time series

N: 26,854 hospitalizations 

Statistical Analyses: GAM 

Covariates: Temperature, barometric 

pressure 

Season: Warm (Apr-Sep) and cold 

(Oct-Mar)

Dose-response Investigated: No

Statistical Package: R package mgcv 

0.9-5 

Lags Considered: 0-3 days 

Pollutant: UFP (PNC) 

Averaging Time: 24 h 

Median particles/cm3: 

Augsburg: 12,400 

Barcelona: 76,300 

Helsinki: 13,600 

Rome: 46,000 

Stockholm: 11,800 

Copollutant (correlation): 

Augsburg 

PM10: r = 0.53 

CO: r = 0.63 

NO2: r = 0.65 

O3: r = 0.26 

Barcelona: 

PM10: r = 0.38 

CO: r = 0.80 

NO2: r = 0.49 

O3: r = -0.35 

Helsinki: 

PM10: r = 0.45 

CO: r = 0.48 

NO2: r = 0.82 

O3: r = 0.01 

Rome: 

PM10: r = 0.32 

CO: r = 0.83 

NO2: r = 0.68 

O3: r = 0.03 

Stockholm: 

PM10: r = 0.06 

CO: r = 0.56 

NO2: r = 0.83 

O3: r = -0.01 

PM Increment: 10,000 particles/cm3 

Pooled Rate Ratio [CI]: All 5 cities 

(35+ yr) 

Same-day lag: 1.005 [0.996,1.015] 

1-day lag: 0.997 [0.982,1.012] 

2-day lag: 0.999 [0.990,1.008] 

3-day lag: 0.998 [0.979,1.017] 

3 cities with hospital discharge register 

(35+ yr) 

Same-day lag: 1.013 [1.000,1.026] 

1-day lag: 0.995 [0.953,1.039] 

2-day lag: 1.001 [0.989,1.014] 

3-day lag: 1.009 [0.974,1.046] 

Warm season (35+ yr) 

Same-day lag: 1.009 [0.972,1.048] 

1-day lag: 1.023 [0.988,1.060]; 

2-day lag: 1.050 [1.016,1.085] 

3-day lag: 1.022 [0.987,1.058] 

Cold season (35+ yr) 

Same-day lag: 1.014 [1.001,1.028] 

1-day lag: 1.001 [0.956,1.048] 

2-day lag: 1.001 [0.989,1.014] 

3-day lag: 1.009 [0.971,1.049] 

Age >75Non-fatal 

Same-day lag: 1.032 [1.008,1.056] 

1-day lag: 1.009 [0.985,1.032] 

2-day lag: 0.989 [0.966,1.013] 

3-day lag: 1.009 [0.969,1.051] 

Fatal 

Same-day lag: 1.016 [0.978,1.055] 

1-day lag: 1.001 [0.966,1.038] 

2-day lag: 1.005 [0.969,1.041] 

3-day lag: 0.984 [0.948,1.021] 

Notes: Rate ratios for PNC are given 

for 0-5 lag days in graph form (Fig 1) for 

each city. Pooled rate ratios were also 

provided for groups <75 yielding similar 

results to the overall 3-city data.

Reference: Metzger et al. (2004, 

044222) 

Period of Study: Aug 1998-Aug 2000

Location: Atlanta Metropolitan area 

(Georgia) 

Outcome (ICD-9): Emergency visits for 

ischemic heart disease (410-414), 

cardiac dysrhythmias (427), cardiac 

arrest (427.5), congestive heart failure 

(428), peripheral vascular and 

cerebrovascular disease (433-437, 440, 

443-444, 451-453), atherosclerosis 

(440), and stroke (436). 

Age Groups: All

Study Design: Time series

N: 4,407,535 emergency department 

visits between 1993-2000 (data not 

reported for 1998-2000) 

Statistical Analyses: Poisson 

generalized linear modeling 

Covariates: Day of the week, hospital 

entry and exit indicator variables, 

federally observed holidays, temporal 

trends, temperature, dew point 

temperature 

Season: All

Dose-response Investigated: No

Statistical Package: SAS 

Lags Considered: 3-day ma, lags 0-7 

Pollutant: UFP (10-100 nm particle 

count) (no/cm3

) 

Averaging Time: 24 h 

Median (10%-90% range): 25,900 

(11,500-74,600) 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10: r = -0.13 

O3: r = -0.13 

NO2: r = 0.26 

CO: r = 0.10 

SO2: r = 0.24 

PM2.5: r = -0.16 

PM2.5 water soluble metals: r = -0.27 

PM2.5 sulfates: r = -0.31; 

PM2.5 acidity: r = -0.39; 

PM2.5 OC: r = 0.08; 

PM2.5 EC: r = 0.08; 

PM2.5 oxygenated hydrocarbon: r = 0.05

Other variables: 

Temperature: r = -0.33 

Dew point: r = -0.41 

PM Increment: 30,000 no/cm3

(approximately 1 SD)3 

RR [95% CI]: For 3 day ma: All CVD: 

0.985 [0.965, 1.005] 

Dysrhythmia: 0.972 [0.937, 1.008] 

Congestive heart failure: 0.983 

[0.943-1.025] 

Ischemic heart disease: 0.989 

[0.953-1.026] 

Peripheral vascular and 

cerebrovascular disease: 0.998 

[0.960-1.039] 

Results for Lags 0-7 expressed in 

figures (see notes). 

Notes: Fig 1: RR (95% CI) for singleday lag models for the association of 

ER visits for CVD with daily ambient 

UFP. 

Summary of Fig 1 results: Null or 

negative associations. 

December 2009 E-132 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: von Klot et al. (2005, 

088070) 

Period of Study: 1992-2001

Location: 

Augsburg, Germany 

Barcelona, Spain 

Helsinki, Finland 

Rome, Italy 

Stockholm, Sweden 

Outcome (ICD-9): Acute myocardial 

infarction (410 

ICD-10: I21-I22), angina pectoris (411, 

413 

ICD-10: I20, I24), dysrhythmia (427 

ICD-10: I46.0, 46.9, I47-I49, R00.1, 

R00.8), heart failure (428 

ICD-10: 150) 

Age Groups: 35+ yr

Study Design: Cohort

N: 22,006 MI survivors 

Statistical Analyses: GAM, Spearman 

correlation 

Covariates: Temperature, dew point 

temp, avg barometric pressure, relative 

humidity 

Season: NR

Dose-response Investigated: No

Statistical Package: R-software with 

“mgcv” package 

Lags Considered: 0-3 days 

Pollutant: UFP (PNC) 

Averaging Time: 24 h 

Mean particle/cm3 (5th-95th 

percentile): 

Augsburg: 

Barcelona: 

Helsinki: 

Rome: 

Stockholm: 

Monitoring Stations: NR 

Copollutant (correlation): 

Augsburg 

PM10: r = 0.52 

CO: r = 0.63 

NO2: r = 0.64 

O3: r =-0.32 

Barcelona 

PM10: r = 0.29 

CO: r = 0.71; 

NO2: r = 0.44 

O3: r =-0.55 

Helsinki 

PM10: r = 0.46 

CO: r = 0.47; 

NO2: r = 0.83 

O3: r =-0.16 

Rome 

PM10: r = 0.33 

CO: r = 0.80; 

NO2: r = 0.71 

O3: r =-0.47 

Stockholm 

PM10: r = 0.06 

CO: r = 0.54; 

NO2: r = 0.80 

O3: r =-0.17 

PM Increment: 10,000 particles/cm3

 Pooled RR Estimate [CI]: 

All cardiac admissions: 1.026 

[1.005,1.048] 

Myocardial infarction: 1.039 

[0.998.1.082] 

Angina pectoris: 1.020 [0.992,1.048] 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-133 
E.2.Short-Term Exposure and Respiratory Outcomes 

E.2.1. Respiratory Morbidity Studies 

Table E-9. Short-term exposure-respiratory morbidity outcomes -PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Aekplakorn, et al. (2003, 

089908) 

Period of Study: 107 days, 

from Oct 1997-Jan 1998 

Location: Mae Mo district, Lampang 

Province, North Thailand 

Outcome: Upper respiratory symptoms, 

lower respiratory symptoms, cough 

Age Groups: 6-14 yr old 

Study Design: Logistic regression 

N: 98 asthmatic school children, 98 

non-asthmatic school children 

Statistical Analyses: GEE, stratified 

analysis, PROC GENMOD 

Covariates: Temperature and relative 

humidity 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: SAS v 8.1 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD): 

Sob Pad station: 31.92 

Sob Mo station: 33.64 

Hua Fai station: 37.45 

Range (Min, Max): 

Sob Pad: 6.63, 153.25 

Sob Mo: 4.23, 121.80 

Hua Fai: 6.98, 113.30 

Monitoring Stations: 3 

Copollutant: PM2.5, SO2 

PM Increment: 10 μg/m3

Odds Ratios [Lower CI, Upper CI] 

lag: 

Asthmatics: URS: 1.03 (0.99, 1.07) 

lag 0 

LRS: 1.04 (0.99, 1.09) 

lag 0 

Cough: 1.04 (1.00, 1.07) 

lag 0 

Non-Asthmatics: URS: 1.04 (0.99, 1.08)

lag 0 

LRS: 1.0 (0.93, 1.07) 

lag 0 

Cough: 0.99 (0.94, 1.05) 

lag 0 

PM10 + SO2

Asthmatics: URS: 1.03 (0.99, 1.07) 

lag 0 

LRS: 1.03 (0.98, 1.09) 

lag 0 

Cough: 1.04 (1.00, 1.08) 

lag 0 

Non-Asthmatics: URS: 1.04 (0.99, 1.08)

lag 0 

LRS: 1.0 (0.93, 1.07) 

lag 0 

Cough: 0.99 (0.95, 1.05) 

lag 0 

December 2009 E-134 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Andersen et al. (2008, 

189651) 

Period of Study: 

Dec 1998-Dec 2004

Location: Copenhagen, Denmark 

Outcome: Daily symptoms (prospective 

daily recording of symptoms via diary) 

Age Groups: 0-3 yr

Study Design: Panel study of children 

with genetic susceptibility to asthma 

(mothers had asthma)

N: 205 children (living within a 15km 

radius of the central monitor during the 

first 3 yr of life) 

born between Aug 2, 1998 and Dec 12, 

2001 

Statistical Analyses: Logistic 

regression model (GEE) 

Covariates: Temperature, season, 

gender, age, exposure to smoking, and 

paternal history of asthma 

Effect modification: gender, medication 

use, and paternal history of asthma

Statistical Package: SAS v9.1 

Lag: 0,1,2,3,4,2-4 

Pollutant: PM10

Mean: 25.1 

SD: 16.7 

Percentiles: 

25th: 15.7 

75th: 30.2 

IQR: 14.5 

Copollutant (correlation): 

PM2.5 (r = 0.79) 

Number concentration of ultrafine 

particles, 

UFP (r = 0.37) 

NO2 (r = 0.43) 

NOX (r = 0.40) 

CO (r = 0.45) 

O3 (r = -0.32) 

Temp (r = 0.25) 

PM Increment: IQR (14.5 μg/m3) 

increase 

Odds Ratios (95%CI) for incident 

wheezing symptoms 

Age 0-1 

L0: 1.05 (0.88, 1.25) 

L1: 1.00 (0.82, 1.22) 

L2: 1.01 (0.83, 1.23) 

L3: 1.20 (0.98, 1.46) 

L4: 1.23 (1.02, 1.48) 

L2-4: 1.21 (0.99, 1.48) 

Age 1-2 

L0: 1.00 (0.86, 1.15) 

L1: 1.02 (0.87, 1.19) 

L2: 1.05 (0.93, 1.19) 

L3: 0.96 (0.84, 1.09) 

L4: 1.04 (0.90, 1.21) 

L2-4: 1.03 (0.88, 1.22) 

Age 2-3 

L0: 0.87 (0.72, 1.06) 

L1: 0.95 (0.78, 1.15) 

L2: 0.99 (0.82, 1.17) 

L3: 1.03 (0.84, 1.25) 

L4: 0.89 (0.74, 1.09) 

L2-4: 0.94 (0.74, 1.19) 

Age 0-3 

L0: 0.97 (0.87, 1.08) 

L1: 0.99 (0.89, 1.10) 

L2: 1.01 (0.92, 1.12) 

L3: 1.03 (0.93, 1.14) 

L4: 1.04 (0.94, 1.15) 

L2-4: 1.04 (0.92, 1.17) 

Two pollutant models (lag 2-4) 

1-pollutant model: 1.21 (0.99, 1.48) 

2-pollutant (adj for NO2): 1.13 (0.88, 

1.45) 

2-pollutant (adj for ): 1.16 (0.90, 1.48) 

2-pollutant (adj for CO): 1.23 (0.96, 

1.57) 

110 children living within 5km radius 

from monitor (sensitivity analysis): Age 

0-1: 1.32 (0.95, 1.82) 

Age 1-2: 1.20 (0.87, 1.67) 

Age 2-3: 0.78 (0.52, 1.16) 

Age 0-3: 1.11 (0.88, 1.39) 

December 2009 E-135 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Boezen et al. (2005, 

087396) 

Period of Study: Two consecutive 

winters (winter 1993-winter 1995)

Location: Rural (Meppel, Nunspeet) 

and urban (Amsterdam) areas in the 

Netherlands 

Outcome: FEV1, airway 

hyperresponsiveness (AHR), serum 

total IgE and daily data on lower 

respiratory symptoms (LRS), upper 

respiratory symptoms (URS), cough 

and morning and evening peak 

expiratory flow 

Age Groups: 50-70 yr 

Study Design: Case-control study

N: 327 patients 

Statistical Analyses: Logistic 

regression 

Covariates: daily minimum 

temperature, linear, quadratic and cubic 

time trend, weekend/holidays, and 

influenza incidence for the rural and 

urban areas and two winters separately 

Season: winter 

Dose-response Investigated? No 

Lags Considered: 0, 1, 2, and 5-day 

mean 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Winter 93/94 Urban: 41.5 

Winter 93/94 Rural: 44.1 

Winter 94/95 Urban: 31.1 

Winter 94/95 Rural: 26.6 

Percentiles: 50th(Median): 

Winter 93/94 Urban: 34.6 

Winter 93/94 Rural: 30.4 

Winter 94/95 Urban: 28.9 

Winter 94/95 Rural: 23.7 

Range (Min, Max): 

93/94 Urban: (12.1-112.7) 

93/94 Rural: (7.9-242.2) 

94/95 Urban: (8.8-89.9) 

94/95 Rural: (7.1-96.9) 

Copollutant: 

SO2 

NO2

BS 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

AHR-/IgEUpper Respiratory Symptoms 

Lag 0: OR = 0.99 (0.97-1.01) 

Lag 1: OR = 1.01 (0.99-1.03) 

Lag 2: OR = 1.00 (0.96-1.02) 

5-day mean: OR = 1.00 (0.96-1.04) 

Cough 

Lag 0: OR = 1.00 (0.99-1.02) 

Lag 1: OR = 0.99 (0.98-1.01) 

Lag 2: OR = 1.00 (0.98-1.01) 

5-day mean: OR = 0.98 (0.95-1.01) 

>10% fall in morning peak expiratory 

flow 

Lag 1: OR = 1.01 (0.98-1.04) 

Lag 2: OR = 0.97 (0.94-1.00) 

5-day mean: OR = 0.97 (0.92-1.02) 

AHR-/IgE+ 

Upper Respiratory Symptoms 

Lag 0: OR = 1.01 (0.99-1.03) 

Lag 1: OR = 1.02 (1.00-1.04) 

Lag 2: OR = 1.01 (0.99-1.03) 

5-day mean: OR = 1.08 (1.04-1.11) 

Cough 

Lag 0: OR = 1.01 (0.99-1.03) 

Lag 1: OR = 0.99 (0.98-1.01) 

Lag 2: OR = 1.00 (0.98-1.02) 

5-day mean: OR = 1.01 (0.97-1.05) 

>10% fall in morning peak expiratory 

flow 

Lag 1: OR = 0.99 (0.97-1.02) 

Lag 2: OR = 0.99 (0.97-1.02) 

5-day mean: OR = 0.97 (0.93-1.01) 

AHR+/IgEUpper Respiratory Symptoms 

Lag 0: OR = 0.99 (0.95-1.03) 

Lag 1: OR = 1.01 (0.97-1.05) 

Lag 2: OR = 0.99 (0.96-1.03) 

5-day mean: OR = 0.98 (0.91-1.06) 

Cough 

Lag 0: OR = 1.00 (0.97-1.02) 

Lag 1: OR = 1.01 (0.98-1.03) 

Lag 2: OR = 0.99 (0.96-1.02) 

5-day mean: OR = 1.02 (0.96-1.08) 

>10% fall in morning peak expiratory 

flow 

Lag 1: OR = 0.99 (0.95-1.03) 

Lag 2: OR = 0.99 (0.95-1.03) 

5-day mean: OR = 0.99 (0.93-1.06) 

AHR+/IgE+ 

Upper Respiratory Symptoms 

Lag 0: OR = 1.01 (0.98-1.04) 

Lag 1: OR = 1.03 (1.00-1.05) 

Lag 2: OR = 1.02 (0.99-1.05) 

5-day mean: OR = 1.06 (1.00-1.11) 

Cough 

Lag 0: OR = 1.03 (1.01-1.06) 

Lag 1: OR = 1.00 (0.98-1.02) 

Lag 2: OR = 0.99 (0.97-1.01) 

5-day mean: OR = 0.99 (0.95-1.04) 

Lag 2: OR = 0.99 (0.96-1.03) 

5-day mean: OR = 0.99 (0.92-1.05) 

>10% fall in morning peak expiratory 

flow 

Lag 1: OR = 1.04 (1.00-1.07) 

Lag 2: OR = 1.03 (0.99-1.06) 

5-day mean: OR = 1.05 (0.99-1.11) 

Reference: Boezen et al. (1999, 

040410) 

Periods of Study: 

3 Winters (1992-1995)

Location: Urban and rural areas of the 

Netherlands 

Outcome: Respiratory symptoms 

Lower respiratory symptoms (wheeze, 

attacks of wheezing, shortness of 

breath) 

Upper respiratory symptoms (sore 

throat, runny or blocked nose) 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Winter 1992-93 

Urban: 54.8 

Rural: 44.7 

Winter 1993-94 

Increment: 100 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

OR for respiratory symptoms and 

exposure to PM10 in children with BHR 

and high serum total IgE 

Lower Respiratory Symptoms 

1.32 (1.07, 1.63) 0 

December 2009 E-136 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Bronchial hyperresponsiveness (BHR) 

Study Design: Time-series 

Statistical Analyses: Logistic 

regression (PROC model) 

Age Groups: 7-11 

Urban: 41.5 3 

Rural: 44.1 

Winter 1994-95 

Urban: 31.1 

Rural: 26.6 

Range (Min, Max): 

Winter 1992-93 

Urban: (4.7, 145.6) 

Rural: (4.8, 103.8) 

Winter 1993-94 

Urban: (12.1, 112.7) 

Rural: (7.9, 242.2) 

Winter 1994-95 

Urban: (8.8, 89.9) 

Rural: (7.1, 96.9) 

Copollutants: 

BS 

SO2 

NO2

1.36 (1.13, 1.64) 1 

1.36 (1.13, 1.65) 2 

2.39 (1.71, 3.35) 0-5 avg. 

Upper Respiratory Symptoms 

1.13 (0.97, 1.32) 0 

1.00 (0.87, 1.16) 1 

0.96 (0.84, 1.11) 2 

0.91 (0.70, 1.18) 0-5 avg 

>10% morning peak expiratory flow 

(PEF) decrease 

1.10 (0.92, 1.33) 0 

1.08 (0.90, 1.28) 1 

1.03 (0.87, 1.23) 2 

1.10 (0.83, 1.46) 0-5 avg 

>10% evening peak expiratory flow 

(PEF) increase 

1.37 (1.16, 1.63) 0 

1.09 (0.92, 1.29) 1 

1.16 (0.98. 1.36) 2 

1.35 (1.04, 1.77) 0-5 avg. 

OR for respiratory symptoms and 

exposure to PM10 in children without 

BHR and low serum total IgE 

Lower Respiratory Symptoms 

1.08 (0.75, 1.57) 0 

1.04 (0.70, 1.53) 1 

0.98 (0.69, 1.39) 2 

1.15 (0.61, 2.15) 0-5 avg. 

Upper Respiratory Symptoms 

1.12 (0.99, 1.28) 0 

1.01 (0.89, 1.15) 1 

1.01 (0.89, 1.15) 2 

0.93 (0.67, 1.28) 0-5 avg 

>10% morning PEF decrease 

1.07 (0.93, 1.23) 0 

0.86 (0.75, 0.99) 1 

0.97 (0.85, 1.11) 2 

0.99 (0.79, 1.23) 0-5 avg 

>10% evening PEF decrease 

1.13 (0.98, 1.30) 0 

1.05 (0.91, 1.21) 1 

0.99 (0.87, 1.14) 2 

0.94 (0.75, 1.17) 0-5 avg 

OR for respiratory symptoms and 

exposure to PM10 in children with BHR 

and low serum total IgE 

Lower Respiratory Symptoms 

0.77 (0.48, 1.24) 0 

1.34 (0.94, 1.93) 1 

1.24 (0.86, 1.81) 2 

1.92 (0.84, 4.41) 0-5 avg 

Upper Respiratory Symptoms 

1.13 (0.92, 1.40) 0 

0.98 (0.79, 1.22) 1 

0.97 (0.79, 1.20) 2 

0.83 (0.54, 1.25) 0-5 avg 

>10% morning PEF decrease 

1.04 (0.78, 1.38) 0 

0.86 (0.66, 1.12) 1 

0.91 (0.71, 1.17) 2 

0.78 (0.51, 1.20) 0-5 avg 

>10% evening PEF decrease 

1.07 (0.82, 1.41) 0 

0.98 (0.76, 1.26) 1 

0.93 (0.73, 1.19) 2 

0.83 (0.55, 1.26) 0-5 avg 

OR for respiratory symptoms and 

exposure to PM10 in children without 

BHR and high serum total IgE 

Lower Respiratory Symptoms 

1.04 (0.80, 1.35) 0 

1.21 (0.98, 1.51) 1 

1.18 (0.96, 1.45) 2 

1.35 (0.89, 2.04) 0-5 avg 

Upper Respiratory Symptoms 

1.01 (0.85, 1.20) 0 

0.95 (0.81, 1.12) 1 

0.93 (0.80, 1.09) 2 

December 2009 E-137 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0.93 (0.69, 1.25) 0-5 avg 

>10% morning PEF decrease 

0.97 (0.80, 1.17) 0 

1.09 (0.91, 1.30) 1 

1.02 (0.85, 1.21) 2 

0.95 (0.71, 1.28) 0-5 avg 

>10% evening PEF decrease 

1.02 (0.85, 1.22) 0 

1.06 (0.90, 1.25) 1 

1.08 (0.93, 1.27) 2 

1.04 (0.80, 1.34) 0-5 avg. 

Reference: Chattopadhyay et al. (2007, 

147471) 

Period of Study: NR

Location: Three different points in 

Kolkata, India: North, South, and 

Central 

Outcome: pulmonary function tests 

(respiratory impairments) 

Age Groups: All ages

Study Design: Cross-sectional

N: 505 people studied for PFT 

total population of Kolkata not given 

Statistical Analyses: Frequencies 

Covariates: Meteorologic data (i.e. 

temperature, wind direction, wind 

speed, and humidity) 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 8 h 

Mean (SD): 

North Kolkata: 535.9 

Central Kolkata: 1114.5 

South Kolkata: 909.2 

Monitoring Stations: 1 

Copollutant: 

PM<10-3.3 

PM<3.3-0.4 

PM Increment: NR 

Respiratory impairments (SD): 

North Kolkata 

Male (n = 137) 

Restrictive: 4 (2.92) 

Obstructive: 5 (3.64) 

Combined Res. And Obs.: 6 (4.37) 

Total: 15 (10.95) 

Female (n = 152) 

Restrictive: 3 (1.97) 

Obstructive: 5 (3.28) 

Combined Res. And Obs.: N/A 

Total: 8 (5.26) 

Total (n = 289) 

Restrictive: 7 (2.42) 

Obstructive: 10 (3.46) 

Combined Res. And Obs: 6 (2.07) 

Total: 23 (7.96) 

Central Kolkata 

Male (n = 44) 

Restrictive: 6 (13.63) 

Obstructive: 1 (2.27) 

Combined Res. And Obs.: 1 (2.27) 

Total: 8 (18.18) 

Female (n = 50) 

Restrictive: 3 (6.00) 

Obstructive: 2 (4.00) 

Combined Res. And Obs.: N/A 

Total: 5 (10.00) 

Total (n = 94) 

Restrictive: 9 (9.57) 

Obstructive: 3 (3.19) 

Combined Res. And Obs.: 1 (1.06) 

Total: 13 (13.82) 

South Kolkata 

Male (n = 52) 

Restrictive: 1 (1.92) 

Obstructive: 2 (3.84) 

Combined Res. And Obs.: 3 (5.76) 

Total: 6 (11.53) 

Female (n = 70) 

Restrictive: 2 (2.85) 

Obstructive: 1 (1.42) 

Combined Res. And Obs.: N/A 

Total: 3 (4.28) 

Total (n = 122) 

Restrictive: 3 (2.45) 

Obstructive: 3 (2.45) 

Combined Res. And Obs.: 3 (2.45) 

Total: 9 (7.37) 

December 2009 E-138 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dales et al. (2006, 090744) 

Period of Study: Jan 1986-Dec 2000

Location: 11 Canadian Cities: Calgary, 

Edmonton, Halifax, London, Hamilton, 

Ottawa, St. John, Toronto, Vancouver, 

Windsor, Winnipeg 

Health Outcome: Respiratory Illness: 

Asphyxia (799) 

Respiratory failure (799.1) 

Dyspnea and respiratory abnormalities 

(786) 

Respiratory distress syndrome (769) 

Unspecified birth asphyxia in live-born 

infant (768.9) 

Other respiratory problems after birth 

(770.8) 

Pneumonia (486)

Study Design: Time-series 

Statistical Analyses: Poisson 

Age Groups: 0-27 days 

Pollutant: PM10

Averaging Time: 24-h avg 

Copollutants (correlation): 

O3: r = -0.29 to 0.41 

NO2: r = -0.26 to 0.69 

SO2: r = -0.09 to 0.61 

CO: r = -0.13 to 0.71 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) Lag: 

In respiratory illness and exposure to 

PM10 in neonates 

PM10 alone: 2.13 (-0.50, 4.76) 

Multipollutant model 

PM10: 1.45 (-1.90, 4.80) 

PM10, O3: 2.67 (0.98, 4.39) 

PM10, NO2: 2.48 (1.18, 3.80) 

PM10, SO2: 1.41 (0.35, 2.47) 

PM10, CO: 1.30 (0.13, 2.49) 

Reference: de Hartog et al. (2003, 

001061) 

Period of Study: Winter of 1998-1999 

Amsterdam, from Nov 1998 to Jun 1999 

Erfurt, from Oct 1998 to Apr 1999 

Helsinki, from Nov 1998 to Apr 1999

Location: 

Amsterdam, the Netherlands; 

Erfurt, Germany; Helsinki, Finland 

Outcome: Respiratory symptoms 

Age Groups: ≥ 50 yr

Study Design: Panel

N: 131 subjects with history of coronary 

heart disease 

Statistical Analyses: Logistic 

regression 

Covariates: Ambient temperature, 

relative humidity, atmospheric pressure, 

incidence of influenza-like illness 

Season: Winter 

Dose-response Investigated? No

Statistical Package: S-PLUS 2000 

Lags Considered: 0-, 1-, 2-, 3-, and 

5-day avg 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Amsterdam: 36.5 

Erfurt: 27.1 

Helsinki: 19.6 

Range (Min, Max): 

Amsterdam: (13.6-112.0) 

Erfurt: (5.2-104.2) 

Helsinki: (6.4-67.4) 

Monitoring Stations: 1 

Copollutant: 

PM2.5

NC0.01-0.1

CO 

NO2

SO2 

‘There was a tendency toward positive 

associations between avoidance of 

activities and both particulate air 

pollution (PM10) and gases, but none of 

the associations were statistically 

significant....In both incidence analyses 

and prevalence analyses, odds ratios 

for PM10 were generally similar to the 

corresponding odds ratios for PM2.5, but 

were somewhat less significant.’ 

Reference: Delfino et al. (1998, 

051406) 

Period of Study: Aug-Oct 1995

Location: Alpine, CA 

Outcome: asthma symptom severity 

Age Groups: 9-17

Study Design: Panel Study

N: 24 non-smoking pediatric asthmatics 

Statistical Analyses: GEE 

Covariates: Day of week, temperature, 

humidity, wind speed

Statistical Package: SAS 

Lags Considered: 0-5, 0, 0-4 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

31 (8) 

90th: 42 

Range (Min, Max): 16, 54 

Copollutant (correlation): 

O3 (r = 0.32) 

PM Increment: 42 μg/m3 (90th 

percentile increase) 

Asthma symptoms: 

Everyone: 1.47 (0.90, 2.39) lag 0 

Everyone: 1.73 (1.03, 2.89) lag 0-4 

Less symptomatic: 2.47 (1.23-4.95) 

lag 0 

Less symptomatic: 4.03 (1.22, 13.33) 

lag 0-4 

More symptomatic: 1.50 (0.80, 2.80) 

lag 0 

More symptomatic: 1.95 (1.12, 3.43) 

lag 0-4 

PM10 + O3

Asthma symptoms: 1.31 (0.84, 2.06) 

lag 0 

1.65 (1.03, 2.66) lag 0-4 

Less symptomatic: 2.08 (1.12-3.83) 

lag 0 

Less symptomatic: 3.35 (1.06, 10.51) 

lag 0-4 

More symptomatic: 1.40 (0.77, 2.53) 

lag 0 

More symptomatic: 1.87 (1.11, 3.13) 

lag 0-4 

December 2009 E-139 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2002, 

093740) 

Period of Study: Mar-Apr 1996

Location: Alpine, California 

(a semi-rural area) 

Outcome: Asthma symptoms that 

interfere with daily activities 

Age Groups: 9-19 yr

Study Design: Daily panel study

N: 22 asthmatic children 

Statistical Analyses: GEE 

Covariates: Temperature, relative 

humidity, day-of-week trends, linear 

time trend across the 61 days, and 

upper or lower respiratory infection 

Season: “Early spring season” of 

Mar-Apr 

Dose-response Investigated? Yes

Statistical Package: SAS, version 8 

Lags Considered: 0-, 1-, 2-, 3-, 4-, 5-, 

and 3-day ma 

 Pollutant: PM10

Averaging Time: 1 h max 

Mean (SD): 38(15) 

Percentiles: 90th: 63 

Range (Min, Max): (12-69) 

Averaging Time: 8 h max 

Mean (SD): 28(12) 

Percentiles: 90th: 46 

Range (Min, Max): (8-57) 

Averaging Time: 24 h 

Mean (SD): 20(9) 

Percentiles: 90th: 32 

Range (Min, Max): (7-42) 

Copollutant (correlation): 

1 h max PM10 

8 h max PM10: r = 0.93 

24 h PM10: r = 0.84 

1 h max O3: r = 0.68 

8 h max O3: r = 0.95 

1 h max NO2: r = 0.49 

8 h max NO2: r = 0.55 

8 h max PM10: 1 h max PM10: r = 0.93 

24 h PM10: r = 0.95 

1 h max O3: r = 0.72 

8 h max O3: r = 0.65 

1 h max NO2: r = 0.48 

8 h max NO2: r = 0.55 

24 h PM10: 1 h max PM10: r = 0.84 

8 h max PM10: r = 0.95 

1 h max O3: r = 0.74 

8 h max O3: r = 0.71 

1 h max NO2: r = 0.37 

8 h max NO2: r = 0.44 

PM Increment: 90th percentile 

increase 

Effect Estimate [Lower CI, Upper CI]: 

ORs for risk of asthma symptoms in 

those who report a respiratory infection 

compared to those who do not have a 

respiratory infection 

1 h max PM10 lag 0: 4.88 (1.31-18.2) 

8 h max PM10 lag 0: 6.78 (1.38-33.3) 

24 h mean PM10 lag 0: 4.68 (0.71-30.7) 

3-day ma 1 h max PM10: 11.1 (1.10-112)

3-day ma 8 h max PM10: 10.1 (1.42-

72.0) 

3-day ma 24 h PM10: 2.67 (0.60-11.8) 

Effect modification by anti-inflammatory 

medication use on the relationship of 

asthma symptoms in children 

1 h max PM10 lag 0: 1.41 (0.87-2.30) 

On medication: 0.96 (0.25-3.69) 

Not on medication: 1.92 (1.22-3.02) 

8 h max PM10 lag 0: 1.19 (0.74-1.94) 

On medication: 0.75 (0.18-3.04) 

Not on medication: 1.68 (0.91-3.09) 

24 h mean PM10 lag 0: 1.08 (0.73-1.61) 

On medication: 0.80 (0.24-2.69) 

Not on medication: 1.35 (0.82-2.22) 

3-day ma 1 h max PM10: 1.45 (0.76-

2.76) 

On medication: 1.01 (0.14-7.02) 

Not on medication: 1.92 (0.99-3.71) 

3-day ma 8 h max PM10: 1.32 (0.76-

2.29) 

On medication: 0.82 (0.17-3.94) 

Not on medication: 1.89 (1.10-3.24) 

3-day ma 24 h PM10: 1.22 (0.84-1.77) 

On medication: 0.75 (0.26-2.14) 

Not on medication: 1.75 (1.15-2.68) 

Dose-response results are found in Fig 

2 and not quantitatively reported 

elsewhere. 

Reference: Delfino et al. (2003, 

090941) 

Period of Study: Nov 1999-Jan 2000

Location: 

Huntington Park, Los Angeles 

Outcome: Asthma severity scale 

Peak Expiratory Flow Rate (PEF) 

Age Groups: Ages 10 to 16

Study Design: Longitudinal study panel

N: 22 children 

Statistical Analyses: Regression 

analysis (GEE, GLM) 

multivariate regression models 

Covariates: Day of the week, Maximum 

Temperature, Respiratory Infections 

Season: Winter 

Dose-response Investigated? No

Statistical Package: SAS 

Lags Considered: 0, 1 

Pollutant: PM10

Mean (SD): 59.9 (24.7) 

Range (Min, Max): 20-126 

IQR: 37 

90th: 86.0 

Monitoring Stations: 1 

Copollutant (correlation): 

8-h max NO2 = 0.38 

8-h max O3 = -0.16 

8-h max CO = 0.50 

8-h max SO2 = 0.73 

PM Increment: IQR 37.0 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 

Lag 0 

Symptom Scores >1: 1.45 (1.11, 1.90) 

Symptom Scores >2: NR 

Lag 1 

Symptom Scores >1: 1.07 (0.64, 1.77) 

Symptom Scores >2: NR 

December 2009 E-140 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2004, 

056897) 

Period of Study: Sep-Oct 1999 

Apr-Jun 2000

Location: Alpine, California 

Outcome: FEV1

Age Groups: 9-19 yr old 

Study Design: Panel study 

N: 24 children 

Statistical Analyses: GLM 

Akaike’s information criterion and 

Bayesian information criterion 

Covariates: Day of week, Personal 

temperature and relative humidity, time 

of FEV1 maneuver (morning, afternoon, 

or evening), Season (fall 1999 or spring 

2000) 

As-needed medication use 

Presence or absence of upper or lower 

respiratory infections 

Season: Spring, Fall 

Dose-response Investigated? No

Statistical Package: SAS 

Lags Considered: Lag 0-4 

Pollutant: PM10

Averaging Time: 4 h, 8 h, 12 h, 24 h 

Personal Monitor 

1-h max personal PM last 

24-h 

Mean (SD): 151.0 (12.03) 

90th: 292.4 

Range (Min, Max): (9.1, 996.8) 

Mean personal PM last 24-h 

Mean (SD): 37.9 (19.9) 

90th: 65.1 

Range (Min, Max): 

(3.9, 113.8) 

Central outdoor stationary-site PM 

1-h Maximum TEOM 

PM10 last 24-h 

Mean (SD): 54.4 (13.8) 

90th: 71.0 

Range (Min, Max): (24.4, 95.4) 

Mean TEOM PM10 last 24-h 

Mean (SD): 29.7 (8.6) 

90th: 40.9 

Range (Min, Max): (12.9, 50.7) 

24-h mean PM10

Mean (SD): 23.6 (9.1) 

90th: 34.6 

Range (Min, Max): (3.2, 48.0) 

Copollutant (correlation): 8-h max 

personal PM 

8-h max O3 = 0.03 

8-h Max NO2 = 0.26 

24-h Mean Personal 

PM = 0.94 

8-h Max TEOM PM10 = 0.38 

24-h Mean TEOM PM10 = 0.40 

24-h Central HI PM10 = 0.37 

24-h Central HI PM2.5 = 0.38 

24-h Outdoor HI PM10 = 0.32 

24-h Outdoor HI PM2.5 = 0.39 

24-h Indoor HI PM10 = 0.23 

24-h Indoor HI PM2.5 = 0.37 

24-h mean personal PM 

8-h max O3 = 0.01 

8-h Max NO2 = 0.27 

8-h Max Personal PM = 0.94 

8-h Max TEOM PM10 = 0.36 

24-h Mean TEOM PM10 = 0.39 

24-h Central HI PM10 = 0.36 

24-h Central HI PM2.5 = 0.43 

24-h Outdoor HI PM10 = 0.34 

24-h Outdoor HI PM2.5 = 0.44 

24-h Indoor HI PM10 = 0.29 

24-h Indoor HI PM2.5 = 0.46 

24-h Mean TEOM PM10

8-h max O3 = 0.41 

8-h Max NO2 = 0.58 

8-h Max Personal PM = 0.40 

24-h Mean Personal PM = 0.39 

8-h Max TEOM PM10 = 0.92 

24-h Central HI PM10 = 0.86 

24-h Central HI PM2.5 = 0.78 

24-h Outdoor HI PM10 = 0.79 

24-h Outdoor HI PM2.5 = 0.78 

24-h Indoor HI PM10 = 0.36 

24-h Indoor HI PM2.5 = 0.59 

Results presented graphically: Percent 

predicted FEV1 was inversely 

associated with personal exposure to 

fine particles. 

- Inverse associations of FEV1 with 

stationary-site indoor, outdoor and 

central-site gravimetric PM2.5 and PM10, 

and with hourly TEOM PM10

December 2009 E-141 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2006, 

090745) 

Period of Study: Region 1: Aug to Mid 

Dec 2003. Region 2: Jul through Nov 

2004

Location: Region 1: Riverside, CA. 

Region 2: Whittier, CA 

Outcome: Fractional Concentration of 

Nitric Oxide in exhaled air (FENO) 

Age Groups: 9 through 18

Study Design: Longitudinal Panel 

Study

N: 45 children 

Statistical Analyses: Linear mixedeffects models 

Two-stage hierarchical model 

Empirical Variograms 

Fourth-order polynomial distributed lag 

mixed-effects model 

Covariates: Personal temperature, 

Personal Rel. Humid., 10-day exposure 

run, Respiratory infections, Region of 

study, Sex, Cumulative daily use of asneeded B-agonist inhalers 

Dose-response Investigated? No 

Lags Considered: Lag 0, Lag 1, 2-day 

ma 

Pollutant: PM10

Central Site 

Averaging Time: 24 h 

Riverside 

Mean (SD): 70.82 (29.36) 

50th(Median): 65.96 

Range (Min, Max): (30.75,54.05) μg/m3

Whittier 

Mean (SD): 35.73 (16.6) 

50th(Median): 34.65 

Range (Min, Max): 

(5.86, 105.46) μg/m3

Monitoring Stations: 48 personal 

nephelometers, 2 central sites 

PM Increment: IQR increase 

(Riverside: 28.41 μg/m3

, Whittier 

21.87 μg/m3) 

Coefficient [Lower CI, Upper CI] 

lag: Lag = 2-day ma 

Stratified by Medication Use 

Not Taking Anti-Inflamm. Medication 

Central 0.76 (-1.54, 3.07) 

Taking Anti-Inflamm. Medication 

Central 0.53 (-0.83, 1.90) 

Inhaled Corticosteroids 

Central 1.28 (-0.01, 2.58) 

Antileukotrienes +- inhaled 

corticosteroids 

Central -2.10 (-5.33, 1.12) 

Notes: Fig of Estimated lag effect of 

hourly personal PM2.5 on FENO. 

Fig of the Estimated lag effect of hourly 

personal PM2.5 on FENO by use of 

medications. 

Fig of one- and two-pollutant models for 

change in FENO using 2-day Ma 

personal and central-site pollutant 

measurements. 

December 2009 E-142 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Desqueyroux et al. (2002, 

026052) 

Period of Study: Nov 1995-Nov 1996

Location: Paris, France 

Outcome: Asthma attacks 

Age Groups: Adults. 

Study Design: Panel study

N: 60 moderate to severe adult 

asthmatics 

Statistical Analyses: Marginal logistic 

regression 

Covariates: FEV1, smoking, allergy, 

oral steroid treatment, mean daily 

temperature, relative humidity, pollen 

counts, season, holiday period 

Season: winter, summer 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 1, 2, 3, 4, 5, 3-5 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Summer: 23 (9) 

Winter: 28 (14) 

Range (Min, Max): 

Summer: 6, 63 

Winter: 9, 84 

Monitoring Stations: 7 

Copollutant: SO2 , NO2, O3

PM Increment: 10 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 0.87 [0.71, 1.06] lag 1 

0.93 [0.80, 1.08] lag 2 

1.11 [0.98, 1.26] lag 3 

1.17 [1.03, 1.33] lag 4 

1.16 [1.01, 1.34] lag 5 

1.21 [1.01, 1.34] lag 3-5 

Vs seasons alone: 

Winter: 1.41 [1.16, 1.71] lag 3-5 

Summer: 1.03 [0.72, 1.47] lag 3-5 

Vs link to explanatory factors: 

No link: [1.71 [1.20, 2.43] lag 3-5 

Link: 1.27 [1.06, 1.52] lag 3-5 

Vs occurrence of infection: 

Without infection: 

1.52 [1.16, 2.00] lag 3-5 

With infection: 1.30 [1.03, 1.65] lag 3-5 

Vs baseline pulmonary function: 

FEV1 >/ = 68% predicted: 

1.38 [1.06, 1.79] lag 3-5 

FEV <68% predicted: 

1.45 [1.11, 1.90] lag 3-5 

Vs smoking habits: 

Nonsmokers: 1.53 [1.18, 1.98] lag 3-5 

Current & ex-smokers: 

1.18 [0.90, 1.54] lag 3-5 

Vs allergy: 

Non-allergic: 1.29 [0.94, 1.77] lag 3-5 

Allergic: 1.49 [1.17, 1.90] lag 3-5 

Vs regular oral steroid treatment: 

No: 1.41 [1.15, 1.73] lag 3-5 

Yes: 1.41 [0.88, 2.25] lag 3-5 

Multipollutant model: PM10 + NO2: 1.43 

[1.16, 1.76] Lag 3-5 

PM10 + SO2: 1.51 [1.20, 1.90] Lag 3-5 

PM10 + O3: 1.09 [0.71, 1.67] Lag 3-5 

Reference: Diette et al. (2007, 156399) 

Period of Study: Sep 2001-Dec 

2003

Location: East Baltimore, MD 

Outcome: Asthma in the last 12 mo 

(493.x) 

Age Groups: 2 to 6 yr old

Study Design: Prospective cohort

N: 150 with asthma 

150 without asthma 

Statistical Analyses: 

Student’s two-tailed t-test 

Kruskal-Wallis test 

Pearson’s chi square 

Fisher’s exact test 

Covariates: Season of collection 

Dose-response Investigated? No

Statistical Package: STATASE 8.0 

Pollutant: PM10

Averaging Time: 72 h 

50th(Median): 43.7 

IQR: (29-70) 

Notes: “Pollutant concentrations in the 

homes of asthmatic and control children 

who lived in the same home for their 

whole life were not different compared 

with those who had moved at least 

once.” 

December 2009 E-143 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ebelt et al. (2005, 056907) 

Period of Study: Summer of 1998

Location: Vancouver, Canada 

Outcome: spirometry 

Age Groups: Range from 54-86 yr 

mean age = 74 yr

Study Design: Extended analysis of a 

repeated-measures panel study

N: 16 persons with COPD 

Statistical Analyses: Earlier analysis 

expanded by developing mixed-effect 

regression models and by evaluating 

additional exposure indicators 

Dose-response Investigated? No

Statistical Package: SAS V8 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Ambient PM10: 17 (6) 

Exposure to ambient PM10: 10.3 (4.6) 

Range (Min, Max): 

Ambient PM10: (7-36) 

Exposure to ambient PM10: (1.5-23.8) 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient PM10-2.5: r = 0.69 

Ambient PM2.5: r = 0.78 

Exposure to Ambient PM10: r = 0.71 

PM Increment: Ambient PM10: 7 (IQR) 

Exposure to ambient PM10: 6.5 (IQR) 

Notes: Effect estimates are presented 

in Fig 2 and Electronic Appendix Table 1 

(only available with electronic version of 

article) and not provided quantitatively 

elsewhere. 

Reference: Fischer et al. (2007, 

156435) 

Period of Study: 7 wk (dates not 

specified)

Location: The Netherlands 

Outcome: Respiratory Symptoms, Sore 

throat, Runny nose, Cold, Sick at home

Study Design: Prospective cohort 

N: 68 

Statistical Analyses: Linear regression 

model (PROC mixed) 

Age Groups: 10-11 

Lag: 1-2 

Statistical Package: SAS v 6.11 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 56 μg/m3 

IQ (25th, 75th): (21, 187) μg/m3

Copollutants: 

BS 

NO2

CO 

NO 

Increment: 10 μg/m3

% Increase in eNO and PM10 and 

change in spirometric lung function lag 

eNO and PM10 only 

6.5 (0.9, 12.4) 1 

7.8 (-11.3, 31.0) 2 

FVC mean (SEM) 

0.4 (0.5) 1 

0.6 (1.6) 2 

FEV1 mean (SEM) 

-0.3 (0.5) 1 

-2.1 (1.9) 2 

PEF mean (SEM) 

-2.8 (3.3) 1 

7.1 (12.0) 2 

MMEF mean (SEM) 

-0.5 (1.7) 1 

-2.5 (5.9) 2 

Reference: Forsberg et al. (1998, 

051714) 

Period of Study: Jan 1994-March 

1994

Location: Urban and rural areas of 

Umea, Sweden 

Outcome: Respiratory Symptoms, 

Shortness of breath 

Wheeze, Asthma attacks, Recent 

asthma, Dry cough, Doctor-diagnosed 

asthma, Recently treated for asthma, 

Early chest illness

Study Design: Cohort panel 

Statistical Analyses: Logistic linear 

regression 

Age Groups: 6-12 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Urban: 13.4 μg/m3 

Rural: 11.5 μg/m3 

Range (Min, Max): 

Urban: (0, 40.5) μg/m3 

Rural: (1.6, 29.0) μg/m3 

Copollutants (correlation): 

BS: r = 0.73 

Increment: 10 μg/m3

OR between prevalence of acute 

respiratory symptoms and PM10

exposure for urban and rural children 

lag 

Urban children: 

Cough: 1.031 (0.957, 1.112) 0 

0.997 (0.923, 1.077) 1 

1.018 (0.940, 1.103): 2 

1.094 (0.895, 1.338) 0-6 avg 

Phlegm: 

0.998 (0.899, 1.108) 0 

1.035 (0.928, 1.154) 1 

1.121 (1.013, 1.240) 2 

1.043 (0.822, 1.324) 0-6 avg 

Upper respiratory symptoms: 

1.004 (0.949, 1.063) 0 

0.975 (0.922, 1.031) 1 

0.951 (0.895, 1.010) 2 

0.849 (0.687, 1.050) 0-6 avg 

Lower respiratory symptoms: 

0.984 (0.872, 1.110) 0 

0.919 (0.812, 1.039) 1 

0.894 (0.771, 1.036) 2 

0.800 (0.617, 1.038) 0-6 avg 

Rural children (control) 

Cough: 

0.997 (0.900, 1.105) 0 

1.003 (0.906, 1.112) 1 

0.997 (0.891, 1.116) 2 

0.855 (0.655, 1.115) 0-6 avg 

Phlegm: 

1.024 (0.880, 1.192) 0 

0.995 (0.853, 1.160) 1 

1.117 (0.956, 1.305) 2 

1.041 (0.742, 1.459) 0-6 avg 

Upper respiratory symptoms: 

1.093 (0.989, 1.208) 0 

1.018 (0.918, 1.130) 1 

December 2009 E-144 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1.075 (0.962, 1.201) 2 

1.052 (0.786, 1.407) 0-6 avg 

Lower respiratory symptoms: 

1.022 (0.855, 1.180) 0 

0.998 (0.855, 1.164) 1 

1.000 (0.830, 1.206) 2 

0.939 (0.703, 1.253) 0-6 avg 

OR between incidence of acute 

respiratory symptoms and PM10

exposure in urban and rural children 

lag 

Urban Children: 

Cough: 

1.114 (0.886, 1.401) 0 

0.891 (0.703, 1.130) 1 

0.766 (0.577, 1.017) 2 

0.817 (0.523, 1.276) 0-6 avg 

Phlegm: 

0.954 (0.664, 1.371) 0 

1.056 (0.744, 1.501) 1 

1.416 (0.969, 2.069) 2 

0.808 (0.357, 1.827) 0-6 avg 

Upper respiratory symptoms: 

1.155 (0.965, 1.383) 0 

0.788 (0.629, 0.986) 1 

0.886 (0.728, 1.077) 2 

0.770 (0.549, 1.081) 0-6 avg 

Lower respiratory symptoms: 

1.060 (0.828, 1.356) 0 

0.763 (0.584, 0.996) 1 

0.652 (0.493, 0.863) 2 

0.519 (0.306, 0.882) 0-6 avg 

Rural Children: 

Cough: 

1.052 (0.767, 1.444) 0 

0.753 (0.547, 1.038) 1 

0.840 (0.571, 1.235) 2 

0.800 (0.409, 1.565) 0-6 avg 

Phlegm: 

1.051 (0.731, 1.509) 0 

1.010 (0.693, 1.472) 1 

0.998 (0.652, 1.528) 2 

0.797 (0.344, 1.847) 0-6 avg 

Upper respiratory symptoms: 

1.044 (0.813, 1.341) 0 

0.810 (0.612, 1.072) 1 

0.800 (0.611, 1.048) 2 

0.714 (0.417, 1.220) 0-6 avg 

Lower respiratory symptoms: 

1.079 (0.756, 1.539) 0 

0.888 (0.615, 1.281) 1 

0.715 (0.472, 1.083) 2 

0.822 (0.395, 1.711) 0-6 avg 

OR between prevalence of medication 

use and PM10 exposure in urban and 

rural children lag 

Bronchodilator use - Urban children: 

0.998 (0.951, 1.048) 0 

0.999 (0.952, 1.049) 1 

1.006 (0.953, 1.062) 2 

0.919 (0.775, 1.090) 0-6 avg 

Rural children: 

0.970 (0.904, 1.040) 0 

0.959 (0.893, 1.030) 1 

1.008 (0.927, 1.095) 2 

1.087 (0.914, 1.292) 0-6 avg 

OR between incidence of medication 

use and PM10 exposure in urban and 

rural children lag 

Bronchodilator use - Urban children: 

1.498 (0.899, 2.498) 0 

1.049 (0.565, 1.947) 1 

1.148 (0.674, 1.954) 2 

1.787 (0.611, 5.227) 0-6 avg 

Rural children: 

1.275 (0.702, 2.315) 0 

0.924 (0.437, 1.956) 1 

December 2009 E-145 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1.005 (0.522, 1.936) 2 

1.823 (0.534, 6.277) 0-6 avg 

Reference: Goncalves et al. (2005, 

089884) 

Period of Study: Dec 1992-Mar 1993. 

Dec 1992-Mar 1994

Location: Sao Paulo 

Outcome: Respiratory 

morbidity/admissions 

Age Groups: Children <13 yr

Study Design: Time series 

Statistical Analyses: Principal 

component analysis 

Covariates: Daily mean temperature, 

daily mean water vapor density, solar 

radiation 

Season: Summer 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: Lag 3 

Pollutant: PM10

Averaging Time: 24 h 

Copollutant: SO2 , O3

PCA coefficients: PC1, PC2, PC3: 

Summer 1992/1993: 

PM10: 0.69, 0.45, 0.13 

Solar Radiation: -0.04, 0.94 to -0.12 

Mean Temperature: 0.62, 0.44 to -0.47 

Mean Water Vapor Density: 

0.73 to -0.46 to -0.26 

SO2: 0.78 to -0.03, 0.33 

O3: 0.18, 0.63, 0.37 

Respiratory Mortality: 

0.05 to -0.02, 0.81 

Variations explained by Principal 

Component: 

PC1: 0.29 

PC2: 0.27 

PC3: 0.17 

Summer 1993/1994: 

PM10: 0.38, 0.80 to -0.23 

Solar Radiation: 0.02, 0.09 to -0.97 

Mean Temperature: 0.71, 0.40 to -0.37 

Mean Water Vapor Density: 

0.88, 0.25, 0.09 

SO2: 0.01, 0.92, 0.00 

O3: 0.47 to -0.06 to -0.35 

Respiratory Mortality: -0.73, 0.11, 0.08 

Variations explained by Principal 

Component: 

PC1: 0.31 

PC2: 0.25 

PC3: 0.18 

Notes: Association between respiratory 

morbidity and air pollution more likely 

during summer with smaller contrasts in 

synoptic weather condition (summer 

1992/93) but respiratory morbidity more 

related to weather variables during 

summer with larger contrasts (summer 

1993/94). 

Reference: Gordian and Choudhury 

(2003, 054842) 

Period of Study: 1994-Dec 1996

Location: Anchorage, Alaska 

Outcome: Asthma medication among 

school children 

Age Groups: Elementary school 

children (kindergarten-6th grade) 

Study Design: Time series 

Statistical Analyses: Time series 

regression model 

Covariates: Day of the week, month, 

time trend, temperature 

Season: All seasons 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 1, 2, 7, 14, 21, 28 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 36.11 (30.46) 

Range (Min, Max): 2.96, 210.0 

Monitoring Stations: 1 

Model regression slope coefficient for 

PM10 (estimated SE) lag: 

7.25 (2.88) 

lag 21 

RR: 1.075 (1.016, 1.138) 

Notes: PM10 coefficients for other lags 

were also statistically significant but not 

reported. 

December 2009 E-146 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Harre et al. (1997, 095726) 

Period of Study: Jun 994-Aug 1994

Location: Christchurch, New Zealand 

Outcome: Respiratory symptoms, 

Cough, Wheeze, Chest tightness, 

Shortness of breath, Change in sputum 

volume, Nose, throat, or eye irritation, 

PEFR

Study Design: Prospective cohort 

Statistical Analyses: Poisson, log 

linear regression 

Age Groups: >55 

Pollutant: PM10

Averaging Time: 24-h avg 

Copollutants: 

CO 

SO2 

NO2

Increment: 35.04 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Chest symptoms: 1.38 (1.07, 1.78) 1 

Wheeze: 0.97 (0.75, 1.26) 1 

Nebulizer Use: 0.71 (0.42, 1.18) 1 

Inhaler Use: 0.94 (0.78, 1.13) 1 

Reference: Hastings and Jardine 

(2002, 030344) 

Period of Study: 1997-1998

Location: Bosnia (U.S. military camps) 

Outcome: Weekly rates of upper 

respiratory disease (URD), reported by 

the medical treatment facility in each 

military camp 

Age Groups: U.S. soldiers

Study Design: Ecologic (at level of 

military camp)

N: 5 camps 

Statistical Analyses: 

1.Pearson correlations between weekly 

URD rates and weekly PM10 (avg and 

max) 

2.Kruskal Wallace test to compare URD 

rates in the 4 exposure quartiles 

3. Mann Whitney test to compare 

dichotomized exposure groups (above 

and below 50th percentile) 

Dose-response Investigated? Yes 

Lags Considered: Weekly rates of 

URD disease were related to avg 

weekly PM levels in the same week 

Pollutant: PM10

Mean (SD): 

PM10 avg: 75.5 

PM10 max: 92.9 

Percentiles: 

PM10 max: 

25th: 58.57 

50th: 74.55 

75th: 107.56 

PM10 avg: 

25th: 42.19 

50th: 64.17 

75th: 81.75 

Range (Min, Max): 

PM10 avg: 25.0, 338.7 

PM10 max: 25.0, 338.7 

Monitoring Stations: At least 1 in each 

of the 5 camps 

PM max Quartiles (combining all 

camps): 

Q1: <58.7 μg/m3

Q2: 60.1 to <75.54 μg/m3

Q3: 78.56 to <107.56 μg/m3

Q4: >107.56 μg/m3

For dichotomous analysis 

cutoff = 74.55 μg/m3

PM avg Quartiles (combining all 

camps): 

Q1: <42.19 μg/m3 

Q2: 42.19 to 64.17 μg/m3 

Q3: 64.17 to 81.75 μg/m3 

Q4: >81.75 μg/m3 

For dichotomous analysis 

cutoff = 64.17 μg/m3

Pearson correlation coefficients 

between URD rate and PM category [pvalue]: PM10 max: quartiles of PM*URD 

rates 

All camps 0.203 [0.041] 

Blue Factory camp 0.277 [0.095] 

Comanche 0.165 [0.237] 

Demi 0.639 [0.123] 

McGovern 0.535 [0.177] 

Tuzla Main 0.107 [0.327] 

PM10 max: dichotomous PM*URD rates: 

All camps 0.283 [0.007] 

Blue Factory camp 0.038 [0.430] 

Comanche 0.282 [0.107] 

Demi 0.927 [0.012] 

McGovern 0.853 [0.033] 

Tuzla Main 0.155 [0.258] 

PM10 avg: quartiles of PM*URD rates: 

All camps 0.149 [0.101] 

Blue Factory camp 0.301 [0.077] 

Comanche 0.246 [0.141] 

Demi 0.437 [0.231] 

McGovern 0.853 [0.033] 

Tuzla Main 0.182 [0.222] 

PM10 avg: dichotomous PM*URD rates: 

All camps 0.060 [0.305] 

Blue Factory camp -0.075 [0.365] 

Comanche 0.143 [0.268] 

Demi N/A* 

McGovern N/A* 

Tuzla Main 0.123 [0.303] 

Kruskal Wallace p-value comparing 

URD rates across exposure quartiles: 

PM10 max 

All camps 0.047 

Blue Factory camp 0.321 

Comanche 0.556 

Demi 0.165 

McGovern 0.202 

Tuzla Main 0.554 

PM10 avg 

December 2009 E-147 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

All camps 0.672 

Blue Factory camp 0.809 

Comanche 0.658 

Demi 0.564 

McGovern 0.157 

Tuzla Main 0.891 

Mann-Whitney p-value comparing URD 

rates between upper and lower 50th 

percentile of PM: 

PM10 max 

All camps 0.034 

Blue Factory camp 0.173 

Comanche 0.314 

Demi 0.083 

McGovern 0.401 

Tuzla Main 0.481 

PM10 avg 

All camps 0.824 

Blue Factory camp 0.682 

Comanche 0.508 

Demi N/A* 

McGovern N/A* 

Tuzla Main 0.656 

Notes: * There were no days that fell in 

the upper 50 percentile for PM avg in 

these camps 

-Rates of URD by PM quartiles for each 

camp presented in figures. Authors 

state, “Generally the avg URD rate 

increased with quartile of maximum 

exposure...the trend was not as clear 

for quartiles of PM10 avg exposure” 

December 2009 E-148 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hong et al. (2007, 091347) 

Period of Study: Mar 23-May 2004

Location: School on the Dukjeok Island 

near Incheon City, Korea 

Outcome: Peak expiratory flow rate 

(PEFR) 

Age Groups: 3rd to 6th grade (mean 

age = 9.6 yr)

Study Design: Panel study

N: 43 schoolchildren 

Statistical Analyses: Mixed linear 

regression 

Covariates: Age, sex, height, weight, 

asthma history, and passive smoking 

exposure at home 

Dose-response Investigated? No 

Lags Considered: 0, 1, 2, 3, 4, 5 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 35.30 (23.48) 

50th (Median): 29.36 

Range (Min, Max): 

(12.24-124.87) 

PM Component: 

Fe: mean = 0.208 (0.203) μg/m3

Median = 0.112 

Range (Min, Max): (0.061-0.806) 

Mn: mean = 0.008 (0.005) μg/m3

Median = 0.007 

Range (Min, Max): (0.000-0.019) 

Pb: mean = 0.051 (0.031) μg/m3

Median = 0.051 

Range (Min, Max): (0.011-0.155) 

Zn: mean = 0.021 (0.021) μg/m3

Median = 0.013 

Range (Min, Max): (0.006-0.112) 

Al: mean = 0.085 (0.100) μg/m3

Median = 0.031 

Range (Min, Max): (0.017-0.344) 

Copollutant: PM2.5

Effect Estimate: Regression 

coefficients of morning and daily mean 

PEFR on PM10 and metal components 

using linear mixed-effects regression 

Lag 1 (PM10) 

Morning PEFR 

Crude: ß = -0.00, p = 0.99 

Adjusted: ß = -0.04, p = 0.37 

Mean PEFR 

Crude: ß = 0.00, p = 0.93 

Adjusted: ß = -0.05, p = 0.12 

Lag 1 (logFe) 

Morning PEFR 

Crude: ß = -1.26, p = 0.31 

Adjusted: ß = -3.24, p = 0.13 

Mean PEFR 

Crude: ß = -1.20, p = 0.20 

Adjusted: ß = -2.37, p = 0.15 

Lag 1 (logMn) 

Morning PEFR 

Crude: ß = -4.40, p < 0.01 

Adjusted: ß = -9.82, p < 0.01 

Mean PEFR 

Crude: ß = -4.05, p < 0.01 

Adjusted: ß = -8.44, p < 0.01 

Lag 1 (logPb) 

Morning PEFR 

Crude: ß = -6.79, p < 0.01 

Adjusted: ß = -6.83, p < 0.01 

Mean PEFR 

Crude: ß = -6.23, p < 0.01 

Adjusted: ß = -6.37, p < 0.01 

Lag 1 (logZn) 

Morning PEFR 

Crude: ß = -0.55, p = 0.71 

Adjusted: ß = -0.98, p = 0.59 

Mean PEFR 

Crude: ß = 1.33, p = 0.24 

Adjusted: ß = 1.53, p = 0.28 

Lag1 (logAl) 

Morning PEFR 

Crude: ß = -0.58, p = 0.57 

Adjusted: ß = -2.22, p = 0.25 

Mean PEFR 

Crude: ß = -0.59, p = 0.45 

Adjusted: ß = -1.48, p = 0.32 

Regression coefficients of morning and 

daily mean PEFR on metal components 

of PM10 and GSTM1 and GSTT1 

genotype using linear mixed-effects 

regression 

Lag 1 (logPb) 

Morning PEFR: ß = -7.26, p < 0.01 

Mean PEFR: ß = -6.43, p < 0.01 

GSTM1 

Morning PEFR: ß = 21.19, p = 0.23 

Mean PEFR: ß = 20.09, p = 0.25 

Lag 1 (logMn) 

Morning PEFR: ß = -10.31, p < 0.01 

Mean PEFR: ß = -8.66, p < 0.01 

GSTM1 

Morning PEFR: ß = 21.02, p = 0.23 

Mean PEFR: ß = 19.84, p = 0.25 

Lag 1 (logPb) 

Morning PEFR: ß = -7.26, p < 0.01 

Mean PEFR: ß = -6.43, p < 0.01 

GSTT1 

Morning PEFR: ß = 2.07, p = 0.90 

Mean PEFR: ß = -2.39, p < 0.88 

Lag 1 (logMn) 

Morning PEFR: ß = -10.32, p < 0.01 

Mean PEFR: ß = -8.67, p < 0.01 

GSTT1 

Morning PEFR: ß = 2.02, p = 0.90 

Mean PEFR: ß = 2.33, p = 0.88 

December 2009 E-149 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hwang et al. (2006, 

088971) 

Period of Study: 2001

Location: Taiwan 

Outcome: Allergic rhinitis

Study Design: Cross-sectional 

Statistical Analyses: Two-stage 

hierarchical models 

Age Groups: 6-15 yr 

Pollutant: PM10

Averaging Time: 1-h avg 

Mean (SD): 55.58 (16.57) 

Range (Min, Max): 

(29.36, 99.58) 

Copollutants (correlation): 

CO: r = 0.27 

NOX: r = 0.34 

O3: r = 0.28 

SO2: r = 0.58 

Increment: 10 μg/m3

Odds Ratio (Lower CI, Upper CI) 

lag: 

PM10 alone: 1.00 (0.99, 1.02) 

, PM10: 0.99 (0.97, 1.00) 

CO, PM10: 1.00 (0.99, 1.01) 

O3, PM10: 1.00 (0.99, 1.02) 

Gender 

Male: 1.02 (0.99, 1.04) 

Female: 0.99 (0.97, 1.02) 

Parental atopy* 

Yes: 1.00 (0.98, 1.03) 

No: 1.01 (0.99, 1.03) 

Parental education 

<6 yr: 1.05 (0.96, 1.14) 

6-8 yr: 1.03 (0.98, 1.07) 

9-11 yr: 1.00 (0.98, 1.03) 

12+ yr: 0.99 (0.97, 1.02) 

Environmental tobacco smoke 

Yes: 1.01 (0.99, 1.03) 

No: 1.00 (0.98, 1.03) 

Visible mold** 

Yes: 1.02 (0.99, 1.06) 

No: 1.00 (0.98, 1.02) 

* Parental atopy was a measure of 

genetic predisposition and was defined 

as the father or the mother of the index 

child ever having been diagnosed as 

having asthma, allergic rhinitis, or atopic 

eczema. 

** Visible mold found in the home. 

Reference: Jalaludin et al. (2004, 

056595) 

Period of Study: Feb 1994-Dec 1994

Location: Western and southwestern 

Sydney, Australia 

Outcome: Respiratory symptoms, 

Wheeze, Dry cough, Wet cough

Study Design: Longitudinal study panel

Statistical Analyses: Logistic 

regression model (GEE) 

Age Groups: 9-11 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 22.8 (13.8) 

IQ Range (25th,75th): (12.00, 122.8) 

Copollutants (correlation): 

O3: r = 0.13 

NO2: r = 0.26 

Increment: 10 μg/m3

Odds Ratio (Lower CI, Upper CI) 

Lag 

Wheeze 

1.01 (0.99, 1.03) 0 

1.01 (0.97, 1.04) 1 

0.99 (0.96, 1.03) 2 

1.02 (0.98, 1.06) 0-2 avg 

1.04 (0.99, 1.10) 0-5 avg 

Dry Cough 

1.00 (0.98, 1.03) 0 

1.00 (0.97, 1.03) 1 

1.00 (0.97, 1.02) 2 

1.00 (0.97, 1.03) 0-2 avg 

1.03 (0.98, 1.08) 0-5 avg 

Wet Cough 

1.01 (0.99, 1.04) 0 

0.99 (0.97, 1.01) 1 

1.00 (0.97, 1.03) 2 

0.99 (0.96, 1.02) 0-2 avg 

0.99 (0.94, 1.04) 0-5 avg 

Inhaled B2-agonist Use 

0.99 (0.98, 1.01) 0 

1.00 (0.98, 1.03) 1 

0.99 (0.97, 1.01) 2 

1.00 (0.97, 1.02) 0-2 avg 

1.02 (0.98, 1.06) 0-5 avg 

Inhaled Corticosteroid Use 

1.00 (0.99, 1.01) 0 

1.00 (0.99, 1.02) 1 

1.00 (0.99, 1.02) 2 

1.00 (0.98, 1.02) 0-2 avg 

1.00 (0.97, 1.02) 0-5 avg 

Doctor Visit for Asthma 

1.11 (1.04, 1.19) 0 

1.10 (1.02, 1.19) 1 

1.15 (1.06, 1.24) 2 

1.11 (1.03, 1.20) 0-2 avg 

1.14 (0.98, 1.31) 0-5 avg 

OR for respiratory symptoms and 

PM10 exposure by different groups 

December 2009 E-150 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

All children 

Wheeze: 1.01 (0.99, 1.04) 

Dry Cough: 1.00 (0.97, 1.02) 

Wet Cough: 1.01 (0.98, 1.04) 

Inhaled B2-agonist Use: 

1.00 (0.98, 1.02) 

Inhaled Corticosteroid Use: 

0.99 (0.98, 1.01) 

Doctor Visit for asthma: 

1.11 (1.03, 1.19) 

Group 1* 

Wheeze: 1.01 (0.98, 1.04) 

Dry Cough: 0.97 (0.94, 0.99) 

Wet Cough: 1.00 (0.97, 1.03) 

Inhaled B2-agonist use: 

1.00 (0.98, 1.02) 

Inhaled Corticosteroid Use: 

1.00 (0.98, 1.01) 

Doctor Visit for asthma: 1.09 

(0.98, 1.21) 

Group 2** 

Wheeze: 1.01 (0.97, 1.05) 

Dry Cough: 1.02 (0.98, 1.06) 

Wet Cough: 1.01 (0.96, 1.06) 

Inhaled B2-agonist use: 

0.99 (0.94, 1.05) 

Inhaled Corticosteroid Use: 

0.99 (0.97, 1.01) 

Doctor Visit for asthma: 

1.12 (1.02, 1.23) 

Group 3*** 

Wheeze: 1.08 (0.90, 1.31) 

Dry Cough: 1.01 (0.91, 1.11) 

Wet Cough: 1.02 (0.94, 1.11) 

Inhaled B2-agonist use: 

0.98 (0.84, 1.11) 

Inhaled Corticosteroid Use: 

1.27 (1.08, 1.49) 

Doctor Visit for asthma: NR 

*Group 1 consists of children with a 

history of wheeze in the past 12 mo, 

positive histamine challenge, and doctor 

diagnosed asthma. 

**Group 2 consists of children with a 

history of wheeze in the past 12 mo and 

doctor diagnosed asthma. 

***Group 3 consists of children only with 

a history y of wheeze in the past 12 mo.

December 2009 E-151 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Jansen, et al. (2005, 

082236) 

Period of Study: 1987-2000 

Location: Seattle, WA 

Outcome: FENO: fractional exhaled 

nitrogen oxide, Spirometry, Blood 

pressure, SaO2: oxygen saturation, 

Pulse rate 

Age Groups: 60-86 yr old 

Study Design: Short-term crosssectional case series 

N: 16 subjects diagnosed with COPD, 

asthma, or both 

Statistical Analyses: Linear mixed 

effects model with random intercepts 

Covariates: Age, relative humidity, 

temperature, medication use

Season: winter 2002-2003 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Fixed-site Monitor: 18.0 

All Subjects (N = 16) 

Indoor, home: 11.93 

Outdoor, home: 13.47 

Personal: 23.34 

Asthmatic Subjects (N = 7) 

Indoor, home: 12.54 

Outdoor, home: 11.86 

Personal: 26.88 

COPD Subjects (N = 9) 

Indoor, home: 11.45 

Outdoor, home: 14.76 

Personal: 19.91 

Range (Min, Max): 

Fixed-site Monitor 2.5, 51 

IQR: 

All Subjects 

Indoor, home: 6.93 

Outdoor, home: 9.53 

Personal: 20.72 

Asthmatic Subjects 

Indoor, home: 10.19 

Outdoor, home: 8.77 

Personal: 20.08 

COPD Subjects 

Indoor, home: 4.56 

Outdoor, home: 6.14 

Personal: 19.94 

PM Increment: 10 μg/m3

Slope [95% CI]: dependence of FENO 

concentration [ppb] on PM10

Asthmatic Subjects 

Indoor, home: 3.81 [-0.86: 8.50] 

Outdoor, home: 5.87 [2.87: 8.88]* 

Personal: 0.66 [-0.56: 1.88] 

COPD Subjects 

Indoor, home: 2.19 [-3.48: 7.87] 

Outdoor, home: 4.45 [-1.11: 10.01] 

Personal: 0.17 [-1.61: 1.96] 

Results indicate that FENO may be a 

more sensitive biomarker of PM 

exposure than other traditional health 

endpoints. 

December 2009 E-152 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Johnston, et al. (2006, 

091386) 

Period of Study: 

7 mo (Apr 7-Nov 7, 2004) 

Location: Darwin, Australia 

Outcome: Asthma symptoms 

Age Groups: All ages 

Study Design: Time-series 

N: 251 people (130 adults, 121 children 

Statistical Analyses: Logistic 

regression model 

Covariates: Minimum air temperature, 

doctor visits for influenza and the 

prevalence of asthma symptoms and, 

the fungal spore count and both onset 

of asthma symptoms and 

commencement of reliever medication

Season: “Dry season”-specific months 

NR, note Southern Hemisphere 

Dose-response Investigated? No 

Statistical Package: STATA8 

Lags Considered: 0-5 days 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD): 20 (6.4) 

Range (Min, Max): 2.6-43.3 

PM Component: Vegetation fire smoke 

(95%) and motor vehicle emissions 

(5%) 

Monitoring Stations: 1 

Correlation: PM2.5

:

 r = 0.90 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

Symptoms attributable to asthma 

Overall:1.010 (0.98,1.04) 

Adults:1.027 (0.987,1.068) 

Children:0.930 (0.966, 1.060) 

Using preventer: 1.022 (0.985, 1.060) 

Became symptomatic 

Overall: 1.240 (1.106,1.39) 

Adults: 1.277 (1.084,1.504) 

Children: 1.247 (1.058,1.468) 

Using preventer:1.317 (1.124,1.543) 

Used Reliever 

Overall: 1.010 (0.99, 1.04) 

Adults: 1.026 (0.990, 1.063) 

Children: 1.006 (0.960,1.055) 

Using preventer:1.035 (1.004,1.060) 

Commenced Reliever 

Overall: 1.132 (0.99, 1.29) 

Adults: 1.199 (0.994, 1.446) 

Children: 1.093 (0.906,1.319) 

Using preventer:1.194 (0.996, 1.432) 

Commenced Oral Steroids 

Overall: 1.540 (1.01, 2.34) 

Adults: 1.752 (1.008, 3.045) 

Children: 1.292 (0.682, 2.448) 

Using preventer:1.430 (0.888, 2.304) 

Asthma Attack 

Overall: 1.030 (0.95, 1.12) 

Adults: 1.08 (0.976, 1.202) 

Children: 0.861 (0.710, 1.044) 

Using preventer:1.051 (0.939,1.175) 

Exercise induced asthma 

Overall: 0.980 (0.92, 1.05) 

Adults: 0.988 (0.902, 1.081) 

Children: 0.972 (0.844,1.119) 

Using preventer:1.026 (0.928,1.134) 

Saw a health professional for asthma 

Overall: 1.030 (0.85, 1.26) 

Adults: 1.064 (0.794, 1.424) 

Children: 0.998 (0.749,1.328) 

Using preventer:0.924 (0.731, 1.169) 

Missed school or work due to asthma 

Overall: 1.102 (0.941, 1.290) 

Adults: 1.135 (0.897, 1.435) 

Children: 1.073 (0.862,1.333) 

Using preventer:1.025 (0.857,1.228) 

Mean daily number of asthma 

symptoms 

Overall: 1.020 (1.001,1.031) 

Adults: 1.027 (1.005,1.049) 

Children: 1.016 (0.986,1.047) 

Using preventer:1.034 (1.011,1.058) 

Mean Daily number of applications of 

reliever 

Overall: 1.020 (1.00,1.030) 

Adults: 1.032 (1.008, 1.057) 

Children: 1.002 (0.969,1.034) 

Using preventer:1.022 (1.001,1.043) 

December 2009 E-153 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Just et al. (2002, 035429) 

Period of Study:Apr 1996-Jun 1996 

Location: Paris, France 

Outcome: Incident and prevalent 

episodes of asthma attacks, nocturnal 

cough, wheeze, symptoms of irritation, 

respiratory infections, supplementary 

use of β2-agonists, Z-transformed peak 

expiratory flow (PEF), daily PEF 

variability 

Age Groups: 7-15 yr old 

Study Design: Cohort

N: 82 children 

Statistical Analyses: Linear 

regression, logistic regression, GEE 

Covariates: Effects of time trend, day 

of the week, weather, pollen levels

Season: Spring/summer 

Lags Considered: 0, 0-2 mean, 0-4 

mean 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD): 23.5 (8.4) 

Range (Min, Max): 9.0, 44.0 

Monitoring Stations: 5 

Copollutant (correlation): 

BS: 0.59 

SO2: 0.70 

NO2: 0.54 

O3: 0.21 

Temp: 0.04 

Humid: -0.41 

PM Increment: 10 μg/m3 for binary 

responses data (results that use odds 

ratios [ORs]) 

Incident episodes of 

1) Asthma 

 a) lag 0: 1.06 (0.61, 1.83) 

 b) 0-2 mean: 1.09 (0.48, 2.49) 

 c) 0-4 mean: 1.07 (0.44, 2.65) 

2) Nocturnal cough 

 a) lag 0: 1.10 (0.88, 1.37) 

 b) 0-2 mean: 1.03 (0.77, 1.37) 

 c) 0-4 mean: 1.11 (0.86, 1.42) 

3) Respiratory infections 

 a) lag 0: 0.64 (0.35, 1.15) 

 b) 0-2 mean: 0.74 (0.38, 1.43) 

 c) 0-4 mean: 0.99 (0.58, 1.68) 

Prevalent episodes of 

1) Asthma 

 a) lag 0: 1.07 (0.72, 1.59) 

 b) 0-2 mean: 1.18 (0.64, 2.17) 

 c) 0-4 mean: 1.16 (0.63, 2.13) 

2) Nocturnal cough 

 a) lag 0: 1.05 (0.83, 1.34) 

 b) 0-2 mean: 1.10 (0.81, 1.50) 

 c) 0-4 mean: 1.09 (0.79, 1.52) 

3) Respiratory infections 

 a) lag 0: 1.17 (0.68, 2.03 ) 

 b) 0-2 mean: 1.31 (0.51, 3.36) 

 c) 0-4 mean: 1.71 (0.71, 4.12) 

4) Eye irritation 

 a) lag 0: 1.18 (1.01, 1.39) 

 b) 0-2 mean: 1.28 (1.03, 1.59) 

 c) 0-4 mean: 1.42 (1.12, 1.80) 

Analysis restricted to days with no 

steroid use: 

Incident episodes of 

1) Eye irritation 

 a) lag 0: 1.07 (0.66, 1.71) 

 b) 0-2 mean: 0.83 (0.45, 1.53) 

 c) 0-4 mean: 0.92 (0.46, 1.83) 

2) Throat irritation 

 a) lag 0: 1.33 (0.66, 2.69) 

 b) 0-2 mean: 1.28 (0.58, 2.80) 

 c) 0-4 mean: 1.06 (0.38, 2.95) 

3) Nose irritation 

 a) lag 0: 0.74 (0.48, 1.13) 

 b) 0-2 mean: 0.76 (0.42, 1.36) 

 c) 0-4 mean: 0.96 (0.53, 1.73) 

Prevalent episodes of 

1) Eye irritation 

 a) lag 0: 1.20 (0.88, 1.65) 

 b) 0-2 mean: 1.71 (0.97, 3.01) 

 c) 0-4 mean: 1.97 (1.03, 3.76) 

2) Throat irritation 

 a) lag 0: 1.23 (0.83, 1.82) 

 b) 0-2 mean: 1.08 (0.68, 1.73) 

 c) 0-4 mean: 0.91 (0.47, 1.73) 

3) Nose irritation 

 a) lag 0: 1.20 (0.91, 1.58) 

 b) 0-2 mean: 1.09 (0.78, 1.52) 

 c) 0-4 mean: 1.09 (0.73, 1.61) 

Notes: The authors noted that incident 

or prevalent wheeze was not correlated 

with levels of any type of pollutant. 

Also, they state no relationship was 

observed between PEF variables and 

levels of PM. 

The authors also note that in a 

multipollutant model assessing 

independent effects of PM and O3 on 

prevalent episodes of eye irritation 

(mean 0-4), the PM parameter 

decreased and was not significant 

(p = 0.19). 

December 2009 E-154 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kulkarni et al. (2006, 

089257) 

Period of Study: Nov 2002-Dec 

2003 

Location: Leicester, United Kingdom 

Outcome: Lung function by spirometry: 

FVC, FEV1, FEV1: FVC, FEF25-75

Age Groups: 8-15 yr 

Study Design: Cross-sectional 

N: 114 children, 64 provided sputum for 

assessment of carbon content of 

macrophages. 

Statistical Analyses: Linear 

regressions, Spearman rank 

correlations. Mann-Whitney, Chi-square 

and unpaired t tests were used to 

compare results between asthmatic and 

non asthmatic children 

Covariates: BMI, sex, exercise, traffic 

PM10

Dose-response Investigated? Yes 

Statistical Package: SPSS 

Pollutant: Primary PM10 (μg/m3) 

concentration was modeled, and was 

considered a covariate for carbon 

content of macrophages. Carbon 

content of alveolar macrophages was 

the primary variable of interest. 

Averaging Time: 1 yr 

50th(Median): 

Children without asthma, 1.21 

Children with asthma, 1.81 

Range (Min, Max): 

Children without asthma, 0.10, 2.17 

Children with asthma, 0.17, 2.13 

PM Component: Carbon content in 

alveolar macrophages 

Monitoring Stations: NR. 

Copollutant (correlation): 

Vs carbon content in macrophages 

(increment, coefficient range]) 

-1.0 μg/m3

, 0.1 [0.01-0.18] 

PM Increment: 1.0 μg/m3 

% Change [Lower CI, Upper CI]: 

Single pollutant model: 

FEV1: -4.3 [-8.5, 0.2] p = 0.04 

R2 = 0.06 

Single pollutant model: 

FVC: -1.2 [-5.6, 3.2] p = 0.59 

R2 = 0.005 

Single pollutant model: 

FEF25-75: -8.6 [ -17.3, 0.1] p = 0.05 

R2 = 0.06 

2 pollutant model with Macrophage 

Carbon: 

FEV1: PM10 -2.9 [-6.9, 1.2] 

p = 0.17 

FVC: PM10 0.1 [-4.4, 4.6] 

p = 0.96 

FEF25-75: PM10 -5.5 [-14.2, 3.1] 

p = 0.21 

Reference: Kuo, et al. (2002, 036310) 

Period of Study: 1-yr period (yr not 

specified) 

Location: Central Taiwan 

Outcome: Asthma (yes/no) 

Age Groups: 13-16 yr 

Study Design: Cohort

N: 12,926 total children 

775 asthmatic children 

8 junior high schools 

Statistical Analyses: Pearson 

correlation coefficients 

Logistic regression 

Covariates: Gender, age, residential 

area, level of parental education, 

number cigarettes smoked by family 

members, incense burning in the home, 

frequency of physical activities 

Dose-response Investigated? No 

Statistical Package: SAS 6.12 

Lags Considered: Monthly avg at each 

school 

Pollutant: PM10

Averaging Time: 1 h 

Mean (SD): 

School A: 59.7 

School B: 65.3 

School C: 84.3 

School D: 59.2 

School E: 75.3 

School F: 60.2 

School G: 54.1 

School H: 69.0 

Monitoring Stations: 8 (1 for each 

school) 

PM Increment: Dichotomized annual 

avg: 

<65.9 μg/m3

≥ 65.9 μg/m3 

OR Estimate [Lower CI, Upper CI] 

lag: 

Crude (outcome = asthma, yes/no) 

<65.9 μg/m3

: 1 (ref) 

≥ 65.9 μg/m3

: 0.837 [NR] 

Adjusted (outcome = asthma, yes/no) 

<65.9 μg/m3

: 1 (ref) 

≥ 65.9 μg/m3: 0.947 [0.640, 1.401] 

Notes: Asthma prevalence was highest 

in urban areas and lowest in rural areas 

Pearson correlation between annual 

PM levels at each school and asthma 

prevalence at each school: 0.214 

(p > 0.05) 

Reference: Lagorio et al. (2006, 

089800) 

Period of Study: 

May 1999-Jun 1999 

Jan 1999-Dec 1999 

Location: Rome, Italy 

Outcome: Lung function of subjects 

(FVC and FEV1) with COPD, Asthma 

Age Groups: 

COPD: 50 to 80 yr 

Asthma: 18 to 64 yr 

Study Design: Time series panel

N: COPD N = 11; Asthma N = 11 

Statistical Analyses: Non-parametric 

Spearman correlation 

GEE 

Covariates: COPD and IHD: daily 

mean temperature, season variable 

(spring or winter), relative humidity, day 

of week 

Asthma: season variable, temperature, 

humidity, and β-2-agonist use

Season: Spring and winter 

Dose-response Investigated? Yes 

Statistical Package: STATA 

Lags Considered: 1-3 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Overall: 42.8 (21.8) 

Spring: 36.9 (10.8) 

Winter: 49.0 (28.1) 

Range (Min, Max): (7.9, 123) 

PM Component: NR 

Monitoring Stations: Two fixed sites: 

(Villa Ada and Istituto superior di Sanita)

 

Copollutant (correlation): 

NO2 r = 0.45 

O3 r = -0.36 

CO r = 0.55 

SO2 r = 0.21 

PM10-2.5 r = 0.61 

PM2.5 r = 0.93 

PM Increment: 1 μg/m3

They observed negative association 

between ambient PM10 and respiratory 

function (FVC and FEV1) in the COPD 

panel. The effect on FVC was seen at 

lag 24 h, 48 h, and 72 h. The effect on 

FEV1 was evident at lag 72 h. There 

was no statistically significant effect of 

PM10 on FVC and FEV1 in the asthmatic 

and IHD panels. 

β Coefficient (SE) 

COPD 

FVC(%) 24 h -0.66 (0.30) 

48-h -0.75 (0.35) 

72-h -0.94 (0.47) 

FEV1(%) 24 h -0.37 (0.27) 

48-h -0.58 (0.31) 

72-h -0.87 (0.43) 

Asthma 

FVC(%) 24 h -0.12 (0.24) 

48-h -0.09 (0.29) 

72-h -0.08 (0.36) 

FEV1(%) 24 h -0.28 (0.28) 

48-h -0.40 (0.34) 

72-h -0.40 (0.43) 

December 2009 E-155 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lee, et al. (2007, 093042) 

Period of Study: 2000-2001 

Location: South-Western Seoul 

Metropolitan area, Seoul, South Korea 

Outcome: PEFR (peak expiratory flow 

rate), lower respiratory symptoms (cold, 

cough, wheeze) 

Age Groups: 61-89 yr (77.8 mean age)

Study Design: Longitudinal panel 

survey 

N: 61 adults 

Statistical Analyses: Logistic 

regression model 

Covariates: Temperature (Celsius), 

relative humidity, age, season 

Dose-response Investigated? No 

Statistical Package: SAS 8.0 

Lags Considered: 0-4 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 71.40 (30.69) 

Percentiles: 25th: 43.47 

50th(Median): 74.92 

75th: 87.54 

Range (Min, Max): 

26.23, 148.34 

Monitoring Stations: 2 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]

lag: 

PEFR (peak expiratory flow rate) 

-0.39 (-0.63 to -0.14) 

1 day 

relative odds of a lower respiratory 

symptom (cold, cough, wheeze) 

1.015 (0.900,1.144) 

1 day 

Reference: Lewis, et al. (2005, 

081079) 

Period of Study: 

Winter 2001-spring 2002 

Location: Detroit, Michigan, USA 

Outcome: Poorer lung function 

(increased diurnal variability and 

decreased forced expiratory volume) 

Age Groups: 7-11 yr 

Study Design: longitudinal cohort study

N: 86 children 

Statistical Analyses: descriptive 

statistics and bivariate analyses of 

exposures, multivariable regression 

models that included interaction terms 

between exposure measures and CS 

use or, alternatively, presence of a URI, 

multivariate analog of linear regression. 

Covariates: sex, home location, annual 

family income, presence of one or more 

smokers in household, race, season 

(entered as dummy variables), and 

parameters to account for intervention 

group effect.

Season: Winter 2001 (Feb 10-23), 

spring 2001 (May 5-18), summer 2001 

(Jul 14-27), fall 2001 (Sep 22-Oct 5), 

winter 2002 (Jan 18-31), and spring 

2002 (May 18-31). 

Dose-response Investigated? No 

Lags Considered: 1-2 days 

3-5 days 

Pollutant: PM10

Averaging Time: 2 wk 

Mean (SD): Eastside 23.0 (13.5) 

Southwest 28.2 (16.1) 

Range (Min, Max): 2.9, 70.9 

PM Component: (“likely” in southwest 

site) carbon and diesel emissions 

Monitoring Stations: 2 

Copollutant: 

PM2.5 0.93 

O3 Daily mean 0.59 

O3 8-h peak 0.57 

PM Increment: 19.1 μg/m3

Lung function among children 

reporting use of maintenance CSs 

Diurnal variability FEV1

Lag 1: 1.53 [-0.85, 3.90] 

Lag 1: 2.94 [-1.07, 6.96] PM10 + O3

Lag 2: 5.32 [0.32, 10.33] 

Lag 2: 13.73 [8.23, 19.23] PM10 + O3

Lag 3-5: 1.46 [-2.21,5.13] 

Lag 3-5: 3.30 [0.58, 6.02] PM10 + O3

Lowest daily value FEV1

Lag 1: -0.28 [-2.34, 1.77] 

Lag 1: -6.25 [-11.15 to -1.36] PM10 + O3

Lag 2: -2.21 [-3.97 to -0.46] 

Lag 2: -5.97 [-11.06 to -0.87] PM10 + O3

Lag 3-5: -2.58 [-7.65, 2.49] 

Lag 3-5: 1.98 [-0.38, 4.33] PM10 + O3

Lung function among children 

reporting presence of URI on day of 

lung function assessment 

Diurnal variability FEV1

Lag 1: 3.51 [-4.52,11.55] 

Lag 1: 3.21 [-1.28,7.71] PM10 + O3

Lag 2: 1.12 [-4.62, 6.86] 

Lag 2: 5.40 [-0.82, 11.62] PM10 + O3

Lag 3-5: 3.90 [0.34, 7.47] 

Lag 3-5: 6.27 [0.07, 12.47] PM10 + O3

Lowest daily value FEV1

Lag 1: -2.72 [-9.47, 4.03] 

Lag 1: -13.11 [-21.59 to -4.62] PM10 + 

O3

Lag 2: 0.24 [-5.10, 4.63] 

Lag 2: -3.32 [-6.83, 0.18] PM10 + O3

Lag 3-5: -4.48 [-8.36, 0.60] 

Lag 3-5: -3.17 [-5.82 to -0.51] PM10 + O3

December 2009 E-156 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mar et al. (2004, 057309) 

Period of Study: 1997-1999 

Location: Spokane, Washington 

Outcome: Respiratory symptoms 

Age Groups: Adults: Ages 20-51 yr 

Children: Ages 7-12 yr 

Study Design: Time-series 

N: 25 people 

Statistical Analyses: Logistic 

regression 

Covariates: Temperature, relative 

humidity, day of-the-wk 

Statistical Package: STATA 6 

Lags Considered: 0-2 days 

Pollutant: PM10

Mean (SD): 

1997: 24.5 (18.5) 

1998: 20.6 (12.3) 

1999: 16.8 (8.0) 

Monitoring Stations: 1 station 

Copollutant (correlation): 

PM10

PM1: r = 0.48 

PM2.5: r = 0.61 

PM10-2.5: r = 0.93 

PM Increment: 10 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 

Adult Respiratory symptoms: 

Wheeze: 1.01[0.93, 1.09] lag 0 

0.98[0.91, 1.06] lag 1 

0.99[0.92, 1.06] lag 2 

Breath: 1.02[0.96, 1.08] lag 0 

1.01[0.97, 1.06] lag 1 

1.02[0.97, 1.06] lag 2 

Cough: 0.96[0.88, 1.05] lag 0 

0.97[0.90, 1.04] lag 1 

0.98[0.92, 1.05] lag 2 

Sputum: 1.01[0.92, 1.12] lag 0 

0.99[0.91, 1.08] lag 1 

1.00[0.93, 1.08] lag 2 

Runny Nose: 0.98[0.93, 1.04] lag 0 

0.97[0.93, 1.02] lag 1; 0.97[0.94, 1.01] 

lag 2 

Eye Irritation: 0.97[0.87, 1.08] lag 0 

0.97[0.88, 1.06] lag 1 

0.97[0.91, 1.04] lag 2 

 

Lower Symptoms: 0.96[0.91, 1.02] 

lag 0 

0.95[0.89, 1.00] lag 1 

0.95[0.90, 1.00] lag 2 

Any Symptoms: 0.97[0.93, 1.02] lag 0 

0.96[0.91, 1.00] lag 1 

0.95[0.91, 0.99] lag 2 

Children Respiratory symptoms: 

Wheeze: 0.92[0.71, 1.18] lag 0 

0.89[0.64, 1.24] lag 1 

0.95[0.69, 1.31] lag 2 

Breath: 1.04[0.95, 1.15] lag 0 

1.04[0.95, 1.15] lag 1 

1.06[0.95, 1.19] lag 2 

Cough: 1.09[1.02, 1.16] lag 0 

1.08[1.02, 1.14] lag 1 

1.10[1.02, 1.18] lag 2 

Sputum: 1.08[0.98, 1.17] lag 0 

1.07[0.98, 1.17] lag 1 

1.07[0.98, 1.16] lag 2 

Runny Nose: 1.08[1.00, 1.16] lag 0 

1.08[1.02, 1.15] lag 1 

1.08[1.02, 1.14] lag 2 

Eye Irritation: 1.06[0.74, 1.51] lag 0 

0.94[0.70, 1.26] lag 1 

0.99[0.88, 1.12]lag 2 

Lower Symptoms: 1.07[1.00, 1.14] 

lag 0 

1.06[0.98, 1.15] lag 1 

1.07[0.95, 1.19] lag 2 

Any Symptoms: 1.07[1.02, 1.11] lag 0 

1.09[1.03, 1.15] lag 1 

1.10[1.03, 1.17] lag 2 

December 2009 E-157 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mar et al. (2005, 087566) 

Period of Study: 1999-2001 

Location: Seattle, Washington 

Outcome: Pulmonary function (arterial 

oxygen saturation) and cardiac function 

(heart rate and blood pressure) 

Study Design: Time series 

N: 88 

Statistical Analyses: Linear logistic 

regression 

Age Groups: >57 

Pollutant: PM10 

Averaging Time: 24-h avg 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

Lag 

Indoor 

Systolic: 0.92 (-0.95, 2.78) 0 

Diastolic: 0.63 (-0.29, 1.56) 0 

Outdoor 

Systolic: -0.10 (-1.37, 1.18) 0 

Diastolic: -0.03 (-0.79, 0.73) 0 

Nephelometer 

Systolic: 0.35 (-0.91, 1.61) 0 

Diastolic: -0.12 (-0.91, 0.67) 0 

% Increase between heart rate and 

PM10 exposure for people >57 

PM10

Indoor: 0.02 (-0.54, 0.58) 0 

Outdoor: -0.48 (-1.03, 0.06) 0 

Nephelometer: -0.31 (-0.76, 0.14) 0 

Reference: McCormack et al. (2009, 

199833) 

Period of Study: Sep 2001-Apr 2004 

Location: East Baltimore, Maryland 

Outcome: Asthma symptoms 

Study Design: Panel 

Statistical Analysis: Chi-square, 

Student t-test, Negative binomial 

regression models with GEE, Logistic 

regression with GEE 

Statistical Package: StataSE 

Age Groups: Asthmatic children aged 

2-6 yr 

Pollutant: PM10-2.5, PM2.5

Averaging Time: 3 days 

Mean (SD) Unit: 

PM10-2.5: 17.4 ± 21.2 μg/m3

PM2.5: 40.3 ± 35.4 μg/m3

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

Relative Risk (Min CI, Max CI) Lag 

Bivariate Models, PM10-2.5 

Cough, wheezing, chest tightness: 

1.05 (0.99-1.10), p = 0.08 

Slow down: 1.08 (1.03-1.13). p < 0.01 

Symptoms with running: 

1.03 (0.97-1.09). p = 0.39 

Nocturnal symptoms: 

1.06 (1.01-1.11), p = 0.03 

Limited speech: 

1.11 (1.05-1.18), p < 0.01 

Rescue medication use: 

1.06 (1.02-1.11), p < 0.01 

Bivariate Models, PM2.5 

Cough, wheezing, chest tightness: 

1.01 (0.98-1.05), p = 0.41 

Slow down: 1.00 (0.97-1.04), p = 0.85 

Symptoms with running: 

1.04 (1.01-1.07), p = 0.14 

Nocturnal symptoms: 

1.02 (0.98-1.05), p = 0.37 

Limited speech: 

1.01 (0.95-1.07), p = 0.33 

Rescue medication use: 

1.03 (1.00-1.60), p = 0.06 

Multivariate Models, PM10-2.5 

Cough, wheezing, chest tightness: 1 

.06 (1.01-1.12), p = 0.02 

Slow down: 1.08 (1.02-1.14), p = 0.01 

Symptoms with running: 

1.00 (0.94-1.08), p = 0.81 

Nocturnal symptoms: 

1.08 (1.01-1.14), p = 0.02 

Limited speech: 

1.11 (1.03-1.19), p < 0.01 

Rescue medication use: 

1.06 (1.01-1.10), p = 0.02 

Multivariate Models, PM2.5 

Cough, wheezing, chest tightness: 

1.03 (0.99-1.07), p = 0.18 

Slow down: 

1.04 (1.00-1.09), p = 0.06 

Symptoms with running: 

1.07 (1.02-1.11), p < 0.01 

Nocturnal symptoms: 

1.06 (1.01-1.10), p = 0.01 

Limited speech: 

1.07 (1.00-1.14), p = 0.04 

Rescue medication use: 

1.04 (1.01-1.08), p = 0.04 

December 2009 E-158 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mortimer et al. (2008, 

187280) 

Period of Study: 1989-2000 

Location: Joaquin Valley, California 

Outcome: Respiratory Symptoms, 

Decreased lung function 

Study Design: Time series 

Statistical Analyses: 

Deletion/Substitution/ Addition algorithm 

(GEE) 

Logistic linear regression 

Age Groups: 6-11 

Pollutant: PM10

Averaging Time: 24-h avg 

Copollutants (correlation): 

CO: r = 0.05 

NO2: r = 0.30 

O3: r = 0.39 

Increment: NR 

β (SE): 

FVC: 

PM10 (age 0-3 yr): 0.0121 (0.0037) 

FEV1: PM10 (age 0-3 yr): 0.0102 

(0.0034) 

PEF: 

PM10 (Mother smoked during 

pregnancy): 

-0.0102 (0.0039) 

Reference: Mortimer et al. (2002, 

030281) 

Period of Study: Jun-Aug 1993 

Location: Eight urban areas of the 

U.S.: Bronx and East Harlem, NY 

Baltimore, MD 

Washington, DC 

Detroit, MI 

Cleveland, OH 

Chicago, IL 

and St. Louis, MO. 

Outcome: peak expiratory flow rate 

(PEFR) and symptoms 

Age Groups: 4-9 yr 

Study Design: Cohort study 

N: 846 children with a history of asthma 

Statistical Analyses: Mixed linear 

models and GEE 

Covariates: Day of study, previous 12-

h mean temperature, urban area, diary 

number, rain in the past 24 h

Season: Summer 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 1-

5 avg, 1-4 avg, 0-4 avg, 0-3 avg 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 53 

Monitoring Stations: NR 

Copollutant (correlation): 

8-h avg O3: r = 0.51 

PM Increment: 20 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

(RR estimates are odds ratios for 

incidence of morning asthma symptoms 

using the avg of lag 1-2) 

3 urban areas (DE, CL, CH) 

Single pollutant: OR = 1.26 (1.00-1.59) 

O3+PM10: OR = 1.25 (0.97-1.61) 

O3+SO2 +NO2+PM10: OR = 1.14 (0.80-

1.48) 

Reference: Moshammer and 

Neuberger (2003, 041956) 

Period of Study: 2000-2001 

Location: Linz, Austria 

Outcome: Lung Function: FVC, FEV1, 

MEF25, MEF50, MEF75, PEF, LQ Signal, 

PAS Signal 

Age Groups: Ages 7 to 10 

Study Design: Case-crossover

N: 161 children 

1898-2120 “half-h means” 

Statistical Analyses: Correlations 

Regression Analysis 

Covariates: Morning, evening, night

Season: Spring, summer, winter, fall 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 8 h 

Daily Means 

Mean (SD): 23.13 (20.08) 

Range (Min, Max): (NR, 190.79) 

Monitoring Stations: 1 

Copollutant (correlation): 

LQ = 0.751 

PAS = 0.406 

Notes: “Acute effects of ‘active particle 

surface’ as measured by diffusion 

charging were found on pulmonary 

function (FVC, FEV1, MEF50) of 

elementary school children and on 

asthma-like symptoms of children who 

had been classified as sensitive.” 

Reference: Moshammer et al. (2006, 

090771) 

Period of Study: 2000-2001 

Location: Linz, Austria 

Outcome: Respiratory symptoms and 

decreased lung function 

Age Groups: Children ages 7-10 

Study Design: Time-series

N: 163 children 

Statistical Analyses: GEE model 

Covariates: Sex, age, height, weight 

Dose-response Investigated? NR 

Statistical Package: NR 

Lags Considered: 1 

Pollutant: PM10

Averaging Time: 8 h 

Mean (SD): 

Maximum 24 h: 76.39 

Annual avg: 19.06 

Percentiles: 

8-h mean 25th: 14.39 

8-h mean 50th(Median): 24.85 

8-h mean 75th: 38.82 

Monitoring Stations: 1 station 

Copollutant (correlation): 

PM1: r = 0.91 

PM2.5: r = 0.93 

NO2: r = 0.62 

PM Increment: 10 μg/m3

% change in Lung Function per 

10 μg/m3 

FEV: 0.11 

FVC: 0.06 

FEV0.5: -0.19 

MEF75%: -0.30 

MEF50%: -0.36 

MEF25%: 0.41 

PEF: 0.22 

% change in Lung Function per IQR 

FEV: -0.27 

FVC: -0.07 

FEV0.5: -0.47 

MEF75%: -0.74 

MEF50%: -0.86 

MEF25%: 0.98 

PEF: -0.54 

December 2009 E-159 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: Sep 1999-Mar 2000 

Location: Vienna, Austria 

Outcome: Ratio measure: Time to peak 

tidal expiratory flow divided by total 

expiration time (i.e., tidal lung function, 

a surrogate for bronchial obstruction) 

Age Groups: 3.0-5.9 yr (preschool 

children) 

Study Design: Longitudinal prospective 

cohort 

N: 56 children 

Statistical Analyses: Mixed models 

linear regression, with autoregressive 

correlation structure 

Covariates: Age, sex, respiratory rate, 

phase angle, temperature, 

kindergarten, parental education, 

observer (also in sensitivity analyses: 

height, weight, cold/sneeze on same 

day, heating with fossil fuels, hair 

cotinine, number of tidal slopes used to 

measure tidal lung function) 

Dose-response Investigated? No 

Statistical Package: SAS 8.0 

Lags Considered: 0 

Pollutant: PM10

Averaging Time: 24 h 

Copollutant (correlation): 

PM2.5 (r = 0.94) in Vienna 

PM Increment: Interquartile range (NR)

Change in mean associated with an 

IQR increase in PM (p-value) 

lag 

-1.067 (0.241) 

lag 0 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: Oct. 2000-May 2001 

Location: Linz, Austria 

Outcome: Forced oscillatory resistance 

(at zero Hz), FVC, FEV1, MEF25, MEF50, 

MEF75, PEF 

Age Groups: 7-10 yr 

Study Design: Longitudinal prospective 

cohort 

N: 164 children 

Statistical Analyses: Mixed models 

linear regression with autoregressive 

correlation structure 

Covariates: sex, time and individual

Season: Oct-May 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-7 

Pollutant: PM10

Averaging Time: 24 h 

Monitoring Stations: 1 

PM Increment: 1 μg/m3

Notes: No significant associations 

between PM10 and the metrics of lung 

function were reported. The authors 

state they only reported significant 

associations, so results are assumed to 

be null. 

Reference: Odajima et al. (2008, 

192005)

Period of Study: Apr 2003-Mar 2004 

Location: Fukuoka, Japan 

Outcome: PEF 

Study Design: Panel/Field 

Statistical Analysis: GEE 

Statistical Package: SAS 

Covariates: Age, sex, growth index, 

temperature, NO2, O3

Age Groups: Asthmatic children, 4-11 

yr old 

Pollutant: PM10

Averaging Time: 3 h 

Mean (SD) Unit: 

Warmer months, 5-8 am 

SPM: 40.7 μg/m3

NO2: 15.2 ppb 

O3: 17.7 ppb 

Warmer months, 7-10pm 

SPM: 41.5 μg/m3

NO2: 20.0 ppb 

O3: 28.1 ppb 

Colder months, 5-8am 

SPM: 32.6 μg/m3

NO2: 20.5 ppb 

O3: 17.5 ppb 

Colder months, 7-10pm 

SPM: 34.7 μg/m3

NO2: 28.0 ppb 

O3: 19.4 ppb 

Range (Min, Max): 

Increment: 10 μg/m3

Relative Risk (Min CI, Max CI) 

Lag 

Apr-Sep, morning sample, multipollutant:: 

SPM, 5am-8am: -0.6 (-1.228, 0.028) 

SPM, 2am-5am: -0.78 (-1.399, -0.161) 

SPM, 11pm-2am: -0.612 (-1.180, -

0.045) 

SPM, 8pm-11am: -0.732 (-1.318, -

0.145) 

O3, 5am-8am: -0.575 (-1.569, 0.419) 

O3, 2am-5am: -0.052 (-0.997, 0.893) 

O3, 11pm-2am: -0.305 (-1.269, 0.658) 

O3, 8pm-11am: -0.416 (-1.283, 0.451) 

NO2, 5am-8am: -0.3 (-2.246, 1.645) 

NO2, 2am-5am: 0.265 (-1.354, 1.885) 

NO2, 11pm-2am: -0.187 (-1.447, 1.073) 

NO2, 8pm-11am: 0.432 (-0.689, 1.553) 

Single-pollutant model: 

SPM, 5am-8am: -0.67 (-1.236, -0.104) 

SPM, 2am-5am: -0.761 (-1.328, -0.194) 

SPM, 11pm-2am: -0.661 (-1.159, -

December 2009 E-160 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Warmer months, 5-8am 

SPM: (11.0, 126.0) 

NO2: (1.3, 44.7) 

O3: (0.3, 52.3) 

Warmer months, 7-10pm 

SPM: (8.3, 191.3) 

NO2: (3.0, 51.3) 

O3: (1.3, 71.3) 

Colder months, 5-8am 

SPM: (9.0, 160.0) 

NO2: (1.3, 44.0) 

O3: (0.6, 48.7) 

Colder months, 7-10pm 

SPM: (10.3, 131.0) 

NO2: (3.6, 49.0) 

O3: (1.0, 60.0) 

Copollutant (correlation): 

Warmer months (24-h mean): 

O3: r = 0.32 

NO2: r = 0.30 

Colder months (24-h mean): 

O3: r = -0.02 

NO2: r = 0.45 

0.163) 

SPM, 8pm-11am: -0.714 (-1.212, -

0.215) 

Evening sample, multi-pollutant model 

SPM, 7pm-10pm: -0.449 (-1.071, 0.174)

SPM, 4pm-7pm: -0.434 (-1.122, 0.254) 

SPM, 1pm-4pm: -0.415 (-1.015, 0.184) 

SPM, 10am-1pm: -0.522 (-1.199, 0.155)

O3, 7pm-10pm: -0.22 (-1.171, 0.731) 

O3, 4pm-7pm: -0.118 (-0.809, 0.574) 

O3, 1pm-4pm: -1.086 (-0.888, 0.516) 

O3, 10am-1pm: -0.315 (-1.123, 0.493) 

NO2, 7pm-10pm: 0.296 (-0.806, 1.397) 

NO2, 4pm-7pm: 0.220 (-0.818, 1.258) 

NO2, 1pm-4pm: 0.438 (-0.568, 1.444) 

NO2, 10am-1pm: 0.536 (-0.546, 1.617) 

Single-pollutant model: 

SPM, 7pm-10pm: -0.449 (-0.956, 0.058)

SPM, 4pm-7pm: -0.449 (-1.029, 0.131) 

SPM, 1pm-4pm: -0.414 (-0.943, 0.115) 

SPM, 10am-1pm: -0.486 (-1.051, 0.079)

Oct-Mar, morning sample, multipollutant:: 

SPM, 5am-8am: 0.290 (-0.279, 0.859) 

SPM, 2am-5am: 0.431 (-0.173, 1.036) 

SPM, 11pm-2am: 0.304 (-0.311, 0.919) 

SPM, 8pm-11am: 0.010 (-0.523, 0.543) 

O3, 5am-8am: -0.415 (-1.568, 0.738) 

O3, 2am-5am: -0.046 (-1.245, 1.153) 

O3, 11pm-2am: 0.004 (-1.265, 1.273) 

O3, 8pm-11am: -0.470 (-2.017, 1.077) 

NO2, 5am-8am: -0.319 (-2.269, 1.631) 

NO2, 2am-5am: 0.262 (-1.777, 2.300) 

NO2, 11pm-2am: 0.609 (-1.132, 2.350) 

NO2, 8pm-11am: 0.155 (-1.545, 1.856) 

Single-pollutant model: 

SPM, 5am-8am: 0.308 (-0.189, 0.805) 

SPM, 2am-5am: 0.485 (-0.026, 0.996) 

SPM, 11pm-2am: 0.486 (-0.049, 1.022) 

SPM, 8pm-11am: 0.100 (-0.414, 0.613) 

Evening Sample, Multi-pollutant Model 

SPM, 7pm-10pm: 0.059 (-0.397, 0.515) 

SPM, 4pm-7pm: 0.360 (-0.093, 0.812) 

SPM, 1pm-4pm: 0.357 (-0.157, 0.871) 

SPM, 10am-1pm: 0.169 (-0.394, 0.731) 

O3, 7pm-10pm: -0.656 (-2.394, 1.083) 

O3, 4pm-7pm: 0.046 (-1.140, 1.232) 

O3, 1pm-4pm: 0.164 (-1.038, 1.365) 

O3, 10am-1pm: 0.665 (-0.613, 1.942) 

NO2, 7pm-10pm: -0.415 (-2.444, 1.613) 

NO2, 4pm-7pm: -0.144 (-1.490, 1.202) 

NO2, 1pm-4pm: -0.181 (-1.821, 1.459) 

NO2, 10am-1pm: 0.194 (-1.503, 1.890) 

Single-pollutant model : 

SPM, 7pm-10pm: 0.071 (-0.388, 0.529) 

SPM, 4pm-7pm: 0.318 (-0.123, 0.758) 

SPM, 1pm-4pm: 0.317 (-0.171, 0.804) 

SPM, 10am-1pm: 0.112 (-0.412, 0.636) 

December 2009 E-161 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peacock et al. (2003, 

042026) 

Period of Study: Nov 1996-Feb 1997 

Location: Southern England 

Outcome: Reduced peak expiratory 

flow rate (PEFR) 

Age Groups: 7-13 yr 

Study Design: Time-series 

N: 179 

Statistical Analyses: GEE, multiple 

regression 

Covariates: Day of the week, 24-h 

mean outside temperature.

Season: Winter 

Dose-response Investigated? No 

Statistical Package: STATA 

Lags Considered: Same day, lag 1, lag 

2, 5-day ma 

Pollutant: PM10 

Averaging Time: Daily 

Mean (SD): 

Rural (nationally validated) 21.2 (11.3) 

Rural (locally validated) 18.7 (11.3) 

Urban 1 18.4 (9.8) 

Urban 2 22.7 (10.6) 

Percentiles: 

10th 

Rural (nationally validated) 11.0 

Rural (locally validated) 9.0 

Urban 1 10.5 

Urban 2 12.5 

90th 

Rural (nationally validated) 33.0 

Rural (locally validated) 32.5 

Urban 1 32.0 

Urban 2 36.0 

Range (Min, Max): 

Rural (nationally validated) 7.0, 82.0 

Rural (locally validated) 6.6, 87.9 

Urban 1 4.7, 62.8 

Urban 2 6.7, 63.7 

Monitoring Stations: 3 

Copollutants: 

NO2

O3

SO2 

SO4

2–

Increment: 10 μg/m3

Odds Ratio (Lower CI, Upper CI) 

Lag 

Change in PEFR 

Community 

-0.04 (-0.11, 0.03) 0 

0.03 (-0.04, 0.05) 1 

-0.01 (-0.07, 0.05) 2 

-0.10 (-0.25, 0.05) 

0-4 avg 

Local 

-0.01 (-0.06, 0.03) 0 

0.04 (0.01, 0.08) 1 

0.01 (-0.04, 0.05) 2 

0.04 (-0.05, 0.13) 

0-4 avg 

20% decrease in PEFR 

All children 

1.012 (0.992, 1.031) 0 

1.016 (0.995, 1.036) 1 

1.013 (1.000, 1.025) 2 

1.037 (0.992, 1.084) 

0-4 avg 

Wheezy Children Only 

1.016 (0.986, 1.047) 0 

1.030 (1.001, 1.060) 1 

1.018 (0.995, 1.041) 2 

1.114 (1.057, 1.174) 

0-4 avg 

Reference: Peled, et al. (2005, 

156015) 

Period of Study: 5-6 wk between MarJun 1999 and Sep-Dec 1999. 

Location: Ashdod, Ashkelon and 

Sderot, Israel 

Outcome: Reduced peak expiratory 

flow (PEF) 

Age Groups: 7-10 yr 

Study Design: Nested cohort study 

N: 285 

Statistical Analyses: Time series 

analysis, generalized linear model, 

GEE, one-way ANOVA 

Covariates: seasonal changes, 

meteorological conditions and personal 

physiological, clinical and 

socioeconomic measurements

Season: Spring, fall 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM10

Averaging Time: Daily 

Mean: 

Ashkelon: 67.1 

Sderot: 52.9 

Ashdod: 31.0 

PM Component: Local industrial 

emissions, desert dust, vehicle 

emissions and emissions from two 

electric power plants 

Monitoring Stations: 6 

Copollutant: PM2.5

PM Increment: 1 μg/m3

β coefficient (SE) [95% CI] 

Sderot: 

PM10 MAX: -0.34 (0.41) [-1.16, 0.46] 

PM10 MAX x sin(ω2 day): 0.84 (0.22) 

[0.405, 1.28] 

PM10 MAX x cos (ω1 day): -1.61 (0.41) 

[-2.43, 0.79] 

PM10 MAX x sin (ω1 day): 0.44 (0.120) 

[-0.68-0.21] 

In Sderot, an interaction between PM10

and the sequential day were 

significantly associated with PEF. 

Reference: Pitard, et al. (2004, 

087433) 

Period of Study: 732 days (Jul 

1998-Jun 2000) 

Location: City of Rouen, France 

Outcome: Respiratory drug sales 

Age Groups: 0-14, 15-64, 65-74, over 

75 yr 

Study Design: Ecological time-series 

N: 106,592 

Statistical Analyses: Generalized 

additive model 

Covariates: Days of the weeks, trend, 

seasonal variations, influenza 

epidemics, meteorological variables, 

holidays 

Dose-response Investigated? No 

Statistical Package: S-plus 

Lags Considered: 0 to 10 days 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD): 16.7 (13.3) 

Percentiles: 

25th: 8.00 

50th(Median): 13.0 

75th: 20 

Range (Min, Max): 2.00, 126

Monitoring Stations: 2 

Copollutant (correlation): 

SO2 (0.39) 

NO2 (0.61) 

PM Increment: 10 μg/m3

Percent increase in sales of antiasthmatics and bronchodilators (Lower 

CI, Upper CI) 

lag: 

6.2 (2.4, 10.1) 

lag 10 days 

Percent increase in sales of cough and 

cold preparation for children under 15 yr 

of age (Lower CI, Upper CI) 

lag: 

9.2 (5.9, 12.6) 

10 days 

December 2009 E-162 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Preutthipan et al. (2004, 

055598) 

Period of Study: 31 days (school 

days) from Jan-Feb 1999 

Location: Mae Pra Fatima School, 

central Bangkok, Thailand 

Outcome: Decreases in peak 

expiratory flow rates (PEFR), 

respiratory symptoms including wheeze, 

shortness of breath, runny/stuffed nose, 

sneezing, cough, phlegm, and sore 

throat 

Age Groups: Third to ninth grade 

Study Design: Time- Series 

N: 133 children (93 asthmatics, 40 

nonasthmatics) 

Statistical Analyses: For continuous 

data, an unpaired t-test or MannWhitney U test was used. For 

categorical data, the chi-square test or 

Fisher’s exact test was used. One-way 

analysis of covariance (ANCOVA) was 

used to compare avg daily reported 

respiratory symptoms, diurnal PEFR 

variability, and the prevalence of PEFR 

decrements between groups of days. 

Covariates: Age, sex, weight, height, 

parents smoking, person smoking in 

home, daily number of household 

cigarettes, air-conditioned bedroom, 

fuel used for cooking (charcoal, gas), 

distance from home to main road 

Dose-response Investigated? No 

Lags Considered: Up to 5 days 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD): 111.0 (39) 

Range (Min, Max): 46, 201 

Monitoring Stations: 1 

Copollutant: 

SO2 

CO 

O3

PM Increment: Authors classified 

exposure according to High and Low 

PM10 days: 

High = >120 μg/m3

Low = <120 μg/m3

Daily reported respiratory symptoms 

and diurnal PEFR variability as 

classified by concurrent days with high 

vs.. low PM10

Mean % reporting (SEM) 

Asthmatics: High PM10

Wheeze/shortness of breath = 

21.3 (1.4) 

Runny/stuffed nose or sneezing = 

42.3 (1.8) 

Cough = 59.9 (1.9) 

Phlegm = 60.5 (2.3) 

Sore throat = 23.7 (1.5) 

Any respiratory symptoms = 72.2 (3.2) 

Diurnal PEFR variability = 3.0 (0.4) 

Asthmatics: Low PM10

Wheeze/shortness of breath = 

19.3 (1.3) 

Runny/stuffed nose or sneezing = 

35.8 (1.6) 

Cough = 59.1 (1.6) 

Phlegm = 58.6 (2.0) 

Sore throat = 21.0 (1.4) 

Any respiratory symptoms = 63.8 (2.8) 

Diurnal PEFR variability = 2.8 (0.3) 

Nonasthmatics: High PM10

Wheeze/shortness of breath = 

11.7 (1.4) 

Runny/stuffed nose or sneezing = 

40.9 (2.5) 

Cough = 50.4 (2.6) 

Phlegm = 50.2 (2.5) 

Sore throat = 27.1 (1.7) 

Any respiratory symptoms = 67.8 (3.7) 

Diurnal PEFR variability = 2.4 (0.4) 

Nonasthmatics: Low PM10

Wheeze/shortness of breath = 9.3 (1.2) 

Runny/stuffed nose or sneezing = 

33.1 (2.2) 

Cough = 54.0 (2.2) 

Phlegm = 49.9 (2.2) 

Sore throat = 23.9 (1.5) 

Any respiratory symptoms = 56.4 (3.2) 

Diurnal PEFR variability = 2.1 (0.4) 

Notes: None of the daily reported 

respiratory symptoms had significant 

direct correlations with daily PM10

levels, according to the authors. 

December 2009 E-163 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rabinovitch et al. (2004, 

096753) 

Periods of Study: Nov 1999-Mar 2000 

Nov 2000-Mar 2001 

Nov 2001-Mar 2002 

Location: Denver, Colorado 

Outcome: Respiratory symptoms, 

Asthma symptoms (cough and 

wheeze), Upper respiratory symptoms 

Study Design: Time-series panel 

Statistical Analyses: Logistic linear 

regression

Age Groups: 6-12 

Pollutants: PM10

Averaging Time: 24-h avg 

Mean (SD): 28.1 (13.2) 

Range (Min, Max): 

(6.0, 102.0) 

Copollutant: 

CO 

NO2

SO2 

O3

Increment: 1 μg/m3

β (SE) 

AM: -0.010 (0.008) 

PM: -0.011 (0.010) 

Odds Ratio (Lower CI, Upper CI) 

Lag 

1.016 (0.911, 1.133) 

0-3 avg. 

OR for respiratory symptoms and PM10

exposure for children age 6-12 

Asthma exacerbation: 

1.00 (0.75, 1.25) 0-3 avg 

Medication: 0.85 (0.75, 0.95) 0-3 avg 

Previous night’s symptoms: 

1.10 (1.00, 1.20) 0-3 avg 

Current day’s symptoms: 

1.00 (0.90, 1.10) 0-3 avg 

% Increase (Lower CI, Upper CI) 

Lag 

% Increase in FEV1 or PEF and PM10

exposure for children age 6-12 

AM FEV1: -0.01 (-0.02, 0.01) 0-3 avg 

PM FEV1: -0.02 (-0.03, 0.02) 0-3 avg 

AM PEF: -0.025 (-0.035, 0.02) 0-3 avg 

PM PEF: 0.00 (-0.03, 0.03) 0-3 avg. 

Reference: Renzetti et al. (2009, 

199834) 

Period of Study: Jun 2006-Jul 2006 

Location: Pescara and Ovindoli, Italy 

Outcome: Airway inflammation and 

function 

Study Design: Panel 

Covariates: NR 

Statistical Analysis: Student T-test, 

Pearson’s correlation coefficients 

Statistical Package: StatView 

Age Groups: Children, mean age 

9.9 yr 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD) Unit: 

Urban: 56.9 ± 13.1 μg/m3

Rural: 13.8 ± 5.6 μg/m3

Copollutant (correlation): NR 

All results are presented in Fig format. 

December 2009 E-164 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rojas-Martinez et al. (2007, 

091064) 

Period of Study: 1996-1999 

Location: Mexico City, Mexico 

Outcome: Lung function: FEV1, FVC, 

FEF25-75% 

Age Groups: Children 8 yr old at time 

of cohort recruitment 

Study Design: School-based “dynamic” 

cohort study 

N: 3170 children 

14,545 observations 

Statistical Analyses: Three-level 

generalized linear mixed models with 

unstructured variance-covariance matrix

Covariates: Age, body mass index, 

height, height by age, weekday spent 

outdoors, environmental tobacco 

smoke, previous-day mean air pollutant 

concentration, time since first test 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 days 

Pollutant: PM10

Averaging Time: 24 h, 6 mo 

Mean (SD): 24-h averaging 

Tlalnepantla: 66.7 (35.6) 

Xalostoc: 96.7 (49.4) 

Merced: 79.3 (40.8) 

Pedregal: 53.4 (31.9) 

Cerro de la Estrella: 69.6 (35.3) 

6-mo averaging 

Mean: 75.6 

Percentiles: 6-mo averaging 

25th: 55.8 

50th(Median): 67.5 

75th: 92.2 

Monitoring Stations: 5 sites for PM10, 

10 for other pollutants 

Copollutant: 

O3

NO2

PM Increment: IQR 

PM10, 6-LC: 36.4 

GIRLS 

One-pollutant model 

FVC: -39 [-47: -31] 

FEV: -29 [-36: -21] 

FEF25-75%: -17 [-36: 1] 

FEV1/FVC: 0.12 [0.07: 0.17] 

Two-pollutant model 

PM10, 6-LC & O3

FVC: -30 [-39: -22] 

FEV: -24 [-31: -16] 

FEF25-75%: -9 [-26: 9] 

FEV1/FVC: 0.10 [0.06: 0.15] 

PM10, 6-LC & NO2

FVC: -21 [-30: -13] 

FEV: -17 [-25: -8] 

FEF25-75%: -23 [-43: -4] 

FEV1/FVC: 0.07 [0.02: 0.13] 

Multipollutant model 

PM10, 6-LC, O3, & NO2

FVC: -14 [-23: -5] 

FEV: -11 [-20: -3] 

FEF25-75%: -7 [-27: 12] 

FEV1/FVC: 0.08 [0.03: 0.13] 

BOYS 

One-pollutant model 

FVC: -33 [-41: -25] 

FEV: -27 [-34: -19] 

FEF25-75%: -18 [-34: -2] 

FEV1/FVC: 0.04 [-0.01: 0.09] 

Two-pollutant model 

PM10, 6-LC & O3

FVC: -28 [-36: -19] 

FEV: -22 [-30: -15] 

FEF25-75%: -10 [-27: 7] 

FEV1/FVC: 0.04 [-0.01: 0.09] 

PM10, 6-LC & NO2

FVC: -16 [-26: -7] 

FEV: -19 [-27: -10] 

FEF25-75%: -26 [-44: -9] 

FEV1/FVC: 0.005 [-0.06: 0.05] 

Multipollutant model 

PM10, 6-LC, O3, & NO2

FVC: -12 [-22: -3] 

FEV: -15 [-23: -6] 

FEF25-75%: -12 [-30: 6] 

FEV1/FVC: -0.002 [-0.06: 0.05] 

Long-term exposure to O3, PM10, and 

NO2 is associated with decrements in 

FVC and FEV1 growth in Mexico City 

schoolchildren. In a multipollutant 

model, PM10 (-12%), O3 (-9%), and NO2

(-41%) each contribute independently 

and statistically significantly to 

diminished FVC growth. For FEV1, 

however, the multipollutant model 

indicates that only PM10 (-15%) and 

NO2 (-25%) each contribute 

independently and statistically 

significantly to diminished FEV1 growth. 

December 2009 E-165 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sahsuvaroglu et al. (2009, 

190983) 

Period of Study: 1994-1995 

Location: Hamilton, Canada 

Outcome: Asthma symptoms 

Study Design: Panel 

Covariates: Neighborhood income, 

dwelling value, state of housing, 

deprivation index, smoking 

Statistical Analysis: Logistic 

regressions 

Statistical Package: SPSS 

N: 6388 

Age Groups: 

Children in grades 1 and 8 

Pollutant: PM10

Averaging Time: 3-yr avg 

Avg: 

All Subjects: 20.90 μg/m3

Boys: 20.88 μg/m3

Girls: 20.92 μg/m3 

Range: 

All Subjects: 26.98 

Boys: 26.98 

Girls: 20.10 

Copollutant (correlation): 

NOXTheissen: 0.083 

SO2Theissen: -0.021 

O3Theissen: -0.251 

NO2Kriged: 0.126 

NO2LUR: 0.072 

Increment: NR 

Odds Ratio (95%CI) for copollutant 

model PM10Spline and NO2LUR 

All Girls: 1.063 (0.969-1.666) 

Older Girls: 1.058 (0.918-1.219) 

Odds Ratio (95%CI) for copollutant 

model PM10Spline and NO2LUR, 

SO2Theissen and O3Theissen 

All Girls: 1.045 (0.943-1.158) 

Older Girls: 1.044 (0.891-1.225) 

Regression coefficients (95%CI) 

between non-allergic asthma and 

PM10Spline exposure 

All Children: 1.043 (0.996-1.092) 

Younger Children: 1.011 (0.929-1.100) 

Older Children: 1.073 (1.013-1.136) 

All Girls: 1.069 (0.999-1.144) 

All Boys: 1.024 (0.962-1.091) 

Younger Girls: 1.065 (0.943-1.203) 

Younger Boys: 0.962 (0.853-1.085) 

Older Girls: 1.072 (0.984-1.169) 

Older Boys: 1.075 (0.995-1.160) 

Reference: Sanchez-Carrillo et al. 

(2003, 098428) 

Period of Study: 1996-1997 

Location: metropolitan Mexico City, 

Mexico 

Outcome: Upper respiratory symptom 

indicator (wet cough, sore throat, 

hoarseness, nose dryness, and head 

cold); Lower respiratory symptom 

indicator (dry cough, lack of air, and 

chest sounds); and Ocular symptom 

indicator (eye irritation, eye itch, eye 

burning, teary eyes, red eyes, and eye 

infection) 

Age Groups: All ages 

Study Design: Cohort

N: 151,418 interviews 

Statistical Analyses: Logistic 

regression models 

Covariates: Sex, age, education, 

cigarette smoking, season, emergency 

episode mass media report, 

temperature, and relative humidity 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: 1 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Northeast: 132 (52) 

Northwest: 87 (46) 

Central: 85 (37) 

Southeast: 79 (35) 

Southwest: 55 (28) 

Range (Min, Max): 

Northeast: (34-269) 

Northwest: (10-275) 

Central: (9-319) 

Southeast: (14-225) 

Southwest: (12-264) 

Monitoring Stations: Up to 32 

Copollutant (correlation): 

O3: r = 0.067 

O3 8: 00-18: 00 h: r = 0.075 

SO2: r = 0.265 

NO2: r = 0.265 

Effect Estimate [Lower CI, Upper CI]: 

PM10 quartiles: 

10.04-52.62 (ref) 52.63-73.58 

Upper respiratory indicator: 

1.02 (0.99-1.06) 

Lower respiratory indicator: 

1.04 (0.99-1.09) 

Ocular indicator: 

0.99 (0.95-1.03) 73.59-101.91 

Upper respiratory indicator: 

1.07 (1.03-1.10) 

Lower respiratory indicator: 

1.09 (1.04-1.14) 

Ocular indicator: 

0.89 (0.86-0.92)101.92-318.80 

Upper respiratory indicator: 

0.93 (0.90-0.97) 

Lower respiratory indicator: 

1.03 (0.98-1.08) 

Ocular indicator: 0.84 (0.81-0.87)

Northeast - 2nd quartile 

Upper respiratory indicator: 

0.354 (0.112-1.222) 

Lower respiratory indicator: 

0.215 (0.040-1.160) 

Ocular indicator: 1.080 (0.915-1.274) 

3rd quartile 

Upper respiratory indicator: 

0.118 (0.039-0.356) 

Lower respiratory indicator: 

0.126 (0.023-0.690) 

Ocular indicator: 1.228 (0.720-2.095) 

4th quartile 

Upper respiratory indicator: 

0.095 (0.034-0.267) 

Lower respiratory indicator: 

0.119 (0.026-0.549) 

Ocular indicator: 0.878 (0.619-1.246) 

Northwest - 2nd quartile 

Upper respiratory indicator: 

0.990 (0.898-1.090) 

Lower respiratory indicator: 

1.246 (1.087-1.429) 

Ocular indicator: 1.218 (0.808-1.834) 

3rd quartile 

Upper respiratory indicator: 

1.133 (0.974-1.317) 

Lower respiratory indicator: 

1.202 (1.044-1.385) 

Ocular indicator: 

0.345 (0.125-0.951) 

4th quartile 

Upper respiratory indicator: 

December 2009 E-166 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1.019 (0.904-1.149) 

Lower respiratory indicator: 

1.344 (1.137-1.589) 

Ocular indicator: 1.949 (1.416-2.683) 

Central - 2nd quartile 

Upper respiratory indicator: 1.088 

(1.002-1.183) 

Lower respiratory indicator: 

1.046 (0.930-1.176) 

Ocular indicator: 1.220 (1.115-1.335) 

3rd quartile 

Upper respiratory indicator: 

1.054 (0.977-1.137) 

Lower respiratory indicator: 

1.055 (0.948-1.175) 

Ocular indicator: 1.049 (0.965-1.142) 

4th quartile 

Upper respiratory indicator: 

0.899 (0.826-0.979) 

Lower respiratory indicator: 

0.952 (0.845-1.073) 

Ocular indicator: 0.875 (0.796-0.963) 

Southeast - 2nd quartile 

Upper respiratory indicator: 

0.778 (0.575-1.052) 

Lower respiratory indicator: 

1.047 (0.916-1.196) 

Ocular indicator: 0.460 (0.299-0.708) 

3rd quartile 

Upper respiratory indicator: 

1.297 (1.127-1.491) 

Lower respiratory indicator: 

1.391 (1.131-1.711) 

Ocular indicator: 0.474 (0.314-0.715) 

4th quartile 

Upper respiratory indicator: 

0.893 (0.812-0.983) 

Lower respiratory indicator: 

0.937 (0.818-1.073) 

Ocular indicator: 0.314 (0.182-0.542) 

Southwest - 2nd quartile 

Upper respiratory indicator: 

0.987 (0.913-1.066) 

Lower respiratory indicator: 

2.181 (1.177-4.040) 

Ocular indicator: 1.026 (0.928-1.135) 

3rd quartile 

Upper respiratory indicator: 

0.673 (0.673-1.886) 

Lower respiratory indicator: 

0.899 (0.790-1.024) 

Ocular indicator: 1.017 (0.862-1.200) 

4th quartile 

Upper respiratory indicator: 

0.524 (0.524-1.787) 

Lower respiratory indicator: 

4.346 (0.917-20.606) 

Ocular indicator: 0.187 (0.090-0.387) 

December 2009 E-167 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Schildcrout et al. (2006, 

089812) 

Period of Study: Nov 1993-Sep 1995 

Location: 

Albuquerque, New Mexico 

Baltimore, Maryland 

Boston, Massachusetts 

Denver, Colorado 

San Diego, California 

Seattle, Washington 

St. Louis, Missouri 

Toronto, Ontario, Canada 

Outcome: Asthma Symptoms, Rescue 

Inhaler Uses 

Age Groups: 5-12 yr 

Study Design: Meta-analysis of CAMP

N: 990 children 

Statistical Analyses: “Working 

independence covariance structure” 

Logistic Regression 

Poisson Regression 

“GEE Procedure” 

Covariates: Season, age, raceethnicity, annual family income, day of 

the week 

Dose-response Investigated? 

Statistical Package: SAS 8.2 

R 

Lags Considered: 0 day lag, 1 day lag, 

2 day lag, 3-day moving sum 

Pollutant: PM10

Averaging Time: 24-h avg 

Seattle: Daily 

Albuquerque: Daily 

Baltimore: 50% of study days measured

Boston: 23% of study days measured 

Denver: 37% of study days measured 

San Diego: 24% of study days 

measured 

St. Louis: 19% of study days measured 

Toronto: 47% of study days measured 

Percentiles: 

10th: 6.8-14.0 

25th: 12.0-22.4 

50th(Median): 17.7-32.4 

75th: 26.2-42.7 

90th: 32.5-53.9 

Monitoring Stations: 1-12 

Copollutant (correlation): 

NO2 r = 0.26-0.64 

SO2 r = 0.31-0.65 

O3 r = 0.03-0.73 

CO r = 0.24-0.88 

PM Increment: 25 μg/m3

One-pollutant model 

Asthma Symptoms: 

1.02 [0.94, 1.11] 0 

1.01 [0.97, 1.06] 1 

1.02 [0.98, 1.07] 2 

1.01 [0.98, 1.05] 

3-day moving sum 

Rescue Inhaler Uses: 

[0.97, 1.05] 0 

[0.97, 1.05] 1 

1.00 [0.97, 1.03] 2 

1.01 [0.98, 1.03] 

3-day moving sum 

Two-pollutant model 

Asthma Symptoms: 

CO-PM10

1.08 [1.01, 1.15] 0 

1.06 [0.99, 1.14] 1 

1.08 [1.02, 1.14] 2 

1.05 [1.01, 1.08] 

3-day moving sum 

NO2

–

 PM10

1.06 [0.99, 1.13] 0 

1.04 [0.97, 1.11] 1 

1.08 [1.02, 1.15] 2 

1.04 [1.00, 1.07] 

3-day moving sum 

SO2-PM10

1.05 [0.98, 1.13]; 0 

1.04 [0.96, 1.14] 1 

1.05 [0.98, 1.12] 2 

1.04 [0.99, 1.08] 

3-day moving sum 

Rescue Inhaler Uses: 

CO-PM10

1.06 [0.99, 1.13] 0 

1.05 [0.99, 1.11] 1; 

1.05 [1.01, 1.09] 2 

1.03 [1.00, 1.07] 

3-day moving sum 

NO2

–

 PM10

1.03 [0.97, 1.08] 0 

1.03 [0.98, 1.08] 1 

1.04 [1.00, 1.09] 2 

1.02 [1.00, 1.05] 

3-day moving sum 

SO2-PM10

1.01 [0.95, 1.07] 0 

1.02 [0.97, 1.07] 1 

1.03 [0.98, 1.09] 2 

1.02 [0.98, 1.05] 

3-day moving sum 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-168 
Table E-10. Short-term exposure - respiratory morbidity outcomes - PM10-2.5. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Aekplakorn et al. 

(2003, 089908) 

Period of Study: 107 days, 

Oct 1997-Jan 1998 

Location: Mae Mo district, 

Lampang Province, north 

Thailand 

Outcome: Upper respiratory 

symptoms, lower respiratory 

symptoms, cough 

Age Groups: 6-14 yr 

Study Design: Logistic regression 

N: 98 asthmatic school children 

Statistical Analyses: Generalized 

Estimating Equations, stratified 

analysis, PROC GENMOD 

Covariates: Temperature and relative 

humidity 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: SAS v 8.1 

Pollutant: PM10-2.5

Averaging Time: Daily 

Mean (SD): NR 

Range (Min, Max): NR 

Monitoring Stations: 3 

Copollutant: PM10, SO2 

PM Increment: 10 μg/m3 

Odds Ratios [Lower CI, Upper CI] lag: 

Asthmatics: 

URS: 1.04 (0.93, 1.17) lag 0 

LRS: 1.09 (0.95, 1.26) lag 0 

Cough: 1.08 (0.96, 1.21) lag 0 

Non-Asthmatics: 

URS: 1.05 (0.99, 1.19) lag 0 

LRS: 0.90 (0.72, 1.11) lag 0 

Cough: 0.95 (0.81, 1.11) lag 0 

December 2009 E-169 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bourotte et al. 

(2007, 150040) 

Period of Study: 

May 2002-Jul 2002 

Location: Sao Paulo, Brazil 

Outcome: Peak expiratory flow (PEF) 

Age Groups: Avg age 39.8 ± 12.3 yr 

Study Design: Cross-sectional 

N: 33 patients 

Statistical Analyses: Linear mixedeffects model 

Covariates: Gender, Age, BMI, Air 

Pollutants, Ambient temperature, 

Relative Humidity 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: S-plus 

Lags Considered: 2-day lag, 3-day 

lag 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 21.7 (12.9) μg/m3

Range (Min, Max): (4.13, 62.0) 

Components: 

Na+ 

K+

 

Mg2+

 

Ca2+ 

Finf 

ClNO3

–

SO4

2–

Monitoring Stations: 1 

PM Increment: NR 

Effect [Lower CI, Upper CI] lag: 

Morning PEF 

Na+

 concurrent day = -0.454 (-1.605, 0.697) 

Na+

 2-day lag = -0.907 (-2.288, 0.474) 

Na+

 3-day lag = -1.361 (-2.972, 0.251) 

K+ concurrent day = 1.685 (-0.492, 3.862) 

K+

 2-day lag = 1.838 (-1.272, 4.984) 

K+

 3-day lag = 2.604 (-0.812, 6.025) 

Mg2

+

 concurrent day = 2.265* (-0.427, 4.956) 

Mg2

+

 2-day lag = 1.271 (-1.869, 4.410) 

Mg2

+ 3-day lag = 0.939 (-2.425, 4.303) 

Ca2

+

 concurrent day = 5.491* (2.558, 8.424) 

Ca2

+

 2-day lag = 6.358* (2.251, 10.465) 

Ca2

+

 3-day lag = 6.069 (1.962, 10.176) 

Finf concurrent day = 1.572 (-0.792, 3.935) 

Finf 2-day lag = 1.630 (-1.679, 4.939) 

Fin 3-day lag = 2.736* (-1.754, 7.226) f

Cl–

 concurrent day = -0.951 (-2.238, 0.336) 

Cl–

 2-day lag = -1.871 (-3.242 to -0.4997) 

Cl–

 3-day lag = -2.286* (-3.934 to -0.638)\ 

NO3

–

 concurrent day = 4.195* (-0.063, 8.452) 

NO3

–

 2-day lag = 6.292* (2.034, 10.55) 

NO3

–

 3-day lag = 7.341* (3.083, 11.60) 

SO4

2– concurrent day = 3.528 (-0.053, 7.110) 

SO4

2– 2-day lag = 4.411* (0.829, 7.991)| 

SO4

2– 3-day lag = 6.175* (2.593, 9.756) 

Evening PEF 

Na+

 concurrent day = -0.680 (-1.831, 0.471) 

Na+ 2-day lag = -1.90 (-3.316 to -0.494) 

Na+

 3-day lag = -2.336* (-3.878 to -0.794) 

K+

 concurrent day = 0.613 (-1.564, 2.790) 

K+ 2-day lag = 0.613 (-2.497, 3.723) 

K+

 3-day lag = 0.000 (-3.421, 3.421)| 

Mg2+ concurrent day = -0.718 (-3.522, 2.085) 

Mg2+ 2-day lag = -1.933 (-5.073, 1.206) 

Mg2+ 3-day lag = -3.591 (-7.056 to -0.126) 

Ca2+ concurrent day = 2.312* (-1.208, 5.832) 

Ca2+ 2-day lag = 2.023 (-2.084, 6.130) 

Ca2+ 3-day lag = 0.578 (-3.530, 4.685) 

Finf concurrent day = -1.281 (-3.644, 1.083) 

Finf 2-day lag = -2.503 (-5.930, 0.924) 

Fin 3-day lag = -4.540 (-9.149, 0.068) f

Cl–

 concurrent day = -0.317 (-1.604, 0.970) 

Cl– 2-day lag = -1.268 (-2.556, 0.019) 

Cl–

 3-day lag = -1.902 (-3.589 to -0.216) 

NO3

– concurrent day = 3.146 (-1.112, 7.404) 

NO3

–

 2-day lag = 3.146 (-1.112, 7.404) 

NO3

–

 3-day lag = 1.049 (-3.209, 5.306) 

SO4

2– concurrent day = 1.764 (-1.817, 5.346) 

SO4

2– 2-day lag = 2.646 (-0.935, 6.228) 

SO4

2– 3-day lag = 1.764 (-1.817, 5.346) 

Reference: Ebelt et al. (2005, 

056907) 

Period of Study: Summer of 

1998

Location: Vancouver, 

Canada 

Outcome: Spirometry 

Age Groups: Range from 54-86 yr 

Mean age= 74 yr 

Study Design: Extended analysis of a 

repeated-measures panel study 

N: 16 persons with COPD 

Statistical Analyses: Earlier analysis 

expanded by developing mixed-effect 

regression models and by evaluating 

additional exposure indicators 

Dose-response Investigated? No 

Statistical Package: SAS V8 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean (SD): 

Ambient PM10-2.5: 5.6 (3.0) 

Exposure to ambient PM10-2.5: 2.4 (1.7) 

Range (Min, Max): 

Ambient PM10-2.5: (-1.2-11.9) 

Exposure to ambient 

PM10-2.5: (-0.4-7.2) 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient PM10: r= 0.69 

Ambient PM2.5: r= 0.15 

Nonsulfate Ambient 

PM2.5: r= 0.14 

Exposure to Ambient 

PM10-2.5: r= 0.73 

PM Increment: Ambient PM10-2.5: 4.5 (IQR) 

Exposure to ambient PM10-2.5: 2.4 (IQR) 

Notes: Effect estimates are presented in Fig 2 and 

Electronic Appendix Table 1 (only available with electronic 

version of article) and not provided quantitatively 

elsewhere. 

December 2009 E-170 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lagorio et 

al.(2006, 089800) 

Period of Study: May 

1999-June 1999 and Nov 

1999-Dec 1999 

Location: Rome, Italy 

Outcome: Lung function of subjects 

(FVC and FEV1) with COPD, Asthma 

Age Groups: COPD 50-80 yr 

Asthma 18-64 yr 

Study Design: Time series 

N: COPD N = 11; Asthma N = 11 

Statistical Analyses: Non-parametric 

Spearman correlation 

GEE 

Covariates: 

COPD: daily mean temperature, 

season variable (spring or winter), 

relative humidity, day of week 

Asthma: season variable, temperature, 

humidity, and -2-agonist use 

Season: Spring and winter 

Dose-response Investigated? Yes 

Statistical Package: STATA 

Lags Considered: 1-3 days 

PM Size: PM10-2.5

Averaging Time: 24 h 

Mean (SD): 

Overall: 15.6 (7.2) 

Spring: 18.7 (7.4) 

Winter: 12.3 (5.4) 

Range (Min, Max): (3.4, 39.6) 

PM Component: 

Cd: 0.46±0.40 ng/m3

Cr: 1.9±1.7 ng/m3

 

Fe: 283±167 ng/m3

Ni: 4.8±6.5 ng/m3

Pb: 30.6±19.0 ng/m3

Pt: 5.0±8.6 pg/m3

V: 1.8±1.4 ng/m3

Zn: 45.8±33.1 ng/m3

Monitoring Stations: Two fixed 

sites: (Villa Ada and Istituto 

superior di Sanita) 

Copollutant (correlation): 

NO2 r = 0.51 

O3 r = 0.31 

CO r = -0.09 

SO2 r = -0.16 

PM10 r = 0.61 

PM2.5 r = 0.34 

PM Increment: 1 μg/m3

They observed no statistically significant effect of PM10-2.5

on FVC and FEV1 on any of the panels (COPD, Asthma). 

β Coefficient (SE) 

COPD 

FVC(%) 

24 h -1.32 (1.06)^l 

48-h -1.46 (1.31) 

72-h -1.38 (1.53) 

FEV1(%) 

24 h -0.59 (0.95) 

48-h -1.01 (1.19) 

72-h -0.90 (1.42) 

Asthma 

FVC(%) 

24 h -0.17 (0.75) 

48-h -0.36 (0.91) 

72-h -0.24 (1.07) 

FEV1(%) 

24 h -0.67 (0.89) 

48-h -1.19 (1.07) 

72-h -0.51 (1.26) 

Reference: Laurent et al. 

(2008, 156672) 

Period of Study: Dec 

2003-Dec 2004 

Location: Strasbourg, France 

Outcome: Sales of short acting βagonists 

Study Design: Case-crossover 

Covariates: NR 

Statistical Analysis: Conditional 

logistic regression 

Age Groups: 0-39 yr 

Pollutant: PM10

Averaging Time: NR 

Mean (SD) Unit: 20.8 (10.2) 

μg/m3

Range (Min, Max): NR 

Copollutant (correlation): NO2, 

O3, correlations NR 

Increment: 10 μg/m3

Percent Increase in Short Acting β-agonists sold

Per increment increase in ambient PM10 at lags 4-7, a 

7.5% increase (95% CI: 4-11.2%) was seen in SABA 

sales. 

All other results were given in Fig 1 and 2 

Reference: Tang et al. (2007, 

091269) 

Period of Study: 

Dec 2003-Feb 2005 

Location: Sin-Chung City, 

Taipei County, Taiwan 

Outcome: Peak expiratory flow rate 

(PEFR) of asthmatic children 

Age Groups: 6-12 yr 

Study Design: Panel study 

N: 30 children 

Statistical Analyses: 

Linear mixed-effect models were used 

to estimate the effect of PM exposure 

on PEFR 

Covariates: Gender, age, BMI, history 

of respiratory or atopic disease in 

family, SHS, acute asthmatic 

exacerbation in past 12 mo, ambient 

temperature and relative humidity, 

presence of indoor pollutants, and 

presence of outdoor pollutants, 

Dose-response Investigated? yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-2 

Pollutant: PM10-2.5

Averaging Time: 1 h 

Mean (SD): 

Personal: 17.8 (19.6) 

Ambient: 17.0 (10.6) 

Range (Min, Max): 

Personal: 0.3-195.7 

Ambient: 0.1-80.2 

Monitoring Stations: 1 

PM Increment: 15.9 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Change in morning PEFR: 

-20.55 (-45.83, 4.73) lag 0 

-39.05 (-104.16 , 26.06) lag 1 

-39.56 (-79.56, 0.44) lag 2 

-37.15 (-105.01, 30.7) 2-day mean 

-35.47 (-27.32, 56.38) 3-day mean 

Change in evening PEFR: 

-1.68 (-19.13, 15.78) lag 0 

1.59 (-14.32, 17.5) lag 1 

0.86 (-30.84, 32.57) lag 2 

5.97 (-15.57, 27.5) 2-day mean 

29.75 (-1.69, 61.18) 3-day mean 

December 2009 E-171 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Trenga et al., 

(2006, 155209) 

Period of Study: 1999-2002 

Location: Seattle, WA 

Outcome: Lung function: FEV1, PEF, 

MMEF (maximal midexpiratory flow 

assessed only for children) 

Age Groups: Adults (56-89-yr-old) 

healthy & with COPD 

Asthmatic children 6-13-yr-old 

Study Design: Adult and pediatric 

panel study over 3 yr with 1 monitoring 

period (“session”) per yr 

N: 57 adults (33 healthy, 24 with 

COPD) = 692 subject-days = 207 

study-days 

17 asthmatic children = 319 subjectdays = 98 study-days 

Statistical Analyses: Mixed effects, 

longitudinal regression models, with 

the effects of pollutant decomposed 

into each subject’s a) overall mean 

b) Difference between their sessionspecific mean and overall mean 

c) Difference between their daily 

values and session-specific mean 

Covariates: Gender, age, ventral site 

temperature and relative humidity, CO, 

NO2

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 days 

Pollutant: PM10-2.5 (coarse) 

Averaging Time: 24 h 

Percentiles: 

Subject-specific exposure 

PM10-PM2.5

Outdoor 

25th: 3.3 

50th (Median): 4.7 

75th: 6.9 

Adults 

Outdoor 

25th: 3.3 

50th (Median): 5.0 

75th: 7.1 

Range (Min, Max): 

Subject-specific exposure 

Children 

Outdoor (0.0, 25.3) 

Adults 

Outdoor (0.0, 25.7) 

Monitoring Stations: 2 

Also subject-specific local 

outdoors (i.e., at each home), 

indoor, and personal 

Copollutant (correlation): 

CO 

NO2

PM2.5

PM Increment: 10 μg/m3

Adult

Outdoor Home PM10-PM2.5

FEV1

Overall: Lag 0 -27.9 [-87.5: 31.8] 

Lag 1 47.1 [-5.1: 99.4] 

No-COPD: Lag 0 -49.2 [-22.3: 23.9] 

Lag 1 74.3 [6.8: 141.8] 

COPD: Lag 0 7.3 [-84.7: 99.4] 

Lag 1 11.5 [-65.4: 88.3] 

PEF 

Overall: Lag 0 5.3 [-5.1: 15.7] 

Lag 1 -2.5 [-11.6: 6.5] 

No-COPD: Lag 0 5.1 [-7.7: 17.8] 

Lag 1 -5.8 [-17.5: 5.9] 

COPD: Lag 0 5.7 [-10.3: 21.6] 

Lag 1 1.7 [-11.5: 14.9] 

Pediatric 

FEV1

Outdoor Home PM10-PM2.5

Overall 

Lag 0 -7.43 [-69.41: 54.55] 

Lag 1 -25.61 [-88.16: 36.94] 

No Anti-inflam. Medication 

Lag 0 -63.87 [-199.58: 71.84] 

Lag 1 -96.48 [-232.48: 39.52] 

Anti-inflam. Medication 

Lag 0 6.57 [-96.90: 110.04] 

Lag 1 -8.63 [-217.39: 200.14] 

PEF 

Outdoor Home PM10-PM2.5

Overall 

Lag 0 4.53 [-6.60: 15.67] 

Lag 1 -3.35 [-14.31: 7.62] 

No Anti-inflam. Medication 

Lag 0 2.05 [-22.36: 26.45] 

Lag 1 -6.56 [-30.90: 17.78] 

Anti-inflam. Medication 

Lag 0 5.15 [-7.90: 18.19] 

Lag 1 -2.58 [-15.35: 10.19] 

MMEF 

Outdoor Home PM10-PM2.5

Overall 

Lag 0 -0.01 [-7.29: 7.28] 

Lag 1 -2.07 [-9.25: 5.12] 

No Anti-inflam. Medication 

Lag 0-7.14 [-23.16: 8.87] 

Lag 1 -14.39 [-30.11: 1.32] 

Anti-inflam. Medication 

Lag 0 1.76 [-6.78: 10.30] 

Lag 1 0.89 [-7.56: 9.33] 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-172 
Table E-11. Short-term exposure - respiratory morbidity outcomes - PM2.5 (including 

components/sources). 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Adamkiewicz et al. (2004, 

087925) 

Period of Study: Aug-Dec 2000 

Location: Steubenville, Ohio 

Outcome: FENO 

Age Groups: Ranged 53.5-90.6 yr 

Study Design: Prospective cohort 

N: Total of 294 breaths from 29 subjects

Statistical Analyses: Fixed effect 

models, ANOVA, GLM procedure 

Covariates: Subject, week of study, 

day of the week, h of the day, ambient 

barometric pressure, temperature, and 

relative humidity 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Hourly lags, 0-48 h 

Pollutant: PM2.5

Averaging Time: 1 h 

Mean (SD): 19.5 

Percentiles: 

25th: 7.6 

75th: 25.5 

Range (Min, Max): NR, 105.8 

Monitoring Stations: 1 

Averaging Time: 24 h 

Mean (SD): 19.7 

Percentiles: 

25th: 9.7 

75th: 27.4 

Range (Min, Max): NR, 57.8 

Monitoring Stations: 1 

Copollutant (correlation): 

Ambient NO 

Indoor NO 

NO2

O 3

SO2 

PM Increment: 17.9 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

1-h Single pollutant models: 

0.36 (0.58-2.14) 

PM Increment: 17.7 

Effect Estimate [Lower CI, Upper CI]: 

24-h ma: 1.45 (0.33-2.57) 

Multipollutant models for PM2.5, ambient 

NO and room NO and estimated 

change in FENO (ppb) for an IQR in 

pollutant measure 

Model 1 1.95 (0.47-3.43) 

Model 2 1.38 (0.26-2.51) 

Model 4 1.97 (0.48-3.46) 

Notes: Association of FENO with PM2.5

at different lags presented in Fig 1 are 

not presented quantitatively elsewhere. 

Reference: Adar et al. (2007, 098635) 

Period of Study: Mar-Jun 2002 

Location: St. Louis, MO 

Outcome: FENO 

Age Groups: 60+ 

Study Design: Panel Study 

N: 44 non-smoking seniors 

Statistical Analyses: Mixed models 

containing random subject effects 

Covariates: Day of week, trip type, 

FENO collection device, current illness, 

use of vitamins, antihistamines, statins, 

steroids, and asthma medications, 

temperature, pollen, mold, NO 

concentration in testing room 

Statistical Package: SAS 

Lags Considered: 0 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Pretrip: 14.8 

Post-trip: 16.5 

Percentiles: 

25th (pretrip): 11.2 

75th (pretrip): 20.1 

25th (post-trip): 11.7 

75th (post-trip): 21.6 

Monitoring Stations: 1 

Copollutant (correlation): BC 

CO 

NO2

SO2

O3

PM Increment: 9.8 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Pre-trip % change: 21.9 (6.7, 39.4) 

Post-trip % change: -4.7 (-17.1, 9.6) 

Reference: Aekplakorn et al. (2003, 

089908) 

Period of Study: 107 days, from Oct 

1997-Jan 1998 

Location: Mae Mo district, Lampang 

Province, north Thailand 

Outcome: Upper respiratory 

symptoms, lower respiratory symptoms, 

cough 

Age Groups: 6-14 yr old 

Study Design: Logistic regression 

N: 98 asthmatic school children 

Statistical Analyses: Generalized 

Estimating Equations, stratified 

analysis, PROC GENMOD 

Covariates: Temperature and relative 

humidity 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: SAS v 8.1 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD): 

Sob Pad station: 24.77 

Sob Mo station: 24.89 

Hua Fai station: 26.27 

Range (Min, Max): 

Sob Pad: 4.52, 24.77 

Sob Mo: 3.13, 24.89 

Hua Fai: 3.67, 26.27 

Monitoring Stations: 3 

Copollutant: 

PM10 

SO2 

PM Increment: 10 μg/m3

Odds Ratios [Lower CI, Upper CI] 

lag: 

Asthmatics: 

URS: 1.04 (0.99, 1.09) lag 0 

LRS: 1.05 (0.98, 1.2) lag 0 

Cough: 1.05 (0.99, 1.10) lag 0 

Non-Asthmatics: 

URS: 1.03 (0.96, 1.09) lag 0 

LRS: 1.02 (0.93, 1.10) lag 0 

Cough: 1.00 (0.93, 1.07) lag 0 

PM10 + SO2

Asthmatics: 

URS: 1.04 (0.99, 1.10) lag 0 

LRS: 1.05 (0.98, 1.10) lag 0 

Cough: 1.05 (0.99, 1.11) lag 0 

Non-Asthmatics: 

URS: 1.03 (0.97, 1.09) lag 0 

LRS: 1.02 (0.93, 1.11) lag 0 

Cough: 1.00 (0.93, 1.07) lag 0 

December 2009 E-173 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Allen et al. (2008, 156208) 

Period of Study: 1999-2002 (additional 

PM composition data collected Dec 

2000 and May 2001) 

Location: Seattle, USA 

Outcome: Daily changes in exhaled 

nitric oxide (FENO) and 4 lung function 

measures, midexpiratory flow (MEF), 

peak expiratory flow (PEF), forced 

expiratory volume in 1 second (FEV1), 

and forced vital capacity (FVC) 

Age Groups: 6-13 yr 

Study Design: Panel study

N: 19 children with asthma 

Statistical Analyses: Linear mixed 

effects model with random intercept to 

test for within participant associations 

Covariates: Temperature, relative 

humidity, BMI, age, and, in the case of 

FENO, ambient NO measured at a 

centrally located monitoring site 

Models also included a term for withinparticipant, within-session effects, and a 

term for participant between-session 

effects 

Effect modification: Decided a priori to 

include interaction term for PM2.5

exposure and inhaled corticosteroids 

Pollutant: PM2.5

Mean (SD): 11.23 (6.48) 

Range (Min, Max): 

2.76-40.38 

25th: 6.38 

75th: 14.73 

Copollutant (correlation): 

Ambient LAC* r=0.83 

Ambient LG**r=0.84 

Personal PM2.5: r=0.34 

Personal LAC: r=0.54 

Ambient-generated PM2.5: r=0.87 

Nonambient-generated PM2.5: r=-0.06 

* LAC Light-absorbing carbon 

** LG: Leroglucosan (a marker of wood 

smoke) 

Health effect estimates presented in 

graphic form (Fig 1). Summary from text 

is as follows: 

Personal LAC, personal PM2.5, and 

ambient-generated PM2.5 were 

associated with (p < 0.05) and ambient 

PM2.5 was marginally associated 

(p=0.09) with increased FENO. Neither 

of the ambient combustion markers 

(LAC, LG) nor nonambient-generated 

PM2.5 was associated with FENO 

changes. 

All of the ambient concentrations were 

associated with decrements in PEF and 

MEF while ambient-generated PM2.5

was marginally associated (p < 0.10). 

Only ambient LG was associated with a 

decrease in FEV1 and there were no 

associations between exposure metrics 

and FVC. 

Reference: Barraza-Villarreal et 

al.(2008, 156254) 

Period of Study: Jun 2003-Jun 2005 

Location: Mexico City 

Outcome: Respiratory Symptoms, 

Coughing, Wheezing, Airway 

inflammation, Asthma 

Study Design: Prospective cohort 

Statistical Analyses: Bivarate analysis 

Age Groups: 6-14 

Pollutant: PM2.5

Averaging Time: Maximum 8-h avg 

Mean (SD) unit: 

28.9 (2.8) 

Range (Min, Max): 

(4.2, 102.8) 

Copollutants (correlation): 

O3

NO2

Increment: 17.5 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

Asthmatic children 

Inflammatory Marker: 

FENO: 1.08 (1.01, 1.16) 0 

IL-8: 1.08 (0.98, 1.19) 0 

ph_EBC: -0.03 (-0.09, 0.03) 0 

Lung Function: 

FEV1: -16.0 (-31.0 to -0.13) 0-4 avg 

FVC: -23.0 (-42.0 to -5.21) 0-4 avg 

FEV25-75: -11.0 (-42.0, 20.3) 0-4 avg 

Nonasthmatic children 

Inflammatory Marker: 

FENO: 0.89 (0.78, 1.01) 0 

IL-8: 1.16 (1.00, 1.36) 0; 

ph_EBC: -0.05 (-0.14, 0.04) 0 

Lung Function: 

FEV1: -21.0 (-42.3, 0.38) 0-4 avg 

FVC: -29.0 (-52.8 to -4.35) 0-4 avg 

FEV25-75: -20.0 (-69.0, 29.0) 0-4 avg 

All children age 6-14 

Respiratory Symptom: 

Cough: 1.11 (1.06, 1.17) 

Wheezing: 1.06 (0.99, 1.13) 

December 2009 E-174 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bennett et al. (2007, 

156268) 

Period of Study: 1992-2005 

Location: Melbourne, Australia 

Outcome: Adverse respiratory 

symptoms (wheeze, shortness of breath 

on waking, cough in the morning, 

phlegm in the morning, cough with 

phlegm in the morning, asthma attack) 

Age Groups: All ages with a mean of 

37.2 yr 

Study Design: Cohort study 

N: 1446 persons 

Statistical Analyses: Logistic 

regression models 

Covariates: Age, gender, current 

smoking status, medication use (ß2-

agonist and inhaled steroid), atopy 

Dose-response Investigated? No 

Statistical Package: STATA statistical 

software, version 9 (Statcorp, 2005) 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 6.8 

Range (Min, Max): (1.8-73.3) 

Monitoring Stations: 1 

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Within-person (longitudinal effects) 

Wheeze: OR=1.08 (0.79-1.48) 

SOB on waking: OR=1.34 (0.84-2.16) 

Cough in the morning: 

OR=0.74 (0.47-1.15) 

Phlegm in the morning: 

OR=1.55 (0.95-2.53) 

Cough w/ phlegm morning: 

OR=1.28 (0.70-2.33) 

Asthma attack: OR=0.91 (0.55-1.49) 

Between-person (cross-sectional) 

effects 

Wheeze: OR=1.32 (0.82-2.10) 

SOB on waking: OR=1.29 (0.46-3.60) 

Cough in the morning: 

OR=0.21 (0.07-0.62) 

Phlegm in the morning: 

OR=0.49 (0.16-1.44) 

Cough w/ phlegm morning: 

OR=0.28 (0.08-0.97) 

Asthma attack: OR=0.52 (0.17-1.59) 

December 2009 E-175 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bourotte et al. (2007, 

150040) 

Period of Study: May 2002-Jul 2002 

Location: Sao Paulo, Brazil 

Outcome: Peak expiratory flow (PEF) 

Age Groups: Avg age 39.8 ± 12.3 yr 

Study Design: Cross-sectional 

N: 33 patients 

Statistical Analyses: 

Linear mixed-effects model 

Covariates: Gender, Age, BMI, Air 

Pollutants, Ambient temperature, 

Relative Humidity 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: S-plus 

Lags Considered: 2-day lag, 3-day lag 

Pollutant: PM2.5 (Fine) 

Averaging Time: 24 h 

Mean (SD): 11.9 (5.12) 

Range (Min, Max): 

(2.82, 26.6) 

Components: 

K+ 

Mg2

+

 

Ca2

+

 

Fin f

Cl–

NO3

–

SO4

2–

Monitoring Stations: 1 

PM Increment: NR 

Effect [Lower CI, Upper CI] lag: 

Morning PEF 

Na+ concurrent day = 

-0.409 (-2.485, 1.667) 

Na+

 2-day lag = -0.818 (-4.139, 2.503) 

Na+

 3-day lag = -0.205 (-4.356, 3.974) 

K+

 concurrent day = 

-0.211 (-2.778, 2.357) 

K+ 2-day lag = -0.843 (-4.695, 3.008) 

K+

 3-day lag = 0.843 (-4.292, 5.978) 

Mg2

+

 concurrent day = 

-1.750 (-5.302, 1.802) 

Mg2

+

 2-day lag = -5.016 (-10.79, 0.762) 

Mg2

+

 3-day lag = -3.850 (-10.15, 2.449) 

Ca2

+

 concurrent day = 

3.192* (-0.599, 6.943) 

Ca2

+

 2-day lag = 5.880 (1.105, 10.65) 

Ca2

+

 3-day lag = 7.560* (2.103, 13.02) 

Finf concurrent day = 

2.218* (-0.033, 4.470) 

Finf 2-day lag = 3.697* (1.446, 5.949) 

Finf 3-day lag =4.067* (1.065, 7.069) 

Cl– concurrent day = 

-1.010 (-3.469, 1.450) 

Cl–

 2-day lag = -1.615 (-5.714, 2.483) 

Cl– 3-day lag = -1.615 (-6.534, 3.303) 

NO3

–

 concurrent day = 

3.144 (0.409, 5.878) 

NO3

–

 2-day lag = 3.593 (0.858, 6.328) 

NO3

–

 3-day lag = 4.491 (1.756, 7.226) 

SO4

2–concurrent day = 

2.210 (-0.032, 4.272) 

SO4

2– 2-day lag = 3.180 (1.028, 5.332) 

SO4

2– 3-day lag = 3.180 (1.028, 5.332) 

Evening PEF 

Na+ concurrent day = 

-1.636 (-3.712, 0.440) 

Na+

 2-day lag = -0.205 (-3.256, 3.117) 

Na+

 3-day lag = -1.023 (-5.174, 3.129) 

K+

 concurrent day = 

-1.897 (-4.465, 0.670) 

K+ 2-day lag = -1.686 (-5.966, 2.592) 

K+

 3-day lag = -1.054 (-6.189, 4.081) 

Mg2

+

 concurrent day = 

-2.753 (-6.400, 0.894) 

Mg2

+

 2-day lag = -2.567 (-8.534, 3.401) 

Mg2

+

 3-day lag = -4.876 (-11.36, 1.612) 

Ca2

+

 concurrent day = 

2.184 (-1.567, 5.935) 

Ca2

+

2-day lag = 5.040 (0.265, 9.815) 

Ca2

+

 3-day lag = 5.040 (-0.417, 10.50) 

Finf f concurrent day = 

1.479 (-0.773, 3.730) 

Finf 2-day lag = 1.819 (-0.403, 4.100) 

Fin 3-day lag = 2.958 (-0.044, 5.960) f

Cl–

 concurrent day = 

 -0.404 (-2.863, 2.055) 

Cl–

 2-day lag = 0.000 (-4.099, 4.099) 

Cl–

 3-day lag =0.202 (-4.716, 5.120) 

NO3

–

 concurrent day = 

1.796 (-0.939, 4.531) 

NO3

–

 2-day lag = 2.695 (-0.040, 5.430) 

NO3

–

 3-day lag = 3.144 (0.409, 5.878) 

SO4

2– concurrent day = 

2.120 (-0.032, 4.272) 

SO4

2– 2-day lag = 2.120 (-0.032, 4.272) 

SO4

2– 3-day lag =2.120 (-0.032, 4.272) 

December 2009 E-176 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: de Hartog et al. (2003, 

001061) 

Period of Study: Winter of 1998-1999 

(in Amsterdam, from Nov 1998-Jun 

1999; in Erfurt, from Oct 1998-Apr 

1999; and in Helsinki, from Nov 

1998-Apr 1999.) 

Location: 

Amsterdam, the Netherlands 

Erfurt, Germany 

and Helsinki, Finland 

Outcome: Respiratory symptoms 

Age Groups: ≥ 50 yr 

Study Design: Cohort 

N: 131 subjects with history of coronary 

heart disease 

Statistical Analyses: Logistic 

regression 

Covariates: Ambient temperature, 

relative humidity, atmospheric pressure, 

incidence of influenza-like illness 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: S-PLUS 2000 

Lags Considered: 0-, 1-, 2-, 3-, and 

5-day avg 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Amsterdam, the Netherlands: 20.0 

Erfurt, Germany: 23.4 

Helsinki, Finland: 12.8 

Range (Min, Max): 

Amsterdam, the Netherlands: (3.8-82.2) 

Erfurt, Germany: (4.5-118.1) 

Helsinki, Finland: (3.1-39.8) 

Unit (i.e. μg/m3

): μg/m3

Monitoring Stations: 1 

Copollutant: 

PM10

NC0.01-0.1 

CO 

NO2

SO2 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Association of air pollution and 

incidence of symptoms in three panels 

of elderly subjects 

Lag 0 

Chest pain w/ physical exertion: 1.04 

(0.96-1.13) 

Shortness of breath: 1.04 (0.96-1.12) 

Awakened, breathing problems: NA 

Avoidance of activities: 1.04 (0.96-1.14) 

Phlegm: 1.03 (0.93-1.13) 

Lag 1 

Chest pain w/ physical exertion: 1.01 

(0.93-1.09) 

Shortness of breath: 1.06 (0.99-1.14) 

Awakened, breathing problems: 1.09 

(1.00-1.20) 

Avoidance of activities: 1.03 (0.95-1.12) 

Phlegm: 1.10 (1.01-1.19) 

Lag 2 

Chest pain w/ physical exertion: 0.98 

(0.90-1.05) 

Shortness of breath: 1.05 (0.98-1.12) 

Awakened, breathing problems: 1.04 

(0.95-1.14) 

Avoidance of activities: 1.05 (0.97-1.14) 

Phlegm: 1.08 (1.00-1.18) 

Lag 3 

Chest pain w/ physical exertion: 1.00 

(0.93-1.08) 

Shortness of breath: 1.08 (1.01-1.15) 

Awakened, breathing problems: 0.99 

(0.91-1.08) 

Avoidance of activities: 1.06 (0.98-1.14) 

Phlegm: 1.10 (1.01-1.19) 

5-day 

Chest pain w/ physical exertion: 1.02 

(0.91-1.13) 

Shortness of breath: 1.12 (1.02-1.24) 

Awakened, breathing problems: 1.03 

(0.90-1.18) 

Avoidance of activities: OR= 1.09 (0.97-

1.22) 

Phlegm: OR= 1.16 (1.03-1.32) 

December 2009 E-177 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2004, 

056897) 

Period of Study: Sep-Oct 1999 

Apr-Jun 2000 

Location: Alpine, California 

Outcome: FEV1

Age Groups: 9-19 yr old 

Study Design: Panel study 

N: 24 children 

Statistical Analyses: GLM 

Akaike’s information criterion and 

Bayesian information criterion 

Covariates: Day of wk, personal 

temperature and relative humidity, time 

of FEV1 maneuver (morning, afternoon, 

or evening), Season (fall 1999 or spring 

2000), As-needed medication use, 

Presence or absence of upper or lower 

respiratory infections 

Season: Spring, fall 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-4 

Pollutant: PM2.5

Averaging Time: 24-h avg 1-h max 

personal PM last 24 h 

Mean (SD): 151.0 (12.03) 90th: 292.4 

Range (Min, Max): (9.1, 996.8) 

Mean personal PM last 24 h 

Mean (SD): 37.9 (19.9) 

90th: 65.1 

Range (Min, Max): 3.9, 113.8 

Home stationary-site PM 

24-h Mean indoor PM2.5 

Mean (SD): 12.1 (5.4) 

90th: 20.2 

Range (Min, Max): 2.8, 35.3 

24-h Mean outdoor PM2.5 

Mean (SD): 11.0 (5.4) 

90th: 18.4 

Range (Min, Max): 1.8, 31.0 

Central outdoor stationary-site PM 

24-h Mean PM2.5 

Mean (SD): 10.3 (5.6) 

90th: 18.4 

Range (Min, Max): 1.7, 29.1 

Copollutant (correlation): 

24-h Central HI PM2.5

8-h max O3 = 0.24 

8-h Max NO2 = 0.73 

8-h Max Personal PM = 0.38 

24-h Mean Personal PM = 0.43 

8-h Max TEOM PM10 = 0.71 

24-h Mean TEOM PM10 = 0.78 

24-h Central HI PM10 = 0.90 

24-h Outdoor HI PM2.5 = 0.89 

24-h Outdoor HI PM10 = 0.72 

24-h Indoor HI PM10 = 0.40 

24-h Indoor HI PM2.5 = 0.73 

Results presented graphically; 

% predicted FEV1 was inversely 

associated with personal exposure to 

fine particles. 

Inverse associations of FEV1 with 

stationary-site indoor, outdoor and 

central-site gravimetric PM2.5 and PM10, 

and with hourly TEOM PM10

December 2009 E-178 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2006, 

090745) 

Period of Study: Region 1: Aug-Mid 

Dec 2003. Region 2: Jul-Nov 2004 

Location: Region 1: Riverside, CA. 

Region 2: Whittier, CA 

Outcome: Fractional Concentration of 

Nitric Oxide in exhaled air (FENO) 

Age Groups: 9 through 18 

Study Design: Longitudinal Panel 

Study 

N: 45 children 

Riverside children 

32 Whittier children 

Statistical Analyses: Linear mixedeffects models 

Two-stage hierarchical model 

Empirical Variograms 

Fourth-order polynomial distributed lag 

mixed-effects model 

Covariates: Personal temperature, 

Personal Rel. Humid., 10-day exposure 

run, Respiratory infections, Region of 

study, Sex, Cumulative daily use of asneeded B-agonist inhalers 

Dose-response Investigated? No 

Lags Considered: 0, 1, 2, MA day 

Pollutant: PM2.5

Personal Exposure 

Averaging Time: 24 h 

Riverside 

Mean (SD): 32.78 (21.84) 

50th(Median): 28.14 

Range (Min, Max): 7.27, 98.43 

Whittier 

Mean (SD): 36.2 (25.46) 50th(Median): 

29.07 

Range (Min, Max): 7.55, 197.05 

Personal Exposure 

Averaging Time: 1 h 

Riverside 

Mean (SD): 97.94 (70.29) 

50th(Median): 83.7 

Range (Min, Max): 14.9, 431.8 

Whittier 

Mean (SD): 93.63 (75.19) 

50th(Median): 71.95 

Range (Min, Max): 5.8, 572.9 

Personal Exposure 

Averaging Time: 8 h 

Riverside 

Mean (SD): 47.21 (30.9) 50th(Median): 

38.5 

Range (Min, Max): 8.9, 132.1 

Whittier 

Mean (SD): 51.75 (36.88) 

50th(Median): 40.15 

Range (Min, Max): 8.7, 254.1 

Central Site 

Averaging Time: 24 h 

Riverside 

Mean (SD): 36.63 (23.46) 

50th(Median): 29.26 

Range (Min, Max): (9.52, 87.22) 

Whittier 

Mean (SD): 18 (12.14) 50th(Median): 

16.3 

Range (Min, Max): 2.7, 77.09 

Monitoring Stations: 48 personal 

nephelometers 

2 central sites 

Copollutant (correlation): 

Personal 

24-h personal PM2.5 1.00 

24-h personal EC 0.18 

24-h personal OC 0.15 

24-h personal NO2 0.33 

24-h central PM2.5 0.64 

24-h central EC 0.12 

24-h central OC 0.21 

24-h central NO2 0.22 

Central 

24-h personal PM2.5 0.64 

24-h personal EC 0.00 

24-h personal OC -0.11 

24-h personal NO2 0.12 

24-h central PM2.5 1.00 

24-h central EC 0.55 

24-h central OC 0.66 

24-h central NO2 0.25 

PM Increment: IQR increase 

(Riverside: 28.41 μg/m3

, Whittier 21.87 

μg/m3) 

Coefficient [Lower CI, Upper CI] 

lag: 

Mixed-model estimates of the 

association between personal and 

central-site air pollutant exposure and 

FENO 

Lag 0 

Personal 0.42 (-0.15, 0.99) 

Central 0.03 (-0.68, 0.74) 

Lag 1 

Personal 0.51 (-0.10, 1.12) 

Central 0.44 (-0.28, 1.16) 

2-day ma 

Personal 1.01 (0.14, 1.88) 

Central 0.52 (-0.43, 1.47) 

Stratified by Medication Use 

Lag = 2-day ma 

Not Taking Anti-Inflamm. Medication 

Personal 1.11 (-1.39, 3.60) 

Central 0.44 (-1.65, 2.53) 

Taking Anti-Inflamm. Medication 

Personal 1.01 (0.19, 1.84) 

Central 0.55 (-0.47, 1.57) 

Inhaled Corticosteroids 

Personal 1.58 (0.72, 2.43) 

Central 1.16 (0.11, 2.20) 

Antileukotrienes +- inhaled 

corticosteroids 

Personal -0.89 (-2.73, 0.95) 

Central -0.75 (-2.83, 1.32) 

Notes: 

Fig of Estimated lag effect of hourly 

personal PM2.5 on FENO. 

Fig of the Estimated lag effect of hourly 

personal PM2.5 on FENO by use of 

medications. 

Fig of one- and two-pollutant models for 

change in FENO using 2-day Ma 

personal and central-site pollutant 

measurements. 

December 2009 E-179 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2006, 

090745) 

Period of Study: Region 1: Aug-Mid 

Dec 2003. Region 2: Jul-Nov 2004 

Location: Region 1: Riverside, CA. 

Region 2: Whittier, CA 

Outcome: Fractional Concentration of 

Nitric Oxide in exhaled air (FENO) 

Age Groups: 9 through 18 

Study Design: Longitudinal Panel 

Study

N: 45 children 

Statistical Analyses: Linear mixedeffects models 

Two-stage hierarchical model 

Empirical Variograms 

Fourth-order polynomial distributed lag 

mixed-effects model 

Covariates: Personal temperature, 

personal rel. humid., 10-day exposure 

run, respiratory infections, region of 

study, sex, cumulative daily use of asneeded B-agonist inhalers 

Dose-response Investigated? No 

Lags Considered: Lag 0, Lag 1, 2-day 

ma 

Pollutant: PM2.5

PM Component: EC 

Personal Exposure 

Averaging Time: 24 h 

Riverside 

Mean (SD): 0.42 (0.69) 50th(Median): 

0.34 μg/m3

Range (Min, Max): 0.01, 6.94 

Whittier 

Mean (SD): 0.78 (1.42) 

50th(Median): 0.47 

Range (Min, Max): 0, 17.2 

Central Site 

Averaging Time: 24 h 

Riverside 

Mean (SD): 1.61 (0.78) 50th(Median): 

1.35 

Range (Min, Max): 0.52, 3.64 

Whittier 

Mean (SD): 0.71 (0.43) 50th(Median): 

0.63 

Range (Min, Max): 0.14, 2.95 

Monitoring Stations: 48 personal 

nephelometers, 

2 central sites 

Copollutant (correlation): 

Personal

24-h personal PM2.5 0.18 

24-h personal EC 1.00 

24-h personal OC 0.41 

24-h personal NO2 0.0.21 

24-h central PM2.5 0.00 

24-h central EC 0.04 

24-h central OC -0.01 

24-h central NO2 0.23 

Central 

24-h personal PM2.5 0.12 

24-h personal EC 0.04 

24-h personal OC 0.03 

24-h personal NO2 0.19 

24-h central PM2.5 0.55 

24-h central EC 1.00 

24-h central OC 0.87 

24-h central NO2 0.70 

PM Increment: IQR increase 

(Riverside: 28.41 μg/m3

, Whittier 21.87 

μg/m3) 

Coefficient [Lower CI, Upper CI] lag: 

Mixed-model estimates of the 

association between personal and 

central-site air pollutant exposure and 

FENO 

Lag 0 

Personal 0.29 (0.10, 0.48) 

Central 0.10 (-0.65, 0.85) 

Lag 1 

Personal -0.01 (-0.23, 0.21) 

Central 0.99 (0.27, 1.71) 

2-day ma 

Personal 0.72 (0.32, 1.12) 

Central 1.38 (0.15, 2.61) 

Stratified by Medication Use 

Lag = 2-day ma 

Not Taking Anti-Inflamm. Medication 

Personal 0.84 (0.08, 1.60) 

Central 1.02 (-2.55, 4.60) 

Taking Anti-Inflamm. Medication 

Personal 0.71 (0.28, 1.15) 

Central 1.42 (0.25, 2.60) 

Inhaled Corticosteroids 

Personal 0.67 (0.28, 1.07) 

Central 1.28 (0.07, 2.49) 

Antileukotrienes +- inhaled 

corticosteroids 

Personal 0.03 (-3.29, 3.35) 

Central 1.15 (-1.58, 3.88) 

Notes: 

Fig of Estimated lag effect of hourly 

personal PM2.5 on FENO. 

Fig of the estimated lag effect of hourly 

personal PM2.5 on FENO by use of 

medications. 

Fig of one- and two-pollutant models for 

change in FENO using 2-day Ma 

personal and central-site pollutant 

measurements. 

December 2009 E-180 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Delfino et al. (2006, 

090745) 

Period of Study: Region 1: Aug-Mid 

Dec 2003. Region 2: Jul through Nov 

2004 

Location: Region 1: Riverside, CA. 

Region 2: Whittier, CA 

Outcome: Fractional Concentration of 

Nitric Oxide in exhaled air (FENO) 

Age Groups: 9 through 18 

Study Design: Longitudinal Panel 

Study 

N: 45 children 

Statistical Analyses: Linear mixedeffects models 

Two-stage hierarchical model 

Empirical Variograms 

Fourth-order polynomial distributed lag 

mixed-effects model 

Covariates: Personal temperature, 

personal rel. humid., 10-day exposure 

run, respiratory infections, region of 

study, sex, cumulative daily use of asneeded B-agonist inhalers

Dose-response Investigated? No 

Lags Considered: Lag 0, Lag 1, 2-day 

ma 

Pollutant: PM2.5

PM Component: OC 

Personal Exposure 

Averaging Time: 24 h 

Riverside 

Mean (SD): 5.63 (2.59) 50th(Median): 

4.98 

Range (Min, Max): 1.94, 12.38 

Whittier 

Mean (SD): 6.81 (3.45) 50th(Median): 

6.43 

Range (Min, Max): 2.18, 31.5 

Central Site 

Averaging Time: 24 h 

Riverside 

Mean (SD): 6.88 (1.86) 

Percentiles: 50th 

Median: 6.07 

Range (Min, Max): 4.11, 11.62 

Whittier 

Mean (SD): 3.93 (1.49) 50th(Median): 

3.76 

Range (Min, Max): 1.64, 8.82 

Monitoring Stations: 48 personal 

nephelometers, 

2 central sites 

Copollutant (correlation): 

Personal 

24-h personal PM2.5 0.15 

24-h personal EC 0.41 

24-h personal OC 1.00 

24-h personal NO2 0.20 

24-h central PM2.5 -0.11 

24-h central EC 0.03 

24-h central OC -0.02 

24-h central NO2 0.21 

Central 

24-h personal PM2.5 0.21 

24-h personal EC -0.01 

24-h personal OC -0.02 

24-h personal NO2 0.17 

24-h central PM2.5 0.66 

24-h central EC 0.87 

24-h central OC 1.00 

24-h central NO2 0.62 

PM Increment: IQR increase 

(Riverside: 28.41 μg/m3

, Whittier 21.87 

μg/m3) 

Mixed-model estimates of the 

association between personal and 

central-site air pollutant exposure and 

FENO 

Lag 0 

Personal 0.51 (-0.28, 1.30) 

Central 0.93 (-0.20, 2.06) 

Lag 1 

Personal 0.13 (-0.77, 1.03) 

Central0.51 (-0.64, 1.66) 

2-day ma 

Personal 0.94 (-0.47, 2.35) 

Central 1.6 (-0.17, 3.37) 

Stratified by Medication Use 

Lag = 2-day ma. 

Not Taking Anti-Inflamm. Medication 

Personal 0.88 (-1.62, 3.38) 

Central 0.36 (-4.07, 4.79) 

Taking Anti-Inflamm. Medication 

Personal 0.87 (-0.79, 2.53) 

Central 2.05 (0.24, 3.86) 

Inhaled Corticosteroids 

Personal 2.47 (0.30, 4.64) 

Central 1.96 (0.14, 3.78) 

Antileukotrienes +- inhaled 

corticosteroids 

Personal 0.52 (-1.99, 3.02) 

Central 1.29 (-2.58, 5.15) 

Notes: 

Fig of Estimated lag effect of hourly 

personal PM2.5 on FENO. 

Fig of the Estimated lag effect of hourly 

personal PM2.5 on FENO by use of 

medications. 

Fig of one- and two-pollutant models for 

change in FENO using 2-day Ma 

personal and central-site pollutant 

measurements 

December 2009 E-181 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dubowsky et al. (2006, 

088750) 

Period of Study: Mar 2002-Jun 

2002

Location: St. Louis, Missouri 

Outcome: Chronic inflammation, 

Diabetes, Obesity, Hypertension, 

Cardiac Risk 

Study Design: 

Prospective Cohort 

Statistical Analyses: 

Poisson, LOESS 

Age Groups: 

≥ 60 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD) unit: 16 (6.0) 

Range (Min, Max): 6.5, 28

Copollutants: 

BC 

CO 

NO2

SO2 

O3

Increment: 5.4 μg/m3

% Increase (Lower CI, Upper CI) 

Lag 

% increase in inflammatory response 

and exposure to PM2.5 in people ≥ 60 

Inflammatory Marker: 

IL-6: -8 (-16, 8) 

1: -6 (-10, 5) 

2: -5 (-11, 6) 

3: -3 (-9, 6) 

4: -4 (-12, 10) 

5: -5 (-13, 8) 

6: -6 (-14, 9) 

7 

CRP: -2 (-22, 15) 

1: 3 (-8, 17) 

2: 4 (-9, 20) 

3: 9 (-4, 27) 

4: 11 (-5, 35) 

5: 8 (-9, 29) 

6: 5 (-12, 26) 

7 

WBC: 0 (-2, 4) 

1: 1 (-1, 2) 

2: 2 (-1, 3) 

3: 1 (-2, 5) 

4: 3 (-1, 10) 

5: 5 (0, 12) 

6: 8 (0, 14) 

7 

% Increase in inflammatory responses 

and exposure to ambient PM2.5

concentrations in people ≥ 60 

Inflammatory Marker: 

CRP 

All conditions*: 14 (-5.4, 37) 

0-5 avg 

3 conditions met*: 81 (21, 172) 

0-5 avg 

2 conditions met*: 11 (-7.3, 33) 

0-5 avg 

IL-6 

All conditions*: -2.1 (-13, 11) 

0-5 avg 

3 conditions met*: 23 (-5.3, 59) 

0-5 avg 

2 conditions met*: -3.1 (-14, 9.7) 

0-5 avg 

WBC 

All conditions*: 3.4 (-1.8, 8.9) 

0-5 avg 

3 conditions met*: 0.4 (-8.8, 11) 

0-5 avg 

2 conditions met*: 3.6 (-1.7, 9.1) 

0-5 avg 

* All conditions met means model is 

adjusted for sex, obesity, diabetes, 

smoking history, ambient and 

microenvironmental apparent 

temperature, mold, pollen, trip, h, and 

vitamins. 

Three conditions met means model is 

adjusted for three of the variables. 

Two conditions met means model is 

adjusted for 2 of the variables. 

December 2009 E-182 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ebelt et al. (2005, 056907) 

Period of Study: Summer of 1998 

Location: Vancouver, Canada 

Outcome: spirometry, 

Age Groups: range from 54-86 yr 

Mean age= 74 yr 

Study Design: extended analysis of a 

repeated-measures panel study 

N: 16 persons with COPD 

Statistical Analyses: Earlier analysis 

expanded by developing mixed-effect 

regression models and by evaluating 

additional exposure indicators 

Dose-response Investigated? No 

Statistical Package: SAS V8 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 

Ambient PM2.5: 11.4 (4.6) 

Exposure to ambient PM2.5: 7.9 (3.7) 

Nonsulfate ambient PM2.5: 9.3 (3.7) 

Exposure to nonsulfate ambient PM2.5: 

6.5 (3.0) 

Total exposure to PM2.5: 18.5 (14.9) 

Exposure to nonambient PM2.5: 10.6 

(14.5) 

Range (Min, Max): 

Ambient PM2.5: (4.2-28.7) 

Exposure to ambient PM2.5: (0.9-21.3) 

Nonsulfate ambient PM2.5: (3.3-23.3) 

Exposure to nonsulfate ambient PM2.5: 

(0.7-16.9) 

Total exposure to PM2.5: (2.2-90.9) 

Exposure to nonambient PM2.5: (-2.6-

85.0) 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient PM10: r= 0.78 

Ambient PM10-2.5: r= 0.15 

Ambient Sulfate- 0.82 

Nonsufate Ambient PM2.5: r= 0.98 

PM Increment: Ambient PM2.5: 5.8 

(IQR) 

Exposure to ambient PM2.5: 4.4 (IQR) 

Nonsulfate ambient PM2.5: 4.2 (IQR) 

Exposure to nonsulfate ambient PM2.5: 

3.4 (IQR) 

Total exposure to PM2.5: 10.1 (IQR) 

Exposure to nonambient PM2.5: 8.9 

(IQR) 

Notes: Effect estimates are presented 

in Fig 2 and Electronic Appendix Table 

1 (only available with electronic version 

of article) and not provided 

quantitatively elsewhere. 

Reference: Ebelt et al. (2005, 056907) 

Period of Study: Summer of 1998 

Location: Vancouver, Canada 

Outcome: spirometry 

Age Groups: Range from 54-86 yr 

Mean age= 74 yr 

Study Design: extended analysis of a 

repeated-measures panel study 

N: 16 persons with COPD 

Statistical Analyses: Earlier analysis 

expanded by developing mixed-effect 

regression models and by evaluating 

additional exposure indicators 

Dose-response Investigated? No 

Statistical Package: SAS V8 

Pollutant: Sulfate (SO4) 

Averaging Time: 24 h 

Mean (SD): 

Ambient Sulfate: 2.0 (1.1) 

Exposure to Ambient Sulfate: 0.2 (4.7) 

Range (Min, Max): 

Ambient Sulfate: (0.4-5.4) 

Exposure to ambient Sulfate: (0.2-4.7) 

Monitoring Stations: 5 

Copollutant (correlation): 

Ambient PM2.5: r= 0.82 

Nonsulfate Ambient PM2.5: r= 0.74 

Exposure to Ambient Sulfate: r= 0.82 

PM Increment: Ambient Sulfate: 1.5 

(IQR) 

Exposure to Ambient Sulfate: 0.9 (IQR) 

Notes: Effect estimates are presented 

in Fig 2 and Electronic Appendix Table 

1 (only available with electronic version 

of article) and not provided 

quantitatively elsewhere. 

Reference: Ferdinands et al. (2008, 

156433) 

Period of Study: Aug 2004

Location: Atlanta, Georgia 

Outcome: Respiratory Symptoms, 

airway inflammation 

Study Design: Prospective cohort 

Statistical Analyses: Pearson 

Correlation Analysis 

Age Groups: 14-18 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD) unit: 27.2 (11.9) 

Range (Min, Max): 21.7, 34.7 

Copollutants (correlation): 

O3: r= 0.8-0.9 

The study presents results qualitatively 

not quantitatively. 

Reference: Gent et al. (2003, 052885) 

Period of Study: Apr-Sep 2001 

Location: Connecticut 

Springfield, MA 

Outcome: Respiratory symptoms 

including: Wheeze, persistent cough, 

chest tightness, shortness of breath 

Age Groups: Infants 

Study Design: 1-yr prospective cohort 

study 

N: 1002 infants 

17160 observations 

Statistical Analyses: Logistic 

regression analysis 

GEEs 

Tests for linear trend 

Test for goodness of fit 

Hosmer-Lemeshow statistic for 

regression 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 13.1 (7.9) 

Percentiles: 20th: 6.9 

40th: 9.0 

50th(Median): 10.3 

60th: 12.1 

80th: 19.0 

Range (Min, Max): 3.7, 44.2 

Monitoring Stations: 4 sites 

Copollutant (correlation): 

Temperature: 0.58 

PM Increment: 12 μg/m3 same day 

19 μg/m3

 previous day 

Model 5 (same day) 

Wheeze <6.9 = 1.00 

6.9-8.9 = 0.95 (0.83, 1.10) 

9.0-12.0 = 1.04 (0.89, 1.20) 

12.1-18.9 = 1.05 (0.92, 1.20) 

≥ 19.0 = 0.93 (0.78, 1.11) 

Persistent Cough <6.9 =1.00 

6.9-8.9 = 0.95 (0.87, 1.04) 

9.0-12.0 = 0.96 (0.87, 1.06) 

12.1-18.9 = 1.00 (0.91, 1.09) 

≥ 19.0 = 0.95 (0.83, 1.09) 

Chest Tightness <6.9 = 1.00 

6.9-8.9 = 1.01 (0.86, 1.19) 

9.0-12.0 = 1.06 (0.89, 1.26) 

12.1-18.9 = 1.24 (1.06, 1.45) 

≥ 19.0 = 1.05 (0.84, 1.33) 

Shortness of Breath <6.9 = 1.00 

6.9-8.9 = 1.01 (0.87, 1.17) 

9.0-12.0 = 1.03 (0.87, 1.22) 

December 2009 E-183 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Covariates: Temperature 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 1-day lag 

12.1-18.9 = 1.07 (0.91, 1.25) ≥ 19.0 = 1.03 (0.83, 1.28) 

Bronchodilator <6.9 = 1.00 

6.9-8.9 = 1.04 (0.99, 1.09) 

9.0-12.0 = 1.02 (0.96, 1.08) 

12.1-18.9 = 1.04 (0.99, 1.09) ≥ 19.0 = 1.02 (0.97, 1.08) 

Model 6 (previous day) 

Wheeze <6.9 = 1.00 

6.9-8.9 = 1.06 (0.95, 1.20) 

9.0-12.0 = 1.09 (0.94, 1.28) 

12.1-18.9 = 1.03 (0.89, 1.19) ≥ 19.0 = 1.14 (0.97, 1.34) 

Persistent Cough <6.9 =1.00 

6.9-8.9 = 1.04 (0.94, 1.14) 

9.0-12.0 = 1.05 (0.94, 1.17) 

12.1-18.9 = 1.03 (0.94, 1.14) ≥ 19.0 = 1.12 (1.02 1.24) 

Chest Tightness <6.9 = 1.00 

6.9-8.9 = 1.03 (0.87, 1.23) 

9.0-12.0 = 1.04 (0.85, 1.27) 

12.1-18.9 = 1.00 (0.84, 1.19) ≥ 19.0 = 1.21 (1.00, 1.46) 

Shortness of Breath <6.9 = 1.00 

6.9-8.9 = 1.00 (0.84, 1.19) 

9.0-12.0 = 1.09 (0.90, 1.31) 

12.1-18.9 = 1.09 (0.90, 1.31) ≥ 19.0 = 1.26 (1.02, 1.54) 

Bronchodilator <6.9 = 1.00 

6.9-8.9 = 0.98 (0.94, 1.03) 

9.0-12.0 = 0.99 (0.95, 1.03) 

12.1-18.9 = 0.97 (0.94, 1.01) ≥ 19.0 = 0.99 (0.95, 1.04)

PM2.5 + O

3: 

Medication Users: Same-day 

Wheeze <6.9 = 1.00 

6.9-8.9 = 0.89 (0.75, 1.29) 

9.0-12.0 = 1.02 (0.87, 1.19) 

12.1-18.9 = 0.94 (0.77, 1.15) ≥ 19.0 = 0.83 (0.65, 1.06) 

Persistent Cough <6.9 = 1.00 

6.9-8.9 = 0.95 (0.84, 1.06) 

9.0-12.0 = 0.97 (0.86, 1.10) 

12.1-18.9 = 0.94 (0.77, 1.15) ≥ 19.0 = 0.83 (0.65, 1.06) 

Chest Tightness <6.9 = 1.00 

6.9-8.9 = 0.90 (0.74, 1.09) 

9.0-12.0 = 0.97 (0.79, 1.18) 

12.1-18.9 = 0.97 (0.76, 1.25) ≥ 19.0 = 0.76 (0.54, 1.05) 

Shortness of Breath <6.9 = 1.00 

6.9-8.9 = 0.95 (0.80, 1.12) 

9.0-12.0 = 1.00 (0.82, 1.21) 

12.1-18.9 = 0.90 (0.73, 1.12) ≥ 19.0 = 0.87 (0.65, 1.17) 

Bronchodilator <6.9 = 1.00 

6.9-8.9 = 1.03 (0.98, 1.08) 

9.0-12.0 = 1.01 (0.96, 1.07) 

12.1-18.9 = 1.02 (0.95, 1.08) ≥ 19.0 = 0.99 (0.91, 1.07)

Previous Day 

Wheeze <6.9 = 1.00 

6.9-8.9 = 1.03 (0.89, 1.18) 

9.0-12.0 = 1.05 (0.88, 1.24) 

12.1-18.9 = 0.98 (0.82, 1.17) ≥ 19.0 = 1.05 (0.85, 1.29) 

Persistent Cough <6.9 = 1.00 

6.9-8.9 = 0.99 (0.89, 1.11) 

9.0-12.0 = 0.98 (0.86, 1.10) 

12.1-18.9 = 0.95 (0.83, 1.10) ≥ 19.0 = 1.00 (0.88, 1.15) 

Chest Tightness <6.9 = 1.00 

6.9-8.9 = 0.89 (0.72, 1.10) 

9.0-12.0 = 0.90 (0.70, 1.16) 

12.1-18.9 = 0.81 (0.63, 1.03) ≥ 19.0 = 0.91 (0.71, 1.17) 

Shortness of Breath <6.9 = 1.00 

6.9-8.9 = 0.96 (0.78, 1.18) 

December 2009 E-184 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

9.0-12.0 = 1.00 (0.81, 1.25) 

12.1-18.9 = 0.96 (0.74, 1.24) 

≥ 19.0 = 1.20 (0.94, 1.52) 

Bronchodilator <6.9 = 1.00 

6.9-8.9 = 0.99 (0.94, 1.04) 

9.0-12.0 = 0.97 (0.93, 1.02) 

12.1-18.9 = 0.96 (0.91, 1.02) 

≥ 19.0 = 0.97 (0.89, 1.04) 

PM2.5 + O3: 

Non-users: Same-day 

Wheeze <6.9 = 1.00 

6.9-8.9 = 0.92 (0.72, 1.17) 

9.0-12.0 = 1.08 (0.85, 1.36) 

12.1-18.9 = 0.94 (0.73, 1.22) 

≥ 19.0 = 1.15 (0.75, 1.75) 

Persistent Cough <6.9 = 1.00 

6.9-8.9 = 0.96 (0.83, 1.12) 

9.0-12.0 = 1.02 (0.89, 1.18) 

12.1-18.9 = 0.93 (0.78, 1.12) 

≥ 19.0 = 1.07 (0.85, 1.34) 

Chest Tightness <6.9 = 1.00 

6.9-8.9 = 0.84 (0.54, 1.31) 

9.0-12.0 = 1.09 (0.74, 1.61) 

12.1-18.9 = 0.78 (0.47, 1.30) 

≥ 19.0 = 0.71 (0.36, 1.39) 

Shortness of Breath <6.9 = 1.00 

6.9-8.9 = 0.61 (0.39, 0.95) 

9.0-12.0 = 1.13 (0.85, 1.50) 

12.1-18.9 = 0.72 (0.42, 1.23) 

≥ 19.0 = 1.17 (0.72, 1.90) 

Bronchodilator Use: <6.9 = 1.00 

6.9-8.9 = 0.95 (0.78, 1.15) 

9.0-12.0 = 0.95 (0.78, 1.16) 

12.1-18.9 = 0.85 (0.69, 1.06) 

≥ 19.0 = 0.99 (0.76, 1.30)

Previous-day 

Wheeze <6.9 = 1.00 

6.9-8.9 = 1.01 (0.78, 1.31) 

9.0-12.0 = 1.15 (0.88, 1.51) 

12.1-18.9 = 1.08 (0.78, 1.51) 

≥ 19.0 = 1.18 (0.71, 1.97) 

Persistent Cough <6.9 = 1.00 

6.9-8.9 = 1.07 (0.94, 1.22) 

9.0-12.0 = 1.13 (0.97, 1.32) 

12.1-18.9 = 1.03 (0.87, 1.22) 

≥ 19.0 = 1.14 (0.88, 1.46) 

Chest Tightness <6.9 = 1.00 

6.9-8.9 = 1.44 (0.90, 2.30) 

9.0-12.0 = 1.50 (0.97, 2.33) 

12.1-18.9 = 1.56 (0.91, 2.66) 

≥ 19.0 = 1.76 (0.83, 3.73) 

Shortness of Breath <6.9 = 1.00 

6.9-8.9 = 0.99 (0.75, 1.30) 

9.0-12.0 = 1.30 (0.88, 1.91) 

12.1-18.9 = 0.84 (0.57, 1.24) 

≥ 19.0 = 1.48 (0.94, 2.34) 

Bronchodilator Use <6.9 = 1.00 

6.9-8.9 = 1.05 (0.85, 1.34) 

9.0-12.0 = 1.28 (1.01, 1.62) 

12.1-18.9 = 1.05 (0.80, 1.37) 

≥ 19.0 = 1.19 (0.83, 1.71) 

Notes: Line graphs of daily levels of O3

and PM2.5 and daily temperature with 

daily prevalence of respiratory 

symptoms for users of asthma 

maintenance medication 

Reference: Gent et al, (2009, 180399) 

Period of Study: 2000-2003 

Location: New Haven County CT 

Outcome: Increased asthma symptoms 

and medication use 

Study Design: Panel 

Covariates: Season, day of the week, 

date 

Statistical Analysis: Logistic 

regression 

Statistical Package: SAS 

Pollutant: PM2.5 and components 

Averaging Time: Daily 

Mean: (estimated sources, μg/m3) 

Motor Vehicle: 6.6 

Road Dust: 2.3 

Sulfur: 5.5 

Odds Ratio and p-value for 

sources and components of PM2.5. 

Lags are 0, 1 or 2 days, and the mean 

of days 0-2 (L02). 

Source: Motor Vehicle 

EC, Increment = 1000 ng/m3

Wheeze 

L0: 1.04, p = 0.04 

L1: 1.01, p = 0.70 

December 2009 E-185 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Age Groups: Children aged 4-12 Biomass Burning: 0.9 

Oil: 0.8 

Sea Salt: 0.5 

Range (Min, Max): NR 

Copollutant (correlation): NR 

L2: 1.00, p = 0.99 

L02: 1.07, p = 0.06 

Persistent Cough 

L0: 1.01, p = 0.42 

L1: 1.01, p = 0.38 

L2: 0.99, p = 0.44 

L02: 1.03, p = 0.23 

Shortness of Breath 

L0: 1.06, p = 0.001 

L1: 1.01, p = 0.65 

L2: 1.01, p = 0.63 

L02: 1.12, p = 0.01 

Chest Tightness 

L0: 1.03, p = 0.20 

L1: 1.02, p = 0.24 

L2: 1.01, p = 0.59 

L02: 1.10, p = 0.04 

Inhaler Use 

L0: 1.01, p = 0.15 

L1: 1.00, p = 0.72 

L2: 1.00, p = 0.75 

L02: 1.02, p = 0.40 

Zn, Increment = 10 ng/m

3

Wheeze 

L0: 1.00, p = 0.69 

L1: 0.99, p = 0.54 

L2: 1.00, p = 0.89 

L02: 1.00, p = 0.98 

Persistent Cough 

L0: 1.00, p = 0.60 

L1: 1.00, p = 0.77 

L2: 0.99, p = 0.24 

L02: 1.00, p = 0.94 

Shortness of Breath 

L0: 1.02, p = 0.001 

L1: 1.00, p = 0.57 

L2: 1.01, p = 0.49 

L02: 1.04, p = 0.06 

Chest Tightness 

L0: 1.00, p = 0.72 

L1: 1.00, p = 0.96 

L2: 1.01, p = 0.38 

L02: 1.03, p = 0.13 

Inhaler Use 

L0: 1.00, p = 0.41 

L1: 1.00, p = 0.44 

L2: 1.00, p = 0.52 

L02: 1.01, p = 0.53 

Pb, Increment = 5 ng/m

3

Wheeze 

L0: 1.02, p = 0.31 

L1: 1.00, p = 0.91 

L2: 1.01, p = 0.62 

L02: 1.07, p = 0.13 

Persistent Cough 

L0: 1.02, p = 0.25 

L1: 1.00, p = 0.88 

L2: 1.00, p = 0.87 

L02: 1.05, p = 0.12 

Shortness of Breath 

L0: 1.03, p = 0.11 

L1: 0.98, p = 0.51 

L2: 1.03, p = 0.05 

L02: 1.12, p = 0.01 

Chest Tightness 

L0: 1.02, p = 0.31 

L1: 0.99, p = 0.79 

L2: 1.03, p = 0.13 

L02: 1.10, p = 0.02 

Inhaler Use 

L0: 1.01, p = 0.06 

L1: 0.98, p = 0.11 

L2: 1.02, p = 0.04 

L02: 1.04, p = 0.10 

Cu, Increment = 5 ng/m

3

Wheeze 

December 2009 E-186 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

L0: 1.01, p = 0.59 

L1: 0.99, p = 0.55 

L2: 0.99, p = 0.82 

L02: 1.02, p = 0.67 

Persistent Cough 

L0: 1.02, p = 0.13 

L1: 1.02, p = 0.21 

L2: 0.98, p = 0.26 

L02: 1.05, p = 0.04 

Shortness of Breath 

L0: 1.06, p = 0.01 

L1: 1.01, p = 0.74 

L2: 0.96, p = 0.10 

L02: 1.06, p = 0.21 

Chest Tightness 

L0: 10.3, p = 0.23 

L1: 1.02, p = 0.42 

L2: 0.97, p = 0.17 

L02: 1.04, p = 0.39 

Inhaler Use 

L0: 1.01, p = 0.22 

L1: 0.99, p = 0.37 

L2: 1.00, p = 0.70 

L02: 1.01, p = 0.46 

Se, Increment = 1 ng/m

3

Wheeze 

L0: 1.00, p = 0.97 

L1: 0.99, p = 0.52 

L2: 1.00, p = 0.91 

L02: 1.02, p = 0.71 

Persistent Cough 

L0: 1.00, p = 0.84 

L1: 0.99, p = 0.32 

L2: 1.00, p = 0.93 

L02: 0.98, p = 0.43 

Shortness of Breath 

L0: 1.02, p = 0.40 

L1: 0.97, p = 0.10 

L2: 1.01, p = 0.55 

L02: 1.02, p = 0.67 

Chest Tightness 

L0: 1.00, p = 0.79 

L1: 0.97, p = 0.13 

L2: 1.01, p = 0.72 

L02: 0.98, p = 0.61 

Inhaler Use 

L0: 0.99, p = 0.20 

L1: 1.01, p = 0.02 

L2: 0.99, p = 0.32 

L02: 0.99, p = 0.75 

Source: Road Dust 

Si, Increment = 100 ng/m

3

Wheeze 

L0: 1.03, p = 0.03 

L1: 1.00, p = 0.99 

L2: 1.02, p = 0.26 

L02: 1.07, p = 0.04 

Persistent Cough 

L0: 1.02, p = 0.01 

L1: 1.00, p = 0.78 

L2: 1.01, p = 0.60 

L02: 1.05, p = 0.02 

Shortness of Breat1.04, p = 0.01h 

L0: 1.04, p = 0.01 

L1: 1.01, p = 0.60 

L2: 1.01, p = 0.63 

L02: 1.08, p = 0.02 

Chest Tightness 

L0: 1.02, p = 0.20 

L1: 1.02, p = 0.17 

L2: 1.00, p = 0.88 

L02: 1.06, p = 0.10 

Inhaler Use 

L0: 1.02, p = 0.004 

L1: 0.99, p = 0.18 

L2: 1.01, p = 0.45 

December 2009 E-187 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

L02: 1.03, p = 0.09 

Fe, Increment = 100 ng/m

3

Wheeze 

L0: 1.04, p = 0.02 

L1: 1.00, p = 0.80 

L2: 1.00, p = 0.87 

L02: 1.07, p = 0.05 

Persistent Cough 

L0: 1.02, p = 0.06 

L1: 1.01, p = 0.52 

L2: 0.99, p = 0.52 

L02: 1.04, p = 0.04 

Shortness of Breath 

L0: 1.06, p = 0.002 

L1: 1.01, p = 0.65 

L2: 0.98, p = 0.27 

L02: 1.08, p = 0.04 

Chest Tightness 

L0: 1.01, p = 0.47 

L1: 1.02, p = 0.22 

L2: 0.98, p = 0.35 

L02: 1.05, p = 0.21 

Inhaler Use 

L0: 1.02, p = 0.004 

L1: 0.99, p = 0.44 

L2: 1.00, p = 0.91 

L02: 1.03, p = 0.08 

Al, Increment = 50 ng/m

3

Wheeze 

L0: 1.02, p = 0.17 

L1: 1.01, p = 0.73 

L2: 1.02, p = 0.30 

L02: 1.07, p = 0.03 

Persistent Cough 

L0: 1.03, p = 0.001 

L1: 1.00, p = 0.96 

L2: 1.00, p = 0.68 

L02: 1.06, p = 0.01 

Shortness of Breath 

L0: 1.05, p = 0.002 

L1: 1.01, p = 0.63 

L2: 1.01, p = 0.59 

L02: 1.09, p = 0.004 

Chest Tightness 

L0: 1.02, p = 0.21 

L1: 1.02, p = 0.18 

L2: 1.00, p = 0.94 

L02: 1.07, p = 0.04 

Inhaler Use 

L0: 1.02, p = 0.02 

L1: 0.99, p = 0.27 

L2: 1.01, p = 0.50 

L02: 1.02, p = 0.11 

Ca, Increment = 50 ng/m

3

Wheeze 

L0: 1.07, p = 0.02 

L1: 1.00, p = 0.97 

L2: 1.01, p = 0.74 

L02: 1.14, p = 0.04 

Persistent Cough 

L0: 1.05, p = 0.01 

L1: 0.99, p = 0.64 

L2: 1.00, p = 0.90 

L02: 1.09, p = 0.03 

Shortness of Breath 

L0: 1.10, p = 0.002 

L1: 1.02, p = 0.66 

L2: 1.00, p = 0.89 

L02: 1.18, p = 0.01 

Chest Tightness 

L0: 1.04, p = 0.26 

L1: 1.03, p = 0.43 

L2: 1.00, p = 0.93 

L02: 1.14, p = 0.07 

Inhaler Use 

L0: 1.04, p = 0.01 

December 2009 E-188 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

L1: 0.97, p = 0.06 

L2: 1.01, p = 0.44 

L02: 1.04, p = 0.17 

Ba, Increment = 10 ng/m

3

Wheeze 

L0: 0.99, p = 0.57 

L1: 1.00, p = 0.92 

L2: 0.99, p = 0.48 

L02: 0.99, p = 0.81 

Persistent Cough 

L0: 1.00, p = 0.83 

L1: 1.01, p = 0.38 

L2: 0.99, p = 0.32 

L02: 1.00, p = 0.81 

Shortness of Breath 

L0: 1.04, p = 0.02 

L1: 1.00, p = 0.96 

L2: 0.96, p = 0.05 

L02: 1.03, p = 0.38 

Chest Tightness 

L0: 1.01, p = 0.63 

L1: 1.00, p = 0.88 

L2: 0.98, p = 0.30 

L02: 1.02, p = 0.51 

Inhaler Use 

L0: 1.01, p = 0.08 

L1: 0.99, p = 0.19 

L2: 1.00, p = 0.92 

L02: 1.01, p = 0.36 

Ti, Increment = 5 ng/m

3

Wheeze 

L0: 1.00, p = 0.59 

L1: 0.99, p = 0.49 

L2: 1.01, p = 0.34 

L02: 1.01, p = 0.56 

Persistent Cough 

L0: 1.00, p = 0.57 

L1: 1.00, p = 0.55 

L2: 1.00, p = 0.30 

L02: 1.01, p = 0.29 

Shortness of Breath 

L0: 1.01, p = 0.01 

L1: 1.00, p = 0.56 

L2: 1.00, p = 0.60 

L02: 1.03, p = 0.05 

Chest Tightness 

L0: 1.00, p = 0.34 

L1: 1.00, p = 0.55 

L2: 0.99, p = 0.49 

L02: 1.01, p = 0.52 

Inhaler Use 

L0: 1.00, p = 0.72 

L1: 1.00, p = 0.30 

L2: 1.00, p = 0.67 

L02: 1.00, p = 0.66 

Source: Sulfur 

S, Increment = 1000 ng/m

3

Wheeze 

L0: 0.98, p = 0.43 

L1: 0.99, p = 0.62 

L2: 1.02, p = 0.29 

L02: 1.00, p = 0.99 

Persistent Cough 

L0: 1.00, p = 0.84 

L1: 1.00, p = 0.69 

L2: 1.02, p = 0.21 

L02: 1.02, p = 0.27 

Shortness of Breath 

L0: 1.01, p = 0.63 

L1: 0.99, p = 0.71 

L2: 1.01, p = 0.55 

L02: 1.01, p = 0.79 

Chest Tightness 

L0: 0.99, p = 0.80 

L1: 1.01, p = 0.62 

December 2009 E-189 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

L2: 1.01, p = 0.81 

L02: 1.02, p = 0.68 

Inhaler Use 

L0: 0.99, p = 0.13 

L1: 1.00, p = 0.81 

L2: 1.02, p = 0.04 

L02: 1.00, p = 0.81 

P, Increment = 50 ng/m

3

Wheeze 

L0: 0.98, p = 0.39 

L1: 0.98, p = 0.48 

L2: 1.02, p = 0.38 

L02: 0.99, p = 0.89 

Persistent Cough 

L0: 1.00, p = 0.75 

L1: 0.99, p = 0.69 

L2: 1.01, p = 0.38 

L02: 1.03, p = 0.30 

Shortness of Breath 

L0: 1.01, p = 0.61 

L1: 0.99, p = 0.71 

L2: 1.01, p = 0.67 

L02: 1.01, p = 0.78 

Chest Tightness 

L0: 1.00, p = 0.88 

L1: 1.01, p = 0.72 

L2: 1.00, p = 0.87 

L02: 1.02, p = 0.67 

Inhaler Use 

L0: 0.98, p = 0.15 

L1: 1.00, p = 0.83 

L2: 1.01, p = 0.11 

L02: 1.00, p = 0.99 

Source: Biomass Burning 

K, Increment = 50 ng/m

3

Wheeze 

L0: 0.98, p = 0.06 

L1: 0.99, p = 0.43 

L2: 1.00, p = 0.85 

L02: 0.96, p = 0.04 

Persistent Cough 

L0: 1.00, p = 0.64 

L1: 1.00, p = 0.83 

L2: 1.00, p = 0.46 

L02: 1.00, p = 0.86 

Shortness of Breath 

L0: 1.01, p = 0.01 

L1: 0.98, p = 0.09 

L2: 1.00, p = 0.38 

L02: 1.00, p = 0.79 

Chest Tightness 

L0: 1.00, p = 0.02 

L1: 0.99, p = 0.24 

L2: 0.98, p = 0.07 

L02: 0.99, p = 0.67 

Inhaler Use 

L0: 1.00, p = 0.68 

L1: 0.99, p = 0.05 

L2: 1.00, p = 0.59 

L02: 0.99, p = 0.28 

Source: Oil 

V, Increment = 10 ng/m

3

Wheeze 

L0: 0.99, p = 0.73 

L1: 0.96, p = 0.03 

L2: 0.99, p = 0.56 

L02: 0.93, p = 0.04 

Persistent Cough 

L0: 1.01, p = 0.56 

L1: 0.99, p = 0.24 

L2: 0.98, p = 0.01 

L02: 0.96, p = 0.05 

Shortness of Breath 

L0: 1.01, p = 0.46 

L1: 0.98, p = 0.24 

December 2009 E-190 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

L2: 1.00, p = 0.83 

L02: 0.98, p = 0.58 

Chest Tightness 

L0: 0.99, p = 0.71 

L1: 0.98, p = 0.32 

L2: 0.98, p = 0.23 

L02: 0.94, p = 0.12 

Inhaler Use 

L0: 0.98, p = 0.12 

L1: 1.00, p = 0.68 

L2: 0.99, p = 0.22 

L02: 0.96, p = 0.03 

Ni, Increment = 5 ng/m

3

Wheeze 

L0: 1.01, p = 0.59 

L1: 0.97, p = 0.09 

L2: 1.00, p = 0.76 

L02: 0.99, p = 0.72 

Persistent Cough 

L0: 1.01, p = 0.21 

L1: 0.99, p = 0.57 

L2: 0.99, p = 0.23 

L02: 1.00, p = 0.99 

Shortness of Breath 

L0: 1.04, p = 0.05 

L1: 0.98, p = 0.36 

L2: 1.00, p = 0.81 

L02: 1.04, p = 0.32 

Chest Tightness 

L0: 1.01, p = 0.58 

L1: 1.00, p = 0.89 

L2: 0.98, p = 0.27 

L02: 1.01, p = 0.84 

Inhaler Use 

L0: 1.01, p = 0.48 

L1: 1.00, p = 0.83 

L2: 0.99, p = 0.51 

L02: 1.01, p = 0.48 

Source: Sea Salt 

Na, Increment = 100 ng/m

3

Wheeze 

L0: 0.98, p = 0.23 

L1: 1.00, p = 0.80 

L2: 1.00, p = 0.88 

L02: 0.97, p = 0.29 

Persistent Cough 

L0: 1.00, p = 0.58 

L1: 0.99, p = 0.19 

L2: 1.00, p = 0.61 

L02: 0.98, p = 0.21 

Shortness of Breath 

L0: 1.00, p = 0.94 

L1: 0.99, p = 0.46 

L2: 1.01, p = 0.63 

L02: 0.99, p = 0.74 

Chest Tightness 

L0: 0.99, p = 0.43 

L1: 0.99, p = 0.75 

L2: 1.00, p = 0.88 

L02: 0.98, p = 0.61 

Inhaler Use 

L0: 0.99, p = 0.35 

L1: 1.00, p = 0.61 

L2: 1.00, p = 0.85 

L02: 0.99, p = 0.37 

Cl, Increment = 10 ng/m

3

Wheeze 

L0: 1.00, p = 0.89 

L1: 1.00, p = 0.88 

L2: 1.00, p = 0.38 

L02: 1.00, p = 0.81 

Persistent Cough 

L0: 1.00, p = 0.31 

L1: 1.00, p = 0.31 

L2: 1.00, p = 0.51 

December 2009 E-191 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

L02: 1.00, p = 0.06 

Shortness of Breath 

L0: 1.00, p = 0.89 

L1: 1.00, p = 0.94 

L2: 1.00, p = 0.70 

L02: 1.00, p = 0.80 

Chest Tightness 

L0: 1.00, p = 0.24 

L1: 1.00, p = 0.28 

L2: 1.00, p = 0.52 

L02: 1.00, p = 0.65 

Inhaler Use 

L0: 1.00, p = 0.69 

L1: 1.00, p = 0.52 

L2: 1.00, p = 0.51 

L02: 1.00, p = 0.83 

Odds Ratio (95%CI) from repeated 

measures logistic regression models 

of respiratory symptoms and daily 

source concentrations of PM2.5. 

Lag 0 Model 

Wheeze, p = 0.23 

Motor Vehicle: 1.05 (0.99-1.10) 

Road Dust: 1.10 (1.01-1.19) 

Sulfur: 0.97 (0.94-1.00) 

Biomass Burning: 0.80 (0.66-0.98) 

Oil: 1.02 (0.86-1.20) 

Sea Salt: 0.96 (0.86-1.07) 

Persistent Cough, p < 0.001 

Motor Vehicle: 1.02 (0.99-1.04) 

Road Dust: 1.06 (1.01-1.11) 

Sulfur: 1.00 (0.98-1.01) 

Biomass Burning: 0.97 (0.92-1.03) 

Oil: 1.02 (0.95-1.10) 

Sea Salt: 0.99 (0.92-1.07) 

Shortness of Breath, p < 0.001 

Motor Vehicle: 1.06 (1.01-1.11) 

Road Dust: 1.12 (1.02-1.22) 

Sulfur: 0.98 (0.94-1.02) 

Biomass Burning: 1.05 (0.95-1.17) 

Oil: 1.07 (0.92-1.26) 

Sea Salt: 1.01 (0.92-1.12) 

Chest Tightness, p < 0.001 

Motor Vehicle: 1.02 (0.97-1.08) 

Road Dust: 1.04 (0.95-1.15) 

Sulfur: 0.99 (0.94-1.03) 

Biomass Burning: 1.06 (0.95-1.18) 

Oil: 0.99 (0.82-1.18) 

Sea Salt: 0.95 (0.84-1.08) 

Inhaler Use, p < 0.001 

Motor Vehicle: 1.02 (1.00-1.05) 

Road Dust: 1.06 (1.02-1.11) 

Sulfur: 0.98 (0.97-1.00) 

Biomass Burning: 1.00 (0.96-1.03) 

Oil: 0.98 (0.91-1.05) 

Sea Salt: 0.99 (0.94-1.04) 

Lag 02 Model 

Wheeze, p = 0.86 

Motor Vehicle: 1.10 (1.01-1.19) 

Road Dust: 1.26 (1.05-1.51) 

Sulfur: 0.98 (0.92-1.04) 

Biomass Burning: 0.64 (0.46-0.88) 

Oil: 0.80 (0.56-1.08) 

Sea Salt: 0.91 (0.82-1.16) 

Persistent Cough, p < 0.001 

Motor Vehicle: 1.03 (0.98-1.09) 

Road Dust: 1.16 (1.02-1.32) 

Sulfur: 1.01 (0.98-1.05) 

Biomass Burning: 0.93 (0.81-1.06) 

Oil: 0.84 (0.71-1.00) 

Sea Salt: 0.88 (0.77-1.01) 

December 2009 E-192 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Shortness of Breath, p = 0.006 

Motor Vehicle: 1.12 (1.01-1.24) 

Road Dust: 1.28 (1.05-1.55) 

Sulfur: 0.97 (0.90-1.04) 

Biomass Burning: 0.78 (0.52-1.18) 

Oil: 0.94 (0.69-1.29) 

Sea Salt: 1.01 (0.79-1.29) 

Chest Tightness, p = 0.39 

Motor Vehicle: 1.08 (0.98-1.20) 

Road Dust: 1.20 (0.97-1.49) 

Sulfur: 1.00 (0.92-1.08) 

Biomass Burning: 0.87 (0.62-1.22) 

Oil: 0.80 (0.58-1.10) 

Sea Salt: 0.95 (0.71-1.27) 

Inhaler Use, p < 0.001 

Motor Vehicle: 1.03 (0.98-1.08) 

Road Dust: 1.09 (1.00-1.19) 

Sulfur: 1.00 (0.97-1.03) 

Biomass Burning: 0.95 (0.87-1.04) 

Oil: 0.92 (0.81-1.05) 

Sea Salt: 0.97 (0.88-1.07) 

Odds Ratio (95%CI) from repeated 

measures logistic regression models 

of respiratory symptoms and daily 

source concentrations of PM2.5 when 

copollutants are included. 

Wheeze 

Motor Vehicle 

NO

2: 1.03 (0.98-1.08) 

CO: 1.05 (0.99-1.11) 

SO

2: 1.04 (0.99-1.09) 

O

3: 1.06 (0.97-1.16) 

Road Dust 

NO

2: 1.11 (1.02-1.20) 

CO: 1.10 (1.01-1.19) 

SO

2: 1.10 (1.01-1.19) 

O

3: 1.11 (1.01-1.23) 

Sulfur 

NO

2: 0.96 (0.92-0.99) 

CO: 0.97 (0.94-1.01) 

SO

2: 0.97 (0.93-1.00) 

O

3: 0.95 (0.91-1.00) 

Biomass Burning 

NO

2: 0.79 (0.65-0.98) 

CO: 0.80 (0.66-0.98) 

SO

2: 0.79 (0.64-0.98) 

O

3: 0.74 (0.57-0.97) 

Oil 

NO

2: 1.02 (0.87-1.21) 

CO: 1.02 (0.86-1.20) 

SO

2: 1.01 (0.86-1.19) 

O

3: 0.92 (0.62-1.39) 

Sea Salt 

NO

2: 0.96 (0.85-1.07) 

CO: 0.96 (0.86-1.08) 

SO

2: 0.95 (0.85-1.07) 

O

3: 1.01 (0.72-1.40) 

Inhaler Use 

Motor Vehicle 

NO

2: 1.02 (0.99-1.04) 

CO: 1.02 (0.99-1.05) 

SO

2: 1.02 (0.99-1.04) 

O

3: 1.02 (0.98-1.07) 

Road Dust 

NO

2: 1.06 (1.02-1.10) 

CO: 1.06 (1.02-1.11) 

SO

2: 1.06 (1.02-1.11) 

O

3: 1.06 (1.00-1.13) 

Sulfur 

NO

2: 0.98 (0.96-1.00) 

CO: 0.98 (0.96-1.00) 

SO

2: 0.98 (0.96-1.00) 

December 2009 E-193 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

O3: 0.97 (0.95-1.00) 

Biomass Burning 

NO2: 1.00 (0.96-1.03) 

CO: 0.99 (0.96-1.03) 

SO2: 0.99 (0.96-1.03) 

O3: 0.99 (0.95-1.03) 

Oil 

NO2: 0.98 (0.91-1.05) 

CO: 0.97 (0.91-1.04) 

SO2: 0.97 (0.91-1.04) 

O3: 1.03 (0.88-1.22) 

Sea Salt 

NO2: 0.99 (0.94-1.04) 

CO: 0.99 (0.94-1.04) 

SO2: 0.99 (0.94-1.04) 

O3: 1.01 (0.88-1.15) 

Reference: Girardot et al. (2006, 

088271) 

Period of Study: 

Aug 2002-Oct 2002 

Jun 2003-Aug 2003 

Location: Charlies Bunion Trail (portion 

of Appalachia Trail) 

Outcome: Pulmonary 

function/spirometry-FVC, FEV1, PEF, 

FVC/FEV1, FEF25-75 

Age Groups: 18-82 yr 

Study Design: Cohort 

N: 354 hikers 

Statistical Analyses: Multiple linear 

regression 

Covariates: Age, h hiked, mean 

temperature, sex, smoking status, 

history of asthma or wheeze symptoms, 

carriage of backpack, whether reaching 

summit or not 

Season: Fall 2002, Summer 2003 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean: 

Trail: 13.9 ± 8.2 

Estimated personal: 15.0 ± 7.4 

Range (Min, Max): 

Trail: 1.6 , 38.4 

Estimated personal: 

0.21, 41.9 

Copollutant (correlation): O3 (r=0.67, 

for estimated personal exposure) 

PM Increment: 1 μg/m3

% Change ± CI 

p value 

Univariate: 

FVC: 0.023 ± 0.035 

0.51 

FEV1: 0.015 ± 0.029 

0.607 

PEF: 0.185 ± 0.091 

0.043 

FVC/FEV1: 0.003 ± 0.023 

0.905 

FEF25-75%: 0.052 ± 0.093 

0.578 

Adjusted: FVC: 0.007 +/ 0.040 

0.966 

FEV1: 0.003 ± 0.033 

0.937 

PEF: 0.258 ± 0.103 

0.013 

FVC/FEV1: - 0.011 ± 0.027 

0.676 

FEF25-75%: - 0.041 ± 0.109 

0.707 

Spirometry result for each quintile ± CI 

Quintile 1 (6.0 μg/m3): FVC (L): 

Prehike: 4.32 ± 0.13 

Posthike: 4.33 ± 0.12 

FEV1 (L): Prehike: 3.39 ± 0.10 

Posthike: 3.40 ± 0.10 

FEV1/FVC (%): Prehike: 78.66 ± 0.86 

Posthike: 78.63 ± 0.81 

FEF25-75% (L/sec): Prehike: 3.27 ±

0.14 

Posthike: 3.26 ± 0.14 

PEF (L/sec): Prehike: 7.91 +/ 0.22 

Posthike: 7.58 ± 0.22 

Quintile 2 (10.4 μg/m3): FVC (L): 

Prehike: 4.30 ± 0.11 

Posthike: 4.30 ± 0.11 

FEV1 (L): Prehike: 3.42 ± 0.09 

Posthike: 3.43 ± 0.09 

FEV1/FVC (%): Prehike: 79.37 ± 0.71 

Posthike: 79.55 ± 0.69 

FEF25-75% (L/sec): Prehike: 3.39 ±

0.14 

Posthike: 3.38 ± 0.14 

PEF (L/sec): Prehike: 8.37 +/ 0.23 

Posthike: 8.26 ± 0.25 

Quintile 3 (14.8 μg/m3): FVC (L): 

Prehike: 4.34 ± 0.12 

Posthike: 4.33 ± 0.12 

FEV1 (L): Prehike: 3.42 ± 0.10 

Posthike: 3.40 ± 0.09 

FEV1/FVC (%): Prehike: 79.20 ± 0.81 

Posthike: 78.83 ± 0.80 

FEF25-75% (L/sec): Prehike: 3.19 ±

0.13 

Posthike: 3.21 ± 0.13 

PEF (L/sec): Prehike: 8.12 +/ 0.25 

Posthike: 7.89 ± 0.25 

Quintile 4 (17.9 μg/m3): 

December 2009 E-194 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

FVC (L): Prehike: 4.23 ± 0.11 

Posthike: 4.23 ± 0.11 

FEV1 (L): Prehike: 3.36 ± 0.10 

Posthike: 3.36 ± 0.10 

FEV1/FVC (%): Prehike: 79.18 ± 0.81 

Posthike: 79.26 ± 0.79 

FEF25-75% (L/sec): Prehike: 3.34 ±

0.15 

Posthike: 3.30 ± 0.15 

PEF (L/sec): Prehike: 7.75 +/ 0.25 

Posthike: 7.73 ± 0.26 

Quintile 5 (25.6 μg/m3): FVC (L): 

Prehike: 4.15 ± 0.11 

Posthike: 4.18 ± 0.12 

FEV1 (L): Prehike: 3.31 ± 0.09 

Posthike: 3.33 ± 0.10 

FEV1/FVC (%): Prehike: 79.73 ± 0.66 

Posthike: 79.55 ± 0.64 

FEF25-75% (L/sec): Prehike: 3.22 ±

0.14 

Posthike: 3.24 ± 0.14 

PEF (L/sec): Prehike: 7.72 +/ 0.22 

Posthike: 7.77 ± 0.23 

Overall (15.0 μg/m3): FVC (L): Prehike: 

4.27 ± 0.05 

Posthike: 4.27 ± 0.05 

FEV1 (L): Prehike: 3.38 ± 0.04 

Posthike: 3.38 ± 0.04 

FEV1/FVC (%): Prehike: 79.2 ± 0.34 

Posthike: 79.2 ± 0.33 

FEF25-75% (L/sec): Prehike: 3.28 ±

0.06 

Posthike: 3.28 ± 0.06 

PEF (L/sec): Prehike: 7.97 +/ 0.11 

Posthike: 7.97 ± 0.11 

Reference: Hertz-Picciotta et al. (2007, 

135917) 

Period of Study: 1994-2003 

Location: Teplice and Prachatice, 

Czech Republic 

Outcome: Lower respiratory 

illness-croup (J05, J04), acute 

bronchitis (J20), acute bronchiolitis 

(J21) 

Age Groups: Neonates followed for 

2-4.5 yr 

Study Design: Cohort 

N: 1133 children 

Statistical Analyses: Generalized 

linear longitudinal models 

Covariates: District, mother’s age, 

mother’s education, mother or adult 

smoke, child’s sex, season, day of the 

week, fuel for heating and/or cooking, 

breastfeeding category, number of other 

children, temperature 

Season: Winter, spring, summer and 

fall 

Dose-response Investigated? No 

Statistical Package: SUDAAN version 

8 

Lags Considered: 1-3, 1-7, 1-14, 1-30, 

1-45 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

PAH: 22.3 (SD-16 for 3-day avg and 11 

for 45-day avg) 

PM Increment: 25 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Birth-23 mo: 

1.30 [1.08, 1.58] lag 1-30 

2-4.5 yr: 

1.23 [0.94, 1.62] lag 1-30 

RR Estimate for categories of 

exposure [Lower CI, Upper CI] lag: 

Crude RR: 

Birth-23 mo: 

> 50 μg/m3

: 2.26 [1.81, 2.82] lag 1-30 

25-50 μg/m3

: 1.48 [1.32, 1.65] lag 1-30 

< 25 μg/m3

: 

Referent 

2-4.5 yr: 

> 50 μg/m3

: 3.66 [2.07, 6.48] lag 1-30 

25-50 μg/m3: 1.60 [1.41, 1.82] lag 1-30 

< 25 μg/m3

: 

Referent 

December 2009 E-195 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hertz- Picciotta et al. 

(2007, 135917) 

Period of Study: 1994-2003 

Location: Teplice and Prachatice, 

Czech Republic 

Outcome: Lower respiratory 

illness-croup (J05, J04), acute 

bronchitis (J20), acute bronchiolitis 

(J21) 

Age Groups: Neonates followed for 

2-4.5 yr 

Study Design: Cohort 

N: 1133 children 

Statistical Analyses: Generalized 

linear longitudinal models 

Covariates: District, mother’s age, 

mother’s education, mother or adult 

smoke, child’s sex, season, day of the 

week, fuel for heating and/or cooking, 

breastfeeding category, number of other 

children, temperature 

Dose-response Investigated? No 

Statistical Package: SUDAAN version 

8 

Lags Considered: 1-3, 1-7, 1-14, 1-30, 

1-45 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

PAH: 

52.5 ng/m3

 (SD-57 ng/m3 for 3-day avg 

and 46 ng/m3

 for 45-day avg) 

PAH Increment: 100 ng/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Birth-23 mos: 

1.29 [1.07, 1.54] lag 1-30 

2-4.5 yr: 

1.56 [1.22, 2.00] lag 1-30 

RR Estimate for categories of exposure 

[Lower CI, Upper CI] lag: 

Crude RR: 

Birth-23 mos: 

> 100 ng/m3

: 2.52 [2.22, 2.87] lag 1-30 

40-100 ng/m3

: 1.87 [1.65, 2.13] lag 1-30

< 40 ng/m3: Reference 

2-4.5 yr: 

> 100 ng/m3

: 2.26 [1.93, 2.65] lag 1-30 

40-100 ng/m3: 1.40 [1.20, 1.64] lag 1-30

< 40 ng/m3

: Reference 

Reference: Hogervorst, et al. (2006, 

156559) 

Period of Study: 2002 

Location: Maastricht, the Netherlands 

(six schools selected) 

Outcome: Decreased lung function 

Age Groups: 8-13 yr 

Study Design: Multivariate linear 

regression (enter method) analysis 

N: 342 children 

Statistical Analyses: ANOVA, chi 

square 

Covariates: Independent variables: 

Age, height, gender, smoking at home 

by parents, pets, use of ventilation 

hoods during cooking, presence of 

unvented geysers, tapestry in the 

home, indoor/outdoor time, education 

level of parents. 

Dependent variables: lung function 

indices 

Dose-response Investigated? No 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD): 19.0 (3.2) 

Monitoring Stations: 6 

Copollutant: 

PM10

Total Suspended Particles (TSP) 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

FEV: 3.62 [0.50,7.63] lag NR 

FVC: 1.80 [-2.10, 5.80] lag NR 

FEF: 5.93 [-2.34, 14.89] lag NR 

Reference: Holguin et al, (2007, 

099000) 

Period of Study: 

Location: Ciudad Juarez, Mexico 

Outcome: FeNO, FEV1

Study Design: Panel 

Covariates: sex, age, body mass 

index, day of week, season, yr of 

maternal and paternal education, 

passive smoking 

Statistical Analysis: linear and 

nonlinear mixed effects models 

Age Groups: 6-12 yr 

Pollutant: PM2.5

Averaging Time: 48 h 

Mean (SD) Unit: 17.5 (8.9) μg/m3

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: NR 

Relative Risk (Min CI, Max CI) 

Lag 

Results not given in table form, but 

abstract states that no significant 

associations with PM2.5 were observed. 

December 2009 E-196 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hong et al. (2007, 091347) 

Period of Study: Mar 23-May 2004 

Location: School on the Dukjeok Island 

near Incheon City, Korea 

Outcome: Peak expiratory flow rate 

(PEFR) 

Age Groups: 3rd-6th grade (mean 

age=9.6 yr) 

Study Design: Panel study 

N: 43 schoolchildren 

Statistical Analyses: Mixed linear 

regression 

Covariates: age, sex, height, weight, 

asthma history, and passive smoking 

exposure at home 

Dose-response Investigated? No 

Lags Considered: 0, 1, 2, 3, 4, 5 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 20.27 (8.23) 

50th(Median): 22.07 

Range (Min, Max): 5.94-36.28 

Copollutant: 

PM10

Components of PM10 

(Fe, Mn, Pb, Zn, Al) 

Effect Estimate: 

Regression coefficients of morning and 

daily mean PEFR on PM2.5

Lag 1 (PM2.5) 

Morning PEFR 

Crude: ß= -0.14, p=0.12 

Adjusted: ß= -0.54, p,0.01 

Mean PEFR 

Crude: ß= -0.15, p=0.02 

Adjusted: ß= -0.54, p,0.01 

Regression coefficients of morning and 

daily mean PEFR on PM2.5 and GSTM1 

and GSTT1 genotype using linear 

mixed-effects regression 

Lag 1 (PM2.5) 

Morning PEFR: ß= -0.57, p < 0.01 

Mean PEFR: ß= -0.56, p < 0.01 

GSTM1 

Morning PEFR: ß= 20.04, p=0.25 

Mean PEFR: ß= 18.75, p=0.28 

GSTT1 

Morning PEFR: ß= 2.31, p=0.89 

Mean PEFR: ß= 1.75, p=0.91 

Reference: Jansen, et al. (2005, 

082236) 

Period of Study: 1987-2000 

Location: Seattle, WA 

Outcome: FENO: fractional exhaled 

nitrogen oxide, Spirometry, Blood 

pressure, SaO2: oxygen saturation, 

Pulse rate 

Age Groups: 60-86-yr-old 

Study Design: Short-term crosssectional case series 

N: 16 subjects diagnosed with COPD, 

asthma, or both 

Statistical Analyses: Linear mixed 

effects model with random intercepts 

Covariates: Age, relative humidity, 

temperature, medication use 

Season: Winter 2002-2003 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Fixed-Site Monitor: 14.0

All Subjects (N=16) 

Indoor, home: 7.29 

Outdoor, home: 10.47 

Asthmatic Subjects (N=7) 

Indoor, home: 7.25 

Outdoor, home: 8.99 

COPD Subjects (N=9) 

Indoor, home: 7.33 

Outdoor, home: 11.66 

Range (Min, Max): 

Fixed-Site Monitor: 1.3, 44

IQR 

All Subjects 

Indoor, home: 4.05 

Outdoor, home: 8.87 

Asthmatic Subjects 

Indoor, home: 5.72 

Outdoor, home: 7.55 

COPD Subjects 

Indoor, home: (3.18 

Outdoor, home: 6.71 

PM Increment: PM2.5: 10 μg/m3

Slope [95% CI]: dependence of FENO 

concentration [ppb] on PM2.5

Asthmatic Subjects 

Indoor, home: 3.69 [-0.74: 8.12] 

Outdoor, home: 4.23 [1.33: 7.13]* 

Copd Subjects 

Indoor, home: -0.35 [-7.45: 6.75] 

Outdoor, home: 3.83 [-1.84: 9.49] 

Results indicate that FENO may be a 

more sensitive biomarker of PM 

exposure than other traditional health 

endpoints. 

December 2009 E-197 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Johnston, et al. (2006, 

091386) 

Period of Study: 7 mo 

(Apr-Nov 2004) 

Location: Darwin, Australia 

Outcome: Asthma symptoms 

Age Groups: All Ages 

Study Design: Time-series 

N: 251 people 

(130 adults, 121 children 

Statistical Analyses: Logistic 

regression model 

Covariates: Minimum air temperature, 

doctor visits for influenza and the 

prevalence of asthma symptoms and, 

the fungal spore count and both onset 

of asthma symptoms and 

commencement of reliever medication 

Season: “Dry season”- note Southern 

Hemisphere 

Dose-response Investigated? No 

Statistical Package: STATA8 

Lags Considered: 0-5 days 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD): 11.1 (5.4) 

Range (Min, Max): 2.2, 36.5 

PM Component: Vegetation fire smoke 

(95%) and motor vehicle emissions 

(5%) 

Monitoring Stations: 1 

PM Increment: 5 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Symptoms attributable to asthma 

Overall: 1.000 (0.98,1.01) 

Adults: 1.000 (0.976,1.026) 

Children: 1.008 (0.980, 1.037) 

Using preventer: 1.013 (0.990, 1.037) 

Became symptomatic 

Overall: 1.150 (1.07,1.23) 

Adults: 1.165 (1.058,1.284) 

Children: 1.148 (1.042,1.264) 

Using preventer: 1.181 (1.076,1.296) 

Used Reliever 

Overall: 1.000 (0.98,1.02) 

Adults: 1.007 (0.980, 1.035) 

Children: 1.002 (0.972,1.034) 

Using preventer: 1.020 (1.000,1.042) 

Commenced Reliever 

Overall: 1.120 (1.03,1.210) 

Adults: 1.141 (1.021, 1.275) 

Children: 1.112 (0.994,1.243) 

Using preventer: 1.129 (1.013,1.257) 

Commenced Oral Steroids 

Overall: 1.310 (1.03,1.66) 

Adults: 1.601 (1.192, 2.150) 

Children: 0.995 (0.625,1.459) 

Using preventer: 1.350 (1.040,1.752) 

Asthma Attack 

Overall: 0.980 (0.94,1.04) 

Adults: 1.026 (0.962, 1.095) 

Children: 0.832 (0.731, 0.946) 

Using preventer: 1.002 (0.934,1.075) 

Exercise induced asthma 

Overall: 0.990 (0.95,1.03) 

Adults: 0.998 (0.943, 1.056) 

Children: 0.982 (0.899,1.071) 

Using preventer: 1.002 (0.942,1.067) 

Saw a health professional for asthma

Overall: 1.030 (0.91,1.16) 

Adults: 1.079 (0.899, 1.296) 

Children: 1.003 (0.841,1.195) 

Using preventer: 0.980 (0.847,1.133) 

Missed school or work due to 

asthma 

Overall: 1.025 (0.9284,1.131) 

Adults: 1.077 (0.923, 1.247) 

Children: 1.000 (0.873,1.458) 

Using preventer: 1.005 (0.897,1.124) 

Mean daily number of asthma 

symptoms 

Overall: 1.003 (0.99,1.01) 

Adults: 0.998 (0.984, 1.012) 

Children: 1.004 (0.985,1.023) 

Using preventer: 1.013 (0.999,1.028) 

Mean Daily number of applications of 

reliever 

Overall: 1.002 (0.993,1.010) 

Adults: 1.001 (0.986, 1.016) 

Children: 1.000 (0.980,1.021) 

Using preventer: 1.005 (0.994,1.017) 

December 2009 E-198 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Koenig et al. (2003, 

156653) 

Period of Study: Winter 2000-2001, 

Spring 2001 

Location: Seattle, WA 

Outcome: Exhaled NO (eNO) 

Age Groups: 6-13 yr old 

Study Design: Cohort 

N: 19 children 

Statistical Analyses: Linear mixedeffects regression 

Covariates: Medication use, ambient 

NO reading for specific individual on 

specific day of session, mean ambient 

NO for subject during session, mean 

ambient NO for subject during all 

sessions 

Season: Winter, Spring 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM2.5

Averaging Time: 10 consecutive days 

Mean (SD): Outdoor: 13.3 (1.4) 

Indoor: 11.1 (4.9) 

Personal: 13.4 (3.2) 

Central-site: 10.1 (5.7) 

Range (Min, Max): Outdoor: Max: 40.4 

Indoor: Max: 36.3 

Personal: Max: 49.4 

Central-site: NR 

Monitoring Stations: Outdoor: NR 

Indoor: NR 

Personal: NR 

Central-site: 3 

Copollutant (correlation): Outdoor 

PM-central-site NO: 0.50 

For NO values < 100 ppb, outdoor PMcentral-site NO: 0.04 

PM Increment: 10 μg/m3

Results presented as change in eNO 

(95% CI) 

Among ICS* nonuser 

Personal monitor 4.48 (1.02, 7.93) 

Outdoor monitor 4.28 (1.38, 7.17) 

Indoor monitor 4.21 (1.02, 7.41) 

Central site 3.82 (1.22, 6.43) 

Among ICS* user 

Personal monitor -0.09 (-2.39, 2.21) 

Outdoor monitor 0.74 (-2.28, 3.76) 

Indoor monitor -1.11 (-5.08, 2.87) 

Central site 1.28 (-1.23, 3.79) 

* ICS: Inhaled corticosteroid 

Reference: Koenig et al. (2003, 

156653) 

Period of Study: Winter 2000-2001, 

Spring 2001 

Location: Seattle, WA 

Outcome: Increased exhaled nitric 

oxide (eNO) 

Age Groups: 6-13 yr of age 

Study Design: Combined recursive 

and predictive model 

N: 19 children with asthma 

Statistical Analyses: Linear mixed 

effects model 

Covariates: Residence type, air 

cleaner, avg outdoor temperature, avg 

daily rainfall 

Season: Winter, Spring 

Dose-response Investigated? No 

Statistical Package: 

STATA 7.0 for health analyses, SAS 8.0 

Pollutant: PM2.5

Averaging Time: Daily 

Mean: Home indoor 9.5 

Home outdoor 11.1 

Recursive model Eag: 7.0 

Recursive model Eig: 2.1 

Predictive model Eag: 6.0 

Predictive model Eig: 4.0 

Combined model Eag: 6.4 

Combined model Eig: 3.2 

25th: Home indoor 5.7 

Home outdoor 6.3 

Recursive model Eag: 4.2 

Recursive model Eig: 0.0 

Predictive model Eag: 3.4 

Predictive model Eig: 0.9 

Combined model Eag: 3.7 

Combined model Eig: 0.5 

50th(Median): Home indoor 7.6 

Home outdoor 9.5 

Recursive model Eag: 5.9 

Recursive model Eig: 1.2 

Predictive model Eag: 5.0 

Predictive model Eig: 2.2 

Combined model Eag: 5.5 

Combined model Eig: 1.7 

75th: Home indoor 10.8 

Home outdoor 14.6 

Recursive model Eag: 9.2 

Recursive model Eig: 2.3 

Predictive model Eag: 7.5 

Predictive model Eig: 4.9 

Combined model Eag: 7.8 

Combined model Eig: 4.2 

Range (Min, Max): Home indoor 2.3, 

36.3 

Home outdoor 2.8, 40.4 

Recursive Eag: 1.8,22.6 

Recursive Eig: 0.0,17.2 

Predictive Eag: 1.3,22.6 

Predictive Eig: 0.0,33.0 

Combined Eag: 1.3,22.6 

Combined Eig: 0.0,33.0 

Monitoring Stations: 19 personal 

environmental monitors 

PM Increment: 10-μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Eag= ambient-generated personal 

exposure 

Eig= indoor-generated personal 

exposure 

eNO= exhaled nitric oxide 

Recursive model with 8 children, Eag 

was marginally associated with 

increases in eNO [5.6 ppb [-0.6,11.9]. 

Eig was not associated with eNO (-0.19 

ppb). 

For those combined estimates, only 

Eag was significantly associated with 

an increase in eNO: 

Eag: 5.0 ppb [0.3, 9.7] 

Eig: 3.3 ppb [1.1, 7.7] 

Notes: Effects were seen only in 

children who were not using 

corticosteroid therapy 

December 2009 E-199 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kongtip et al. (2006, 

096920) 

Period of Study: Sep-Oct 2004 

Location: Dindang district, Bangkok 

metropolitan, Thailand 

Outcome: respiratory and other 

Outcomes reported 

Age Groups: Age range 15-55 yr 

Study Design: Panel study 

N: 77 street vendors 

Statistical Analyses: Binary logistic 

regression 

Covariates: Gender, age, type of fuel 

used, working duration (months) 

Dose-response Investigated? No 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 70.94 

Percentiles: 50th(Median): 72.05 

Range (Min, Max): 23.20-120.00 

Monitoring Stations: 1 

Copollutant (correlation): 

SO2 

NO2

O3

VOCs 

CO 

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Model 1 

Headache: 1.011 (0.999-1.022) 

Nose congestion: 1.006 (0.997-1.015) 

Sore throat: 1.000 (0.991-1.008) 

Cold: 1.006 (0.995-1.017) 

Cough: 0.989 (0.980-0.998) 

Phlegm: 0.998 (0.992-1.003) 

Chest tightness: 0.995 (0.955-1.036) 

Fever: 1.008 (0.993-1.024) 

Eye irritation: 1.022 (1.011-1.033) 

Dizziness: 1.027 (1.013-1.041) 

Weakness: 0.996 (0.983-1.008) 

Upper respiratory symptom: 1.001 

(0.994-1.008) 

Lower respiratory symptom: 0.997 

(0.992-1.002) 

Model 2 

Headache: 1.004 (0.996-1.013) 

Nose congestion: 1.003 (0.996-1.010) 

Sore throat: 0.995 (0.989-1.001) 

Cold: 0.996 (0.988-1.004) 

Cough: 0.990 (0.983-0.996) 

Phlegm: 0.995 (0.991-0.999) 

Chest tightness: 0.997 (0.970-1.025) 

Fever: 1.010 (0.998-1.022) 

Eye irritation: 1.019 (1.010-1.028) 

Dizziness: 1.020 (1.009-1.032) 

Weakness: 1.003 (0.994-1.012) 

Upper respiratory symptom: 0.995 

(0.990-1.000) 

Lower respiratory symptom: 0.995 

(0.991-0.999) 

Reference: Lagorio et al. (2006, 

089800) 

Period of Study: 

May-Jun1999 and Nov-Dec 1999 

Location: Rome, Italy 

Outcome: Lung function (FVC and 

FEV1) of subjects with COPD, Asthma 

Age Groups: COPD 50-80 yr 

Asthma 18-64 yr 

Study Design: Time series 

N: COPD = 11 

Asthma = 11 

Statistical Analyses: Non-parametric 

Spearman correlation 

GEE 

Covariates: COPD and IHD: daily 

mean temperature, season variable 

(spring or winter), relative humidity, day 

of week 

Asthma: season variable, temperature, 

humidity, and β-2-agonist use 

Season: Spring and Winter 

Dose-response Investigated? Yes 

Statistical Package: STATA 

Lags Considered: 1-3 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Overall: 27.2 (19.4) 

Spring: 18.2 (5.0) 

Winter: 36.7 (24.1) 

Range (Min, Max): 4.5, 100 

PM Component: 

Cd: 0.46±0.40 ng/m3

Cr: 1.9±1.7 ng/m3

 

Fe: 283±167 ng/m3

Ni: 4.8±6.5 ng/m3

Pb: 30.6±19.0 ng/m3

Pt: 5.0±8.6 pg/m3

V: 1.8±1.4 ng/m3

Zn: 45.8±33.1 ng/m3 

Monitoring Stations: 2 fixed sites: 

(Villa Ada and Istituto superior di Sanita)

 

Copollutant (correlation): 

NO2 r = 0.43 

O3 r = -0.51 

CO r = 0.67 

SO2 r = 0.34 

PM10-2.5 r = 0.34 

PM10 r = 0.93 

PM Increment: 1 μg/m3

They observed negative association 

between ambient PM2.5 and respiratory 

function (FVC and FEV1) in the COPD 

panel. The effect on FVC was seen at 

lag 24 h, 48 h, and 72 h. The effect on 

FEV1 was evident at lag 72 h. There 

was no statistically significant effect of 

PM2.5 on FVC and FEV1 in the 

asthmatic and IHD panels. 

β Coefficient (SE) 

COPD

FVC(%) 

24 h -0.80 (0.36) 

48-h -0.89 (0.41) 

72-h -1.10 (0.55) 

FEV1(%) 

24 h -0.47 (0.33) 

48-h -0.69 (0.37) 

72-h -1.06 (0.50) 

Asthma 

FVC(%) 

24 h -0.14 (0.29) 

48-h -0.07 (0.33) 

72-h -0.06 (0.39) 

FEV1(%) 

24 h -0.30 (0.34) 

48-h -0.36 (0.39) 

72-h -0.40 (0.46) 

December 2009 E-200 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lee et al. (2007, 093042) 

Period of Study: 2000-2001 

Location: South-Western Seoul 

Metropolitan area, Seoul, South Korea 

Outcome: PEFR (peak expiratory flow 

rate), lower respiratory symptoms (cold, 

cough, wheeze) 

Age Groups: 61-89 yr of age (77.8 

mean age) 

Study Design: longitudinal panel 

survey 

N: 61 adults 

Statistical Analyses: SAS MIXED, 

logistic regression model 

Covariates: Temperature (Celsius), 

relative humidity, age, 

Dose-response Investigated? No 

Statistical Package: SAS 8.0 

Lags Considered: 0-4 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 51.15 (19.94) 

Percentiles: 

25th: 33.00 

50th(Median): 53.20 

75th: 87.54 

Range (Min, Max): 

17.94, 92.71 

Monitoring Stations: 2 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI] 

lag: 

PEFR (peak expiratory flow rate) 

-0.54 (-0.89,-0.19) 

1 day 

relative odds of a lower respiratory 

symptom (cold, cough, wheeze) 

0.976 (0.849,1.121) 

1 day 

Reference: Lewis et al. (2005, 081079) 

Period of Study: Winter 2001-Spring 

2002 

Location: Detroit, Michigan, USA 

Outcome: Poorer lung function 

(increased diurnal variability and 

decreased forced expiratory volume) 

Age Groups: 7-11 yr old 

Study Design: Longitudinal cohort 

study 

N: 86 children 

Statistical Analyses: Descriptive 

statistics and bivariate analyses of 

exposures, multivariable regression 

multivariate analog of linear regression. 

Covariates: Sex, home location, 

annual family income, presence of one 

or more smokers in household, race, 

season (entered as dummy variables), 

and parameters to account for 

intervention group effect. 

Season: Winter 2001 (Feb 10-23), 

Spring 2001 (May 5-18), Summer 2001 

(Jul 14-27), Fall 2001 (Sep 22-Oct 5), 

Winter 2002 (Jan 18-31), and Spring 

2002 (May 18-31)]. 

Dose-response Investigated? No 

Lags Considered: 1-2 days, 3-5 days 

Pollutant: PM2.5

Averaging Time: 2 wk 

Mean (SD): 

Eastside 

15.7 (10.6) 

Southwest 

17.5 (12.2) 

Range (Min, Max): 1.0, 56.1 

Monitoring Stations: 2 

Copollutant (correlation): 

PM10 0.93 

O3 Daily mean 0.57 

O3 8-h peak 0.53 

PM Increment: 12.5 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Lung function among children reporting 

use of maintenance CSs 

Diurnal variability FEV1

Lag 1: 1.61 [-0.5,3.72] 

Lag 1: 0.99 [-5.64, 7.62] PM2.5 + O3

Lag 2: 2.96 [-1.74,7.66] 

Lag 2: 4.62 [-4.31, 13.54] PM2.5 + O3

Lag 3-5: 1.37 [-1.49,4.22] 

Lag 3-5: 2.70 [1.0, 4.40] PM2.5 + O3

Lowest daily value FEV1

Lag 1: -2.23 [-6.99,2.53] 

Lag 1: 3.36 [-3.92, 10.63] PM2.5 + O3

Lag 2: -0.21 [-4.09,3.68] 

Lag 2: 0.88 [-8.69, 10.46] PM2.5 + O3

Lag 3-5: -0.76 [-5.00, 3.49] 

Lag 3-5: -2.78 [-4.87 to -0.70] PM2.5 + 

O3

Lung function among children reporting 

presence of URI on day of lung function 

assessment 

Diurnal variability FEV1

Lag 1: 4.08 [-1.78, 9.94] 

Lag 1: 3.99 [-2.76, 10.74] PM2.5 + O3

Lag 2: 7.62 [-0.49, 15.73] 

Lag 2: 4.10 [-1.41, 9.60] PM2.5 + O3

Lag 3-5: 1.47 [-7.73, 10.67] 

Lag 3-5: 3.81 [-1.83, 9.45] PM2.5 + O3

Lowest daily value FEV1

Lag 1: -1.21 [5.62,3.21] 

Lag 1: -0.74 [-4.14, 2.65] PM2.5 + O3

Lag 2: -0.10 [4.36,4.16] 

Lag 2: -1.67 [-5.09, 1.75] PM2.5 + O3

Lag 3-5: -2.88 [-5.46 to -0.30] 

Lag 3-5: -2.78 [-4.79 to -0.77] PM2.5 + 

O3

December 2009 E-201 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Liu et al. (2009, 192003)

Period of Study: 4 wk in 2005 

Location: Windsor, Ontario, Canada 

Outcome: Decreased lung function 

Study Design: Panel 

Statistical Analysis: mixed-effects 

regression models 

Statistical Package: S-PLUS 

Age Groups: Asthmatic children, 

9-14 yr 

Pollutant: PM2.5

Averaging Time: 1, 2 & 3 days 

Mean (SD) Unit (1d): 6.5 μg/m3

Range (Min, Max): 2.0-19.0 

Copollutant (correlation): 

SO2: 0.56 

NO2: 0.71 

O3: -0.41 

Increment: 5.4 μg/m3

Percent Change (Min CI, Max CI) 

Lag

FEV1

Same Day: -0.5 (-1.3-0.3) 

Lag 1 Day: -0.5 (-1.1-0.5) 

2-Day Avg: -0.6 (-1.5-0.4) 

3-Day Avg: -1.1 (-3.1-0.9) 

FEF 25%-75% 

Same Day: -1.9 (-3.5--0.3) 

Lag 1 Day: -1.2 (-2.8-0.3) 

2-Day Avg: -2.0 (-3.8--0.2) 

3-Day Avg: -3.3 (-7.2-0.8) 

FeNO 

Same Day: 5.3 (-3.6-15) 

Lag 1 Day: 1.7 (-6.3-15) 

2-Day Avg: 4.3 (-5.4-15.1) 

3-Day Avg: -17.3 (-33.5-2.9) 

TBARS 

Same Day: 16.9 (2.2-33.6) 

Lag 1 Day: 14.6 (0.8-30.4) 

2-Day Avg: 22.0 (4.8-42.1) 

3-Day Avg: 69.1 (20.1-138.2) 

8-Isoprostane 

Same Day: 5.1 (-3.6-14.5) 

Lag 1 Day: -3.8 (-12.1-5.3) 

2-Day Avg: 0.1 (-9.8-11.1) 

3-Day Avg: 5.8 (-15.8-33.0)/ 

December 2009 E-202 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mar et al. (2004, 057309) 

Period of Study: 1997-1999 

Location: Spokane, Washington 

Outcome: Respiratory Symptoms 

Age Groups: Adults: Ages 20-51 yr 

Children: Ages 7-12 yr 

N: 25 people 

Statistical Analyses: Logistic 

regression 

Covariates: Temperature, relative 

humidity, day of-the-wk 

Statistical Package: STATA 6 

Lags Considered: 0-2 days 

Pollutant: PM2.5 

Mean (SD): 

1997: 11.0 (5.9) 

1998: 10.3 (5.4) 

1999: 8.1 (3.8) 

Unit (i.e. μg/m3

): 

Monitoring Stations: 1 station 

Copollutant (correlation): 

PM2.5

PM1 r = 0.92 

PM10 r = 0.61 

PM10-2.5 r = 0.28 

PM Increment: 10 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 

Adult Respiratory symptoms: 

Wheeze: 

1.04[0.86, 1.26] lag 0 

1.00[0.83, 1.19] lag 1 

0.99[0.84, 1.17] lag 2 

Breath: 

0.97[0.87, 1.08] lag 0 

0.98[0.87, 1.10] lag 1 

0.95[0.80, 1.13] lag 2 

Cough: 

0.86[0.62, 1.21] lag 0 

0.87[0.63, 1.20] lag 1 

0.89[0.66, 1.20] lag 2 

Sputum: 

0.94[0.63, 1.41] lag 0 

0.90[0.62, 1.31] lag 1 

0.92[0.66, 1.27] lag 2 

Runny Nose: 

0.98[0.83, 1.15] lag 0 

0.95[0.82, 1.10] lag 1 

0.93[0.80, 1.08] lag 2 

Eye Irritation: 

0.91[0.70, 1.20] lag 0 

0.89[0.70, 1.13] lag 1 

0.86[0.68, 1.08] lag 2 

Lower Symptoms: 

0.91[0.73, 1.13] lag 0 

0.89[0.72, 1.10] lag 1 

0.89[0.72, 1.10] lag 2 

Any Symptoms: 

0.92[0.80, 1.07] lag 0 

0.89[0.76, 1.04] lag 1 

0.89[0.75, 1.05] 

lag 2 

Children Respiratory symptoms: 

Wheeze: 

0.55[0.26, 1.19] lag 0 

0.53[0.18, 1.58] lag 1 

0.55[0.19, 1.64] lag 2 

Breath: 

1.13[0.86, 1.48] lag 0 

1.12[0.86, 1.44] lag 1 

1.10[0.82, 1.48] lag 2 

Cough: 

1.17[0.98, 1.40] lag 0 

1.21[1.00, 1.47] lag 1 

1.18[0.99, 1.42] lag 2 

Sputum: 

1.06[0.92, 1.22] lag 0 

1.10[0.91, 1.34] lag 1 

1.09[0.92, 1.30] lag 2 

Runny Nose: 

1.09[0.85, 1.39] lag 0 

1.12[0.89, 1.41] lag 1 

1.16[0.94, 1.42] lag 2 

Eye Irritation: 

0.93[0.53, 1.64] lag 0 

0.75[0.45, 1.27] lag 1 

0.77[0.65, 0.91] lag 2 

Lower Symptoms: 

1.18[1.00, 1.38] lag 0 

1.21[1.00, 1.46] lag 1 

1.17[0.96, 1.43] lag 2 

Any Symptoms: 

1.17[1.03, 1.34] lag 0 

1.22[1.04, 1.43] lag 1 

1.23[1.07, 1.42] lag 2 

December 2009 E-203 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mar et al. (2005, 087566) 

Period of Study: 1999-2001

Location: Seattle, Washington 

Outcome: Pulmonary function (arterial 

oxygen saturation) and cardiac function 

(heart rate and blood pressure) 

Study Design: Time series 

Statistical Analyses: Linear logistic 

regression 

Age Groups: > 57 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

Lag 

Personal: 

Systolic: 0.37 (-0.93, 1.67) 0 

Diastolic: -0.20 (-0.85, 0.46) 0 

Indoor: 

Systolic: 0.92 (-2.04, 3.87) 0 

Diastolic: 0.38 (-1.43, 2.20) 0 

Outdoor: 

Systolic: -0.81 (-2.34, 0.73) 0 

Diastolic: -0.46 (-1.49, 0.57) 

0 

% Increase between heart rate and 

PM2.5 exposure for people > 57 

PM2.5: 

Personal: 0.44 (0.04, 0.84) 0 

Indoor: 0.22 (-0.71, 1.16) 0 

Outdoor: -0.75 (-1.42 to -0.07) 0 

Reference: Mar et al. (2005, 088759) 

Period of Study: 1999-2002 

Location: Seattle, Washington 

Outcome: Respiratory Symptoms 

Age Groups: 6-13 yr 

Study Design: Time-Series 

N: 19 children 

Statistical Analyses: Polynomial 

distributed lag model, Poisson 

regression 

Covariates: Age, ambient NO levels, 

temperature, relative humidity, 

modification of use of inhaled 

corticosteroids 

Season: Winter, Spring 

Dose-response Investigated? No 

Statistical Package: STATA 

Lags Considered: 0-8 h 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Results presented in Fig 1. 

Monitoring Stations: 3 Stations 

PM Increment: 10 μg/m3

Change in FE(NO) (exhaled NO 

concentration) with air pollution 

[Lower CI, Upper CI] lag: 

Medication use: 

No meds: 6.99[3.43, 10.55] lag 1-h 

Meds: -0.18[-3.33, 2.97] lag 1-h 

No meds: 6.30[2.64, 9.97] lag 4-h 

Meds: -0.77[-4.58, 3.04] lag 4-h 

No meds: 0.46[-1.18, 2.11] lag 8-h 

Meds: 0.40[-1.94, 2.74] lag 8-h 

Reference: McCreanor et al. (2007, 

092841) 

Period of Study: 2003-2005 

Location: London, England 

Outcome: Decreased Lung Function 

Age Groups: Adults 

Study Design: Crossover study 

N: 60 adults 

Statistical Analyses: Linear regression

Covariates: Temperature, relative 

humidity, age, sex, bod-mass index, 

and race or ethnic group 

Pollutant: PM2.5

Averaging Time: 1 h 

Mean (SD): NR 

 50th(Median): Oxford St: 28.3 

Hyde Park: 11.9 

Range (Min, Max): 

Oxford St: (13.9, 76.1) 

Hyde Park: (3, 55.9) 

% changes in FEV and FVC are 

presented in Fig 1-3. Results are not 

presented quantitatively in text or 

tables. The authors did not find any 

significant differences in respiratory 

symptoms between the two locations. 

Also, there were no significant 

differences in sputum eosinophil counts 

or eosinophil cationic protein levels. 

Reference: Moshammer and 

Neuberger (2003, 041956) 

Period of Study: 2000-2001 

Location: Linz, Austria 

Outcome: Lung Function: FVC, FEV1, 

MEF25, MEF50, MEF75, PEF, LQ Signal, 

PAS Signal 

Age Groups: Ages 7-10 

Study Design: Case-crossover 

N: 161 children 

1898-2120 “half-h means” 

Statistical Analyses: Correlations 

Regression Analysis 

Covariates: Morning, evening, night 

Season: Spring, Summer, Winter, Fall 

Dose-response Investigated? No 

Pollutant: PM2.5

Averaging Time: 8 h means & daily 

means 

Mean (SD): 14.61 (10.83) 

Range (Min, Max): 

(NR, 119.92) 

Monitoring Stations: 1 

Copollutant (correlation): 

LQ = 0.751 

PAS = 0.354 

Notes: “Acute effects of ‘active particle 

surface’ as measured by diffusion 

charging were found on pulmonary 

function (FVC, FEV1, MEF50) of 

elementary school children and on 

asthma-like symptoms of children who 

had been classified as sensitive.” 

December 2009 E-204 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Moshammer et al. (2006, 

090771) 

Period of Study: 2000-2001 

Location: Linz, Austria 

Outcome: Respiratory symptoms and 

decreased lung function 

Age Groups: Children ages 7-10 

Study Design: Time-series 

N: 163 children 

Statistical Analyses: Generalized 

estimating equations model 

Covariates: Sex, age, height, weight 

Dose-response Investigated? NR 

Statistical Package: NR 

Lags Considered: 1 

Pollutant: PM2.5

Averaging Time: 8 h 

Mean (SD): 

Maximum 24 h: 76.39 

Annual avg: 19.06 

Percentiles: 8-h mean 25th: 8.64 

8-h mean 50th(Median): 15.70 

8-h mean 75th: 25.82 

Monitoring Stations: 1 station 

Copollutant (correlation): 

PM1 r = 0.95 

PM10 r = 0.93 

NO2 r = 0.54 

PM Increment: 10 μg/m3

% change in Lung Function per 10 

μg/m3 

FEV: 0.23 

FVC: 0.08 

FEV0.5: 0.33 

MEF75%: -0.49 

MEF50%: -0.58 

MEF25%: -0.83 

PEF: 0.41 

% change in Lung Function per IQR 

FEV: -0.59 

FVC: -0.2 

FEV0.5: 0.85 

MEF75%: -1.25 

MEF50%: -1.48 

MEF25%: -2.14 

PEF: -1.06 

Multiple pollutant model 

FEV: 0.10 

FVC: 0.21 

FEV0.5: 0.06 

MEF75%: -0.15 

MEF50%: 0.04 

MEF25%: -0.21 

PEF: -0.18 

% change in Lung Function per IQR 

FEV: 0.27 

FVC: 0.54 

FEV0.5: 0.15 

MEF75%: -0.39 

MEF50%: 0.11 

MEF25%: 0.54 

PEF: 0.015: -0.47 

Reference: Murata et al. (2007, 

189159) 

Period of Study: Nov 2004 

Location: Tokyo, Japan 

Outcome: Exhaled nitric oxide levels, 

(eNO), a marker of airway inflammation 

Age Groups: 5-10 yr 

Study Design: Cohort/Panel study 

N: 19 schoolchildren* 

Statistical Analyses: Linear regression

Covariates: None 

Season: Nov (fall) 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Lag h 1-24, 8-h ma, 

7-h ma, 6-h ma, 24-h ma 

Pollutant: PM2.5

Averaging Time: Hourly, 24 h 

Mean (SD): 

39.0 (16.9) μg/m3

 (daily mean) 

Range (Min, Max): 

10, 120 (range of hourly values) 

Monitoring Stations: 1, on the street 

where the children lived 

PM Increment: IQR 110 μg/m3

Mean [Lower CI, Upper CI] lag: 

0.145 [0.62, 0.228] ppb eNO 

8-h ma 

Notes: Associations for lag h 1-24 

presented in figures. Authors state 

“Individual hourly lag models showed a 

consistent association between the 

eNO value and PM2.5 for exposure in 

the previous 24 h” 

“The trend on the graphs strongly 

suggest that fluctuations in eNO were 

affected by changes in air pollutants 

over at least the previous 8-h period” 

PM2.5, black carbon, and NOX were all 

highly correlated (shown in figures), so 

effects are difficult to separate 

Pollutant concentrations peaked in the 

morning and evening h during traffic 

peaks 

December 2009 E-205 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: Jun 1999-Jun 2000 

Location: Austria (Vienna and a rural 

area near Linz) 

Outcome: Questionnaire derived 

asthma score, and a 1-5 point 

respiratory health rating by parent 

Age Groups: 7-10 yr 

Study Design: Cross-sectional survey 

N: about 2000 children 

Statistical Analyses: mixed models 

linear regression-used factor analysis to 

develop the “asthma score” 

Covariates: Pre-existing respiratory 

conditions, temperature, rainy days, # 

smokers in household, heavy traffic on 

residential street, gas stove or heating, 

molds, sex, age of child, allergies of 

child, asthma in other family members 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 4-wk avg (preceding 

interview) 

Pollutant: PM2.5

Averaging Time: 24 h 

Copollutant (correlation): 

PM10 (r=0.94) in Vienna 

PM Increment: 10 μg/m3 

Change in mean associated unit 

increase in PM 

(p-value) 

lag 

Respiratory Health score 

Vienna: 0.016 (p>0.05) 

lag 4 week avg 

Rural area: 0.022 (p < 0.05) 

lag 4 week avg 

Asthma score 

Vienna: 0.006 (p>0.05) 

lag 4 week avg 

Rural area: 0.004 (p>0.05) 

lag 4 week avg 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: Sep 1999-Mar 2000 

Location: Vienna, Austria 

Outcome: Ratio measure: Time to peak 

tidal expiratory flow divided by total 

expiration time (i.e., tidal lung function, 

a surrogate for bronchial obstruction) 

Age Groups: 3.0-5.9 yr (preschool 

children) 

Study Design: 

Longitudinal prospective cohort 

N: 56 children 

Statistical Analyses: mixed models 

linear regression, with autoregressive 

correlation structure 

Covariates: Age, sex, respiratory rate, 

phase angle, temperature, 

kindergarten, parental education, 

observer (also in sensitivity analyses: 

height, weight, cold/sneeze on same 

day, heating with fossil fuels, hair 

cotinine, number of tidal slopes used to 

measure tidal lung function) 

Dose-response Investigated? No 

Statistical Package: SAS 8.0 

Lags Considered: Lag 0 

Pollutant: PM2.5

Averaging Time: 24 h 

PM Component: Total carbon 

EC 

OC 

Copollutant (correlation): 

PM10 (r=0.94) in Vienna 

PM Increment: Interquartile range (NR)

Change in mean associated with an 

IQR increase in PM (p-value) 

lag 

PM2.5 mass: -0.987 (0.091) 

lag 0 

Total carbon: -0.815 (0.041) 

lag 0 

EC: -0.657 (0.126) 

lag 0 

OC: -0.942 (0.025) 

lag 0 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: Oct. 2000-May 2001 

Location: Linz, Austria 

Outcome: Forced oscillatory resistance 

(at zero Hz), FVC, FEV1, MEF25, MEF50, 

MEF75, PEF 

Age Groups: 7-10 yr 

Study Design: Longitudinal 

prospective cohort 

N: 164 children 

Statistical Analyses: Mixed models 

linear regression with autoregressive 

correlation structure 

Covariates: Sex, time and individual 

Season: Oct-May 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: Lag 0-7 

Pollutant: PM2.5

Averaging Time: 24 h 

Monitoring Stations: 1 

PM Increment: 1 μg/m3

Notes: Authors report increased 

oscillatory resistance significantly 

associated with PM2.5 (lag 0) 

December 2009 E-206 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: O'Connor et al. (2008, 

156818) 

Period of Study: Aug 1998-Jul 2001 

Location: Boston, the Bronx, Chicago, 

Dallas, New York, Seattle, Tucson 

Outcome: Pulmonary function and 

respiratory symptoms 

Age Groups: 5-12 yr 

Study Design: Inner-City Asthma Study 

(ICAS)-Panel/cohort study 

N: 861 children 

Statistical Analyses: Mixed effects 

models 

Lags Considered: Lag 0-6, 0-4 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 14 

Range (Min, Max): 

5-35 (estimated from Fig) 

Copollutant (correlation): 

NO2 (r=0.59) 

SO2 (r=0.37) 

CO (r=0.44) 

O3 (r=-0.02) 

PM Increment: 13.2 μg/m3 90th-10th 

percentile 

Change in pulmonary function 

lag 

FEV1: -1.47 (-2.00 to -0.94) lag 0-4 

PEFR: -1.10 (-1.65 to -0.56) lag 0-4 

PM2.5+O3+NO2

FEV1: -0.73 (-1.33 to -0.12) lag 0-4 

PEFR: -0.25 (-0.88, 0.38) lag 0-4 

Risk of Respiratory Symptoms 

lag 

Wheeze: 0.98 (0.88, 1.09) lag 0-4 

Nighttime asthma: 1.11 (0.94, 1.30) 

lag 0-4 

Slow play: 1.01 (0.89, 1.15) lag 0-4 

Missed school: 1.33 (1.06, 1.66) lag 0-4 

PM2.5+O3+NO2

Wheeze: 0.92 (0.81, 1.05) lag 0-4 

Nighttime asthma: 1.03 (0.86, 1.23) 

lag 0-4 

Slow play: 0.92 (0.79, 1.06) lag 0-4 

Missed school: 1.13 (0.87, 1.45) lag 0-4

Reference: Peacock et al. (2003, 

042026) 

Period of Study: Nov 1996-Feb 1997 

Location: northern Kent, UK 

Outcome: Reduced peak expiratory 

flow rate (PEFR) 

Age Groups: 7-13 yr of age 

Study Design: Time Series 

N: 179 

Statistical Analyses: generalized 

estimating equations 

Covariates: Day of the week, 24-h 

mean outside temperature. 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: STATA 

Lags Considered: Same day, lag 1, 

lag 2, 5-day ma 

Pollutant: Sulfate (SO4

2–) 

Averaging Time: Daily avg 

Mean (SD): Urban 2 

24 h avg: 1.3 (1.1) 

Percentiles: 

10th: Urban 2 0.5 

90th: Urban 2 2.4 

Range (Min, Max): 

Urban 2 0.3, 6.7 

Monitoring Stations: 3 

Sulfate (SO4

2–) 

Increment: 1.3 μg/m3

Odds ratio [Lower CI, Upper CI] 

lag: 

1.090 [0.898, 1.322] 

5 days 

Reference: Peled, et al. (2005, 

156015) 

Period of Study: 5-6 wk between 

Mar-Jun 1999 and Sep-Dec 1999. 

Location: Ashdod, Ashkelon and 

Sderot, Israel 

Outcome: Reduced peak expiratory 

flow (PEF) 

Age Groups: 7-10 yr 

Study Design: Nested cohort study 

N: 285 

Statistical Analyses: Time series 

analysis 

Generalized linear model, generalized 

estimating equations, one-way ANOVA, 

generalized linear model 

Covariates: Seasonal changes, 

meteorological conditions and personal 

physiological, clinical and 

socioeconomic measurements 

Season: Spring, Fall 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM2.5

Averaging Time: Daily 

Mean: 

Ashkelon: 24.0 

Sderot: 29.2 

Ashdod: 23.9 

PM Component: Local industrial 

emissions, desert dust, vehicle 

emissions and emissions from two 

electric power plants 

Monitoring Stations: 6 

Copollutant: PM10

PM Increment: 1 μg/m3

β coefficient (SE) [95% CI] 

Ashkelon: 

PM2.5 MAX: -0.144 (0.12) [-0.38-0.09] 

Ashdod: 

PM2.5 MAX: -2.74 (0.61) [-3.95-1.53] 

PM2.5 MAX TMAX: 0.11 (0.02) [0.06-

0.16] 

In Ashdod, PM2.5 and an interaction 

between PM2.5 and temperature were 

significantly associated. 

December 2009 E-207 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Penttinen et al. (2006, 

087988) 

Period of Study: Nov 1996-Apr 1997 

Location: Helsinki, Finland 

Outcome: Decreased lung function and 

respiratory symptoms 

Age Groups: Adults, mean age 53 yr 

Study Design: Time Series 

N: 78 people 

Statistical Analyses: Generalized least 

squares autoregressive model 

Covariates: Temperature, relative 

humidity, day of study, day of study 

squared, binary dummy variable for 

weekends 

Season: Winter, Spring 

Dose-response Investigated? NR 

Statistical Package: SAS version 6 

Lags Considered: 0-3 

Pollutant: PM2.5

PM Component: Soil, heavy fuel oil, 

sea salt 

Averaging Time: 24 h 

Percentiles: 25th: 

Long range transport: 2.44 

Local combustion: 1.75 

Soil: 0.14 

Heavy fuel oil: -0.13 

Sea Salt: 0.22 

Unidentifiable: -1.41 

All sources: 6.47 

50th(Median): 

Long range transport: 4.15 

Local combustion: 2.41 

Soil: 0.64 

Heavy fuel oil: 0.10 

Sea Salt: 0.27 

Unidentifiable: 0.02 

All sources: 8.37 

75th: 

Long range transport: 7.33 

Local combustion: 3.05 

Soil: 1.46 

Heavy fuel oil: 0.52 

Sea Salt: 0.42 

Unidentifiable: 0.74 

All sources: 11.15 

Range (Min, Max): 

Long range transport: (-0.89, 28.31) 

Local combustion: (0.83, 6.51) 

Soil: (-1.13, 6.43) 

Heavy fuel oil: (-0.67, 4.74) 

Sea Salt: (0.09, 0.98) 

Unidentifiable: (-4.40, 4.77) 

All sources: (4.11, 33.53) 

Monitoring Stations: 1 site 

PM Increment: 1.3 μg/m3

PM2.5, long range: 

PEF Morning: 

0.37[-0.59, 1.34] lag 0 

-1.04[-1.88 to -0.19] lag 1 

-0.82[-1.81, 0.16] lag 2 

0.22[-0.64, 1.08] lag 3 

-0.24[-1.12, 0.64] 5 day mean. 

PEF Afternoon: 

0.20[-0.67, 1.06] lag 0 

-0.20[-1.24, 0.83] lag 1 

-0.30[-1.14, 0.53] lag 2 

0.45[-0.57, 1.47] lag 3 

0.03[-0.79, 0.85] 5 day mean. 

PEF Evening: 

-0.33[-1.30, 0.64] lag 0 

-0.29[-1.13, 0.55] lag 1 

-0.41[-1.46, 0.64] lag 2 

0.39[-0.47, 1.24] lag 3 

0.07[-0.81, 0.95] 5 day mean 

PM2.5, local combustion: 

PEF Morning: 

-0.73[-1.69, 0.23] lag 0 

-0.46[-1.24, 0.32] lag 1 

-0.43[-1.49, 0.63] lag 2 

0.34[-0.47, 1.15] lag 3 

-0.25[-1.03, 0.53] 5 day mean. 

PEF Afternoon: 

-0.21[-1.07, 0.65] lag 0 

-0.81 [-1.77, 0.16] lag 1 

-0.83[-1.74, 0.09] lag 2 

0.20[-0.80, 1.20] lag 3 

-0.87[-1.63 to -0.12] 5 day mean. 

PEF Evening: 

-0.51[-1.48, 0.45] lag 0 

-1.16[-1.93 to -0.39] lag 1 

0.23[-1.35, 0.90] lag 2 

0.56[-0.21, 1.32] lag 3 

-1.14[-1.95 to -0.33] 5 day mean 

PM2.5, soil: 

PEF Morning: 

0.81[0.05, 1.57] lag 0 

0.03 [-0.65, 0.71] lag 1 

0.50[-0.34, 1.35] lag 2 

-0.07[-0.74, 0.61] lag 3 

0.39[-0.46, 1.23] 5 day mean. 

PEF Afternoon: 

1.05[0.38, 1.72] lag 0 

0.40[-0.38, 1.19] lag 1 

0.66 [0.03, 1.30] lag 2 

-0.36[-1.12, 0.41] lag 3 

0.55 [-0.21, 1.32] 5 day mean. 

PEF Evening: 

1.08[0.33, 1.84] lag 0 

1.00[0.31, 1.68] lag 1 

0.33[-0.56, 1.22] lag 2 

-0.84 [-1.53 to -0.15]lag 3 

0.90[0.08, 1.73] 5 day mean 

PM2.5, oil: 

PEF Morning: 

-0.22[-1.00, 0.56] lag 0 

-0.20[-1.24, 0.84] lag 1 

0.66[-0.68, 2.00] lag 2 

0.57 [-0.18, 1.32] lag 3 

0.10[-0.61, 0.81] 5 day mean. 

PEF Afternoon: 

-0.04[-0.75, 0.67] lag 0 

December 2009 E-208 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

0.29[-0.98, 1.55] lag 1 

0.08 [-1.13, 1.28] lag 2 

0.62[-0.31, 1.54] lag 3 

0.07 [-0.64, 0.78] 5 day mean. 

PEF Evening: 

0.57[-0.23, 1.37] lag 0 

0.12[-0.92, 1.15] lag 1 

-0.97[-2.39, 0.45] lag 2 

0.40[-0.31, 1.12] lag 3 

0.43[-0.33, 1.19] 5 day mean 

PM2.5, salt: 

PEF Morning: 

0.76[-0.13, 1.65] lag 0 

0.43 [-0.30, 1.16] lag 1 

0.13[-0.75, 1.02] lag 2 

0.38[-0.47, 1.23] lag 3 

0.95[-0.18, 2.09] 5 day mean. 

PEF Afternoon: 

0.62[-0.18, 1.41] lag 0 

0.80[-0.08, 1.69] lag 1 

0.14[-0.62, 0.90] lag 2 

0.16[-0.83, 1.15] lag 3 

0.88 [-0.18, 1.94] 5 day mean. 

PEF Evening: 

1.09[0.19, 1.98] lag 0 

0.63[-0.10, 1.35] lag 1 

0.32[-0.62, 1.26] lag 2 

-0.31[-1.16, 0.54] lag 3 

0.88[-0.27, 2.02] 5 day mean 

PM2.5, unidentified: 

PEF Morning: 

0.38[-0.67, 1.43] lag 0 

0.09[-0.83, 1.00] lag 1 

0.22[-0.82, 1.26] lag 2 

0.78 [-0.10, 1.66] lag 3 

0.78[-0.14, 1.69] 5 day mean. 

PEF Afternoon: 

0.02[-0.92, 0.96] lag 0 

0.65[-0.48, 1.77] lag 1 

0.17[-0.71, 1.05] lag 2 

0.69[-0.36, 1.75] lag 3 

0.17 [-0.72, 1.06] 5 day mean. 

PEF Evening: 

-0.11[-1.17, 0.95] lag 0 

0.19[-0.72, 1.10] lag 1 

0.86[-0.25, 1.96] lag 2 

0.15[-0.70, 1.01] lag 3 

-0.19[-1.15, 0.77] 5 day mean 

PM2.5, local combustion: 

PEF morning: 

Cu: -0.25 [-1.25, 0.75] 

Zn: -0.45[-1.19, 0.29] 

Mn: 0.13[-0.83, 1.08] 

Fe: 0.08[-0.70, 0.85]. 

PEF afternoon: 

Cu: -0.37[-1.29, 0.55] 

Zn: -0.19[-0.87, 0.50] 

Mn: -0.48[-1.37, 0.42] 

Fe: 0.29[-0.45, 1.04]. 

PEF evening: 

Cu: -0.48[-1.47, 0.52] 

Zn: -0.17[-0.92, 0.57] 

Mn: 0.51[-0.44, 1.47] 

Fe: 0.34[-0.46, 1.14] 

PM2.5, long range: 

PEF morning: 

S: 0.11[-0.886, 1.07] 

K: -0.10[-1.00, 0.80] 

Pb: -0.62[-1.37, 0.13] 

December 2009 E-209 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Br: -0.40 [-1.40, 0.60]. 

PEF afternoon: 

S: -0.05[-0.92, 0.81] 

K: 0.26[-0.56, 1.07] 

Pb: -0.12[-0.84, 0.60] 

Br: 0.15[-0.81, 1.12]. 

PEF evening: 

S: 0.08[-0.86, 1.02] 

K: 0.18[-0.70, 1.07]; 

Pb: -0.20[-0.97, 0.58] 

Br: 0.35[-0.71, 1.40] 

PM2.5, soil: 

PEF morning: 

Si: 0.27[-0.43, 0.97] 

Al: 0.17 [-0.72, 1.05] 

Ca: 0.13[-1.08, 1.35]. 

PEF afternoon: 

Si: 0.39[-0.24, 1.01] 

Al: 0.49[-0.29, 1.27] 

Ca: 0.15[-0.92, 1.22] 

PEF evening: 

Si: 0.60[-0.06, 1.26] 

Al: 0.76[-0.08, 1.60] 

Ca: 0.90[-0.22, 2.03] 

PM2.5, Oil combustion: 

PEF morning: 

V: -0.01[-0.87, 0.86] 

Ni: -0.09[-1.08, 0.90]. 

PEF afternoon: 

V: -0.48[-1.32, 0.35] 

Ni: 0.26[-0.72, 1.23]. 

PEF evening: 

V: 0.02[-00.88, 0.92] 

Ni: 0.50[-0.55, 1.55] 

PM2.5, Sea salt: 

PEF morning: 

Na: 0.92[-0.34, 2.17] 

Cl: 0.93[0.08, 1.79] 

PEF afternoon: 

Na: 0.96[-0.24, 2.16] 

Cl: 0.57[-0.22, 1.36] 

PEF evening 

Na: 0.87[-0.40, 2.15] 

Cl: 0.65[-0.19, 1.49]

December 2009 E-210 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Pino et al. (2004, 050220) 

Period of Study: Apr 1995-Oct 1996

Location: Santiago, Chile 

Outcome: Respiratory Symptoms, 

Wheezing bronchitis 

Study Design: Time-series 

Statistical Analyses: Bayesian 

hierarchical analysis, cubic spline 

Age Groups: 4 mo-2 yr old 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD) unit: 52.0 (31.6) 

Range (5th, 95th): 17.0, 114.0

Copollutants (correlation): 

SO2: r= 0.73 

NO2: r= 0.85 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

% increase in wheezing bronchitis and 

PM2.5 exposure for infants 4 mo-2 yr old 

4.75 (1.25, 8.25) 1 

3.85 (0.45, 7.75) 2 

2.25 (-1.00, 6.00) 3 

1.75 (-2.20, 5.75) 4 

4.00 (0.25, 8.00) 5 

5.00 (1.00, 8.50) 6 

7.00 (3.50, 11.00) 7 

8.10 (4.00, 11.25) 8 

9.00 (6.00, 12.00) 9 

8.75 (5.75, 12.00) 10 

1.50 (-3.50, 4.75) 11 

0.25 (-3.75, 4.25) 12 

0.00 (-4.00, 4.00) 13 

1.00 (-3.50, 4.50) 14 

1.50 (-3.50, 4.50) 15 

OR for wheezing bronchitis and PM2.5

exposure in infants 4 mo to 2 yr old 

according to family history of asthma 

Yes to family history of asthma 

1.09 (1.00, 1.19) 1 

1.10 (1.02, 1.20) 2 

1.11 (1.02, 1.22) 3 

No to family history of asthma 

1.04 (1.00, 1.08) 1 

1.02 (0.98, 1.06) 2 

1.01 (0.96, 1.05) 3 

Reference: Rabinovitch et al., (2006, 

088031) 

Period of Study: 2001-2003 (two 

winters 2001-2002 and 2002-2003) 

Location: Denver, CO 

Outcome: Bronchodilator doser 

activations (daily) and urinary 

leukotriene E4 (daily) 

Age Groups: Children 6-13 yr old 

Study Design: School-based cohort 

study 

N: 73 children 

Statistical Analyses: Doser activation: 

Poisson regression with GEE with AR1 

working covariance 

Urinary leukotriene E4: linear mixed 

model with spatial exponential 

covariance 

Covariates: Temperature, pressure, 

humidity, time trend, Friday indicator, 

upper respiratory infection (URI), height 

(leukotriene E4 only). 

Season: Winter 

Dose-response Investigated? NR 

Statistical Package: SAS 

Lags Considered: 0-2 days 

Pollutant: PM2.5

Averaging Time: 

Morning (midnight to 11: 00 AM) mean 

Morning (midnight to 11: 00 AM) 

maximum 

24-h mean 

Mean (SD): 

24-h mean, TEOM 

Year 1, N: 55 days: 6.5 (3.2) 

Year 2, N: 128 days: 8.2 (3.7) 

24-h mean, FRM 

Year 1, N: 55 days: 11.8 (7.2)

Year 2, N: 122 days: 11.2 (5.5) 

Morning mean, TEOM 

Year 1, N: 71 days: 7.4 (4.7) 

Year 2, N: 127 days: 9.1 (5.0) 

Morning maximum, TEOM 

Year 1, N: 71 days: 15.5 (9.5) 

Year 2, N: 127 days: 18.4 (9.6) 

Percentiles: 

24-h mean, TEOM 

Year 1 

25th: 4.4 

50th(Median): 6.2 

75th: 7.9 

Year 2 

25th: 55 

50th(Median): 7.3 

75th: 9.9 

24-h mean, FRM 

Year 1 

25th: 7.8 

50th(Median): 10.1 

75th: 14.1 

Year 2 

25th: 7.5 

50th(Median): 9.3 

75th: 13.3 

Morning mean, TEOM 

Year 1 

25th: 4.0 

PM Increment: IQR (over current and 

previous day) 

Doser Activation 

Morning avg PM2.5 TEOM 

Year 1: 

Pct Increase: 3.0 [-0.5: 6.6] p = 0.10 

Year 2: 

Pct Increase: 2.7 [1.1: 4.4] p = 0.006 

Aggregated yr: 2.2 [0.7: 3.6] p = 0.005 

Morning max PM2.5 TEOM 

Year 1 

Pct Increase: 4.0 [0.5: 7.6] p = 0.02 

Year 2 

Pct Increase: 2.3 [0.7: 4.0] p = 0.009 

Aggregated yr 2.6 [0.9: 4.2] p= 0.002 

24-h PM2.5

TEOM 

Lag 0: 0.4 [-0.7: 1.6] p-value = 0.45 

Lag 1: 0.9 [-0.7: 2.4] p-value = 0.27 

Lag 2: -0.4 [-1.7: 0.9] p-value = 0.59 

Lag 0-2 Avg: 0.6 [-1.0: 2.2] 

p-value = 0.43 

FRM 

Lag 0: 0.2 [-1.2: 1.6] p-value = 0.81 

Lag 1: 0.9 [-0.9: 2.6] p-value = 0.31 

Lag 2: -0.2 [-2.2: 1.8] p-value = 0.88 

Lag 0-2 Avg: 1.2 [-0.6: 2.9] 

p-value = 0.20 

Morning avg PM2.5 TEOM 

URI not adjusted 

Mild/Moderate Asthmatics: 

1.5 [-0.5: 3.4] p = 0.14 

Severe Asthmatics: 3.7 [1.6: 5.8] 

p- = 0.0006 

Difference between severity groups, 

p = 0.12 

Aggregated severity group: 

2.2 [0.7: 3.6] p= 0.005 

URI adjusted 

Mild/Moderate Asthmatics: 

1.0 [-1.9: 3.9]p= 0.50 

Severe Asthmatics: 6.0 [1.8: 10.1] 

p = 0.006 

Difference between severity groups, 

December 2009 E-211 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

50th(Median): 5.9 

75th: 9.6 

Year 2 25th: 5.2 

50th (Median): 8.5 

75th: 11.6 

Morning maximum, TEOM 

Year 1 25th: 8 

50th (Median): 13 

75th: 20 

Year 2 25th: 11 

50th (Median): 16 

75th: 23 

Range (Min, Max): 

24-h mean, TEOM 

Year 1 (2.1, 23.7) 

Year 2 (1.7, 20.5) 

24-h mean, FRM 

Year 1 (4.3, 53.5) 

Year 2 (3.4, 26.3) 

Morning mean, TEOM 

Year 1 (1.4, 22.7) 

Year 2 (1.6, 30.2) 

Morning maximum, TEOM 

Year 1 (4, 42) 

Year 2 (4, 46) 

Monitoring Stations: 2 (1 TEOM and 1 

Federal Reference Monitor [FRM]) 

p = 0.08 

Aggregated severity groups: 

2.7 [-0.1: 5.4] p= 0.06 

Morning maximum PM2.5 TEOM 

URI not adjusted 

Mild/Moderate Asthmatics: 

1.9 [-0.2: 4.1] p= 0.07 

Severe Asthmatics: 3.9 [1.1: 6.8] 

p = 0.006 

Difference between severity groups, 

p = 0.29 

Aggregated severity groups: 2.6 [0.9: 

4.2] p= 0.002 

URI adjusted 

Mild/Moderate Asthmatics: 

1.6 [-2.2: 5.4] p = 0.41 

Severe Asthmatics: 8.1 [2.9: 13.4] 

p = 0.003 

Difference between severity groups, 

p = 0.03 

Aggregated severity groups: 

3.8 [0.2: 7.4] p = 0.04 

Leukotriene E4 

24-h PM2.5

TEOM 

Lag 0: 3.3 [-0.7: 7.2] p = 0.09 

Lag 1: -1.6[-5.7: 2.5] p = 0.40 

Lag 2: 1.1 [-2.8: 5.1] p= 0.64 

Lag 0-2 Avg: 2.3 [-4.0: 8.6] p = 0.45 

FRM 

Lag 0: 2.7 [1.1: 6.5] p = 0.12 

Lag 1: -0.8 [-4.9: 3.3] p = 0.65 

Lag 2: -0.8 [-4.9: 3.3] p = 0.71 

Lag 0-2 Avg: 2.6 [-2.3: 7.5] p = 0.27 

Leukotriene E4 

Morning avg PM2.5 TEOM 

Height 25percentile: 8.9 [3.0: 14.7] p= 

0.004 

Height 50percentile: 5.9 [1.4: 10.4] p = 

0.01 

Height 75percentile: 1.9 [-3.4: 7.3] p = 

0.47 

Model w/o Height × Pollutant: 5.6 [1.0: 

10.2] p = 0.02 

Morning maximum PM2.5 TEOM 

Height 25percentile: 8.3 [3.4: 13.2] p = 

0.001 

Height 50percentile: 6.1 [2.1: 10.2] p= 

0.004 

Height 75 percentile: 3.2 [-2.0: 8.4] p= 

0.23 

Model w/o Height × 

Pollutant: 6.2 [1.9: 10.5] p = 0.006 

Reference: Rabinovitch et al. (2004, 

096753) 

Periods of Study: 

Nov 1999-Mar 2000

Nov 2000-Mar 2001 

Nov 2001-Mar 2002 

Location: Denver, Colorado 

Outcome: Respiratory symptoms, 

Asthma symptoms (cough and 

wheeze), Upper respiratory symptoms 

Study Design: Time-series 

Statistical Analyses: Logistic linear 

regression, PROC Mixed, PROC 

Genmod 

Age Groups: 6-12 

Pollutant: PM2.5 

Averaging Time: 24-h avg 

Mean (SD): 10.8 (7.1) 

Range (Min, Max): (1.8, 53.5) 

Copollutant (correlation): 

CO 

NO2

SO2

O3

PM Increment: 1 μg/m3

β (SE) 

AM: -0.003 (0.009) 

PM: 0.004 (0.011) 

Odds Ratio (Lower CI, Upper CI) 

Lag 

0.971 (0.843, 1.118) 

0-3 avg. 

December 2009 E-212 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ranzi et al. (2004, 089500) 

Period of Study: Feb-May 1999 

Location: Emilia-Romagmna, Italy 

(urban-industrial and rural area) 

Outcome: respiratory symptoms, PEF 

measurements, drug consumption and 

daily activity 

Age Groups: Children, mean age=(7.2-

7.9 yr) 

Study Design: Panel study 

N: 120 children 

Statistical Analyses: Ecological 

analysis and Panel analysis 

Covariates: Temperature, humidity, 

gender, medicinal use, symptomatic 

status of previous day 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 0-3 ma 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Urban= 53.07 

Rural= 29.11 

Monitoring Stations: 3 

Copollutant (correlation): 

TSP: r=0.613 

Daily air pollution concentrations: r= 

0.658 

PM Increment: 10 μg/m3

Effect Estimate: 

Urban-industrial panel 

Cough and Phlegm: RR=1.0044 

(1.0011-1.0077) 

Reference: Rodriguez et al. (2007, 

092842) 

Period of Study: 1996-2003 

Location: Perth, Australia 

Outcome: Body temperature, cough, 

runny/ blocked nose, wheeze/ rattle 

chest (daily) 

Age Groups: Children 0-5 yr old 

Study Design: hospital-based cohort 

study 

N: 198-263 children 

Statistical Analyses: Logistic 

regression with GEE and AR (order not 

specified) working covariance 

Covariates: temperature, humidity 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-5 days 

Pollutant: PM2.5

Averaging Time: 1 h and 24 h 

Mean (SD): 1-h averaging, 20.767 

24-h averaging, 8.534 

Range (Min, Max): 1-h averaging 

(0.012: 93.433) 

24-h averaging 

(0.004: 39.404) 

Monitoring Stations: 10 total, usually 

3-5 sites for each pollutant 

Copollutant (correlation): 

O3

NO+

CO 

 

PM Increment: NR 

[Lower CI, Upper CI] 

lag: NR 

LAG: 0 day 

PM2.5, 1-h 

Body temperature: 1.004 [0.998: 1.011] 

Cough: 1.006 [1.000: 1.012] 

Wheeze/rattle chest: 

1.004 [0.998: 1.010] 

Runny/blocked nose: 

0.997 [0.983: 1.010] 

PM2.5, 24-h 

Body temperature: 1.005 [0.986: 1.024] 

Cough: 1.019 [0.999: 1.040] 

Wheeze/rattle chest: 

0.990 [0.969: 1.012] 

Runny/blocked nose: 

0.968 [0.926: 1.013] 

LAG: 5 days 

PM2.5, 1-h 

Body temperature: 1.005 [0.999: 1.040] 

Cough: 1.003 [0.995: 1.010] 

Wheeze/rattle chest: 1.005 [0.998: 

10.12] 

Runny/blocked nose: 1.015 [1.000: 

1.030] 

PM2.5, 24-h 

Body temperature: 1.020 [0.998: 1.011] 

Cough: 1.006 [0.984: 1.011] 

Wheeze/rattle chest: 

1.018 [0.997: 1.040] 

Runny/blocked nose: 

1.039 [0.990: 1.089] 

LAG: 0-5 days 

PM2.5, 1-h 

Body temperature: 1.000 [0.998: 1.002] 

Cough: 1.001 [0.999: 1.003] 

Wheeze/rattle chest: 

1.002 [1.000: 1.004] 

Runny/blocked nose: 

1.01 [0.997: 1.006] 

1.02 PM2.5, 24-h 

Body temperature: 1.000 [0.994: 1.005] 

Cough: 1.004 [0.997: 1.011] 

Wheeze/rattle chest: 

1.001 [0.995: 1.007] 

Runny/blocked nose: 

0.998 [0.985: 1.011] 

December 2009 E-213 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sakai et al. (2004, 087435) 

Period of Study: 

Nov 1999-Mar 2001 

Location: Diesel-powered ship from 

Tokyo, Japan to Showa Station on Ongul 

Island, Antarctica for 366 days (from Feb 

1, 2000) and then heading back to 

Japan on Feb 1, 2001 

Outcome: circulating leukocyte counts 

and serum inflammatory cytokine levels 

Age Groups: 24-57 yr, mean=36.1 ± 4.7 

yr 

Study Design: Cohort 

N: 39 members of 41st Japanese 

Antarctic Research Expedition 

(JARE-41) 

Statistical Analyses: ANOVA 

Covariates: Smoking history, 

occupational pollutant exposure 

Dose-response Investigated? No 

Statistical Package: SPSS 11.5J 

Pollutant: PM5.0-2.0

Averaging Time: 24 h 

Unit (i.e. μg/m3): particles/L 

PM Component: organic and inorganic 

substances, including microorganisms 

Copollutant (correlation): 

PM2.0-0.3

PM10-5.0

Effect Estimate: 

Multiple regression analysis between 

inhaled factors in Antarctica 

Total leukocyte 

Cigarette smoking= 0.211, p < 0.001 

Support staff= 0.139, p=0.024 

Total PM= 0.168, p=0.004 

Segmented PMN 

Cigarette smoking= 0.015, p=0.805 

Support staff= 0.097, p=0.119 

Total PM= 0.272, p < 0.001 

Band-formed PMN 

Cigarette smoking= 0.035, p=0.543 

Support staff= 0.010, p=0.864 

Total PM= 0.470, p < 0.001 

Monocyte 

Cigarette smoking= 0.081, p=0.187 

Support staff= -0.019, p=0.759 

Total PM= 0.328, p < 0.001 

G-CSF 

Cigarette smoking= 0.131, p < 0.038 

Support staff= 0.176, p=0.005 

Total PM= 0.078, p=0.186 

IL-6 

Cigarette smoking= 0.182, p=0.004 

Support staff= 0.076, p=0.228 

Total PM= 0.158, p=0.008 

Reference: Sakai et al. (2004, 087435) 

Period of Study: Nov 1999-Mar 28, 

2001 

Location: Diesel-powered ship from 

Tokyo, Japan to Showa Station on Ongul 

Island, Antarctica for 366 days (from Feb 

1, 2000) and then heading back to 

Japan on Feb 1, 2001 

Outcome: circulating leukocyte counts 

and serum inflammatory cytokine levels 

Age Groups: 24-57 yr, mean=36.1 ± 4.7 

yr 

Study Design: cohort 

N: 39 members of 41st Japanese 

Antarctic Research Expedition (JARE41) 

Statistical Analyses: ANOVA 

Covariates: Smoking history, 

occupational pollutant exposure 

Dose-response Investigated? No 

Statistical Package: SPSS 11.5J 

Pollutant: PM10-5.0

Averaging Time: 24 h 

Unit (i.e. μg/m3): particles/L 

Monitoring Stations: NR 

Copollutant (correlation): 

PM2.0-0.3

PM10-5.0

Effect Estimate: 

Multiple regression analysis between 

inhaled factors in Antarctica 

Total leukocyte 

Cigarette smoking= 0.211, p < 0.001 

Support staff= 0.139, p=0.024 

Total PM= 0.168, p=0.004 

Segmented PMN 

Cigarette smoking= 0.015, p=0.805 

Support staff= 0.097, p=0.119 

Total PM= 0.272, p < 0.001 

Band-formed PMN 

Cigarette smoking= 0.035, p=0.543 

Support staff= 0.010, p=0.864 

Total PM= 0.470, p < 0.001 

Monocyte 

Cigarette smoking= 0.081, p=0.187 

Support staff= -0.019, p=0.759 

Total PM= 0.328, p < 0.001 

G-CSF 

Cigarette smoking= 0.131, p < 0.038 

Support staff= 0.176, p=0.005 

Total PM= 0.078, p=0.186 

IL-6 

Cigarette smoking= 0.182, p=0.004 

Support staff= 0.076, p=0.228 

Total PM= 0.158, p=0.008 

December 2009 E-214 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Silkoff et al. (2005, 087471) 

Period of Study: Winter 1999-2000, 

Winter 2000-2001 

Location: Denver, CO 

Outcome: Lung function: FEV1, PEF 

Age Groups: Adults (>40 yr-old) with 

COPD, as well as >10 pack-yr tobacco 

use, FEV1 < 70%, FEV1/FVC < 60%, 

and no other lung disease 

Study Design: COPD patient panel 

study (2 independent panels 

One for each winter) 

N: 34 subjects (16 1st winter, 18 

second winter) 

Statistical Analyses: Mixed effects 

models with first-order, autoregressive, 

ma variance-covariance 

Binary outcomes (rescue medication 

use, total symptom score) assessed 

using Poisson regression with GEE and 

first-order, auto-regressive variancecovariance 

Covariates: Temperature, relative 

humidity, barometric pressure analysis 

run separately for each winter 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Winter 1999-2000: 9.0 (5.2) 

Winter 2000-2001: 14.3 (9.6) 

Percentiles: 

Winter 1999-2000 

25th 5.4 

50th(Median): 7.7 

75th: 11.3 

Winter 2000-2001 

25th 7.6 

50th(Median): 11.7 

75th: 17.2 

Range (Min, Max): 

Winter 1999-2000 

(1.8, 36.6) 

Winter 2000-2001 

(3.4, 59.6) 

Monitoring Stations: multiple sites 

Copollutant (correlation): 

CO 

NO2

PM10

PM Increment: SD 

Winter 1999-2000: 5.2 

Winter 2000-2001: 9.6 

Model results reported graphically only. 

No quantitative results reported. 

Direction of slope (±) and statistical 

significance (SIG: yes; NS: no) inferred 

from graphs. 

Among subjects with severe COPD 

observed in Winter 1999-2000, 

statistically significant, but marginal, 

improvements in PEF associated with 

morning lag 0 PM2.5. 

There were no statistically significant 

associations between rescue 

medication use and symptom score 

with PM. 

Reference: Sivacoumar et al. (2006, 

111115) 

Period of Study: Apr 1998-May 1998; 

Sep 1998-Oct 1998 

Location: Pammal, India 

Outcome: Respiratory symptoms, 

Decreased pulmonary function 

Study Design: Case-control 

Statistical Analyses: Poisson 

Age Groups: >18 

Pollutant: PM2.5

Averaging Time: 24-h avg 

The study does not present quantitative 

results of association. 

Reference: Slaughter et al. (2003, 

086294) 

Period of Study: 1994 

Location: Seattle, WA 

Outcome: Asthma attacks, asthma 

severity, medication use 

Age Groups: 5.1-13.1 yr old 

Study Design: Cross-sectional study 

N: 133 children 

Statistical Analyses: Ordinal Logistic 

Regression 

Poisson Modeling 

Covariates: Temperature, Day of the 

Week, Seasonality 

Dose-response Investigated? No 

Statistical Package: STATA 

Lags Considered: 1-, 2-, 3-day lag 

Pollutant: PM2.5

Averaging Time: 

Daily Avg 

25th: 5.0 

50th(Median): 7.3 3 

75th: 11.3 

Monitoring Stations: 3 

Copollutant (correlation): 

PM10 = 0.75 

CO = 0.82 

PM Increment: 10 μg/m3 increase 

RR Estimate [Lower CI, Upper CI] 

lag: 

Inhaler use: 

1-day lag: 1.04 (0.98, 1.10) 

OR Estimate [Lower CI, Upper CI] 

lag: 

Asthma Attack: 

1-day lag: 1.20 (1.05, 1.37) 

Previous day: 1.13 (1.03, 1.23) 

Medication Use 

Nontransition model: 

Previous Day: 1.08 (1.01, 1.15) 

Notes: Figures of estimated odds ratios 

for having a more serious asthma 

attack for short-term, within-subject 

increases in PM2.5, PM10, and CO. 

Transition models additionally control 

for the previous day’s severity. 

Figures of estimated relative risks for 

having inhaler use for short-term, 

within-subject increases in PM2.5, PM10, 

and CO. Transition models additionally 

control for the previous day’s severity. 

December 2009 E-215 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Strand et al. (2006, 

089203) 

Period of Study: 2002-2004 

Location: Denver, Colorado, United 

States 

Outcome: Reduced forced expiratory 

volume (FEV1) 

Age Groups: 6-12 yr old 

Study Design: Mixed model analysis 

(using the default restricted maximum 

likelihood (REML) estimators) 

N: 50 children 

Statistical Analyses: least squares 

regression, SAS “Output Delivery 

System” (ODS) 

Season: Fall and Winter 

Dose-response Investigated? Yes 

Statistical Package: SAS 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD): 

Outdoor: 12.699 (6.426) 

Indoor: 8.148 (4.348) 

Sulfate/PM2.5/outdoor: 0.079 (0.067) 

Sulfate/PM2.5/indoor: 0.074 (0.060) 

Range (Min, Max): 

Mean Personal: (0, 3.035) 

Outdoor: (0, 6.303) 

Indoor: (0, 2.759) 

PM Component: EC, sulfate, nitrate and 

ETS. 

Monitoring Stations: 2 fixed monitors 

and up to 10 personal monitors on a 

given day. 

Copollutant (correlation): Sulfate 

(0.63) 

PM Increment: 10 μg/m3

Effects Estimate: 

Using the estimated slope for the 

validation study model [Lower CI, Upper 

CI] lag: 

2.2 percent decrease in FEV1 per 10 

μg/m3

 increase in ambient PM2.5 [0.0, 

4.3 decrease] 1 day 

Reference: Tang et al. (2007, 091269) 

Period of Study: Dec 2003-Feb 2005 

Location: Sin-Chung City, Taipei 

County, Taiwan 

Outcome: Peak expiratory flow rate 

(PEFR) of asthmatic children 

Age Groups: 6-12 yr 

Study Design: Panel study 

N: 30 children 

Statistical Analyses: Linear mixedeffect models were used to estimate the 

effect of PM exposure on PEFR 

Covariates: Gender, age, BMI, history 

of respiratory or atopic disease in 

family, SHS, acute asthmatic 

exacerbation in past 12 mo, ambient 

temp and relative humidity, presence of 

indoor pollutants, and presence of 

outdoor pollutants, 

Dose-response Investigated? yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-2 

Pollutant: PM2.5

Averaging Time: 1 h 

Mean (SD): 

Personal: 27.8 (25.3) 

Range (Min, Max): 

Personal: 1.4-263.4 

Monitoring Stations: 1 

PM Increment: 24.5 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Change in morning PEFR: 

-6.00 (-29.85, 17.85) lag 0 

-12.52 (-77.93, 52.9) lag 1 

-24.87 (-71.49, 21.74) lag 2 

-45.67 (-117.09, 25.74) 2-day mean 

-5.69 (-105.96, 94.59) 3-day mean 

Change in evening PEFR: 

0.50 (-18.82, 19.82) lag 0 

16.66 (-7.59, 40.9) lag 1 

11.60 (-11.1, 34.31) lag 2 

39.97 (7.1, 72.85) 2-day mean 

-3.32 (-66.14, 59.5) 3-day mean 

Reference: Timonen et al. (2004, 

087915) 

Period of Study: Oct 1998-Apr 1999 

Location: Amsterdam, Netherlands 

Erfurt, Germany 

Helsinki, Finland 

Outcome: Urinary concentration of 

Clara cell protein CC16 of subjects with 

coronary heart disease 

Age Groups: 50+ 

Study Design: Longitudinal cohort 

study (panel) 

N: 37 (Amsterdam) 

47 (Erfurt) 

47 (Helsinki) 

Statistical Analyses: The response of 

interest was log transformed, creatinine 

adjusted CC16. Mixed-effect model was 

used to investigate the association 

between CC16 and air pollutants. 

Covariates: Subjects, long term time 

trend, temperature (lags 0-3), relative 

humidity (lags 0-3), barometric pressure 

(lags 0-3), and weekday of visit. 

Dose-response Investigated? yes 

Statistical Package: S-Plus and SAS 

Lags Considered: 0-3 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Amsterdam: 20.0 μg/m3

Erfurt: 23.1 μg/m3

Helsinki: 12.7 μg/m3 

Range (Min, Max): 

Amsterdam: 3.8-82.2 

Erfurt: 4.5-118.1 

Helsinki: 3.1-39.8 

Monitoring Stations: 3 

Copollutant (correlation): 

Spearman Correlation: 

NC 0.01-0.1: Amsterdam -0.15 

Erfurt 0.62 

Helsinki 0.14 

NC0.1-1.0: Amsterdam 0.80 

Erfurt 0.84 

Helsinki 0.80 

NO2: Amsterdam 0.49 

Erfurt 0.82 

Helsinki 0.35 

CO: Amsterdam 0.58 

Erfurt 0.77 

Helsinki 0.40 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Pooled estimate; 

2.8 (-1.1-6.7) lag 0 

2.9 (-0.6-6.5) lag 1 

5.0 (-2.4-12.4) lag 2 

1.6 (-4.7-7.9) lag 3 

9.7 (-6.0-25.4) 5-day mean 

CC16 was not associated to PM2.5

in the pooled analysis but CC16 was 

significantly associated to PM2.5

in Helsinki: 

23.3 (6.3-40.3) lag 0 

6.4 (-8.2-21.1) lag 1 

20.2 (6.9-33.5) lag 2 

17.6 (4.3-30.9) lag 3 

38.8 (15.8-61.8) 5-day mean 

December 2009 E-216 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Trenga et al. (2006, 

155209) 

Period of Study: 1999-2002 

Location: Seattle, WA 

Outcome: Lung function: FEV1, PEF, 

MMEF (maximal midexpiratory flow 

assessed only for children) 

Age Groups: Adults (56-89-yr-old) 

healthy & with COPD 

Asthmatic children 6-13-yr-old 

Study Design: Adult and pediatric 

panel study over 3 yr with 1 monitoring 

period (“session”) per yr 

N: 57 adults (33 healthy, 24 with COPD) 

= 692 subject-days = 207 study-days 

17 asthmatic children = 319 subjectdays = 98 study-days 

Statistical Analyses: Mixed effects, 

longitudinal regression models, with the 

effects of pollutant decomposed into 

each subject’s 

a) overall mean 

b) Difference between their sessionspecific mean and overall mean 

c) Difference between their daily values 

and session-specific mean 

Covariates: Gender, age, ventral site 

temperature and relative humidity, CO, 

NO2

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Percentiles: 

Children 

Personal 

25th: 8.1 

50th(Median): 11.3 

75th: 16.3 

Indoor 

25th: 5.7 

50th(Median): 7.5 

75th: 10.2 

Local outdoor 

25th: 6.4 

50th(Median): 9.6 

75th: 14. 

Adults 

Personal 

25th: 5.9 

50th(Median): 8.5 

75th: 12.4 

Indoor 

25th: 5.1 

50th(Median): 7.6 

75th: 10.8 

Local outdoor 

25th: 6 

50th(Median): 8.6 

75th: 13.1 

Range (Min, Max): 

Children, Personal 1.0, 49.4 

Indoor (2.2, 36.3) 

Local outdoor (2.8, 40.4) 

Adults, Personal 1.3, 66.6 

Indoor(1.6, 65.3) 

Local outdoor (0.0, 41.5) 

Monitoring Stations: 2 

also subject-specific local outdoors (i.e., 

at each home), indoor, and personal 

Copollutant (correlation): 

CO 

NO2

PM2.5

PM10-2.5 (coarse) 

PM Increment: 10 μg/m3

ADULT 

Personal PM2.5 - FEV1

Overall: Lag 0 -6.0 [-29.1: 17.2]

Lag 1 12.0 [-12.9: 36.9] 

No-COPD: Lag 0 -4.6 [-31.0: 21.9] 

Lag 1 19.3 [-8.2: 46.7] 

COPD: Lag 0 -10.2 [-55.8: 35.4] 

Lag 1 -19.0 [-74.1: 36.2] 

PEF: Lag 0 1.5 [-2.2: 5.2] 

Lag 1 2.1 [-1.9: 6.1] 

No-COPD: Lag 0 3.4 [-0.9: 7.6] 

Lag 1 1.9 [-2.5: 6.3] 

COPD: Lag 0 -4.3 [-11.5: 3.0] 

Lag 1 2.6 [-6.3: 11.5]

Indoor PM2.5 - FEV1 

Overall: Lag 0 -12.8 [-44.5: 19.0] 

Lag 1 19.4 [-11.3: 50.1] 

No-COPD: Lag 0 -15.8 [-50.0: 18.4] 

Lag 1 28.4 [-4.6: 61.3] 

COPD: Lag 0 2.6 [-71.7: 76.8] 

Lag 1 -29.7 [-102.9: 43.5] 

PEF 

Overall: Lag 0 -0.5 [-5.6: 4.6] 

Lag 1 2.3 [-3.3: 7.8] 

No-COPD: Lag 0 0.1 [-5.4: 5.6] 

Lag 1 2.5 [-3.5: 8.4] 

COPD: Lag 0 -3.2 [-15.1: 8.7] 

Lag 1 1.1 [-12.0: 14.3] 

Outdoor Home PM2.5 - FEV1 

Overall: Lag 0 -1.4 [-35.6: 32.7] 

Lag 1 -2.4 [-37.6: 32.7]. No-COPD: Lag 

0 1.5 [-36.1: 39.2] 

Lag 1 10.7 [-26.9: 48.4] 

COPD: Lag 0 -8.9 [-62.2: 44.4] 

Lag 1 -45.2 [-102.6: 12.1] 

PEF 

Overall: Lag 0 2.3 [-3.3: 7.9] 

Lag 1 0.4 [-5.6: 6.4] 

No-COPD: Lag 0 4.0 [-2.2: 10.1] 

Lag 1 2.0 [-4.4: 8.4] 

COPD: Lag 0 -1.8 [-10.6: 6.9] 

Lag 1 -4.8 [-14.6: 4.9] 

Central Sites PM2.5 - FEV1 

Overall: Lag 0 -35.5 [-70.0: -1.0] 

Lag 1 -40.4 [-71.1: -9.6]. No-COPD: Lag 

0 -32.6 [-69.5: 4.3] 

Lag 1 -29.0 [-62.5: 4.5] 

COPD: Lag 0 -43.6 [-95.0: 7.8] 

Lag 1 -70.8 [-118.4: 23.1] 

PEF 

Overall: Lag 0 1.5 [-4.2: 7.1] 

Lag 1 -2.3 [-7.4: 2.9] 

No-COPD: Lag 0 2.5 [-3.5: 8.6] 

Lag 1 -0.5 [-6.1: 5.0] 

COPD: Lag 0 -1.5 [-9.9: 6.9] 

Lag 1 -7.1 [-15.0: 0.9] 

PEDIATRIC FEV1 

Personal PM2.5 Overall: 

Lag 0 -13.08 [-38.26: 12.10] 

Lag 1 -16.12 [-42.61: 10.37]. 

No anti-inflammatory medication: 

 Lag 0 -41.73 [-94.31: 10.84] 

Lag 1 -30.99 [-82.17: 20.19]. 

Anti-inflammatory medication: 

Lag 0 -4.61 [-34.49: 25.28] 

Lag 1 -10.87 [-45.01: 23.27] 

Indoor PM2.5 

Overall: 

Lag 0 -45.90 [-89.92: 1.88] 

Lag 1 -64.78 [-111.27: 18.28] 

No anti-inflammatory medication: 

Lag 0 -75.92 [-145.16: 6.67] 

Lag 1 -65.08 [-136.98: 6.82]. 

Anti-inflammatory medication: 

Lag 0 -28.50 [-94.72: 37.71] 

December 2009 E-217 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Lag 1 -64.60 -147.23: 18.04] 

Outdoor Home PM2.5 

Overall: 

Lag 0 -13.11 [-57.41: 31.19] 

Lag 1 -9.37 [-54.73: 36.00]. 

No anti-inflammatory medication: 

Lag 0 -24.42 [-81.22: 32.38] 

Lag 1 16.52 [-45.76: 78.80]. 

Anti-inflammatory medication: 

 Lag 0 -3.59 [-75.88: 68.70] 

Lag 1-26.76 [-89.53: 36.01] 

Central Sites PM2.5. 

Overall: 

Lag 0 -12.32 [-53.21: 28.56] 

Lag 1 5.75 [-33.27: 44.76]. 

No anti-inflammatory medication: 

Lag 0 -33.59 [-89.99: 22.82] 

Lag 1 31.30 [-29.91: 92.51] 

Anti-inflammatory medication: 

Lag 0 -2.13 [-71.99: 67.73] 

Lag 1 -3.53 [-67.32: 60.27] 

PEF: 

Personal PM2.5 Overall: 

Lag 0 0.31 [-4.02: 4.64] 

Lag 1 -2.19 [-6.49: 2.12] 

No anti-inflammatory medication: 

Lag 0 0.22 [-8.85: 9.29] 

Lag 1 -10.48 [-18.68: 2.28] 

Anti-inflammatory medication: 

Lag 0 0.34 [-4.67: 5.35] 

Lag 1 0.74 [-4.21: 5.69] 

Indoor PM2.5 Overall: 

Lag 0 -8.68 [-16.64: -0.72] 

Lag 1 -9.22 [-17.51: -0.93] 

No anti-inflammatory medication: 

Lag 0 -13.34 [-25.90: -0.79] 

Lag 1 -17.13 [-29.86: 4.41]. 

Anti-inflammatory medication: 

Lag 0 -5.98 [-15.85: 3.89] 

Lag 1 -4.19 [-14.59: 6.20] 

Outdoor Home PM2.5 

Overall: 

Lag 0 -6.27 [-14.07: 1.53] 

Lag 1 -5.64 [-13.73: 2.44]. 

No anti-inflammatory medication: 

Lag 0 -7.52 [-17.56: 2.51] 

Lag 1 -6.92 [-18.03: 4.19]. 

Anti-inflammatory medication: 

Lag 0 -5.22 [-14.77: 4.34] 

Lag 1 -4.78 [-14.42: 4.86] 

Central Sites PM2.5

Overall: 

Lag 0 -5.62 [-12.86: 1.62] 

Lag 1 -2.45 [-9.34: 4.43]. 

No anti-inflammatory medication: 

Lag 0 -6.32 [-16.31: 3.68] 

Lag 1 -0.83 [-11.60: 9.95] 

Anti-inflammatory medication: 

Lag 0 -5.29 [-13.42: 2.85] 

Lag 1 -3.04 [-10.76: 4.67] 

MMEF 

Personal PM2.5

Overall: 

Lag 0 -0.99 [-3.96: 1.98] 

Lag 1 -1.08 [-4.05: 1.88]. 

No anti-inflammatory medication: 

Lag 0 -3.32 [-9.52: 2.88] 

Lag 1 -2.49 [-8.23: 3.25]. 

Anti-inflammatory medication: 

Lag 0 -0.31 [-3.77: 3.16] 

Lag 1 -0.59 [-4.06: 2.89] 

Indoor PM2.5

Overall: Lag 0 -3.29 [-8.52: 1.94]

Lag 1 -11.08 [-16.26: 5.90]. 

Anti-inflammatory medication: 

Lag 0-12.65 [-20.74: -4.56]’ Lag 1 -

December 2009 E-218 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

13.84 [-21.82: 5.85] 

Anti-inflammatory medication: 

Lag 0 2.14 [-4.17: 8.45] 

Lag 1 -9.33 [-15.89: -2.78] 

Outdoor Home PM2.5 

Overall: 

Lag 0 -4.13 [-9.28: 1.01]

Lag 1 -0.73 [-6.02: 4.56]

No anti-inflammatory medication: 

Lag 0 -8.23 [-14.77: 1.69] 

Lag 1 -1.19 [-8.45: 6.07] 

Anti-inflammatory medication: 

Lag 0 -0.68 [-6.87: 5.50] 

Lag 1 -0.42 [-6.72: 5.87] 

Central Sites PM2.5. 

Overall: 

Lag 0 -2.10 [-6.99: 2.79] 

Lag 1 -0.12 [-4.67: 4.42]

No anti-inflammatory medication: 

Lag 0 -8.21 [-14.79: 1.62] 

Lag 1 -0.22 [-7.34: 6.90] 

Anti-inflammatory medication: 

Lag 0 0.82 [-4.48: 6.12]. 

Lag 1 -0.09 [-5.19: 5.01] 

Reference: Tang et al. (2007, 091269) 

Period of Study: Dec 2003-Feb 2005 

Location: Sin-Chung City, Taipei 

County, Taiwan 

Outcome: Peak expiratory flow rate 

(PEFR) of asthmatic children 

Age Groups: 6-12 yr 

Study Design: Panel study 

N: 30 children 

Statistical Analyses: Linear mixedeffect models were used to estimate the 

effect of PM exposure on PEFR 

Covariates: Gender, age, BMI, history 

of respiratory or atopic disease in family, 

SHS, acute asthmatic exacerbation in 

past 12 mo, ambient temp and relative 

humidity, presence of indoor pollutants, 

and presence of outdoor pollutants, 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-2 

Pollutant: PM2.5-1

Averaging Time: 1 h 

Mean (SD): 

Personal: 6.2 (4.8) 

Range (Min, Max): 

Personal: 0.3-86.8 

Monitoring Stations: 1 

No quantitative effects reported. 

Reference: Tang et al. (2007, 091269) 

Period of Study: Dec 2003-Feb 2005 

Location: Sin-Chung City, Taipei 

County, Taiwan 

Outcome: Peak expiratory flow rate 

(PEFR) of asthmatic children 

Age Groups: 6-12 yr 

Study Design: Panel study 

N: 30 children 

Statistical Analyses: Linear mixedeffect models were used to estimate the 

effect of PM exposure on PEFR 

Covariates: Gender, age, BMI, history 

of respiratory or atopic disease in family, 

SHS, acute asthmatic exacerbation in 

past 12 mo, ambient temp and relative 

humidity, presence of indoor pollutants, 

and presence of outdoor pollutants, 

Dose-response Investigated? yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-2 

Pollutant: PM1 

Averaging Time: 1 h 

Mean (SD): 

Personal: 34.0 (28.9) 

Ambient: 31.4 (18.8) 

Range (Min, Max): 

Personal: 1.8-284.6 

Ambient: 0.1-128.4 

Monitoring Stations: 1 

PM Increment: 27.6 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Change in morning PEFR: 

-6.44 (-30.18, 17.29) lag 0 

-12.26 (-77.6 , 53.09) lag 1 

-4.38 (-54.79, 46.03) lag 2 

-44.06 (-113.79, 25.67) 2-day mean 

-6.01 (-101.48, 89.46) 3-day mean 

Change in evening PEFR: 

1.17 (-17.79, 20.13) lag 0 

-4.98 (-27.77, 17.81) lag 1 

11.30 (-11.55, 34.16) lag 2 

41.74 (11.36, 72.13) 2-day mean 

28.21 (-19.08, 75.5) 3-day mean 

December 2009 E-219 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Timonen et al. (2004, 

087915) 

Period of Study: Oct 1998-Apr 1999 

Location: 

Amsterdam, The Netherlands 

Erfurt, Germany 

Helsinki, Finland 

Outcome: Urinary concentration of 

Clara cell protein CC16 of subjects with 

coronary heart disease 

Age Groups: 50+ 

Study Design: Longitudinal cohort 

study (panel) 

N: 

N=37 (Amsterdam) 

N=47 (Erfurt) 

N=47 (Helsinki) 

Statistical Analyses: The response of 

interest was log transformed, creatinine 

adjusted CC16. Mixed-effect model was 

used to investigate the association 

between CC16 and air pollutants. 

Covariates: Subjects, long term time 

trend, temperature (lags 0-3), relative 

humidity (lags 0-3), barometric pressure 

(lags 0-3), and weekday of visit. 

Dose-response Investigated? yes 

Statistical Package: 

S-Plus and SAS 

Lags Considered: 0-3 

Pollutant: NC 0.01-0.1 

Averaging Time: 24 h 

Mean (SD): 

Amsterdam: 17338 /cm3

Erfurt: 21124 /cm3

Helsinki: 17041 /cm3 

Range (Min, Max): 

Amsterdam: 5699-37195 

Erfurt: 3867-96678 

Helsinki: 2305-50306 

Unit (i.e. μg/m3

): 1/cm3 

Monitoring Stations: 3 

PM2.5: 

Amsterdam -0.15 

Erfurt 0.62 

Helsinki 0.14 

NO2: 

Amsterdam 0.49 

Erfurt 0.82 

Helsinki 0.72 

CO: 

Amsterdam 0.22 

Erfurt 0.72 

Helsinki 0.35 

PM Increment: 10,000 /cm3

RR Estimate [Lower CI, Upper CI] 

lag: 

Pooled estimate; 

1.7 (-4.4-7.8) lag 0 

-1.8 (-8.3-4.6) lag 1 

1.5 (-5.6-8.6) lag 2 

2.3 (-4.8-9.3) lag 3 

1.8 (-9.4-13.0) 5-day mean 

There was no association between NC 

0.01-0.1 and CC16 in the pooled 

analysis. 

Reference: Timonen et al. (2004, 

087915) 

Period of Study: Oct 1998-Apr 1999 

Location: 

Amsterdam, The Netherlands 

Erfurt, Germany 

Helsinki, Finland 

Outcome: Urinary concentration of 

Clara cell protein CC16 of subjects with 

coronary heart disease 

Age Groups: 50+ 

Study Design: Longitudinal cohort 

study (panel) 

N: 

N=37 (Amsterdam) 

N=47 (Erfurt) 

N=47 (Helsinki) 

Statistical Analyses: The response of 

interest was log transformed, creatinine 

adjusted CC16. Mixed-effect model was 

used to investigate the association 

between CC16 and air pollutants. 

Covariates: Subjects, long term time 

trend, temperature (lags 0-3), relative 

humidity (lags 0-3), barometric pressure 

(lags 0-3), and weekday of visit. 

Dose-response Investigated? Yes 

Statistical Package: S-Plus and SAS 

Lags Considered: 0-3 

Pollutant: NC10-0.1 

Averaging Time: 24 h 

Mean (SD): 

Amsterdam: 2131 /cm3

Erfurt: 1829 /cm3

Helsinki: 1390 /cm3 

Range (Min, Max): 

Amsterdam: 413-6413 

Erfurt: 303-6848 

Helsinki: 344-3782 

Unit (i.e. μg/m3

): 1/cm3 

Monitoring Stations: 3 

Copollutant (correlation): 

Spearman Correlation: 

NC 0.1-0.01: 

Amsterdam 0.16 

Erfurt 0.67 

Helsinki 0.53 

PM2.5: 

Amsterdam 0.80 

Erfurt 0.84 

Helsinki 0.80 

NO2: Amsterdam 0.67 

Erfurt 0.82 

Helsinki 0.72 

CO: 

Amsterdam 0.60 

Erfurt 0.78 

Helsinki 0.51 

PM Increment: 1000 /cm3

RR Estimate [Lower CI, Upper CI] lag: 

Pooled estimate; 

4.3 (-1.4-10.0) lag 0 

5.1 (-0.6-10.7) lag 1 

4.5 (-0.5-9.6) lag 2 

1.6 (-3.5-6.7) lag 3 

13.1 (-4.3-30.5) 5-day mean 

CC16 was not associated to NC 0.1-1.0 

in the pooled analysis but CC16 was 

significantly associated to NC 0.1-1.0 in 

Helsinki: 

15.5 (0.001-30.9) lag 0 

10.8 (-4.2-25.8) lag 1 

10.5 9-4.1-25.1) lag 2 

17.4 (3.4-31.4) lag 3 

43.2 (17.4-69.0) 5-day mean 

December 2009 E-220 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: von Klot et al. (2002, 

034706) 

Period of Study: Sep 1996-Mar 1997 

(winter) 

Location: Erfurt, Germany 

Outcome: Asthma symptoms 

(wheezing, shortness of breath at rest, 

waking up with breathing problems, or 

coughing without having a cold) and 

Asthma medication (inhaled short-acting 

ß2- agonists, inhaled long-acting ß2- 

agonists, inhaled corticosteroids, 

cromolyn sodium, theophylline, oral 

corticosteroids, and N-acetylcysteine) 

Age Groups: Adults, mean=59.0 yr and 

range =37-77 yr 

Study Design: Panel study 

N: 53 adult asthmatics 

Statistical Analyses: Logistic 

regression models 

Covariates: Seasonal variation in 

medication use or symptom prevalence, 

meteorological factors (relative humidity, 

temperature), weekend, Christmas 

holidays 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

8, 9, 10, ma calculated from same day 

and preceding days 

Pollutant: MC0.5-0.1 

Averaging Time: 10-min intervals 

Mean (SD): 24.8 

Percentiles: 

25th: 11.4 

50th(Median): 19.6 

75th: 33.1 

Range (Min, Max): (2.4-108.3) 

Copollutant (correlation): 

PM10-2.5: r= 0.51 

NC0.1-0.01: r= 0.45 

NC0.5-0.1: r= 0.95 

NC2.5-0.5: r= 0.92 

MC2.5-0.01: r= 1.00 

PM10: r= 0.91 

NO2: r= 0.69 

CO: r= 0.66 

SO2: r= 0.60 

NC Increment: 1 IQR 

Effect Estimate [Lower CI, Upper CI]: 

Association between the prevalence of 

inhaled ß2- agonist use and MC0.1-0.5 

Same day, IQR= 21, 

OR= 0.98 (0.92-1.04) 

5-day mean, IQR= 21 

OR= 1.11 (1.02-1.20) 

14-day mean IQR= 17, 

OR= 1.01 (0.93-1.10) 

Association between the prevalence of 

inhaled corticosteroid use and 

MC0.1-0.5 

Same day, IQR= 2, 

OR= 1.09 (1.02-1.17) 

5-day mean IQR= 21, 

OR= 1.28 (1.18-1.39) 

14-day mean, IQR= 17, 

OR= 1.49 (1.38-1.61) 

Association between the prevalence of 

wheezing and MC0.1-0.5 

Same day, IQR= 21, 

OR= 1.01 (0.94-1.08) 

5-day mean, IQR= 21, 

OR= 1.08 (0.99-1.17) 

14-day mean, IQR= 17, 

OR= 1.05 (0.96-1.15) 

Reference: von Klot et al. (2002, 

034706) 

Period of Study: Sep 1996-Mar 1997 

(winter) 

Location: Erfurt, Germany 

Outcome: Asthma symptoms 

(wheezing, shortness of breath at rest, 

waking up with breathing problems, or 

coughing without having a cold) and 

Asthma medication (inhaled short-acting 

ß2- agonists, inhaled long-acting ß2- 

agonists, inhaled corticosteroids, 

cromolyn sodium, theophylline, oral 

corticosteroids, and N-acetylcysteine) 

Age Groups: Adults, mean=59.0 yr and 

range =37-77 yr 

Study Design: Panel study 

N: 53 adult asthmatics 

Statistical Analyses: Logistic 

regression models 

Covariates: Seasonal variation in 

medication use or symptom prevalence, 

meteorological factors (relative humidity, 

temperature), weekend, Christmas 

holidays 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

8, 9, 10, ma calculated from same day 

and preceding days 

Pollutant: MC2.5-0.01 

Averaging Time: 10-min intervals 

Mean (SD): 30.3 

Percentiles: 

25th: 13.5 

50th(Median): 24.6 

75th: 41.3 

Range (Min, Max): (3.6-133.8) 

Copollutant (correlation): 

PM10-2.5: r= 0.52 

NC0.5-0.1: r= 0.45 

NC2.5-0.5: r= 0.94 

MC0.5-0.1: r= 1.00 

NC0.1-0.01: r= 0.45 

PM10: r= 0.94 

NO2: r= 0.68 

CO: r= 0.65 

SO2: r= 0.62 

NC Increment: 1 IQR 

Effect Estimate [Lower CI, Upper CI]: 

Association between the prevalence of 

inhaled ß2- agonist use and MC0.01-

2.5 

Same day, IQR= 28, OR= 0.96 (0.90-

1.04) 

5-day mean, IQR= 26 , OR= 1.10 (1.01-

1.20) 

14-day mean, IQR= 20, OR= 1.03 

(0.95-1.12) 

December 2009 E-221 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: von Klot et al. (2002, 

034706) 

Period of Study: Sep 1996-Mar 1997 

(winter) 

Location: Erfurt, Germany 

Outcome: Asthma symptoms 

(wheezing, shortness of breath at rest, 

waking up with breathing problems, or 

coughing without having a cold) and 

Asthma medication (inhaled short-acting 

ß2- agonists, inhaled long-acting ß2- 

agonists, inhaled corticosteroids, 

cromolyn sodium, theophylline, oral 

corticosteroids, and N-acetylcysteine) 

Age Groups: Adults, mean=59.0 yr and 

range =37-77 yr 

Study Design: Panel study 

N: 53 adult asthmatics 

Statistical Analyses: Logistic 

regression models 

Covariates: Seasonal variation in 

medication use or symptom prevalence, 

meteorological factors (relative humidity, 

temperature), weekend, Christmas 

holidays 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

8, 9, 10, ma calculated from same day 

and preceding days 

Pollutant: NC0.1-0.01 

Averaging Time: 10-min intervals 

Mean (SD): 17,300 /cm3

Percentiles: 

25th: 9286 

50th(Median): 16940 

75th: 24484 

Range (Min, Max): (3272-46195) 

Unit (i.e. μg/m3

): 1/cm3

Copollutant (correlation): 

PM10-2.5: r= 0.41 

NC0.5-0.1: r= 0.55 

NC2.5-0.5: r= 0.34 

MC0.5-0.1: r= 0.45 

MC2.5-0.01: r= 0.45 

PM10: r= 0.51 

NO2: r= 0.66 

CO: r= 0.66 

SO2: r= 0.36 

NC Increment: 1 IQR 

Effect Estimate [Lower CI, Upper CI]: 

Association between the prevalence of 

inhaled ß2- agonist use and NC0.01-0.1

Same day, IQR= 15000, 

OR= 0.97 (0.90-1.04) 

5-day mean, IQR= 10000, 

OR= 1.11 (1.01-1.21) 

14-day mean, IQR= 7700, 

OR= 1.08 (0.96-1.21) 

Association between two pollutants, 

jointly in one model, and the 

Outcomes 

Inhaled short-acting ß2- agonist use 

NC0.1-0.01 OR= 1.07 (0.97-1.18) 

MC0.5-0.1: OR= 1.07 (0.98-1.18) 

Inhaled corticosteroid use 

NC0.1-0.01 OR= 1.01 (0.87-1.18) 

MC0.5-0.1: OR= 1.53 (1.39-1.69) 

Wheezing 

NC0.1-0.01 OR= 1.12 (1.01-1.24) 

MC0.5-0.1: OR= 1.02 (0.92-1.12) 

Association between the prevalence of 

inhaled corticosteroid use and NC0.01-

0.1 

Same day, IQR= 15000, 

OR= 1.07 (1.00-1.15) 

5-day mean, IQR= 10000, 

OR= 1.22 (1.12-1.33) 

14-day mean, IQR= 7700, 

OR= 1.45 (1.29-1.63) 

Association between the prevalence of 

wheezing and NC0.1-0.01 

Same day, IQR= 15000, 

OR= 0.94 (0.86-1.01) 

5-day mean, IQR= 10000, 

OR= 1.13 (1.03-1.24) 

14-day mean, IQR= 7700, 

OR= 1.27 (1.13-1.43) 

Association between the prevalence of 

respiratory symptoms and NC0.1-0.01 

Attack of shortness of breath and 

wheezing 

Same day, IQR= 15000, 

OR= 1.01 (0.91-1.12) 

5-day mean, IQR= 10000, 

OR= 1.08 (0.96-1.21) 

14-day mean, IQR= 7700, 

OR= 1.26 (1.08-1.48) 

Walking up with breathing problems 

Same day, IQR= 15000, 

OR= 1.04 (0.96-1.13) 

5-day mean, IQR= 10000, 

OR= 1.09 (0.99-1.19) 

14-day mean, IQR= 7700, 

OR= 1.26 (1.13-1.41) 

Shortness of breath 

Same day, IQR= 15000, 

OR= 0.98 (0.90-1.06) 

5-day mean, IQR= 10000, 

OR= 1.09 (0.99-1.19) 

14-day mean, IQR= 7700, 

OR= 1.24 (1.11-1.40) 

Phlegm 

Same day, IQR= 15000, 

OR= 1.01 (0.94-1.09) 

December 2009 E-222 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

5-day mean, IQR= 10000, 

OR= 1.11 (1.02-1.21) 

14-day mean, IQR= 7700, 

OR= 1.11 (0.99-1.25) 

Cough 

Same day, IQR= 15000, 

OR= 1.07 (0.98-1.16) 

5-day mean, IQR= 10000, 

OR= 1.17 (1.07-1.28) 

14-day mean, IQR= 7700, 

OR= 1.20 (1.06-1.35) 

Reference: von Klot et al. (2002, 

034706) 

Period of Study: Sep 1996-Mar 1997 

(winter) 

Location: Erfurt, Germany 

Outcome: Asthma symptoms 

(wheezing, shortness of breath at rest, 

waking up with breathing problems, or 

coughing without having a cold) and 

Asthma medication (inhaled short-acting 

ß2- agonists, inhaled long-acting ß2- 

agonists, inhaled corticosteroids, 

cromolyn sodium, theophylline, oral 

corticosteroids, and N-acetylcysteine) 

Age Groups: Adults, mean=59.0 yr and 

range =37-77 yr 

Study Design: Panel study 

N: 53 adult asthmatics 

Statistical Analyses: Logistic 

regression models 

Covariates: Seasonal variation in 

medication use or symptom prevalence, 

meteorological factors (relative humidity, 

temperature), weekend, Christmas 

holidays 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

8, 9, 10, ma calculated from same day 

and preceding days 

Pollutant: NC0.5-0.1 

Averaging Time: 10-min intervals 

Mean (SD): 2005 /cm3

Percentiles: 

25th: 958 

50th(Median): 1610 

75th: 2767 

Range (Min, Max): (291-6700) 

Unit (i.e. μg/m3

): 1/cm3

Copollutant (correlation): 

PM10-2.5: r= 0.50 

NC0.1-0.01: r= 0.55 

NC2.5-0.5: r= 0.76 

MC0.5-0.1: r= 0.95 

MC2.5-0.01: r= 0.93 

PM10: r= 0.85 

NO2: r= 0.75 

CO: r= 0.79 

SO2: r= 0.51 

NC Increment: 1 IQR 

Effect Estimate [Lower CI, Upper CI]: 

Association between the prevalence of 

inhaled ß2- agonist use and NC0.5-0.1 

Same day, IQR= 1800, 

OR= 0.99 (0.92-1.05) 

5-day mean, IQR= 1500, 

OR= 1.10 (1.03-1.19) 

14-day mean, IQR= 1450, 

OR= 0.95 (0.86-1.05) 

Association between the prevalence of 

inhaled corticosteroid use and NC0.5-

0.1 

Same day, IQR= 1800, 

OR= 1.06 (0.99-1.14) 

5-day mean, IQR= 1500, 

OR= 1.23 (1.14-1.32) 

14-day mean, IQR= 1450, 

OR= 1.51 (1.37-1.67) 

Association between the prevalence of 

wheezing and NC0.5-0.1 

Same day, IQR= 1800, 

OR= 1.00 (0.93-1.07) 

5-day mean, IQR= 1500, 

OR= 1.08 (1.00-1.17) 

14-day mean, IQR= 1450, 

OR= 1.11 (1.00-1.24) 

December 2009 E-223 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: von Klot et al. (2002, 

034706) 

Period of Study: Sep 1996-Mar 1997 

(winter) 

Location: Erfurt, Germany 

Outcome: Asthma symptoms 

(wheezing, shortness of breath at rest, 

waking up with breathing problems, or 

coughing without having a cold) and 

Asthma medication (inhaled short-acting 

ß2- agonists, inhaled long-acting ß2- 

agonists, inhaled corticosteroids, 

cromolyn sodium, theophylline, oral 

corticosteroids, and N-acetylcysteine) 

Age Groups: Adults, mean=59.0 yr and 

range =37-77 yr 

Study Design: Panel study 

N: 53 adult asthmatics 

Statistical Analyses: Logistic 

regression models 

Covariates: Seasonal variation in 

medication use or symptom prevalence, 

meteorological factors (relative humidity, 

temperature), weekend, Christmas 

holidays 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

8, 9, 10, ma calculated from same day 

and preceding days 

Pollutant: NC2.5-0.5 

Averaging Time: 10-min intervals 

Mean (SD): 21.4 /cm3

Percentiles: 

25th: 5.6 

50th(Median): 13.0 

75th: 31.6 

Range (Min, Max): (0.9-127.6) 

Unit (i.e. μg/m3

): 1/cm3

Copollutant (correlation): 

PM10-2.5: r= 0.48 

NC0.1-0.01: r= 0.34 

NC0.5-0.1: r= 0.76 

MC0.5-0.1: r= 0.92 

MC2.5-0.01: r= 0.94 

PM10: r= 0.88 

NO2: r= 0.54 

CO: r= 0.46 

SO2: r= 0.66 

NC Increment: 1 IQR 

Effect Estimate [Lower CI, Upper CI]: 

Association between the prevalence of 

inhaled ß2- agonist use and NC2.5-0.5 

Same day, IQR= 26, OR= 0.99 (0.93-

1.05) 

5-day mean, IQR= 22, OR= 1.09 (1.01-

1.17) 

14-day mean, IQR= 17, OR= 1.08 

(1.02-1.15) 

Association between the prevalence of 

inhaled corticosteroid use and NC2.5-

0.5 

Same day, IQR= 26, OR= 1.13 (1.06-

1.21) 

5-day mean, IQR= 22, OR= 1.28 (1.19-

1.37) 

14-day mean, IQR= 17, OR= 1.44 

(1.36-1.53) 

Association between the prevalence of 

wheezing and NC2.5-0.5 

Same day, IQR= 26, OR= 1.03 (0.95-

1.10) 

5-day mean, IQR= 22, OR= 1.05 (0.97-

1.13) 

14-day mean, IQR= 17, OR= 1.03 

(0.96-1.10) 

Reference: von Klot et al. (2002, 

034706) 

Period of Study: Sep 1996-Mar 1997 

(winter) 

Location: Erfurt, Germany 

Outcome: Asthma symptoms 

(wheezing, shortness of breath at rest, 

waking up with breathing problems, or 

coughing without having a cold) and 

Asthma medication (inhaled short-acting 

ß2- agonists, inhaled long-acting ß2- 

agonists, inhaled corticosteroids, 

cromolyn sodium, theophylline, oral 

corticosteroids, and N-acetylcysteine) 

Age Groups: Adults, mean=59.0 yr and 

range =37-77 yr 

Study Design: Panel study 

N: 53 adult asthmatics 

Statistical Analyses: Logistic 

regression models 

Covariates: Seasonal variation in 

medication use or symptom prevalence, 

meteorological factors (relative humidity, 

temperature), weekend, Christmas 

holidays 

Season: Winter 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

8, 9, 10, ma calculated from same day 

and preceding days 

Pollutant: PM10-2.5

Averaging Time: 24 h 

Mean (SD): 10.3 

Percentiles: 

25th: 2.9 

50th(Median): 6.9 

75th: 14.6 

Range (Min, Max): (-8.7-64.3) 

Copollutant (correlation): 

NC0.1-0.01: r= 0.41 

NC0.5-0.1: r= 0.50 

NC2.5-0.5: r= 0.48 

MC0.5-0.1: r= 0.51 

MC2.5-0.01: r= 0.52 

PM10: r= 0.67 

NO2: r= 0.45 

CO: r= 0.42 

SO2: r= 0.28 

PM Increment: 1 IQR 

Effect Estimate [Lower CI, Upper CI]: 

Association between the prevalence of 

inhaled ß2- agonist use and PM10-2.5

Same day, IQR= 12, OR= 1.01 (0.95-

1.06) 

5-day mean, IQR= 11, OR= 1.01 (0.94-

1.09) 

14-day mean, IQR= 6.7, OR= 0.92 

(0.86-1.00) 

Association between the prevalence of 

inhaled corticosteroid use and PM10-2.5

Same day, IQR= 12, OR= 1.03 (0.98-

1.08) 

5-day mean, IQR= 11, OR= 1.12 (1.04-

1.20) 

14-day mean, IQR= 6.7, OR= 1.27 

(1.18-1.37) 

Association between the prevalence of 

wheezing and PM10-2.5

Same day, IQR= 12, OR= 0.97 (0.91-

1.02) 

5-day mean, IQR= 11, OR= 1.06 (0.98-

1.15) 

14-day mean, IQR= 6.7, OR= 1.05 

(0.96-1.15) 

Reference: Ward et al. (2002, 025839) 

Period of Study: 1997 (two 8-wk 

periods) 

Location: Birmingham and Sandwell, 

UK 

Outcome: Change in PEF (peak 

expiratory flow), self reported 

respiratory symptoms (same day 

cough, illness, short of breath, waking 

up at night with cough or wheeze, 

wheeze) 

Age Groups: 9 yr olds 

Study Design: 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Winter: 12.7 μg/m3

Summer: 12.3 μg/m3

Range (Min, Max): 

PM Increment: 

Winter: 12.3 μg/m3 

Summer: 6.3 μg/m3

Mean (PEF l/min) [Lower CI, Upper CI]

lag: 

Winter morning: 

0.80 [-1.97, 3.67] lag 0 

0.62 [-2.22, 3.54] lag 1 

December 2009 E-224 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Time-series Panel study 

N: 162 children from 5 schools 

Statistical Analyses: Linear regression 

(PEF), 

Logistic regression (respiratory 

symptoms) 

Covariates: Trend, temperature, 

schooldays (yes/no) 

Season: Winter (Jan 13-Mar 10) 

Summer (May 19- Jul 14) 

Dose-response Investigated? No 

Statistical Package: Nr 

Lags Considered: Lag 0, lag 1, lag 2, 

lag 3, 7-day ma 

Winter: 4, 37 

Summer: 5, 28 

PM Component: 

Total mass 

Monitoring Stations: 

5 stations near the 5 schools 

Copollutant (correlation): 

Winter: 

PM10(r=0.93) 

NO2 (r=0.88) 

O3 (r=-0.83) 

Summer: 

HNO3 (r=0.81) 

-0.86 [-4.32, 2.47] lag 2 

-2.47 [-5.30, 0.36] lag 3 

-4.07 [-10.60, 2.42] 7-day mean 

Winter afternoon: 

0.95 [-2.22, 4.23] lag 0 

-0.99 [-4.69, 2.72] lag 1 

-1.60 [-5.18, 2.01] lag 2 

-3.45 [-6.53 to -0.25] lag 3 

1.00 [-11.47, 13.56] 7-day mean 

Summer morning: 

-1.49 [-3.65, 0.67] lag 0 

0.21 [-2.12, 2.55] lag 1 

2.50 [0.28, 4.72] lag 2 

3.41 [1.40, 5.44] lag 3 

3.90 [-2.53, 10.33] 7-day mean 

Summer afternoon: 

-0.49 [-2.43, 1.45] lag 0 

-0.78 [-2.72, 1.16] lag 1 

0.57 [-1.35, 2.49] lag 2 

0.16 [-1.85, 2.17] lag 3 

-0.08 [-5.43, 5.27] 7-day mean 

Winter morning in atopy/recent 

wheezing subgroup: 

-0.072 [-0.527, 0.383] lag 0 

-0.271 [-0.701, 0.159] lag 1 

0.127 [-0.354, 0.608] lag 2 

0.055 [-0.391, 0.501] lag 3 

Winter morning in no atopy or recent 

wheezing subgroup: 

0.126 [-0.413 , 0.666] lag 0 

0.193 [-0.340 , 0.728] lag 1 

-0.170 [-0.788 , 0.447] lag 2 

-0.314 [-0.846 , 0.216] lag 3 

Winter morning in subgroup with 

parental atopy/recent wheezing: 

0.187 [-0.008 , 0.382] lag 0 

-0.006 [-0.207 , 0.195] lag 1 

-0.011 [-0.226 , 0.204] lag 2 

-0.037 [-0.228 , 0.154] lag 3 

Winter morning in subgroup without 

parental atopy/recent wheezing: 

0.026 [-0.341 , 0.395] lag 0 

0.068 [-0.307 , 0.444] lag 1 

-0.099 [-0.535 , 0.335] lag 2 

-0.252 [-0.615 , 0.110] lag 3 

RR Estimate [Lower CI, Upper CI] 

lag: 

Cough: 

Winter: 0.98 [0.80, 1.18] lag 0 

0.95 [0.77, 1.17] lag 1 

1.02 [0.83, 1.24] lag 2 

1.01 [0.83, 1.23] lag 3 

1.31 [0.82, 2.09] 7-day mean 

Summer: 1.13 [1.04, 1.22] lag 0 

1.04 [0.94, 1.13] lag 1 

0.94 [0.87, 1.02] lag 2 

0.89 [0.82, 0.96] lag 3 

0.81 [0.62, 1.06] 7 day mean 

Illness: 

Winter: 1.17 [1.05, 1.32] lag 0 

1.07 [0.95, 1.23] lag 1 

1.16 [1.01, 1.35] lag 2 

1.01 [0.90, 1.16] lag 3 

1.57 [1.15, 2.13] 7-day mean 

Summer: 1.02 [0.91, 1.13] lag 0 

1.00 [0.89, 1.13] lag 1 

0.96 [0.85, 1.07] lag 2 

0.97 [ 0.86, 1.09] lag 3 

0.68 [0.41, 1.13] 7-day mean 

December 2009 E-225 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Shortness of breath: 

Winter: 1.07 [0.94, 1.24] lag 0 

0.98 [0.84, 1.13] lag 1 

0.96 [0.82, 1.13] lag2 

0.91 [0.79, 1.07] lag 3 

0.82 [0.58, 1.18] 7-day mean 

Summer: 1.04 [0.90, 1.20] lag 0 

1.08 [0.93, 1.25] lag 1 

0.97 [0.84, 1.13] lag 2 

0.93 [0.81, 1.08] lag 3 

1.16 [0.76, 1.77] 7-day mean 

Wake at night with cough/wheeze: 

Winter: 1.10 [0.96, 1.26] lag 0 

1.05 [0.90, 1.22] lag 1 

0.98 [0.83, 1.13]; lag 2 

0.94 [0.81, 1.09]; lag 3 

0.93 [0.66, 1.32] 7-day mean 

Summer: 0.93 [0.78, 1.10] lag 0 

0.81 [0.67, 0.98] lag 1 

0.91 [0.77, 1.09] lag 2 

0.97 [0.83, 1.13] lag 3 

1.04 [0.57, 1.90] 7-day mean 

Wheeze: 

Winter: 0.98 [0.83, 1.16] lag 0 

0.90 [0.75, 1.05] lag 1 

1.00 [0.83, 1.20] lag 2 

1.13 [0.95, 1.35] lag 3 

1.02 [0.68, 1.57]; 7-day mean 

Summer: 1.02 [0.88, 1.19] lag 0 

0.98 [0.84, 1.16] lag 1 

0.87 [0.74, 1.02] lag 2 

0.85 [0.72, 0.99] lag 3 

0.96 [0.51, 1.81] 7-day mean

Reference: Ward et al. (2002, 025839) 

Period of Study: 1997 (two 8-wk 

periods) 

Location: Birmingham and Sandwell, 

UK 

Outcome: Change in PEF (peak 

expiratory flow), self reported 

respiratory symptoms (same day 

cough, illness, short of breath, waking 

up at night with cough or wheeze, 

wheeze) 

Age Groups: 9 yr olds 

Study Design: 

Time-series panel study 

N: 162 children from 5 schools 

Statistical Analyses: Linear regression 

(PEF), 

Logistic regression (respiratory 

symptoms) 

Covariates: Trend, temperature, 

schooldays (yes/no) 

Season: Winter (Jan 13-Mar 10) 

Summer (May 19- Jul 14) 

Dose-response Investigated? No 

Statistical Package: Nr 

Lags Considered: Lag 0, lag 1, lag 2, 

lag 3, 7-day ma 

Pollutant: Sulfate 

Averaging Time: 24 h 

Mean (SD): 

Winter: 2.4 μg/m3

Summer: 3.8 μg/m3

Range (Min, Max): 

Winter: 0.8, 14.9 

Summer: 1.1, 7.8 

PM Component: 

SO4

Monitoring Stations: 2 stations 

PM Increment: 

Winter: 4.8 μg/m3 

Summer: 3.1 μg/m3

Mean (PEF l/min) [Lower CI, Upper CI]

lag 

Winter morning: 

-1.75 [-4.00, 0.50] lag 0 

-0.91 [-3.44, 1.62] lag 1 

-0.62 [-3.16, 1.91] lag 2 

-1.82 [-4.27, 0.64] lag 3 

-3.22 [-8.03, 1.58] 7-day mean 

Winter afternoon: 

0.99 [-1.58, 3.55] lag 0 

0.79 [-2.42, 4.00] lag 1 

-1.89 [-4.99, 1.21] lag 2 

-1.73 [-4.69, 1.23] lag 3 

-1.96 [-13.35, 9.42] 7-day mean 

Summer morning: 

-0.72 [-3.27, 1.82] lag 0 

-1.69 [-4.28, 0.90] lag 1 

1.35 [-1.27, 3.97] lag 2 

3.38 [1.03, 5.72] lag 3 

2.98 [-4.17, 10.13] 7-day mean 

Summer afternoon: 

-0.32 [-2.81, 2.17] lag 0 

0.84 [-1.63, 3.30] lag 1 

-0.08 [-2.61, 2.44] lag 2 

 -0.25 [-2.69, 2.19]lag 3 

-2.20 [-9.51, 5.12] 7-day mean 

Winter morning in atopy/recent 

wheezing subgroup: 

0.200 [-0.755, 1.156] lag 0 

-0.219 [-1.318, 0.881] lag 1 

-0.431 [-1.526, 0.664]; lag 2 

1.200 [0.095, 2.305] lag 3 

December 2009 E-226 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Winter morning in no atopy or recent 

wheezing subgroup: 

-0.613 [-1.714, 0.488] lag 0 

-0.174 [-1.423, 1.075] lag 1 

0.006 [-1.243, 1.253] lag 2 

-1.080 [-2.308, 0.148] lag 3 

Winter morning in subgroup with 

parental atopy/recent wheezing: 

0.457 [0.003 , 0.910] lag 0 

0.078 [-0.503, 0.660] lag 1 

-0.102 [-0.656, 0.452] lag 2 

0.002 [-0.609, 0.613] lag 3 

Winter morning in subgroup without 

parental atopy/recent wheezing: 

-0.622 [-1.379, 0.136] lag 0 

-0.272 [-1.147, 0.602] lag 1 

-0.138 [-1.005, 0.728] lag 2 

-0.496 [-1.359, 0.367] lag 3 

RR Estimate [Lower CI, Upper CI] 

lag: 

Cough: 

Winter: 1.01 [0.84, 1.20] lag 0 

1.02 [0.85, 1.24] lag 1 

0.99 [0.82, 1.20] lag 2 

0.86 [0.71, 1.05] lag 3 

0.78 [0.53, 1.14] 7-day mean 

Summer: 1.08 [0.98, 1.20] lag 0 

1.03 [0.93, 1.15] lag 1 

0.97 [0.88, 1.07] lag 2 

0.90 [0.82, 0.99] lag 3 

0.73 [0.54, 0.97] 7 day mean 

Illness: 

Winter: 1.06 [0.96, 1.17] lag 0 

1.15 [1.03, 1.28] lag 1 

1.14 [1.00, 1.28] lag 2 

1.04 [0.92, 1.18] lag 3 

1.30 [1.00, 1.66] 7-day mean 

Summer: 0.98 [0.86, 1.11] lag 0 

0.97 [0.84, 1.12] lag 1 

1.01 [0.88, 1.16] lag 2 

0.95 [0.84, 1.09] lag 3 

0.72 [0.46, 1.12] 7-day mean 

Shortness of breath: 

Winter: 0.96 [0.85, 1.07] lag 0 

0.98 [0.86, 1.12] lag 1 

0.94 [0.82, 1.07] lag2 

0.93 [0.81, 1.08] lag 3 

0.80 [0.59, 1.07] 7-day mean 

Summer: 0.95 [0.80, 1.14] lag 0 

1.07 [0.89, 1.28] lag 1 

1.04 [0.87, 1.24] lag 2 

0.94 [0.80, 1.12] lag 3 

|0.58 [0.33, 1.04] 7-day mean 

Wake at night with cough/wheeze: 

Winter: 0.97 [0.87, 1.08] lag 0 

1.01 [0.89, 1.15] lag 1 

1.00 [0.88, 1.14]; lag 2 

0.93 [0.82, 1.07]; lag 3 

0.79 [0.59, 1.05] 7-day mean 

Summer: 0.95 [0.78, 1.16] lag 0 

0.81 [0.67, 0.99] lag 1 

0.93 [0.76, 1.13] lag 2 

0.87 [0.72, 1.05] lag 3 

0.77 [0.41, 1.48] 7-day mean 

Wheeze: 

Winter: 1.00 [0.87, 1.15] lag 0 

0.96 [0.82, 1.13] lag 1 

0.88 [0.75, 1.04] lag 2 

1.12 [0.95, 1.32] lag 3 

December 2009 E-227 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0.83 [0.58, 1.20]; 7-day mean 

Summer: 0.97 [0.80, 1.17] lag 0 

.09 [0.89, 1.32] lag 1 

1.00 [0.82, 1.22] lag 2 

0.81 [0.69, 0.97] lag 3 

1.30 [0.68, 2.50] 7-day mean 

Reference: Ward et al. (2002, 025839) 

Period of Study: 1997 (two 8-week 

periods) 

Location: Birmingham and Sandwell, 

UK 

Outcome: Change in PEF (peak 

expiratory flow), self reported 

respiratory symptoms (same day 

cough, illness, short of breath, waking 

up at night with cough or wheeze, 

wheeze) 

Age Groups: 9 yr olds 

Study Design: Time-series panel study 

N: 162 children from 5 schools 

Statistical Analyses: Linear regression 

(PEF), 

Logistic regression (respiratory 

symptoms) 

Covariates: Trend, temperature, 

schooldays (yes/no) 

Season: Winter (Jan 13-Mar 10) 

Summer (May 19- Jul 14) 

Dose-response Investigated? No 

Statistical Package: Nr 

Lags Considered: Lag 0, lag 1, lag 2, 

lag 3, 7-day ma 

Pollutant: NO3

Averaging Time: 24 h 

Mean (SD): 

Winter: 3.6 μg/m3

Summer: 3.5 μg/m3

Range (Min, Max): 

Winter: 0.1, 29.9 

Summer: 0.7, 13.2 

Monitoring Stations: 2 stations 

PM Increment: Winter: 6.7 μg/m3

Summer: 3.7 μg/m3

Mean (PEF l/min) [Lower CI, Upper CI] 

lag: 

Winter morning: 

-2.08 [-4.02 to -0.15] lag0 

-0.64 [-2.87, 1.59] lag 1 

0.71 [-1.69, 3.11] lag 2 

-1.38 [-3.61, 0.84] lag 3 

-0.92 [-5.32, 3.47] 7-day mean 

Winter afternoon: 

0.24 [-1.89, 2.38] lag0 

-0.72 [-3.87, 2.43] lag 1 

-1.37 [-5.11, 2.38] lag 2 

-2.54 [-5.74, 0.66] lag 3 

0.21 [-7.67, 8.11] 7-day mean 

Summer morning: 

-0.80 [-2.74, 1.15] lag 0 

0.68 [-1.31, 2.67] lag1 

1.42 [-0.73, 3.58] lag2 

2.54 [0.48, 4.59] lag3 

1.74 [-2.66, 6.13] 7-day mean 

Summer afternoon: 

-0.72 [-2.47, 1.03] lag 0 

-0.59 [-2.36, 1.18] lag 1 

-0.33 [-2.11, 1.45] lag 2 

0.66 [-1.26, 2.58] lag 3 

0.47 [-3.36, 4.29] 7-day mean 

Winter morning in atopy/recent 

wheezing subgroup: 

-0.036 [-0.627 , 0.555] lag 0 

0.142 [-0.573 , 0.857] lag 1 

0.000 [-0.760, 0.759] lag 2 

0.689 [-0.061, 1.439] lag 3 

Winter morning in no atopy or recent 

wheezing subgroup: 

-0.434 [-1.116, 0.248] lag 0 

-0.201 [-1.002 , 0.600] lag 1 

0.154 [-0.703 , 1.010] lag 2 

-0.605 [-1.422 , 0.210] lag 3 

Winter morning in subgroup with 

parental atopy/recent wheezing: 

0.228 [-0.054, 0.511] lag 0 

0.476 [0.060, 0.892] lag 1 

0.196 [-0.202, 0.594] lag 2 

0.083 [-0.321, 0.487] lag 3 

Winter morning in subgroup without 

parental atopy/recent wheezing: 

-0.482 [-0.952, -0.012] lag 0 

-0.276 [-0.846, 0.294] lag 1 

0.078 [-0.520, 0.675] lag 2 

-0.298 [-0.864, 0.268] lag 3 

RR Estimate [Lower CI, Upper CI] 

lag: 

Cough: Winter: 

0.92 [0.80, 1.07] lag 0 

0.91 [0.77, 1.07] lag 1 

0.99 [0.83, 1.17] lag 2 

0.87 [0.73, 1.03] lag 3 

0.71 [0.52, 0.97] 7-day mean 

Summer: 1.05 [0.97, 1.13] lag 0 

December 2009 E-228 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1.01 [0.93, 1.10] lag 1 

0.95 [0.88, 1.03] lag 2 

0.89 [0.83, 0.96] lag 3 

0.81 [0.68, 0.97] 7 day mean 

Illness: Winter: 1.05 [0.97, 1.14] lag 0

1.11 [1.01, 1.22] lag 1 

1.13 [1.01, 1.26] lag 2 

1.13 [1.04, 1.26] lag 3 

1.13 [0.92, 1.38] 7-day mean 

Summer: 0.97 [0.87, 1.09] lag 0 

0.98 [0.87, 1.10] lag 1 

0.95 [0.85, 1.06] lag 2 

0.94 [0.85, 1.05] lag 3 

0.74 [0.54, 1.03] 7-day mean 

Shortness of breath: Winter: 

0.99 [0.90, 1.10] lag 0 

1.01 [0.90, 1.13] lag 1 

0.93 [0.82, 1.05] lag2 

0.98 [0.86, 1.13] lag 3 

0.85 [0.67, 1.08] 7-day mean 

Summer: 1.04 [0.90, 1.18] lag 0 

1.12 [0.98, 1.28] lag 1 

1.04 [0.90, 1.20] lag 2 

0.90 [0.79, 1.03] lag 3 

1.06 [0.78, 1.43] 7-day mean 

Wake at night with cough/wheeze: 

Winter: 

0.98 [0.89, 1.08] lag 0 

1.05 [0.94, 1.16] lag 1 

0.99 [0.88, 1.12]; lag 2 

0.99 [0.87, 1.12]; lag 3 

0.84 [0.67, 1.05] 7-day mean 

Summer: 0.94 [0.80, 1.09] lag 0 

0.86 [0.72, 1.01] lag 1 

0.94 [0.79, 1.11] lag 2 

0.92 [0.79, 1.07] lag 3 

0.95 [0.62, 1.47] 7-day mean 

Wheeze: Winter: 0.98 [0.87, 1.10] lag 0

1.00 [0.87, 1.14] lag 1 

0.89 [0.77, 1.03] lag 2 

1.11 [0.95, 1.30] lag 3 

0.80 [0.61, 1.07] 7-day mean 

Summer: 1.01 [0.87, 1.17] lag 0 

0.96 [0.83, 1.11] lag 1 

0.95 [0.82, 1.10] lag 2 

0.87 [0.75, 1.01] lag 3 

1.04 [0.67, 1.60] 7-day mean 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-229 
E.2.2. Respiratory Emergency Department Visits and Hospital Admissions 

Table E-12. Short-term exposure-respiratory-ED/HA-PM10. 

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Andersen et al. (2008, 

189651) 

1st page: 458 

Period of Study: May 2001- Dec 2004 

Location: Copenhagen, Denmark 

Hospital Admissions/ED visits 

Outcome (ICD-10): 

RD, including chronic bronchitis 

(J41-42), emphysema (J43), other 

chronic obstructive pulmonary disease 

(J44), asthma (J45), and status 

asthmaticus (J46). 

Pediatric hospital admissions for 

asthma (J45) and status asthmaticus 

(J46). 

Age Groups Analyzed: >65 yr (RD 

combined), 5-18 yr (asthma) 

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAM 

Covariates: temperature, dew-point 

temperature, long-term trend, 

seasonality, influenza, day of the week, 

public holidays, school holidays (only 

for 5-18 yr olds), pollen (only for 

pediatric asthma outcome) 

Season: NR 

Dose-response Investigated: No 

Statistical package: R statistical 

software (gam procedure, mgcv 

package) 

Lags Considered: Lag 0 -5 days, 

5-day avg (lag 0-4) for RD, and a 6-day 

avg (lag 0-5) for asthma. 

Pollutant: PM10 (μg/m3) 

Averaging Time: 24 h 

Mean (SD): 24(14) 

Median: 21

IQR: 16-29

99th percentile: 72 

Monitoring Stations: 1 

Copollutant (correlation): 

NCtot: r = 0.39 

NC100: r = 0.28 

NCa12: r = 0.02 

Nca23: r = -0.12 

NCa57: r = 0.45 

Nca212: r = 0.63 

PM2.5: r = 0.80 

CO: r = 0.37 

NO2: r = 0.35 

: r = 0.32 

 curbside: r = 0.18 

O3: r = -0.21 

Other variables: 

Temperature: r = 0.12 

Relative humidity: r = 0.05 

PM Increment: 13 μg/m3 3 (IQR) 

Relative risk (RR) Estimate [CI]: 

RD hospital admissions (5 day avg, 

lag 0 -4), age 65+: One-pollutant 

model: 1.06 [1.02-1.09] 

Adj for NCtot: 1.05 [1.01-1.10] 

Adj for NCa212: 1.04 [0.98-1.11] 

Asthma hospital admissions (6-day 

avg lag 0-5), age 5 - 18: One-pollutant 

model: 1.02 [0.93-1.12] 

Adj for NCtot: 1.01 [0.91-1.12] 

Adj for NCa212: 0.94 [0.81-1.09] 

Estimates for individual day lags 

reported only in Fig form (see notes): 

Notes: Fig 2: Relative risks and 95% 

confidence intervals per IQR in single 

day concentration (0-5 day lag). 

Summary of Fig 2: RD: Positive, 

statistically or marginally significant 

associations at Lag 2-5. Asthma: Wide 

confidence intervals make interpretation 

difficult. Positive associations at Lag 1, 

2, 3, and 5. 

Reference: Cheng et al. (2007, 

093034)

Period of Study: 1996-2004

Location: Kaohsiung, Taiwan 

Outcome (ICD-9: 480-486): 

Pneumonia 

Age Groups: NR

Study Design: Case-crossover 

N: 82,587 pneumonia hospital 

admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature and humidity 

on the same day 

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: Cumulative lag 

period up to 2 previous days 

Pollutant: PM10

Averaging Time: 24 h

Mean (min-max): 

77.01 (16.7-232) 

Percentiles: 25%: 42.12 

50%: 75.27 

75%: 104.65 

Monitoring Stations: 6

Copollutant: NR 

PM Increment: 62.53 μg/m3 (IQR) 

OR Estimate [CI]: Single Pollutant 

Model: Temp>25oC: 1.21 [1.15,1.28] 

Temp < 25oC: 1.57 [1.50,1.65] 

Two-Pollutant Model: Temp>25oC 

Adj. for SO2: 1.21 [1.14,1.28] 

Adj. for NO2: 1.15 [1.07,1.24] 

Adj. for CO: 1.10 [1.03,1.17] 

Adj. for O3: 0.96 [0.89,1.03] 

Temp < 25oC 

Adj. for SO2: 1.56 [1.48,1.65] 

Adj. for NO2: 1.09 [1.02,1.16] 

Adj. for CO: 1.30 [1.22,1.39] 

Adj. for O3: 1.56 [1.48,1.65]

December 2009 E-230 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chimonas and Gessner 

(2007, 093261)

Period of Study: Jan 1999-Jun 2003

Location: Anchorage, Alaska

Outcome (ICD-9): Asthma (493.0-

493.9); Lower respiratory illness-LRI 

(466.1, 466.0, 480-487, 490, 510-511); 

Inhaled quick-relief medication; Steroid 

medication 

Age Groups: <20 yr old 

Study Design: Time series 

N: 42,667 admissions 

Statistical Analyses: GEE for 

multivariable modeling 

Covariates: Season, serial correlation, 

yr, weekend, temperature, precipitation, 

and wind speed 

Season: NR 

Dose-response Investigated? No 

Statistical Package: SPSS (dataset), 

SAS (analysis) 

Lags Considered: 1 day and 1 week

Pollutant: PM10

Averaging Time: 24 h and 1 wk 

Mean (min-max): 

Daily: 27.6 (2-421) 

Weekly: 25.3 (5.0-116.0) 

Monitoring Stations: NR

Copollutant: Daily PM2.5

ρ = 0.25 (p < 0.01) 

Weekly PM2.5

ρ = 0.08 (p = 0.21) 

PM Increment: 10 μg/m3

RR Estimate [CI]: 

Same Day 

Outpatient Asthma: 1.006 [1.001,1.013] 

Outpatient LRI: 1.001 [0.987,1.015] 

Inpatient Asthma: 1.003 [0.922,1.091] 

Inpatient LRI: 1.015 [0.978,1.053] 

Inhaled Steroid Prescriptions: 

1.006 [0.996,1.011] 

Quick-relief Medication: 

1.018 [1.006,1.030] 

Weekly (median increase) 

Outpatient Asthma: 1.021 [1.004,1.038] 

Outpatient LRI: 1.013 [0.978,1.049] 

Inpatient Asthma: 1.023 [0.948,1.104] 

Inpatient LRI: 1.025 [0.981,1.072] 

Inhaled Steroid Prescriptions: 

0.989 [0.969,1.010] 

Quick-relief Medication: 

1.057 [1.037,1.077] 

Reference: Chiu et al. (2008, 191989) 

Period of Study: 1996-2001 

Location: Taipei, Taiwan 

Outcome: Hospital admissions for 

COPD 

Study Design: Time-series 

Covariates: Temperature, humidity, 

PM10 and O3

Statistical Analysis: Poisson 

regression 

Statistical Package: SAS 

Age Groups: All 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD) Unit: 

Index Days: 111.68 ± 38.32 μg/m3

Comparison Days: 55.43 ± 24.66 μg/m3

Range (Min, Max): NR 

Copollutant (correlation): NR 

All results refer to “dust storm days” and 

can be found in Table 3 

Reference: Chiu et al. (2009, 190249) 

Period of Study: 1996-2004 

Location: Taipei, Taiwan 

Outcome: Hospital admissions for 

pneumonia (ICD-9 480-486) 

Study Design: Time-series 

Covariates: Weather variables, day of 

the week, seasonality, long-term time 

trends 

Statistical Analysis: Conditional 

logistic regression 

Statistical Package: SAS 

Age Groups: All 

Pollutant: PM10

Averaging Time: 24 h 

Mean Unit: 49.47 μg/m3

Range (Min, Max): 14.42, 234.91 

Copollutant (correlation): 

SO2: 0.50 

NO2: 0.58 

CO: 0.34 

O3: 0.31 

Increment: IQR 

Odds Ratio (95% CI) 

Temperature ≥ 23o C: 1.11 (1.08-1.14) 

Temperature < 23o C: 1.09 (1.07-1.11) 

Adjusted for SO2

Temperature ≥ 23o C: 1.10 (1.08-1.13) 

Temperature < 23o C: 1.19 (1.17-1.22) 

Adjusted for NO2

Temperature ≥ 23o C: 0.90 (0.88-0.93) 

Temperature < 23o C: 1.09 (1.07-1.12) 

Adjusted for CO 

Temperature ≥ 23o C: 1.03 (1.00-1.05) 

Temperature < 23o C: 1.07 (1.05-1.10) 

Adjusted for O3

Temperature ≥ 23o C: 1.05 (1.03-1.08) 

Temperature < 23o C: 1.09 (1.07-1.11) 

December 2009 E-231 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Erbas et al. (2005, 073849) 

Period of Study: Jan 2000-Dec 2001 

Location: Melbourne, Australia 

Hospital Admissions 

Outcome (ICD-10): Asthma (J45, J46) 

Age Groups: 1-15 yr 

Study Design: Time series 

N: 8955 asthma cases 

Statistical Analyses: GAM, GEE (if 

autocorrelation was present in 

residuals) 

Covariates: Temp and humidity 

Season: NR 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2 days 

Pollutant: PM10

Averaging Time: 1 h 

Mean (SD): 

Western: 2.99 (2.11) 

10th percentile: 13.67 

90th percentile: 48.00 

Inner Melbourne: 4.54 (2.65) 

10th percentile: 15.63 

90th percentile: 59.73 

South/Southeastern: 1.13 (1.18) 

10th percentile: 12.00 

90th percentile: 36.05 

Eastern: 3.61 (2.39) 

10th percentile: 16.00 

90th percentile: 51.05

Combined: 30.07 (10.55-112.33) 

SD = 15.27 

10th percentile: 16.00 

90th percentile: 50.51 

Monitoring Stations: Data obtained 

from an air quality simulation model 

(TAPM) by CSIRO Atmospheric 

Research 

Copollutant: NR 

PM Increment: Increase from 10th to 

90th percentile 

RR Estimate [CI]: 

Same day lag 

Western: NR 

Inner Melbourne: 1.17 [1.05,1.31] 

South/Southeastern: 1.14 [0.95,1.33] 

Eastern: 1.09 [1.01,1.18] 

Notes: All other lags NR 

Reference: Farhat et al. (2005, 

089461)

Period of Study: Aug 1996-Aug 1997 

Location: São Paulo, Brazil 

Hospital Admissions and Emergency 

Room Visits 

Outcome (ICD-9): Lower respiratory 

tract diseases (466, 480-519) including 

pneumonia or bronchopneumonia (480-

486), asthma (493), bronchiolitis (466) 

Age Groups: <13 yr 

Study Design: Time series 

N: 43,635 

Statistical Analyses: GAM, Poisson 

regression, Pearson correlation 

Covariates: Time, temperature, 

humidity, weekday 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0-7 days

Pollutant: PM10

Averaging Time: 24 h

Mean (min-max): 

62.6 (25.5-186.3) 

SD = 26.6 

IQr = 30 

N = 396 

Monitoring Stations: 13 

Copollutant (correlation): SO2: 

r = 0.69 

NO2: r = 0.83 

O3: r = 0.35 

CO: r = 0.72 

(all p < 0.05) 

Additional correlations: 

Rel humidity: r = -0.55 

Min temp: r = -0.44 

(both p < 0.05) 

PM Increment: 30 μg/m3 (IQR) 

RR Estimate [CI]: 

Lower respiratory tract disease 

5-day ma 

Copollutant model: 

NO2: 2.1 [-7.1,11.3] 

SO2: 16.5 [10.5,22.6] 

O3: 10.1 [5.0,15.2] 

CO: 14.1 [8.1,20.2] 

Multipollutant model: 5.2 [-4.6,15.1] 

Pneumonia or bronchopneumonia 

6-day ma 

Copollutant model: 

NO2: 14.8 [-3.8,33.4] 

SO2: 14.8 [-0.3,30.0]; O3: 16.2 [1.0,31.3]

CO: 17.6 [0.4,34.8] 

Multipollutant model: 5.23 [-16.2,26.6] 

Asthma or bronchiolitis 

2-day ma 

Copollutant model: 

NO2: -11.04 [-50.0,28.0] 

SO2: 15.8 [-7.8,39.3] 

O3: 11.7 [-10.4, 33.9] 

CO: 12.4 [-14.8,39.7] 

Multipollutant model: -15.5 [-61.2,30.2] 

December 2009 E-232 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Fung et al. (2006, 089789) 

Period of Study: June 1995-Mar 99 

Location: Vancouver, Canada

Hospital Admission/ED 

Outcome: Respiratory diseases (460-

519) 

Age Groups: Age >65 

Study Design: Time series

N: 26,275 individuals admitted 

Statistical Analyses: Poisson 

regression (spline 12 knots), casecrossover (controls +/7 days from case 

date), Dewanji and Moolgavkar (DM) 

method 

Covariates: Long-term trends, day-ofthe-week effect, weather

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SPlus, R 

Lags Considered: 0-7 days 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 13.31(6.13) μg/m3

Range (Min, Max): (3.77, 52.17) 

Monitoring Stations: NR 

Copollutant (correlation): PM10: 

PM2.5 r = 0.80 

PM10-2.5 r = -0.11 

CO r = 0.46 

Coh r = 0.61 

O3 r = -0.08 

NO2 r = 0.54 

SO2 r = 0.61 

PM Increment: : 7.9 μg/m3

Rr Estimate (65+ Yr) 

Dm Method: 

1.014[0.998,1.029] 

Lag 0 

1.016[0.998,1.034] 

3-day avg 

0.988[0.970, 1.006] 

5-day avg 

0.983[0.963, 1.004] 

7-day avg Time Series: 

1.016[0.999, 1.033] 

Lag 0 

1.015[0.996, 1.035] 

3-day avg 

1.009[0.987, 1.032] 

5-day avg 

1.009[0.983, 1.036] 

7-day avg 

Case-Crossover: 

1.017[0.998, 1.036] 

Lag 0 

1.015[0.993, 1.037] 

3-day avg 1.008[0.984, 1.033] 

5-day avg 

1.003[0.976, 1.031] 

7-day avg 

Reference: Fung al. (2005, 093262) 

Period of Study: Nov 1995-Dec 2000 

Location: London, Ontario 

Hospital Admissions 

Outcome (ICD-9): Asthma (493) and all 

other respiratory diseases (460-519) 

Age Groups: <65 yr 

65+ yr 

Study Design: Time series 

N: 5574 respiratory admissions 

Statistical Analyses: GAM with locally 

weighted regression smoothers 

(LOESS) 

Covariates: Maximum and minimum 

temp, humidity, day of the week, 

seasonal cycles, secular trends 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: Current to 3-day 

mean

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

38.0 (5-248) 

SD = 23.5 

Monitoring Stations: 4 

Copollutant (correlation): 

NO2: r = 0.30 

SO2: r = 0.24 

CO: r = 0.21 

O3: r = 0.53 

COH: r = 0.29 

PM Increment: 26 μg/m3

% Change in Daily Admission [CI]: 

Age <65 

Current day mean: -0.9 [-6.8,5.4] 

2-day mean: -1.3 [-8.5,6.6] 

3-day mean: 1.9 [-6.5,11] 

Age 65+ 

Current day mean: 3.3 [-1.7,8.6] 

2-day mean: 5 [-1.5,11.9] 

3-day mean: 1.2 [-6.1,9.1]

December 2009 E-233 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Galán et al. (2003, 087408) 

Period of Study: 1995-1998 

Location: Madrid, Spain 

Hospital Admissions 

Outcome (ICD): Asthma (493) 

Age Groups: All ages 

Study Design: Time series 

N: 555,153 at-risk 

Statistical Analyses: GAM, 

autoregressive Poisson regression 

Covariates: Temperature, relative 

humidity, pollen, yr, day of the week, 

public holiday 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0, 1, 2, 3, and 4 day

s

Pollutant: PM10

Averaging Time: 24 h

Mean (min-max): 

32.1 (11.2-108.6) 

SD = 12.1 

Monitoring Stations: 13 

Copollutant (correlation): 

SO2: r = 0.581 

NO2: r = 0.717 

O3: r = -0.188 

Other variables: 

O.europaea: r = -0.066 

Plantago sp.: r = -0.202 

Poaceae: r = -0.132 

Urticaceae: r = -0.104 

Temp: r = -0.122 

Humidity: r = 0.119 

PM Increment: 10 μg/m3

RR Estimate [CI]: 

Single-pollutant 

Current-day lag: 1.011 (0.980-1.042) 

1-day lag: 1.006 (0.976-1.037) 

2-day lag: 1.008 (0.978-1.038) 

3-day lag: 1.039 (1.010-1.068) 

4-day lag: 1.027 (0.999-1.056) 

Adjustment for pollen (PM10 3-day lag) 

O. europaea: 1.041 (1.011-1.071) 

Plantago sp.: 1.046 (1.017-1.076) 

Poaceae: 1.043 (1.015-1.073) 

Urticaceae: 1.038 (1.009-1.068) 

All four: 1.045 (1.016-1.074)

Reference: Hajat et al. (2002, 030358) 

Period of Study: Jan 1992-Dec 1994 

Location: London, England

Family Practice consultations 

Outcome: Upper Resp Disease 

(excluding allergic rhinitis) (460-3), 

(465), (470-5), (478) 

Age Groups: 0-14, 

15-64, >65 yr 

Study Design: Time series

N: 268,718-295,740 registered patients 

Statistical Analyses: Poisson 

regression, GAM, LOESS smoothers, 

default convergence criteria 

Covariates: Long term trends, pollen 

counts, flu, meteorological variables 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SPLUS 

Lags Considered: 2-3

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 28.5 (13.7) μg/m3

Percentiles: 10th: 15.8 

90th: 46.5 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: All Year: 18 

Warm Season: 15 

Cold Season: 20 

% Change, Single Pollutant Models: 

All Year: Ages 

0-14: 2.0[-0.2, 4.2] Lag 3 

Ages 15-64: 5.7[2.9, 8.6] 

Lag 2 

Ages >65: 10.2[5.3, 15.3] Lag 2 

Warm Season: Ages 0-14: 1.1[-2.4, 4.8] 

Lag 3 

Ages 15-64: 6.0[2.7, 9.4] 

Lag 2 

Ages >65: 0.1[-7.7, 8.5] Lag 2 

Cold Season: Ages 0-14: 2.7[-0.1, 5.5] 

Lag 3 

Ages 15-64: 3.6[1.0, 6.4] 

Lag 2 

Ages >65: 18.9[11.7, 26.7] Lag 2 

% Change, 2 Pollutant Models: 

0-14 Yr 

PM10 w/ NO2: 3.8[1.6, 6.1] 

PM10 w/ O3: 1.8[-0.4, 3.9] 

PM10 w/ SO2: 2.0[-0.6, 4.6] 

15-65 Yr 

PM10 w/ NO2: 2.8[0.7, 4.9] 

PM10 w/ O3: 4.8[2.6, 7.0] 

PM10 w/ SO2: 4.8[2.2, 7.5] 

>65 Yr 

PM10 w/ NO2: 4.6[0.5, 8.8] 

PM10 w/ O3: 10.7[5.7, 16.0] 

PM10 w/ SO2: 10.6[4.5, 17.1] 

December 2009 E-234 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hanigan et al. (2008, 

156518) 

Period of Study: 1996-2005 (Apr-Nov 

of each yr) 

Location: Darwin, Australia 

Outcome: Cardiorespiratory Disease 

HA (ICD 9: 390-519 

ICD 10: I00-99 & J00-99) 

Age Groups: NR

Study Design: Time series 

N: 8279 events 

Statistical Analyses: Poisson 

regression 

Covariates: Indigenous status, 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: Lags 0-3 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 21.2 (8.2)

Range: 55.2 

Monitoring Stations: 2 (monitored & 

modeled) 

Copollutant: NR 

Co-pollutant Correlation 

N/A 

PM Increment: 10 μg/m3

Percent Change (Lower CI, Upper CI), 

lag: 

Total Respiratory: 4.81 (-1.04, 11.01), 

lag 0 

Total Resp., Indigenous: 9.40 (1.04, 

18.46), lag 0 

Total Resp., Non-Indigenous: 3.14 (-

2.99, 9.66), lag 

Resp. Infection, Indigenous: 15.02 

(3.73, 27.54), lag 3 

Resp. Infection, Non-Indigenous: 0.67 (-

7.55, 9.61), lag 3 

Asthma Indigenous: 16.27 (3.55, 

40.17), lag 1 

Asthma Non-Indigenous: 8.54 (-5.60, 

24.80), lag 1 

*Fig 3. percent change in hospital 

admissions per 10 μg/m3

 increase in 

PM10

Reference: Hanigan et al. (2008, 

156518) 

Period of Study: 1996-2005 (Apr-Nov 

of each yr) 

Location: Darwin, Australia 

Hospital Admissions/ED visits 

Outcome (ICD-9 or ICD-10): 

Daily emergency hospital admissions 

for total respiratory (ICD-9: 460-519 

ICD-10: J00-J99), asthma (ICD-9: 493 

ICD-10: J45-J47), COPD (ICD-9: 

490-492, 494-496 

ICD-10: J40-J44, J47, J67), and 

respiratory infections (ICD-9: 461-466, 

480-487, 514 

ICD-10: J00-J22). 

Age Groups Analyzed: All 

Study Design: Time series 

N: 8,279 hospital admissions 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Indigenous status, time in 

days, temperature, relative humidity, 

day of the week, influenza epidemics, 

change between ICD editions, holidays, 

yrly population 

Season: Apr-Nov (corresponding to the 

dry season) 

Dose-response Investigated? No 

Statistical package: R version 2.3.1 

Lags Considered: Lag 0 -3 

Pollutant: PM10 

Averaging Time: 24 h 

Mean (SD range): 21.2 (8.2- 55.2) 

Monitoring Stations: N/A (see notes) 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3 

Percent change [95% CI]: 

Overall respiratory disease: 

Lag 0: 4.81 [-1.04, 11.01] 

Lag 0 (indigenous people): 

9.40 [1.04, 18.46] 

Lag 0 (non-indigenous people): 

3.14 [-2.99, 9.66] 

In unstratified analyses, the subgroups 

of respiratory infections, asthma, and 

COPD all had positive associations with 

PM10 Lag 0. 

Asthma: 

Lag 1 (indigenous people): 

16.27 [-3.55, 40.17] 

Lag 1 (non-indigenous people): 

8.54 

[-5.60, 24.80] 

Respiratory infections: 

Lag 3 (indigenous people): 

15.02 [3.73, 27.54] 

Lag 3 (non-indigenous people): 

0.67 [-7.55, 9.61] 

Notes: 

Fig 3: Associations between 

hospitalizations for non-indigenous and 

indigenous people with estimated 

ambient PM10. 

Summary of Fig 3: Confidence 

intervals were wide, but indigenous 

people generally had stronger 

associations with PM10 than nonindigenous people. Daily PM10 exposure 

levels were estimated for the population 

of the city from visibility data using a 

previously validated models.

December 2009 E-235 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hapcioglu et al. (2006, 

093263) 

Period of Study: Jan 1997-Dec 2001 

Location: Istanbul, Turkey 

Hospital Admissions 

Outcome (ICD-9): COPD (ICD: NR) 

Age Groups: NR 

Study Design: Time series

N: 1586 patients 

Statistical Analyses: Multiple stepwise 

regression, Pearson correlation 

Covariates: Humidity, temperature, and 

pressure 

Season: Summer, fall, winter, spring 

Dose-response Investigated? No 

Statistical Package: SPSS 

Lags Considered: NR

Pollutant: PM10

Averaging Time: 1 mo 

Mean (SD): NR

Monitoring Stations: 1 

Copollutant: NR 

Correlation with COPD: 

r = 0.28 

p = 0.03 

Adj for temp: r = 0.16 

p = 0.23 

PM Increment: NR 

Notes: RRs only provided for season, 

not PM 

Reference: Hwang and Chan (2002, 

023222) 

Period of Study: 1998 

Location: Taiwan

Clinic visits 

Outcome: LRI 

466, 480-486 (acute bronchitis, acute 

bronchiolitis, pneumonia) 

Age Groups: 0-14 yr, 15-64, 65+ yr 

Study Design: Cluster analysis of small 

study areas

N: 50 communities 

Statistical Analyses: GLM to model 

temporal patterns, hierarchical model to 

obtain estimates across 50 communities 

Covariates: Day of week, temperature, 

dew point, summer/Winter

Season: All 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: 0-2

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 58.9 μg/m3 (14.0) 

Range (Min, Max): 33.3, 83.1 μg/m3

PM Component: 

Monitoring Stations: 59 

Notes: Number Of stations estimated 

from fig. 

Copollutant: NR 

PM Increment: 

10% Increase In PM10 (5.9 μg/m3) 

Percent Change: 

0-14 

0.5% (-0.1, 0.8] Lag0 

[-0.3, 0.3] Lag1 

0.3 [0.0, 0.6] Lag2 

15-64 

0.6 [0.2, 0.9] Lag0 

0.2 [-0.1, 0.5] Lag1 

0.3 [0.0, 0.6] Lag2 

65+ 

0.8 [0.4, 1.1] Lag0 

0.3 [-0.1, 0.6] Lag1 

0.5 [0.1, 0.8] Lag2 

All Ages 

0.5 [0.2, N0.8] Lag0 

[-0.3, 0.3] Lag1 

0.3 [0.0, 0.6] Lag2 

Reference: Jaffe et al. (2003, 041957)

Period of Study: July 1991-June 

1996 

Location: Cincinnati, Cleveland, 

Columbus, Ohio

ED visits 

Outcome (ICD10): Asthma (493) 

Age Groups: Age 5-34 yr 

Study Design: Time-series

N: 4,416 recipients 

Statistical Analyses: Poisson 

regression, GAM 

Covariates: City, day of week, wk, yr, 

minimum temperature, dispersion 

parameter 

Season: Jun-Aug only 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: 0-3 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Cincinnati: 43.0(16.4) 

Cleveland: 60.8(28.4) 

Columbus: 37.4(16.3) 

Range (Min, Max): 

Cincinnati: (16,90) 

Cleveland: (12,183) 

Columbus: (7,87) 

Monitoring Stations: 3 

Copollutant (correlation): 

Cincinnati: 

PM10

O3 r = 0.42 

NO2 r = 0.36 

SO2 r = 0.31 

Cleveland: 

PM10

O3 r = 0.42 

NO2 r = 0.34 

SO2 r = 0.29 

Columbus: 

PM10

O3 r = 0.51 

NO2 r = Na 

SO2 r = 0.42 

PM Increment: 50 μg/m3

% Change 

Asthma 

Cincinnati: -22%[-49,-19] Lag 3 

Cleveland: 12%[0,27] Lag 2 

Columbus: 32%[-6,-85] Lag 3 

Ar Estimate [Lower Ci, Upper Ci] 

Lag: 

Asthma 

Cincinnati: PM10: Nr 

Cleveland: PM10: 1.32 

Columbus: PM10: 3.62 

Notes: Dose response was investigated 

by assessing the relationship between 

odds of ed visit by quintile of PM10. 

Results are displayed in Fig. “no 

consistent effects for all three cities 

were observed for PM10.” Rate ratios 

were also reported for each city. 

December 2009 E-236 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Jalaludin et al. (2004, 

056595) 

Period of Study: Feb-Dec 1994 

Location: Sydney, Australia 

Doctor Visits 

Outcome (ICD- NR): Respiratory 

symptoms (wheeze, dry cough, and wet 

cough), asthma medication use, and 

doctor visits for asthma 

Age Groups: Primary school children 

Study Design: Longitudinal cohort 

study 

N: 125 children 

Statistical Analyses: GEE logistic 

regression models 

Covariates: Temperature, humidity, 

daily pollen count, daily alternaria count, 

number of h spend outdoors, season 

Season: Fall (Feb-Apr), winter (MayAug), spring/summer (Sep-Dec) 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 22.8 (13.8) 

Monitoring Stations: 4 

Copollutant (correlation): 

O3: r = 0.13 

NO2: r = 0.26 

Other variables: 

Temp: r = 0.04 

Humidity: r = -0.29 

Total pollen: r = 0.04 

Alternaria: r = 0.04 

PM Increment: IQR (μg/m3) 

Same day: 12.0 

1-day lag: 12.02 

2-day lag: 12.25 

2-day avg: 11.15 

5-day avg: 10.23 

OR Estimate [CI]: 

Doctor Visits for Asthma 

Same day: 1.11 [1.04,1.19] 

1-day lag: 1.10 [1.02,1.19] 

2-day lag: 1.15 [1.06,1.24] 

2-day avg: 1.11 [1.03,1.20] 

5-day avg: 1.14 [0.98,1.31] 

Prevalence of Doctor Visits for 

Asthma: 

Quartile 1: 0.50 (mean PM = 12.4) 

Quartile 2: 0.38 (mean PM = 17.2) 

Quartile 3: 0.65 (mean PM = 23.0) 

Quartile 4: 0.63 (mean PM = 38.3) 

Notes: ORs and prevalence are also 

provided for wheeze, dry cough, wet 

cough, inhaled β2-agonist use, and 

inhaled corticosteroid use. None were 

statistically significant. 

December 2009 E-237 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Johnston et al. (2007, 

155882) 

Period of Study: 2000, 2004, 2005 

(Apr-Nov of each yr) 

Location: Darwin, Australia 

Hospital Admissions/ED visits 

Outcome (ICD-10): 

All respiratory conditions (J00-J99), 

including asthma (J45-46), COPD 

(J40-J44), and respiratory infections 

(J00-J22). 

Age Groups Analyzed: All 

Study Design: Case-crossover 

N: 2466 emergency admissions 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Weekly influenza rates, 

temperature, humidity, days with rainfall 

>5mm, public holidays, school holiday 

periods (for respiratory conditions only) 

Season: Apr-Nov (dry season) 

Dose-response Investigated? No 

Statistical package: NR 

Lags Considered: 0-3 days 

Pollutant: PM10 

Averaging Time: 24 h 

Median: 17.4 

IQR: 13.6-22.3 

10-90th Percentile: 10.3-27.7 

Range: 1.1-70.0

Monitoring Stations: 1 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3 

 OR Estimate [95% CI]: All respiratory 

conditions: Lag 0: 1.08 [0.98-1.18] 

Lag 0 (indigenous): 1.17 [0.98-1.40] 

COPD: Lag 0: 1.21 [1.0-1.47] 

Lag 0 (indigenous): 1.98 [1.10-3.59] 

Asthma: Lag 0: 1.14 [0.90-1.44] 

Asthma + COPD: Lag 0: 1.19 

[1.03-1.38] 

Notes: Fig 1: Adjusted OR and 95% CI 

for hospital admissions for all 

respiratory conditions per 10 μg/m3

 rise 

in PM10 for the same day and lags up to 

3 days, overall and stratified by 

indigenous status. 

Summary of Fig 1 results: Marginally 

significant positive association at Lag 0 

in overall study population. Larger 

marginally significant positive 

association among indigenous people. 

Fig 2: OR and 95% CI for hospital 

admissions for COPD. Summary of Fig 

2 results: Marginally significant positive 

associations at Lag 0 and Lag 1 in 

overall study population and among 

non-indigenous people. Large, 

statistically significant positive 

association at Lag 0 for indigenous 

people, with smaller, non-significant 

positive associations at Lag 1 and Lag2.

Fig 3: OR and 95% CI for hospital 

admissions for asthma. 

Summary of Fig 3 results: Positive, 

non-significant (sometime marginally 

significant) associations at Lag 0, Lag 2, 

and Lag 3 for overall population and 

indigenous status strata. 

Fig 4: OR and 95% CI for hospital 

admissions for respiratory infections. 

Summary of Fig 4 results: Negative 

associations at Lag 2 and Lag 3 in all 

population strata. 

December 2009 E-238 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kim et al. (2007, 092837) 

Period of Study: 2002 

Location: Seoul, Korea

Ed Visits 

Outcome (ICD10): Asthma (J45), (J46) 

Age Groups: All Ages 

Study Design: Cass-Crossover

N: 92,535 Visits 

Statistical Analyses: Conditional 

Logistic Regression, Relative Effect 

Modification (Rem) 

Covariates: Time Trend, Season, Daily 

Mean Temperature, Relative Humidity, 

Air Pressure. Sep As Modifier Of Air 

Pollution Asthma Visit Association.

Season: All Year 

Dose-response Investigated? No 

Statistical Package: Nr 

Lags Considered: 0-2 days 

Pollutant: PM10

Averaging Time: 8 h 

Mean (SD): Daily Concentration: 67.6 

(39.0) μg/m3

Relevant Exposure Term (Difference 

Between Concentration On Event Day 

And Mean Of Concentrations On 

Control Days): 26.0 (19.7) 

Percentiles: 50th(Median): Daily 

Concentration: 61.9 

Relevant Exposure Term: 21.6 

Range (Min, Max): Daily 

Concentration: (4.9, 302.0) 

Relevant Exposure Term: (0.0, 143.1) 

Monitoring Stations: 3 

Copollutant: Nr 

PM Increment: 47.4 μg/m3

Rr Estimate For Asthma (Stratified 

By Sep): 

Individual Level Sep: 

Quintile 1-1.06[1.02, 1.09] 

Quintile 2-1.07[1.04, 1.10] 

Quintile 3-1.06[1.03, 1.10] 

Quintile 4-1.03[0.99, 1.07] 

Quintile 5-1.10[1.05, 1.14] 

Regional Level Sep: 

Quintile 1-1.04[0.99, 1.10] 

Quintile 2-1.03[1.00, 1.07] 

Quintile 3-1.05[1.03, 1.08] 

Quintile 4-1.06[1.02, 1.10] 

Quintile 5-1.09[1.06, 1.13] 

Total-1.06[1.04, 1.08], 3 D Ma 

Notes: Relative Effect Modification 

(Rem) Estimates Presented In Paper. 

Reference: Ko et al. (2007, 091639) 

Period of Study: Jan 2000-Dec 2004 

Location: Hong Kong, China

Ed Visits 

Outcome (ICD-9): COPD: chronic 

bronchitis (491), emphysema (492), 

chronic airway obstruction (496) 

Age Groups: All Ages 

Study Design: Time Series 

N: 15 hospitals, 119,225 admissions 

Statistical Analyses: Poisson 

regression, gam with stringent 

convergence criteria, aphea2 protocol. 

Covariates: Time trend, season, 

temperature, humidity, other cyclical 

factors, day, day of wk, holidays

Season: All yr, interactions with season 

tested 

Dose-response Investigated? No 

Statistical Package: Splus 4.0 

Lags Considered: 0-5 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 50.1(23.9) μg/m3

Percentiles: 25th: 31.9 

50th(Median): 44.5 

75th: 64.1 

Range (Min, Max): (13.6, 172.2) 

Monitoring Stations: 14 Stations 

Copollutant (correlation): 

PM10: 

SO2 r = 0.436 

NO2 r = 0.229 

O3 r = 0.421 

PM2.5 r = 0.952 

PM Increment: 10 μg/m3 

Rr Estimate 

COPD: 

1.003[1.000, 1.005] Lag 0 

1.005[1.002, 1.007] Lag 1 

1.010[1.007, 1.012] Lag 2 

1.011[1.008, 1.013] Lag 3 

1.008[1.006, 1.011] Lag 4 

1.007[1.004, 1.009] Lag 5 

1.005[1.002, 1.008] Lag 0-1 

1.011[1.008, 1.014] Lag 0-2 

1.016[1.013, 1.019] Lag 0-3 

1.020[1.017, 1.024] Lag 0-4 

1.024[1.021, 1.028] Lag 0-5 

December 2009 E-239 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ko et al. (2007, 091639) 

Period of Study: 

Jan 2000-Dec 2004 

Location: Hong Kong, China 

Hospital Admission 

Outcome (ICD-9): Asthma (493) 

Age Groups: All, 0-14, 15-56, 65+ 

Study Design: Time series

N: 69,716 admissions, 15 hospitals 

Statistical Analyses: Poisson 

regression, with GAM with stringent 

convergence criteria. 

Covariates: Time trend, season, 

temperature, humidity, other cyclical 

factors 

Season: All yr, evaluated effect of 

season in analysis 

Dose-response Investigated? No 

Statistical Package: SPLUS 4.0 

Lags Considered: 0-5 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 52.5(27.1) μg/m3

Percentiles: 25th: 30.9 

50th(Median): 

47.1 

75th: 68.8 

Range (Min, Max): (13.4, 198.9) 

Monitoring Stations: 14 stations 

Copollutant (correlation): 

PM10: SO2 r = 0.436 

NO2 r = 0.761 

O3 r = 0.600 

PM2.5 r = 0.956

PM Increment: 10.0 μg/m3

RR Estimate: 

Asthma (Single-pollutant model): 

1.006[1.003, 1.010] lag 0 

1.005[1.002, 1.009] lag 1 

1.005[1.002, 1.009] lag 2 

1.008[1.005, 1.012] lag 3 

1.006[1.002, 1.009] lag 4 

1.006[0.999, 1.006] lag 5 

1.008[1.004, 1.012]; lag 0-1 

1.012[1.008, 1.016] lag 0-2 

1.015[1.011, 1.019] lag 0-3 

1.018[1.013, 1.022] lag 0-4 

1.019[1.015, 1.024] lag 0-5 

Asthma by age group 

0-14: 1.023[1.015, 1.031] lag 0-5 

14-65: 1.014[1.006, 1.022] lag 0-5 

>65: 1.015[1.009, 1.022] lag 0-4 

Asthma-Effect of season: 1.148[1.051, 

1.245] lag 0-5 

Reference: Kuo et al. (2002, 036310) 

Period of Study: 1 yr 

Location: central Taiwan 

Hospital Admissions 

Outcome (ICD-NR): Asthma 

Age Groups: 13-16 yr 

Study Design: Cohort 

N: 12,926 

Statistical Analyses: Multiple logistic 

regression, Pearson correlation 

Covariates: Sex, age, residential area, 

level of parents’ education, number of 

cigarettes smoked by smokers in the 

family, incense burning, frequency of 

physical activity 

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: NR

Pollutant: PM10

Averaging Time: 1 h 

Mean (min-max): NR 

Range: (54.1-84.3)

Monitoring Stations: 8 

Copollutant: Values NR 

Notes: Author states that a positive 

correlation was found between NO2 and 

PM10

PM Increment: NR 

OR Estimate: 

PM10 <65.9 μg/m3

-referent 

PM10 >65.9 μg/m3

Crude OR: 0.837 

Adj OR: 0.947 

95% CI: (0.640,1.401)

Reference: Langley-Turnbaugh et al. 

(2005, 093269) 

Period of Study: 2000-2001 

Location: Portland, Bridgeton, and 

Presque Isle, Maine 

Hospital Admissions 

Outcome (ICD-9): Asthma (493xx) 

Age Groups: 0-18 yr, 19+ yr 

Study Design: Time series 

N: NR 

Statistical Analyses: NR 

Covariates: NR 

Season: Winter, spring, summer, fall 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: NR 

Notes: Hospital admissions were used 

to determine seasonality of asthma 

admissions so that PM components 

from those time periods could be 

analyzed 

Pollutant: PM10

Averaging Time: NR 

Mean (min-max): NR 

Monitoring Stations: NR 

Copollutant: NR 

PM Increment: NR 

RR Estimate [CI]: NR 

Notes: Portland filters contained more 

PM in the winter (Jan) and Bridgeton 

filters contained more PM in the spring 

(May) 

study analyzed metal components of 

PM10 (Mn, Cu, Pb, As, V, Ni, Al) 

Clinical data shows a strong peak in fall 

and weaker peaks in Jan and May for 

asthma admissions

December 2009 E-240 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lee et al. (2002, 034826) 

Period of Study: Dec 1997-Dec 1999 

Location: Seoul, Korea 

Hospital Admissions 

Outcome (ICD10): Asthma, J45, J46, 

Age Groups: Children <15 yr

Study Design: Time-Series 

N: 822 days, 6,436 admissions 

Statistical Analyses: Poisson 

regression, GAM, LOESS smoothers. 

Covariates: Days of the week, 

temperature, humidity 

Season: All 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-5, 0-1 ma for 1-2, 

2-3, and 3-4 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 64.0 (31.8) μg/m3

Percentiles: 25th: 40.5 μg/m3

50th(Median): 59.1 μg/m3

75th: 80.9 μg/m3

Range (Min, Max): NR 

Monitoring Stations: 27 

Notes: Copollutant (correlation): 

PM10-SO2: 0.585 

PM10-NO2: 0.738 

PM10-O3: 0.106 

PM10-CO: 0.598

PM Increment: IQR: 40.4 μg/m3

RR Estimate: 

Single Pollutant: 

1.07 (1.04, 1.11) lag 1 

Two pollutant models: 

+SO2: 1.05 (1.01, 1.09) lag 1 

+NO2: 1.03 (0.99, 1.07) lag 1 

+O3: 1.06 (1.03, 1.10) lag 1 

+CO: 1.04 (1.00, 1.08) lag 1 

Three pollutant models: 

+O3 + CO: 1.02 (0.98, 1.06), lag 1 

Four pollutant models: 

+O3 + CO +SO2: 1.02 (0.98, 1.06), lag 1 

Five pollutant model: 

1.016 (0.975, 1.059) lag 1 

Notes: Investigated the association 

between outdoor air pollution and 

asthma attacks in children <15 yr. 

Reference: Lee et al. (2006, 090176) 

Period of Study: Jan 1997-Dec 2002 

Location: Hong Kong, China

Hospital Admission 

Outcome: Asthma (493) 

Age Groups: <18 yr 

Study Design: Time series

N: 26,663 asthma admissions for 

asthma and 5821 admissions for 

influenza 

Statistical Analyses: Poisson 

regression, GAM 

Covariates: Temperature, atmospheric 

pressure, relative humidity 

Season: All 

Dose-response Investigated? No 

Statistical Package: SAS 8.02 

Lags Considered: 0-5 

Notes: Controls were admissions for 

influenza ICD9 487 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 56.1 (24.2) 

Percentiles: 25th: 37.3 

50th(Median): 51.1 

75th: 70.7 

Monitoring Stations: 10 

Notes: Copollutant (correlation): 

PM10-PM2.5: 0.90 

PM10-SO2: 0.39 

PM10-NO2: 0.80 

PM10-O3: 0.60

PM Increment: IQr = 33.4 

Percent Increase: 

Single pollutant model: 

4.97 [2.96, 7.03], lag 0 

5.71 [3.78, 7.68], lag 1 

6.40 [4.51, 8.32 ], lag 2 

7.25 [5.38, 9.16 ], lag 3 

7.45 [5.58, 9.35], lag 4 

5.96 [4.11, 7.85 ], lag 5 

Multipollutant model (SO2, CO, NO2, O3)

3.67 [1.52,5.86] lag4 

Reference: Lin et al. (2005, 087828) 

Period of Study: 1998-2001 

Location: Toronto, North York, East 

York, Etobicoke, Scarborough, and York 

(Canada) 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

infections including laryngitis, tracheitis, 

bronchitis, bronchiolitis, pneumonia, 

and influenza (464, 466, 480-487) 

Age Groups: 0-14 yr 

Study Design: Bidirectional casecrossover 

N: 6782 respiratory infection 

hospitalizations 

Statistical Analyses: Conditional 

logistic regression (Cox proportional 

hazards model) 

Covariates: Daily mean temp and dew 

point temp 

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 8.2 PHREG 

procedure 

Lags Considered: 1-7 day avg

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

20.41 (4.00-73.00) 

SD = 10.14 

Monitoring Stations: 4 

Copollutant (correlation): 

PM2.5: r = 0.87 

PM10-2.5: r = 0.76 

CO: r = 0.10 

SO2: r = 0.48 

NO2: r = 0.54 

O3: r = 0.54 

PM Increment: 12.5 μg/m3

OR Estimate [CI]: 

Adjusted for weather 

4-day avg: 1.22 [1.10,1.34] 

6-day avg: 1.25 [1.11,1.40] 

Adj for weather and other gaseous 

pollutants 

4-day avg: 1.14 [0.99,1.32] 

6-day avg: 1.20 [1.01,1.42] 

Notes: OR’s were also categorized into 

“Boys” and “Girls,” yielding similar 

results

December 2009 E-241 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lin et al, (2008, 126812) 

Period of Study: 1991-2001 

Location: New York State, U.S. 

Outcome: Respiratory hospital 

admissions (ICD-9 466, 490-493, 496 

Study Design: Time-series 

Covariates: Demographic 

characteristics, PM10, meteorological 

conditions, day of the week, 

seasonality, long term trends and 

different lag periods 

Statistical Analysis: GAM and casecrossover design at the regional level 

and Bayesian hierarchical model at the 

state level 

Age Groups: Children 0-17 yr 

Pollutant: O3 (PM10 is secondary) 

Averaging Time: 24 h 

Mean (SD) Unit: 19.56 (10.92) μg/m3

Range (Min, Max): 1.0, 90.00 

Copollutant (correlation): 

Given in Fig 3 

All PM10 results are given in Fig 3

Reference: Lin et al. (2002, 026067) 

Period of Study: Jan 1981-Dec 1993 

Location: Toronto 

Hospital Admissions 

Outcome (ICD-9): Asthma (493) 

Age Groups: 6-12 yr 

Study Design: Uni- and bi-directional 

case-crossover (UCC, BCC) and timeseries (TS) 

N: 7,319 asthma admissions 

Statistical Analyses: Conditional 

logistic regression, GAM 

Covariates: Maximum and minimum 

temp, avg relative humidity 

Season: Apr-Sep, Oct-Mar 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1-7 day avg

Pollutant: PM10

Averaging Time: 6 days (predicted 

daily values) 

Mean (min-max): 

30.16 (3.03-116.20) 

SD = 13.61 

Monitoring Stations: 1 

Copollutant (correlation): 

PM2.5: r = 0.87 

PM10-2.5: r = 0.83 

CO: r = 0.38 

SO2: r = 0.44 

NO2: r = 0.52 

O3: r = 0.44 

PM Increment: 14.8 μg/m3

RR Estimate [CI]: 

Adj for weather and gaseous pollutants 

BCC 5-day avg: 0.99 [0.90,1.09] 

BCC 6-day avg: 1.01 [0.90,1.12] 

TS 5-day avg: 1.03 [0.95,1.11] 

TS 6-day avg: 1.02 [0.94,1.11] 

Boys-adj for weather 

UCC 1-day avg: 1.10 [1.04,1.17] 

UCC 2-day avg: 1.10 [1.02,1.17] 

BCC 1-day avg: 1.04 [0.98,1.09] 

BCC 2-day avg: 1.01 [0.95,1.08] 

TS 1-day avg: 1.03 [0.99,1.07] 

TS 2-day avg: 1.01 [0.96,1.05] 

Girls-adj for weather 

UCC 1-day avg: 1.07 [0.99,1.16] 

UCC 2-day avg: 1.15 [1.04,1.26] 

BCC 1-day avg: 0.99 [0.92,1.06] 

BCC 2-day avg: 1.03 [0.95,1.12] 

TS 1-day avg: 0.99 [0.94,1.04] 

TS 2-day avg: 1.02 [0.96,1.08] 

Notes: The author also provides RR 

using UCC, BCC, and TS analysis for 

female and male groups for days 3-7, 

yielding similar results 

Reference: Linares et al. (2006, 

092846) 

Period of Study: Jan 1995-Dec 2000 

Location: Madrid, Spain

Outcome: Respiratory system diseases 

460-519, bronchitis 460-496, 

pneumonia 480-487 

Age Groups: <10 yr

Study Design: Time series

N: ~15,000 admissions, 2192 days 

Statistical Analyses: Poisson 

regression, dummy variables to adjust 

for season and weather 

Covariates: Temperature, difference in 

barometric pressure, relative humidity, 

pollen counts, influenza epidemics 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-13 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 33.4 μg/m3, (13.7) 

Range (Min, Max): 6, 109 μg/m3

Monitoring Stations: 24 

Notes: Copollutant (correlation): 

PM10-SO2: 0.532 

PM10-O3: -0.289 

PM10-: 0.721 

PM10-NO2: 0.711

PM Increment: 10 μg/m3

RR Estimate 

Bronchitis 

1.09 [1.01, 1.16] lag 2 

AR% Estimate 

Bronchitis 

7.9 [CI NR] lag2 

Notes: Only statistically significant 

relative and attributable risks were 

presented by the authors. 

The authors conducted multivariate 

modeling using a linear term to 

represent PM10. They also report an 

apparent estimated PM10 effect 

threshold of 60 μg/m3

, based on 

examination of a scatter plot of 

respiratory emergency hospital 

admissions and PM10 levels. 

December 2009 E-242 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Luginaah, et al. (2005, 

057327) 

Period of Study: Apr 1995-Dec 2000 

Location: Windsor, Ontario, Canada

Hospital Admission/ED: 

admission 

Outcome: All respiratory: 460-519 

Age Groups: All, 0-14, 15-64, and >65

Study Design: Times-series, bidirectional case-crossover

N: 4214 admissions 

Statistical Analyses: Poisson 

regression, GAM w/ stringent 

convergence criteria or natural splines, 

conditional logistic regression 

Covariates: Age, sex 

Maximum & minimum temperature, 

change in barometric pressure from 

previous day 

Season: All 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 1-3

Pollutant: PM10

Averaging Time: 24-h max 

Mean (SD): 50.6 ,(35.5) 

Range (Min, Max): 9, 349 

Monitoring Stations: 4 

Notes: Copollutant (correlation): 

PM10-NO2: 0.33 

PM10-SO2: 0.22 

PM10-CO: 0.21 

PM10-O3: 0.33

PM Increment: Interquartile range 

(75th-25th) 31 μg/m3

RR Estimates (Time Series) 

All Age Groups Females 

0.996 [0.950, 1.044], lag 1 

1.015 [0.963, 1.069], lag 2 

1.022 [0.968, 1.078], lag 3 

All Age Groups Males 

1.008 [0.965, 1.054], lag 1 

1.036 [0.986, 1.089], lag 2 

1.027 [0.974, 1.083], lag 3 

RR Estimates (Case Crossover) 

All Age Groups Females 

1.034 [0.974, 1.098], lag 1 

1.045 [0.972, 1.124], lag 2 

1.054 [0.970, 1.145], lag 3 

All Age Groups Males 

0.997 [0.942, 1.056], lag 1 

1.022 [0.953, 1.097], lag 2 

1.008 [0.930, 1.092], lag 3 

Notes: Results, stratified by age group 

available in manuscript. 

Reference: Martins et al. (2002, 

035059) 

Period of Study: May 1996-Sep 1998 

Location: Sao Paulo, Brazil

Hospital Admission/ED: 

ER visits 

Outcome (ICD10): Chronic lower 

respiratory disease (CLRD) (40-47) 

Includes chronic bronchitis, 

emphysema, other COPDs, asthma, 

bronchiectasia 

Age Groups: >64 yr

Study Design: Time series

N: 712 for CLRD 

1 hospital 

Statistical Analyses: Poisson 

regression GAM, LOESS smoothers, no 

mention of stringent criteria 

Covariates: Day of week, time 

minimum temperature, relative humidity 

Season: All 

Statistical Package: S-Plus 

Lags Considered: 2-7 3 day ma

Pollutant: PM10

Averaging Time: Daily 

Mean (SD): 60.0 μg/m3, (26.3) 

Range (Min, Max): 

22.8. 186.5 μg/m3

PM Component: None 

Monitoring Stations: 12 

Notes: Copollutant (correlation): 

PM10-CO: 0.73 

PM10- NO2: 0.83 

PM10-SO2: 0.72 

PM10-O3: 0.35

PM Increment: 1 μg/m3

Regression Coefficients (SE): 

0.0024 (0.0023), 6 day ma 

Notes: % Increase (SD) for ER visits 

per 2435 μg/m3

 (IQR) PM10 (lag 6 day 

ma) presented graphically in text. 

December 2009 E-243 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Masjedi et al. (2003, 

052100) 

Period of Study: Sep 1997-Feb 1998 

Location: Tehran, Iran 

Hospital Admissions 

Outcome (ICD-9): Acute asthma and 

COPD exacerbations (ICD: NR) 

Age Groups: NR 

Study Design: Time series 

N: 355 patients 

Statistical Analyses: Multiple stepwise 

regression, autoregression method 

(time series), Pearson correlation 

Covariates: NR 

Season: NR 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 3-, 7-, and 10-day 

mean

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

108.41 (14.5-506.60) 

SD = 59.55 

Monitoring Stations: 3 

Copollutant: NR 

PM Increment: NR 

Results: 

Time-series analysis 

Asthma: β = 0.002 

p = 0.32 

COPD: β = 0.004 

p = 0.02 

Total Acute Resp Conditions: β = 0.006 

p = 0.27 

Correlation of 3-day mean 

Asthma: r = -0.21 

β = -0.16 

p = 0.08 

Correlation of weekly mean 

Asthma: r = -0.27 

β = -0.008 

p = 0.12 

Correlation of 10-day mean 

Asthma: r = -0.38 

β = -0.066 

p = 0.089

Reference: McGowan et al. (2002, 

030325) 

Period of Study: Jun 1988-Dec 1998 

Location: Christchurch, New Zealand 

Hospital Admissions 

Outcome (ICD-9): Pneumonia (480-

487), acute respiratory infections (460-

466), chronic lung diseases (491-492, 

494-496), asthma (493) 

Age Groups: <15 yr, 15-64, 65+ 

Study Design: Time series 

N: 20,938 admissions 

Statistical Analyses: GAM with log 

link, Linear Regression Model 

Covariates: Wind speed, relative 

humidity, temperature 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-PLUS 

Lags Considered: 0-6 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

25.17 (0-283) 

SD = 25.49 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: 14.8 μg/m3 (IQR) 

% Increase [CI]: 

Respiratory Admissions (2-day lag) 

0-14 yr: 3.62 [2.34,4.90] 

15-64 yr: 3.39 [1.85,4.93] 

65+ yr: 2.86 [1.23,4.49] 

All ages: 3.37 [2.34,4.40] 

Overall 

Acute respiratory infections: 4.53 

[2.82,6.24] 

Pneumonia/influenza: 5.32 [3.46,7.18] 

Chronic lung diseases: 3.95 [2.15,5.75] 

Asthma: 1.86 [0.48,.3.24] 

Total Respiratory Admissions 

Same day lag: 2.52 [1.49,3.55] 

1-day lag: 2.56 [1.53,3.59] 

2-day lag: 3.37 [2.34,4.40] 

3-day lag: 3.09 [2.06,4.12] 

4-day lag: 3.13 [2.10,4.16] 

5-day lag: 3.21 [2.18,4.24]; 

6-day lag: 3.09 [2.06,4.12]

December 2009 E-244 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Medina-Ramon et al. 

(2006, 087721) 

Period of Study: 1986-99 

Location: 36 U.S. Cities

Outcome: 490-496, except 493 

(COPD), 480-487 (Pneumonia) 

Age Groups: 65 + (U.S. Medicare 

beneficiaries) 

Study Design: Case crossover

N: 578,006 COPD admissions 

1,384,813 Pneumonia admissions 

Statistical Analyses: Conditional 

logistic regression, Meta-analysis using 

REML random effects models 

Covariates: Mean and variance of daily 

summer apparent temperature index, % 

65+ living in poverty,% households with 

central air-conditioning mortality rate for 

emphysema among 65+(surrogate for 

smoking history), % PM10 from traffic 

Season: Warm(May -Sepnd 

Cold(Oct-Apr) 

Dose-response Investigated? No 

Statistical Package: SAS 

STATA 

Lags Considered: 0-1 days 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 30.4 μg/m3 (5.1) 

Monitoring Stations: at least one per 

city 

Notes: PM10 measurements made 

every 2, 3 or 6 days depending on the 

city. 

Copollutant: NR

PM Increment: 10 μg/m3

% change [Lower CI, Upper CI] 

lag: 

COPD warm season 

0.81(0.22,1.41) at lag 0 

1.47(0.93,2.01) at lag 1 

COPD cold season 

0.06(-0.40,0.51) at lag 0 

0.10(-0.30,0.49) at lag 1 

Pneumonia warm season 

0.84 (0.50,1.19) at lag 0 

0.79 (0.45,1.13) at lag 1 

Pneumonia cold season 

0.30 (0.07,0.53) at lag 0 

0.14 (-0.17,0.45) at lag 1 

Reference: Meng et al., (2007, 093275) 

Period of Study: Nov 2000-Sep 2001 

Location: Los Angeles and San Diego 

counties, California 

Outcome (ICD-NR): Poorly controlled 

asthma defined as (1) daily or weekly 

asthma symptoms or (2) at least 1 ED 

visit or hospitalization due to asthma 

over the past 12 mo 

Age Groups: >18 yr 

Study Design: Time series 

N: 1609 asthma patients 

Statistical Analyses: Logistic 

regression 

Covariates: Age, sex, race/ethnicity, 

poverty level, insurance status, smoking 

behavior, employment, asthma 

medication use, and county 

Season: NR 

Dose-response Investigated: No 

Statistical Package: NR 

Lags Considered: NR 

Pollutant: PM10

Averaging Time: 24 h 

Mean (25-75th percentile): NR 

Monitoring Stations: NR 

Copollutant (correlation): 

PM2.5: r = 0.84 

O3: r = -0.72 

NO2: r = 0.83 

CO: r = 0.42 

Other variables: 

Traffic: r = 0.14 

PM Increment: 10 μg/m3 

 OR Estimate [CI]: 

All Adults: 1.08 [0.82,1.43] 

18-64 yr: 1.14 [0.84,1.55] 

65+: 0.84 [0.41,1.73] 

Men: 0.72 [0.42,1.21] 

Women: 1.38 [0.99,1.94] 

Exposure above 44.01 μg/m3

 (annual 

concentration) 

All Adults: 1.56 [0.96,2.52] 

18-64 yr: 1.40 [0.81,2.41] 

65+: 2.23 [0.60,8.27] 

Men: 0.80 [0.27,2.41] 

Women: 2.06 [1.17,3.61] 

Notes: This study focused more on the 

relation between poorly controlled 

asthma and traffic density.

December 2009 E-245 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Middleton et al. (2008, 

156760) 

Period of Study: 1995-1998, 

2000-2004 

Location: Nicosia, Cyprus 

Hospital Admissions/ED visits 

Outcome (ICD-NR): 

Hospital admissions for all respiratory 

disease (ICD-10: J00-J99). 

Age Groups Analyzed: All, also 

stratified by age (<15 vs.. >15 yr) 

Study Design: Time series

N: Statistical Analyses: Generalized 

additive Poisson models 

Covariates: Seasonality, day of the 

week, long- and short-term trend, 

temperature, relative humidity

Season: NR 

Dose-response Investigated: No 

Statistical package: STATA SE 9.0, 

and the MGCV package in the R 

software (R 2.2.0) 

Lags Considered: lag 0 -2 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD 

median 

5% - 95% 

range): 

Cold: 

57.6 (52.5 

50.8 

20.0-103.0 

5.0-1370.6) 

Warm: 

53.4 (50.5 

30.7 

32.0-77.6 

18.4-933.5) 

Monitoring Stations: 2 

Copollutant (correlation): NR 

Other variables: 

PM Increment: 10 μg/m3 , and across 

quartiles of increasing levels of PM10

Percentage increase estimate [CI]: 

All age/sex groups (Lag 0): 

All admissions: 0.85 (0.55, 1.15) 

Respiratory (all): 0.10 (-0.91, 1.11) 

Respiratory (cold months): 

 -0.33 (-1.47, 0.82) 

Respiratory (warm months): 

1.42 (-0.42, 3.31) 

CVD + RD: 0.56 (-0.21, 1.34) 

Nicosia residents (Lag 0): 

Respiratory (all): 0.25 (-0.84, 1.36) 

Respiratory (cold months): 

-0.22 (-1.45, 1.02) 

Respiratory (warm months): 

1.80 (-0.22, 3.85) 

CVD + RD: 0.38 (-0.47, 1.23) 

Males (Lag 0): 

All admissions: 0.96 (0.54, 1.39) 

Respiratory (all): -0.06 (-1.37, 1.26) 

Respiratory (cold months): 

 -0.16 (-1.76, 1.46) 

Respiratory (warm months): 

1.10 (-1.47, 3.74) 

CVD + RD: 0.63 (-0.34, 1.62) 

Females (Lag 0): 

All admissions: 0.74 (0.31, 1.18) 

Respiratory (all): 0.39 (-1.21, 2.02) 

Respiratory (cold months): 

-0.26 (-2.18, 1.70) 

Respiratory (warm months): 

3.27 (-0.00, 6.65) 

CVD + RD: 0.59 (-0.68, 1.87) 

Aged <15 yr (Lag 0): 

All admissions: 0.47 (-0.13, 1.08) 

Respiratory (all): -0.35 (-1.77, 1.08) 

Respiratory (cold months): 

-0.31 (-2.02, 1.42) 

Respiratory (warm months): 

-0.59 (-3.53, 2.45) 

Aged >15 yr (Lag 0): 

All admissions: 0.98 (0.63, 1.33) 

Respiratory (all): 0.59 (-0.87, 2.07) 

Respiratory (cold months): 

0.02 (-1.76, 1.83) 

Respiratory (warm months): 

3.89 (1.05, 6.80)

Reference: Moore et al. (2008, 196685) 

Period of Study: 1983-2000 

Location: California’s South Coast Air 

Basin 

Outcome: Hospital admissions for 

asthma (ICD-9 493) 

Study Design: Time-series 

Covariates: Income, demographic and 

residential variables 

Statistical Analysis: HRMSM 

Age Groups: Children ages 0-19 yr 

Pollutant: O3 (PM10 secondary) 

Averaging Time: Quarterly 

Mean (SD) Unit: NR 

Range (Min, Max): NR 

Copollutant (correlation): 

1hr O3: 0.52 

8hr O3: 0.46 

24 h NO2: 0.53 

24 h CO: 0.36 

24 h SO2: 0.13 

Results given are for O3

December 2009 E-246 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Nascimento et al. (2006, 

093247) 

Period of Study: May 2000-Dec 2001 

Location: São Jose dos Campos, 

Brazil 

Hospital Admissions 

Outcome (ICD-10): Pneumonia (J12-

J18) 

Age Groups: 0-10 yr 

Study Design: Time series 

N: 1265 admissions 

Statistical Analyses: GAM, Poisson 

regression 

Covariates: Temperature, humidity 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus, SPSS 

Lags Considered: 0-7 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

40.2 (3.4-196.6) 

SD = 26.9 

Monitoring Stations: 2 

Copollutant (correlation): 

SO2: r = 0.30 

O3: r = 0.09 

Other variables: 

Admissions: r = 0.21 

Temp: r = -0.14 

Notes: All p < 0.05 

PM Increment: 24.7 μg/m3

Regression coefficients (SE): 

Same day: -0.00053 (0.00125) 

1-day lag: 0.00029 (0.00057) 

2-day lag: 0.00089 (0.00069) 

3-day lag: 0.00122 (0.00053)* 

4-day lag: 0.00126 (0.00055)* 

5-day lag: 0.00098 (0.00071) 

6-day lag: 0.00035 (0.00056) 

7-day lag: -0.00067 (0.00123) 

*p < 0.05 

Notes: Percent increase over all lag 

days is displayed in Fig 2 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: 1999-2000 (1 yr 

period) 

Location: Vienna and Lower Austria 

Hospital Admissions 

Outcome (ICD-9): Bronchitis, 

emphysema, asthma, bronchiectasis, 

extrinsic allergic alveolitis, and chronic 

airway obstruction (490-496) 

Age Groups: 3.0-5.9 yr 

7-10 yr 

65+ 

Study Design: Time series 

N: 366 days (admissions NR) 

Statistical Analyses: GAM 

Covariates: SO2, NO, NO2, O3, 

temperature, humidity, and day of the 

week 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-14 days

Pollutant: PM10

Averaging Time: 24 h 

Maximum daily mean: 

Vienna: 105 

Rural area: NR 

Monitoring Stations: NR 

Copollutant: NR 

PM Increment: 10 μg/m3

Log Relative Rate Estimate (p-value): 

Vienna 

Male: 2 day lag = 4.217 (0.030) 

Association with tidal lung function: 

β = -1.067 (p-value = 0.241) 

Notes: Effect parameters with 

significant coefficients for respiratory 

health included: male sex, allergy, 

asthma in family, and traffic for Vienna 

and age, allergy, asthma in family, and 

passive smoking for the rural area. 

Effect parameters with significant 

coefficients for log asthma score were 

allergy, asthma in family, and rain for 

Vienna and allergy, asthma in family, 

and passive smoking for the rural area. 

Reference: Oftedal et al. (2003, 

055623) 

Period of Study: 1995-2000 

Location: Drammen, Norway

Hospital Admissions 

Outcome: All Respiratory (460-517) 

Age Groups: All

Study Design: Time-series

N: ~4,458 admissions 

Statistical Analyses: Poisson 

regression, GAM w/ stringent 

convergence criteria 

Covariates: Temperature, humidity, 

influenza epidemics, summer and 

Christmas vacation 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 

Lags Considered: 2-3

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 16.8 μg/m3, (10.2) 1994-

1997 

16.5 μg/m3

, (10.3) 1998-2000 

16.6 , μg/m3

 (10.2) total period 

PM Component: Benzene, 

formaldehyde, toluene 

Monitoring Stations: NR 

Notes: Copollutant (correlation): 

Correlation between pollutants ranged 

from -0.47-0.78 with the exception of 

the VOCs studied 

Notes: Benzene, formaldehyde and 

toluene also evaluated 

PM Increment: IQr = 11.04 

RR Estimate 

1.035 [0.990, 1.083] 1994-1997 

0.992 [0.948, 1.037] 1998-2000 

1.021 [0.990, 1.053] 1994-2000 

2 Pollutant Model 

PM10 w/ benzene: 1.01 (0.978, 1.043)

December 2009 E-247 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peel et al. (2005, 056305) 

Period of Study: Jan 1993-Aug 2000 

Location: Atlanta, Georgia

ED visits 

Outcome: Asthma (493, 786.09) 

COPD (491, 492, 496) 

URI (460-466, 477) 

Pneumonia (480-486) 

Age Groups: All ages. Secondary 

analyses conducted by age group: 0-1, 

2-18, >18 

Study Design: Time series

N: 31 hospitals 

Statistical Analyses: Poisson GEE for 

URI, asthma and all RD 

Poisson GLM for pneumonia and 

COPD) 

Covariates: Avg temperature and dew 

point, pollen counts 

Season: All (secondary analyses of 

warm season) 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.3, S-Plus 

2000 

Lags Considered: 0-7 day , 3 day ma, 

0-13 days unconstrained distributed lag

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 27.9 (12.3) μg/m3

Percentiles: 10th: 13.2

90th: 44.7 

Monitoring Stations: 

“Several” 

Copollutant (correlation): 

8 h O3: r = 0.59 

1 h NO2: r = 0.49 

1 h CO: r = 0.47 

1 h SO2: r = 0.20 

24-h PM2.5: 0.84 

24 h PM10-2.5: r = 0.59 

24 h UF: r = -0.13 

Components: r ranged from 0.42-0.74

PM Increment: PM10: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

All Respiratory Outcomes: 

1.013 (1.004-1.021), 3 day ma 

URI: 

1.014 (1.004-1.025) , 3 day ma 

1.073 (1.048-1.099) , 14-day dist. lag 

Asthma: 

1.009 (0.996-1.022), 3 day ma 

1.099 (1.065-1.135), 14-day dist. lag: 

Pediatric Asthma 2-18yrs): 

1.016 (0.998 -1.034) 

Pneumonia: 

1.011 (0.996-1.027) , 3 day ma 

1.087 (1.044-1.132), 14-day dist. lag 

COPD: 

1.018 (0.994-1.043), 3 day ma 

1.092 (1.023-1.165), 14-day dist. lag 

Notes: RRs obtained using AQS 1993-

2000, AQS 1998-2000 and ARIES data 

compared. Infant (0-1 y) and pediatric 

(2-18 y) asthma was associated more 

strongly with PM10, PM2.5 and OC than 

adult asthma. 

Reference: Ren et al. (2006, 092824) 

Period of Study: Jan 1996-Dec 2001 

Location: Brisbane, Australia 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

diseases (460-519) excluding influenza 

(487.0-487.8) 

Age Groups: NR 

Study Design: Time series 

N: NR 

Statistical Analyses: GAM 

Covariates: Day of week, relative 

humidity, influenza outbreaks 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 

Lags Considered: 0, 1, and 2 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 15.84 (2.5-60) 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: NR 

Coefficient Estimates: 

Respiratory Hospital Admissions 

Same day: -0.004296 

1-day lag: -0.002474 

2-day lag: -0.004229 

*all statistically significant 

Respiratory Emergency Visits 

Same day: -0.000887 

1-day lag: -0.004209 

2-day lag: -0.003440 

Notes: Relative risks were provided in 

graphical form (Fig 3) 

Reference: Sauerzapf et al. (2009, 

180082) 

Period of Study: Mar 2006-Mar 2007 

Location: Norfolk, UK 

Outcome: COPD 

Study Design: Case-Crossover 

Covariates: Environmental factors and 

Influenza 

Statistical Analysis: Logistic 

regression 

Statistical Package: SPSS 14 

Age Groups: >18 yr 

N: 1050 adult COPD admissions 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD) Unit: 

Control: 19.87 (8.51) μg/m3

Case: 20.47 (9.27) μg/m3

Range (Min, Max): 

Control: 9.77-34.27 

Case: 10.04-35.03 

Copollutant (correlation): NR 

Increment: 10 μg/m3

Odds Ratio (95% CI) 

Lag 0-7, unadjusted: 1.079 (0.980-

1.188) 

Lag 0-8, adjusted: 1.101 (0.988-1.226) 

Lag 1-8, unadjusted: 1.056 (0.961-

1.161) 

Lag 1-8, adjusted: 1.054 (0.949-1.170) 

December 2009 E-248 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sinclair and Tolsma (2004, 

088696)

Period of Study: 25 Months 

Location: Atlanta, Georgia 

Outpatient Visits

Outcome: Asthma (493) 

URI (460, 461, 462, 463, 464, 465, 466, 

477) 

LRI (466.1, 480, 481, 482, 483, 484, 

485, 486). 

Age Groups: < = 18 yr, 18+ yr (asthma)

All ages (URI//LRI) 

Study Design: Times series

N: 25 mo 

260,000-275,000 health plan members 

(Aug 1998-Aug 2000) 

Statistical Analyses: Poisson GLM 

Covariates: Season, Day of week, 

Federal Holidays, Study Months 

Season: NR 

Dose-response Investigated?: No 

Statistical Package: SAS 

Lags Considered: Three 3-day ma (0-

2, 2-5, 6-8)

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): PM10 mass-29.03 μg/m3

(11.61)

Monitoring Stations: 1 

Notes: Copollutant: NR

PM Increment: 11.61 (1 SD)

RR Estimate [Lower CI, Upper CI] 

lag: 

Child Asthma: 1.049 (S), lag 3-5 day 

LRI: 1.074 (S), 3-5 day lag 

Notes: Numerical findings for significant 

results only presented in manuscript. 

Results for all lags presented 

graphically for each outcome (asthma, 

URI, and LRI). 

Reference: Slaughter et al. (2005, 

073854)

Period of Study: Jan 1995-Jun 2001 

Location: Spokane, WA 

Hospital Admissions and ED visits 

Outcome: All respiratory (460-519) 

Asthma (493) 

COPD (491,492, 494,496) 

Pneumonia (480-487) 

Acute URI not including colds and 

sinusitis (464, 466, 490) 

Age Groups: All, 15+ yr for COPD

Study Design: Time series

N: 2373 visit records 

Statistical Analyses: Poisson 

regression, GLM with natural splines. 

For comparison also used GAM with 

smoothing splines and default 

convergence criteria. 

Covariates: Season, temperature, 

relative humidity, day of week 

Season: All 

Dose-response Investigated?: No 

Statistical Package: SAS, SPLUS 

Lags Considered: 1 -3 day 

Pollutant: PM10

Averaging Time: 24-h avg 

Range (90% of concentrations): 7.9-

41.9 μg/m3

Monitoring Stations: 

1 

Notes: Copollutant (correlation): 

PM10

PM1 r = 0.50 

PM2.5 r = 0.62 

PM10-2.5 r = 0.94 

CO r = 0.32 

Temperature r = 0.11

PM Increment: 25 μg/m3 

RR Estimate [Lower CI, Upper CI] 

lag: 

ER visits -- PM10

All Respiratory 

Lag 1: 1.01 [0.99, 1.04] 

Lag 2: 1.01 [0.98, 1.03] 

Lag 3: 1.02 [0.99, 1.04] 

Acute Asthma 

Lag 1: 1.03 [0.98, 1.07] 

Lag 2: 1.01 [0.96, 1.05] 

Lag 3: 1.00 [0.95, 1.04] 

COPD (adult) 

Lag 1: 1.00 [0.93, 1.07] 

Lag 2: 0.99 [0.92, 1.06] 

Lag 3: 1.02 [0.95, 1.08] 

Hospital Admissions -- PM10

All Respiratory 

Lag 1: 0.99 [0.95, 1.02] 

Lag 2: 0.99 [0.96, 1.02] 

Lag 3: 1.00 [0.97, 1.03] 

Asthma 

Lag 1: 1.03 [0.95, 1.12] 

Lag 2: 1.01 [0.94, 1.10] 

Lag 3: 1.00 [0.92, 1.09] 

COPD (adult) 

Lag 1: 0.98 [0.90, 1.07] 

Lag 2: 1.03 [0.96, 1.11] 

Lag 3: 1.02 [0.94, 1.09]

December 2009 E-249 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sun et al. (2006, 090768) 

Period of Study: Jan 2004-Dec 2004 

Location: Taichung, Taiwan (Central 

Taiwan)

ED visits 

Outcome: Asthma (493.xx) 

Age Groups: <55, <16, 16-55 yr 

Study Design: Cross-sectional 

N: NR 

All diagnoses for all patients at 4 

medical centers 

Statistical Analyses: Pearson’s 

correlations, multiple correlation 

coefficients from regression analyses. 

Covariates: Only copollutants 

considered 

Dose-response Investigated? No 

Statistical Package: SPSS 

Lags Considered: None

Pollutant: PM10

Averaging Time: Monthly avg for 2004 

Mean (SD): ~ 60.3 μg/m3 (NR) 

(estimated from Fig)* 

Range (Min, Max): (~35, 80) 

Monitoring Stations: 11 

Copollutant: NR

Children ED Visits 

r = 0.626 

P = 0.015 

Adult ED Visits 

r = 0.384 

P = 0.109

Reference: Szyszkowicz (2007, 

092829) 

Period of Study: Jan 1992-Mar 2002 

Location: Edmonton, Canada 

Outcome: ED visits for asthma (ICD-

(493) 

Study Design: Time-series 

Covariates: Temperature, relative 

humidity 

Statistical Analysis: Poisson 

regression 

Age Groups: All 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD) Unit: 22.6 (13.1) μg/m3

Median, IQR: 19.4, 15.0 

Copollutant (correlation): NR 

Increment: IQR 

Percent Relative Risk (95% CI)

*Only statistically significant results are 

presented in the paper* 

No lag, ≥ 10 yr 

Apr-Sep, All: 3.7 (1.5-6.0) 

Apr-Sep, Female: 4.5 (1.8-7.3) 

Apr-Sep, Male: 3.3 (0.1-6.7) 

2 day lag, < 10 yr 

Year round, All: 2.7 (0.1-5.4) 

Apr-Sep, All: 6.3 (2.6-10.2) 

Apr-Sep, Male: 7.4 (3.1-11.9) 

2 day lag, ≥ 10 yr 

Apr-Sep, All: 2.4 (0.1-4.7) 

Apr-Sep, Female: 3.9 (1.1-6.7)

Reference: Tecer et al, (2008, 180030) 

Period of Study: Dec 2004-Oct 2005 

Location: Zonguldak, Turkey 

Outcome: ED visits for respiratory 

problems (ICD-9 470-478, 493) 

Study Design: Bidirectional Casecrossover 

Covariates: Daily meteorological 

parameters 

Statistical Analysis: Conditional 

logistic regression 

Statistical Package: Stata 

Age Groups: 0-14 yr 

Pollutant: PM10

Averaging Time: NR 

Mean, Unit: 53.3 μg/m3

Range (Min, Max): 12-237.5 

Copollutant (correlation): 

PM2.5/PM10

Mean: 0.56 

Range: 0.17-0.88 

Increment: 10 μg/m3

Odds Ratio (95% CI)

Asthma 

Lag 0: 1.14 (1.03-1.26) 

Lag 1: 0.92 (0.83-1.02) 

Lag 2: 0.92 (0.81-1.03) 

Lag 3: 1.01 (0.92-1.11) 

Lag 4: 1.16 (1.06-1.26) 

Allergic Rhinitis with Asthma 

Lag 0: 1.07 (1.01-1.13) 

Lag 1: 0.96 (0.91-1.02) 

Lag 2: 0.93 (0.88-0.99) 

Lag 3: 0.96 (0.90-1.02) 

Lag 4: 1.08 (1.02-1.14) 

Allergic Rhinitis 

Lag 0: 1.06 (0.99-1.13) 

Lag 1: 1.08 (1.01-1.16) 

Lag 2: 0.92 (0.87-0.99) 

Lag 3: 0.97 (0.92-1.03) 

Lag 4: 1.09 (1.03-1.16) 

Upper Respiratory Disease 

Lag 0: 0.88 (0.68-1.14) 

Lag 1: 1.17 (0.91-1.51) 

Lag 2: 1.00 (0.76-1.31) 

Lag 3: 0.95 (0.76-1.19) 

Lag 4: 1.15 (0.97-1.35) 

Lower Respiratory Disease 

Lag 0: 1.01 (0.86-1.19) 

Lag 1: 1.04 (0.88-1.23) 

Lag 2: 1.04 (0.92-1.18) 

Lag 3: 1.23 (1.07-1.41) 

Lag 4: 0.99 (0.90-1.08) 

December 2009 E-250 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Tolbert et al. (2007, 

090316) 

Period of Study: 1993-2004 

Location: Atlanta Metropolitan area, 

Georgia 

Hospital Admissions/ED visits 

Outcome (ICD-9): 

Combined RD group, including: 

Asthma (493, 786.07, 786.09), COPD 

(491, 492, 496), URI (460-465, 460.0, 

477), pneumonia (480-486), and 

bronchiolitis (466.1, 466.11, and 

466.19)) 

Age Groups Analyzed: All 

Study Design: Time series 

N: 10,234,490 ER visits (283,360 and 

1,072,429 visits included in the CVD 

and RD groups, respectively) 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Long-term temporal trends, 

season (for RD outcome), temperature, 

dew point, days of week, federal 

holidays, hospital entry and exit 

Season: All 

Dose-response Investigated: No 

Statistical package: SAS version 9.1 

Lags Considered: 3-day ma(lag 0 -2) 

Pollutant: PM10 

Averaging Time: 24 h 

Mean (median 

IQR, range, 10th-90th percentiles): 

26.6 (24.8 

17.5-33.8 

0.5-98.4 

12.3-42.8) 

Monitoring Stations: NR 

Copollutant (correlation): 

O3: r = 0.59 

NO2: r = 0.53 

CO: r = 0.51 

SO2: r = 0.21 

Coarse PM: r = 0.67 

PM2.5: r = 0.84 

PM2.5 SO4: r = 0.69 

PM2.5 EC: r = 0.61 

PM2.5 OC: r = 0.65 

PM2.5 TC: r = 0.67 

PM2.5 water-sol metals: r = 0.73 

OHC: r = 0.53 

PM Increment: 16.30 μg/m3 (IQR) 

Risk ratio [95% CI]: 

Single pollutant models: 

RD: 1.015 (1.006-1.024) 

Notes: Results of selected multipollutant models for respiratory disease 

are presented in Fig 2. 

Fig 2: PM10 adjusted for CO, O3, NO2, 

or NO2/O3 (nonwinter months only) 

Summary of results: PM10 remained 

predictive of RD in non-winter months 

after adjustment for pollutants.

Reference: Tsai et al. (2006, 089768) 

Period of Study: 1996-2003 

Location: Kaohsiung City, Taiwan

Outcome: Asthma (493) 

Age Groups: All (universal health care 

covers >96% of the population) 

Study Design: Case crossover

N: 17,682 admissions 

63 hospitals 

Statistical Analyses: Conditional 

Logistic Regression 

Covariates: Temperature, humidity 

Season: Warm and cool seasons 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2 day cumulative

Pollutant: PM10

Averaging Time: 24-h avg

Mean (SD): 76.62 μg/m3

 (NR) 

Percentiles: 25th: 41.73 

50th(Median): 74.40 

75th: 104.01 

Range (Min, Max): (16.70, 232.00) 

Monitoring Stations: 6

Copollutant: NR

PM Increment: 62.28 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 

Single-pollutant model, 0-2 day 

cumulative lag 

≥ 25oC: 1.302 [1.155, 1.467] 

<25oC: 1.556 [1.398, 1.371] 

Two-pollutant models, 0-2 day 

cumulative lag 

PM10 w/ SO2

≥ 25oC: 1.305 [1.156, 1.473] 

<25oC: 1.540 [1.374, 1.727] 

PM10 w/ O3

≥ 25oC: 0.985 [0.842, 1.152] 

<25oC: 1.581 [1.402, 1.783] 

PM10 w/ NO2

≥ 25oC: 1.237 [1.052, 1.455] 

<25oC: 1.009 [0.875, 1.163] 

PM10 w/ CO 

≥ 25oC: 1.156 [1.012, 1.320] 

<25oC: 1.300 [1.134, 1.490]

December 2009 E-251 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ulirsch et al. (2007, 

091332) 

Period of Study: Nov 1994-Mar 2000 

Location: Pocatello, Idaho 

Chubbuck, Idaho

Outcome: Respiratory Disease (460-

499, 509-519) 

Reactive Airway Disease (786.09) 

Age Groups: All age groups

Study Design: Time series

N: 39,347 visits (TS1) 

29,513 visits (TS2) 

Statistical Analyses: Poisson 

regression, GLM. Sensitivity Analyses 

Covariates: Time, Temperature, 

Relative Humidity Influenza 

Season: Warm/Cool 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0-4 day lags 

Notes: Time series (TS) 1 includes HA, 

ED and urgent care visits. TS 2 includes 

family practice data available after 1997 

Pollutant: PM10

Averaging Time: NR

Mean (SD): TS1: 24.2 μg/m3

 (NR) 

10th: 10.5 

90th: 40.7 

TS2: 23.2 

10th: 10.0 

90th: 37.4 

Range (Min, Max): 

TS1: (3.0, 183.0) 

TS2: (3.0, 183.0) 

Monitoring Stations: 4

Notes: Copollutant (correlation): 

PM10 w/ NO2: r = 0.47. PM10 with other 

copollutants weakly correlated. 

PM Increment: Single Pollutant 

Models, TS1: 24.4 μg/m3

Single Pollutant Models: TS2: 

23.2 μg/m3

Multipollutant Models: TS1/TS2: 

50 μg/m3

Mean Percentage Change, lag 0 

TS 1: Single Pollutant 

All-age (all yr): 4.0 [1.4,6.7] 

18-64: 3.4 [0.2, 6.7] 

0-17: 4.3 [-0.1, 8.9] 

65+: 5.6 [-1.4, 13.1] 

0-17/65+: 5.5 [1.4, 9.6] 

All age (Cool season): 4.3 [1.3, 7.5] 

All age (Warm season): 6.7 [-0.8, 14.8] 

TS2: Single Pollutant 

All-age: 3.3 [0.3, 6.3] 

18-64: 3.3 [-0.4, 7.0] 

0-17: 5.0 [0.1, 10.1] 

65+: 6.9 [-0.4, 14.7] 

Multipollutant (PM10 + SO2) 

All-age (all yr): TS1 10.8 

TS2 17.5 

18-64: TS1 8.0 

TS2 9.1 

0-17: TS1 10.8 

TS2 32.7 

65+: TS1 8.7 

TS2 31.3 

0-17/65+: TS1 14.2 

TS2 25.3 

All age (Cool season) TS1 11.9 

Multipollutant (PM10 + NO2) 

All-age (all yr) TS1: TS2 16.3 

18-64: TS1 9.3 

TS2 17.3 

0-17: TS1 4.6 

TS2 18.7 

65+: TS1 12.4 

TS2 32.7 

0-17/65+: TS1 9.5 

32.7 

All age (Cool season): TS1 11.1 

TS2 16.8 

Notes: Results from multipollutant 

model with PM10, SO2 and NO2 also 

available. 

Reference: Vegni and Ros (2004, 

087448) 

Period of Study: Sep 2001-Sep 2002 

Location: Milan area, Italy 

Hospital Admissions 

Outcome (ICD-9): Respiratory, noninfectious admissions (ICD: NR) 

Age Groups: NR 

Study Design: Time series 

N: 9881 admissions 

Statistical Analyses: Poisson 

regression 

Covariates: Temperature, wind velocity, 

relative humidity, week day, holidays 

Season: Spring, summer, fall, winter 

Dose-response Investigated? No 

Statistical Package: STATA v. 5 

Lags Considered: 0, 1, and 2 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (5th-95th percentile): 

Overall: 41.5 (13-98) SD = 28.2 

Spring: 29.0 (10-51) SD = 12.6 

Summer: 24.8 (10-40) SD = 9.9 

Fall: 51.8 (21-114) SD = 27.1 

Winter: 64.1 (20-135) SD = 35.7 

Monitoring Stations: 1 

Copollutant: NR 

PM Increment: Increase from 5th-95th 

percentile 

Spring: 85 μg/m3

summer: 30 μg/m3

Fall: 93 μg/m3

Winter: 115 μg/m3

RR Estimate [CI]: 

Overall: 1.10 [0.83,1.46] 

Adjusted: 0.97 [0.67,1.41] 

Notes: 1-day and 2-day lags show 

similar results, with no association 

between PM10 and daily hospital 

admissions 

December 2009 E-252 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Vigotti et al. (2007, 090711) 

Period of Study: Jan 2000-Dec 2000 

Location: Pisa, Italy

ED Visits

Outcome: Asthmatic attack (493), dry 

cough (468), acute bronchitis (466) 

Age Groups: <10 yr; 65+ yr 

Study Design: Time series

N: 966 Emergency room visits 

Statistical Analyses: Poisson 

regression, GAM, LOESS smoothers, 

stringent criteria

Covariates: Temperature, humidity, 

relative humidity, day of study, rainfall, 

influenza, day of-the-wk, holidays, time 

trend 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-5 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 35.4 (15.8) μg/m3

Percentiles: 25th: NR 

50th(Median): 31.6 

75th: NR 

Range (Min, Max): (9.5, 100.1) 

Monitoring Stations: 

2 

Copollutant (correlation): 

PM10: 

NO2 r = 0.58 

CO r = 0.70

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

<10 y: 10%[2.3, 18.2] 

lag 1 

65+: 8.5% [1.5, 16.1] 

lag 2 

Reference: Xirasagar et al. (2006, 

093267) 

Period of Study: 1998-2001 

Location: Taiwan 

Hospital Admission/ED: 

Outcome: Asthma or Asthmatic 

Bronchitis (493) 

Age Groups: <2 yr old, 2~5 yr old, 

6~14 yr old 

Study Design: 

N: 27, 275 pediatric hospitalizations 

Statistical Analyses: ARIMA Modeling 

Spearman’s Correlations 

Covariates: Season, ambient temp., 

rel. humidity, atmospheric pressure, 

rainfall, h of sunshine 

Season: Spring: Feb-Apr 

Summer: May-Jul 

Fall: Aug-Oct 

Winter: Nov-Jan 

Dose-response Investigated? No 

Statistical Package: EViews 4 

Lags Considered: NR

Pollutant: PM10

Averaging Time: Monthly means 

Mean (SD): 24.4 μg/m3 (NR) 

Percentiles: NR

Range (Min, Max): NR 

PM Component: NR 

Monitoring Stations: 44 air quality 

monitoring banks. 23 weather 

observatories

Notes: Copollutant (correlation): 

<2 yr old: r = 0.315 

2~5 yr old: r = 0.589 

6~14 yr old: r = 0.493

PM Increment: NR 

RR Estimate [Lower CI, Upper CI] 

lag: NR 

AR Estimate [Lower CI, Upper CI] 

lag: NR 

Notes: Plot of monthly asthma 

admission rates per 100,000 population 

by age group 

Plot of mean monthly concentration 

trends of criteria air pollutants 

Mean monthly trends of climatic factors 

Other Outcomes Assessed? NR 

Other Exposures Assessed? 

Seasonality 

December 2009 E-253 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Wong et al., (2002, 

023232) 

Period of Study: 1995-1997 (Hong 

Kong) and 1992-1994 (London) 

Location: Hong Kong and London 

Hospital Admissions 

Outcome (ICD- NR): Asthma (493) for 

ages 15-64 and respiratory disease 

(460-519) for ages 65+ 

Age Groups: 15-64, 65+ 

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson 

regression, GAM 

Covariates: Temperature, humidity, and 

influenza 

Season: Warm (Apr-Sep) and cool 

(Oct-Mar) 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 

Lags Considered: 0-3 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): Hong Kong: 51.8 

(14.1-163.8) SD = 25.0 

London: 28.5 (6.8-99.8) 

SD = 13.7 

Monitoring Stations: NR 

Copollutant (correlation): 

Hong Kong 

NO2: r = 0.82 

SO2: r = 0.30 

O3: r = 0.54 

London 

NO2: r = 0.68 

SO2: r = 0.64 

O3: r = 0.17 

Other variables: Hong Kong 

Temp: r = -0.42 

Humidity: r = -0.53 

London 

Temp: r = 0.02 

Humidity: r = -0.05 

PM Increment: 10 μg/m3

ER Estimate [CI]: 

Single-pollutant excess risk (mean lag 

0-1 day) 

Asthma-Hong Kong: -1.1 [-2.4,0.1] 

Asthma-London: 1.4 [-0.1,3.0] 

Respiratory Disease-Hong Kong: 

1.0 [0.5,1.5] 

Respiratory Disease-London: 

0.4 [-0.3,1.2] 

Warm season 

Asthma-Hong Kong: -1.0 [-2.8, 0.8] 

Asthma-London: 0.6 [-1.9,3.1] 

Respiratory Disease-Hong Kong: 

0.8 [0.1,1.4] 

Respiratory Disease-London: 

1.8 [0.5,3.1] 

Cool season 

Asthma-Hong Kong: -1.2 [-2.8,0.4] 

Asthma-London: 1.6 [-0.3,3.6] 

Respiratory Disease-Hong Kong: 

1.2 [0.6,1.9] 

Respiratory Disease-London: 

-0.5 [-1.5,0.5] 

Notes: RRs are shown graphically in 

Fig 1 and 2. Exposure response curves 

are provided in Fig 5 of the article 

Reference: Wong et al. (2006, 093266) 

Period of Study: 2000-2002 

Location: Hong Kong (8 districts) 

General Practitioner Visits 

Outcome (ICPC-2): Respiratory 

diseases/symptoms: upper respiratory 

tract infections (URTI), lower respiratory 

infections, influenza, asthma, COPD, 

allergic rhinitis, cough, and other 

respiratory diseases 

Age Groups: All ages 

Study Design: Time series 

N: 269,579 visits 

Statistical Analyses: GAM, Poisson 

regression 

Covariates: Season, day of the week, 

climate 

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0-3 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): Ranged from 43.4-

56.9 (dependent on location) 

Monitoring Stations: 1 per district 

Copollutant (correlation): 

PM2.5: r = 0.94 

O3: r = 0.40 

SO2: r = 0.28 

PM Increment: 10 μg/m3

RR Estimate [CI]: 

Overall URTI 

1.020 [1.016,1.025] 

Overall Non-UTRI 

1.025 [1.018,1.032] 

Notes: RRs are also reported for each 

individual general practitioner yielding 

similar results 

December 2009 E-254 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yang et al. (2007, 092847) 

Period of Study: 1996-2003 

Location: Taipei, Taiwan

Hospital Admission/ED: 

Outcome: Asthma (493) 

Age Groups: All ages 

Study Design: Case-crossover

N: 25,602 asthma hospital admissions 

Statistical Analyses: NR 

Covariates: Temperature, humidity, day 

of-the-wk, seasonality, long term trends 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2

Pollutant: PM10

Averaging Time: NR 

Mean (SD): 48.99 μg/m3

Percentiles: 25th: 32.64 

50th(Median): 44.13 

75th: 59.05 

Range (Min, Max): (14.44, 234.91) 

PM Component: NR 

Monitoring Stations: 

6 Stations 

Notes: Copollutant: NR

PM Increment: 26.41 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 

Asthma 

Single-Pollutant Model: Temperature 

>25° C: 1.046[0.971, 1.128] 

Temperature <25° C: 

1.048[1.011, 1.251] 

Two-Pollutant Model: Adjusted for SO2: 

>25° C-1.006[0.920, 1.099] 

<25° C-1.088[1.040, 1.138] 

Adjusted for NO2: 

>25° C-0.800[0.717, 0.892] 

<25° C-0.982[0.937, 1.029] 

Adjusted for CO: 

>25° C-0.920[0.844, 1.002] 

<25° C-1.029[0.984, 1.076] 

Adjusted for O3: 

>25° C-1.038[0.950, 1.134] 

<25° C-1.042[1.004, 1.081]

AR Estimate [Lower CI, Upper CI] 

lag: NR 

Notes: Other Outcomes Assessed? 

NR 

Other Exposures Assessed? SO2, 

NO2, CO, O3

Reference: Yang et al. (2007, 092847) 

Period of Study: 1996-2003 

Location: Taipei, Taiwan

Hospital Admission 

Outcome: COPD (490-192), (494), 

(496) 

Age Groups: All ages 

Study Design: Case-crossover

N: 46,491COPD admissions, 47 

hospitals 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Weather, day of-the-wk, 

seasonality, long term trends 

Season: Warm/Cool 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-2 cumulative

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 48.99 μg/m3

25th: 32.64 

50th(Median): 44.13 

75th: 59.05 

Range (Min, Max): 

(14.44, 48.99) 

Monitoring Stations: 

6 Stations 

Notes: Copollutant: NR

PM Increment: 26.41 μg/m3

OR Estimate [Lower CI, Upper CI] 

Single-Pollutant Model (0-2 day cum 

lag): 

Temperature >20° C: 1.133[1.098, 

1.168] 

Temperature <20° C: 1.035[0.994, 

1.077] 

Two-Pollutant Model: 

PM10 w/ SO2: 

>20° C-1.180[1.139, 1.223] 

<20° C-1.004[0.954, 1.057] 

PM10 w/ NO2: 

>20° C-1.013[0.973, 1.055] 

<20° C-1.074[1.022, 1.129] 

PM10 w/ CO: 

>20° C-1.061[1.023, 1.100] 

<20° C-1.067[1.016, 1.120] 

PM10 w/ O3: 

>20° C-1.097[1.062, 1.133] 

<20° C-1.036[0.996, 1.079]

December 2009 E-255 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yang et al. (2004, 087488) 

Period of Study: Jun 1995-Mar 1999 

Location: Vancouver area, British 

Columbia 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

diseases (460-519), pneumonia only 

(480-486), asthma only (493) 

Age Groups: 0-3 yr 

Study Design: Case control, 

bidirectional case-crossover (BCC), and 

time series (TS) 

N: 1610 cases 

Statistical Analyses: Chi-square test, 

Logistic regression, GAM (time-series), 

GLM with parametric natural cubic 

splines 

Covariates: Gender, socioeconomic 

status, weekday, season, study yr, 

influenza epidemic month 

Season: Spring, summer, fall, winter 

Dose-response Investigated? No 

Statistical Package: SAS (Case 

control and BCC), S-Plus (TS) 

Lags Considered: 0-7 days

Pollutant: PM10

Averaging Time: 24 h 

Mean (min-max): 

13.3 (3.8-52.2) 

SD = 6.1 

Monitoring Stations: NR (data 

obtained from Greater Vancouver 

Regional District Air Quality Dept) 

Copollutant (correlation): 

PM2.5: r = 0.83 

PM10-2.5: r = 0.83 

CO: r = 0.46 

O3: r = -0.08 

NO2: r = 0.54 

SO2: r = 0.61 

PM Increment: 7.9 μg/m3 (IQR) 

OR Estimate [CI]: 

Values NR 

Notes: Author states that ORs for PM10

increased with lag time up to 3 days for 

both single and multiple-pollutant 

models. 

1

All units expressed in μg/m3 unless otherwise specified.

Table E-13. Short-term exposure-respiratory-ED/HA-PM10-2.5. 

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chen et al. 

(2005, 087555) 

Period of Study: 

Jun 1995-Mar 1999 

Location: Vancouver area, 

BC 

Hospital Admissions 

Outcome (ICD-9): Acute respiratory 

infections (460-466), upper 

respiratory tract infections (470-478), 

pneumonia and influenza (480-487), 

COPD and allied conditions (490-

496), other respiratory diseases (500-

519) 

Age Groups: >65 yr 

Study Design: Time series 

N: 12,869 

Statistical Analyses: GLM 

Covariates: Temp and relative 

humidity

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 1, 2, 3, 4, 5, 6, 

and 7-day avg 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 24 h 

Mean (min-max): 

5.6 (0.1-24.6) 

SD = 3.6 

Monitoring Stations: 13 

Copollutant (correlation): 

PM2.5: r = 0.38 

PM10: r = 0.83 

COH: r = 0.63 

CO: r = 0.53 

O3: r = -0.13 

NO2: r = 0.54 

SO2: r = 0.57 

Other variables: 

Mean temp: r = 0.13 

Rel humidity: r = -0.27 

PM Increment: 4.2 μg/m3

RR Estimate [CI]: 

Adj for weather conditions 

Overall admission 

1-day avg: 1.03 [1.00,1.06] 

2-day avg: 1.05 [1.02,1.08] 

3-day avg: 1.06 [1.02,1.09] 

Adj for weather conditions and copollutants 

Overall admission 

1-day avg: 1.02 [0.98,1.06] 

2-day avg: 1.05 [1.01,1.10] 

3-day avg: 1.06 [1.02,1.11] 

Notes: RR’s were also provided for lags 4-7 in Table 3, 

yielding similar results 

December 2009 E-256 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Fung et al. (2006, 

089789)

Period of Study: 

Jun 1995-Mar 1999 

Location: Vancouver, 

Canada

Hospital Admission/ED: Hospital 

Admission 

Outcome: Respiratory diseases 

(460-519) 

Age Groups: Age >65 

Study Design: Time series

N: 26,275 individuals admitted 

Statistical Analyses: Poisson 

regression (spline 12 knots), casecrossover (controls +/7 days from 

case date), Dewanji and Moolgavkar 

(DM) method 

Covariates: Long-term trends, dayof-the-week effect, weather 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SPlus, R 

Lags Considered: 0-7 days 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 24-h avg

Mean (SD) 

5.6(3.88) μg/m3

Range (Min, Max): 

(-2.9, 27.07) 

Monitoring Stations: 

NR 

Notes: Copollutant 

(correlation): 

PM10-2.5

PM10 r = 0.83 

PM2.5 r = 0.34 

CO r = 0.51 

CoH r = 0.61 

O3 r = -0.11 

NO2 r = 0.52 

SO2 r = 0.57

PM Increment: : 

4.3 μg/m3

RR Estimate (65+ yr) 

DM method: 

1.011[0.998,1.024] lag 0 

1.016[1.0,1.032] 3-day avg 

1.020[1.001,1.039] 5-day avg 

1.020[0.998,1.042] 7-day avg

Time series: 

1.0168[1.003, 1.031] lag 0 

1.020[1.003, 1.037] 3-day avg 

1.019[0.999, 1.039] 5-day avg 

1.018[0.994, 1.042] 7-day avg

Case-crossover: 

1.019[1.003, 1.034] lag 0 

1.019[1.009, 1.038] 3-day avg 

1.020[0.999, 1.042] 5-day avg 

1.018[0.994, 1.043] 7-day avg 

Reference: Halonen et al. 

(2009, 180379) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome: Hospital Admissions 

Age Groups: 65+ yr

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson, GAM 

Covariates: Temperature, humidity, 

influenza epidemics, high pollen 

episodes, holidays 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: Lags 0-3 & 5-day 

(0-4) mean 

Pollutant: PM10-2.5 

Averaging Time: Daily 

Mean (SD): NR

Min: 0.0 

25th percentile: 4.9 

50th percentile: 7.5 

75th percentile: 12.1 

Max: 101.4

Monitoring Stations: NR 

Copollutant: 

PM<0.03, PM0.03-0.1, PM<0.1, 

PM<0.10.29, PM2.5, CO, NO2

Co-pollutant Correlation 

PM<0.03: 0.14 

PM0.03-0.1: 0.28 

PM<0.1: 0.24 

PM<0.10.29: 0.20 

PM2.5: 0.25 

PM Increment: Interquartile Range 

Percent Change (Lower CI, Upper CI): 

All Respiratory Mortality 

Lag 0: -0.66 (-4.16, 2.97) 

Lag 1: 2.90 (-0.48, 6.39) ‡ 

Lag 2: 0.35 (-3.03, 3.84) 

Lag 3: -0.38 (-3.67, 3.02) 

5-day mean: 0.36 (-4.54, 5.51) 

Pneumonia HA 

Lag 0: 0.72 (-1.28, 2.77) 

Lag 1: 0.55 (-1.34, 2.49) 

Lag 2: 0.65 (-1.24, 2.58) 

Lag 3: 0.03 (-1.86, 1.96) 

5-day mean: 

Asthma + COPD HA 

Lag 0: 2.49 (0.47, 4.56)* 

Lag 1: 1.37 (-0.66, 3.44) 

Lag 2: 0.7 (-1.36, 2.80) 

Lag 3: 1.97 (-0.02, 4.00)‡ 

5-day mean: 2.67 (-0.17, 5.58)‡ 

Other HA 

Lag 0: 1.38 (-1.24, 4.06) 

Lag 1: -1.62 (-4.22, 1.05) 

Lag 2: -1.25 (-3.88, 1.45) 

Lag 3: 0.04 (-2.52, 2.67) 

5-day mean: 0.24 (-3.62, 4.26) 

*p < 0.05, ‡p < 0.10 

December 2009 E-257 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Host et al. (2007, 

155851) 

Period of Study: 2000-2003

Location: Six French cities: 

Le Havre, Lille, Marseille, 

Paris, Rouen, and Toulouse 

Outcome (ICD-10): Daily 

hospitalizations for all respiratory 

diseases (J00-J99), respiratory 

infections (J10-J22). 

Age Groups: For all respiratory 

diseases: 0-14 yr, 15-64 yr, and ≥

65 yr 

For respiratory infections: All ages

Study Design: Time series

N: NR (Total population of cities: 

approximately 10 million) 

Statistical Analyses: Poisson 

regression 

Covariates: Seasons, days of the 

week, holidays, influenza epidemics, 

pollen counts, temperature, and 

temporal trends

Dose-response Investigated: No

Statistical Package: MGCV package 

in R software (R 2.1.1) 

Lags Considered: Avg of 0-1 days 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean μg/m3 (5th -95th 

percentile): 

Le Havre: 7.3 (2.5-14.0) 

Lille: 7.9 (2.2-13.7) 

Marseille: 11.0 (4.5-21.0) 

Paris: 8.3 (3.2-15.9) 

Rouen: 7.0 (3.0-12.5) 

Toulouse: 7.7 (3.0-15.0) 

Monitoring Stations: 

13 total: 1 in Toulouse 

4 in Paris 

2 each in other cities 

Copollutant (correlation): 

PM2.5: Overall: r>0.6 

Ranged between r = 0.28 and 

r = 0.73 across the six cities. 

PM Increment: 10 μg/m3 , and an 18.8 μg/m3 increase 

(corresponding to an increase in pollutant levels between 

the lowest of the 5th percentiles and the highest of the 95th 

percentiles of the cities’ distributions) 

ERR (excess relative risk) Estimate [CI]: For all respiratory 

diseases (10 μg/m3

 increase): 0-14 yr: 6.2% [0.4, 12.3] 

15-64 yr: 2.6% 

[-0.5, 5.8] 

≥ 65 yr: 1.9% [-1.9, 5.9] 

For all respiratory diseases (18.8 μg/m3

 increase): 0-14 yr: 

12.0 [0.8, 24.3] 

15-64 yr: 5.0 [-0.9, 11.1] 

≥ 65 yr: 3.7 [-3.6, 11.4] 

For respiratory infections (10 μg/m3

): All ages: 4.4% [0.9, 

8.0] 

For respiratory infections (18 μg/m3

): All ages: 8.4% [1.7, 

15.5]

Reference: Lin et al. (2005, 

087828) 

Period of Study: 1998-2001 

Location: Toronto, North 

York, East York, Etobicoke, 

Scarborough, and York 

(Canada) 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

infections including laryngitis, 

tracheitis, bronchitis, bronchiolitis, 

pneumonia, and influenza (464, 466, 

480-487) 

Age Groups: 0-14 yr 

Study Design: Bidirectional casecrossover 

N: 6782 respiratory infection 

hospitalizations 

Statistical Analyses: Conditional 

logistic regression (Cox proportional 

hazards model) 

Covariates: Daily mean temp and 

dew point temp

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 8.2 

PHREG procedure 

Lags Considered: 1- to 7-day avg 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 24 h 

Mean (min-max): 

10.86 (0-45.00) 

SD = 5.37 

Monitoring Stations: 4 

Copollutant (correlation): 

PM2.5: r = 0.33 

PM10: r = 0.76 

CO: r = 0.06 

SO2: r = 0.29 

NO2: r = 0.40 

O3: r = 0.30 

PM Increment: 6.5 μg/m3

OR Estimate [CI]: 

Adjusted for weather 

4-day avg: 1.16 [1.07,1.26] 

6-day avg: 1.21 [1.10,1.32] 

Adj for weather and other gaseous pollutants 

4-day avg: 1.13 [1.03,1.23] 

6-day avg: 1.17 [1.06,1.29] 

Notes: OR’s were also categorized into “Boys” and “Girls,” 

yielding similar results 

December 2009 E-258 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lin et al. (2002, 

026067) 

Period of Study: 

Jan 1981-Dec 1993 

Location: Toronto 

Hospital Admissions 

Outcome (ICD-9): Asthma (493) 

Age Groups: 6-12 yr 

Study Design: Uni- and bi-directional 

case-crossover (UCC, BCC) and 

time-series (TS) 

N: 7,319 asthma admissions 

Statistical Analyses: Conditional 

logistic regression, GAM 

Covariates: Maximum and minimum 

temp, avg relative humidity

Season: Apr-Sep, Oct-Mar 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1- to 7-day avg 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 6 days 

(predicted daily values) 

Mean (min-max): 

12.17 (0-68.00) 

SD = 7.55 

Monitoring Stations: 1 

Copollutant (correlation): 

PM2.5: r = 0.44 

PM10: r = 0.83 

CO: r = 0.17 

SO2: r = 0.28 

NO2: r = 0.38 

O3: r = 0.56 

PM Increment: 8.4 μg/m3

RR Estimate [CI]: 

Adj for weather and gaseous pollutants 

BCC 5-day avg: 1.14 [1.01,1.28] 

BCC 6-day avg: 1.17 [1.03,1.33] 

TS 5-day avg: 1.14 [1.05,1.23] 

TS 6-day avg: 1.15 [1.06,1.25] 

Boys-adj for weather 

UCC 1-day avg: 1.08 [1.01,1.16] 

UCC 2-day avg: 1.08 [0.99,1.17] 

BCC 1-day avg: 1.06 [1.00,1.14] 

BCC 2-day avg: 1.06 [0.98,1.14] 

TS 1-day avg: 1.08 [1.03,1.12] 

TS 2-day avg: 1.07 [1.01,1.13] 

Girls-adj for weather 

UCC 1-day avg: 1.07 [0.97,1.18] 

UCC 2-day avg: 1.16 [1.03,1.31] 

BCC 1-day avg: 0.98 [0.90,1.07] 

BCC 2-day avg: 1.05 [0.94,1.16] 

TS 1-day avg: 1.00 [0.94,1.06] 

TS 2-day avg: 1.05 [0.98,1.13] 

Notes: The author also provides RR using UCC, BCC, and 

TS analysis for female and male groups for day 3-7, yielding 

similar results 

Reference: Peel et al. (2005, 

056305) 

Period of Study: 

Jan 1993-Aug 2000 

Location: Atlanta, Georgia

ED visits 

Outcome: Asthma (493, 786.09) 

COPD (491, 492, 496) 

URI (460-466, 477) 

Pneumonia (480-486) 

Age Groups: All ages. Secondary 

analyses conducted by age group: 0-

1, 2-18, >18 

Study Design: Time series

N: 31 hospitals 

Statistical Analyses: Poisson GEE 

for URI, asthma and all RD 

Poisson GLM for pneumonia and 

COPD) 

Covariates: Avg temperature and 

dew point, pollen counts 

Season: All (secondary analyses of 

warm season) 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.3 

S-Plus 2000 

Lags Considered: 0-7 days, 3-day 

ma, 0-13 days unconstrained 

distributed lag 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 24 h avg 

Mean (SD): 9.7 (4.7) 

Percentiles: 10th: 4.4 

90th: 16.2 

Monitoring Stations: 

“Several” 

Copollutant (correlation): 

24 h PM10: r = 0.59 

8 h O3: r = 0.35 

1 h NO2: r = 0.46 

1 h CO: r = 0.32 

1 h SO2: r = 0.21 

24 h PM2.5: r = 0.43 

Components: r ranged from 

0.23-0.51 

PM Increment: 5 

RR Estimate [Lower CI, Upper CI] 

All Respiratory Outcomes: 1.003 [0.982, 1.025] 

URI: 1.013 [0.987, 1.039] 

Asthma: 0.998 [0.987, 1.039] 

Pneumonia: 0.975 [0.940, 1.011] 

COPD: 0.948 [0.897, 1.003] 

December 2009 E-259 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peng et al. (2008, 

156850) 

Period of Study: Jan 

1999-Dec 2005

Location: 108 U.S. counties 

in the following states: 

Alabama, Arizona, California, 

Colorado, Connecticut, 

District of Columbia, Florida, 

Georgia, Idaho, Illinois, 

Indiana, Kentucky, Louisiana, 

Maine, Maryland, 

Massachusetts, Michigan, 

Minnesota, Missouri, Nevada, 

New Hampshire, New Jersey, 

New Mexico, New York, North 

Carolina, Ohio, Oklahoma, 

Oregon, Pennsylvania, Rhode 

Island, South Carolina, 

Tennessee, Texas, Utah, 

Virginia, Washington, West 

Virginia, Wisconsin 

Outcome (ICD-9): Emergency 

hospitalizations for respiratory 

disease, including COPD (490-492) 

and respiratory tract infections 

(464-466, 480 - 487) 

Age Groups: 65 + yr, 65-74, ,75 +

Study Design: Time series

N: Approximately 12 million Medicare 

enrollees (1.4 million RD admissions) 

Statistical Analyses: Two-stage 

Bayesian hierarchical models: Over 

dispersed Poisson models for countyspecific data. Bayesian hierarchical 

models to obtain national avg 

estimate 

Covariates: Day of the week, agespecific intercept, temperature, dew 

point temperature, calendar time, 

indicator for age of 75 yr or older. 

Some models were adjusted for 

PM2.5. 

Dose-response Investigated: No

Statistical Package: R version 2.6.2 

Lags Considered: 0-2 days 

Pollutant: PM10-2.5 

Averaging Time: 24 h 

Mean (IQR): All counties 

assessed: 9.8 (6.9-15.0) 

Counties in Eastern U.S.: 9.1 

(6.6-13.1) 

Counties in Western U.S.: 15.4 

(10.3-21.8) 

Monitoring Stations: At least 1 

pair of co-located monitors 

(physically located in the same 

place) for PM10 and PM2.5 per 

county 

Copollutant (correlation): 

PM2.5: r = 0.12 

PM10: r = 0.75 

Other variables: Median withincounty correlations between 

monitors: r = 0.60 

PM Increment: 10 μg/m3 

Percentage change [95% CI]: Respiratory disease (RD): 

Lag 0 (unadjusted for PM2.5): 0.33 [-0.21, 0.86] 

Lag 0 (adjusted for PM2.5): 0.26 [-0.32, 0.84] 

Most values NR (see note) 

Notes: Fig 3: Percentage change in emergency hospital 

admissions for RD per 10 μg/m3

 increase in PM (single 

pollutant model and model adjusted for PM2.5 concentration) 

Fig 4: Percentage change in emergency hospital 

admissions rate for CVD and RD per a 10 μg/m3

 increase in 

PM10-2.5 (0-2 day lags, Eastern vs.. Western USA) 

Reference: Slaughter et al. 

(2005, 073854) 

Period of Study: 

Jan 1995-Jun 2001 

Location: Spokane, WA 

Hospital Admissions and ED visits 

Outcome: All respiratory (460-519) 

Asthma (493) 

COPD (491,492, 494,496) 

Pneumonia (480-487) 

Acute URI not including colds and 

sinusitis (464, 466, 490) 

Age Groups: All, 15+ yr for COPD 

Study Design: Time series

N: 2373 visit records 

Statistical Analyses: Poisson 

regression, GLM with natural splines. 

For comparison also used GAM with 

smoothing splines and default 

convergence criteria. 

Covariates: Season, temperature, 

relative humidity, day of week 

Season: All 

Dose-response Investigated?: No 

Statistical Package: SAS, SPLUS 

Lags Considered: 1 -3 days 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 24 h avg 

Range (90% of 

Concentrations): Reported for 

PM2.5 and PM10 only 

Monitoring Stations: 1

Copollutant (correlation): 

PM10-2.5

PM1 r = 0.19 

PM2.5 r = 0.31 

PM10 r = 0.94 

CO r = 0.32 

Temperature r = 0.11 

PM Increment: 25 μg/m3 

RR Estimate [Lower CI, Upper CI] lag: 

ER visits: 

PM10-2.5 

All Respiratory 

Lag 1: 1.01 [0.98, 1.04] 

Lag 2: 1.01 [0.98, 1.04] 

Lag 3: 1.02 [0.99, 1.05] 

Acute Asthma 

Lag 1: 1.03 [0.98, 1.08] 

Lag 2: 1.01 [0.96, 1.07] 

Lag 3: 0.99 [0.94, 1.05] 

COPD (adult) 

Lag 1: 1.01 [0.93, 1.09] 

Lag 2: 0.98 [0.90, 1.06] 

Lag 3: 1.02 [0.95, 1.10] 

December 2009 E-260 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Tecer et al. 

(2008, 180030) 

Period of Study: 

Dec 2004-Oct 2005 

Location: Zonguldak, Turkey 

Outcome: ED visits for respiratory 

problems (ICD-9 470-478, 493) 

Study Design: Bidirectional Casecrossover 

Covariates: Daily meteorological 

parameters 

Statistical Analysis: Conditional 

logistic regression 

Statistical Package: Stata 

Age Groups: 0-14 yr 

Pollutant: PM10-2.5

Averaging Time: NR 

Mean, Unit: 24.3 μg/m3

Range (Min, Max): 4, 195.8 

Copollutant (correlation): 

PM2.5/PM10-2.5

Mean: 1.49 

Range: 0.21, 7.53 

Increment: 10 μg/m3

Odds Ratio (95% CI)

Asthma 

Lag 0: 1.18 (1.01-1.39) 

Lag 1: 0.92 (0.78-1.08) 

Lag 2: 0.98 (0.84-1.15) 

Lag 3: 1.11 (0.97-1.27) 

Lag 4: 1.17 (1.05-1.31) 

Allergic Rhinitis with Asthma 

Lag 0: 0.96 (0.88-1.04) 

Lag 1: 1.08 (0.99-1.18) 

Lag 2: 0.93 (0.86-1.02) 

Lag 3: 0.94 (0.86-1.03) 

Lag 4: 1.10 (1.03-1.18) 

Allergic Rhinitis 

Lag 0: 1.06 (0.95-1.19) 

Lag 1: 1.17 (1.04-1.31) 

Lag 2: 0.92 (0.84-1.02) 

Lag 3: 0.99 (0.91-1.08) 

Lag 4: 1.15 (1.06-1.25) 

Upper Respiratory Disease 

Lag 0: 0.80 (0.54-1.19) 

Lag 1: 1.22 (0.92-1.61) 

Lag 2: 0.97 (0.70-1.33) 

Lag 3: 0.94 (0.66-1.33) 

Lag 4: 1.08 (0.88-1.32) 

Lower Respiratory Disease 

Lag 0: 0.90 (0.71-1.16) 

Lag 1: 1.20 (0.97-1.50) 

Lag 2: 1.00 (0.84-1.19) 

Lag 3: 1.26 (1.08-1.47) 

Lag 4: 1.02 (0.93-1.13) 

Reference: Yang et al., 

(2004, 087488) 

Period of Study: 

Jun 1995-Mar 1999 

Location: Vancouver area, 

British Columbia 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

diseases (460-519), pneumonia only 

(480-486), asthma only (493) 

Age Groups: 0-3 yr 

Study Design: Case control, 

bidirectional case-crossover (BCC), 

and time series (TS) 

N: 1610 cases 

Statistical Analyses: Chi-square 

test, Logistic regression, GAM (timeseries), GLM with parametric natural 

cubic splines 

Covariates: Gender, socioeconomic 

status, weekday, season, study yr, 

influenza epidemic month

Season: Spring, summer, fall, winter 

Dose-response Investigated? No 

Statistical Package: SAS (Case 

control and BCC), S-Plus (TS) 

Lags Considered: 0-7 days 

Pollutant: PM10-2.5 (μg/m3) 

Averaging Time: 24 h 

Mean (min-max): 

5.6 (0-24.6) 

SD = 3.6 

Monitoring Stations: NR (data 

obtained from Greater 

Vancouver Regional District Air 

Quality Dept) 

Copollutant (correlation): 

PM2.5: r = 0.39 

PM10: r = 0.83 

CO: r = 0.33 

O3: r = -0.16 

NO2: r = 0.37 

SO2: r = 0.54 

PM Increment: 4.2 μg/m3 (IQR) 

OR Estimate [CI]: 

3-day lag 

1.12 [0.98,1.28] 

Adj for gaseous pollutants: 1.22 [1.02,1.48] 

Notes: Author states that ORs for PM10-2.5 increased with lag 

time up to 3 days for both single and multiple-pollutant 

models. More adjusted ORs and RRs are provided in Fig 1. 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-261 
Table E-14. Short-term exposure-respiratory-ED/HA-PM2.5 (including PM components/sources). 

Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Andersen et al. (2008, 

189651) 

Period of Study: May 2001-Dec 2004

Location: Copenhagen, Denmark 

Outcome (ICD-10): RD, including 

chronic bronchitis (J41-42), 

emphysema (J43), other chronic 

obstructive pulmonary disease (J44), 

asthma (J45), and status asthmaticus 

(J46). Pediatric hospital admissions for 

asthma (J45) and status asthmaticus 

(J46). 

Age Groups: > 5-18 yr (asthma)

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson GAM 

Covariates: Temperature, dew-point 

temperature, long-term trend, 

seasonality, influenza, day of the week, 

public holidays, school holidays (only 

for 5-18 yr olds), pollen (only for 

pediatric asthma outcome) 

Season: NR

Dose-response Investigated: No

Statistical Package: R statistical 

software (gam procedure, mgcv 

package) 

Lags Considered: Lag 0-5 days, 4-day 

pollutant avg (lag 0-3) for CVD, 5-day 

avg (lag 0-4) for RD, and a 6-day avg 

(lag 0-5) for asthma. 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean μg/m3 (SD): 10(5) 

Median: 9 

IQR: 7-12 

99th percentile: 28 

Monitoring Stations: 1 

Copollutant (correlation): 

NCtot: r = 0.40 

NC100: r = 0.29 

NCa12: r = 0.07 

Nca23: r = -0.25 

NCa57: r = 0.51 

NCa212: r = 0.82 

PM10: r = 0.80 

CO: r = 0.46 

NO2: r = 0.42 

: r = 0.40 

NOX curbside: r = 0.28 

O3: r = -0.20 

Other variables: 

Temperature: r = -0.01 

Relative humidity: r = 0.21 

PM Increment: 5 μg/m3 (IQR) 

Relative risk (RR) Estimate [CI]: RD 

hospital admissions (5-day avg, lag 

0-4), age 65+: 

One-pollutant model: 1.00 [0.95-1.00] 

Adj for NCtot: 1.00 [0.95-1.06] 

Asthma hospital admissions (6-day avg 

lag 0-5), age 5-18: 

One-pollutant model: 1.15 [1.00-1.32] 

Adj for NCtot: 1.13 [0.98-1.32] 

Estimates for individual day lags 

reported only in Fig form (see notes): 

Notes: RD: No statistically or marginally 

significant associations. Positive 

associatons at Lag 4-5.Asthma: Wide 

confidence intervals make interpretation 

dificult. Positive associations at Lag 1, 

2, 3. 

Reference: Babin et al. (2007, 093250) 

Period of Study: Oct 2001-Sep 2004 

Location: Washington, DC 

ED Visit/Admissions 

Outcome: Asthma-493 

Age Groups: 1-17 yr,1-4, 5-12, 13-17 

Study Design: Time-series

N: NR 

Statistical Analyses: Poisson 

regression, spline w/ 12 knots to adjust 

for long term trend 

Covariates: Temperature, mold, pollen, 

seasonal trends, 

Season: All 

Dose-response Investigated?No 

Statistical Package: STATA 

Lags Considered: 0-4

Pollutant: PM2.5

Averaging Time: 24 h 

Mean: “low, never reached code red” 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: 3 

Copollutant (correlation): NR 

PM Increment: 1 μg/m3

%Change ED Visits 

Ages 5-12: 

-0.2 (-0.6,0.2), lag 0 

% Change ED Admissions: 

Ages 5-12: 

-0.4 (-1.6,0.8), lag 0 

Ages 1-17: 

 0.2 (-0.6,1.1), lag 0 

AR Estimate [Lower CI, Upper CI] lag: 

NR 

Notes: No significant interactions 

between PM and O3 or other covariates 

were observed. 

December 2009 E-262 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Barnett et al. (2005, 

087394) 

Period of Study: 1998-2001 

Location: 5 Australian cities (Brisbane, 

Canberra, Melbourne, Perth, and 

Sydney) and 2 New Zealand cities 

(Auckland, Christchurch) 

Outcome (ICD: NR): All respiratory 

admissions (including asthma, 

pneumonia, and acute bronchitis) 

Age Groups: Children aged <1 yr, 1-

4 yr, and 5-14 yr 

Study Design: Matched casecrossover 

N: ~2.4 million children <15 yr old 

Statistical Analyses: Random effects 

meta-analysis 

Covariates: Temperature, current 

minus previous day’s temperature, 

relative humidity, pressure, extremes 

of hot and cold, day of the week, 

public holiday, and day after public 

holiday

Season: Warm (Nov-Apr) and Cool 

(May-Oct) 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: NR 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (min-max): 

Auckland (A): 11.0 (2.1-37.6) 

Brisbane (B): 9.7 (3.2-122.8) 

Canberra (Ca): NR 

Christchurch (Ch): NR 

Melbourne (M): 8.9 (2.8-43.3) 

Perth (P): 8.1 (1.7-29.3) 

Sydney (S): 9.4 (2.4-82.1) 

Monitoring Stations: 1-3 per city 

Copollutant: NR 

PM Increment: 3.8 μg/m3 (IQR) 

Percent Increase Estimate [CI]: 

Pneumonia & Acute Bronchitis: 

Single Pollutant Model 

<1 yr (B,M,P,S): 1.7 [ 0.0,3.4] 

1-4 yr (B,M,P,S): 2.4 [0.1,4.7] 

Matched Multipollutant Model 

1-4 yr with 1-h SO2 (B,S): 1.9 [-1.7,5.6] 

1-4 yr with temp (B,M,P,S): 2.3 [-0.4,5.1]

Respiratory Admissions: 

Single Pollutant Model 

<1 yr (B,M,P,S): 2.4 [1.0,3.8] 

1-4 yr (B,M,P,S): 1.7 [0.7,2.7] 

Matched Pollutant Model 

<1 yr with 1-h SO2 (B,S): 3.1 [0.5,5.7] 

<1 yr with temp (B,M,P,S): 1.8 [0.2,3.4] 

1-4 yr with PM10 (B,M,P,S): 2.9 [0.2,5.6] 

1-4 yr with 1-h SO2 (B,S): 1.3 [-1.8,4.4] 

1-4 yr with 1-h NO2 (B,M,P,S): 

-1.5 [-3.2,0.2] 

1-4 yr with temp (B,M,P,S,): 

1.5 [-0.2,3.1] 

Reference: Bell et al. (2008, 091268) 

Period of Study: 1995-2002

Location: Taipei, Taiwan 

Outcome (ICD-9): Hospital admissions 

for asthma (493), and pneumonia (486). 

Age Groups: All

Study Design: Time series 

N: 19,966 hospital admissions for 

pneumonia, and 10,231 for asthma 

Statistical Analyses: Poisson 

regression 

Covariates: Day of the week, time, 

apparent temperature, long-term trends, 

seasonality 

Season: All

Dose-response Investigated: No

Statistical Package: NR 

Lags Considered: lags 0-3 days, mean 

of lags 0-3 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (range 

IQR): 31.6 (0.50-355.0 

20.2) 

Monitoring Stations: 2 

Copollutant (correlation): NR 

PM Increment: 20 μg/m3 (near IQR) 

Percentage increase estimate [95% CI]: 

Asthma: L0: 0.46 (-2.41, 3.42) 

L1: -1.36 (-4.33, 1.71) 

L2: -0.83 (-3.67, 2.10) 

L3: -0.78 (-3.63, 2.16) 

L03: -1.75 (-6.21, 2.92) 

Pneumonia: L0: 0.06 (-2.74, 2.94) 

L1: 0.34 (-2.446, 3.20) 

L2: -0.59 (-3.38, 2.29) 

L3: -0.44 (-3.22, 2.41) 

L03: -0.61 (-4.87, 3.85) 

Reference: Bell et al. (2008, 091268) 

Period of Study: 1999-2005

Location: 202 U.S. counties 

Outcome (ICD-9): COPD (490-492), 

respiratory tract infections (464-466, 

480-487) 

Age Groups: 65+

Study Design: Time series 

N: NR 

Statistical Analyses: Two-stage 

Bayesian hierarchical model to find 

national avg 

First stage: Poisson regression (countyspecific) 

Covariates: Day of the week, 

temperature, dew point temperature, 

temporal trends, indicator for persons 

75+ yr, population size 

Season: All, Jun-Aug (Summer), 

Sep-Nov (Fall), Dec-Feb (Winter), 

Mar-May (Spring)

Dose-response Investigated: No

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (μg/m3): 

Descriptive information presented in Fig 

S2 (boxplots): 

IQR: 8.7 μg/m3

Monitoring Stations: NR 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3 

Percent increase [95% PI]: 

Respiratory admissions: 

Lag 0 (all seasons): 0.22 [-0.12-0.56] 

Lag 0 (winter, national): 1.05 [0.29-1.82]

Lag 0 (winter, northeast): 

1.76 [0.60-2.93] 

Lag 0 (winter, southeast): 

0.59 [-1.35-2.58] 

Lag 0 (winter, northwest): 

-0.07 [-6.74-7.08] 

Lag 0 (winter, southwest): 

0.03 [-1.25-1.34] 

Lag 0 (spring, national): 

0.31 [-0.47-1.11] 

Lag 0 (spring, northeast): 

0.34 [-0.66-1.34] 

Lag 0 (spring, southeast): 

-0.06 [-1.77-1.68] 

Lag 0 (spring, northwest): 

-8.52 [-25.62-12.51] 

Lag 0 (spring, southwest): 

1.87 [-2.00-5.90] 

Lag 0 (summer, national): 

-0.62 [-1.33-0.09] 

December 2009 E-263 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Statistical Package: NR 

Lags Considered: 0-2 day lags 

Lag 0 (summer, northeast): 

-0.8 [-1.65-0.07] 

Lag 0 (summer, southeast): 

-0.15 [-1.88-1.61] 

Lag 0 (summer, northwest): 

0.25 [-21.46-27.96] 

Lag 0 (summer, southwest): 

0.64 [-5.38-7.04] 

Lag 0 (fall, national): 

0.02 [-0.63-0.67] 

Lag 0 (fall, northeast): 

-0.01 [-0.87-0.85] 

Lag 0 (fall, southeast): 

-0.58 [-2.06-0.91] 

Lag 0 (fall, northwest): 

-1.38 [-11.84-10.32] 

Lag 0 (fall, southwest): 

1.77 [-0.73-4.33] 

Lag 1 (all seasons): 0.05 [-0.29-0.39] 

Lag 1 (winter): 0.50 [-0.27-1.27] 

Lag 1 (spring): -0.24 [-1.01-0.53] 

Lag 1 (summer): 0.28 [-0.39-0.95] 

Lag 1 (fall): 0.15 [-0.49-0.79] 

Lag 2 (all seasons): 0.41 [0.09-0.74] 

Lag 2 (winter, national): 0.72 [0.01-1.43]

Lag 2 (winter, northeast): 

0.79 [-0.21-1.80] 

Lag 2 (winter, southeast): 

0.4 [-1.45, 2.27] 

Lag 2 (winter, northwest): 

-0.06 [-6.52-6.85] 

Lag 2 (winter, southwest): 

1.2 [-0.10-2.52] 

Lag 2 (spring, national): 

0.35 [-0.29-0.99] 

Lag 2 (spring, northeast): 

 0.04 [-0.88-0.97] 

Lag 2 (spring, southeast): 

0.75 [-0.82-2.34] 

Lag 2 (spring, northwest): 

2.29 [-14.26-22.03] 

Lag 2 (spring, southwest): 

1.05 [-2.18-4.39] 

Lag 2 (summer, national): 0.57 [-

0.07-1.23] 

Lag 2 (summer, northeast): 

0.77 [-0.01-1.56] 

|Lag 2 (summer, southeast): 

-0.52 [-2.07-1.06] 

Lag 2 (summer, northwest): 

0.74 [-18.73-24.86] 

Lag 2 (summer, southwest): 

2.41 [-2.61-7.69] 

Lag 2 (fall, national): 

0.39 [-0.22-1.01] 

Lag 2 (fall, northeast): 

0.12 [-0.82-1.07] 

Lag 2 (fall, southeast): 

0.14 [-1.29-1.59] 

Lag 2 (fall, northwest): 

-0.74 [-10.08-9.58] 

Lag 2 (fall, southwest): 

0.97[-1.36-3.36]

Reference: Bell et al. (2009, 191007) 

Period of Study: 1999-2005 

Location: 168 U.S. Counties 

Outcome: Respiratory hospital 

admissions 

Study Design: Retrospective Cohort 

Covariates: Socio-economic 

conditions, long term temperature 

Statistical Analysis: Bayesian 

hierarchical model 

Age Groups: ≥65 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD) Unit: NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 20% of the population 

acquiring air conditioning 

Percent Change (95% CI) in 

community-specific PM health effect 

estimates for respiratory hospital 

admissions 

Any AC, including window units 

Yearly health effect: 44.5 (-87.5-176) 

Summer health effect: -74.8 (-417-267) 

Winter health effect: -32.5 (-245-180) 

Central AC 

Yearly health effect: 27.6 (-46.7-102) 

Summer health effect: -38.6 (-160-82.6) 

Winter health effect: 43.8 (-125-213) 

December 2009 E-264 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bell et al. (2009, 191007) 

Period of Study: 1999-2005 

Location: 168 U.S. Counties 

Outcome: Respiratory HA 

Age Groups: 65+

Study Design: Time series 

N: NR 

Statistical Analyses: Bayesian 

Hierarchical Regression 

Covariates: Time trend, day of week, 

seasonality, dew point, temperature 

Statistical Package: NR 

Lags Considered: 0-2 

Pollutant: PM2.5

Averaging Time: Daily 

Mean: 

EC: 0.715 

Ni: 0.002 

V: 0.003 

Min: 

EC: 0.309 

Ni: 0.003 

V: 0.001 

Max: 

EC: 1.73 

Ni: 0.021 

V: 0.010 

Interquartile Range: 

EC: 0.245 

Ni: 0.001 

V: 0.001 

Interquartile Range of Percents: 

EC: 1.7 

Ni: 0.01 

V: 0.01 

Monitoring Stations: NR 

Copollutant: Al, NH4+, As, Ca, Cl, Cu, 

EC, OMC, Fe, Pb, Mg. Ni, NO3-, K, Si, 

Na+, SO4=, Ti, V, Zn 

Co-pollutant Correlation: 

Ni, V: 0.48 

V, EC: 0.33 

Ni, EC: 0.30 

Note: Pollutant concentrations available 

for all fractions of PM2.5

PM Increment: Interquartile Range in 

the fraction of PM2.5

Percent Increase (Lower CI, Upper 

CI): 

EC: 511 (80.7, 941), lag 0 

EC + Ni: 399 (-45.1, 843), lag 0 

EC + V: 386 (-74.8, 846), lag 0 

EC + Ni, V: 362 (-98.0, 823), lag 0 

Ni: 223 (36.9, 410), lag 0 

Ni + EC: 176 (-18.7, 370), lag 0 

Ni + V: 151 (-78.4, 381), lag 0 

Ni + EC, V: 136 (-94.9, 368), lag 0 

V: 392 (46.3, 738), lag 0 

V + EC: 279 (-93.2, 651), lag 0 

V+ Ni: 230 (-193.7, 653), lag 0 

V + EC, Ni: 140 (-300, 579), lag 0 

EC: -1.5 (80.7, 941), lag 1 

EC: 17.5 (-22.3, 57.3), lag 2 

Ni: -7.2 (-66.6. 52.1), lag 1 

Ni: -4.9 (-22.3, 12.5), lag 2 

V: -19.6 (-127, 88.3), lag 1 

V: 10.5 (-21.5, 42.4), lag 2 

HS education: -77.8 (-390, 234), lag 0 

median income: 45.9 (-411, 503), lag0 

Percent black: -53.1 (-557, 451), lag 0 

Percent living in urban area: -41.9 (-

774.7, 691), lag 0 

Population: -22.9 (-121, 75.3), lag 0 

Notes: Interquartile ranges in percent 

HS education, median income, percent 

black, percent living in urban area, and 

population are 5.2 %, $9,223, 17.3%, 

11.0%, and 549,283 respectively. 

Reference: Chardon et al. (2007, 

091308) 

Period of Study: 2000-2003 

Location: Greater Paris Area, France

Doctors house calls 

Outcome (ICPC2): Asthma (R96), 

Upper respiratory disease (URD R07, 

R21, R29, R75, R76, R02) , Lower 

respiratory disease (LRD, R05, R78) 

Age Groups: All 

Study Design: Time series

N: 8027 for asthma 

52928 for LRD 

74845 for URD 

Statistical Analyses: Quasi-Poisson, 

GAM, parametric penalized spline 

smoothers. 

Covariates: Lagged and current 

temperature, humidity, long term trends, 

seasonality, pollen counts, influenza 

epidemic, days of the week, holidays, 

bank holidays

Season: All 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: 0-3 days

Pollutant: PM2.5

Averaging Time: Mean of the daily 

means 

Mean (SD): 14.7(7.34) μg/m3

Percentiles: 25th: 9.5 

50th(Median): 12.9 

75th: 18.2 

Range (Min, Max): (3, 69.6) 

Monitoring Stations: 1- 4 

Copollutant: 

PM10: r = 0.95 

NO2: r = 0.68 

PM Increment: 10 μg/m3

% Change, lag 0-3-day avg 

URD 

6.0 (3.1, 9.1) 

LRD 

5.8 (2.8, 8.9) 

Asthma 

4.4 (-1.3, 10.4) 

December 2009 E-265 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chen et al. (2005, 087555) 

Period of Study: Jun 1995-Mar 1999 

Location: Vancouver area, BC 

Hospital Admissions 

Outcome (ICD-9): Acute respiratory 

infections (460-466), upper respiratory 

tract infections (470-478), pneumonia 

and influenza (480-487), COPD and 

allied conditions (490-496), other 

respiratory diseases (500-519) 

Age Groups: >65 yr 

Study Design: Time series 

N: 12,869 

Statistical Analyses: GLM 

Covariates: Temp and relative humidity

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 1-, 2-, 3-, 4-, 5-, 6-, 

and 7-day avg

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (min-max): 

7.7 (2.0-32.0) 

SD = 3.7 

Monitoring Stations: 13 

Copollutant (correlation): 

PM10: r = 0.83 

PM10-2.5: r = 0.38 

COH: r = 0.39 

CO: r = 0.23 

O3: r = -0.01 

NO2: r = 0.36 

SO2: r = 0.42 

Other variables: 

Mean temp: r = 0.41 

Rel humidity: r = -0.23 

PM Increment: 4.0 μg/m3 (IQR) 

RR Estimate [CI]: 

Adj for weather conditions 

Overall admission 

1-day avg: 1.02 [0.99,1.05] 

2-day avg: 1.02 [0.99,1.06] 

3-day avg: 1.02 [0.98,1.05] 

Adj for weather conditions and 

copollutants 

Overall admission 

1-day avg: 1.01 [0.98,1.06] 

2-day avg: 1.01 [0.98,1.05] 

3-day avg: 1.00 [0.96,1.04] 

Notes: RR’s were also provided for lags 

4-7 in Table 3, yielding similar results 

Reference: Chimonas and Gessner 

(2007, 093261) 

Period of Study: Jan 1999-Jun 2003 

Location: Anchorage, Alaska 

Outcome (ICD-9): Asthma (493.0-

493.9) 

Lower respiratory illness-LRI (466.1, 

466.0, 480-487, 490, 510-511) 

Inhaled quick-relief medication 

Steroid medication 

Age Groups: <20 yr old 

Study Design: Time series 

N: 42,667 admissions 

Statistical Analyses: GEE for 

multivariable modeling 

Covariates: Season, serial correlation, 

yr, weekend, temperature, precipitation, 

and wind speed

Season: NR 

Dose-response Investigated? No 

Statistical Package: SPSS (dataset), 

SAS (analysis) 

Lags Considered: 1 day and 1 wk 

Pollutant: PM2.5

Averaging Time: 24 h and 1 wk 

Mean (min-max): 

Daily: 6.1 (0.5-69.8) 

Weekly: 5.8 (1.8-45.0) 

Monitoring Stations: NR 

Copollutant: N/A 

PM Increment: 5 μg/m3

RR Estimate [CI]: 

Same Day 

Outpatient Asthma: 0.992 [0.964,1.024] 

Outpatient LRI: 0.952 [0.907,1.001] 

Inpatient Asthma: 0.936 [0.798,1.098] 

Inpatient LRI: 0.919 [0.823,1.027] 

Inhaled Steroid Prescriptions: 

0.988 [0.902,1.083] 

Quick-relief Medication: 

0.962 [0.901,1.028] 

Weekly (median increase) 

Outpatient Asthma: 0.983 [0.935,1.038] 

Outpatient LRI: 0.969 [0.874,1.075] 

Inpatient Asthma: 0.754 [0.513.1.109] 

Inpatient LRI: 0.943 [0.715,1.245] 

Inhaled Steroid Prescriptions: 

1.018 [0.883,1.175] 

Quick-relief Medication: 

0.978 [0.882,1.087] 

Reference: Delfino et al. (2009, 

191994) 

Period of Study: Oct 2003-Nov 2003 

Location: Southern California 

Outcome: Respiratory hospital 

admissions 

Study Design: Time series 

Statistical Analysis: Poisson 

regression with GEE 

Age Groups: All 

Pollutant: PM2.5

Averaging Time: Hourly 

Mean (SD) Unit by county: 

Los Angeles 

Before Fires: 27.2 (12.4) μg/m3

 

During Fires: 54.1 (21.0) μg/m3

After Fires: 15.9 (5.5) μg/m3

Orange 

Before Fires: 23.2 (9.6) μg/m3

During Fires: 64.3 (26.5) μg/m3

After Fires: 15.5 (10.2) μg/m3

Riverside 

Before Fires: 32.7 (14.7) μg/m3

During Fires: 42.1 (25.5) μg/m3

After Fires: 16.9 (10.2) μg/m3

San Bernadino 

Before Fires: 35.7 (16.6) μg/m3

During Fires: 45.3 (28.7) μg/m3

After Fires: 18.5 (8.3) μg/m3

San Diego 

Before Fires: 18.5 (6.7) μg/m3

During Fires: 76.1 (66.6) μg/m3

After Fires: 14.2 (7.2) μg/m3

Increment: 10 μg/m3

Relative Rate (Min CI, Max CI)

All Respiratory, All Ages: All Periods: 

1.009 (0.999-1.018) 

Pre-Wildfire: 1.022 (1.004-1.040) 

Wildfire: 1.028 (1.014-1.041), p = 0.639 

Post-Wildfire: 0.999 (0.968-1.031), 

p = 0.198 

All Respiratory, Ages 0-4: All Periods: 

0.994 (0.967-1.021) 

Pre-Wildfire: 0.982 (0.921-1.046) 

Wildfire: 1.045 (1.010-1.082), p = 0.103 

Post-Wildfire: 0.894 (0.807-0.991), 

p = 0.126 

All Respiratory, Ages 5-19: All Periods: 

1.014 (0.983-1.046) 

Pre-Wildfire: 1.026 (0.946-1.113) 

Wildfire: 1.027 (0.984-1.076), p = 0.990 

Ventura 

Post-Wildfire: 0.958 (0.852-1.077), 

p = 0.354 

All Respiratory, Ages 20-64: All Periods: 

December 2009 E-266 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Before Fires: 18.4 (8.3) μg/m3

During Fires: 50.1 (50.5) μg/m3

After Fires: 12.9 (4.3) μg/m3

Copollutant (correlation): NR 

1.015 (1.002-1.029) 

Pre-Wildfire: 1.036 (1.007-1.066) 

Wildfire: 1.024 (1.005-1.044), p = 0.534 

Post-Wildfire: 1.007 (0.960-1.056), 

p = 0.315 

All Respiratory, Ages 65-99: All Periods: 

1.009 (0.996-1.022) 

Pre-Wildfire: 1.022 (0.994-1.050) 

Wildfire: 1.030 (1.011-1.049), p = 0.649 

Post-Wildfire: 1.024 (0.967-1.074), 

p = 0.932 

Asthma, All Ages, Male and Female: All 

Periods: 1.022 (1.001-1.042) 

Pre-Wildfire: 0.998 (0.949-1.050) 

Wildfire: 1.048 (1.021-1.076), p = 0.097 

Post-Wildfire: 0.986 (0.910-1.068), 

p = 0.792 

Asthma, All Ages, Male: All Periods: 

1.010 (0.980-1.040) 

Pre-Wildfire: 1.021 (0.944-1.106) 

Wildfire: 1.031 (0.990-1.073), p = 0.848 

Post-Wildfire: 1.063 (0.948-1.192), 

p = 0.553 

Asthma, All Ages, Female: All Periods: 

1.029 (1.001-1.058) 

Pre-Wildfire: 0.979 (0.913-1.050) 

Wildfire: 1.059 (1.022-1.097), p = 0.056 

Post-Wildfire: 0.928 (0.829-1.037), 

p = 0.412 

Asthma, Ages 0-4, Males and Females: 

All Periods: 0.996 (0.947-1.048) 

Pre-Wildfire: 0.924 (0.824-1.035) 

Wildfire: 1.083 (1.021-1.149), p = 0.017 

Post-Wildfire: 0.924 (0.767-1.113), 

p = 0.999 

Asthma, Ages 0-4, Males: All Periods: 

1.018 (0.963-1.076) 

Pre-Wildfire: 0.942 (0.815-1.089) 

Wildfire: 1.086 (1.016-1.162), p = 0.101 

Post-Wildfire: 1.057 (0.839-1.332), 

p = 0.380 

Asthma, Ages 0-4, Females: All 

Periods: 0.937 (0.845-1.040) 

Pre-Wildfire: 0.880 (0.706-1.099) 

Wildfire: 1.073 (0.965-1.194), p = 0.116 

Post-Wildfire: 0.699 (0.515-0.949), 

p = 0.214 

Asthma, Ages 5-19, Males and 

Females: All Periods: 

1.006 (0.966-1.048) 

Pre-Wildfire: 1.045 (0.936-1.167) 

Wildfire: 0.999 (0.935-1.068), p = 0.492 

Post-Wildfire: 0.918 (0.788-1.069), 

p = 0.198 

Asthma, Ages 5-19, Males: All Periods: 

0.991 (0.935-1.051) 

Pre-Wildfire: 1.034 (0.892-1.198) 

Wildfire: 0.969 (0.883-1.064), p = 0.462 

Post-Wildfire: 0.979 (0.806-1.189), 

p = 0.671 

Asthma, Ages 5-19, Females: All 

Periods: 1.026 (0.964-1.092) 

Pre-Wildfire: 1.065 (0.901-1.260) 

Wildfire: 1.033 (0.943-1.132), p = 0.768 

Post-Wildfire: 0.831 (0.640-1.079), 

p = 0.136 

Asthma, Ages 20-64, Males and 

Females: All Periods: 1.043 (1.012-

December 2009 E-267 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

1.076) 

Pre-Wildfire: 1.037 (0.957-1.123) 

Wildfire: 1.041 (0.995-1.090), p = 0.931 

Post-Wildfire: 1.000 (0.882-1.132), 

p = 0.624 

Asthma, Ages 20-64, Males: All Periods: 

1.013 (0.954-1.077) 

Pre-Wildfire: 1.159 (0.996-1.349) 

Wildfire: 0.939 (0.837-1.053), p = 0.026 

Post-Wildfire: 1.275 (1.020-1.595), 

p = 0.486 

Asthma, Ages 20-64, Females: All 

Periods: 1.052 (1.015-1.090) 

Pre-Wildfire: 0.995 (0.904-1.096) 

Wildfire: 1.064 (1.014-1.116), p = 0.247 

Post-Wildfire: 0.908 (0.780-1.056), 

p = 0.310 

Asthma, Ages 65-99, Males and 

Females: All Periods: 1.027 (0.974-

1.082) 

Pre-Wildfire: 0.951 (0.849-1.064) 

Wildfire: 1.101 (1.030-1.178), p = 0.032 

Post-Wildfire: 1.168 (0.967-1.412), 

p = 0.072 

Asthma, Ages 65-99, Males: All Periods: 

1.046 (0.957-1.142) 

Pre-Wildfire: 0.948 (0.804-1.116) 

Wildfire: 1.185 (1.077-1.305), p = 0.029 

Post-Wildfire: 0.902 (0.629-1.294), 

p = 0.804 

Asthma, Ages 65-99, Females: All 

Periods: 1.018 (0.958-1.081) 

Pre-Wildfire: 0.947 (0.813-1.102) 

Wildfire: 1.065 (0.977-1.162), p = 0.195 

Post-Wildfire: 1.263 (1.024-1.557), 

p = 0.032 

Acute Bronchitis and Bronchiolitis, All 

Ages: All Periods: 1.044 (0.990-1.102) 

Pre-Wildfire: 1.001 (0.890-1.126) 

Wildfire: 1.096 (1.018-1.179), 

p = 0.223 

Post-Wildfire: 1.031 (0.870-1.222), 

p = 0.779 

Acute Bronchitis and Bronchiolitis, Ages 

0-4: All Periods: 1.017 (0.949-1.089) 

Pre-Wildfire: 0.987 (0.847-1.149) 

Wildfire: 1.092 (0.997-1.195), p = 0.276 

Post-Wildfire: 0.910 (0.700-1.183), 

p = 0.588 

Acute Bronchitis and Bronchiolitis, Ages 

5-19: No Convergence 

Acute Bronchitis and Bronchiolitis, Ages 

20-64: All Periods: 1.039 (0.912-1.183) 

Pre-Wildfire: 1.001 (0.792-1.266) 

Wildfire: 1.044 (0.872-1.252), p = 0.778 

Post-Wildfire: 1.259 (0.921-1.722), 

p = 0.275 

Acute Bronchitis and Bronchiolitis, Ages 

65-99: All Periods: 1.134 (1039-1.238) 

Pre-Wildfire: 1.073 (0.764-1.505) 

Wildfire: 1.143 (1.032-1.265), p = 0.730 

Post-Wildfire: 1.190 (0.865-1.638), 

p = 0.652 

COPD, Ages 20-99: All Periods: 1.018 

(0.994-1.042) 

Pre-Wildfire: 1.007 (0.958-1.058) 

Wildfire: 1.038 (1.004-1.075), p = 0.320 

Post-Wildfire: 1.024 (0.943-1.112), 

December 2009 E-268 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

p = 0.728 

COPD, Ages 20-64: All Periods: 1.022 

(0.980-1.066) 

Pre-Wildfire: 0.995 (0.916-1.081) 

Wildfire: 1.068 (1.009-1.131), p = 0.161 

Post-Wildfire: 1.015 (0.893-1.153), 

p = 0.728 

COPD, Ages 65-99: All Periods: 1.019 

(0.992-1.048) 

Pre-Wildfire: 1.014 (0.955-1.077) 

Wildfire: 1.031 (0.990-1.074), p = 0.660 

Post-Wildfire: 1.023 (0.928-1.128), 

p = 0.878 

Pneumonia, All Ages: All Periods: 1.009 

(0.994-1.024) 

Pre-Wildfire: 1.045 (0.931-1.180) 

Wildfire: 1.028 (1.007-1.050), p = 0.420 

Post-Wildfire: 0.980 (0.927-1.035), 

p = 0.045 

Pneumonia, Ages 0-4: All Periods: 

0.995 (0.944-1.049) 

Pre-Wildfire: 1.048 (0.931-1.180) 

Wildfire: 1.018 (0.948-1.092), p = 0.691 

Post-Wildfire: 0.823 (0.649-1.044), 

p = 0.089 

Pneumonia, Ages 5-19: All Periods: 

1.031 (0.966-1.098) 

Pre-Wildfire: 1.017 (0.882-1.172) 

Wildfire: 1.064 (0.990-1.142), p = 0.586 

Post-Wildfire: 1.017 (0.767-1.349), 

p = 0.998 

Pneumonia, Ages 20-64: All Periods: 

1.008 (0.982-1.035) 

Pre-Wildfire: 1.041 (0.982-1.104) 

Wildfire: 1.032 (0.994-1.072), p = 0.823 

Post-Wildfire: 1.013 (0.913-1.124), 

p = 0.633 

Pneumonia, Ages 65-99: All Periods: 

1.011 (0.993-1.030) 

Pre-Wildfire: 1.050 (1.006-1.097) 

Wildfire: 1.029 (1.002-1.057), p = 0.445 

Post-Wildfire: 0.985 (0.920-1.055), 

p = 0.127 

Relative Rate (Min CI, Max CI) in 

relation to pre-wildfire period (1) 

All Respiratory, All Ages: Wildfire, 

unadjusted for PM2.5: 0.961 (0.916-

1.008) 

Wildfire, adjusted for PM2.5: 0.903 

(0.850-0.960) 

Post-wildfire, unadjusted for PM2.5: 

1.143 (1.072-1.219) 

Post-wildfire, adjusted for PM2.5: 

1.173 (1.097-1.253) 

All Respiratory, Ages 0-4: Wildfire, 

unadjusted for PM2.5: 

0.865 (0.757-0.989) 

Wildfire, adjusted for PM2.5: 

0.842 (0.717-0.988) 

Post-wildfire, unadjusted for PM2.5: 

1.152 (0.957-1.388) 

Post-wildfire, adjusted for PM2.5: 

1.162 (0.954-1.415) 

All Respiratory, Ages 5-19: Wildfire, 

unadjusted for PM2.5: 

1.098 (0.901-1.324) 

Wildfire, adjusted for PM2.5: 

1.087 (0.863-1.370) 

December 2009 E-269 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Post-wildfire, unadjusted for PM2.5: 

1.373 (1.089-1.732) 

Post-wildfire, adjusted for PM2.5: 

1.467 (1.142-1.883) 

All Respiratory, Ages 20-64: Wildfire, 

unadjusted for PM2.5: 

0.991 (0.922-1.066) 

Wildfire, adjusted for PM2.5: 

0.923 (0.843-1.012) 

Post-wildfire, unadjusted for PM2.5: 

1.074 (0.971-1.188) 

Post-wildfire, adjusted for PM2.5: 

1.104 (0.992-1.228) 

All Respiratory, Ages 65-99: Wildfire, 

unadjusted for PM2.5: 0.932 (0.867-1.003) 

Wildfire, adjusted for PM2.5: 

0.874 (0.795-0.959) 

Post-wildfire, unadjusted for PM2.5: 

1.147 (1.045-1.259) 

Post-wildfire, adjusted for PM2.5: 1.193 (1.084-1.313) 

Asthma, All Ages: Wildfire, unadjusted 

for PM2.5: 1.088 (0.965-1.227) 

Wildfire, adjusted for PM2.5: 

0.992 (0.856-1.149) 

Post-wildfire, unadjusted for PM2.5: 

1.264 (1.085-1.473) 

Post-wildfire, adjusted for PM2.5: 

1.336 (1.134-1.573) 

Asthma, Ages 0-4: Wildfire, unadjusted 

for PM2.5: 0.806 (0.632-1.029) 

Wildfire, adjusted for PM2.5: 

1.282 (0.958-1.716) 

Post-wildfire, unadjusted for PM2.5: 

1.092 (1.759-1.572) 

Post-wildfire, adjusted for PM2.5: 

1.133 (0.777-1.654) 

Asthma, Ages 5-19: Wildfire, 

unadjusted for PM2.5: 

1.254 (0.999-1.575) 

Wildfire, adjusted for PM2.5: 

1.282 (0.958-1.716) 

Post-wildfire, unadjusted for PM2.5: 

1.564 (1.160-2.109) 

Post-wildfire, adjusted for PM2.5: 

1.629 (1.184-2.243) 

Asthma, Ages 20-64: Wildfire, 

unadjusted for PM2.5: 

1.273 (1.067-1.518) 

Wildfire, adjusted for PM2.5: 

1.221 (0.979-1.524) 

Post-wildfire, unadjusted for PM2.5: 

1.362 (1.043-1.779) 

Post-wildfire, adjusted for PM2.5: 

1.486 (1.111-1.987) 

Asthma, Ages 65-99: Wildfire, 

unadjusted for PM2.5: 

0.869 (0.657-1.151) 

Wildfire, adjusted for PM2.5: 

0.645 (0.450-0.925) 

Post-wildfire, unadjusted for PM2.5: 

0.924 (0.606-1.408) 

Post-wildfire, adjusted for PM2.5: 

1.005 (0.650-1.552) 

Acute Bronchitis and Bronchiolitis, All 

Ages: Wildfire, unadjusted for PM2.5: 

1.143 (0.878-1.490) 

Wildfire, adjusted for PM2.5: 

0.959 (0.696-1.321) 

December 2009 E-270 
Reference Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Post-wildfire, unadjusted for PM2.5: 

1.482 (1.042-2.109) 

Post-wildfire, adjusted for PM2.5: 

1.580 (1.089-2.291) 

Acute Bronchitis and Bronchiolitis, Ages 

0-4: Wildfire, unadjusted for PM2.5: 

1.128 (0.819-1.555) 

Wildfire, adjusted for PM2.5: 

0.899 (0.607-1.333) 

Post-wildfire, unadjusted for PM2.5: 

1.520 (0.947-2.440) 

Post-wildfire, adjusted for PM2.5: 

1.547 (0.954-2.507) 

Acute Bronchitis and Bronchiolitis, 

Ages 5-19 

No Correlation 

Acute Bronchitis and Bronchiolitis, 

Ages 20-64: Wildfire, unadjusted for 

PM2.5: 1.350 (0.688-2.648) 

Wildfire, adjusted for PM2.5: 1.320 (0.608-2.863) 

Post-wildfire, unadjusted for PM2.5: 

2.454 (1.068-5.640) 

Post-wildfire, adjusted for PM2.5: 

2.515 (1.055-5.998) 

Acute Bronchitis and Bronchiolitis, 

Ages 65-99: Wildfire, unadjusted for 

PM2.5: 1.166 (0.643-2.115) 

Wildfire, adjusted for PM2.5: 

0.934 (0.422-20.66) 

Post-wildfire, unadjusted for PM2.5: 

0.911 (0.428-1.942) 

Post-wildfire, adjusted for PM2.5: 

0.997 (0.439-2.262) 

COPD, Ages 20-99: Wildfire, 

unadjusted for PM2.5: 

0.988 (0.875-1.115) 

Wildfire, adjusted for PM2.5: 

0.913 (0.779-1.069) 

Post-wildfire, unadjusted for PM2.5: 

1.043 (0.885-1.228) 

Post-wildfire, adjusted for PM2.5: 

1.064 (0.897-1.262) 

COPD, Ages 20-64: Wildfire, 

unadjusted for PM2.5: 

0.967 (0.779-1.201) 

Wildfire, adjusted for PM2.5: 

0.873 (0.660-1.156) 

Post-wildfire, unadjusted for PM2.5: 

1.175 (0.862-1.601) 

Post-wildfire, adjusted for PM2.5: 

1.311 (0.954-1.802) 

COPD, Ages 65-99: Wildfire, 

unadjusted for PM2.5: 

1.002 (0.869-1.156) 

Wildfire, adjusted for PM2.5: 

0.926 (0.767-1.117) 

Post-wildfire, unadjusted for PM2.5: 

0.985 (0.811-1.196) 

Post-wildfire, adjusted for PM2.5: 

0.981 (0.798-1.206) 

Pneumonia, All Ages: Wildfire, 

unadjusted for PM2.5: 

0.943 (0.868-1.025) 

Wildfire, adjusted for PM2.5: 

0.888 (0.799-0.986) 

Post-wildfire, unadjusted for PM2.5: 

1.294 (1.158-1.446) 

Post-wildfire, adjusted for PM2.5: 

1.318 (1.174-1.479) 

December 2009 E-271 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Pneumonia, Ages 0-4: Wildfire, 

unadjusted for PM2.5: 

0.938 (0.705-1.247) 

Wildfire, adjusted for PM2.5: 

0.951 (0.678-1.333) 

Post-wildfire, unadjusted for PM2.5: 

1.458 (0.974-20182) 

Post-wildfire, adjusted for PM2.5: 

1.374 (0.885-2.133) 

Pneumonia, Ages 5-19: Wildfire, 

unadjusted for PM2.5: 

0.891 (0.604-1.312) 

Wildfire, adjusted for PM2.5: 

0.830 (0.541-1.272) 

Post-wildfire, unadjusted for PM2.5: 0.960 (0.588-1.569) 

Post-wildfire, adjusted for PM2.5: 

0.969 (0.578-1.624) 

Pneumonia, Ages 20-64: Wildfire, 

unadjusted for PM2.5: 0.927 (0.795-1.081) 

Wildfire, adjusted for PM2.5: 

0.837 (0.690-1.016) 

Post-wildfire, unadjusted for PM2.5: 

1.314 (1.064-1.622) 

Post-wildfire, adjusted for PM2.5: 1.300 

(1.047-1.615) 

Pneumonia, Ages 65-99: Wildfire, 

unadjusted for PM2.5: 

0.959 (0.861-1.068) 

Wildfire, adjusted for PM2.5: 

0.899 (1.782-1.033) 

Post-wildfire, unadjusted for PM2.5: 

1.277 (1.102-1.481) 

Post-wildfire, adjusted for PM2.5: 

1.331 (1.142-1.552) 

Reference: Dominici et al. (2006, 

088398) 

Period of Study: 1999-2002

Location: 204 U.S. counties, located 

in: Alabama, Alaska, Arizona, Arkansas, 

California, Colorado, Connecticut, 

Delaware, District of Columbia, Florida, 

Georgia, Hawaii, Idaho, Illinois, Indiana, 

Iowa, Kansas, Kentucky, Louisiana, 

Maine, Maryland, Massachusetts, 

Michigan, Minnesota, Mississippi, 

Missouri, Nevada, New Hampshire, 

New Jersey, New Mexico, New York, 

North Carolina, Ohio, Oklahoma, 

Oregon, Pennsylvania, Rhode Island, 

South Carolina, Tennessee, Texas, 

Utah, Virginia, Washington, West 

Virginia, Wisconsin 

Outcome (ICD-9: Daily counts of 

hospital admissions for primary 

diagnosis of chronic obstructive 

pulmonary disease (490-492), and 

respiratory tract infections (464-466, 

480-487). 

Age Groups: >65 yr

Study Design: Time series 

N: 11.5 million Medicare enrollees 

Statistical Analyses: Bayesian 2-stage 

hierarchical models. 

First stage: Poisson regression (countyspecific) 

Second stage: Bayesian hierarchical 

models, to produce a national avg 

estimate 

Covariates: Day of the week, 

seasonality, temperature, dew point 

temperature, long-term trends 

Season: NR

Dose-response Investigated: No

Statistical Package: R statistical 

software version 2.2.0 

Lags Considered: 0-2 days, avg of 

days 0-2 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (μg/m3

 ) (IQR): 13.4 (11.3-15.2) 

Monitoring Stations: NR 

Copollutant (correlation): NR 

Other variables: Median of pairwise 

correlations among PM2.5 monitors 

within the same county for 2000: r = 

0.91 (IQR: 0.81-0.95) 

PM Increment: 10 μg/m3 (Results in 

figures see notes) 

Percent increase in risk [95% PI]: 

COPD (Lag 0): Age 65 +: 0.91 [0.18, 

1.64] 

Age 65-74: 0.42 [-0.64, 1.48] 

Age 75+: 1.47 [0.54, 2.40] 

Respiratory tract infection: Age 65+: 

0.92 [0.41, 1.43] 

Age 65-74: 0.93 [0.04, 1.82] 

Age 75+: 0.92 [0.32, 1.53] 

Annual reduction in admissions 

attributable to a 10 μg/m3

 reduction in 

daily PM2.5 level (95% PI): 

Cerebrovascular disease: Annual 

number of admissions: 226,641 

Annual reduction in admissions: 1836 

[680, 2992] 

COPD: Annual number of admissions: 

108,812 

Annual reduction in admissions: 990 

[196, 1785] 

Respiratory tract infections: Annual 

number of admissions: 226,620 

Annual reduction in admissions: 2085 

[929, 3241] 

December 2009 E-272 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dominici et al. (2006, 

088398) 

Period of Study: 1999-2002 

Location: U.S. (mainland) 

Outcome (ICD-9): Respiratory tract 

infections (464-466, 480-487) and 

Chronic Obstructive Pulmonary Disease 

(490-492) 

Age Groups: All >65 yr 

65-74 yr 

>75 yr 

Study Design: Time series 

N: 11.5 million at-risk 

Statistical Analyses: Bayesian 2-stage 

hierarchical models (day-to-day 

variation), Poisson regression (countyspecific RRs) 

Covariates: Calendar time (seasonality 

and yr), temperature, dew point 

Season: NR 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0, 1, 2 days 

Pollutant: PM2.5

Averaging Time: Daily or every 3 days 

(depending on county) 

Mean: 13.4 (IQR: 11.3-15.2) 

Monitoring Stations: NR (used data 

from Air Quality System database) 

Copollutant: NR 

PM Increment: 10 μg/m3

Percentage Change in Hospital 

Admission Rates [PI]: 

COPD-Same day 

All >65: 0.91 [0.18,1.64] 

65-74 yr: 0.42 [-0.64,1.48] 

>75: 1.47 [0.54,2.40] 

Respiratory Tract Infections-2-day lag 

All >65: 0.92 [0.41,1.43] 

65-74 yr: 0.93 [0.04,1.82] 

>75: 0.92 [0.32,1.53] 

Notes: Other lag data shown in Fig 2-4 

Reference: Erbas et al. (2005, 073849)

Period of Study: Jul 1989-Dec 1992 

Location: Melbourne, Australia 

Outcome (ICD): 

COPD (490-492, 494, 496) 

Asthma (493) 

Age Groups: NR 

Study Design: Time series 

N: NR 

Statistical Analyses: GLM, GAM, 

Parameter Driven Poisson Regression, 

Transitional Regression, SeasonalTrend decomposition based on Loess 

smoothing for seasonal adjustment 

Covariates: Secular trends, 

seasonality, relative humidity, dry bulb 

temp, dew point temp 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus, SAS 

Lags Considered: 0-5 days 

Pollutant: PM0.1-1 (API) 

Averaging Time: 24 h

Mean (min-max): NR 

Monitoring Stations: 9

Copollutant (correlation): NR 

PM Increment: Increase from the 

10th-90th percentile (value NR) 

RR Estimate [CI]: 

COPD 

GAM: 

0.95 [0.91,1.00] 

GLM, PDM, TRM: NR 

Asthma 

NR 

Notes: This study was used to 

demonstrate that conclusions are highly 

dependent on the type of model used 

December 2009 E-273 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Fung et al. (2006, 089789) 

Period of Study: Jun 1995-Mar 1999 

Location: Vancouver, Canada

Hospital Admission/ED: 

Hospital Admission 

Outcome: Respiratory diseases 

(460-519) 

Age Groups: Age >65 

Study Design: Time series, case 

crossover

N: 26,275 individuals admitted 

Statistical Analyses: Poisson 

regression (spline 12 knots), casecrossover (controls +/7 days from case 

date), Dewanji and Moolgavkar (DM) 

method 

Covariates: Long-term trends, day-ofthe-week effect, weather 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SPlus, R 

Lags Considered: 0-7 days 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 7.72(3.61) 

Range (Min, Max): (2, 32) 

Monitoring Stations: NR 

Copollutant (correlation): 

PM2.5: 

PM10 r = 0.80 

PM10-2.5 r = 0.34 

CO r = 0.23 

CoH r = 0.38 

O3 r = -0.03 

NO2 r = 0.36 

SO2 r = 0.42 

PM Increment: : 4 μg/m3

RR Estimate (65+ yr) 

DM method: 

1.007[0.994, 1.020] 

Current 

1.007[0.990,1.023] 3 day 

0.995[0.979,1.012] 5 day 

0.995[0.971,1.020] 7 day 

Time series: 

1.003[0.989, 1.018] 

Current 

1.000[0.982, 1.018] 3 day 

0.993[0.972, 1.014] 5 day 

0.995[0.971, 1.020] 7 day 

Case-crossover: 

1.002[0.986, 1.019] 

Current 

1.001[0.981, 1.021] 3 day 

0.988[0.966, 1.011] 5 day 

0.984[0.959, 1.010] 7 day 

Reference: Hinwood et al. (2006, 

088976) 

Period of Study: Jan 1992-Dec 1998 

Location: Perth, Australia

Hospital Admission 

Outcome (ICD-9): COPD (490-496.99, 

except asthma), pneumonia /influenza 

(480-489.99), asthma 

Age Groups: All ages 

Study Design: Time stratified casecrossover

N: NR 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Time trend, season, 

temperature, humidity, day of wk, 

holidays 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 0-3 days 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 9.2 (4.3) 

Percentiles: 

10th: 5.0 

90th: 14.5 

Monitoring Stations: 13 

Notes: Copollutant: NR 

Increment: 1 μg/m3

Notes: Odds ratio for PM2.5 and all 

respiratory, COPD, pneumonia and 

asthma. Authors found an elevation in 

the odds ratio for lags 2 and 3 

reaaching significance in all age groups 

for lag 3. For each increase of 1 μg/m3

, 

the number of hospitalizations 

increases 0.2% for respiratory disease, 

0.5% for pneumonia and 0.3% for 

asthna. PM2.5 concentrations were also 

significantly associated with asthma for 

those aged under 15 yr with an 

estimated 0.5% increase in 

hospitalizations. 

December 2009 E-274 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hirshon et al. (2008, 

180375) 

Period of Study: Jun 2002-Nov 2002 

Location: Baltimore, Maryland 

Outcome: Hospital admissions for 

asthma 

Study Design: Time-series 

Covariates: Spatial distance from 

pollution monitor, demographic 

variation, long term, seasonal and daily 

trends, weather and other pollutants 

Statistical Analysis: Overdispersed 

Poisson regression 

Age Groups: 0-17 yr 

Pollutant: PM2.5 zinc 

Averaging Time: 24 h 

Mean (SD) Unit: 22.42 (25.14) μg/m3

Range (Min, Max): NR 

Copollutant (correlation): 

Ni: 0.41 

Cr: 0.17 

Fe: 0.54 

Sulfate: 0.01 

CO: 0.40 

PM2.5: 0.39 

O3: 0.01 

NO2: 0.66 

EC: 0.48 

Increment: NR 

Relative Risk (95% CI), Best fit Model 

Medium = 8.63-20.76 ng/m3

High = >20.76 ng/m3

No Lag 

Medium: 1.12 (0.98-1.28) 

High: 1.09 (0.91-1.30) 

1-day Lag 

Medium: 1.23 (1.07-1.41) 

High: 1.16 (0.97-1.39) 

2-day Lag 

Medium: 1.11 (0.94-1.30) 

High: 1.15 (0.96-1.38) 

Controlling for Time Trends 

No Lag 

Medium: 1.08 (0.95-1.23) 

High: 0.98 (0.86-1.11) 

1-day Lag 

Medium: 1.13 (1.003-1.28) 

High: 1.03 (0.91-1.16) 

2-day Lag 

Medium: 1.13 () 

High: 0.98-1.31 

Controlling for Time Trends and 

Additional Copollutants

No Lag 

Medium: 1.12 (0.98-1.29) 

High: 1.09 (1.01-1.30) 

1-day Lag 

Medium: 1.20 (1.04-1.38) 

High: 1.12 (0.93-1.35) 

2-day Lag 

Medium: 1.12 (0.95-1.32) 

High: 1.19 (0.98-1.44) 

Reference: Host et al. (2007, 155851) 

Period of Study: 2000-2003

Location: Six French cities: Le Havre, 

Lille, Marseille, Paris, Rouen, and 

Toulouse 

Outcome (ICD-10): Daily 

hospitalizations for all respiratory 

diseases (J00-J99), respiratory 

infections (J10-J22). 

Age Groups: For all respiratory 

diseases: 0-14 yr, 15-64 yr, and ≥ 65 yr. 

For respiratory infections: All ages

Study Design: Time series

N: NR (Total population of cities: 

approximately 10 million) 

Statistical Analyses: Poisson 

regression 

Covariates: Seasons, days of the 

week, holidays, influenza epidemics, 

pollen counts, temperature, and 

temporal trends 

Season: NR

Dose-response Investigated: No

Statistical Package: MGCV package in 

R software (R 2.1.1) 

Lags Considered: Avg of 0-1 days 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (5th -95th percentile): 

Le Havre: 13.8 (6.0-30.5) 

Lille: 15.9 (6.9-26.3) 

Marseille: 18.8 (8.0-33.0) 

Paris: 14.7 (6.5-28.8) 

Rouen: 14.4 (7.5-28.0) 

Toulouse: 13.8 (6.0-25.0) 

Monitoring Stations: 

13 total: 1 in Toulouse 

4 in Paris 

2 each in other cities 

Copollutant (correlation): 

PM10-2.5: Overall: r > 0.6 

Ranged between r = 0.28 and 

r = 0.73 across the six cities. 

PM Increment: 10 μg/m3 increase, and 

a 27 μg/m3

 increase (corresponding to 

the difference between the lowest of the 

5th percentiles and the highest of the 

95th percentiles of the cities’ 

distributions) 

ERR (excess relative risk) Estimate [CI]: 

For all respiratory diseases (27 μg/m3

increase): 0-14 yr: 1.1% [-3.1, 5.5] 

15-64 yr: 2.2% [-1.8, 6.4]; 

≥ 65 yr: 1.3% [-5.3, 8.2] 

For respiratory infections (10 μg/m3

increase): All ages: 2.5% [0.1, 4.8] 

For respiratory infections (27 μg/m3

increase): All ages: 7.0% [0.7, 13.6] 

December 2009 E-275 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ko et al. (2007, 091639) 

Period of Study: Jan 2000-Dec 2004 

Location: Hong Kong, China

ED Visits 

Outcome (ICD-9): COPD: Chronic 

bronchitis (491), Emphysema (492), 

Chronic airway obstruction (496) 

Age Groups: All ages 

Study Design: Time series 

N: 15 hospitals, 119,225 admissions 

Statistical Analyses: Poisson 

regression, GAM with stringent 

convergence criteria, APHEA2 protocol. 

Covariates: Time trend, season, 

temperature, humidity, other cyclical 

factors, day, day of wk, holidays 

Season: All yr, interactions with season 

tested 

Dose-response Investigated? No 

Statistical Package: SPLUS 4.0 

Lags Considered: 0-5 days 

Pollutant: PM2.5 

Averaging Time: 24 h 

Mean (SD): 35.7 (20.6) 

Percentiles: 

25th: 19.4 

50th(Median): 31.7 

75th: 46.7 

Range (Min, Max): (6.0, 163.2) 

Monitoring Stations: 14 

Copollutant (correlation): 

PM2.5: 

PM10 r = 0.952 

NO2 r = 0.441 

O3 r = 0.394 

SO2 r = 0.282 

PM Increment: PM10

RR Estimate 

COPD: 

1.002[0.998, 1.001] lag 0 

1.003[0.999, 1.007] lag 1 

1.011[1.007, 1.014] lag 2 

1.013[1.010, 1.017] lag 3 

1.011[1.008, 1.015] lag 4 

1.009[1.006, 1.013] lag 5 

1.004[0.999, 1.008]lag 0-1 

1.010[1.006, 1.015]lag 0-2 

1.018[1.013, 1.022]lag 0-3 

1.024[1.019, 1.029]lag 0-4 

1.031[1.026, 1.036]lag 0-5 

4-Pollutant model: 

1.014[1.007, 1.022] lag 0-5 

3-Pollutant model: 

1.011[1.004, 1.017] lag 0-5 

Reference: Ko et al. (2007, 092844) 

Period of Study: Jan 2000-Dec 2005 

Location: Hong Kong, China

Hospital Admission 

Outcome (ICD-9): Asthma (493) 

Age Groups: All, 0-14, 15-56, 65+ 

Study Design: Time series

N: 69,716 admissions, 15 hospitals 

Statistical Analyses: Poisson 

regression, with GAM with stringent 

convergence criteria. 

Covariates: Time trend, season, 

temperature, humidity, other cyclical 

factors 

Season: All yr, evaluated effect of 

season in analysis 

Dose-response Investigated? No 

Statistical Package: SPLUS 4.0 

Lags Considered: 0-5 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 36.4 (21.1) 

Percentiles: 

25th: 20.0 

50th(Median): 32.5 

75th: 47.7 

Range (Min, Max): (6, 163) 

Monitoring Stations: 14 

Copollutant (correlation): 

PM2.5: 

PM10 r = 0.956 

NO2 r = 0.774 

O3 r = 0.585 

SO2 r = 0.482 

PM Increment: 10.0 μg/m3

RR Estimate 

Asthma (Single-pollutant model): 

1.008[1.004, 1.013] lag 0 

1.004[1.000, 1.009] lag 1 

1.004[1.000, 1.009] lag 2 

1.009[1.005, 1.014] lag 3 

1.006[1.001, 1.011] lag 4 

1.002[0.998, 1.007] lag 5 

1.009[1.004, 1.014] lag 0-1 

1.012[1.007, 1.018] lag 0-2 

1.017[1.011, 1.022] lag 0-3 

1.020[1.014, 1.026] lag 0-4 

1.021[1.015, 1.028] lag 0-5 

Asthma in Age: 

0-14: 1.024[1.013, 1.034] lag 0-5 

14-65: 1.018[1.008, 1.029] lag 0-5 

>65: 1.021[1.012, 1.030] lag 0-4 

Asthma-Cold Season: 

1.139[1.043, 1.244] lag 0-5 

Reference: Lee et al. (2006, 090176) 

Period of Study: Jan 1997-Dec 2002 

Location: Hong Kong, China

Hospital Admission 

Outcome: Asthma (493) 

Age Groups: <18 yr 

Study Design: Time series

N: 26,663 asthma admissions for 

asthma and 5821 admissions for 

influenza 

Statistical Analyses: Poisson 

regression, GAM 

Covariates: Temperature, atmospheric 

pressure, relative humidity 

Season: All 

Dose-response Investigated? No 

Statistical Package: SAS 8.02 

Lags Considered: 0-5 

Notes: Controls were admissions for 

influenza ICD9 487 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 45.3 μg/m3, (16.2) 

Percentiles: 25th: 33.4 

50th(Median): 43.0 

75th: 54.0 

Range (Min, Max): NR 

Monitoring Stations: 10 

Copollutant (correlation): 

PM2.5-PM10: 0.89 

PM2.5-SO2: 0.48 

PM2.5-NO2: 0.74 

PM2.5-O3: 0.47 

PM Increment: IQr = 20.6 μg/m3

Percent increase: 

Single pollutant model: 

5.10 [2.95, 7.30], lag 0 

5.00 [2.88, 7.16], lag 1 

5.48 [2.75, 6.95], lag 2 

4.83 [2.78, 6.93], lag 3 

6.59 [4.51, 8.72], lag 4 

5.24 [3.18, 7.34 ], lag 5 

Multipollutant model (SO2, NO2, CO, O3)

3.24 [0.93, 5.60], lag 4 

December 2009 E-276 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Letz and Quinn (2005, 

088752) 

Period of Study: Oct 2001-Aug 2002 

Location: San Antonio,Texas 

Emergency Dept Visits 

Outcome (ICD-9): Asthma or reactive 

airway disease (493.0-493.9), wheezing 

(786.07), dyspnea (786.01-786.9), 

shortness of breath (786.05), bronchitis 

(490-496), or cough (786.2) 

Age Groups: NR (basic air force 

trainees) 

Study Design: Historic (retrospective) 

cohort 

N: 149 ED visits 

Statistical Analyses: Pearson 

correlation 

Covariates: NR

Season: NR 

Dose-response Investigated? No 

Statistical Package: SPSS 

Lags Considered: NR

Pollutant: PM2.5

Averaging Time: 24-h AQI 

AQI Range (min-max): (4-109) 

Monitoring Stations: Data obtained 

from the Texas Commission on 

Environmental Quality 

Copollutant (correlation): NR 

PM Increment: NR 

Correlation with Outcomes: 

Same-day 

All visits: r = 0.082 

Proven asthmatic events: r = -0.042 

3-day 

All visits: r = 0.097 

Proven asthmatic events: r = 0.011 

Reference: Lin et al. (2005, 087828) 

Period of Study: 1998-2001 

Location: Toronto, North York, East 

York, Etobicoke, Scarborough, and York 

(Canada) 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

infections including laryngitis, tracheitis, 

bronchitis, bronchiolitis, pneumonia, 

and influenza (464, 466, 480-487) 

Age Groups: 0-14 yr 

Study Design: Bidirectional casecrossover 

N: 6782 respiratory infection 

hospitalizations 

Statistical Analyses: Conditional 

logistic regression (Cox proportional 

hazards model) 

Covariates: Daily mean temp and dew 

point temp

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 8.2 PHREG 

procedure 

Lags Considered: 1- to 7-day avg

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (min-max): 

9.59 (0.25-50.50) 

SD = 7.06 

Monitoring Stations: 4 

Copollutant (correlation): 

PM10-2.5: r = 0.33 

PM10: r = 0.87 

CO: r = 0.10 

SO2: r = 0.47 

NO2: r = 0.48 

O3: r = 0.56 

PM Increment: 7.8 μg/m3

OR Estimate [CI]: 

Adjusted for weather 

4-day avg: 1.11 [1.02,1.22] 

6-day avg: 1.11 [1.00,1.24] 

Adj for weather and other gaseous 

pollutants 

4-day avg: 0.94 [0.81,1.08] 

6-day avg: 0.90 [0.76,1.07] 

Notes: OR’s were also categorized into 

“Boys” and “Girls,” yielding similar 

results 

December 2009 E-277 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lin et al. (2002, 026067) 

Period of Study: Jan 1981-Dec 1993 

Location: Toronto 

Hospital Admissions 

Outcome (ICD-9): Asthma (493) 

Age Groups: 6-12 yr 

Study Design: Uni- and bi-directional 

case-crossover (UCC, BCC) and timeseries (TS) 

N: 7,319 asthma admissions 

Statistical Analyses: Conditional 

logistic regression, GAM 

Covariates: Maximum and minimum 

temp, avg relative humidity

Season: Apr-Sep, Oct-Mar 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1- to 7-day avg

Pollutant: PM2.5

Averaging Time: 6 days (predicted 

daily values) 

Mean (min-max): 

17.99 (1.22-89.59) 

SD = 8.49 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10: r = 0.87 

PM10-2.5: r = 0.44 

CO: r = 0.45 

SO2: r = 0.46 

NO2: r = 0.50 

O3: r = 0.21 

PM Increment: 9.3 μg/m3

RR Estimate [CI]: 

Adj for weather and gaseous pollutants 

BCC 5-day avg: 0.94 [0.85,1.03] 

BCC 6-day avg: 0.92 [0.83,1.02] 

TS 5-day avg: 0.96 [0.90,1.02] 

TS 6-day avg: 0.94 [0.88,1.01] 

Boys-adj for weather 

UCC 1-day avg: 1.09 [1.04,1.15] 

UCC 2-day avg: 1.09 [1.02,1.16] 

BCC 1-day avg: 1.01 [0.97,1.06] 

BCC 2-day avg: 0.99 [0.93,1.05] 

TS 1-day avg: 1.00 [0.97,1.04] 

TS 2-day avg: 0.98 [0.94,1.02] 

Girls-adj for weather 

UCC 1-day avg: 1.06 [0.99,1.14] 

UCC 2-day avg: 1.11 [1.02,1.21] 

BCC 1-day avg: 0.99 [0.93,1.06] 

BCC 2-day avg: 1.02 [0.94,1.09] 

TS 1-day avg: 0.99 [0.95,1.04] 

TS 2-day avg: 1.00 [0.95,1.06] 

Notes: The author also provides RR 

using UCC, BCC, and TS analysis for 

female and male groups for days 3-7, 

yielding similar results 

Reference: Magas et al. (2007, 

090714) 

Period of Study: 2001-2003 

Location: Oklahoma City Metro area, 

Oklahoma and Cleveland counties

Hospital Admission/ED: Admissions 

Outcome: Asthma 493.01-493.99 

Age Groups: <15 yr 

Study Design: Time series

N: 1,270 admissions 

Statistical Analyses: Negative 

binomial regression 

Covariates: Temperature, humidity, 

pollen count, mold 

Season: All 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Monitoring Stations: 10 

Copollutant (correlation): NR 

Notes: Coefficient for PM2.5 was not 

significant and thus not reported. 

Reference: Mohr et al. (2008, 180215) 

Period of Study: Jun 2001-May 2003 

Location: St. Louis, MO 

Outcome: Asthma ER Visits

Age Groups: 2-17 yr 

Study Design: Time series

Statistical Analyses: GEE Poisson 

models 

Covariates: Season, weekend 

exposure, allergens 

Dose-response Investigated: No 

Statistical Package: SAS 

Lags Considered: 1 day 

Pollutant: PM2.5 EC 

Averaging Time: 24 h 

Std Dev: 0.1

Monitoring Stations: 1 

Copollutant: NOX, SO2, O3

Co-pollutant Correlation 

NOX: 0.68* 

SO2: 0.09 

O3: -0 06 

*p≤0.05 

PM Increment: 0.1 μg/m3

Relative Risk Effect (Lower CI, Upper 

CI): 

Weekend Exposure 

Summer: 1.05 (1.00, 1.11) 

Fall: 0.99 (0.97, 1.01) 

Winter: 0.96 (0.92, 1.00) 

Spring: 0.96 (0.92, 1.00) 

Weekday Exposure 

Summer: 1.01 (0.98, 1.03) 

Fall: 1.00 (0.99, 1.01) 

Winter: 0.99 (0.96, 1.01) 

Spring: 0.98 (0.96, 1.01) 

December 2009 E-278 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: 1999-2000 (1-yr 

period) 

Location: Vienna and Lower Austria 

Hospital Admissions 

Outcome (ICD-9): Bronchitis, 

emphysema, asthma, bronchiectasis, 

extrinsic allergic alveolitis, and chronic 

airway obstruction (490-496) 

Age Groups: 3.0-5.9 yr 

7-10 yr 

65+ yr 

Study Design: Time series 

N: 366 days (admissions NR) 

Statistical Analyses: GAM 

Covariates: SO2, NO, NO2, O3, 

temperature, humidity, and day of the 

week

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-14 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Maximum daily mean: 

Vienna: 96.4 

Rural area: 48.0 

Monitoring Stations: NR 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3

Log Relative Rate Estimate (p-value): 

Vienna 

Male: 2-day lag = 5.467 (0.019) 

Female: 3-day lag = 5.596 (0.009) 

Rural 

Male: 10-day lag = 9.893 (0.012) 

Female: 11-day lag = 10.529 (0.011) 

Association with tidal lung functioN: 

β = -0.987 (p-value = 0.091) 

Notes: Effect parameters with 

significant coefficients for respiratory 

health included: male sex, allergy, 

asthma in family, and traffic for Vienna 

and age, allergy, asthma in family, 

passive smoking, and PM fraction for 

the rural area. Effect parameters with 

significant coefficients for log asthma 

score were allergy, asthma in family, 

and rain for Vienna and allergy, asthma 

in family, and passive smoking for the 

rural area. Cross-correlation coefficients 

are provided in Fig 1. 

Reference: Ostro et al. (2008, 097971) 

Period of Study: 2000-2003 

Location: Six California Counties 

Outcome: Respiratory disease 

(ICD-9 460-519) 

Study Design: Time-Series 

Statistical Analysis: Poisson 

Regression 

Statistical Package: R 

Age Groups: Children <19 yr 

Pollutant: PM2.5 and components 

Averaging Time: 24 h 

Mean (SD) Unit: 19.4 μg/m3

IQR: 14.6 μg/m3

Copollutants: 

EC, OC, NO2, SO4, Cu, Fe, K, Si, Zn 

Increment: NR 

Relative Risk (Min CI, Max CI) 

Lag 

Full results are presented graphically in 

figures 1 and 2. 

Excess risks for all-yr respiratory 

hospital admissions in children <19yrs, 

3-day lag 

PM2.5: 4.1% (1.8-6.4) 

EC: 5.4% (0.8-10.3) 

Fe: 4.7% (2.2-7.2) 

OC: 3.4% (1.1-5.7) 

Nitrates: 3.3% (1.1-5.5) 

Sulfates: 3.0% (0.4-5.7) 

Excess risks for cool season (Oct-Mar) 

respiratory hospital admissions in 

children <19yrs, 3 day lag 

PM2.5: 5.1% (1.6-8.9) 

EC: 6.8% (-0.2-14.2) 

Fe: 4.8% (1.7-8.0) 

K: 4.0% (0.3-7.7) 

December 2009 E-279 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Slaughter et al. (2005, 

073854)

Period of Study: Jan 1995-Jun 2001 

Location: Spokane, WA 

Hospital Admissions and ED visits 

Outcome: All respiratory (460-519) 

Asthma (493) 

COPD (491,492, 494,496) 

Pneumonia (480-487) 

Acute URI not including colds and 

sinusitis (464, 466, 490) 

Age Groups: All, 15+ yr for COPD 

Study Design: Time series

N: 2373 visit records 

Statistical Analyses: Poisson 

regression, GLM with natural splines. 

For comparison also used GAM with 

smoothing splines and default 

convergence criteria. 

Covariates: Season, temperature, 

relative humidity, day of week 

Season: All 

Dose-response Investigated?: No 

Statistical Package: SAS, SPLUS 

Lags Considered: 1 -3 days 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Range (90% of Concentrations): 

4.2-20.2 μg/m3

Monitoring Stations: 

One 

Notes: Copollutant (correlation): 

PM2.5

PM1 r = 0.95 

PM10 r = 0.62 

PM10-2.5 r = 0.31 

CO r = 0.62 

Temperature r = 0.21 

PM Increment: 10 μg/m3 

RR Estimate [Lower CI, Upper CI] 

lag: 

ER visits: 

PM2.5

All Respiratory 

Lag 1: 1.01 [0.98, 1.04] 

Lag 2: 1.02 [0.99, 1.04] 

Lag 3: 1.02 [0.99, 1.05] 

Acute Asthma 

Lag 1: 1.03 [0.98, 1.09] 

Lag 2: 1.00 [0.95, 1.05] 

Lag 3: 1.01 [0.96, 1.06] 

COPD (adult) 

Lag 1: 0.96 [0.89, 1.04] 

Lag 2: 1.01 [0.93, 1.09] 

Lag 3: 1.00 [0.93, 1.08] 

Hospital Admissions: 

PM2.5

All Respiratory 

Lag 1: 0.98 [0.94, 1.01] 

Lag 2: 0.99 [0.96, 1.03] 

Lag 3: 1.01 [ 0.98, 1.05] 

Asthma 

Lag 1: 1.01 [0.91, 1.11] 

Lag 2: 1.03 [0.94, 1.13] 

Lag 3: 1.02 [0.93, 1.13] 

COPD (adult) 

Lag 1: 0.99 [0.91, 1.08] 

Lag 2: 1.06 [0.98, 1.16] 

Lag 3: 1.03 [0.94, 1.12]

Reference: Tecer et al. (2008, 180030) 

Period of Study: Dec 2004-Oct 2005 

Location: Zonguldak, Turkey 

Outcome: ED visits for respiratory 

problems (ICD-9 470-478, 493) 

Study Design: Bidirectional Casecrossover 

Covariates: Daily meteorological 

parameters 

Statistical Analysis: Conditional 

logistic regression 

Statistical Package: Stata 

Age Groups: 0-14 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean, Unit: 29.1 μg/m3

Range (Min, Max): 4.55, 95.65 

Copollutant (correlation): 

PM2.5/PM10

Mean: 0.56 

Range: 0.17-0.88 

PM2.5/PM10-2.5

Mean: 1.49 

Range: 0.21-7.53 

Increment: 10 μg/m3

Odds Ratio (95% CI)

Asthma 

Lag 0: 1.15 (0.99-1.34) 

Lag 1: 0.85 (0.70-1.03) 

Lag 2: 0.87 (0.73-1.04) 

Lag 3: 0.93 (0.79-1.10) 

Lag 4: 1.25 (1.05-1.50) 

Allergic Rhinitis with Asthma 

Lag 0: 1.21 (1.10-1.33) 

Lag 1: 0.84 (0.75-0.93) 

Lag 2: 0.89 (0.81-0.98) 

Lag 3: 0.99 (0.90-1.09) 

Lag 4: 1.06 (0.95-1.19) 

Allergic Rhinitis 

Lag 0: 1.08 (0.98-1.20) 

Lag 1: 1.03 (0.93-1.13) 

Lag 2: 0.89 (0.80-0.99) 

Lag 3: 0.98 (0.89-1.09) 

Lag 4: 1.18 (1.00-1.24) 

Upper Respiratory Disease 

Lag 0: 0.99 (0.49-2.00) 

Lag 1: 0.52 (0.22-1.20) 

Lag 2: 1.29 (0.75-2.22) 

Lag 3: 1.29 (0.69-2.43) 

Lag 4: 1.47 (0.87-2.50) 

Lower Respiratory Disease 

Lag 0: 1.06 (0.78-1.44) 

Lag 1: 0.85 (0.59-1.22) 

Lag 2: 1.08 (0.72-1.61) 

Lag 3: 1.18 (0.92-1.52) 

Lag 4: 0.72 (0.54-0.96)h 

Reference: Tolbert et al. (2007, 

090316) 

Period of Study: Aug 1998-Dec 2004

Location: Atlanta Metropolitan area, 

Georgia 

Outcome (ICD-9): 

Combined RD group, including: 

Asthma (493, 786.07, 786.09), COPD 

(491, 492, 496), URI (460-465, 460.0, 

477), pneumonia (480-486), and 

bronchiolitis (466.1, 466.11, and 

466.19)) 

Age Groups: All

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (median IQR, range, 10th-90th 

percentiles): 

PM2.5: 17.1 (15.6 

11.0-21.9 

0.8-65.8 

7.9-28.8) 

PM2.5 sulfate: 4.9 (3.9 

2.4-6.2 

PM Increment: 

PM2.5: 10.96 μg/m3

 (IQR) 

PM2.5 sulfate: 3.82 μg/m3

 (IQR) 

PM2.5 total carbon: 3.63 μg/m3

 (IQR) 

PM2.5 OC: 2.61 μg/m3

 (IQR) 

PM2.5 EC: 1.15 μg/m3

 (IQR) 

PM2.5 water-soluble metals: 0.03 μg/m3

December 2009 E-280 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Study Design: Time series 

N: NR for 1998-2004. 

For 1993-2004: 10,234,490 ER visits 

(283,360 and 1,072,429 visits included 

in the CVD and RD groups, 

respectively) 

Statistical Analyses: Poisson 

generalized linear models 

Covariates: Long-term temporal 

trends, season (for RD outcome), 

temperature, dew point, days of week, 

federal holidays, hospital entry and exit 

Season: All

Dose-response Investigated: No

Statistical Package: SAS version 9.1 

Lags Considered: 3-day ma(lag 0 -2) 

0.5-21.9 

1.7-9.5) 

PM2.5 OC: 4.4 (3.8 

2.7-5.3 

0.4-25.9 

2.1-7.2) 

PM2.5 EC: 1.6 (1.3 

0.9-2.0 

0.1-11.9 

0.6-3.0) 

PM2.5 water-soluble metals: 0.030 

(0.023 

0.014-0.039 

0.003-0.202 

0.009-0.059) 

Monitoring Stations: 1 

Copollutant (correlation): Between 

PM2.5 and: 

PM10: r = 0.84 

O3: r = 0.62 

NO2: r = 0.47 

CO: r = 0.47 

SO2: r = 0.17 

PM10-2.5: r = 0.47; 

PM2.5 SO4: r = 0.76; 

PM2.5 EC: r = 0.65; 

PM2.5 OC: r = 0.70; 

PM2.5 TC: r = 0.71; 

PM2.5 water-sol metals: 

r = 0.69 

OHC: r = 0.50 

Between PM2.5 SO4 and: PM10: r = 0.69 

O3: r = 0.56 

NO2: r = 0.14 

CO: r = 0.14 

SO2: r = 0.09 

PM10-2.5: r = 0.32; 

PM2.5: r = 0.76; 

PM2.5 EC: r = 0.32; 

PM2.5 OC: r = 0.33; 

PM2.5 TC: r = 0.34; 

PM2.5 water-sol metals: 

r = 0.65 

OHC: r = 0.47 

Between PM2.5 EC and: PM10: r = 0.61 

O3: r = 0.40 

NO2: r = 0.64 

CO: r = 0.66 

SO2: r = 0.22 

PM10-2.5: r = 0.49 

PM2.5: r = 0.65 

PM2.5 SO4: r = 0.32 

PM2.5 OC: r = 0.82 

PM2.5 TC: r = 0.91 

PM2.5 water soluble metals: r = 0.52 

OHC: r = 0.35 

Between PM2.5 OC and: PM10: r = 0.65 

O3: r = 0.54 

NO2: r = 0.62 

CO: r = 0.59 

SO2: r = 0.17 

PM10-2.5: r = 0.49 

PM2.5: r = 0.70 

PM2.5 SO4: r = 0.33 

PM2.5 EC: r = 0.82 

PM2.5 TC: r = 0.98 

PM2.5 water-sol metals: 

r = 0.49 

OHC: r = 0.37 

Between PM2.5 total carbon and: PM10: r 

= 0.67 

O3: r = 0.52 

NO2: r = 0.65 

CO: r = 0.63 

SO2: r = 0.19 

PM10-2.5: r = 0.51 

PM2.5: r = 0.71 

(IQR) 

Risk ratio [95% CI] (single pollutant 

models): 

PM2.5: 

RD: 1.005 [0.995-1.015] 

PM2.5 sulfate: 

RD: 1.007 [0.996-1.018] 

PM2.5 total carbon: 

RD: 1.001 [0.993-1.008] 

PM2.5 OC: 

RD: 1.003 [0.995-1.011] 

PM2.5 EC: 

RD: 0.996 [0.989-1.004] 

PM2.5 water-soluble metals: 

RD: 1.005 [0.995-1.015] 

December 2009 E-281 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

PM2.5 SO4: r = 0.34 

PM2.5 EC: r = 0.91 

PM2.5 OC: r = 0.98 

PM2.5 water-sol metals: 

r = 0.52 

OHC: r = 0.38 

Between PM2.5 water-soluble metals 

and: PM10: r = 0.73 

O3: r = 0.43 

NO2: r = 0.32 

CO: r = 0.35 

SO2: r = 0.06 

PM10-2.5: r = 0.50 

PM2.5: r = 0.69 

PM2.5 SO4: r = 0.65 

PM2.5 EC: r = 0.52 

PM2.5 OC: r = 0.49 

PM2.5 TC: r = 0.52 

Reference: Wong et al. (2006, 093266) 

Period of Study: 2000-2002 

Location: Hong Kong (8 districts) 

General Practitioner Visits 

Outcome (ICPC-2): Respiratory 

diseases/symptoms: upper respiratory 

tract infections (URTI), lower respiratory 

infections, influenza, asthma, COPD, 

allergic rhinitis, cough, and other 

respiratory diseases 

Age Groups: All ages 

Study Design: Time series 

N: 269,579 visits 

Statistical Analyses: GAM, Poisson 

regression 

Covariates: Season, day of the week, 

climate

Season: NR 

Dose-response Investigated? No 

Statistical Package: S-Plus 

Lags Considered: 0-3 days

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (min-max): 

35.7 (9-120) 

SD = 16.7 

Monitoring Stations: 1 per district 

Copollutant (correlation): 

PM10: r = 0.94 

PM Increment: 10 μg/m3

RR Estimate [CI]: 

Overall URTI 

1.021 [1.010,1.032] 

Notes: RRs are also reported for each 

individual general practitioner yielding 

similar results 

Reference: Yang Q et al. (2004, 

087488) 

Period of Study: Jun 1995-Mar 1999 

Location: Vancouver area, British 

Columbia 

Hospital Admissions 

Outcome (ICD-9): Respiratory 

diseases (460-519), pneumonia only 

(480-486), asthma only (493) 

Age Groups: 0-3 yr 

Study Design: Case control, 

bidirectional case-crossover (BCC), and 

time series (TS)

N: 1610 cases 

Statistical Analyses: Chi-square test, 

Logistic regression, GAM (time-series), 

GLM with parametric natural cubic 

splines 

Covariates: Gender, socioeconomic 

status, weekday, season, study yr, 

influenza epidemic month

Season: Spring, summer, fall, winter 

Dose-response Investigated? No 

Statistical Package: SAS (Case 

control and BCC), S-Plus (TS) 

Lags Considered: 0-7 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (min-max): 

7.7 (2.0-32.0) 

SD = 3.7 

Monitoring Stations: NR (data 

obtained from Greater Vancouver 

Regional District Air Quality Dept) 

Copollutant (correlation): 

PM10: r = 0.83 

PM10-2.5: r = 0.39 

CO: r = 0.24 

O3: r = -0.03 

NO2: r = 0.37 

SO2: r = 0.43 

PM Increment: 4.0 μg/m3 (IQR) 

OR Estimate [CI]: 

Values NR 

Notes: Author states that no significant 

association was found between PM2.5

and respiratory disease hospitalizations.

December 2009 E-282 
Reference Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zanobetti and Schwartz 

(2006, 090195) 

Period of Study: 1995-1999 

Location: Boston, MA

Hospital Admission/ED: 

Outcome: Pneumonia (480-487) 

Age Groups: >65 y 

Study Design: Case-crossover, time 

stratified

N: 24,857 for Pneumonia 

Statistical Analyses: Condition logistic 

regression 

Covariates: Season, long term trend, 

day of-the-wk, mean temperature, 

relative humidity, barometric pressure, 

extinction coefficient 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 

Notes: Also looked at MI cohort 

Pollutant: PM non-traffic 

Averaging Time: 24 h 

Percentiles (pneumonia cohort): 

5th: -7.3 

25th: -3.28 μg/m3

50th(Median): -0.88 

75th: 1.92 

95th: 12.11 

PM Component: BC 

Monitoring Stations: 4-5 monitors 

Copollutant (correlation): 

PM non-traffic: 

PM2.5 r = 0.74 

CO r = -0.01 

NO2 r = 0.14 

O3 r = -0.47 

BC r = -0.01 

PM Increment: PM non-traffic lag 0: 

13.44 μg/m3

PM non-traffic lag 0-1 avg: 10.28 μg/m3

% change in Pneumonia: 

PM non-traffic -0.57 [-7.51, 6.36] 

lag 0 

PM non-traffic -0.94 [-7.20, 5.32] 

mean lag 1 

Reference: Zhong et al. (2006, 

093264) 

Period of Study: Apr-Oct 2002 

Location: Cincinnati, Ohio 

Hospital Admissions 

Outcome (ICD-9): Asthma (493-

493.91) 

Age Groups: 1-18 yr 

Study Design: Time series 

N: 1254 admissions 

Statistical Analyses: Poisson multiple 

regression, GAM 

Covariates: Season, temperature, 

humidity, O3, day of the week

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: 1-5 days 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 

Apr: 12.4 (3.8) 

May: 13.6 (5.8) 

Jun: 21.6 (9.9) 

Jul: 25.8 (11.9) 

Aug: 20.3 (8.7) 

Sep: 19.5 (11.1) 

Oct: 12.8 (6.4) 

Monitoring Stations: NR (data 

obtained from the National Virtual Data 

System) 

Copollutant (correlation): NR 

Notes: Author states all pairwise 

correlations were insignificant 

PM Increment: NR 

RR Estimate [CI]: 

NR 

Notes: This study focused primarily on 

aeroallergens and asthma visits 

Reference: Zanobetti and Schwartz 

(2006, 090195) 

Period of Study: 1995-1999 

Location: Boston, MA 

Outcome: Pneumonia (480-487) 

Age Groups: >65 y 

Study Design: Case-crossover, time 

stratified

N: 24,857 for Pneumonia 

Statistical Analyses: Condition logistic 

regression 

Covariates: Season, long term trend, 

day of-the-wk, mean temperature, 

relative humidity, barometric pressure, 

extinction coefficient 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 

Notes: Also looked at MI cohort 

Pollutant: PM2.5

Averaging Time: 24 h 

Percentiles (pneumonia cohort): 

25th: 7.23 μg/m3

50th(Median): 11.10 

75th: 16.14 

PM Component: Black Carbon (BC), 

PM non-traffic 

Monitoring Stations: 4-5 monitors 

Copollutant (correlation): 

PM2.5: 

CO r = 0.52 

NO2 r = 0.55 

O3 r = 0.20 

BC r = 0.66 

PM non-traffic r = 0.74

PM Increment: PM2.5 lag 0: 

17.17 μg/m3

PM2.5 lag 0-1 avg: 16.32 μg/m3

% change in Pneumonia: 

6.48[1.13, 11.43] 

lag 0 

5.56[-0.45, 11.27] 

mean lag 1 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-283 
Table E-15. Short-term exposure-respiratory-ED/HA-Other Size Fractions. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Andersen et al. (2007, 

093201) 

Period of Study: 2001-2004 

Location: Copenhagen, Denmark 

Outcome (ICD10): 

Respiratory disease (J41-46) 

Asthma (J45, 46) 

Age Groups: 5-18 and >65 

Study Design: Time-series 

N: 1327 days 

~1.5 million people at-risk 

Statistical Analyses: Poisson 

regression, GAM. 

Covariates: Influenza epidemics, 

pollen, temperature, dew point, day-ofweek, holiday, season. 

Season: All 

Dose-response Investigated? No 

Statistical Package: R with gam and 

mgcv packages. 

Lags Considered: 0-5

Pollutant: Number concentration (NC) 

of ultrafine & accumulation mode 

particles 

Averaging Time: 24 h 

Mean particles/cm3 (SD): 

NCtot (total): 8116 (3502) 

25th: 4959 

50th: 6243 

75th: 8218 

99th: 16189 

IQR: 3259 

NC100 (<100 nm): 6847 (2864) 

25th: 5738 

50th (Median): 7358 

75th: 9645 

99th: 19895 

IQR: 3907 

Mean particles/cm3

 for 4 size modes 

(median diameter (nm) noted): 

NCa12: 493(315) 

NCa23: 2253 (1364) 

NCa57: 5104 (2687) 

NCa212: 6847 (2864) 

Monitoring Stations: 3 (Background, 

rural Background, urban Curbside, 

urban) 

Notes: NC exposure data available for 

n = 578 days. Information on 

distribution of 4 size modes provided in 

the paper. 

Copollutant (correlation): 

NCtot and PM10: r = 0.39 

NCtot and PM2.5: r = 0.40 

NCtot and NO2: r = 0.68 

PM10 and PM2.5: r = 0.8 

“Low or no” correlations between 4 size 

modes 

NCa212 and PM2.5: r = 0.8 

NCa212 and PM10: r = 0.63 

NCa57 and NO2: r = 0.57 

Notes: selected correlations reported in 

text, all correlations in annex to the 

manuscript 

PM Increment: Based on the IQR, 

specific to metric (see below). 

RR Estimate: 

Single pollutant results, Asthma, 

(5-18 yr), lag 0-5: 

PM2.5: 1.15 [1, 1.32], IQr = 5 

NCtot: 1.07 [0.98, 1.17], IQr = 3907 

NC100: 1.06 [0.97, 1.16], IQr = 3259 

NCa12: 1.08 [0.99, 1.18], IQr = 342 

NCa212: 1.08 [1, 1.17], IQr = 495 

NCa23: 1.09 [0.98, 1.21], IQr = 1786 

NCa57: 1.02 [0.94, 1.12], IQr = 3026 

2-pollutant results: 

NCa212 w/ PM10: 1.1 [0.96, 1.13], 

IQr = 495 

NCtot w/ PM10: 1.03 [0.92, 1.15] 

NCtot w/ PM2.5: 1.04 [0.85, 1.28] 

All RD, (>65 yr), lag 0-4, single pollutant 

results: 

PM2.5: 1 [0.95, 1.05] 

NCtot: 1.04 [1, 1.07] IQr = 3907 

NC100: 1.03 [0.99, 1.07], IQr = 3259 

NC12: 1.01 [0.98, 1.05], IQr = 342 

NC212: 1.04 [1.01, 1.08], IQr = 495 

NCa23: 0.99 [0.94, 1.03], IQr = 1786 

NCa57: 1.04 [1, 1.08], IQr = 3026 

2-pollutant results: 

NCa212 w/ PM10: 1.01 [0.96, 1.07], 

IQr = 495 

NCtot w/ PM2.5: 0.97 [0.89, 1.05] 

NCtot w/ PM10: 1 [0.96, 1.05] 

Notes: Multipollutant model results also 

included for models with 4 size modes. 

Reference: Agarwal et al. (2006, 

099086) 

Period of Study: 2000-2003 

Location: Safdarjung area of Delhi 

Outcome (ICD-NR): COPD, asthma, 

emphysema 

Age Groups: NR 

Study Design: Time series 

N: NR 

Statistical Analyses: Kruskal-Wallis 

one-way analysis, Chi-square, 

Multivariate linear regression 

Covariates: Temp (min & max), relative 

humidity at 0830 and 1730 h, wind 

speed 

Season: I (Jan-Mar), II (Apr-Jun), III 

(Jul-Sep), IV (Oct-Dec) 

Dose-response Investigated? Yes 

Statistical Package: SPSS 

Lags Considered: NR 

Pollutant: SPM (Suspended PM) 

Averaging Time: 8 h

Mean μg/m3

 (SD): 

Qtr I: 297.5 (34.6) 

Qtr II: 398.0 (85.6) 

Qtr III: 220.0 (78.0) 

Qtr IV: 399.0 (54.6) 

Monitoring Stations: 2 

Copollutant (correlation): 

RSPM: r = 0.771 

Other variables: 

RH0830: r = -0.482 

RH1730: r = -0.531 

COPD: r = 0.474 

PM Increment: NR 

RR Estimate [CI]: NR 

Notes: This study analyzed seasonal 

variation of pollutants and health 

outcomes and correlations among the 

variables 

December 2009 E-284 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Agarwal et al. (2006, 

099086) 

Period of Study: 2000-2003 

Location: Safdarjung area of Delhi 

Outcome (ICD-NR): COPD, asthma, 

emphysema 

Age Groups: NR 

Study Design: Time series 

N: NR 

Statistical Analyses: Kruskal-Wallis 

one-way analysis, Chi-square, 

Multivariate linear regression 

Covariates: Temp (min & max), relative 

humidity at 0830 and 1730 h, wind 

speed 

Season: I (Jan-Mar), II (Apr-Jun), III 

(Jul-Sep), IV (Oct-Dec) 

Dose-response Investigated? Yes 

Statistical Package: SPSS 

Lags Considered: NR 

Pollutant: RSPM (Respirable 

Suspended PM <10 μm) 

Averaging Time: 8 h

Mean μg/m3

 (SD): 

Qtr I: 119.0 (19.8) 

Qtr II: 132.0 (28.4) 

Qtr III: 75.0 (23.4) 

Qtr IV: 168.0 (40.6) 

Monitoring Stations: 2 

Copollutant (correlation): SPM: 

r = 0.771 

Other variables: 

Temp (min): r = -0.420 

COPD: r = 0.353 

PM Increment: NR 

RR Estimate [CI]: NR 

Notes: This study analyzed seasonal 

variation of pollutants and health 

outcomes and correlations among the 

variables 

Reference: Arbex et al. (2007, 091637) 

Period of Study: Mar 2003-Jul 2004 

Location: Araraquara, Sao Paulo State, 

Brazil 

Hospital Admission 

Outcome (ICD10): Asthma (J15, J45)

Age Groups: All

Study Design: Time-series 

N: 493 days, 1 hospital, 640 admissions

Statistical Analyses: Generalized 

linear Poisson regression model with 

natural cubic spline, Mann-Whitney U 

Test 

Covariates: Temperature and humidity 

Season: All 

Dose-response Investigated? Yes, 

quintile analysis 

Statistical Package: SPSS V.11 & 

Splus 4.5 

Lags Considered: 0-9 

Pollutant: TSP 

Averaging Time: 24 h 

Mean (SD): 46.8 μg/m3 (24.4) 

Range (Min, Max): 

6.7-137.8 μg/m3

Monitoring Stations: 1 

Notes: TSP used as a proxy for fine & 

ultrafine particles since it is composed 

of 85-95% PM2.5. 

Copollutant (correlation): NR

PM Increment: 10 μg/m3 

% Increase 

6.96 [1.4-12.86] 2-day ma 

9.090 [3.12-15.40] 3 day ma 

10.28 [4.05-16.90] 4-day ma 

11.63 [5.46-19.318] 5 day ma 

12.61 [5.68-20.00] 6-day ma 

12.56 [5.47-20.13] 7-day ma 

% Increase by TSP quintile: 

9.25-28.45 μg/m3: : 1.00 

28.46-48.85 μg/m3

: : 1.55 [045-5.77] 

48.86-69.06 μg/m3: : 2.46 [1.08-5.60] 

69.07-88.44 μg/m3

: : 2.77 [1.32-5.84] 

88.45-108.9 μg/m3

: : 2.94 [1.48-5.85] 

Notes: No TSP threshold for asthma 

admissions noted. Analysis of lag 

structure indicated that the acute effect 

of TSP on admissions started 1 day 

after TSP concentration increase and 

remained unchanged for next 4 days. 

Notes: To evaluate the association 

between TSP generated from burning 

sugar cane and asthma hospital 

admissions. 

Reference: Bartzokas et al. (2004, 

093252) 

Period of Study: Jun 1992-May 2000 

Location: Athens, Greece 

Outcome: Respiratory and 

cardiovascular diseases (combined) 

Age Groups: NR 

Study Design: Time series 

N: 1554 patients 

Statistical Analyses: Simple linear 

regression and linear stepwise 

regression, Pearson correlation 

Covariates: Temperature, atmospheric 

pressure, relative humidity, wind speed 

Season: Warm (May-Sep) and cold 

(Nov-Mar) 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: NR 

Pollutant: PM4.5 (black smoke) 

Averaging Time: 10-day ma 

Mean μg/m3 (SD): NR

Monitoring Stations: 1 

Copollutant (correlation): N 

PM Increment: NR 

Correlation with Number of 

Admissions: 

Entire yr 

Original: r = 0.18 

Smoothed: r = 0.31 

Warm period 

Original: r = 0.19 

Smoothed: r = 0.30 

Cold period 

Original: r = 0.18 

Smoothed: r = 0.34 

*All above values are statistically 

significant 

December 2009 E-285 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Erbas et al. (2005, 073849) 

Period of Study: Jul 1989-Dec 1992 

Location: Melbourne, Australia 

Outcome (ICD): 

COPD (490-492, 494, 496) 

Asthma (493) 

Age Groups: NR 

Study Design: Time series 

N: NR 

Statistical Analyses: GLM, GAM, 

Parameter Driven Poisson Regression, 

Transitional Regression, SeasonalTrend decomposition based on Loess 

smoothing for seasonal adjustment 

Covariates: Secular trends, 

seasonality, relative humidity, dry bulb 

temp, dew point temp 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus, SAS 

Lags Considered: 0-5 days 

Pollutant: PM 0.1-1 (API) 

Averaging Time: 24 h

Mean (min-max): NR 

Monitoring Stations: 9

Copollutant (correlation): NR 

PM Increment: Increase from the 10th90th percentile (value NR) 

RR Estimate [CI]: 

COPD 

GAM: 

0.95 [0.91,1.00] 

GLM, PDM, TRM: NR 

Asthma 

NR 

Notes: This study was used to 

demonstrate that conclusions are highly 

dependent on the type of model used 

Reference: Halonen et al. (2008, 

189507) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome: Respiratory Hospitalizations 

& Mortality (ICD 10: J00-99) 

Age Groups: 65+ yr

Study Design: Time series 

N: NR 

Statistical Analyses: Poisson, GAM 

Covariates: Temperature, humidity, 

influenza epidemics, high pollen 

episodes, holidays 

Dose-response Investigated? No 

Statistical Package: R 

Lags Considered: Lags 0-3 & 5-day 

(0-4) mean 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD): NR

Min: 1.1 

25th percentile: 5.5 

50th percentile: 9.5 

75th percentile: 11.7 

Max: 69.5 

Monitoring Stations: NR 

Copollutant: PM<0.03, PM0.03-0.1, 

PM<0.1, 

PM<0.10.29, PM10-2.5, CO, NO2

Co-pollutant Correlation 

PM<0.03: 0.14 

PM0.03-0.1: 0.48 

PM<0.1: 0.35 

PM<0.10.29: 0.88 

PM10-2.5: 0.25 

PM Increment: Interquartile 

Percent Change (Lower CI, Upper 

CI): 

All Respiratory Mortality 

Lag 0: 2.67 (-0.39, 5.82) ‡ 

Lag 1: 1.59 (-1.43, 4.70) 

Lag 2: 0.03 (-2.99, 3.16) 

Lag 3: -0.11 (-3.13, 3.01) 

5-day mean: 1.39 (-2.83, 5.81) 

Pneumonia HA 

Lag 0: 0.93 (-0.85, 2.75) 

Lag 1: 2.41 (0.64, 4.21) 

Lag 2: 1.48 (-0.27, 3.26) 

Lag 3: 1.91 (0.14, 3.70) 

5-day mean: 3.10 (0.60, 5.65) 

Asthma + COPD HA 

Lag 0: 2.48 (0.60, 4.39) 

Lag 1: 2.62 (0.78, 4.49) 

Lag 2: 1.22(-0.62, 3.10) 

Lag 3: 0.59 (-1.28, 2.49) 

5-day mean: 2.49 (-0.08, 5.12) 

Other HA 

Lag 0: 0.05 (-2.38, 2.54) 

Lag 1: 0.2 (-2.17, 2.62) 

Lag 2: 2.03 (-0.29, 4.41) 

Lag 3: 1.72 (-0.63, 4.12) 

5-day mean: 1.88 (-1.50, 5.36) 

*p < 0.05, ‡p < 0.10 

December 2009 E-286 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Llorca et al. (2005, 087825) 

Period of Study: Jan 1992-Dec 1995 

Location: Torrelavega, Spain 

Outcome (ICD-9): Respiratory (460-

519) and cardiac (390-459) admissions 

(analyzed combined and individually) 

Age Groups: NR 

Study Design: Time series 

N: 18,137 admissions 

Statistical Analyses: Stepwise multiple 

linear regression, Poisson regression, 

Spearman correlation 

Covariates: Influenza, day of week, 

wind speed, northeast and southwest 

winds, minimum and maximum 

temperature 

Season: NR 

Dose-response Investigated? No 

Statistical Package: STATA 

Intercooled, Release 6 

Lags Considered: NR 

Pollutant: TSP (total suspended 

particles) 

Averaging Time: 24 h 

Mean μg/m3 (SD): 

48.8 (23.7) 

Monitoring Stations: 3 

Copollutant (correlation): 

SO2: r = -0.400 

SH2: r = -0.392 

NO: r = -0.109 

NO2: r = -0.120 

Other variables: 

Rain: r = -0.339 

Max temp: r = 0.071 

Min temp: r = -0.003 

Avg temp: r = 0.035 

Wind speed: r = -0.357 

PM Increment: NR 

Rate Ratio Estimate [CI]: 

Cardiorespiratory Admissions 

Single-pollutant model: 0.92 [0.86,0.98] 

Five-pollutant model: 1.05 [0.97,1.14] 

Respiratory Admissions 

Single-pollutant model: 0.98 [0.89,1.08] 

Five-pollutant model: 0.91 [0.80,1.02] 

Reference: Michaud et al. (2004, 

188530) 

Period of Study: Jan 1997-May 2001 

Location: Hilo, Hawaii 

ED visits 

Outcome: Asthma/COPD (490-496) 

Respiratory Irritation (506-508) 

Age Groups: All

Study Design: Time-series

N: 1,561 ER visits 

Statistical Analyses: Multiple linear 

regression 

Covariates: Hourly temperature, 

minimum daily temperature, minimum 

daily temperature, humidity, yr, month, 

day of the week 

Season: all 

Dose-response Investigated? No 

Statistical Package: 

STATA 6.0 

SAS 

Lags Considered: Previous night, 

1,2,3

Pollutant: PM1 

Averaging Time: 24-h avg

Mean (SD): 1.91 (2.95) μg/m3

Range (Min, Max): 

0.0, 56.6 μg/m3

Monitoring Stations: 2 

Notes: Copollutant (correlation): NR

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Asthma, COPD (499-496): Adjusted for 

day, month & yr: 

1.11 (0.92, 1.34), 00: 00-6: 00AM 

1.14 (1.03, 1.26), lag 1 

1.06 (0.83, 0.94), lag 2 

0.91 (0.06, 1.05), lag 3 

Asthma (493, 495): Adjusted for day, 

month & yr: 

1.03 (0.90, 1.42), 00: 00-6: 00AM 

1.02 (0.94, 1.21), lag 1 

1.02 (0.99, 1.23), lag 2 

0.97 (0.69, 1.15), lag 3 

Bronchitis (490, 491): Adjusted for day, 

month & yr: 

1.02 (0.82, 1.41), 00: 00-6: 00AM 

1.07 (1.18, 1.49), lag 1 

0.97 (0.60, 1.34), lag 2 

0.93 (0.43, 1.18), lag 3 

Notes: Crude and estimates adjusted 

for month and yr only also presented. 

Notes: Volcanic fog = vog 

December 2009 E-287 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Migliaretti et al. (2005, 

088689) 

Period of Study: 1997-1999 

Location: Turin, Italy

Cases: Asthma (493) 

Controls: Admissions for nonrespiratory or cardiac conditions (460-

487, 490-493, 494-496, 500-519, 390-

405, 410-429) 

Age Groups: 0-14, 15-64, >64

Study Design: Case-control

N: Cases: 1,401 

Controls: 201,071 

Statistical Analyses: Logistic 

regression 

Covariates: Gender, age, daily mean 

temperature, season, day of week, 

holidays, education level 

Season: All 

Dose-response Investigated? No 

Lag: 0- to 2-day avg 

Pollutant: TSP 

Averaging Time: Means of daily total 

levels at stations 

Mean (SD): 105.3 μg/m3 , (44.2) 

Percentiles: 25th: NR 

50th(Median): 96.0 μg/m3

75th NR 

Monitoring Stations: 

10 

Notes: Copollutant (correlation): 

All seasons: NO3

–

TSP = 0.80 

Winter: NO3

–

TSP = 0.77 

Summer: NO3

–

TSP = 0.69

PM Increment: 10 μg/m3 increase 

% Increase, lag 0-2-day avg 

1 pollutant model: 

<15: 1.90[0.40, 3.40] 

15-64: 2.30 [-0.01, 5.20] 

>64: 2.30 [1.10, 3.60] 

Total: 2.30[1.10, 3.60] 

% Increase, lag 0-2-day avg 

2 pollutant model: 

<15: -0.12 [-0.03, 2.50] 

15-64: 0.90 [-0.04, 5.61] 

>64: 1.2 [-0.01, 4.32] 

Total: 0.91 [-0.02, 3.11]

Reference: Migliaretti et al. (2004, 

087425) 

Period of Study: 1997-1999 

Location: Turin, Italy

Outcome: 

Cases: Asthma (493) 

Controls: Non-respiratory or cardiac 

admissions (460-487, 490-493, 494-

496, 500-519, 390-405, 410-429) 

Age Groups: 0-15 

Study Design: Case-control

N: Cases: 1,060 

Controls: 25,523 

Statistical Analyses: Logistic 

regression μg/m3 increase 

Covariates: Gender, age, daily mean 

temperature, season, day of week, 

holidays, solar radiation 

Season: All 

Lags Considered: 1- to 3-day avg 

Pollutant: Total suspended particulate 

Averaging Time: Mean of admission 

day and 3 preceding days 

Mean (SD): 114.5 μg/m3, (42.8) 

Percentiles: 

25th: NR 

50th(Median): 109.9 μg/m3

75th: NR 

Monitoring Stations: 10 

Notes: Copollutant (correlation): 

TSP-NO: 0.76

PM Increment: 10 μg/m3

% Increase, lag 1-3-day avg 

<4 yr: 1.8% [0.00, 3.05] 

4-15 yr: 3.0% [0.01, 5.08]

all: 1.8% [0.03, 3.02] 

adjusted for all covariates 

Notes: Multipollutant models also used 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: 1999-2000 (1-yr 

period) 

Location: Vienna and Lower Austria 

Outcome (ICD-9): Bronchitis, 

emphysema, asthma, bronchiectasis, 

extrinsic allergic alveolitis, and chronic 

airway obstruction (490-496) 

Age Groups: 3.0-5.9 yr 

7-10 yr 

65+ yr 

Study Design: Time series 

N: 366 days (admissions NR) 

Statistical Analyses: GAM 

Covariates: SO2, NO, NO2, O3, 

temperature, humidity, and day of the 

week 

Season: NR 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 2000 

Lags Considered: 0-14 days 

Pollutant: PM1

Averaging Time: 24 h 

Mean μg/m3 (SD): NR 

Monitoring Stations: NR 

Copollutant (correlation): NR 

PM Increment: NR 

Effect parameters (Vienna children): 

Respiratory Health 

Male sex = 0.098 

Allergy = 0.238 

Asthma in family = 0.190 

Traffic = 0.112 

Log Asthma Score 

Allergy = 0.210 

Asthma in family = 0.112 

Rain = 0.257 

*only significant coefficients are 

presented 

Association with tidal lung function: 

β = -1.059 (p-value = 0.060) 

Notes: No significant associations 

between PM and respiratory mortality 

were found for either sex. Data is also 

provided for children in the rural area 

where age, allergy, asthma in family, 

passive smoking, and PM fraction had 

significant coefficients. 

December 2009 E-288 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peel et al. (2005, 056305) 

Period of Study: Jan 1993-Aug 2000 

Location: Atlanta, Georgia

Hospital Admission/ED: 

ED visits 

Outcome: Asthma 493, 786.09 

COPD 491, 492, 496 

URI 460-466, 477 

Pneumonia 480-486 

Age Groups: All ages. Secondary 

analyses conducted by age group: 

Infants 0-1 yr 

Pediatric asthma 2-18 yr 

Adults >18 yr

Study Design: Case-control 

All respiratory disease vs. finger 

wounds 

N: 31 hospitals 

ED visits NR 

Statistical Analyses: Poisson 

generalized linear models 

General linear models 

Covariates: Avg temperature and dew 

point, pollen counts 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.3 

S-Plus 2000 

Lags Considered: 0-7 days and 

14-day distributed lag 

Pollutant: UF (10-100nm) 

Averaging Time: 24-h avg 

Mean (SD): 3800 (40700) 

Percentiles: 

10th: 11500 

90th: 74600 

PM Component: Oxygenated 

hydrocarbons (OH), sulfate, acidity, EC 

(EC), OC (OC), water-soluble transition 

metals 

Monitoring Stations: “Several” 

Copollutant (correlation): 

PM10: r = -0.13 

O3: r = -0.13 

NO2: r = 0.26 

CO: r = 0.10 

SO2: r = 0.24 

PM2.5: r = -0.16 

PM10-2.5: r = 0.13 

Increment: 

30,000 #/cm3

All Respiratory Disease 

0.984 [0.968-1.000] 

URI 

0.986 [0.966, 1.006] 

Asthma 

0.999 [0.977, 1.021] 

Pneumonia 

0.997 [0.953, 1.002] 

COPD 

0.982 [0.942, 1.022] 

Reference: Simpson et al. (2005, 

087438) 

Period of Study: 1996-1999 

Location: Brisbane, Sydney, 

Melbourne, and Perth, Australia

Outcome: All Respiratory (460-519) 

Asthma (493) 

COPD (490-492) 

Pneumonia, acute bronchitis (466, 

480-486) 

Age Groups: All ages, split into f15-64 

and >64 yr

Study Design: Time-series

N: NR ~64,000 admissions 

Statistical Analyses: GAM w/ LOESS 

smoothers 

GLM w/ natural and penalized spline 

smoothers 

Covariates: Temperature, relative 

humidity, rain, day of the week, public 

and school holidays, influenza 

epidemics, and controlled burn events 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: S-Plus 

R Lags Considered: 1-3 days, 0- to 

1-day avg 

Pollutant: BSP (indicator of particles 

<2 μm in diameter) 

(10 -4 m -1) 

Averaging Time: 24-h avg 

Mean (SD): Means only 

Brisbane 0.3 10 -4 m -1 

Sydney 0.3 10 -4 m -1 

Melbourne 0.3 10 -4 m -1 

Perth 0.3 10 -4 m -1 

Range (Min, Max): 

Brisbane 0.0, 2.5 10 -4 m -1 

Sydney 0.0, 1.6 10 -4 m -1 

Melbourne 0.0, 2.2 10 -4 m -1 

Perth 0.1, 1.8 10 -4 m -1 

PM Component: Monitoring Stations: 

“network of sites across each city” 

Copollutant (correlation): NR 

PM Increment: “per unit increase” 

RR Estimate [Lower CI, Upper CI] 

lag: 

Single pollutant model 

Respiratory >64 yr 

1.0401 [1.0045, 1.0770] lag1 

1.0520 [1.0164, 1.0889] lag2; 

1.0451 [1.0093, 1.0821] lag3 

1.0552 [1.0082, 1.1045] lag 0-1 avg 

Asthma 15-64 yr 

1.0641 [1.0006, 1.1315] lag2 

1.0893 [1.0240, 1.1587] lag3 

Asthma + COPD >64 yr 

1.0713 [1.0179, 1.1276] lag3 

1.0552 [1.0082, 1.1045] lag 0-1 avg 

Pneumonia & Acute Bronchitis >64 yr 

1.0587 [1.0013, 1.1193] lag1 

1.0636 [1.0056, 1.1249] lag 2 

1.0769 [1.0046, 1.1544] lag 0-1 avg 

Multipollutant model 

Respiratory admissions >64 yr 

No other pollutants: 

1.0552 [1.0082, 1.1045] lag 0-1 avg 

Max 1 h NO2

1.0028 [0.9513, 1.0572] lag 0-1 avg 

Max 1 h O3

1.0534 [1.0058-1.1033] lag 0-1 avg 

December 2009 E-289 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sinclair and Tolsma (2004, 

088696)

Period of Study: 25 mo 

Location: Atlanta, Georgia 

Outpatient Visits 

Outcome: Asthma (493) 

URI (460, 461, 462, 463, 464, 465, 466, 

477) 

LRI (466.1, 480, 481, 482, 483, 484, 

485, 486). 

Age Groups: < = 18 yr; 18+ yr 

(asthma); All ages (URI//LRI) 

Study Design: Times series

N: 25 mo 

260,000-275,000 health plan members 

(Aug 1998-Aug 2000) 

Statistical Analyses: Poisson GLM 

Covariates: Season, day of week, 

federal holidays, study months 

Season: NR 

Dose-response Investigated?: No 

Statistical Package: SAS 

Lags Considered: Three 3-day ma 

(0-2, 2-5, 6-8) 

Pollutant: PM2.5-10 (μg/m3) 

Averaging Time: 24-h avg 

Mean (SD): PM coarse mass 

(2.5-10 μm)-9.67 μg/m3

 (4.74) 

Monitoring Stations: 1 

Copollutant (correlation): NR 

PM Increment: 4.74 (1 SD)

RR Estimate [Lower CI, Upper CI] 

lag: 

Child Asthma: 

Coarse PM = 1.053 (S) 

3-5 day lag 

URI: 

Course PM = 1.021 (S) 

3-5 day lag 

LRI: 

Coarse PM = 1.07 (S) 

3-5 day lag 

Notes: Numerical findings for significant 

results only presented in manuscript. 

Results for all lags presented 

graphically for each outcome (asthma, 

URI, and LRI). 

Reference: Sinclair and Tolsma (2004, 

088696)

Period of Study: 25 mo 

Location: Atlanta, Georgia 

Outpatient Visits

Outcome: Asthma (493) 

URI (460, 461, 462, 463, 464, 465, 466, 

477) 

LRI (466.1, 480, 481, 482, 483, 484, 

485, 486). 

Age Groups: < = 18 yr, 18+ yr (asthma)

All ages (URI//LRI) 

Study Design: Times series

N: 25 mo 

260,000-275,000 health plan members 

(Aug 1998-Aug 2000) 

Statistical Analyses: Poisson GLM 

Covariates: Season, day of week, 

federal holidays, study months 

Season: NR 

Dose-response Investigated?: No 

Statistical Package: SAS 

Lags Considered: Three 3-day ma 

(0-2, 2-5, 6-8)

Pollutant: UF (PM10-100 nm) 

Averaging Time: 24 h avg 

Mean (SD): PM10-100 nm area 

(μm2/cm3

)- 249.33 (244.09) 

Monitoring Stations: 1

Copollutant (correlation): NR 

PM Increment: NR

RR Estimate [Lower CI, Upper CI] 

lag: 

Adult Asthma: 

Ultrafine PM area = 1.223 (S) 

3-5 days lag 

URI: 

Ultrafine PM: = 1.041 (S) 

0-2 days lag 

LRI: 

Ultrafine PM area = 1.099 (S) 

6-8 days lag 

Notes: Numerical findings for significant 

results only presented in manuscript. 

Results for all lags presented 

graphically for each outcome (asthma, 

URI, and LRI). 

December 2009 E-290 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Slaughter et al. (2005, 

073854)

Period of Study: Jan 1995-Jun 2001 

Location: Spokane, WA 

Hospital Admissions and ED visits 

Outcome: All respiratory (460-519) 

Asthma (493) 

COPD (491,492, 494,496) 

Pneumonia (480-487) 

Acute URI not including colds and 

sinusitis (464, 466, 490) 

Age Groups: All, 15+ yr for COPD 

Study Design: Time series

N: 2373 visit records 

Statistical Analyses: Poisson 

regression, GLM with natural splines. 

For comparison also used GAM with 

smoothing splines and default 

convergence criteria. 

Covariates: Season, temperature, 

relative humidity, day of week 

Season: All 

Dose-response Investigated?: No 

Statistical Package: SAS, SPLUS 

Lags Considered: 1 -3 days 

Pollutant: PM1

Averaging Time: 24-h avg 

Range (90% of concentrations): 

3.3-17.6 μg/m3

Monitoring Stations: 1

Copollutant (correlation): 

PM1

PM2.5 r = 0.95 

PM10 r = 0.50 

PM10-2.5 r = 0.19 

CO r = 0.63 

PM Increment: 10 μg/m3 

RR Estimate [Lower CI, Upper CI] 

lag: 

ED visits: 

PM1 

All Respiratory 

Lag 1: 1.01 [0.98, 1.04] 

Lag 2: 1.02 [0.99, 1.06] 

Lag 3: 1.02 [0.99,1.06] 

Acute Asthma 

Lag 1: 1.03 [0.97, 1.09] 

Lag 2: 0.99 [0.93, 1.05] 

Lag 3: 1.02 [0.96, 1.08] 

COPD (adult) 

Lag 1: 0.96 [0.87, 1.05] 

Lag 2: 1.02 [0.93, 1.12] 

Lag 3: 0.99 [0.90, 1.09]

Reference: Slaughter et al. (2005, 

073854)

Period of Study: Jan 1995-Jun 2001 

Location: Spokane, WA 

Hospital Admissions and ED visits 

Outcome: All respiratory (460-519) 

Asthma (493) 

COPD (491,492, 494,496) 

Pneumonia (480-487) 

Acute URI not including colds and 

sinusitis (464, 466, 490) 

Age Groups: All, 15+ yr for COPD 

Study Design: Time series

N: 2373 visit records 

Statistical Analyses: Poisson 

regression, GLM with natural splines. 

For comparison also used GAM with 

smoothing splines and default 

convergence criteria. 

Covariates: Season, temperature, 

relative humidity, day of week 

Season: All 

Dose-response Investigated?: No 

Statistical Package: SAS, SPLUS 

Lags Considered: 1 -3 days 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Range (90% of Concentrations): 

4.2-20.2 μg/m3

Monitoring Stations: 1

Notes: Copollutant (correlation): 

PM2.5

PM1 r = 0.95 

PM10 r = 0.62 

PM10-2.5 r = 0.31 

CO r = 0.62 

Temperature r = 0.21 

PM Increment: 10 μg/m3 

RR Estimate [Lower CI, Upper CI] 

lag: 

ER visits: 

PM2.5

All Respiratory 

Lag 1: 1.01 [0.98, 1.04] 

Lag 2: 1.02 [0.99, 1.04] 

Lag 3: 1.02 [0.99, 1.05] 

Acute Asthma 

Lag 1: 1.03 [0.98, 1.09] 

Lag 2: 1.00 [0.95, 1.05] 

Lag 3: 1.01 [0.96, 1.06] 

COPD (adult) 

Lag 1: 0.96 [0.89, 1.04] 

Lag 2: 1.01 [0.93, 1.09] 

Lag 3: 1.00 [0.93, 1.08] 

Hospital Admissions: 

PM2.5

All Respiratory 

Lag 1: 0.98 [0.94, 1.01] 

Lag 2: 0.99 [0.96, 1.03] 

Lag 3: 1.01 [ 0.98, 1.05] 

Asthma 

Lag 1: 1.01 [0.91, 1.11] 

Lag 2: 1.03 [0.94, 1.13] 

Lag 3: 1.02 [0.93, 1.13] 

COPD (adult) 

Lag 1: 0.99 [0.91, 1.08] 

Lag 2: 1.06 [0.98, 1.16] 

Lag 3: 1.03 [0.94, 1.12]

December 2009 E-291 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zanobetti and Schwartz 

(2006, 090195) 

Period of Study: 1995-1999 

Location: Boston, MA 

Outcome: Pneumonia (480-487) 

Age Groups: >65 y 

Study Design: Case-crossover, time 

stratified

N: 24,857 for Pneumonia 

Statistical Analyses: Condition logistic 

regression 

Covariates: Season, long term trend, 

day of-the-wk, mean temperature, 

relative humidity, barometric pressure, 

extinction coefficient 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 

Notes: Also looked at MI cohort 

Pollutant: PM2.5

Averaging Time: 24 h 

Percentiles (pneumonia cohort): 

25th: 7.23 μg/m3

50th(Median): 11.10 

75th: 16.14 

PM Component: Black Carbon (BC), 

PM non-traffic 

Monitoring Stations: 4-5 monitors 

Copollutant (correlation): 

PM2.5: CO r = 0.52 

NO2 r = 0.55 

O3 r = 0.20 

BC r = 0.66 

PM non-traffic r = 0.74

PM Increment: PM2.5 lag 0: 

17.17 μg/m3

PM2.5 lag 0-1 avg: 16.32 μg/m3

% change in Pneumonia: 

6.48[1.13, 11.43] 

lag 0 

5.56[-0.45, 11.27] 

mean lag 1 

Reference: Zanobetti and Schwartz 

(2006, 090195) 

Period of Study: 1995-1999 

Location: Boston, MA 

Outcome: Pneumonia (480-487) 

Age Groups: >65 y 

Study Design: Case-crossover, time 

stratified

N: 24,857 for Pneumonia 

Statistical Analyses: Condition logistic 

regression 

Covariates: Season, long term trend, 

day of-the-wk, mean temperature, 

relative humidity, barometric pressure, 

extinction coefficient 

Season: All yr 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: 0-1 

Notes: Also looked at MI cohort 

Pollutant: BC 

Averaging Time: 24 h 

Percentiles (pneumonia cohort): 

5th: 0.42 

25th: 0.74 μg/m3

50th(Median): 1.15 

75th: 1.72 

95th: 2.83 

PM Component: PM non-traffic 

Monitoring Stations: 4-5 monitors 

Copollutant (correlation): 

BC: 

PM2.5 r = 0.66 

CO r = 0.82 

NO2 r = 0.70 

O3 r = -0.25 

PM non-traffic r = -0.01 

PM Increment: BC lag 0: 2.05 μg/m3

BC lag 0-1 avg: 1.69 μg/m3

% change in Pneumonia: 

BC-10.76[4.54, 15.89] 

lag 0 

BC-11.71[4.79, 17.36] 

mean lag 1 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-292 
E.3.Short-Term Exposure and Mortality 

Table E-16. Short-term exposure-mortality - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Aga et al. (2003, 054808) 

Period of Study: ~5 yr for most cities, 

during the 1990s 

Location: 28 European cities 

(APHEA2) 

Outcome: Nonaccidental Mortality 

(<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: All ages 

>65 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): (15, 66) 

Copollutant: BS 

Note: PM10 only measured in 21 cities. 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

All ages 

Fixed effects: 0.71% (0.60,0.83) 0-1 

Random effects: 0.67% (0.47,0.87) 0-1 

>65 

Fixed effects: 0.79% (0.66,0.92) 0-1 

Random effects: 0.74% (0.52,0.95) 0-1 

Models with effect modifiers (>65) 

24-h NO2: 

25th Percentile: 0.30% (0.07,0.53) 

75th Percentile: 0.97% (0.82,1.11) 

24-h temperature: 

25th Percentile: 0.44% (0.25,0.64) 

75th Percentile: 0.91% (0.77,1.05) 

24-h relative humidity: 

25th Percentile: 0.98% (0.82,1.14) 

75th Percentile: 0.52% (0.33,0.71) 

Age standardized annual mortality rate: 

25th Percentile: 0.93% (0.77,1.09) 

75th Percentile: 0.61% (0.43,0.79) 

Proportion individuals >65 

25th Percentile: 0.67% (0.50,0.83) 

75th Percentile: 0.85% (0.71,0.99) 

Northwest/Central East: 

25th Percentile: 0.81% (0.63,0.98) 

75th Percentile: 0.26% (-0.05,0.57) 

Northwest/South: 

25th Percentile: 0.81% (0.63,0.98) 

75th Percentile: 1.04% (0.81,1.27) 

Reference: Analitis et al. (2006, 

088177) 

Period of Study: NR 

Location: 29 European cities 

(APHEA2) 

Outcome: Mortality: Cardiovascular 

diseases (390-459) 

Respiratory diseases (460-519) 

Study Design: Time-series 

Statistical Analyses: 2-stage 

hierarchical modeling 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: Range: 9-64 μg/m3

Range (Min, Max): NR 

Copollutant: BS 

Note: PM10 only measured in 21 cities. 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cardiovascular: Fixed effects: 0.64% 

(0.47, 0.80) 0-1 

Random effects: 

0.76% (0.47, 1.05) 0-1 

0.90% (0.57, 1.23) 0-5 

Respiratory: Fixed effects: 

0.58% (0.21, 0.95) 0-1 

Random effects: 

0.71% (0.22, 1.20) 0-1 

1.24% (0.49, 1.99) 0-5 

Reference: Ballester et al. (2002, 

030371) 

Period of Study: 1990-1996 

Location: 13 Spanish cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular diseases (390-459) 

Respiratory diseases (460-519) 

Study Design: Ecological time series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): Huelva: 42.5 (15) 

Madrid: 37.8 (17.7) 

Sevilla: 45.1 (14) 

Range (Min, Max): NR 

Copollutant: 

BS 

TSP 

SO2

Note: PM10 only measured in 3 cities. 

Increment: 10 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Nonaccidental: 

Random effects: 

1.006 (0.998, 1.015) 0-1 

Fixed Effects: 1.005 (1.001, 1.010) 0-1 

PM10+SO2: 1.013 (1.006, 1.020) 0-1 

Cardiovascular: 

1.012 (1.005, 1.018) 0-1 

PM10+SO2: Random effects: 

1.024 (1.001, 1.048) 0-1 

Fixed effects: 1.021 (1.007, 1.035) 0-1 

Respiratory: 

1.013 (1.001, 1.026) 0-1 

PM10+SO2: 1.003 (0.983, 1.023) 0-1 

December 2009 E-293 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bateson and Schwartz 

(2004, 086244) 

Period of Study: 1988-1991 

Location: Cook County, Illinois 

Outcome: Mortality: 

Heart Disease (390-429) 

Respiratory (460-519) 

Study Design: Bi-directional casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: ≥ 65 

Study population: 

65,180 elderly residents with history of 

hospitalization for heart or lung disease 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SE) unit: 37.6 (15.5) μg/m3 

Range (Min, Max): (3.7, 128) 

Copollutant: NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

All-cause: 1.14% (0.44, 1.85) 0-1 

Modification of Effect by Prior Diagnosis

Myocardial Infarction: 

1.98% (-0.25, 4.26) 0-1 

Diabetes: 1.49% (-0.06, 3.07) 0-1 

Congestive heart failure: 

1.28% (-0.06, 2.64) 0-1 

COPD: 0.58% (-0.82, 2.00) 0-1 

Conduction Disorders: 

0.64% (-0.61, 1.90) 0-1 

All other heart or lung diseases: 

0.74% (-0.29, 1.79) 0-1 

All-cause 

Men 

65: 2.0% (0.3, 3.8) 0-1 

75: 1.5% (-0.2, 3.1) 0-1 

85: 0.9% (-0.7, 2.5) 0-1 

95: 0.3% (-1.3, 1.9) 0-1 

All: 1.3% (0.4, 2.3) 0-1 

Women 

65: 0.1% (-1.6, 1.9) 0-1 

75: 0.7% (-1.1, 2.4) 0-1 

85: 1.2% (-0.5, 3.0) 0-1 

95: 1.8% (0.03, 3.6) 0-1 

All: 1.0% (0.1, 1.9) 0-1 

Total 

65: 1.1% (-0.12, 2.3) 0-1 

75: 1.1% (-0.1, 2.3) 0-1 

85: 1.2% (-0.0, 2.4) 0-1 

95: 1.2% (0.0, 2.4) 0-1 

All: 1.1% (0.4, 1.9) 0-1 

Reference: Bell et al. (2009, 191007) 

Period of Study: 1987-2000 

Location: 84 U.S. Counties 

Outcome: Mortality 

Study Design: Time-series 

Covariates: Socio-economic 

conditions, long term temperature 

Statistical Analysis: Bayesian 

hierarchical model 

Age Groups: All 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD) Unit: NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 20% of the population 

acquiring air conditioning 

Percent Change (95% CI) in 

community-specific PM health effect 

estimates for mortality 

Any AC, including window units 

Yearly health effect: -30.4 (-80.4-19.6) 

Summer health effect: 29.9 (-84-144) 

Winter health effect: -573 (-9100-7955) 

Central AC 

Yearly health effect: -39 (-81.4-3.3) 

Summer health effect: 20. (-60.3-64.3) 

Winter health effect: -1777 (-5755-2201)

Reference: Bell et al. (2007, 093256) 

Period of Study: 1999-2005 

Location: U.S. 

Outcome: Mortality 

Age Groups: 65+

Study Design: Time series 

N: NR 

Statistical Analyses: Bayesian 

Hierarchical Regression 

Covariates: Time trend, day of week, 

seasonality, dew point, temperature 

Statistical Package: NR 

Lags Considered: 0-2 

Pollutant: PM10

Averaging Time: Daily 

Mean: Ni: 0.002 

Min: Ni: 0.003 

Max: Ni: 0.021 

Interquartile Range: Ni: 0.001 

Interquartile Range of Percents: 

Ni: 0.01 

Monitoring Stations: NR 

Copollutant: Al, NH4+, As, Ca, Cl, Cu, 

EC, OMC, Fe, Pb, Mg. Ni, NO3-, K, Si, 

Na+, SO4=, Ti, V, Zn 

Co-pollutant Correlation 

Ni, V: 0.48 

Ni, EC: 0.30 

Note: Pollutant concentrations available 

for all fractions of PM2.5

PM Increment: Interquartile Range in 

the fraction of PM2.5

Percent Increase in PM10 Health 

Effect (Lower CI, Upper CI) 

Ni: 14.8 (-8.1, 37.7), lag 0 

Ni: 14.7 (4.0, 25.3), lag 1 

Ni: 14.7 (1.8, 27.5), lag 2 

HS education: -31.9 (-82.4, 18.6) 

median income: -12.3 (-62.3, 37.7) 

Percent black: 48.7 (-15.8, 113) 

Percent living in urban area: -20.1 (-

102, 61.7) 

Population: 5.1 (-14.4, 24.5) 

Notes: Interquartile ranges in percent 

HS education, median income, percent 

black, percent living in urban area, and 

population are 5.2 %, $9,223, 17.3%, 

11.0%, and 549,283 respectively. 

December 2009 E-294 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bellini et al. (2007, 097787) 

Period of Study: 1996-2002 

Location: 15 Italian cities 

Outcome: Mortality 

All-cause (nonaccidental) (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Study Design: Meta-analysis 

Statistical Analyses: Poisson GLM 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant: 

SO2

NO2

CO 

O3

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

All-cause: 

0.31% (-0.19, 0.74) 0-1 

Winter: 0.08% 0-1 

Summer: 1.95% 0-1 

PM10+O3: 0.30% 0-1 

PM10+NO2: 0.08% 0-1 

Respiratory: 

0.54% (-0.91, 1.74) 0-1 

Winter: 0.27% 0-1 

Summer: 3.61% 0-1 

PM10+O3: 0.55% 0-1 

PM10+NO2: 0.19% 0-1 

Cardiovascular: 

0.54% (0.02, 1.02) 0-1 

Winter: 0.20% 0-1 

Summer: 2.79% 0-1 

PM10+O3: 0.57% 0-1 

PM10+NO2: 0.39% 0-1 

Reference: Burnett et al. (2004, 

086247) 

Period of Study: 1981-1999 

Location: 12 Canadian cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: 1. Poisson, 

natural splines 

2. Random effects regression model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

PM2.5: 12.8 

PM10-2.5: 11.4 

Range (Min, Max): NR 

Copollutant (correlation): 

NO2 

O3 

SO2 

CO 

Note: PM10 measurement calculated as 

the sum of PM2.5 and PM10-2.5

measurements. 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

1981-1999 

PM10: 0.57% (0.05, 0.89) 1 

PM10+NO2: 0.07% (-0.44, 0.58) 1 

 

Reference: Cakmak et al. (2007, 

091170) 

Period of Study: Jan 1997-Dec 2003 

Location: Chile-7 cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular diseases (390-459) 

Respiratory diseases (460-519) 

Study Design: Time-series 

Statistical Analyses: Poisson 

Random effects regression model 

Age Groups: All age 

≤ 64 yr 

65-74 yr 

75-84 yr 

≥ 85 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 84.9 

Range (Min, Max): NR 

Copollutant (correlation): 

O3: r = -0.16-0.13 

SO2: r = 0.37-0.77 

CO: r = 0.49-0.82 

Note: Correlations are between 

pollutants for seven monitoring stations. 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental: 

0.97% (-1.09, 2.76) 0 

1.31% (-1.56, 3.68) 0-5 

PM10+O3+SO2+CO: 

0.80% (-0.87, 2.28) 0 

≤ 64: 

0.52% (-0.55, 1.51) 0 

0.49% (-0.51, 1.43) 0-5 

65-75: 

1.07% (-1.23, 3.03) 0 

1.31% (-1.57, 3.69) 0-5 

75-84: 

1.41% (-1.71, 3.94) 0 

1.93% (-2.57, 5.30) 0-5 

≥ 85: 

1.56% (-1.94, 4.34) 0 

2.14% (-2.97, 5.85) 0-5 

Apr-Sep: 

1.03% (-1.17, 2.93) 0 

1.37% (-1.64, 3.82) 0-5 

Oct-Mar: 

0.07% (-0.07, 0.21) 0 

0.15% (-0.15, 0.44) 0-5 

Cardiovascular: 

1.14% (-1.31, 3.21) 0 

1.49% (-1.82, 4.14) 0-5 

Respiratory: 

2.03% (-2.75, 5.56) 0 

3.11% (-5.25, 8.25) 0-5 

December 2009 E-295 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chen et al. (2008, 190106) 

Period of Study: 2001-2004 

Location: Shanghai, China 

Outcome 

(ICD9: 2001; ICD10: 2002-2004): 

Mortality: 

Nonaccidental causes (ICD9 <800; 

ICD10 A00-R99) 

Cardiovascular (ICD9 390-459; I 

CD10 I00-I99) 

Respiratory (ICD9 460-519; 

ICD10 J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 102.0 

Range (Min, Max): (14.0-566.8) 

Copollutant (correlation): 

SO2 r = 0.64 

NO2 r = 0.71 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental 

Single Pollutant: 0.26% (0.14, 0.37) 

PM10+SO2: 0.08% (-0.07, 0.22) 

PM10+NO2: 0.01% (-0.14, 0.17) 

PM10+SO2+NO2: 0.00% (-0.16, 0.16) 

Cardiovascular mortality 

Single Pollutant: 0.27% (0.10, 0.44) 

PM10+SO2: 0.12% (-0.10, 0.34) 

PM10+NO2: 0.01% (-0.22, 0.25) 

PM10+SO2+NO2: 0.01% (-0.23, 0.25) 

Respiratory mortality 

Single Pollutant: 0.27% (-0.01, 0.56) 

PM10+SO2: -0.04% (-0.41, 0.33) 

PM10+NO2: -0.05% (-0.45, 0.34) 

PM10+SO2+NO2: -0.10% (-0.50, 0.30) 

Reference: Daniels et al. (2004, 

087343) 

Period of Study: 1987-1994 

Location: 20 Largest U.S. cities 

Outcome: 

Mortality: 

Total (Nonaccidental) mortality 

Cardiovascular-Respiratory (390-448) 

(480-486, 487, 490-496, 507) 

Other-cause mortality 

Study Design: Time-series 

Statistical Analyses: City-Specific 

Estimates: Poisson GLM, natural cubic 

splines 

Combined Estimates: 2-stage Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Los Angeles: 46.0 

New York: 28.8 

Chicago: 35.6 

Dallas-Ft. Worth: 23.8 

Houston: 30.0 

San Diego: 33.6 

Santa Ana-Anaheim: 37.4 

Phoenix: 39.7 

Detroit: 40.9 

Miami: 25.7 

Philadelphia: 35.4 

Minneapolis: 26.9 

Seattle: 25.3 

San Jose: 30.4 

Cleveland: 45.1 

San Bernardino: 37.0 

Pittsburgh: 31.6 

Oakland: 26.3 

Atlanta: 34.4 

San Antonio: 23.8 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Total (nonaccidental): 

0.17% (0.03, 0.30) 0 

0.20% (0.07, 0.33) 1 

0.28% (0.16, 0.41) 0-1 avg 

Cardiovascular-Respiratory: 

0.17% (-0.01, 0.35) 0 

0.27% (0.09, 0.44) 1 

0.30% (0.18, 0.51) 0-1 avg 

Other-cause: 

0.17% (-0.03, 0.37) 0 

0.12% (-0.07, 0.31) 1 

0.20% (0.01, 0.38) 0-1 avg 

Threshold Models: Total Mortality 

Threshold = 15 μg/m3

0.30% (0.17, 0.42) 0-1 avg 

Threshold = 0 μg/m3

0.28% (0.16, 0.41) 0-1 avg 

Threshold = 20 μg/m3

0.30% (0.16, 0.43) 0-1 avg 

December 2009 E-296 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: De Leon et al. (2003, 

055688) 

Period of Study: Jan 1985-Dec 1994 

Location: New York, New York 

Outcome: Mortality: 

Circulatory (390-459) 

Cancer (140-239) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: All ages 

<75 yr 

>75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

33.27 μg/m3

IQR (25th, 75th): 

(22.67, 40.83) 

Copollutant (correlation): 

O3

CO 

SO2

NO2

Increment: 18.16 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

All Ages 

Cancer: 1.014 (1.000, 1.029) 0-1 

-w/out respiratory: 

1.011 (0.996, 1.026) 0-1 

-w/ respiratory: 

1.051 (0.998, 1.107) 0-1 

Circulatory: 1.025 (1.014, 1.035) 0-1 

-w/out respiratory: 

1.022 (1.012, 1.033) 0-1 

-w/ respiratory: 

1.054 (1.022, 1.086) 0-1 

<75 yr 

Cancer: 1.003 (0.985, 1.021) 0-1 

-w/out respiratory: 

1.002 (0.983, 1.022) 0-1 

-w/ respiratory: 

1.009 (0.943, 1.078) 0-1 

Circulatory: 1.027 (1.012, 1.043) 0-1 

-w/out respiratory: 

1.027 (1.011, 1.043) 0-1 

-w/ respiratory: 

1.033 (0.980, 1.089) 0-1 

>75 yr 

Cancer: 1.033 (1.009, 1.058) 0-1 

-w/out respiratory: 

1.025 (1.000, 1.050) 0-1 

-w/ respiratory: 

1.129 (1.041, 1.225) 0-1 

-w/out pneumonia: 

1.026 (1.002, 1.050) 0-1 

-w/ pneumonia: 

1.183 (1.058, 1.323) 0-1 

-w/out COPD: 1.032 (1.008, 1.057) 0-1 

-w/ COPD: 1.008 (0.849, 1.197) 0-1 

Circulatory: 1.025 (1.012, 1.038) 0-1 

-w/out respiratory: 

1.022 (1.008, 1.035) 0-1 

-w/ respiratory: 

1.066 (1.027, 1.106) 0-1 

-w/out pneumonia: 

1.023 (1.010, 1.036) 0-1 

-w/ pneumonia: 

1.078 (1.018, 1.141) 0-1 

-w/out COPD: 

1.025 (1.012, 1.038) 0-1 

-w/ COPD: 

1.058 (0.991, 1.130) 0-1 

Reference: Dominici et al. (2003, 

042804) 

Period of Study: 1987-1994 

Location: 88 U.S. cities 

Outcome: Mortality: 

All-cause (nonaccidental) (<800) 

Cardiac (390-448) 

Respiratory (490-496) 

Influenza (487) 

Pneumonia (480-486, 507) 

Other causes 

Study Design: Time-series 

Statistical Analyses: 2-stage Bayesian 

hierarchical model 

Age Groups: <65 yr; 65-74 yr; ≥ 75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cardio-respiratory 

0.31% (0.15, 0.50) 1 

All-cause 

0.22% (0.10, 0.38) 1 

Other causes 

0.13% (-0.05, 0.29) 1 

Reference: Dominici et al. (2004, 

059158) 

Period of Study: 1987-1994 

Location: 90 U.S. cities (NMMAPS) 

Outcome: Mortality: 

Total (nonaccidental) 

Study Design: Time-series 

Statistical Analyses: Poisson. GAM, 

GLM 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

α = 3 

0.2% (0.05, 0.35) 

December 2009 E-297 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dominici et al. (2004, 

096951) 

Period of Study: 1986-1993 

Location: 10 U.S. cities 

Outcome: Mortality: 

Total (nonaccidental) 

Study Design: Time-series 

Statistical Analyses: 2-stage Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Birmingham 34.8 

Canton 28.4 

Colorado Springs 27.5 

Minneapolis/St. Paul 28.1 

Seattle 32.2 

Spokane 42.9 

Chicago 36.3 

Detroit 36.7 

New Haven 28.6 

Pittsburgh 36.0 

New York: 28.8 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Combined analysis: 

0.26% (-0.37, 0.65) 0-1 

Separate analysis: 

0.28% (-0.12, 0.63) 0-1 

Notes: A separate analysis assumes 

the mortality data does not provide any 

information on the log relative rates of 

mortality. 

Reference: Dominici et al. (2007, 

097361) 

Period of Study: PM10: 1987-2000 

PM2.5: 1999-2000 

Location: 100 U.S. counties 

(NMMAPS) 

Outcome: Mortality: 

All-cause (nonaccidental) 

Cardiorespiratory 

Other-cause 

Study Design: Time-series 

Statistical Analyses: 2-stage Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

PM10

All-cause: 

East: 

1987-1994: 0.29% (0.12, 0.46) 1 

1995-2000: 0.13% (-0.19, 0.44) 1 

1987-2000: 0.25% (0.11, 0.39) 1 

West: 

1987-1994: 0.12% (-0.07, 0.30) 1 

1995-2000: 0.18% (-0.07, 0.44) 1 

1987-2000: 0.12% (-0.02, 0.26) 1 

National: 

1987-1994: 0.21% (0.10, 0.32) 1 

1995-2000: 0.18% (0.00, 0.35) 1 

1987-2000: 0.19% (0.10, 0.28) 1 

Cardiorespiratory: 

East: 

1987-1994: 0.39% (0.16, 0.63) 1 

1995-2000: 0.30% (-0.13, 0.73) 1 

1987-2000: 0.34% (0.15, 0.54) 1 

West: 

1987-1994: 0.17% (-0.07, 0.40) 1 

1995-2000: 0.13% (-0.23, 0.50) 1 

1987-2000: 0.14% (-0.05, 0.33) 1 

National: 

1987-1994: 0.28% (0.14, 0.43) 1 

1995-2000: 0.21% (-0.03, 0.44) 1 

1987-2000: 0.24% (0.13, 0.36) 1 

Other-cause: 

East: 

1987-1994: 0.21% (-0.03, 0.44) 1 

1995-2000: 0.00% (-0.49, 0.50) 1 

1987-2000: 0.15% (-0.09, 0.39) 1 

West: 

1987-1994: 0.09% (-0.21, 0.38) 1 

1995-2000: 0.23% (-0.15, 0.62) 1 

1987-2000: 0.17% (-0.07, 0.41) 1 

National: 

1987-1994: 0.15% (-0.02, 0.32) 1 

1995-2000: 0.17% (-0.07, 0.41) 1 

1987-2000: 0.15% (0.00, 0.29)1 

Reference: Dominici et al. (2007, 

099135) 

Period of Study: 2000-2005 

Location: 72 U.S. counties 

representing 69 communities 

Outcome: Total mortality 

Study Design: Time-series 

Statistical Analyses: 2-stage Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

The study does not provide results 

quantitatively. 

Note: The study investigated whether 

county-specific short-term effects of 

PM10 on mortality are modified by longterm county-specific nickel or vanadium 

PM2.5 concentrations. 

December 2009 E-298 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Fischer et al. (2003, 

043739) 

Period of Study: 1986-1994 

Location: The Netherlands 

Outcome: Mortality: 

Nonaccidental (<800) 

Pneumonia (480-486) 

COPD (490-496) 

Cardiovascular (390-448) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: 

<45 yr 

45-64 yr 

65-74 yr 

≥ 75 yr 

Pollutant: PM10 

Averaging Time: 24-h avg 

Median (SD) unit: 34 

Range (Min, Max): (10, 278) 

Copollutant: 

BS 

O3

NO2

SO2

CO 

Increment: 80 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Cardiovascular 

<45: 0.906 (0.728, 1.128) 0-6 

45-64: 1.023 (0.945, 1.106) 0-6 

65-74: 1.002 (0.945, 1.062) 0-6 

≥ 75: 1.016 (0.981, 1.052) 0-6 

COPD 

<45: 1.153 (0.587, 2.268) 0-6 

45-64: 1.139 (0.841, 1.541) 0-6 

65-74: 1.166 (0.991, 1.372) 0-6 

≥ 75: 1.066 (0.965, 1.178) 0-6 

Pneumonia 

<45: 1.427 (0.806, 2.525) 0-6 

45-64: 1.712 (1.042, 2.815) 0-6 

65-74: 1.240 (0.879, 1.748) 0-6 

≥ 75: 1.123 (1.011, 1.247) 0-6 

Reference: Fischer et al. (2004, 

055605) 

Period of Study: Jun 2003-Aug 2003 

Location: The Netherlands 

Outcome: Total mortality 

Study Design: NR 

Statistical Analyses: NR 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: Weekly avg 

Mean (SD): 

2000: 31 

2002: 33 

2003: 35 

IQR (25th, 75th): NR 

Copollutant: O3

The study does not present quantitative 

results. 

Notes: The study estimates the number 

of deaths attributable to PM10 during the 

summers of 2000, 2002, and 2003. 

Reference: Forastiere et al. (2005, 

086323) 

Period of Study: 1998-2000 

Location: Rome, Italy 

Outcome: Mortality: 

Ischemic heart disease (410-414) 

Study Design: Time-stratified casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: >35 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean (SD): 

52.1 (22.2) 

IQR (25th, 75th): 

(36.0, 65.7) 

Copollutant (correlation): 

PNC: r = 0.38 

CO: r = 0.34 

NO2: r = 0.45 

SO2: r = 0.23 

O3: r = 0.13 

Increment: 29.7 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

4.8% (0.1, 9.8) 0 

4.9% (0.0, 10.1) 1 

3.8% (-1.0, 8.9) 2 

2.8% (-2.0, 7.7) 3 

6.1% (0.6, 11.9) 0-1 

Reference: Forastiere et al. (2007, 

090720) 

Period of Study: 1998-2001 

Location: Rome, Italy 

Outcome: Mortality: 

Natural (<800) 

Malignant neoplasms (140-208) 

Diabetes mellitus (250) 

Hypertensive disease (401-405) 

Previous acute myocardial infarction 

(410, 412) 

Other ischemic heart diseases (411, 

413-414) 

Conduction disorders (426) 

Dysrhythmia (427) 

Heart failure (428) 

Cerebrovascular disease (430-438) 

Peripherical artery disease (440-448) 

COPD (490-496) 

Study Design: Time-stratified casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: >35 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean Range (SD) unit: 51.0 

(21.0) μg/m3

IQR (25th, 75th): 

(36.1, 63.0) 

Copollutant (correlation): NR 

 Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

Nonaccidental: 1.1% (0.7, 1.6) 0-1 

Low income: 1.9% 0-1 

Low SES: 1.4% 0-1 

High income: 0.0% 0-1 

High SES: 0.1% 0-1 

Low PM Area: 0.9% (-0.4, 2.1) 0-1 

High PM Area: 1.47% (0.4, 2.5) 0-1 

December 2009 E-299 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Forastiere et al. (2008, 

186937) 

Period of Study: 1997-2004 

Location: 9 Italian cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-stratified case- crossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: >35 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean Range (SD) unit: 

35.1-71.5 

Range (5th, 95th): 

Lowest 5th: 14.3 

Highest 95th: 147.0 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Total: 0.60% (0.31, 0.89) 0-1 

Age 

35-64: -0.20% (-0.77, 0.37) 0-1 

65-74: 0.51% (0.05, 0.98) 0-1 

75-84: 0.59%(0.20, 0.97) 0-1 

≥ 85: 0.97% (0.53, 1.42) 0-1 

≥ 65: 0.75% (0.42, 1.09) 

Sex 

Men: 0.72% (0.37, 1.07) 0-1 

Women: 0.83% (0.33, 1.33) 0-1 

Median income (by census block) 

Low (<20th percentile): 

0.80% (-0.02, 1.62) 0-1 

Mid-low (20th-50th percentile): 

0.68% (0.25, 1.12) 0-1 

Mid-high (51st-80th percentile): 

0.85% (0.40, 1.30) 0-1 

High (>80th percentile): 

0.30% (-0.25, 0.86) 0-1 

Location of death 

Out-of-hospital: 0.71% (0.32, 1.11) 0-1 

Discharged 2-28 days before death: 

1.34% (0.49, 2.20) 0-1 

In-hospital: 0.65% (0.33, 0.97) 0-1 

Nursing home: -0.04% (-1.02, 0.95) 0-1 

Reference: Goldberg et al. (2003, 

035202) 

Period of Study: 1984-1993 

Location: Montreal, Quebec, Canada 

Outcome: Mortality: Congestive Heart 

Failure (428) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

splines 

Age Groups: ≥ 65 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean (SD): PM10: 32.2 (17.6) 

IQR (25th, 75th): PM10: (19.7, 41.1) 

Copollutant (correlation): PM2.5, TSP, 

Sulfate, CoH, SO2, NO2, CO, O3

This study does not present results 

quantitatively for PM10

Reference: Goldberg et al. (2003, 

035202) 

Period of Study: 1984-1993 

Location: Montreal, Quebec, Canada 

Outcome: Mortality: 

Diabetes (250) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

spline 

Age Groups: ≥ 65 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean (SD): 

PM10: 32.2 (17.6) μg/m3

IQR (25th, 75th): 

PM10: (19.7, 41.1) 

Copollutant (correlation): PM2.5, 

Sulfate, CoH, SO2, NO2, CO, O3

This study does not present results 

quantitatively for PM10

Reference: Kan and Chen (2003, 

087372) 

Period of Study: Jan 2000-Dec 2001 

Location: Shanghai, China 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

COPD (490-496) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: All ages 

<65 yr 

65-75 yr 

>75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 91.14 (51.85) 

Range (Min, Max): (17.0, 385.0) 

Copollutant (correlation): 

SO2: r = 0.71 

NO2: r = 0.73 

Increment: 10 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Nonaccidental: 

All ages: 1.003 (1.001, 1.005) 0 

<65: 1.001 (0.997, 1.005) 0 

65-75: 1.005 (1.001, 1.008) 0 

>75: 1.003 (1.001, 1.006) 0 

Cardiovascular: 

All ages: 1.003 (1.000, 1.006) 0 

<65: 1.002 (0.994, 1.010) 0 

65-75: 1.003 (0.998, 1.008) 0 

>75: 1.003 (1.000, 1.006) 0 

COPD: 

All ages: 1.005 (0.999, 1.011) 0 

<65: 1.004 (0.981, 1.027) 0 

65-75: 0.996 (0.986, 1.007) 0 

>75: 1.006 (1.000, 1.012) 0 

Multipollutant models: 

SO2: 1.001 (0.998, 1.003) 0 

NO2: 1.001 (0.998, 1.003) 0 

SO2+NO2: 1.000 (0.997, 1.003) 0 

December 2009 E-300 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kan and Chen (2003, 

087372) 

Period of Study: Jan 2000-Dec 2001 

Location: Shanghai, China 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

COPD (490-496) 

Study Design: Case-crossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 91.14 (51.85) 

IQR (25th, 75th): (54, 114) 

Copollutant (correlation): 

SO2: r = 0.71 

NO2: r = 0.73 

Increment: 10 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

Nonaccidental: 

Bidirectional referent days: 

7 days: 1.000 (0.9988, 1.002) 0-1 ma 

7 and 14 days: 

1.002 (1.000, 1.004) 0-1 ma 

7, 14, and 21 days: 

1.003 (1.001, 1.005) 0-1 ma 

Unidirectional referent days: 

7 days: 1.015 (1.012, 1.018) 0-1 ma 

7 and 14 days: 1.017 (1.015, 1.019) 

0-1 ma 

7, 14, and 21 days: 1.019 (1.012, 

1.021) 0-1 ma 

Bidirectional referent days (7, 14, and 

21 days): 

Cardiovascular: 

1.004 (1.001, 1.007) 0-1 ma 

COPD: 

1.006 (0.999, 1.013) 0-1 ma 

Nonaccidental: 

PM10+SO2: 0.997 (0.994, 1.025) 0-1 ma 

PM10+NO2: 0.997 (0.994, 1.025) 0-1 ma 

PM10+SO2+NO2: 0.995 (0.992, 1.025) 

0-1 ma 

Reference: Kan et al. (2005, 087561) 

Period of Study: Apr 2003-May 2003 

Location: Beijing, China 

Outcome: Mortality: 

Severe acute respiratory syndrome 

(SARS) 

Study Design: Time-series 

Statistical Analyses: Poisson, GAM, 

smoothing spline 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 149.1 (8.1) 

Range (Min, Max): (34, 246) 

Copollutant: 

SO2

NO2

Increment: 10 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

0.99 (0.96-1.03) 0 

1.00 (0.97-1.04) 1 

1.02 (0.98-1.06) 2 

1.04 (0.99-1.09) 3 

1.06 (1.00-1.11) 4 

1.06 (1.00-1.12) 5 

1.05 (0.98-1.12) 6 

Reference: Kan et al. (2007, 091267) 

Period of Study: Mar 2004-Dec 2005 

Location: Shanghai, China 

Outcome (ICD10): Mortality: 

Total (nonaccidental) (A00-R99) 

Cardiovascular (I00-I99) 

Respiratory (J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

penalized splines 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 107.9 (2.39) μg/m3

Range (Min, Max): (22.0, 403.0) 

Copollutant (correlation): 

PM10

PM2.5: r = 0.84 

PM10-2.5: r = 0.88 

O3: r = 0.21 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

PM10

Total: 0.16% (0.02, 0.30) 0-1 

Cardiovascular: 0.31% (0.10, 0.53) 0-1 

Respiratory: 0.33% (-0.08, 0.75) 0-1 

 

December 2009 E-301 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kan et al. (2008, 156621) 

Period of Study: Jan 2001-Dec 2004 

Location: Shanghai, China 

Outcome: Mortality: Total 

(nonaccidental) (A00-R99) 

Cardiovascular (I00-I99) 

Respiratory (J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: 

All ages; 

0-4 yr 

5-44 yr 

45-64 yr 

≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Warm season: 87.4 (1.8) 

Cool season: 116.7 (2.8) 

Entire period: 102.0 (1.7) 

Range (Min, Max): NR 

Copollutant (correlation): 

SO2

NO2

O3

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental 

Warm season: 0.21 (0.09, 0.3) 0-1 

Cool season: 0.26 (0.22, 0.30) 0-1 

Entire period: 0.25 (0.14, 0.37) 0-1 

Female: 0.33 (0.18, 0.48) 0-1 

Male: 0.17 (0.03, 0.32) 0-1 

5-44: 0.04 (-0.52, 0.59) 0-1 

45-64: 0.17 (-0.11, 0.45) 0-1 

≥ 65: 0.26 (0.15, 0.38) 0-1 

Cardiovascular 

Warm season: 0.22 (-0.14, 0.58) 0-1 

Cool season: 0.25 (0.05, 0.45) 0-1 

Entire period: 0.27 (0.10, 0.44) 0-1 

Respiratory 

Warm season: -0.28 (-0.93, 0.38) 0-1 

Cool season: 0.58 (0.25, 0.92) 0-1 

Entire period: 0.27 (-0.01, 0.56) 0-1 

Stratified by Educational Attainment 

Nonaccidental: 

Low: 0.33 (0.19, 0.47) 0-1 

High: 0.18 (0.01, 0.36) 0-1 

Cardiovascular: 

Low: 0.30 (0.10, 0.51) 0-1 

High: 0.23 (-0.03, 0.50) 0-1 

Respiratory: 

Low: 0.36 (0.00, 0.72) 0-1 

High: 0.02 (-0.43, 0.47) 0-1 

Reference: Keatinge and Donaldson 

(2006, 087536) 

Period of Study: 1991-2002 

Location: London, England 

Outcome: Mortality: Total 

(nonaccidental) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant: 

O3

SO2

Increment: 10 μg/m3

Mortality per 106 (Lower CI, Upper 

CI) lag: 

PM10+Temp: 

2.1 (0.9, 3.3) 0-2 avg 

PM10+Temp+Acclim: 

1.6 (0.4, 2.8) 0-2 avg 

PM10+Temp+Acclim+Acclim x T: 

1.5 (0.3, 2.6) 0-2 avg 

PM10+Temp+Acclim+Acclim x T+Sun: 

1.4 (0.2, 2.5) 0-2 avg 

PM10+Temp+Acclim+Acclim x 

T+Sun+Wind: 0.8 (-0.4, 1.9) 0-2 avg 

PM10+Temp+Acclim+Acclim x 

T+Sun+Wind+Abs. Humid.: 

0.8 (-0.3, 1.9) 0-2 avg 

PM10+Temp+Acclim+Acclim x 

T+Sun+Wind+Abs. Humid.+ Rain: 

0.9 (-0.3, 2.0) 0-2 avg 

PM10+Temp+Abs. Humid.: 

1.9 (0.7, 3.1) 0-2 avg 

Reference: Kettunen et al. (2007, 

091242) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome (ICD10): Mortality: 

Stroke (I60-I61, I63-I64) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

penalized thin-plate splines 

Age Groups: ≥ 65 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 

Cold Season: 16.3 

Warm Season: 16.5 

Range (Min, Max): 

Cold Season: (3.1, 136.7) 

Warm Season: (3.3, 67.4) 

Copollutant: 

PM2.5

PM10-2.5

UFP 

O3

CO 

NO2

Increment: 

Cold Season: 13.8 μg/m3

Warm Season: 9.8 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cold Season 

-0.56% (-3.32, 2.29) 0 

-0.93% (-3.55, 1.75) 1 

-1.68% (-4.30, 1.00) 2 

-1.53% (-4.14, 1.14) 3 

Warm Season 

10.89% (0.95, 21.81) 0 

8.56% (-0.88, 18.90) 1 

2.06% (-6.76, 11.71) 2 

-2.89% (-11.32, 6.34) 3 

December 2009 E-302 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kim et al. (2003, 155899) 

Period of Study: Jan 1995-Dec 1999 

Location: Seoul, Korea 

Outcome (ICD10): Mortality: 

Nonaccidental (all except S01-S99, 

T01-T98) 

Cardiovascular (I00-I52) 

Respiratory (J00-J98) 

Cerebrovascular (I60-I69) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 69.19 (10.36) 

IQR (25th, 75th): 

(44.82, 87.95) 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

All cause: 

2.8% (1.8, 3.7) 0 

2.8% (1.9, 3.7) 1 

1.4% (0.5, 2.3) 2 

3.7% (2.1, 5.4) distributed lag (6-day) 

Respiratory: 

8.3% (4.3, 12.5) 0 

6.4% (2.7, 10.2) 1 

6.5% (2.7, 10.4) 2 

13.9% (6.8, 21.5) distributed lag (6-day)

Pneumonia: 

11.6% (4.2, 19.6) 0 

9.0% (2.1, 16.3) 1 

7.7% (0.8, 15.2) 2 

17.1% (4.1, 31.7) distributed lag (6-day 

) 

COPD: 

4.2% (-1.2, 10.0) 0 

3.5% (-1.5, 8.9) 1 

1.4% (-3.7, 6.8) 2 

12.2% (2.5, 22.9) distributed lag (6-day 

) 

Cardiovascular: 

2.0% (-0.9, 5.0) 0 

3.3% (0.6, 6.2) 1 

2.9% (0.1, 5.8) 2 

4.4% (-0.6, 9.6) distributed lag (6-day) 

Myocardial infarction: 

2.6% (-2.3, 7.8) 0 

5.8% (1.0, 10.7) 1 

5.5% (0.7, 10.6) 2 

4.9% (-3.4, 13.9) distributed lag (6-day) 

Cerebrovascular: 

3.2% (0.8, 5.5) 0 

3.1% (0.9, 5.3) 1 

2.4% (0.1, 4.6) 2 

6.3% (2.3, 10.5) distributed lag (6-day) 

Ischemic stroke: 

-0.6% (-5.6, 4.7) 0 

0.6% (-4.2, 5.7) 1 

-0.1% (-4.9, 5.1) 2 

10.3% (1.0, 20.4) distributed lag (6-day)

Reference: Kim et al. (2004, 087417) 

Period of Study: Jan 1997-Dec 2001 

Location: Seoul, Korea 

Outcome: Mortality: Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 68.23 (36.36) μg/m3

IQR (25th, 75th): (42.56, 84.67) 

Copollutant (correlation): NR 

Increment: 42.11 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

1.021 (1.009, 1.035) 

December 2009 E-303 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Le Tertre et al. (2005, 

087560) 

Period of Study: NR 

Location: 21 European cities 

(APHEA-2) 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: Empirical Bayes 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant: NO2

Increment: 1.0 μg/m3

β coefficient (SE) lag: 

Athens: 0.001311 (0.0003) 

Barcelona: 0.000575 (0.0002) 

Basel: 0.000462 (0.0005) 

Birmingham: 0.000305 (0.0003) 

Budapest: -0.000248 (0.0005) 

Cracow: 0.000155 (0.0004) 

Erfurt: -0.000465 (0.0004) 

Geneva: -0.000059 (0.0005) 

Helsinki: 0.000389 (0.0004) 

London: 0.000591 (0.0002) 

Lyon: 0.001554 (0.0005) 

Madrid: 0.000372 (0.0003) 

Milan: 0.000901 (0.0002) 

Paris: 0.000411 (0.0003) 

Prague: 0.000097 (0.0002) 

Rome: (0.001333 (0.0003) 

Stockholm: 0.000479 (0.0009) 

Tel Aviv: 0.000522 (0.0003) 

Teplice: 0.000876 (0.0004) 

Torino: 0.000938 (0.0002) 

Zurich: 0.000365 (0.0004) 

Toulouse: NR (NR) 

Overall: 0.00055 (0.000098) 

Reference: Lee et al. (2007, 093042) 

Period of Study: Jan 2000-Dec 2004 

Location: Seoul, Korea 

Outcome (ICD10): Mortality: 

Nonaccidental (A00-R99) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

w/ Asian dust days: 70.00 (47.80) 

w/o Asian dust days: 65.77 (33.60) 

Asian dust days only: 188.49 (142.85) 

Copollutant: 

CO 

NO2

SO2

O3

Increment: 41.49 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Model with Asian Dust Days 

0.7% (0.2, 1.3) 1-3 

Model without Asian dust days 

1.0% (0.2, 1.8) 1-3 

Reference: Lee and Shaddick (2007, 

156685) 

Period of Study: Jan 1993-Dec 1997 

Location: Cleveland, Ohio 

Detroit, Michigan 

Minneapolis, Minnesota 

Pittsburgh, Pennsylvania 

Outcome (ICD10): Mortality: 

Nonaccidental 

Study Design: Time-series 

Statistical Analyses: 

1. Bayesian, penalized spline 

2. Likelihood, penalized spline 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Increment: 10 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Constant model 

Cleveland: 1.0049 

1 

Detroit: 1.0046 

1 

Minneapolis: 1.0052 

1 

Pittsburgh: 1.0045 

1 

Reference: Martins et al. (2004, 

087457) 

Period of Study: Jan 1997-Dec 1999 

Location: São Paulo, Brazil 

Outcome (ICD10): Mortality: 

Respiratory (J00-J99) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural cubic splines 

Age Groups: ≥ 60 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Cerqueira Cesar: 42.5(22.9) 

Santa Amaro: 49.6(32.1) 

Central: 52.1(23.5) 

Penha: 40.4(23.8) 

Santana: 72.6(24.5) 

Sao Miguel Paulista: 68.6(31.0) 

Range (Min, Max): NR 

The study does not present quantitative 

results. 

December 2009 E-304 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Nawrot et al. (2007, 

098619) 

Period of Study: Jan 1997-Dec 2003 

Location: Flanders, Belgium 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Study Design: Time-series 

Statistical Analyses: Main analysis: 

Segmented regression models 

Sensitivity analysis: Poisson GAM, 

LOESS 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 

Winter: 43.3(0.88) 

Spring: 39.5(0.88) 

summer: 37.7(0.91) 

Fall: 37.2(0.88) 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 

Main analysis: NR 

Sensitivity analysis: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Highest season-specific PM10 quartile 

vs. the lowest season-specific PM10

quartile 

Summer: 7.8% (6.1, 9.6) 

Spring: 6.3% (4.7, 7.8) 

Fall: 2.2% (0.58, 3.8) 

Winter: 1.4% (0.06, 2.9) 

Warm months (Jun, Jul, Aug): 

 7.9% (6.2, 9.6) 

Cold months (Dec, Jan, Feb): 

 1.5% (0.22, 3.3) 

Intermediate months (Mar, Apr, May, 

Sep, Oct, Nov): 4.2% (2.9, 5.6) 

Warmer Periods (Apr-Sep) 

Nonaccidental: 1.5% (1.1, 2.0) 0 

Respiratory: 2.0% (0.6, 3.7) 0 

Cardiovascular: 1.8% (1.1, 2.4) 0 

December 2009 E-305 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: O’Neill et al. (2004, 

087429) 

Period of Study: 1996-1998 

1994-1995 

Location: Mexico City, Mexico 

Outcome: Mortality: 

Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

cubic spline 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Range: 

Hi-Vol: 46.3-164.0 

TEOM: 48.2-107.5 

Predicted: 30.2-162.4 

Impactor: 58.4 

Range (Min, Max): 

Xalostoc 

Hi-Vol: (40.0, 335.0) 

TEOM: (16.5, 291.2) 

Predicted: (60.6, 320.0) 

Tlalnepantla 

Hi-Vol: (25.0, 264.0) 

TEOM: (10.4, 275.9) 

Predicted: (17.7, 175.0) 

Merced 

Hi-Vol: (17.0, 266.0) 

TEOM: (9.4, 318.7) 

Predicted: (12.3, 160.8) 

Cerro de la Estrella 

Hi-Vol: (15.0, 292.0) 

TEOM: (13.7, 268.3) 

Predicted: (11.2, 154.4) 

Pedregal (1996-1998) 

Hi-Vol: (5.0, 226.0) 

TEOM: (7.8, 264.4) 

Predicted: (-0.5, 86.3) 

Pedregal (1994-1995) 

Hi-Vol: (24.0, 114.0) 

TEOM: (8.7, 152.5) 

Impactor: (15.0, 154.0) 

Predicted: (3.9, 75.9) 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

TEOM 

0.04% (-0.12, 0.20) 0 

-0.02% (-0.18, 0.13) 1 

-0.01% (-0.27, 0.25) 2 

-0.03% (-0.19, 0.13) 3 

-0.03% (-0.19, 0.13) 4 

-0.05% (-0.21, 0.11) 5 

0.05% (-0.25, 0.35) 0-5 

Predicted 

-0.05% (-0.29, 0.19) 0 

0.09% (-0.16, 0.34) 1 

-0.12% (-0.43, 0.20) 2 

-0.02% (-0.26, 0.21) 3 

-0.14% (-0.37, 0.09) 4 

-0.05% (-0.28, 0.18) 5 

0.00% (-0.39, 0.38) 0-5 

Sierra-Anderson High Volume Air 

Sampler 

0.02% (-0.29, 0.32) 0 

0.13% (-0.27, 0.54) 1 

0.21% (-0.10, 0.52) 2 

0.53% (0.07, 0.99) 3 

0.11% (-0.20, 0.41) 4 

0.38% (0.07, 0.70) 5 

GAM: 2 LOESS terms, default 

convergence 

1.68% (0.45, 2.93) 0 

-0.36% (-1.56, 0.86) 1 

-0.21% (-1.40, 1.00) 2 

-0.18% (-1.40, 1.05) 3 

1.31% (0.08, 2.55) 4 

1.49% (0.25, 2.73) 5 

1.77% (-0.26, 3.83) 0-5 

Parametric: cubic splines 

5 df 

1.45% (0.09, 2.83) 0 

-0.71% (-2.06, 0.67) 1 

-0.59% (-1.95, 0.79) 2 

-0.70% (-2.09, 0.71) 3 

0.92% (-0.46, 2.32) 4 

1.17% (-0.19, 2.55) 5 

1.17% (-1.54, 3.95) 0-5 

10 df 

1.60% (0.20, 3.02) 0 

-0.80% (-2.18, 0.60) 1 

-0.73% (-2.11, 0.68) 2 

-1.05% (-2.49, 0.40) 3 

0.64% (-0.79, 2.10) 4 

1.05% (-0.36, 2.48) 5 

0.51% (-2.60, 3.71) 0-5 

2 df 

1.79% (0.48, 3.11) 0 

-0.09% (-1.38, 1.22) 1 

0.10% (-1.18, 1.40) 2 

0.20% (-1.10, 1.52) 3 

1.60% (0.30, 2.91) 4 

1.72% (0.43, 3.04) 5 

1.90% (-0.36, 4.21) 0-5 

Reference: O’Neill et al. (2005, 

098094) 

Period of Study: 1996-1998 

1996-1999 

Location: Mexico City and Monterrey, 

Mexico 

Outcome: Mortality: Nonaccidental 

Cardiovascular (390-460) 

Respiratory (460-520) 

Other-causes 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

cubic splines 

Age Groups: All ages, 0-15, ≥ 65 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Mexico City: 75.8 (31.4) 

Monterrey: 50.0 (23.5) 

Range (Min, Max): 

Mexico City: (18.0, 233.9) 

Monterrey: (6.2, 230.8) 

Copollutant: O3

The study focuses on the 

temperature-mortality relationship and 

only includes PM10 as a covariate in 

models. 

December 2009 E-306 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: O'Neill et al. (2008, 

192314) 

Period of Study: Jan 1998-Dec 2002 

Location: 

Mexico City, Mexico 

Santiago, Chile 

São Paulo, Brazil 

Outcome: 

Study Design: Time-series 

Covariates: Temperature, day of week, 

temporal trends, sex 

Statistical Analysis: Poisson 

regression 

Statistical Package: S-Plus 

Age Groups: Adults over 21 yr 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD) μg/m3: 

Mexico City: 53.8 (24.9) 

São Paulo: 48.9 (21.9) 

Santiago: 78.7 (33.0) 

Range (Min, Max): 

Mexico City: 1.08-192.2 

São Paulo: 12.0-171.3 

Santiago: 8.0-218.6 

Copollutant: NR 

Increment: 10 μg/m3

Percent increase (95% CI) in allcause adult mortality (>22yrs) by 

educational level and sex

Mexico City 

All Adults, Concurrent Day 

None: 0.76 (0.17-1.36) 

Primary: 0.27 (-0.19-0.72) 

Secondary: 0.19 (-0.19-0.57) 

≥ 12 yr: 0.83 (0.03-1.63) 

All Adults, Lag 1 

None: 0.62 (0.02-1.22) 

Primary: 0.62 (0.17-1.08) 

Secondary: 0.29 (-0.09-0.90) 

≥ 12 yr: 0.58 (-0.21-1.38) 

All Adults, Distributed Lags 0-5 

None: 0.91 (-0.07-1.89) 

Primary: 0.48 (-0.27-1.24) 

Secondary: 0.27 (-0.36-0.90) 

≥ 12 yr: 0.75 (-0.49-2.02) 

All Adults, df (yr) 

None: 5.4 

Primary: 6.0 

Secondary: 6.0 

≥ 12 yr: 3.0 

Women, Concurrent Day 

None: 0.65 (-0.08-1.38) 

Primary: 0.48 (-0.13-1.09) 

Secondary: 0.35 (-0.16-0.86) 

≥ 12 yr: 1.64 (0.69-2.59) 

Women, Lag 1 

None: 0.62 (-0.12-1.36) 

Primary: 1.03 (0.42-1.64) 

Secondary: 0.59 (0.08-1.11) 

≥ 12 yr: 1.79 (0.84-2.75) 

Women, Distributed Lags 0-5 

None: 0.46 (-0.74-1.68) 

Primary: 1.39 (0.42-2.36) 

Secondary: 0.51 (-0.30-1.33) 

≥ 12 yr: 1.71 (0.61-2.83) 

Women, df (yr) 

None: 5.4 

Primary: 4.4 

Secondary: 4.8 

≥ 12 yr: 1.0 

Men, Concurrent Day 

None: 0.75 (-0.21-1.72) 

Primary: 0.52 (-0.11-1.15) 

Secondary: 0.56 (0.08-1.05) 

≥ 12 yr: 1.20 (0.25-2.17) 

Men, Lag 1 

None: 0.45 (-0.51-1.42) 

Primary: 0.70 (0.06-1.34) 

Secondary: 0.47 (-0.02-0.95) 

≥ 12 yr: 0.74 (-0.22-1.70) 

Men, Distributed Lags 0-5 

None: 1.24 (-0.25-2.75) 

Primary: 0.65 (-0.39-1.69) 

Secondary: 0.88 (0.11-1.66) 

≥ 12 yr: 1.07 (-0.41-2.57) 

Men, df (yr) 

None: 3.8 

Primary: 5.6 

Secondary: 4.6 

≥ 12 yr: 3.8 

São Paulo 

All Adults, Concurrent Day 

None: 0.77 (-0.28-1.82) 

Primary: 1.27 (0.78-1.76) 

Secondary: 0.93 (-0.07-1.94) 

≥ 12 yr: 2.93 (2.00-2.88) 

All Adults, Lag 1 

None: 0.70 (-0.34-1.76) 

Primary: 1.32 (0.83-1.82) 

Secondary: 1.91 (0.58-2.60) 

≥ 12 yr: 2.20 (1.27-3.15) 

December 2009 E-307 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

All Adults, Distributed Lags 0-5 

None: 0.76 (-0.91-2.46) 

Primary: 1.34 (0.55-2.14) 

Secondary: 1.91 (0.35-2.60) ≥ 12 yr: 2.20 (1.27-3.15) 

All Adults, df (yr) 

None: 4.0 

Primary: 4.0 

Secondary: 2.8 ≥ 12 yr: 1.6 

Women, Concurrent Day 

None: 1.93 (0.87-3.00) 

Primary: 1.72 (1.04-2.41) 

Secondary: 0.85 (-0.21-1.92) ≥ 12 yr: 1.84 (0.56-3.13) 

Women, Lag 1 

None: 1.41 (0.34-2.48) 

Primary: 1.64 (0.96-2.33) 

Secondary: 1.43 (0.36-2.50) ≥ 12 yr: 2.27 (0.99-3.56) 

Women, Distributed Lags 0-5 

None: 2.00 (0.40-3.63) 

Primary: 2.05 (0.96-3.14) 

Secondary: 1.61 (0.07-3.17) ≥ 12 yr: 3.35 (1.49-5.25) 

Women, df (yr) 

None: 2.4 

Primary: 3.6 

Secondary: 1.4 ≥ 12 yr: 0.8 

Men, Concurrent Day 

None: -0.43 (-2.15-1.32) 

Primary: 1.36 (0.71-2.02) 

Secondary: 1.74 (0.77-2.72) ≥ 12 yr: 2.81 (1.71-3.92) 

Men, Lag 1 

None: -0.44 (-2.17-1.33) 

Primary: 1.44 (0.79-2.10) 

Secondary: 1.52 (0.55-2.49) ≥ 12 yr: 1.48 (0.38-2.59) 

Men, Distributed Lags 0-5 

None: -0.30 (-3.09-2.56) 

Primary: 1.67 (0.65-2.70) 

Secondary: 1.06 (-0.34-2.49) ≥ 12 yr: 3.18 (1.60-4.79) 

Men, df (yr) 

None: 4.4 

Primary: 3.2 

Secondary: 0.8 ≥ 12 yr: 1.2 

Santiago 

All Adults, Concurrent Day 

None: 1.44 (0.53-2.36) 

Primary: 0.06 (-0.21-0.34) 

Secondary: 0.42 (0.06-0.78) ≥ 12 yr: 1.32 (0.60-2.05) 

All Adults, Lag 1 

None: 2.08 (1.16-30.1) 

Primary: 0.53 (0.25-0.81) 

Secondary: 0.55 (0.19-0.91) ≥ 12 yr: 1.31 (0.59-2.04) 

All Adults, Distributed Lags 0-5 

None: 3.18 (1.60-4.78) 

Primary: 0.58 (0.10-1.06) 

Secondary: 1.10 (0.48-1.73) ≥ 12 yr: 2.00 (0.93-3.07) 

All Adults, df (yr) 

None: 3.6 

Primary: 5.6 

Secondary: 4.0 ≥ 12 yr: 1.6 

Women, Concurrent Day 

None: 0.91 (-0.06-1.89) 

Primary: 0.31 (-0.06-0.68) 

Secondary: 0.84 (0.33-1.36) ≥ 12 yr: 0.60 (-0.32-1.52) 

Women, Lag 1 

December 2009 E-308 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

None: 1.58 (0.58-2.58) 

Primary: 0.79 (0.42-1.17) 

Secondary: 0.76 (0.25-1.28) ≥ 12 yr: 0.53 (-0.39-1.45) 

Women, Distributed Lags 0-5 

None: 1.15 (-0.48-2.80) 

Primary: 1.05 (0.41-1.69) 

Secondary: 1.29 (0.40-2.19) ≥ 12 yr: 1.06 (-0.27-2.41) 

Women, df (yr) 

None: 2.6 

Primary: 4.8 

Secondary: 4.4 ≥ 12 yr: 1.0 

Men, Concurrent Day 

None: 0.05 (-1.02-1.12) 

Primary: -0.11 (-0.5-0.28) 

Secondary: 0.18 (-0.31-0.68) ≥ 12 yr: 1.52 (0.70-2.35) 

Men, Lag 1 

None: 0.61 (-0.44-1.68) 

Primary: 0.23 (-0.16-0.62) 

Secondary: 0.49 (0.00-0.98) ≥ 12 yr: 1.03 (0.21-1.86) 

Men, Distributed Lags 0-5 

None: 2.08 (0.28-3.91) 

Primary: 0.16 (-0.50-0.82) 

Secondary: 1.27 (0.43-2.12) ≥ 12 yr: 1.98 (0.76-3.20) 

Men, df (yr) 

None: 2.8 

Primary: 4.8 

Secondary: 4.4 ≥ 12 yr: 1.6 

Percent increase (95% CI) in allcause adult mortality (≥65yrs) by 

educational level and sex 

Mexico City 

All Adults, Concurrent Day 

None: 0.41 (-0.25-1.08) 

Primary: 0.40 (-0.15-0.95) 

Secondary: 0.50 (-0.01-1.01) ≥ 12 yr: 1.51 (0.39-2.63) 

All Adults, Lag 1 

None: 0.20 (-0.47-0.87) 

Primary: 0.80 (0.24-1.36) 

Secondary: 0.60 (0.09-1.12) ≥ 12 yr: 1.09 (-0.02-2.22) 

All Adults, Distributed Lags 0-5 

None: 0.27 (-0.83-1.38) 

Primary: 0.99 (0.07-1.91) 

Secondary: 0.30 (-0.56-1.16) ≥ 12 yr: 1.83 (0.09-3.59) 

All Adults, df (yr) 

None: 5.6 

Primary: 5.4 

Secondary: 6.0 ≥ 12 yr: 3.2 

Women, Concurrent Day 

None: 0.49 (-0.30-1.29) 

Primary: 0.39 (-0.33-1.11) 

Secondary: 0.52 (-0.16-1.20) ≥ 12 yr: 1.29 (0.12-2.48) 

Women, Lag 1 

None: 0.73 (-0.07-1.54) 

Primary: 1.24 (0.52-1.97) 

Secondary: 0.55 (-0.13-1.23) ≥ 12 yr: 1.50 (0.32-2.70) 

Women, Distributed Lags 0-5 

None: 0.75 (-0.56-2.08) 

Primary: 1.43 (0.29-2.59) 

Secondary: 0.06 (-1.01-1.15) ≥ 12 yr: 1.48 (0.10-2.87) 

Women, df (yr) 

None: 5.4 

Primary: 4.2 

Secondary: 4.8 

December 2009 E-309 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) ≥ 12 yr: 0.6 

Men, Concurrent Day 

None: 0.90 (-0.23-2.04) 

Primary: 0.37 (-0.40-1.16) 

Secondary: 0.78 (0.07-1.49) ≥ 12 yr: 1.66 (0.30-3.04) 

Men, Lag 1 

None: -0.15 (-1.27-0.98) 

Primary: 0.26 (-0.53-1.05) 

Secondary: 0.93 (0.22-1.65) ≥ 12 yr: 0.95 (-0.41-2.32) 

Men, Distributed Lags 0-5 

None: 0.80 (-0.95-2.58) 

Primary: 0.29 (-0.99-1.58) 

Secondary: 1.06 (-0.08-2.21) ≥ 12 yr: 1.76 (-0.35-3.91) 

Men, df (yr) 

None: 3.8 

Primary: 5.6 

Secondary: 4.6 ≥ 12 yr: 3.8 

São Paulo 

All Adults, Concurrent Day 

None: 0.60 (-0.48-1.70) 

Primary: 0.59 (1.00-2.19) 

Secondary: 1.21 (-0.01-2.44) ≥ 12 yr: 2.80 (1.67-3.94) 

All Adults, Lag 1 

None: 0.62 (-0.47-1.72) 

Primary: 1.48 (0.89-2.07) 

Secondary: 2.31 (1.08-3.55) ≥ 12 yr: 2.52 (1.40-3.66) 

All Adults, Distributed Lags 0-5 

None: 0.91 (-0.84-2.69) 

Primary: 1.73 (0.79-2.67) 

Secondary: 3.25 (1.39-5.16) ≥ 12 yr: 3.63 (2.01-5.29) 

All Adults, df (yr) 

None: 4.0 

Primary: 3.8 

Secondary: 2.6 ≥ 12 yr: 1.6 

Women, Concurrent Day 

None: 1.82 (0.71-2.94) 

Primary: 1.84 (1.05-2.64) 

Secondary: 0.62 (-0.55-1.81) ≥ 12 yr: 1.00 (-0.27-2.29) 

Women, Lag 1 

None: 1.36 (0.25-2.49) 

Primary: 1.76 (0.97-2.56) 

Secondary: 1.57 (0.39-2.76) ≥ 12 yr: 1.39 (0.12-2.68) 

Women, Distributed Lags 0-5 

None: 1.80 (0.12-3.51) 

Primary: 1.97 (0.73-3.22) 

Secondary: 1.89 (0.19-3.61) ≥ 12 yr: 2.53 (0.70-4.40) 

Women, df (yr) 

None: 2.4 

Primary: 3.4 

Secondary: 1.2 ≥ 12 yr: 0.8 

Men, Concurrent Day 

None: -0.67 (-2.50-1.19) 

Primary: 1.82 (1.00-2.65) 

Secondary: 2.46 (1.31-3.63) ≥ 12 yr: 1.73 (0.47-3.00) 

Men, Lag 1 

None: -0.59 (-2.42-1.26) 

Primary: 1.59 (0.78-2.41) 

Secondary: 2.64 (1.49-3.80) ≥ 12 yr: 0.89 (-0.35-2.15) 

Men, Distributed Lags 0-5 

None: 1.50 (-1.52-4.60) 

Primary: 2.46 (1.20-3.74) 

Secondary: 2.24 (0.56-3.95) ≥ 12 yr: 1.45 (-0.34-3.29) 

December 2009 E-310 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Men, df (yr) 

None: 4.6 

Primary: 3.0 

Secondary: 0.8 ≥ 12 yr: 1.0 

Santiago 

All Adults, Concurrent Day 

None: 1.49 (0.54-2.45) 

Primary: 0.28 (-0.03-0.59) 

Secondary: 0.58 (0.13-1.04) ≥ 12 yr: 2.32 (1.50-3.15) 

All Adults, Lag 1 

None: 2.20 (1.24-3.17) 

Primary: 0.74 (0.43-1.05) 

Secondary: 0.64 (0.20-1.11) ≥ 12 yr: 2.20 (1.36-3.04) 

All Adults, Distributed Lags 0-5 

None: 3.21 (1.54-4.90) 

Primary: 0.92 (0.38-1.46) 

Secondary: 1.46 (0.67-2.25) ≥ 12 yr: 4.02 (2.78-5.27) 

All Adults, df (yr) 

None: 3.8 

Primary: 5.2 

Secondary: 4.0 ≥ 12 yr: 1.8 

Women, Concurrent Day 

None: 1.39 (0.41-2.39) 

Primary: 0.4 (0.01-0.8) 

Secondary: 0.91 (0.29-1.53) ≥ 12 yr: 0.87 (-0.02-1.78) 

Women, Lag 1 

None: 1.83 (0.83-2.85) 

Primary: 0.98 (0.58-1.38) 

Secondary: 0.73 (0.11-1.35) ≥ 12 yr: 0.76 (-0.15-1.68) 

Women, Distributed Lags 0-5 

None: 2.47 (0.85-4.11) 

Primary: 1.2 (0.52-1.88) 

Secondary: 1.71 (0.65-2.78) ≥ 12 yr: 0.87 (-0.02-1.78) 

Women, df (yr) 

None: 2.4 

Primary: 4.8 

Secondary: 4.4 ≥ 12 yr: 0.6 

Men, Concurrent Day 

None: 0.54 (-0.51-1.61) 

Primary: 0.34 (-0.12-0.80) 

Secondary: 0.25 (-0.40-0.91) ≥ 12 yr: 1.97 (1.09-2.86) 

Men, Lag 1 

None: 0.84 (-0.21-1.91) 

Primary: 0.43 (-0.03-0.89) 

Secondary: 0.61 (-0.04-1.26) ≥ 12 yr: 1.57 (0.67-2.46) 

Men, Distributed Lags 0-5 

None: 2.41 (0.64-4.22) 

Primary: 0.80 (0.02-1.59) 

Secondary: 1.58 (0.45-2.71) ≥ 12 yr: 2.99 (1.66-4.33) 

Men, df (yr) 

None: 2.0 

Primary: 4.4 

Secondary: 4.4 ≥ 12 yr: 1.8 

December 2009 E-311 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Peng et al. (2005, 087463) 

Period of Study: 1987-2000 

Location: 100 U.S. cities (NMMAPS) 

Outcome: Mortality: 

Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Bayesian 

semiparametric hierarchical models 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 27.1 

Range (Min, Max): (13.2, 48.7) 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Winter: 

-0.4% (-0.30, 0.21) 0 

0.15% (-0.08, 0.39) 1 

0.10% (-0.13, 0.33) 2 

Spring: 

0.32% (0.08, 0.56) 0 

0.14% (-0.14, 0.42) 1 

0.05% (-0.21, 0.32) 2 

Summer: 

0.13% (-0.11, 0.37) 0 

0.36% (0.11, 0.61) 1 

-0.03% (-0.27, 0.21) 2 

Fall: 

0.05% (-0.16, 0.25) 0 

0.14% (-0.06, 0.34) 1 

0.13% (-0.08, 0.35) 2 

All Seasons: 

0.09% (-0.01, 0.19) 0 

0.19% (0.10, 0.28) 1 

0.08% (-0.03, 0.19) 2 

PM10 only (45 cities): 

Winter: 0.15% (-0.16, 0.45) 1 

Spring: 0.13% (-0.21, 0.48) 1 

Summer: 0.30% (-0.10, 0.69) 1 

Fall: 0.07% (-0.23, 0.37) 1 

PM10 + O3 (45 cities): 

Winter: 0.18% (-0.16, 0.52) 1 

Spring: 0.10% (-0.30, 0.49) 1 

Summer: 0.33% (-0.14, 0.81) 1 

Fall: 0.08% (-0.25, 0.41) 1 

PM10 + O3 (45 cities): 

Winter: 0.13% (-0.24, 0.49) 1 

Spring: 0.1% 9(-0.18, 0.56) 1 

Summer: 0.28% (-0.13, 0.70) 1 

Fall: -0.01% (-0.34, 0.31) 1 

PM10 + NO2 (45 cities): 

Winter: 0.21% (-0.18, 0.60) 1 

Spring: 0.19% (-0.17, 0.54) 1 

Summer: 0.34% (0.01, 0.68) 1 

Fall: 0.13% (-0.12, 0.39) 1 

Reference: Penttinen et al. (2004, 

087432) 

Period of Study: 1988-1996 

Location: Helsinki, Finland 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: 

15-64 yr 

65-74 yr 

≥ 75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 21 μg/m3

Range (Min, Max): (0.2, 213) 

Copollutant (correlation): 

O3: r = -0.09 

NO2: r = 0.50 

CO: r = 0.45 

SO2: r = 0.61 

TSP: r = 0.72 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Total (nonaccidental) 

-0.23% (-1.47, 1.01) 0 

0.88% (-0.32, 2.08) 1 

0.11 (-0.51, 0.73) 0-3 avg 

Cardiovascular 

-1.22% (-3.00, 0.56) 0 

0.63% (-1.09, 2.35) 1 

0.08% (-0.96, 0.81) 0-3 avg 

Respiratory 

3.94% (0.01, 7.87) 0 

3.96% (0.11, 7.81) 1 

2.13% (0.03, 4.22) 0-3 avg 

Reference: Qian et al. (2007, 093054) 

Period of Study: 2001-2004 

Location: Wuhan, China 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiovascular (390-459) 

Stroke (430-438) 

Cardiac Diseases (390-398) 

Respiratory (460-519) 

Cardiopulmonary 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

natural splines 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 141.8 3 

Range (Min, Max): (24.8, 477.8) 

Copollutant (correlation): 

NO2

SO2

O3

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental 

0.36% (0.19, 0.53) 0 

0.28% (0.12, 0.45) 1 

0.43% (0.24, 0.62) 0-1 

0.08% (-0.15, 0.31) 0-4 

<45 yr 

0.28% (-0.26, 0.82) 0 

0.45% (-0.06, 0.96) 1 

0.53% (-0.08, 1.13) 0-1 

0.41% (-0.31, 1.13) 0-4 

≥ 45 yr 

0.36% (0.19, 0.54) 0 

0.27% (0.10, 0.44) 1 

0.42% (0.22, 0.62) 0-1 

0.05% (-0.18, 0.29) 0-4 

<65 yr 

December 2009 E-312 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

<45 yr ≥ 45 yr 

<65 yr ≥ 65 yr 

0.20% (-0.08, 0.49) 0 

0.25% (-0.03, 0.52) 1 

0.33% (0.01, 0.66) 0-1 

0.01% (-0.38, 0.39) 0-4 ≥ 65 yr 

0.41% (0.21, 0.61) 0 

0.30% (0.10, 0.49) 1 

0.46% (0.24, 0.69) 0-1 

0.10% (-0.16, 0.37) 0-4 

Cardiovascular 

0.51% (0.28, 0.75) 0 

0.35% (0.12, 0.58) 1 

0.58% (0.31, 0.84) 0-1 

0.35% (0.05, 0.66) 0-4 

<45 yr 

0.59% (-0.62, 1.82) 0 

0.93% (-0.22, 2.08) 1 

1.07% (-0.27, 2.42) 0-1 

1.15% (-0.40, 2.72) 0-4 ≥ 45 yr 

0.51% (0.27, 0.75) 0 

0.33% (0.10, 0.56) 1 

0.56% (0.30, 0.83) 0-1 

0.33% (0.02, 0.63) 0-4 

<65 yr 

0.27% (-0.23, 0.76) 0 

0.30% (-0.16, 0.77) 1 

0.42% (-0.12, 0.97) 0-1 

0.43% (-0.19, 1.06) 0-4 ≥ 65 yr 

0.57% (0.31, 0.83) 0 

0.36% (0.11, 0.61) 1 

0.61% (0.32, 0.90) 0-1 

0.33% (0.00, 0.67) 0-4 

Stroke 

0.44% (0.16, 0.72) 0 

0.41% (0.14, 0.68) 1 

0.58% (0.27, 0.89) 0-1 

0.45% (0.09, 0.81) 0-4 

<45 yr 

1.18% (-0.45, 2.83) 0 

1.66% (0.11, 3.24) 1 

1.91% (0.10, 3.75) 0-1 

2.72% (0.58, 4.89) 0-4 ≥ 45 yr 

0.42% (0.14, 0.70) 0 

0.37% (0.10, 0.65) 1 

0.55% (0.23, 0.86) 0-1 

0.39% (0.03, 0.76) 0-4 

<65 yr 

0.26% (-0.35, 0.87) 0 

0.38% (-0.20, 0.96) 1 

0.48% (-0.19, 1.16) 0-1 

0.57% (-0.21, 1.35) 0-4 ≥ 65 yr 

0.49% (0.17, 0.80) 0 

0.41% (0.11, 0.72) 1 

0.61% (0.26, 0.96) 0-1 

0.42% (0.02, 0.83) 0-4 

Cardiac 

0.49% (0.08, 0.89) 0 

0.28% (-0.11, 0.67) 1 

0.49% (0.04, 0.94) 0-1 

0.22% (-0.29, 0.74) 0-4 

<45 yr 

0.25% (-1.64, 2.17) 0 

0.56% (-1.22, 2.38) 1 

0.61% (-1.47, 2.74) 

0-1 

-0.42% (-2.80, 2.02) 0-4 ≥ 45 yr 

0.49% (0.09, 0.91) 0 

0.27% (-0.12, 0.66) 1 

0.48% (0.03, 0.94) 0-1 

0.25% (-0.27, 0.77) 0-4 

December 2009 E-313 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

<65 yr 

0.00% (-0.89, 0.90) 0 

0.12% (-0.73, 0.98) 1 

0.13% (-0.86, 1.13) 0-1 

0.05% (-1.08, 1.20) 0-4 ≥ 65 yr 

0.60% (0.17, 1.03) 0 

0.32% (-0.10, 0.74) 1 

0.57% (0.09, 1.06) 0-1 

0.26% (-0.29, 0.82) 0-4 

Respiratory 

0.71% (0.20, 1.23) 0 

0.63% (0.13, 1.13) 1 

0.86% (0.28, 1.44) 0-1 

0.19% (-0.48, 0.87) 0-4 

<45 yr 

1.74% (-1.28, 4.86) 0 

2.52% (-0.30, 5.42) 1 

2.95% (-0.41, 6.42) 0-1 

3.47% (-0.61, 7.73) 0-4 ≥ 45 yr 

0.69% (0.18, 1.21) 0 

0.58% (0.09, 1.08) 1 

0.81% (0.23, 1.39) 0-1 

0.13% (-0.54, 0.80) 0-4 

<65 yr 

0.06% (-1.30, 1.43) 0 

-0.53% (-1.83, 0.79) 1 

-0.32% (-1.84, 1.22) 0-1 

-0.72% (-2.47, 1.05) 0-4 ≥ 65 yr 

0.79% (0.27, 1.31) 0 

0.76% (0.26, 1.26) 1 

0.99% (0.41, 1.57) 0-1 

0.30% (-0.38, 0.98) 0-4 

Cardiopulmonary 

0.46% (0.23, 0.69) 0 

0.35% (0.13, 0.57) 1 

0.53% (0.28, 0.79) 0-1 

0.11% (-0.19, 0.42) 0-4 

<45 yr 

0.71% (-0.48, 1.92) 0 

1.26% (0.14, 2.4) 1 

1.39% (0.06, 2.74) 0-1 

1.41% (-0.18, 3.03) 0-4 ≥ 45 yr 

0.45% (0.23, 0.68) 0 

0.32% (0.10, 0.54) 1 

0.51% (0.25, 0.77) 0-1 

0.08% (-0.23, 0.38) 0-4 

<65 yr 

0.14% (-0.34, 0.61) 0 

0.15% (-0.30, 0.61) 1 

0.23% (-0.30, 0.76) 0-1 

0.11% (-0.52, 0.74) 0-4 ≥ 65 yr 

0.53% (0.28, 0.78) 0 

0.39% (0.15, 0.63) 1 

0.60% (0.32, 0.88) 0-1 

0.11% (-0.22, 0.45) 0-4 

Two-pollutant Models 

Nonaccidental 

PM10+NO

2: 0.14% (-0.07, 0.36) 0 

PM10+SO

2: 0.37% (0.20, 0.55) 0 

PM10+O

3: 0.34% (0.17, 0.51) 0 

Cardiovascular 

PM10+NO

2: 0.34% (0.04, 0.63) 0 

PM10+SO

2: 0.53% (0.28, 0.77) 0 

PM10+O

3: 0.50% (0.26, 0.74) 0 

Stroke 

PM10+NO

2: 0.28% (-0.07, 0.63) 0 

PM10+SO

2: 0.49% (0.21, 0.78) 0 

PM10+O

3: 0.44 (0.16, 0.72) 0 

December 2009 E-314 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Cardiac 

PM10+NO2: 0.24% (-0.27, 0.75) 0 

PM10+SO2: 0.43 (0.01, 0.84) 0 

PM10+O3: 0.44% (0.03, 0.85) 0 

Respiratory 

PM10+NO2: 0.46% (-0.19, 1.12) 0 

PM10+SO2: 0.64% (0.11, 1.18) 0 

PM10+O3: 0.67% (0.15, 1.20) 0 

Cardiopulmonary 

PM10+NO2: 0.26% (-0.02, 0.55) 0 

PM10+SO2: 0.46% (0.23, 0.70) 0 

PM10+O3: 0.44% (0.21, 0.67) 0 

Reference: Qian et al. (2008, 156894) 

Period of Study: Jul 2001-Jun 2004 

Location: Wuhan, China 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiovascular (390-459) 

Stroke (430-438) 

Cardiac diseases (390-398, 410-429) 

Respiratory (460-519) 

Cardiopulmonary (390-459, 460-519) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines and penalized splines 

Age Groups: All ages 

<65 yr 

≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Normal temperature: 145.7 (64.6) 

Low temperature: 117.3 (49.5) 

High temperature: 96.3 (27.9) 

Range (Min, Max): NR 

Copollutant (correlation): 

Normal temperature: 

NO2: r = 0/72 

SO2: r = 0.59 

O3: r = 0.06 

Low temperature: 

NO2: r = 0.83 

SO2: r = 0.74 

O3: r = 0.19 

High temperature: 

NO2: r = 0.68 

SO2: r = 0.15 

O3: r = 0.65 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental: 

Normal: 

All ages: 0.36 (0.17, 0.56) 0-1 

<65: 0.23 (-0.10, 0.56) 0-1 

≥ 65: 0.51 (0.18, 0.64) 0-1 

PM10+NO2: 0.07 (-0.17, 0.30) 0-1 

PM10+SO2: 0.27 (0.06, 0.47) 0-1 

PM10+O3: 0.38 (0.18, 0.58) 0-1 

Low: 

All ages: 0.62 (-0.09, 1.34) 0-1 

<65: 1.78 (0.52, 3.05) 0-1 

≥ 65: 0.22 (-0.61, 1.05) 0-1 

PM10+NO2: 0.24 (-0.49, 0.97) 0-1 

PM10+SO2: 0.45 (-0.27, 1.17) 0-1 

PM10+O3: 0.72 (0.00, 1.44) 0-1 

High: 

All ages: 2.20 (0.74, 3.68) 0-1 

<65: 2.34 (-0.09, 4.83) 0-1 

≥ 65: 2.14 (0.42, 3.89) 0-1 

PM10+NO2: 1.87 (0.42, 3.35) 0-1 

PM10+SO2: 2.12 (0.67, 3.60) 0-1 

PM10+O3: 2.15 (0.55, 3.77) 0-1 

Cardiovascular: 

Normal: 

All ages: 0.39 (0.11, 0.66) 0-1 

<65: 0.17 (-0.40, 0.73) 0-1 

≥ 65: 0.44 (0.14, 0.74) 0-1 

PM10+NO2: 0.11 (-0.23, 0.45) 0-1 

PM10+SO2: 0.27 (-0.02, 0.55) 0-1 

PM10+O3: 0.42 (0.15, 0.70) 

Low: 

All ages: 0.72 (-0.25, 1.70) 0-1 

<65: 2.63 (0.67, 4.63) 0-1 

≥ 65: 0.24 (-0.84, 1.32) 0-1 

PM10+NO2: 0.37 (-0.62, 1.38) 0-1 

PM10+SO2: 0.50 (-0.47, 1.49) 0-1 

PM10+O3: 0.82 (-0.16, 1.80) 0-1 

High: 

All ages: 3.28 (1.24, 5.37) 0-1 

<65: 4.32 (0.10, 8.71) 0-1 

≥ 65: 3.03 (0.77, 5.34) 0-1 

PM10+NO2: 3.00 (0.95, 5.09) 0-1 

PM10+SO2: 3.20 (1.16, 5.29) 0-1 

PM10+O3: 3.71 (1.50, 5.96) 0-1 

Stroke: 

Normal: 

All ages: 0.38 (0.06, 0.70) 

<65: 0.17 (-0.53, 0.88) 0-1 

≥ 65: 0.43 (0.07, 0.79) 0-1 

PM10+NO2: 0.09 (-0.31, 0.49) 0-1 

PM10+SO2: 0.31 (-0.03, 0.64) 0-1 

PM10+O3: 0.38 (0.05, 0.71) 0-1 

Low: 

All ages: 0.67 (-0.50, 1.85) 0-1 

<65: 2.85 (0.34, 5.42) 0-1 

≥ 65: 0.11 (-1.22, 1.45) 0-1 

PM10+NO2: 0.29 (-0.90, 1.51) 0-1 

PM10+SO2: 0.53 (-0.65, 1.73) 0-1 

December 2009 E-315 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

PM10+O

3: 0.69 (-0.48, 1.87) 0-1 

High: 

All ages: 2.35 (-0.03, 4.78) 0-1 

<65: 4.54 (-0.79, 10.16) 0-1 ≥ 65: 1.83 (-0.83, 4.57) 

PM10+NO

2: 2.05 (-0.34, 4.49) 0-1 

PM10+SO

2: 2.31 (-0.07, 4.74) 0-1 

PM10+O

3: 2.77 (0.25, 5.35) 0-1 

Cardiac: 

Normal: 

All ages: 0.32 (-0.14, 0.79) 0-1 

<65: -0.04 (-1.07, 1.01) 0-1 ≥ 65: 0.40 (-0.10, 0.91) 0-1 

PM10+NO

2: 0.02 (-0.57, 0.60) 0-1 

PM10+SO

2: 0.11 (-0.38, 0.61) 0-1 

PM10+O

3: 0.41 (-0.06, 0.89) 0-1 

Low: 

All ages: 0.50 (-1.10, 2.13) 0-1 

<65: 1.79 (-1.65, 5.35) 0-1 ≥ 65: 0.19 (-1.55, 1.95) 0-1 

PM10+NO

2: 0.12 (-1.53, 1.80) 0-1 

PM10+SO

2: 0.14 (-1.48, 1.78) 0-1 

PM10+O

3: 0.72 (-0.90, 2.37) 0-1 

High: 

All ages: 3.31 (-0.22, 6.97) 0-1 

<65: 2.71 (-4.58, 10.56) 0-1 ≥ 65: 3.45 (-0.41, 7.46) 0-1 

PM10+NO

2: 3.01 (-0.54, 6.69) 0-1 

PM10+SO

2: 3.17 (-0.37, 6.84) 0-1 

PM10+O

3: 4.92 (0.96, 9.03) 0-1 

Respiratory: 

Normal: 

All ages: 0.80 (0.25, 1.35) 0-1 

<65: -0.35 (-1.85, 1.18) 0-1 ≥ 65: 0.93 (0.38, 1.50) 0-1 

PM10+NO

2: 0.30 (-0.39, 0.99) 0-1 

PM10+SO

2: 0.64 (0.07, 1.22) 0-1 

PM10+O

3: 0.84 (0.28, 1.41) 0-1 

Low: 

All ages: 1.07 (-0.76, 2.95) 0-1 

<65: -1.13 (-6.33, 4.35) 0-1 ≥ 65: 1.30 (-0.57, 3.20) 0-1 

PM10+NO

2: 0.44 (-1.46, 2.36) 0-1 

PM10+SO

2: 0.80 (-1.05, 2.69) 0-1 

PM10+O

3: 1.11 (-0.73, 2.99) 0-1 

High: 

All ages: 1.15 (-3.54, 6.07) 0-1 

<65: -3.42 (-15.82, 10.80) 0-1 ≥ 65: 1.76 (-3.03, 6.78) 0-1 

PM10+NO

2: 0.63 (-4.07, 5.55) 0-1 

PM10+SO

2: 1.03 (-3.66, 5.94) 0-1 

PM10+O

3: 2.66 (-2.44, 8.02) 0-1 

Cardiopulmonary: 

Normal: 

All ages: 0.45 (0.19, 0.70) 0-1 

<65: 0.07 (-0.47, 0.61) 0-1 ≥ 65: 0.53 (0.25, 0.81) 0-1 

PM10+NO

2: 0.15 (-0.17, 0.47) 0-1 

PM10+SO

2: 0.34 (0.07, 0.61) 0-1 

PM10+O

3: 0.43 (0.17, 0.70) 0-1 

Low: 

All ages: 0.69 (-0.22, 1.61) 0-1 

<65: 1.95 (0.04, 3.90) 0-1 ≥ 65: 0.43 (-0.57, 1.44) 0-1 

PM10+NO

2: 0.33 (-0.61, 1.27) 0-1 

PM10+SO

2: 0.50 (-0.42, 1.43) 0-1 

PM10+O

3: 0.76 (-0.16, 1.68) 0-1 

High: 

All ages: 3.02 (1.03, 5.04) 0-1 

<65: 3.49 (-0.66, 7.81) 0-1 ≥ 65: 2.91 (0.74, 5.12) 0-1 

PM10+NO

2: 2.70 (0.72, 4.73) 0-1 

PM10+SO

2: 2.95 (0.96, 4.97) 0-1 

PM10+O

3: 3.32 (1.16, 5.53) 0-1 

December 2009 E-316 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ren et al. (2006, 092824) 

Period of Study: Jan 1996-Dec 2001 

Location: Brisbane, Australia 

Outcome: Mortality: 

Nonaccidental 

Cardiovascular (390-448) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

cubic spline 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 15.84 

Range (Min, Max): (2.5, 60) 

Copollutant: O3

The study presents quantitative results 

associated with an incremental increase 

in temperature, not PM10. 

Reference: Roberts (2004, 087924) 

Period of Study: 1987-1994 

Location: Cook County, Illinois 

Allegheny County, Pennsylvania 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

smooth splines 

Poisson GLM, natural cubic splines 

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 

Cook County 

Lower Temp.: 29.24 

Middle Temp.: 30.03 

Upper Temp.: 52.76 

Allegheny County 

Lower Temp.: 16.50 

Middle Temp.: 24.97 

Upper Temp.: 55.42 

Range (10th, 90th): 

Cook County 

Lower Tem.: (16.42, 46.42) 

Middle Temp.: (14.79, 56.33) 

Upper Temp.: (30.81, 82.81) 

Allegheny County 

Lower Temp.: (5.14, 34.54) 

Middle Temp.: (8.91, 57.91) 

Upper Temp.: (30.91, 88.99) 

Increment: 10 μg/m3

% Increase (SE) lag: 

GLM 

Cook 

α = 0.5 

No Interaction: 0.288% (0.157) 0 

Low Temp.: -0.272% (0.380) 0 

Middle Temp.: 0.344% (0.165) 0 

Upper Temp.: 0.281% (0.239) 0 

No Interaction: 0.359% (0.149) 1 

Low Temp.: -0.168% (0.372) 1 

Middle Temp.: 0.361% (0.156) 1 

Upper Temp.: 0.616% (0.250) 1 

No Interaction: 0.465% (0.176) 0-1 ma 

Low Temp.: 0.043% (0.397) 0-1 ma 

Middle Temp.: 0.506% (0.184) 0-1 ma 

Upper Temp.: 0.464% (0.256) 0-1 ma 

No Interaction: 0.633% (0.214) 0-3 ma 

Low Temp.: 0.365% (0.419) 0-3 ma 

Middle Temp.: 0.638% (0.222) 0-3 ma 

Upper Temp.: 0.718% (0.295) 0-3 ma 

α = 1 

No Interaction: 0.117% (0.157) 0 

Low Temp.: -0.351% (0.406) 0 

Middle Temp.: 0.161% (0.165) 0 

Upper Temp.: 0.096% (0.264) 0 

No Interaction: 0.141% (0.150) 1 

Low Temp.: -0.366% (0.397) 1 

Middle Temp.: 0.161% (0.156) 1 

Upper Temp.: 0.301% (0.278) 1 

No Interaction: 0.260% (0.181) 0-1 ma 

Low Temp.: -0.163% (0.431) 0-1 ma 

Middle Temp.: 0.305% (0.188) 0-1 ma 

Upper Temp.: 0.207% (0.291) 0-1 ma 

No Interaction: 0.289% (0.225) 0-3 ma 

Low Temp.: 0.014% (0.459) 0-3 ma 

Middle Temp.: 0.311% (0.231) 0-3 ma 

Upper Temp.: 0.301% (0.334) 0-3 ma 

α = 2 

No Interaction: 0.060% (0.158) 

0 

0 

Low Temp.: -0.464% (0.486) 

0 

0 

Middle Temp.: 0.115% (0.168) 

0 

0 

Upper Temp.: -0.022% (0.319) 

0 

0 

No Interaction: 0.101% (0.152) 1 

Low Temp.: -0.432% (0.484) 1 

Middle Temp.: 0.089% (0.160) 1 

Upper Temp.: 0.455% (0.327) 1 

No Interaction: 0.129% (0.184) 0-1 ma 

Low Temp.: -0.320% (0.546) 0-1 ma 

Middle Temp.: 0.157% (0.193) 0-1 ma 

Upper Temp.: 0.130% (0.346) 0-1 ma 

No Interaction: 0.090% (0.236) 0-3 ma 

Low Temp.: -0.319% (0.572) 0-3 ma 

Middle Temp.: 0.105% (0.244) 

0-3 ma 

Upper Temp.: 0.193% (0.412) 

0-3 ma 

December 2009 E-317 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Allegheny α = 0.5 

No Interaction: 0.078% (0.209) 0 

Low Temp.: -0.759% (0.643) 0 

Middle Temp.: 0.207% (0.216) 0 

High Temp.: -0.367% (0.364) 0 

No Interaction: 0.189% (0.206) 1 

Low Temp.: -0.335% (0.691) 1 

Middle Temp.: 0.293% (0.215) 1 

High Temp.: -0.171% (0.349) 1 

No Interaction: 0.224% (0.246) 0-1 ma 

Low Temp.: -0.753% (0.763) 0-1 ma 

Middle Temp.: 0.353% (0.253) 0-1 ma 

High Temp.: -0.142% (0.382) 0-1 ma 

No Interaction: 0.526% (0.300) 0-3 ma 

Low Temp.: 0.050% (0.733) 0-3 ma 

Middle Temp.: 0.688% (0.310) 0-3 ma 

High Temp.: -0.043% (0.436) 0-3 ma α = 1 

No Interaction: 0.078% (0.211) 0 

Low Temp.: -0.694% (0.656) 0 

Middle Temp.: 0.214% (0.219) 0 

High Temp.: -0.533% (0.430) 0 

No Interaction: 0.179% (0.207) 1 

Low Temp.: -0.283% (0.718) 1 

Middle Temp.: 0.273% (0.217) 1 

High Temp.: -0.221% (0.396) 1 

No Interaction: 0.221% (0.249) 0-1 ma 

Low Temp.: -0.731% (0.794) 0-1 ma 

Middle Temp.: 0.348% (0.258) 0-1 ma 

High Temp.: -0.253% (0.447) 0-1 ma 

No Interaction: 0.464% (0.309) 0-3 ma 

Low Temp.: 0.056% (0.780) 0-3 ma 

Middle Temp.: 0.626% (0.319) 0-3 ma 

High Temp.: -0.356% (0.516) 0-3 ma α = 2 

No Interaction: 0.034% (0.217) 0 

Low Temp.: -1.059% (0.715) 0 

Middle Temp.: 0.162% (0.230) 0 

High Temp.: -0.233% (0.489) 0 

No Interaction: 0.130% (0.214) 1 

Low Temp.: -0.189% (0.800) 1 

Middle Temp.: 0.157% (0.226) 1 

High Temp.: 0.070% (0.471) 1 

No Interaction: 0.183% (0.260) 0-1 ma 

Low Temp.: -0.918% (0.907) 0-1 ma 

Middle Temp.: 0.279% (0.273) 0-1 ma 

High Temp.: -0.001% (0.526) 0-1 ma 

No Interaction: 0.270% (0.331) 0-3 ma 

Low Temp.: -0.105% (0.898) 0-3 ma 

Middle Temp.: 0.394% (0.346) 0-3 ma 

High Temp.: -0.287% (0.615) 0-3 ma 

GAM 

Cook α = 0.5 

No Interaction: 0.438% (0.151) 0 

Low Temp.: -0.178% (0.364) 0 

Middle Temp.: 0.439% (0.163) 0 

Upper Temp.: 0.627% (0.197) 0 

No Interaction: 0.495% (0.144) 1 

Low Temp.: -0.114% (0.361) 1 

Middle Temp.: 0.460% (0.151) 1 

Upper Temp.: 0.938% (0.208) 1 

No Interaction: 0.710% (0.169) 0-1 ma 

Low Temp.: 0.151% (0.379) 0-1 ma 

Middle Temp.: 0.686% (0.180) 0-1 ma 

Upper Temp.: 0.952% (0.214) 0-1 ma 

No Interaction: 0.923% (0.203) 0-3 ma 

Low Temp.: 0.532% (0.402) 0-3 ma 

Middle Temp.: 0.855% (0.210) 0-3 ma 

Upper Temp.: 1.289% (0.251) 0-3 ma α = 1 

No Interaction: 0.190% (0.154) 0 

December 2009 E-318 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Low Temp.: -0.338% (0.414) 0 

Middle Temp.: 0.242% (0.162) 0 

Upper Temp.: 0.161% (0.230) 0 

No Interaction: 0.239% (0.146) 1 

Low Temp.: -0.283% (0.406) 1 

Middle Temp.: 0.248% (0.152) 1 

Upper Temp.: 0.453% (0.244) 1 

No Interaction: 0.353% (0.174) 0-1 ma 

Low Temp.: -0.074% (0.437) 0-1 ma 

Middle Temp.: 0.388% (0.182) 0-1 ma 

Upper Temp.: 0.345% (0.251) 0-1 ma 

No Interaction: 0.453% (0.213) 0-3 ma 

Low Temp.: 0.190% (0.460) 0-3 ma 

Middle Temp.: 0.455% (0.219) 0-3 ma 

Upper Temp.: 0.557% (0.294) 0-3 ma α = 2 

No Interaction: 0.071% (0.157) 

0 

0 

Low Temp.: -0.534% (0.478) 

0 

0 

Middle Temp.: 0.132% (0.165) 

0 

0 

Upper Temp.: 0.011% (0.264) 

0 

0 

No Interaction: 0.099% (0.150) 1 

Low Temp.: -0.467% (0.472) 1 

Middle Temp.: 0.109% (0.156) 1 

Upper Temp.: 0.329% (0.278) 1 

No Interaction: 0.168% (0.180) 0-1 ma 

Low Temp.: -0.371% (0.525) 0-1 ma 

Middle Temp.: 0.216% (0.188) 0-1 ma 

Upper Temp.: 0.116% (0.290) 0-1 ma 

No Interaction: 0.149% (0.227) 0-3 ma 

Low Temp.: -0.291% (0.557) 0-3 ma 

Middle Temp.: 0.174% (0.233) 0-3 ma 

Upper Temp.: 0.210% (0.340) 0-3 ma 

Allegheny α = 0.5 

No Interaction: 0.245% (0.203) 0 

Low Temp.: -0.727% (0.648) 0 

Middle Temp.: 0.314% (0.216) 0 

High Temp.: 0.308% (0.287) 0 

No Interaction: 0.446% (0.199) 1 

Low Temp.: -0.307% (0.701) 1 

Middle Temp.: 0.469% (0.211) 1 

High Temp.: 0.556% (0.285) 1 

No Interaction: 0.522% (0.237) 0-1 ma 

Low Temp.: -0.646% (0.761) 0-1 ma 

Middle Temp.: 0.567% (0.251) 0-1 ma 

High Temp.: 0.640% (0.307) 0-1 ma 

No Interaction: 0.977% (0.282) 0-3 ma 

Low Temp.: 0.307% (0.733) 0-3 ma 

Middle Temp.: 1.027% (0.296) 0-3 ma 

High Temp.: 1.001% (0.352) 0-3 ma α = 1 

No Interaction: 0.107% (0.209) 0 

Low Temp.: -0.819% (0.699) 0 

Middle Temp.: 0.229% (0.219) 0 

High Temp.: -0.214% (0.350) 0 

No Interaction: 0.223% (0.205) 1 

Low Temp.: -0.316% (0.751) 1 

Middle Temp.: 0.295% (0.216) 1 

High Temp.: 0.002% (0.341) 1 

No Interaction: 0.267% (0.246) 0-1 ma 

Low Temp.: -0.797% (0.840) 0-1 ma 

Middle Temp.: 0.372% (0.257) 0-1 ma 

High Temp.: 0.035% (0.372) 0-1 ma 

No Interaction: 0.534% (0.302) 0-3 ma 

Low Temp.: 0.029% (0.810) 0-3 ma 

Middle Temp.: 0.660% (0.314) 0-3 ma 

High Temp.: 0.071% (0.431) 0-3 ma 

December 2009 E-319 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

α = 2 

No Interaction: 0.061% (0.214) 0 

Low Temp.: -1.048% (0.749) 0 

Middle Temp.: 0.206% (0.226) 0 

High Temp.: -0.332% (0.419) 0 

No Interaction: 0.145% (0.211) 1 

Low Temp.: -0.278% (0.816) 1 

Middle Temp.: 0.210% (0.223) 1 

High Temp.: -0.105% (0.394) 1 

No Interaction: 0.180% (0.256) 0-1 ma 

Low Temp.: -1.028% (0.931) 0-1 ma 

Middle Temp.: 0.298% (0.269) 0-1 ma 

High Temp.: -0.114% (0.441) 0-1 ma 

No Interaction: 0.275% (0.324) 0-3 ma 

Low Temp.: -0.384% (0.915) 0-3 ma 

Middle Temp.: 0.436% (0.338) 0-3 ma 

High Temp.: -0.366% (0.513) 0-3 ma 

Reference: Roberts (2004, 087924) 

Period of Study: 1987-1994 

Location: Cook County, Illinois 

Allegheny County, Pennsylvania 

Outcome: Mortality: 

Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Poisson GLM 

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): 

Max = 89 

The study does not present quantitative 

results. 

Reference: Roberts (Roberts, 2005, 

087992) 

Period of Study: 

Cook County: 1987-2000. 

Allegheny County: 1987-1998 

Location: Cook County, Illinois 

Allegheny County, Pennsylvania 

Outcome: Mortality: 

Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Poisson 

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: NR 

β (SE) lag: 

Standard Model 

Cook County 

0.000127 (0.000264) 0 

-0.000042 (0.000249) 1 

-0.000441 (0.000246) 2 

Allegheny County 

0.000693 (0.000437) 0 

0.000356 (0.000423) 1 

0.000524 (0.000415) 2 

Moving Total Model 

Cook County 

0.000150 (0.000187) k = 2 

-0.000047 (0.000153) k = 3 

0.000009 (0.000133) k = 4 

Allegheny County 

0.000633 (0.000310) k = 2 

0.000542 (0.000255) k = 3 

0.000598 (0.000351) k = 4 

Reference: Roberts (2006, 089762) 

Period of Study: 1987-2000 

Location: Cook County, Illinois 

Suffolk County, Massachusetts 

(NMMAPS) 

Outcome: Mortality: 

Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Poisson GLM 

Age Groups: ≥ 65 yr 

Pollutant: PM10 

Averaging Time: 24-h avg 

Mean (SD): 

Cook County: 33.7 (19.4) 

Suffolk County: 25.9 (11.8) 

Range (10th, 90th): 

Cook County: (13.4, 58.1) 

Suffolk County: (14.0, 41.7) 

Copollutant (correlation): 

Cook County 

CO: r = 0.30 

NO2: r = 0.53 

SO2: r = 0.45 

O3: r = 0.44 

Suffolk County 

CO: r = 0.33 

NO2: r = 0.43 

SO2: r = 0.23 

O3: r = 0.36 

Increment: 

Cook County: 19.4 μg/m3

Suffolk County: 14.0 μg/m3

 

% Increase (SD) lag: 

Cook County 

Standard Model: 0.49% (0.25) 0 

Proposed Model: 0.29% (0.16) 0 

Standard Model: 0.67% (0.25) 0-2 avg 

Proposed Model: 0.49% (0.25) 0-2 avg 

Suffolk County 

Standard Model: 0.88% (1.27) 0 

Proposed Model: 0.85% (0.84) 0 

Standard Model: 1.60% (0.71) 0-2 avg 

Proposed Model: 1.35% (0.73) 0-2 avg 

December 2009 E-320 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Roberts and Martin (2006, 

097799) 

Period of Study: 1987-2000 

Location: Cook County, Illinois 

(NMMAPS) 

Outcome: Mortality: Nonaccidental 

Study Design: Time-series 

Statistical Analyses: Dose-response 

1. Piecewise linear relationship (nothreshold) with change point at 

25 μg/m3

 and 50 μg/m3 

2. Piecewise linear relationship 

(threshold), exposure below 25 μg/m3

no effect, and exposures above 

50 μg/m3

 having a different effect then 

exposures between 25 μg/m3

 and 

50 μg/m3

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

IQR (25th, 75th): 

(23.9, 45.4) 

Suffolk County: (14.0, 41.7) 

Copollutant (correlation): NR 

The study does not present quantitative 

results. 

Reference: Roberts and Martin (2006, 

088670) 

Period of Study: 1987-2000 

Location: 109 U.S. cities (NMMAPS) 

Outcome: Mortality: Nonaccidental 

Cardiorespiratory 

Study Design: Time-series 

Statistical Analyses: Poisson 

2-stage Bayesian hierarchical model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

IQR (25th, 75th): NR 

Copollutant (correlation): NR 

Increment: NR 

β x 1000 (SE x 1000) lag: 

Nonaccidental 

Model 1 

Base df: 0.079 (0.050) 0 

Double df: 0.044 (0.046) 0 

Half df: 0.107 (0.052) 0 

Base df: 0.180 (0.044) 1 

Double df: 0.149 (0.047) 1 

Half df: 0.254 (0.048) 1 

Base df: 0.059 (0.056) 2 

Double df: 0.024 (0.056) 2 

Half df: 0.143 (0.054) 2 

Model 2 

Base df: 0.115 (0.037) 0-2 ma 

Double df: 0.107 (0.034) 0-2 ma 

Half df: 0.145 (0.039) 0-2 ma 

Cardio-respiratory 

Model 1 

Base df: 0.103 (0.068) 0 

Double df: 0.056 (0.067) 0 

Half df: 0.134 (0.066) 0 

Base df: 0.232 (0.060) 1 

Double df: 0.179 (0.067) 1 

Half df: 0.309 (0.059) 1 

Base df: 0.210 (0.078) 2 

Double df: 0.144 (0.075) 2 

Half df: 0.305 (0.079) 2 

Model 2 

Base df: 0.168 (0.047) 0-2 ma 

Double df: 0.140 (0.044) 0-2 ma 

Half df: 0.196 (0.051) 0-2 ma 

Notes: Model 1 uses current day’s 

mortality count, while Model 2 uses a 3-

day moving total mortality count. 

December 2009 E-321 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Roberts and Martin (2007, 

156917) 

Period of Study: 1987-2000 

Location: 8 U.S. cities and >100 U.S. 

cities (NMMAPS) 

Outcome: Mortality: Total 

(nonaccidental) 

Cardiorespiratory 

Study Design: Time-series 

Statistical Analyses: Poisson 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Increment: 10 μg/m3

β x 1000 (SE x 1000) lag: 

8 U.S. cities 

Distributed Lag Model: 0.229 

0-2 

Weighted Model: 0.315 

0-2 

Standard Model: 

0.276 

0 

-0.062 

1 

0.476 

2 

90 U.S. cities 

Total (nonaccidental) 

Standard Model: 

0.078 (0.039) 

0 

0.182 (0.037) 

1 

0.108 (0.036) 

2 

Moving Total Model: 0.131 (0.023) 

0-2 

Weighted Model: 0.274 (0.075) 

0-2 

Cardio-respiratory 

Standard Model: 

0.096 (0.055) 

0 

0.232 (0.053) 

1 

0.226 (0.051) 

2 

Moving Total Model: 

0.174 (0.032) 

0-2 

Weighted Model: 

0.389 (0.105) 

0-2 

Notes: The 8 U.S. cities consist of 

Chicago, Cleveland, Denver, El Paso, 

Houston, Nashville, Pittsburgh, and Salt 

Lake City. 

December 2009 E-322 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Roberts and Martin (2007, 

156916) 

Period of Study: 1987-2000 

Location: 10 U.S. cities (NMMAPS) 

Outcome: Mortality: Nonaccidental

Study Design: Time-series 

Statistical Analyses: Poisson 

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Anchorage: 27.32 

Chicago: 36.95 

Cleveland: 39.83 

Detroit: 40.78 

El Paso: 40.14 

Minneapolis/St. Paul: 28.01 

Pittsburgh: 35.09 

Salt Lake City: 37.40 

Seattle: 28.72 

Spokane: 34.52 

Range (Min, Max): NR 

Increment: NR 

β Coefficient (SE) lag: 

Pooled Estimates 

Combined Model (Unconstrained 

Distributed Lag Model + Piecewise 

Linear Dose-Response Function) 

Change-point: 60 μg/m3

Slope below: 0.00130 (0.00016) 

0-5 

Slope above: -0.00163 (0.00026) 

0-5 

Change-point: 30 μg/m3

Slope below: 0.00014 (0.00039) 

0-5 

Slope above: -0.00003 (0.00015) 

0-5 

Piecewise Linear Dose-Response 

Model 

Change-point: 60 μg/m3

Slope below: 0.00044 (0.00011) 

3-day ma 

Slope above: -0.00077 (0.00020) 

3- day ma 

Change-point: 30 μg/m3

Slope below: 0.00022 (0.00026) 

3-day ma 

Slope above: -0.00004 (0.00011) 

3-day ma 

Polynomial Distributed Lag Model 

(degree 2) 

0.00046 (0.00011) 

0-5 

Reference: Samoli et al. (2005, 

087436) 

Period of Study: 1990-1997 

Location: 22 European cities (APHEA2) 

Outcome: Mortality: 

All-cause (nonaccidental) (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Study Design: Time-series 

Statistical Analyses: Hierarchical 

modeling: 

1. Poisson GAM, penalized splines 

2. Multivariate modeling 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 

Range: (Stockholm: 14 μg/m3

 to Torino: 

65 μg/m3) 

Percentile (90th): 

Range: (Stockholm: 27 μg/m3

 to Torino: 

129 μg/m3) 

Copollutant (correlation): BS 

The study does not present quantitative 

results. 

Reference: Schwartz (2004, 078998) 

Period of Study: 1986-1993 

Location: 14 U.S. cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Case-crossover 

Time-series 

Statistical Analyses: Conditional 

logistic regression 

Poisson 

Age Groups: All ages 

Notes: Case days matched to referent 

days that had the same temperature. 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3 

% Increase (Lower CI, Upper CI) lag: 

Overall: 

Two stage: 0.36% (0.22, 0.50) 1 

Single stage: 0.33% (0.19, 0.46) 1 

More winter temperature lags: 

Two Stage: 0.39% (0.23, 0.56) 1 

One stage: 0.32% (0.19, 0.46) 1 

Time stratified with temperature 

matching: 

Two Stage: 0.39% (0.19, 0.58) 1 

One Stage: 0.53% (0.34, 0.72) 1 

Poisson regression: 

0.40% (0.18, 0.62) 1 

December 2009 E-323 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Schwartz (2004, 053506) 

Period of Study: 1986-1993 

Location: 14 U.S. cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Case-crossover 

Statistical Analyses: Time-stratified 

conditional logistic regression 

Age Groups: All ages 

Notes: Case days matched to referent 

days based on concentration of 

gaseous air pollutants. Matched on the 

following conditions: 

1. 24-h avg SO2 within 1 ppb 

2. Daily-maximum O3 within 2 ppb 

3. 24-h avg NO2 within 1 ppb 

4. 24-h avg CO within 0.03 ppm 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: Range: 23-36 μg/m3

IQR (25th, 75th): 

Range 25th: 17-24 μg/m3

Range 75th: 31-57 μg/m3

Copollutant (correlation): CO 

SO2

NO2

O3

Increment: 10 μg/m3 

β x 1000 (SE x 1000) lag: 

Matched on CO: 0.527 (0.251) 

0-1 avg 

Matched on O3: 0.451 (0.170) 

0-1 avg 

Matched on NO2: 0.784 (0.185) 

0-1 avg 

Matched on SO2: 0.811 (0.175) 

0-1 avg 

Reference: Sharovsky et al. (2004, 

156976) 

Period of Study: Jul 1996-Jun 1998 

Location: São Paulo, Brazil 

Outcome: Mortality: 

Myocardial infarction 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: ≥ 35 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 58.2 (25.8) 

Range (Min, Max): (23, 186) 

Copollutant (correlation): 

CO: r = 0.73 

SO2: r = 0.72 

Increment: 10 μg/m3 

β (SE) lag: 

PM10: 0.001 (0.001) 

PM10+CO+SO2: 0.0004 (0.0008) 

Reference: Simpson et al. (2005, 

087438) 

Period of Study: 1/1996-12/1999 

Location: 4 Australian cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Study Design: Time-series 

meta-analysis 

Statistical Analyses: Poisson GAM, 

natural splines 

Poisson GLM, natural splines 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Brisbane: 16.60 

Sydney: 16.30 

Melbourne: 18.20 

Range (Min, Max): 

Brisbane: (2.6, 57.6) 

Sydney: (3.7, 75.5) 

Melbourne: (3.3, 51.9) 

Copollutant: 

PM2.5

CO 

NO2

Increment: 10 μg/m3 

% Increase (Lower CI, Upper CI) 

lag: 

0.2% (-0.8, 1.2) 

Reference: Slaughter et al. (2005, 

073854) 

Period of Study: Jan 1995-Dec 1999 

Location: Spokane, Washington 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (9th, 95th): (7.9, 41.9) μg/m3

Copollutant (correlation): 

PM10

PM10-2.5: r = 0.94 

CO: r = 0.32 

Increment: : 25 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

1.00 (0.97, 1.03) 1 

0.98 (0.95, 1.01) 2 

1.00 (0.97, 1.03) 3 

Reference: Staniswalis et al. (2005, 

087473) 

Period of Study: 1992-1995 

Location: El Paso, Texas 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: Poisson 

Principal component analysis (PCA) 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): 

(0.2, 133.4) 

Notes: The chemical composition and 

size distribution of PM was not 

available, therefore, the study used 

wind speed as a surrogate variable for 

the PM10 composition. 

Increment: 10 μg/m3 

% Increase (Lower CI, Upper CI) 

lag: 

Poisson regression: 1.7% 3 

PCA: 

24-hly measurements: 2.06% 3 

Daily avg: 1.7% 3 

Reference: Stafoggia et al. (2008, 

157005) 

Period of Study: 1997-2004 

Outcome: 

Mortality: 

Total (nonaccidental) (<800) 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD) unit: 

Bologna: 50.4 (31.7) 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cardiovascular 

All yr: 0.63% (0.31, 1.38) 0-1 

December 2009 E-324 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Location: 9 Italian cities Cardiovascular (390-459) 

Respiratory (460-519) 

Other natural causes 

Study Design: Time-stratified casecrossover 

Statistical Analyses: 

Conditional logistic regression 

Age Groups: ≥ 35 yr 

Florence: 37.5 (16.6) 

Mestre: 48.1 (26.8) 

Milan: 57.9 (38.0) 

Palermo: 36.2 (21.7) 

Pisa: 35.1 (14.9) 

Rome: 47.3 (19.9) 

Taranto: 59.8 (18.9) 

Turin: 71.5 (38.1) 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Winter: 0.15% (-0.29, 0.59) 0-1 

Spring: 0.72% (-0.07, 1.52) 0-1 

Summer: 2.90% (1.14, 4.69) 0-1 

Fall: 1.37% (0.43, 2.32) 0-1 

Apparent Temperature 

<50th Percentile: 

0.31% (-0.06, 0.67) 0-1 

50th-75th Percentile: 

2.05% (0.47, 3.66) 0-1 

>75th Percentile: 2.68% (1.20, 4.17) 0-1

Respiratory 

All yr: 0.98% (0.27, 1.70) 0-1 

Winter: 0.41% (-0.67, 1.51) 0-1 

Spring: 2.99% (1.18, 4.83) 0-1 

Summer: 3.89% (0.19, 7.73) 0-1 

Fall: 0.45% (-1.11, 2.03) 0-1 

Apparent Temperature 

<50th Percentile: 

0.54% (-0.47, 1.57) 0-1 

50th-75th Percentile: 

3.15% (0.64, 5.73) 0-1 

>75th Percentile: 

4.12% (0.44, 7.93) 0-1 

Other natural causes 

All yr: 0.37% (0.09, 0.66) 0-1 

Winter: 0.14% (-0.36, 0.63) 0-1 

Spring: 0.29% (-0.47, 1.05) 0-1 

Summer: 2.15% (0.90, 3.42) 0-1 

Fall: 0.70% (-0.41, 1.83) 0-1 

Apparent Temperature 

<50th Percentile: 

0.07% (-0.27, 0.41) 0-1 

50th-75th Percentile: 

1.08% (-0.02, 2.19) 0-1 

>75th Percentile: 

2.30% (1.06, 3.56) 0-1 

Total (nonaccidental) 

All yr: 0.53% (0.25, 0.80) 0-1 

Winter: 0.20% (-0.08, 0.49) 0-1 

Spring: 0.62% (0.14, 1.10) 0-1 

Summer: 2.54% (1.31, 3.78) 0-1 

Fall: 1.21% (0.37, 2.06) 0-1 

Apparent Temperature 

<50th Percentile: 

0.21% (-0.06, 0.47) 0-1 

50th-75th Percentile: 

1.60% (0.64, 2.57) 0-1 

>75th Percentile: 

2.55% (1.58, 3.52) 0-1 

β coefficient (SE) lag: 

Linear interaction PM10 and Apparent 

Temperature 

Cardiovascular 

<50th Percentile: 

-0.000117 (0.000415) 0-1 

50th-75th Percentile: 

0.003445 (0.001407) 0-1 

>75th Percentile: 

0.002764 (0.001795) 0-1 

Respiratory 

<50th Percentile: 

0.001119 (0.000943) 0-1 

50th-75th Percentile: 

-0.001120 (0.003480) 0-1 

>75th Percentile: 

0.005306 (0.004350) 0-1 

Other natural causes 

<50th Percentile: 

0.000411 (0.000383) 0-1 

50th-75th Percentile: 

-0.001526 (0.001207) 0-1 

>75th Percentile: 

December 2009 E-325 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0.002564 (0.001958) 0-1 

Total (nonaccidental) 

<50th Percentile: 

0.000246 (0.000269) 0-1 

50th-75th Percentile: 

0.000584 (0.000880) 0-1 

>75th Percentile: 

0.002396 (0.001629) 0-1 

Reference: Stölzel et al. (2007, 

091374) 

Period of Study: Sep 1995-Aug 2001 

Location: Erfurt, Germany 

Outcome: 

Mortality: 

Total (nonaccidental) (<800) 

Cardio-respiratory (390-459, 460-519, 

785, 786) 

Study Design: Time-series 

Statistical Analyses: 

Poisson GAM 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD) unit: : 31.9 (23.2) 

IQR (25th, 75th): 

 (16.5, 39.5) 

Copollutant (correlation): 

MC0.1-0.5: r = 0.85 

MC0.01-2.5: r = 0.84 

NO: r = 0.54 

NO2: r = 0.62 

CO: r = 0.50 

Increment: 23 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Total (nonaccidental) 

1.004 (0.980 

1.029) 

0 

1.004 (0.981 

1.027) 

1 

0.998 (0.976 

1.021) 

2 

0.984 (0.962 

1.006) 

3 

0.993 (0.972 

1.015) 

4 

0.990 (0.969 

1.012) 

5 

Cardio-respiratory 

1.007 (0.981 

1.034) 

0 

1.006 (0.981 

1.032) 

1 

0.996 (0.971 

1.021) 

2 

0.977 (0.953 

1.002) 

3 

0.994 (0.970 

1.018) 

4 

0.993 (0.969 

1.017) 

5 

Reference: Sullivan et al. (2003, 

043156) 

Period of Study: 

1985-1994 

Location: Western Washington 

Outcome: 

Out-of-hospital cardiac arrest 

Study Design: Case-crossover 

Statistical Analyses: 

Conditional logistic regression 

Age Groups: 19-79 

Study Population: Out-of-hospital 

cardiac arrests: 1,206 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 

Lag 0: 28.05 

Lag 1: 27.97 

Lag 2: 28.40 

Range (Min, Max): (7.38, 89.83) 

Copollutant (correlation): 

SO2

CO 

Notes: Study used nephelometry to 

measure particles and equated the 

measurements to PM2.5 concentrations. 

Increment: : 16.51 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

Overall 

1.05 (0.87, 1.27) 

0 

0.91 (0.75, 1.11) 

1 

1.03 (0.82, 1.28) 

2 

December 2009 E-326 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sunyer et al. (2002, 

034835) 

Period of Study: 1985-1995 

Location: Barcelona, Spain 

 

Outcome: Mortality: 

Respiratory mortality 

Study Design: Case-crossover 

Statistical Analyses: Condition logistic 

regression 

Age Groups: >14 

Study population: Asthmatic individuals: 

5,610 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 61.2 

Range (Min, Max): (17.3, 240.7) 

Copollutant: 

BS 

NO2

O3

SO2

CO 

Increment: 32.7 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

Asthmatic individuals with 1 ED visit 

0.884 (0.672, 1.162) 0-2 avg 

Asthmatic individuals with >1 ED visit 

1.084 (0.661, 1.778) 0-2 avg 

Asthma/COPD individuals with >1 ED 

visit 

1.011 (0.746, 1.368) 0-2 avg 

Reference: Touloumi et al. (2005, 

087477) 

Period of Study: 1990-1997 

Location: 7 European cities (London, 

Budapest, Stockholm, Zurich, Paris, 

Lyon, Madrid) (APHEA2) 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiovascular (390-459) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Median (SD) unit: 

London: 25.1 

Budapest: 40.2 

Stockholm: 13.7 

Zurich: 27.5 

Paris: 22.2 

Lyon: 38.5 μ 

Madrid: 33.4 

IQR (25th, 75th): 

London: (20.3, 33.9) 

Budapest: (34.3, 45.8) 

Stockholm: (10.3, 19.1) 

Zurich: (19.2, 38.5) 

Paris: (16.0, 33.0) 

Lyon: (29.7, 50.4) 

Madrid: (27.6, 41.0) 

Copollutant (correlation): NR 

Increment: 10 μg/m3

β (x 1000) (SE (x 1000)): 

Total (nonaccidental) 

No control: 0.4834 (0.1095) 

Reported Influenza Data 

Count ID: 0.4967 (0.1089) 

I1 ID: 0.4740 (0.1090) 

MI ID: 0.5019 (0.1096) 

RI-ID: 0.4735 (0.1091) 

SF ID: 0.6714 (0.1080) 

Estimated Influenza Data 

APHEA-2: 0.5550 (0.1076) 

I1 EID: 0.5640 (0.1073) 

MI EID: 0.5872 (0.1100) 

RI EID: 0.5872 (0.1074) 

SF EID: 0.6641 (0.1073) 

Cardiovascular 

No control: 0.8432 (0.1665) 

Reported Influenza Data 

Count ID: 0.8896 (0.1662) 

I1 ID: 0.8545 (0.1661) 

MI ID: 0.8693 (0.1674) 

RI-ID: 0.8649 (0.1665) 

SF ID: 1.0107 (0.1659) 

Estimated Influenza Data 

APHEA-2: 0.9389 (0.1654) 

I1 EID: 0.9485 (0.1648) 

MI EID: 1.0440 (0.1686) 

RI EID: 0.9718 (0.1653) 

SF EID: 1.0585 (0.1652) 

Notes: I1 = one indicator for all 

epidemics 

M1 = multiple indicators, one per 

epidemic 

R1 = indicators for intervals indicating 

the range of influenza counts 

SF = separate smooth function during 

epidemic periods. 

Reference: Tsai et al. (2003, 050480) 

Period of Study: 1994-2000 

Location: Kaohsiung, Taiwan 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Respiratory (460-519) 

Circulatory (390-459) 

Study Design: Bidirectional casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 81.45 

Range (Min, Max): (20.50, 232.00) 

Copollutant: 

SO2

NO2

CO 

O3 

Increment: 67.00 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

Total (nonaccidental) 

1.000 (0.947, 1.056) 0-2 avg 

Respiratory 

1.023 (0.829, 1.264) 0-2 avg 

Circulatory 

0.971 (0.864, 1.092) 0-2 avg 

December 2009 E-327 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Vajanapoom et al. (2002, 

042542) 

Period of Study: 1992-1997 

Location: Bangkok, Thailand 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Respiratory (460-519) 

Cardiovascular (390-459) 

Other-causes 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: 

All ages 

55-64 yr 

65-74 yr 

≥ 75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 68.0 (23.9) 

IQR (25th, 75th): 

(50.1, 80.7) 

Copollutant (correlation): NR 

Increment: 30 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Total (nonaccidental) 

All ages: 2.3% (1.3, 3.3) 0-4 ma 

55-64: 1.5% (-0.8, 3.9) 0-4 ma 

65-74: 4.2% (2.0, 6.3) 0-4 ma 

≥ 75: 3.9% (2.1, 5.6) 0-4 ma 

Cardiovascular 

All ages: 0.8% (-0.9, 2.4) 0 

55-64: -2.5% (-6.3, 1.3) 0 

65-74: 2.9% (-0.7, 6.5) 0 

≥ 75: 1.6% (-1.8, 5.0) 0 

Respiratory 

All ages: 5.1% (0.6, 9.6) 0-2 ma 

55-64: 1.4% (-11.3, 14.2) 0-2 ma 

65-74: 2.8% (-9.5, 15.2) 0-2 ma 

≥ 75: 10.2% (-0.1, 20.5) 0-2 ma 

Other-causes 

All ages: 2.4% (1.3, 3.5) 0-4 ma 

55-64: 1.7% (-1.1, 4.5) 0-4 ma 

65-74: 5.6% (3.1, 8.1) 0-4 ma 

≥ 75: 3.7% (1.8, 5.6) 0-4 ma 

Reference: Vedal et al. (2003, 039044) 

Period of Study: Jan 1994-Dec 1996 

Location: Vancouver, British Columbia, 

Canada 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Respiratory (460-519) 

Cardiovascular (390-459) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

LOESS 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 14.4 (5.9) 

Range (Min, Max): (4.1, 37.2) 

Copollutant (correlation): O3: r = 0.48 

SO2: r = 0.76 

NO2: r = 0.84 

CO: r = 0.71 

The study does not present quantitative 

results 

Reference: Venners et al. (2003, 

089931) 

Period of Study: Jan 1995-Dec 1995 

Location: Chongqing, China 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

cubic spline 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 146.8 

Range (Min, Max): (44.7, 666.2) 

Copollutant: SO2

Notes: PM10 was measured for only 7 

mo of the study period. 

Increment: 100 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

1.00 (0.93, 1.07) 0 

0.98 (0.91, 1.04) 1 

1.00 (0.93, 1.07) 2 

0.96 (0.90, 1.03) 3 

0.97 (0.90, 1.03) 4 

0.99 (0.93, 1.06) 5 

Reference: Vichit-Vadakan et al. (2008, 

157095) 

Period of Study: Jan 1999-Dec 2003 

Location: Bangkok, Thailand 

Outcome (ICD10): Mortality: 

Nonaccidental (A00-R99) 

Cardiovascular (I00-I99) 

Ischemic heart diseases (I20-I25) 

Stroke (I60-I69) 

Conduction disorder (I44-I49) 

Respiratory (J00-J98) 

Lower Respiratory Infection (J10-J22) 

COPD (J40-J47) 

Asthma (J45-J46) 

Senility (R54) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

cubic spline 

Age Groups: All ages 

0-4 yr 

5-44 yr 

18-50 yr 

45-64 yr 

≥ 50 yr 

≥ 65 yr 

≥ 75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 52.1 (20.1) 

Range (Min, Max): (21.3, 169.2) 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) 

lag: 

Cause-specific mortality: 

Nonaccidental: 1.3% (0.8, 1.7) 0-1 

Cardiovascular: 1.9% (0.8, 3.0) 0-1 

Ischemic heart disease: 

1.5% (-0.4, 3.5) 0-1 

Stroke: 2.3% (0.6, 4.0) 0-1 

Conduction disorders: 

-0.%3 (-5.9, 5.6) 0-1 

Cardiovascular: 

≥ 65 1.8 (0.2, 3.3) 0-1 

Respiratory: 

All ages: 1.0 (-0.4, 2.4) 0-1 

≤ 1: 14.6 (2.9, 27.6) 0-1 

≥ 65: 1.3 (-0.8, 3.3) 0-1 

LRI: <5: 7.7 (-3.6, 20.3) 0-1 

COPD: 1.3 (-1.8, 4.4) 0-1 

Asthma: 7.4 (1.1, 14.1) 0-1 

Senility: 1.8 (0.7, 2.8) 0-1 

Age-specific for nonaccidental 

0-4: 0.2 (-2.0, 2.4) 0-1 

5-44: 0.9 (0.2, 1.7) 0-1 

18-50: 1.2 (0.5, 1.9) 0-1 

45-64: 1.1 (0.4, 1.9) 0-1 

≥ 50: 1.4 (0.9, 1.9) 0-1 

December 2009 E-328 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

≥ 65: 1.5 (0.9, 2.1) 0-1 

≥ 75: 2.2 (1.3, 3.0) 0-1 

Sex-specific for nonaccidental 

Male: 1.2 (0.7, 1.7) 0-1 

Female: 1.3 (0.7, 1.9) 0-1 

Nonaccidental 

1.2 (0.8, 1.6) 0 

0.9 (0.6, 1.3) 1 

0.9 (0.5, 1.3) 2 

0.8 (0.4, 1.2) 3 

0.3 (-0.1, 0.7) 4 

1.3 (0.8, 1.7) 0-1 

1.4 (0.9, 1.9) 0-4 

Cardiovascular 

1.5 (0.5, 2.6) 0 

1.7 (0.7, 2.7) 1 

1.6 (0.6, 2.6) 2 

0.8 (-0.1, 1.8) 3 

-0.1 (-1.1, 0.9) 4 

1.9 (0.8, 3.0) 0-1 

1.9 (0.6, 3.2) 0-4 

Respiratory 

1.0 (-0.3, 2.3) 0 

0.8 (-0.5, 2.0) 1 

1.1 (-0.1, 2.3) 2 

1.3 (0.1, 2.6) 3 

0.7 (-0.6, 1.9) 4 

1.0 (-0.4, 2.4) 0-1 

1.9 (1.2, 2.6) 0-4 

≥ 65 

1.5 (0.9, 2.0) 0 

1.1 (0.6, 1.7) 1 

1.1 (0.6, 1.6) 2 

1.2 (0.6, 1.7) 3 

0.7 (0.2, 1.2) 4 

1.5 (0.9, 2.1) 0-1 

1.9 (1.2, 2.6) 0-4 

Sensitivity analysis: 

Nonaccidental (df): 

3: 1.3 (0.9, 1.8) 

4: 1.2 (0.8, 1.7) 

6: 1.3 (0.8, 1.7) 

6, with SO2: 1.2 (0.8, 1.7) 

6, with NO2: 1.0 (0.2, 1.8) 

6, with O3: 1.1 (0.6, 1.7) 

9: 1.1 (0.7, 1.6) 

12: 1.1 (0.6, 1.5) 

15: 1.2 (0.7, 1.6) 

Cardiovascular (df): 

3: 1.8 (0.8, 2.7) 

4: 1.6 (0.7, 2.6) 

6: 1.7 (0.7, 2.7) 

6, with SO2: 2.0 (0.9, 3.3) 

6, with NO2: 2.3 (0.2, 4.3) 

6, with O3: 1.8 (0.5, 3.2) 

9: 1.7 (0.6, 2.8) 

12: 1.8 (0.7 to 3.0) 

15: 2.2 (0.9, 3.4) 

December 2009 E-329 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Villeneuve et al. (2003, 

055051) 

Period of Study: 1986-1999 

Location: Vancouver, Canada 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (401-440) 

Respiratory (460-519) 

Cancer (140-239) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

splines 

Age Groups: ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Daily 14.0 

Every 6th Day 19.6 

Range (Min, Max): 

Daily (3.8, 52.2) 

Every 6th Day (3.5, 63.0) 

Copollutant: 

SO2

CO 

NO2

O3

PM2.5

PM10-2.5

Increment: 15.4 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental 

3.7% (-0.5, 8.0) 0-2 avg 

2.6% (-0.9, 6.1) 0 

2.7% (-0.7, 6.2) 1 

1.9% (-1.4, 5.3) 2 

Cardiovascular 

3.4% (-2.7, 9.8) 0-2 avg 

5.1% (0.0, 10.4) 0 

1.3% (-3.8, 6.7) 1 

0.6% (-4.3, 5.7) 2 

Respiratory 

PM10

0.1% (-9.5, 10.8) 0-2 avg 

1.0% (-7.5, 10.4) 0 

0.4% (-7.7, 9.3) 1 

-1.3% (-8.9, 7.1) 2 

Cancer 

1.2% (-6.9, 10.1) 0-2 avg 

-2.5% (-8.8, 4.3) 0 

2.3% (-4.6, 9.6) 1 

3.3% (-3.7, 10.8) 2 

Reference: Welty et al. (2008, 157134) 

Period of Study: 1987-2000 

Location: Chicago, Illinois 

Outcome: Mortality: 

Total (nonaccidental) 

Study Design: Time-series 

Statistical Analyses: Poisson-Gibbs 

Sampler 

Bayesian Distributed Lag Model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) 

lag: 

Poisson-Gibbs Sampler 

0.17% (0.01, 0.34) 3 

-0.24% (-0.73, 0.23) 0-14 

Unconstrained: 

-0.19% (-0.86, 0.48) 0-14 

Bayesian Distributed Lag Model 

-0.21% (-0.86, 0.41) 0-14 

Reference: Welty and Zeger (2005, 

087484) 

Period of Study: 1987-2000 

Location: 100 U.S. cities (NMMAPS) 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Study Design: Time-series 

Statistical Analyses: Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (SE) lag: 

Distributed Lag Model: 

Seasonally-Temporally Varying 

Temperature variables: 0, 1-2, 1-7, 1-14 

S(t, 1 × yr): 0.229 (0.053) 1 

S(t, 2 × yr): 0.220 (0.053) 1 

S(t, 4 × yr): 0.187 (0.050) 1 

S(t, 8 × yr): 0.178 (0.049) 1 

Temperature variables: 0, 1-2, 1-7, 

1-14, 0×1-2, 0×1-7, 

1-2 × 1-7 

S(t, 1 × yr): 0.195 (0.048) 1 

S(t, 2 × yr): 0.200 (0.051) 1 

S(t, 4 × yr): 0.176 (0.050) 1 

S(t, 8 × yr): 0.149 (0.050) 1 

Distributed Lag Model: Nonlinear 

Temperature variables: 0, 1-2, 1-7, 1-14 

S(t, 4 × yr): 0.239 (0.053) 1 

Temperature variables: 0, 1-2, 1-7, 

1-14, 0×1-2, 0×1-7, 1-2 × 1-7 

S(t, 4 × yr): 0.172 (0.045) 1 

Temperature variables: S(0,2), S(1-2,2), 

S(1-7,2), S(1-14,2) 

S(t, 4 × yr): 0.186 (0.046) 1 

Temperature variables: S(0,2), S(1-2,2), 

S(1-7,2), S(1-14,2), S(0×1-2,2), 

S(0×1-7,2), S(1-2 × 1-7,2) 

S(t, 4 × yr): 0.189 (0.047) 1 

December 2009 E-330 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Temperature variables: S(0,4), S(1-2,4), 

S(1-7,4), S(1-14,4) 

S(t, 4 × yr): 0.175 (0.046) 1 

Temperature variables: S(0,4), S(1-2,4), 

S(1-7,4), S(1-14,4), S(0×1-2,4), 

S(0×1-7,4), S(1-2 × 1-7,4) 

S(t, 4 × yr): 0.190 (0.048) 1 

Temperature variables: 0, 1-2, 1-7 

S(t, 4 × yr): 0.252 (0.053) 1 

Temperature variables: 0, 1-2, 1-7, 

0×1-2, 0×1-7, 1-2 × 1-7 

S(t, 4 × yr): 0.186 (0.044) 1 

Temperature variables: S(0,2), S(1-2,2), 

S(1-7,2) 

S(t, 4 × yr): 0.198 (0.046) 1 

Temperature variables: S(0,2), S(1-2,2), 

S(1-7,2), S(0×1-2,2), S(0×1-7,2), 

S(1-2 × 1-7,2) 

S(t, 4 × yr): 0.201 (0.047) 1 

Temperature variables: S(0,4), S(1-2,4), 

S(1-7,4) 

S(t, 4 × yr): 0.189 (0.045) 1 

Temperature variables: S(0,4), S(1-2,4), 

S(1-7,4), S(0×1-2,2), S(0×1-7,4), 

S(1-2 × 1-7,2) 

S(t, 4 × yr): 0.205 (0.047) 1 

Temperature variables: S(0,4), S(1-2,4) 

S(t, 4 × yr): 0.250 (0.045) 1 

Temperature variables: S(0,4), S(1-2,4), 

S(0×1-2,4) 

S(t, 4 × yr): 0.253 (0.044) 1 

Temperature variables: S(0,4) 

S(t, 4 × yr): 0.220 (0.045) 1 

Notes: 0 indicates current-day 

temperature 

1-r indicates avg of lag 1 through lag r 

temperature 

S (, ρ) indicates a natural spline smooth 

with ρ degrees of freedom. 

S (t, α x yr) indicates the natural spline 

smooth of time with degrees of freedom 

equal to α x (number of yr of data). 

December 2009 E-331 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Wong et al. (2007, 098391) 

Period of Study: Jan 1998-Dec 1998 

Location: Hong Kong, China 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiorespiratory (390-519) 

Study Design: Main analysis: Timeseries 

Sensitivity analysis: Case-crossover, 

case-only 

Statistical Analyses: Main analysis: 

Poisson GAM 

Sensitivity analysis: Conditional 

logistic regression 

Age Groups: ≥ 30 yr; ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

48.1 (24.3) 

Range (Min, Max): 

(15.5, 140.5) 

Copollutant: 

NO2

SO2

O3

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) 

lag: 

Main Analysis 

Nonaccidental 

Smokers: 

≥ 301: .80% (0.35, 3.26) 0 

1.77% (0.46, 3.11) 2 

≥ 65: 3.20% (1.36, 5.07) 0 

2.42% (0.73, 4.13) 2 

Never-smokers 

≥ 30: -0.37% (-2.23, 1.52) 0 

-0.03% (-1.72, 1.66) 2 

≥ 65P -0.70% (-2.81, 1.46) 0 

-0.13% (-2.04, 1.80) 2 

Cardiorespiratory 

Smokers 

≥ 30: 1.43% (-0.86, 3.78) 0 

2.32% (0.24, 4.44) 2 

≥ 65: 2.98% (0.47, 5.55) 0 

2.61% (0.31, 4.95) 2 

Never-smokers 

≥ 30: 0.02% (-2.75, 2.87) 0 

-0.79% (-3.33, 1.82) 2 

≥ 65: 0.25% (-2.62, 3.19) 0 

-0.66% (-3.29, 2.04) 2 

Sensitivity Analysis 

Poisson Regression 

Nonaccidental 

≥ 30: 1.81% (0.21, 3.44) 0 

1.93% (0.32, 3.56) 2 

1.99% (0.14, 3.87) 0-3 

≥ 65: 2.31% (0.37, 4.29) 0 

2.16% (0.20, 4.15) 2 

2.57% (0.30, 4.89) 0-3 

Cardiorespiratory 

≥ 30: 1.04% (-1.45, 3.59) 0 

2.18% (-0.35, 4.77) 2 

1.66% (-1.24, 4.64) 0-3 

≥ 65: 1.69% (-0.93, 4.37) 0 

2.44% (-0.23, 5.18) 2 

2.30% (-0.80, 5.50) 0-3 

Case-only: Logistic Regression 

Nonaccidental 

≥ 30: 1.79% (0.21, 3.37) 0 

1.94% (0.33, 3.56) 2 

≥ 65: 2.30% (0.42, 4.17) 0 

2.16% (0.26, 4.07) 2 

Cardiorespiratory 

≥ 30: 1.01% (-1.37, 3.40) 0 

2.16% (-0.28, 4.61) 2 

≥ 65: 1.65% (-0.96, 4.27) 0 

2.42% (-0.27, 5.12) 2 

Case-crossover 

Nonaccidental 

≥ 30: 2.54% (0.35, 4.78) 0 

1.35% (-0.81, 3.56) 2 

≥ 65: 3.96% (1.37, 6.63) 0 

2.20% (-0.35, 4.81) 2 

Cardiorespiratory 

≥ 30: 0.48% (-2.74, 3.80) 0 

3.24% (-0.03, 6.61) 2 

≥ 65: 2.17% (-1.40, 5.86) 0 

3.43% (-0.13, 7.13) 2 

Reference: Wong et al. (2007, 093278) 

Period of Study: Jan 1998-Dec 1998 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

48.1 (24.3) 

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) 

lag: 

Nonaccidental 

December 2009 E-332 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Location: Hong Kong, China Cardiorespiratory (390-519) 

Study Design: Main analysis: Timeseries 

Sensitivity analysis: Case-only 

Statistical Analyses: Main analysis: 

Poisson GAM, natural cubic spline 

Sensitivity analysis: Logistic 

regression 

Age Groups: ≥ 30 yr; ≥ 65 yr 

Range (Min, Max): (15.5, 140.5) 

Copollutant: 

NO2

SO2

O3

Exercise 

≥ 30: 0.13% (-1.16, 1.44) 1 

≥ 65: 0.24% (-1.16, 1.67) 1 

Never-exercise 

≥ 30: 1.04% (0.07, 2.02) 1 

≥ 65: 1.26% (0.27, 2.27) 1 

Cardio-respiratory 

Exercise 

≥ 30: 0.46% (-1.43, 2.39) 1 

≥ 65: 0.30% (-1.65, 2.29) 1 

Never-exercise 

≥ 30: 0.97% (-0.36, 2.32) 1 

≥ 65: 0.98% (-0.45, 2.43) 1 

Difference in % Excess Risk (Exercise 

vs. Never-Exercise) 

Nonaccidental 

Poisson Regression 

≥ 30: -2.86% (-4.03 to -1.67) 1 

≥ 65: -3.06% (-4.37 to -1.74) 1 

Case-only 

≥ 30: -2.91% (-4.04 to -1.77) 1 

≥ 65: -3.12% (-4.38 to -1.84) 1 

Cardiorespiratory 

Poisson regression 

≥ 30: -2.55% (-4.32 to -0.75) 1 

≥ 65: -2.64% (-4.48 to -0.76) 1 

Case-only 

≥ 30: -2.63% (-4.32 to -0.92) 1 

≥ 65: -2.73% (-4.50 to -0.92) 1 

Adjusted Case-only 

Nonaccidental 

Sex 

≥ 30: -2.88% (-1.73 to -4.01) 1 

≥ 65: -3.09% (-1.82 to -4.35) 1 

Education 

≥ 30: -2.94% (-1.80 to -4.07) 1 

≥ 65: -3.18% (-1.90 to -4.44) 1 

Job 

≥ 30: -2.88% (-1.74 to -4.02) 1 

≥ 65: -3.11% (-1.83 to -4.37) 1 

Smoking 

≥ 30: -2.82% (-1.66 to -3.96) 1 

≥ 65: -2.97% (-1.68 to -4.25) 1 

Illness time 

≥ 30: -2.94% (-1.80 to -4.07) 1 

≥ 65: -3.16% (-1.88 to -4.42) 1 

Cardiorespiratory 

Sex 

≥ 30: -2.61% (-0.89 to -4.29) 1 

≥ 65: -2.71% (-0.90 to -4.48) 1 

Education 

≥ 30: -2.58% (-0.85 to -4.27) 1 

≥ 65: -2.77% (-0.95 to -4.54) 1 

Job 

≥ 30: -2.68% (-0.96 to -4.37) 1 

≥ 65: -2.68% (-0.88 to -4.46) 1 

Smoking 

≥ 30: -2.46% (-0.73 to -4.17) 1 

≥ 65: -2.50% (-0.68 to -4.29) 1 

Illness Time 

≥ 30: -2.63% (-0.91 to -4.32) 1 

≥ 65: -2.73% (-0.92 to -4.51) 1 

December 2009 E-333 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Case-only by Exercise Group (Never as 

Reference) 

Nonaccidental 

≥ 30 

Low: -3.34% (-5.77 to -0.85) 1 

Moderate: -6.32% (-8.55 to -4.03) 1 

High: -1.74% (-3.06 to -0.40) 1 

≥ 65 

Low: -3.79% (-6.67 to -0.82) 1 

Moderate: -7.78% (-10.39 to -5.10) 1 

High: -1.77% (-3.21 to -0.31) 1 

Cardiorespiratory 

≥ 30 

Low: -3.95% (-7.77, 0.04) 1 

Moderate: -8.50% (-11.84 to -5.02) 1 

High: -0.62% (-2.58, 1.38) 1 

≥ 65 

Low: -3.97% (-8.17, 0.43) 1 

Moderate: -9.42% (-13.00 to -5.69) 1 

High: -0.68% (-2.71, 1.38) 1 

Reference: Wong et al. (2002, 025436) 

Period of Study: 1995-1998 

Location: Hong Kong, China 

Outcome: Mortality: 

Respiratory (461-519) 

COPD (490-496) 

Pneumonia & Influenza (480-487) 

Cardiovascular (390-459) 

IHD (410-414) 

Cerebrovascular (430-438) 

Study Design: Time-series 

Statistical Analyses: Poisson 

Age Groups: ≥ 30 yr; ≥ 65 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

51.53 (24.79) 

Range (Min, Max): 

(14.05, 163.79) 

Copollutant (correlation): 

NO2: r = 0.780 

SO2: r = 0.344 

O3: r = 0.538 

Increment: 10 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

Respiratory 

1.008 (1.001 to 1.014) 1 

COPD 

1.017 (1.002, 1.033) 0-3 

Pneumonia & Influenza 

1.007 (0.999, 1.015) 2 

Cardiovascular 

1.003 (0.998, 1.016) 2 

IHD 

1.013 (1.001, 1.025) 0-3 

Cerebrovascular 

1.007 (0.998, 1.016) 2 

Respiratory 

PM10+SO2+O3+NO2: 

1.005 (0.992, 1.010) 1 

COPD 

PM10+SO2+O3+NO2: 

0.991 (0.968, 1.015) 0-3 

PM10+O3+NO2: 

0.993 (0.970, 1.016) 0-3 

Pneumonia & Influenza 

PM10+SO2+O3+NO2: 

1.002 (0.991, 1.013) 2 

IHD 

0.994 (0.978, 1.009) 0-3 

December 2009 E-334 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Wong et al. (2008, 157152) 

Period of Study: 

Bangkok: 1999-2003 

Hong Kong: 1996-2002 

Shanghai & Wuhan: 2001-2004 

Location: Bangkok, Thailand 

Hong Kong, Shanghai, and Wuhan, 

China 

Outcome (ICD10): Mortality: 

Natural causes (A00-R99) 

Cardiovascular (I00-I99) 

Respiratory (J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

≥ 65 yr 

≥ 75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Bangkok: 52.0 

Hong Kong: 51.6 

Shanghai: 102.0 

Wuhan: 141.8 

Range (Min, Max): 

Bangkok: (21.3, 169.2) 

Hong Kong: (13.7, 189.0) 

Shanghai: (14.0, 566.8) 

Wuhan: (24.8, 477.8) 

Copollutant: 

NO2

SO2

O3 

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) 

lag: 

Random Effects (4 cities) 

Natural causes: 0.55% (0.26, 0.85) 0-1 

Cardiovascular: 0.58% (0.22, 0.93) 0-1 

Respiratory: 0.62% (0.22, 1.02) 0-1 

Random Effects (3 Chinese cities) 

Natural causes: 0.37% (0.21, 0.54) 0-1 

Cardiovascular: 0.44% (0.19, 0.68) 0-1 

Respiratory: 0.60% (0.16, 1.04) 0-1 

Sensitivity Analysis 

Random Effects (4 cities) 

Omit PM10>95th: 0.53% (0.27, 0.78) 0-1

Omit PM10>75th: 0.53% (0.29, 0.78) 0-1

Omit PM10>180 μg/m3

: 

0.65% (0.24, 1.06) 0-1 

Omit stations with high traffic source: 

0.55% (0.26, 0.85) 0-1 

Warm season-dichotomous variables: 

0.86% (0.11, 1.60) 0-1 

Add temperature at lag 1-2 days: 0.51% 

(0.23, 0.79) 0-1 

Add temperature at lag 3-7 days: 0.35% 

(0.14, 0.57) 0-1 

Daily PM10 defined by centering: 0.54% 

(0.26, 0.82) 0-1 

Natural spline with (8, 4, 4f: 0.54% 

(0.26, 0.81) 0-1 

Penalized spline: 

0.52% (0.26, 0.77) 0-1 

Random Effects (3 Chinese cities) 

Omit PM10>95th: 0.47% (0.21, 0.73) 0-1

Omit PM10>75th: 0.55% (0.24, 0.85) 0-1

Omit PM10>180 μg/m3

: 

0.46% (0.15, 0.76) 0-1 

Omit stations with high traffic source: 

0.38% (0.20, 0.57) 0-1 

Warm season-dichotomous variables: 

0.43% (0.10, 0.76) 0-1 

Add temperature at lag 1-2 days: 

0.36% (0.18, 0.53) 0-1 

Add temperature at lag 3-7 days: 

0.25% (0.10, 0.40) 0-1 

Daily PM10 defined by centering: 

0.37% (0.21, 0.53) 0-1 

Natural spline with (8, 4, 4f: 

0.36% (0.23, 0.49) 0-1 

Penalized spline: 

0.34% (0.23, 0.45) 0-1 

Reference: Wong et al. (2008, 157151) 

Period of Study: Jan 1996-Dec 2002 

Location: Hong Kong 

Outcome (ICD10): Mortality: 

Nonaccidental (A00-T99 

Z00-Z99) 

Cardiovascular (I00-I99) 

Respiratory (J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 51.6 (25.3) 

Range (Min, Max): (13.5, 188.5) 

Copollutant: 

NO2

SO2

O3 

Increment: 10 μg/m3 

% Excess Risk (Lower CI, Upper CI) 

lag: 

Nonaccidental: 

Low SDI 

0.37 (-0.10, 0.84) 0 

0.40 (-0.04, 0.84) 1 

0.14 (-0.28, 0.57) 2 

-0.12 (-0.55, 0.30) 3 

-0.14 (-0.56, 0.28) 4 

Middle SDI 

0.70 (0.34, 1.07) 0 

0.48 (0.14, 0.82) 1 

0.35 (0.02, 0.68) 2 

0.18 (-0.14, 0.51) 3 

0.17 (-0.16, 0.50) 4 

High SDI 

0.22 (-0.29, 0.73) 0 

0.46 (-0.01, 0.94) 1 

0.29 (-0.17, 0.75) 2 

-0.05 (-0.51, 0.40) 3 

-0.06 (-0.51, 0.40) 4 

All areas 

December 2009 E-335 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

0.45 (0.19, 0.72) 0 

0.40 (0.15, 0.64) 1 

0.22 (-0.02, 0.45) 2 

0.00 (-0.24, 0.23) 3 

0.03 (-0.20, 0.26) 4 

Cardiovascular: 

Low SDI 

0.14 (-0.77, 1.06) 0 

0.64 (-0.21, 1.49) 1 

0.24 (-0.58, 1.07) 2 

-0.27 (-1.09, 0.55) 3 

0.01 (-0.80, 0.83) 4 

Middle SDI 

0.66 (0.00, 1.34) 0 

0.49 (-0.13, 1.12) 1 

0.80 (0.20, 1.40) 2 

0.65 (0.06, 1.25) 3 

0.52 (-0.07, 1.12) 4 

High SDI 

0.83 (-0.08, 1.75) 0 

0.89 (0.04, 1.75) 1 

0.12 (-0.70, 0.95) 2 

-0.09 (-0.91, 0.73) 3 

0.04 (-0.77, 0.86) 4 

All areas 

0.52 (0.05, 1.00) 0 

0.58 (0.14, 1.03) 1 

0.43 (0.00, 0.86) 2 

0.14 (-0.28, 0.57) 3 

0.23 (-0.20, 0.65) 4 

Respiratory: 

Low SDI 

0 0.69 (-0.44, 1.82) 0 

1 0.55 (-0.50, 1.61) 1 

2 0.36 (-0.66, 1.39) 2 

3 -0.24 (-1.25, 0.78) 3 

4 -0.17 (-1.17, 0.85) 4 

Middle SDI 

0.31 (-0.50, 1.13) 0 

0.77 (0.01, 1.53) 1 

0.85 (0.12, 1.59) 2 

0.66 (-0.07, 1.39) 3 

0.69 (-0.03, 1.42) 4 

High SDI 

0.27 (-0.85, 1.40) 0 

0.72 (-0.32, 1.78) 1 

1.46 (0.45, 2.47) 2 

0.70 (-0.30, 1.71) 3 

0.48 (-0.52, 1.48) 4 

All areas 

0.39 (-0.20, 0.99) 0 

0.70 (0.15, 1.26) 1 

0.89 (0.36, 1.42) 2 

0.45 (-0.08, 0.98) 3 

0.43 (-0.10, 0.96) 4 

High SDI vs. Middle SDI 

Nonaccidental: 0.23 (-0.25, 0.72) 0-1 

Cardiovascular: 0.49 (-0.40, 1.40) 0-1 

Respiratory: 0.49 (-0.58, 1.58) 0-1 

High SDI vs. Low SDI 

Nonaccidental: 0.12 (-0.42, 0.67) 0-1 

Cardiovascular: 0.82 (-0.20, 1.86) 0-1 

Respiratory: -0.15 (-1.39, 1.10) 0-1 

Trend Test 

Nonaccidental: 0.04 (-0.15, 0.22) 0-1 

Cardiovascular: 0.27 (-0.07, 0.61) 0-1 

Respiratory: -0.04 (-0.46, 0.37) 

December 2009 E-336 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0-1 SDI = Social Deprivation Index. The 

higher the SDI the lower the SES of the 

individual. 

Reference: Yang et al. (2004, 055603) 

Period of Study: 1994-1998 

Location: Taipei, Taiwan 

Outcome: Mortality: 

Nonaccidental (<800) 

Circulatory (390-459) 

Respiratory (460-519) 

Study Design: Bi-directional casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 51.99 

Range (Min, Max): (13.71, 211.30) 

Copollutant: 

SO2

NO2

CO 

O3 

Increment: 31.43 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

Nonaccidental 

0.995 (0.971, 1.020) 0 

Respiratory 

0.986 (0.906, 1.074) 0 

Circulatory 

0.988 (0.942, 1.035) 

December 2009 E-337 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zanobetti et al. (2003, 

042812) 

Period of Study: 1990-1997 

Location: 10 European cities 

(APHEA2) 

Outcome: Mortality: 

Nonaccidental (<800) 

Circulatory (390-459) 

Respiratory (460-519) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: 

15-64 yr 

65-74 yr 

≥ 75 yr 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Athens: 42.7 (12.9) 

Budapest: 41 (9.1) 

Lodz: 53.5 (15.5) 

London: 28.8 (13.7) 

Madrid: 37.8 (17.7) 

Paris: 22.5 (11.5) 

Prague: 76.2 (45.7) 

Rome: 58.7 (17.4) 

Stockholm: 15.5 (7.9) 

Tel Aviv: 50.3 (57.5) 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cardiovascular 

0.69% (0.31, 1.08) 0-1 avg 

40-day distributed lag 

1.99% (1.44, 2.54) 

4th degree 

1.97% (1.38, 2.55) 

Unrestricted 

Respiratory 

0.74% (-0.17, 1.66) 0-1 avg 

40-day distributed lag 

4.21% (1.70, 6.79) 

4th degree 

4.20% (1.08, 7.42) 

Unrestricted 

Unrestricted distributed lags 

Cardiovascular 

1.34% (0.89, 1.79) 20 

1.72% (1.20, 2.25) 30 

1.97% (1.38, 2.55) 40 

Respiratory 

1.71% (-0.65, 4.12) 20 

2.62% (0.19, 5.11) 30 

4.20% (1.08, 7.42) 40 

40-day lags 

Nonaccidental 

15-64 

-0.25% (-0.87, 0.36) 

4th degree 

-0.01 (-0.76, 0.75) 

Unrestricted 

65-74 

0.78% (0.23, 1.33) 

4th degree 

0.74% (0.02, 1.45) 

Unrestricted 

≥ 75 

1.84% (0.92, 2.78) 

4th degree 

1.94% (1.07, 2.81) 

Unrestricted 

Cardiovascular 

65-74 

2.06% (1.05, 3.09) 

4th degree 

1.62 (0.54, 2.70) 

Unrestricted 

≥ 75 

2.35% (1.42, 3.29) 

4th degree 

2.52% (1.57, 3.48) 

Unrestricted 

Respiratory 

≥ 75 

4.57% (1.25, 7.99) 

4th degree 

4.52% (0.89, 8.28) 

Unrestricted 

December 2009 E-338 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zeka et al. (2005, 088068) 

Period of Study: Jan 1989-Dec 2000 

Location: 20 U.S. cities 

Outcome (ICD10): Mortality: 

All-cause (nonaccidental) (V01-Y98) 

Heart Disease (I01-I51) 

IHD (I20-I25) 

Myocardial infarction (I21, I22) 

Dysrhythmias (I46-I49) 

Heart failure (I50) 

Stroke (I60-I69) 

Respiratory (J00-J99) 

Pneumonia (J12-J18) 

COPD (J40-J44, J47) 

Study Design: Time-stratified casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: All ages 

Pollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Birmingham: 31.9 (18.0) μg/m3 

Boulder: 22.1 (11.3) 

Caton: 26.6 (11.5) 

Chicago: 33.7 (16.4) 

Cincinnati: 31.4 (13.9) 

Cleveland: 37.5 (18.7) 

Colorado Springs: 24.0 (13.2) 

Columbus: 28.5 (12.5) 

Denver: 28.5 (12.8) 

Detroit: 32.1 (17.7) 

Honolulu: 15.9 (6.8) 

Minneapolis: 24.7 (12.3) 

Nashville: 30.1 (12.1) 

New Haven: 25.4 (14.4) 

Pittsburgh: 30.2 (18.5) 

Provo: 33.7 (22.2) 

Seattle: 26.4 (14.7) 

Salt lake City: 35.0 (20.8) μ 

Terra Haute: 29.2 (14.6) μ 

Youngstown: 30.8 (13.9) 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Single-lag model 

All-Cause (nonaccidental) 

0.20% (0.08, 0.32) 0 

0.35% (0.21, 0.49) 1 

0.24% (0.14, 0.34) 2 

Respiratory 

0.34% (-0.07, 0.75) 0 

0.52% (0.15, 0.89) 1 

0.51% (0.16, 0.86) 2 

COPD 

-0.06% (-0.63, 0.51) 0 

0.43% (-0.14, 1.00) 1 

0.39% (-0.16, 0.94) 2 

Pneumonia 

0.50% (0.09, 1.09) 0 

0.59% (-0.12, 1.30) 1 

0.82% (0.25, 1.39) 2 

Heart disease 

0.12% (-0.06, 0.30) 0 

0.30% (0.12, 0.48) 1 

0.37% (0.17, 0.57) 2 

IHD 

0.19% (-0.03, 0.41) 0 

0.41% (0.19, 0.63) 1 

0.43% (0.10, 0.76) 2 

Myocardial Infarction 

0.36% (-0.05, 0.77) 0 

0.17% (-0.18, 0.52) 1 

0.13% (-0.22, 0.48) 2 

Heart Failure 

0.17% (-0.63, 0.97) 0 

-0.01% (-0.81, 0.79) 1 

0.78% (-0.004, 1.56) 2 

Dysrhythmias 

-0.23% (-1.41, 0.95) 0 

0.37% (-0.47, 1.21) 1 

0.33% (-0.55, 1.21) 2 

Stroke 

0.09% (-0.49, 0.60) 0 

0.41% (-0.02, 0.84) 1 

0.14% (-0.27, 0.55) 2 

Unconstrained distributed lag model 

All-cause (nonaccidental) 

0.45% (0.25, 0.65) 0-3 

Respiratory 

0.87% (0.38, 1.36) 0-3 

COPD 

0.43% (-0.35, 1.21) 0-3 

Pneumonia 

1.24% (0.46, 2.02) 0-3 

Heart Disease 

0.50% (0.25, 0.75) 0-3 

IHD 

0.65% (0.32, 0.98) 

Myocardial Infarction 

0.36% (-0.25, 0.97) 0-3 

Heart Failure 

0.60% (-0.50, 1.70) 0-3 

Dysrhythmias 

0.20% (-1.03, 1.43) 0-3 

Stroke 

0.46% (-0.13, 1.05) 0-3 

Reference: Zeka et al. (2006, 088749) 

Period of Study: Jan 1989-Dec 2000 

Location: 20 U.S. cities 

Outcome (ICD10): Mortality: 

All-cause (nonaccidental) (V01-Y98) 

Heart Disease (I01-I51) 

Myocardial infarction (I21, I22) 

Stroke (I60-I69) 

Respiratory (J00-J99) 

Study Design: Time-stratified casePollutant: PM10

Averaging Time: 24-h avg 

Mean (SD): 

Birmingham: 31.9 (18.0) μg/m3 

Boulder: 22.1 (11.3) 

Caton: 26.6 (11.5) 

Chicago: 33.7 (16.4) 

Cincinnati: 31.4 (13.9) 

Cleveland: 37.5 (18.7) 

Colorado Springs: 24.0 (13.2) 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: All-cause (nonaccidental) 

Male: 0.46% (0.28, 0.64) 1-2 avg 

Female: 0.37% (0.17, 0.57) 1-2 avg 

White: 0.40% (0.22, 0.58) 1-2 avg 

Black: 0.37% (-0.02, 0.76) 1-2 avg 

Age: 

<65: 0.25% (0.01, 0.49) 1-2 avg 

75: 0.23% (-0.06, 0.52) 1-2 avg 

December 2009 E-339 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

crossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: 

All ages 

<65 yr 

65-75 yr 

>75 yr 

Columbus: 28.5 (12.5) 

Denver: 28.5 (12.8) 

Detroit: 32.1 (17.7) 

Honolulu: 15.9 (6.8) 

Minneapolis: 24.7 (12.3) 

Nashville: 30.1 (12.1) 

New Haven: 25.4 (14.4) 

Pittsburgh: 30.2 (18.5) 

Provo: 33.7 (22.2) 

Seattle: 26.4 (14.7) 

Salt lake City: 35.0 (20.8) 

Terra Haute: 29.2 (14.6) 

Youngstown: 30.8 (13.9) 

Range (Min, Max): NR 

Copollutant (correlation): NR 

>75: 0.64% (0.44, 0.84) 1-2 avg 

Educational Attainment: 

Low (<8 yr): 

0.62% (0.29, 0.95) 1-2 avg 

Medium (8-12 yr): 

0.36% (0.12, 0.60) 1-2 avg 

High (>12 yr): 

0.27% (-0.004, 0.54) 1-2 avg 

Location of Death: 

In hospital: 0.22% (0.04, 0.40) 1-2 avg 

Out of hospital: 

0.71% (0.51, 0.91) 1-2 avg 

Season: 

Winter: 0.28% (0.04, 0.52) 1-2 avg 

Summer: 0.19% (-0.22, 0.60) 1-2 avg 

Transition (spring/fall): 

0.49% (0.25, 0.73) 1-2 avg 

Respiratory 

Male: 0.71% (0.004, 1.42) 0-3 

Female: 1.04% (0.33, 1.75) 0-3 

White: 0.88% (0.33, 1.43) 0-3 

Black: 0.71% (-0.56, 1.98) 0-3 

Age: 

<65: 0.94% (-0.31, 2.19) 0-3 

65-75: 0.87% (-0.25, 1.99) 0-3 

>75: 0.88% (0.17, 1.59) 0-3 

Educational Attainment: 

Low (<8 yr): 

0.82% (-0.32, 1.96) 0-3 

Medium (8-12 yr): 

0.88% (0.12, 1.64) 0-3 

High (>12 yr): 

0.88% (-0.04, 1.80) 0-3 

Location of Death: 

In hospital: 0.78% (0.17, 1.39) 0-3 

Out of hospital: 1.09% (0.25, 1.93) 0-3 

Season: 

Winter: -0.007% (-0.87, 0.86) 0-3 

Summer: 0.69% (-0.68, 2.06) 0-3 

Transition (spring/fall): 

1.57% (0.86, 2.28) 0-3 

Heart Disease 

Male: 0.54% (0.23, 0.85) 2 

Female: 0.46% (0.15, 0.77) 2 

White: 0.50% (0.25, 0.75) 2 

Black: 0.64% (0.13, 1.15) 2 

Age: 

<65: 0.04% (-0.45, 0.53) 2 

65-75: 0.60% (0.13, 1.07) 2 

>75: 0.65% (0.30, 1.00) 2 

Educational Attainment: 

Low (<8 yr): 

0.72% (0.23, 1.21) 2 

Medium (8-12 yr): 

0.38% (0.07, 0.69) 2 

High (>12 yr): 

0.54% (0.13, 0.95) 2 

Location of Death: 

In hospital: 0.15% (-0.14, 0.44) 2 

Out of hospital: 0.93% (0.60, 1.26) 2 

Season: 

Winter: 0.41% (-0.002, 0.82) 2 

Summer: 0.52 (0.03, 1.01) 2 

Transition (spring/fall): 

0.56% (0.13, 0.99) 2 

December 2009 E-340 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Myocardial Infarction 

Male: 0.21% (-0.40, 0.82) 0 

Female: 0.59% (0.08, 1.10) 0 

White: 0.24% (-0.27, 0.75) 0 

Black: 0.99% (0.05, 1.93) 0 

<65: 0.12% (-0.76, 1.00) 0 

65-75: 0.92% (0.21, 1.63) 0 

>75: 0.16% (-0.58, 0.90) 0 

Educational Attainment: 

Low (<8 yr): 0.33% (-0.83, 1.49) 0 

Medium (8-12 yr): 0.79% (0.28, 1.30) 0 

High (>12 yr): -0.13% (-0.82, 0.56) 0 

Location of Death: 

In hospital: 0.34% (-0.11, 0.79) 0 

Out of hospital: 0.48% (-0.23, 1.19) 0 

Season: 

Winter: 0.32% (-0.37, 1.01) 0 

Summer: 0.30% (-0.82, 1.42) 0 

Transition (spring/fall): 

0.38% -0.31, 1.07) 0 

Stroke 

Male: 0.11% (-0.58, 0.80) 1 

Female: 0.59% (-0.04, 1.22) 1 

White: 0.48% (0.01, 0.95) 1 

Black: 0.13% (-0.87, 1.13) 1 

Age: 

<65: 0.09% (-1.09, 1.27) 1 

65-75: -0.46% (-1.42, 0.50) 1 

>75: 0.80% (0.27, 1.33) 1 

Educational Attainment: 

Low (<8 yr): 0.07% (-1.44, 1.58) 1 

Medium (8-12 yr): 0.29% (-0.32, 0.90) 1 

High (>12 yr): 0.52% (-0.28, 1.32) 1 

Location of Death: 

In hospital: 0.06% (-0.49, 0.61) 1 

Out of hospital: 0.87% (0.05, 1.69) 1 

Season: 

Winter: -0.09% (-0.93, 0.75) 1 

Summer: 0.67% (-0.31, 1.65) 1 

Transition (spring/fall): 

0.51% (-0.20, 1.22) 1 

Contributing causes of disease: Allcause 

Secondary pneumonia present: 

0.67% (0.16, 1.18) 1-2 avg 

Secondary pneumonia absent: 

0.34% (0.16, 0.52) 1-2 avg 

Secondary heart failure present: 

0.42% (0.01, 0.83) 1-2 avg 

Secondary heart failure absent: 

0.37% (0.19, 0.55) 1-2 avg 

Secondary stroke present: 

0.85% (0.30, 1.40) 1-2 avg 

Secondary stroke absent: 

0.32% (0.14, 0.50) 1-2 avg 

Diabetes present: 

0.57% (0.02, 1.12) 1-2 avg 

Diabetes absent: 

0.34% (0.14, 0.54) 1-2 avg 

Respiratory 

Secondary pneumonia present: 

1.28% (-0.33, 2.89) 0-3 

Secondary pneumonia absent: 

0.78% (0.15, 1.41) 0-3 

Secondary heart failure present: 

1.48% (0.07, 2.89) 0-3 

Secondary heart failure absent: 

December 2009 E-341 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0.79% (0.26, 1.32) 0-3 

Secondary stroke present: 

1.95% (-0.11, 4.01) 0-3 

Secondary stroke absent: 

0.80% (0.29, 1.31) 0-3 

Diabetes present: 

1.96% (-0.22, 4.14) 0-3 

Diabetes absent: 

0.82% (0.31, 1.33) 0-3 

Heart Disease 

Secondary pneumonia present: 

0.66% (-0.63, 1.95) 2 

Secondary pneumonia absent: 

0.49% (0.27, 0.71) 2 

Secondary stroke present: 

0.73% (-0.05, 1.51) 2 

Secondary stroke absent: 

0.48% (0.24, 0.72) 2 

Diabetes present: 

0.34% (-0.42, 1.10) 2 

Diabetes absent: 0 

.52% (0.28, 0.76) 2 

Myocardial Infarction 

Secondary pneumonia present: 

1.54% (-1.05, 4.13) 0 

Secondary pneumonia absent: 

0.42% (0.05, 0.79) 0 

Secondary stroke present: 

0.50% (-1.38, 2.38) 0 

Secondary stroke absent: 

0.36% (-0.05, 0.77) 0 

Diabetes present: 

0.70% (-0.38, 1.78) 0 

Diabetes absent: 

0.41% (0.04, 0.78) 0 

Stroke 

Secondary pneumonia present: 

1.74% (0.35, 3.13) 1 

Secondary pneumonia absent: 

0.29% (-0.16, 0.74) 1 

Secondary heart failure present: 

1.01% (-0.77, 1.79) 1 

Secondary heart failure absent: 

0.38% (-0.05, 0.81) 1 

Diabetes present: 

1.02% (-0.53, 2.57) 1 

Diabetes absent: 

0.37% (-0.08, 0.82) 1 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-342 
Table E-17. Short-term exposure-mortality - PM10-2.5. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Burnett et al. (2004, 

086247) 

Period of Study: 1981-1999 

Location: 12 Canadian cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: 

1. Poisson, natural splines 

2. Random effects regression 

model 

Age Groups: All ages 

Pollutant: P10-2.5 

Averaging Time: 24-h avg 

Mean (SD): 11.4 

Range (Min, Max): NR 

Copollutant: 

NO2

O 3

SO2

CO 

PM10

PM2.5

Note: PM10 measurement 

calculated as the sum of PM2.5

and PM10-2.5 measurements. 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

1981-1999 

PM10-2.5: 0.31% (-0.66, 1.33) 1 

PM10-2.5+NO2: 0.65% (-0.23, 1.59) 1 

Reference: Kan et al. (2007, 091267) 

Period of Study: Mar 2004-Dec 2005 

Location: Shanghai, China 

Outcome (ICD10): Mortality: 

Total (nonaccidental) (A00-R99) 

Cardiovascular (I00-I99) 

Respiratory (J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson 

GAM, penalized splines 

Age Groups: All ages 

Pollutant: PM10-2.5

Averaging Time: 24-h avg 

Mean (SD): 56.4 (1.34) 

Range (Min, Max): (8.3, 235.0) 

Copollutant (correlation): 

PM10: r = 0.88 

PM2.5: r = 0.48 

O3: r = 0.07 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: Total: 0.12% (-0.13, 0.36) 

0-1 

Cardiovascular: 0.34% (-0.05, 0.73) 

0-1 

Respiratory: 0.40% (-0.34, 1.13) 

0-1 

Reference: Kettunen et al. (2007, 

091242) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome (ICD10): Mortality: 

Stroke (I60-I61, I63-I64) 

Study Design: Time-series 

Statistical Analyses: Poisson 

GAM, penalized thin-plate 

splines 

Age Groups: ≥ 65 yr 

Pollutant: PM10-2.5

Averaging Time: 24-h avg 

Median (SD) unit: Cold Season: 

6.7 

Warm Season: 8.4 

Range (Min, Max): 

Cold Season: (0.0, 101.4) 

Warm Season: (0.0, 42.0) 

Copollutant: O3, CO, NO2

PM10

PM2.5

UFP 

Increment: 

Cold Season: 8.3 μg/m3

Warm Season: 5.7 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cold Season: -1.04% (-6.63, 4.89) 0 

-2.49% (-7.57, 2.88) 

1. -4.93% (-9.99, 0.41) 2 

-4.33% (-9.32, 0.93) 3 

Warm Season: 7.05% (-1.88, 16.80) 0 

4.38% (-4.26, 13.81) 

1: -1.19% (-9.45, 7.84) 2 

1.42% (-6.79, 10.34) 3 

Reference: Klemm et al. (2004, 

056585) 

Period of Study: Aug 1998-Jul 2000 

Location: Fulton and DeKalb counties, 

Georgia (ARIES) 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Cancer (140-239) 

Study Design: Time-series 

Statistical Analyses: Poisson 

GLM, natural cubic splines 

Age Groups: <65 yr, ≥ 65 yr 

Pollutant: PM10-2.5

Averaging Time: 24-h avg 

Mean (SD): 9.69 (3.94) 

Range (Min, Max): (1.71, 25.17) 

Copollutant: PM2.5

O3

NO2

CO 

SO2

Acid 

EC 

OC 

SO4

Oxygenated Hydrocarbons 

Nonmethane hydrocarbons 

NO3

Increment: NR 

β (SE) 

lag: 

Quarterly Knots: 

0.00433 (0.00333) 0-1 

Monthly Knots: 

0.00617 (0.00360) 0-1 

Biweekly Knots: 

0.00516 (0.00381) 0-1 

December 2009 E-343 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005

Location: Barcelona, Spain 

Outcome: Respiratory mortality 

Study Design: Cohort 

Covariates: Temperature, 

humidity 

Statistical Analysis: 

autoregressive Poisson 

regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM10-2.5

Averaging Time: 24 h 

Mean (SD) Unit: 14.0 (9.5) 

μg/m3

Range (Min, Max): 0.1, 93.1 

Copollutant: PM2.5-1, PM1 

Increment: 10 μg/m3

Odds Ratio (95%CI) Lag 

Single Pollutant Model 

Avg L0-1: 1.000 (0.944-1.060), p = 0.991 

L1: 1.002 (0.955-1.052), p = 0.931 

L2: 1.070 (1.023-1.118), p = 0.003 

Multi-pollutant Model 

Avg L0-1: 1.002 (0.937-1.071), p = 0.958 

L1: 0.998 (0.943-1.056), p = 0.0.936 

L2: 1.033 (0.980-1.089), p = 0.226 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: 

Cardiovascular mortality 

Study Design: Cohort 

Covariates: Temperature, 

humidity 

Statistical Analysis: 

Autoregressive Poisson 

regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM10-2.5

Averaging Time: 24 h 

Mean (SD) Unit: 14.0 (9.5) 

μg/m3

Range (Min, Max): 0.1, 93.1 

Copollutant: PM2.5-1, PM1 

Increment: 10 μg/m3

Odds Ratio (95%CI) Lag 

Avg L0-1: 1.054 (1.019-1.089), p = 0.002 

L1: 1.059 (1.031-1.072), p = 0.000 

L2: 1.044 (1.017-1.072), p = 0.001 

Multi-pollutant Model 

Avg L0-1: 1.053 (1.013-1.094), p = 0.009 

L1: 1.059 (1.026-1.094), p = 0.001 

L2: 1.044 (1.012-1.078), p = 0.007 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: 

Cerebrovascular mortality 

Study Design: Cohort 

Covariates: Temperature, 

humidity 

Statistical Analysis: 

Autoregressive Poisson 

regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM10-2.5

Averaging Time: 24 h 

Mean (SD) Unit: 14.0 (9.5) 

μg/m3

Range (Min, Max): 0.1, 93.1 

Copollutant: PM2.5-1, PM1 

Increment: 10 μg/m3

Odds Ratio (95%CI) Lag 

Avg L0-1: 1.087 (1.018-1.161), p = 0.013 

L1: 1.086 (1.030-1.145), p = 0.002 

L2: 1.051 (0.997-1.108), p = 0.064 

Multi-pollutant Model 

Avg L0-1: 1.103 (1.022-1.191), p = 0.011 

L1: 1.098 (1.030-1.171), p = 0.004 

L2: 1.076 (1.010-1.146), p = 0.023 

Reference: Slaughter et al. (2005, 

073854) 

Period of Study: Jan 1995-Dec 1999

Location: Spokane, Washington

Outcome: Mortality: 

Nonaccidental (< 800)

Study Design: Time-series

Statistical Analyses: Poisson 

GLM, natural splines

Age Groups: All ages 

Pollutant: PM10-2.5

Averaging Time: 24-h avg

Mean (SD) unit: NR

Range (9th, 95th): NR

Copollutant (correlation): 

PM1: r = 0.19 

PM2.5: r = 0.31 

PM10: r = 0.94 

CO: r = 0.32 

This study does not present quantitative results for 

PM10-2.5. 

Reference: Stieb et al. (2002, 025205) 

Period of Study: 

Publication dates of studies: 1985-Dec 

2000 

Mortality series: 1958-1999 

Location: 40 cities (11 Canadian cities, 

19 U.S. cities, Santiago, Amsterdam, 

Erfurt, 7 Korean cities) 

Outcome: Mortality: All-cause 

(nonaccidental) 

Study Design: Meta-analysis 

Statistical Analyses: Random 

effects model 

Age Groups: All ages 

Pollutant: PM10-2.5

Averaging Time: NR 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant: 

Varied between studies: 

PM2.5, O3, SO2, NO2, CO 

Increment: 13.0 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Single-pollutant models: 10 studies 

PM10-2.5: 1.2% (0.5, 1.9) 

Multipollutant models: 6 studies 

PM10-2.5: 0.9% (-0.3, 2.0) 

December 2009 E-344 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Villeneuve et al. (2003, 

055051) 

Period of Study: 1986-1999 

Location: Vancouver, Canada 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (401-440) 

Respiratory (460-519) 

Cancer (140-239) 

Study Design: Time-series 

Statistical Analyses: Poisson, 

natural splines 

Age Groups: ≥ 65 

Pollutant: PM10-2.5

Averaging Time: 24-h avg 

Mean (SD): 

Daily: 6.1 

Every 6th Day 

8.3 

Range (Min, Max): 

Daily: (0.0, 72.0) 

Every 6th Day: (0.7, 35.0) 

Copollutant: 

PM2.5

PM10

SO2

CO 

NO2

O3

Increment: 11.0 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental 

1.4% (-2.5, 5.4) 0-2 avg 

1.0% (-1.9, 4.0) 0 

-1.1% (-4.0, 1.8) 1 

2.0% (-1.0, 5.1) 2 

Cardiovascular 

5.9% (-0.2, 12.4) 0-2 avg 

5.9% (1.1, 10.8) 0 

1.4% (-3.3, 6.4) 1 

2.2% (-2.0, 6.7) 2 

Respiratory 

-1.0% (-9.8, 8.8) 0-2 avg 

-1.5% (-9.4, 7.1) 0 

-1.5% (-8.4, 6.0) 1 

0.1% (-6.4, 6.9) 2 

Cancer 

4.4% (-3.6, 13.1) 0-2 avg 

3.1% (-2.9, 9.4) 0 

-1.0% (-6.9, 5.3) 1 

4.0% (-2.1, 10.4) 2 

Reference: Wilson et al. (2007, 

157149) 

Period of Study: 1995-1997 

Location: Phoenix, Arizona 

Outcome: Mortality: 

Cardiovascular 

Study Design: Time-series 

Statistical Analyses: Poisson 

GAM, nonparametric smoothing 

spline 

Age Groups: >25 

Pollutant: PM10-2.5

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) lag: 

Central Phoenix: 

2.4% (-1.2, 6.1) 0-5 ma 

Middle Phoenix: 

3.8% (0.3, 7.5) 0-5 ma 

3.4% (1.0, 5.8) 1 

3.0% (0.7, 5.4) 2 

Outer Phoenix: 

1.6% (-1.9, 5.2) 0-5 ma 

1

All units expressed in μg/m3 unless otherwise specified.

December 2009 E-345 
Table E-18. Short-term exposure-mortality - PM2.5 (including PM components/sources). 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Basu et al. (2008, 098716) 

Period of Study: May 1999-Sept 2003 

Location: 9 California counties 

Outcome (ICD10): Mortality: 

Nonaccidental (V01-Y98) 

Study Design: 

(1) Main analysis: Case-crossover 

(2) Sensitivity analysis: Time-series 

Statistical Analyses: 

(1) Main analysis: conditional logistic 

regression 

(2) Sensitivity analysis: Poisson GAM 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SE) unit: 

Contra Costa: 8.6 

Fresno: 7.6 

Kern: 11.3 

Los Angeles: 19.8 

Orange: 17.0 

Riverside: 28.4 

Sacramento: 8.8 

San Diego: 13.4 

Santa Clara: 10.8 

IQR (25th, 75th): 

Contra Costa: (5.8, 10.1) 

Fresno: (3.8, 9.8) 

Kern: (8.0, 13.5) 

Los Angeles: (14.7, 23.3) 

Orange: (11.8, 21.0) 

Riverside: (17.9, 36.1) 

Sacramento: (5.8, 10.1) 

San Diego: (10.3, 15.8) 

Santa Clara: (7.2, 13.8) 

Copollutant (correlation): 

PM10 r = 0.45 

O3 (1hr) r = 0.28 

O3 (8hr) r = 0.22 

CO r = 0.45 

NO2 r = 0.43 

The study does not provide results 

quantitatively. 

Reference: Dominici et al. (2007, 

097361) 

Period of Study: 

PM10: 1987-2000 

PM2.5: 1999-2000

Location: 100 U.S. counties 

(NMMAPS) 

Outcome: Mortality: 

All-cause (nonaccidental) 

Cardiorespiratory 

Other-cause 

Study Design: Time-series 

Statistical Analyses: 2-stage Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

1999-2000: 

All-cause: 0.29% (0.01, 0.57) 1 

Cardiorespiratory: 0.38% (-0.07, 0.82) 1

Reference: Dominici et al. (2007, 

099135) 

Period of Study: 2000-2005 

Location: 72 U.S. counties 

representing 69 communities 

Outcome: Total mortality 

Study Design: Time-series 

Statistical Analyses: 2-stage Bayesian 

hierarchical model 

Age Groups: All ages 

Pollutant: PM2.5, Nickel, speciated fine 

PM, and Vanadium 

Averaging Time: Annual avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

The study does not provide results 

quantitatively. 

Note: The study investigated whether 

county-specific short-term effects of 

PM10 on mortality are modified by longterm county-specific nickel or vanadium 

PM2.5 concentrations. 

Reference: Franklin et al. (2007, 

091257) 

Period of Study: 1997-2002 

Location: 27 U.S. communities 

Outcome: Mortality: 

All-cause (nonaccidental (<800) 

Cardiovascular (390-429) 

Respiratory (460-519) 

Stroke (430-438) 

Study Design: Time-stratified casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 15.7 μg/m3

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

All-cause (nonaccidental): 

0.67% (-0.12, 1.46) 0 

1.21% (0.29, 2.14) 

10.82% (0.02, 1.63) 0-1 

Respiratory: 

1.31% (-0.10, 2.73) 0 

1.78% (0.20, 3.36) 1 

1.67% (0.19, 3.16) 0-1 

Cardiovascular: 

0.34% (-0.61, 1.28) 0 

0.94% (-0.14, 2.02) 1. 

0.54% (-0.47, 1.54) 0-1 

Stroke: 

0.62% (-0.69, 1.94) 0 

1.03% (0.02, 2.04) 1. 

0.67% (-0.23, 1.57) 0-1 

December 2009 E-346 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Age≥ 75: 

All cause: 1.66% (0.62, 2.70) 1 

Respiratory: 1.85% (0.27, 3.44) 1 

Cardiovascular: 1.29% (0.15, 2.42) 1 

Stroke: 1.52% (0.37, 2.67) 1 

Age<75: 

All cause: 0.62% (-0.30, 1.55) 1 

Respiratory: 1.53% (-0.67, 3.74) 1 

Cardiovascular: 0.26% (-1.04, 1.56) 1 

Stroke: -0.78% (-2.32, 0.76) 1 

Male: 

All cause: 1.06% (0.07, 2.06) 1 

Respiratory: 1.90% (0.14, 3.65) 1 

Cardiovascular: 0.52% (-0.63, 1.66) 1 

Stroke: 0.79% (-0.42, 2.02) 1 

Female: 

All cause: 1.34% (0.40, 2.27) 1 

Respiratory: 1.57% (-0.22, 3.35) 1 

Cardiovascular: 1.30% (0.14, 2.46) 1 

Stroke: 0.79% (-0.51, 2.09) 1 

East: 

ll cause: 1.95% (0.50, 3.40)1 

Respiratory: 2.66% (0.33, 5.00) 1 

Cardiovascular: 1.52% (0.06, 2.98) 1 

Stroke: 1.16% (-0.40, 2.73) 1 

West: 

All cause: 0.05% (-1.80, 1.89) 1 

Respiratory: 0.67% (-2.00, 3.34) 1| 

Cardiovascular: 0.11% (-2.03, 2.24) 1| 

Stroke: 0.94% (-0.38, 2.26) 1 

PM2.5>15 μg/m

3

: 

All cause: 1.10% (-0.43, 2.64) 1 

Respiratory: 1.42% (-0.84, 3.68) 1 

Cardiovascular: 0.88% (-0.87, 2.62) 1 

Stroke: 0.91% (-0.28, 2.10) 1 

PM2.5

≤ 15 μg/m

3

: 

All cause: 1.41% (-0.49, 3.30) 1 

Respiratory: 2.46% (-0.49, 5.42) 1 

Cardiovascular: 1.09% (-1.15, 3.32) 1 

Stroke: 1.36% (-0.56, 3.27) 1 

Effect of A/C at percentile of air 

conditioning prevalence: 

25th percentile (45% prevalence of 

A/C): 

All cause: 1.50% (0.13, 2.88) 1 

Respiratory: 2.27% (0.27, 4.27) 1 

Cardiovascular: 1.04% (-0.54, 2.63) 1 

Stroke: 1.04% (-0.44, 2.53) 1 

75th percentile (80% prevalence of 

A/C): 

All cause: 0.85% (-0.64, 2.35) 1 

Respiratory: 1.04% (-1.29, 3.37) 1 

Cardiovascular: 0.81% (-0.93, 2.61) 1 

Stroke: 1.03% (-0.76, 2.83) 1 

Effect of A/C at percentile of air 

conditioning prevalence in cities with 

summer peaking PM2.5 concentrations: 

25th percentile (45% prevalence of 

A/C): 

All cause: 1.01% (-0.30, 2.32) 1 

Respiratory: 0.76% (-1.38, 2.90) 1 

Cardiovascular: 0.43% (-0.86, 1.72) 1 

Stroke: -0.18% (-2.08, 1.73) 1 

75th percentile (77% prevalence of 

A/C): 

All cause: -0.55% (-1.95, 0.85) 1 

December 2009 E-347 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Respiratory: -2.08% (-4.47, 0.31) 1 

Cardiovascular: -1.02% (-2.44, 0.41) 1 

Stroke: 0.69% (-1.19, 2.57) 1 

Reference: Franklin et al. (2008, 

097426) 

Period of Study: 2000-2005 

Location: 25 U.S. communities 

Outcome (ICD10): Mortality: 

Nonaccidental (V01-Y98) 

Respiratory (J00-J99) 

Cardiovascular (I01-I52) 

Stroke (I60-J69) 

Study Design: Time-series 

Statistical Analyses: 

1st stage: Poisson, cubic spline 

2nd stage: Random effects metaanalysis 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Range Mean (SD): 

Winter: 9.6-34.4 

Spring: 6.7-27.6 

Summer: 7.6-26.0 

Fall: 9.5-32.1 

Range (Min, Max): NR 

Copollutant: 

Al, As, Br, Cr, EC, Fe, K, Mn, Na+, Ni, 

NO3

–

, NH4, OC, Pb, Si, SO4

2–, V, Zn 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental: 0.74% (0.41, 1.07) 0-1 

Cardiovascular: 0.47% (0.02, 0.92) 0-1 

Respiratory: 1.01% (-0.03, 2.05) 1-2 

Stroke: 0.68% (-0.21, 1.57) 0-1 

Winter: 0.15% (-0.42, 0.72) 0-1 

Spring: 1.88% (1.29, 2.48) 0-1 

Summer: 0.99% (0.35, 1.68) 0-1 

Fall: 0.19% (-0.25, 0.64) 0-1 

West: 0.51% (0.10, 0.92) 0-1 

East & Central: 

0.92% (0.44, 1.39) 0-1 

% Increase per 10 μg/m3

 increase in 

PM2.5 for an IQR increase in species to 

PM2.5 mass proportion 

Univariate analysis 

Al: 0.58% 

As: 0.55% 

Br: 0.38 

Cr: 0.33% 

EC: 0.06% 

Fe: 0.12% 

K: 0.41% 

Mn: 0.14% 

Na+: 0.20% 

Ni: 0.37% 

NO3-: -0.49% 

NH4: 0.04% 

OC: -0.02% 

Pb: 0.17% 

Si: 0.41% 

SO4

2–: 0.51% 

V: 0.30% 

Zn: 0.23% 

Multivariate (1) 

Al: 0.79% 

Ni: 0.34% 

SO4

2–: 0.75% 

Multivariate (2) 

Al: 0.61% 

Ni: 0.35% 

As: 0.58% 

Reference: Holloman et al. (2004, 

087375) 

Period of Study: 1999-2001 

Location: 7 North Carolina counties 

Outcome (ICD10): Mortality: 

Cardiovascular (I00-I99) 

Study Design: Time-series 

Statistical Analyses: 3-stage Bayesian 

hierarchical model 

Age Groups: >16 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

2.5% (-3.9 to 9.6) 

0 

4.0% (-3.3 to 12.2) 

1 

11.4% (2.8-19.8) 

2 

-1.1% (-7.5 to 5.2) 

3 

December 2009 E-348 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hopke et al. (2006, 

088390) 

Period of Study: Washington, DC: Aug 

1988-Dec 1997. Phoenix, Arizona: Mar 

1995-Jun 1998 

Location: Washington, DC and 

surrounding counties 

Phoenix, Arizona 

Outcome: Mortality: 

Total (nonaccidental) 

Cardiovascular 

Cardiovascular-Respiratory 

Study Design: Source-apportionment 

Statistical Analyses: Receptor 

modeling 

Age Groups: All ages 

Pollutant: 

Source-apportioned PM2.5: 

Washington, DC: Soil 

Traffic 

Secondary Sulfate 

Nitrate 

Residual Oil 

Wood Smoke 

Sea Salt 

Incinerator 

Primary Coal 

Phoenix, Arizona: Crustal 

Traffic 

Vegetation and Wood Burning 

Secondary Sulfate 

Metals 

Sea Salt 

Primary Coal 

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

The study does not present quantitative 

results. 

Reference: Ito et al. (2006, 088391) 

Period of Study: Aug 1988-Dec 1997 

Location: Washington, DC and 

surrounding counties 

Outcome: Mortality: 

Total (nonaccidental) 

Cardiovascular 

Cardiovascular-Respiratory 

Study Design: Time-series 

Source-apportionment 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

Pollutant: 

Source-apportioned PM2.5: 

Soil 

Traffic 

Secondary Sulfate 

Nitrate 

Residual Oil 

Wood Smoke 

Sea Salt 

Incinerator 

Primary Coal 

Averaging Time: 24-h avg 

Mean (SD): 17.8 (8.7) 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 

PM2.5 = 28.7 μg/m3 

PM2.5 Sources 5-95th = Not reported 

% Increase (Lower CI, Upper CI) lag: 

Secondary sulfate (variance-weighted 

mean percent excess mortality) 

6.7% (1.7, 11.7) 3 

Primary coal-related PM2.5 (mean 

percent excess mortality) 

5.0% (1.0, 9.1) 3 

Residual oil (mean percent excess 

mortality) 

2.7% (-1.1, 6.5) 2 

Traffic-related PM2.5 (mean percent 

excess mortality) 

2.6% (-1.6, 6.9) NR 

Soil-related PM2.5 (mean percent 

excess mortality) 

2.1% (-0.8, 4.9) NR 

PM2.5 Sensitivity analysis: 

2 df/yr: 7.9% (3.3, 12.6) 3 

4 df/yr: 8.3% (3.7, 13.1) 3 

8 df/yr: 8.3% (3.7, 13.2) 3 

16 df/yr: 8.1% (3.1, 13.2) 3 

Reference: Kan et al. (2007, 091267) 

Period of Study: Mar 2004-Dec 2005 

Location: Shanghai, China 

Outcome (ICD10): Mortality: 

Total (nonaccidental) (A00-R99) 

Cardiovascular (I00-I99) 

Respiratory (J00-J98) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

penalized splines 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 52.3 (1.57) 

Range (Min, Max): (2.0, 330.3) 

Copollutant (correlation): 

PM10: r = 0.84 

PM10-2.5: r = 0.48 

O3: r = 0.31 

Increment: 10 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

Total: 0.36% (0.11, 0.61) 0-1 

Cardiovascular: 0.41% (0.01, 0.82) 0-1 

Respiratory: 0.95% (0.16, 1.73) 0-1 

December 2009 E-349 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kettunen et al. (2007, 

091242) 

Period of Study: 1998-2004 

Location: Helsinki, Finland 

Outcome (ICD10): Mortality: 

Stroke (I60-I61, I63-I64) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

penalized thin-plate splines 

Age Groups: ≥ 65 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Median (SD) unit: 

Cold Season: 8.2 

Warm Season: 7.8 

Range (Min, Max): 

Cold Season: (1.1, 69.5) 

Warm Season: (1.1, 41.5) 

Copollutant: 

O3

CO 

NO2

PM10

PM10-2.5

UFP 

Increment: 

Cold Season: 6.7 μg/m3 

Warm Season: 5.7 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Cold Season 

-0.19% (-3.77, 3.51) 0 

-0.17% (-3.73, 3.52) 1 

0.59% (-2.95, 4.26) 2 

0.46% (-3.10, 4.15) 3 

Warm Season 

6.86% (0.37, 13.78) 0 

7.40% (1.33, 13.84) 1 

4.01% (-1.79, 10.14) 2 

-1.72% (-7.38, 4.29) 3 

Reference: Klemm et al. (2004, 

056585) 

Period of Study: Aug 1998-Jul 2000 

Location: Fulton and DeKalb counties, 

Georgia (ARIES) 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Cancer (140-239) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural cubic splines 

Age Groups: <65 

≥ 65 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 19.62 (8.32) 

Range (Min, Max): (5.29, 48.01) 

Copollutant: 

PM10-2.5

O 3

NO2

CO 

SO2

Acid 

EC 

OC 

SO4

Oxygenated Hydrocarbons 

Nonmethane hydrocarbons 

NO3

Increment: NR 

β (SE) lag: 

Quarterly Knots: 

PM2.5: 0.00398 (0.00161) 

0-1 

Monthly Knots: 

PM2.5: 0.00544 (0.00184) 

0-1 

Biweekly Knots: 

PM2.5: 0.00369 (0.00201) 

0-1 

Reference: Lippmann et al. (2006, 

091165) 

Period of Study: 2000-2003 

Location: 60 U.S. cities (NMMAPS) 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM 

Age Groups: All ages 

Pollutant: Speciated Fine PM: 

Al, Ar, Cr, Cu, EC, Fe, Mn, Ni, Nitrate, 

OC, Pb, Se, Si, Sulfate, V, Zn 

Averaging Time: Annual avg 

Mean (SD): R 

Range (Min, Max): NR 

The study does not present quantitative 

results. 

Reference: Mar et al. (2005, 087566) 

Period of Study: 1995-1997 

Location: Phoenix, Arizona 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-448) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM 

Age Groups: ≥ 65 

Pollutant: 

Source-apportioned PM2.5: 

Soil 

Traffic 

Secondary Sulfate 

Nitrate 

Residual Oil 

Wood Smoke 

Sea Salt 

Incinerator 

Primary Coal 

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Increment: PM2.5 Sources 5-95th = NR 

% Increase (median percent excess 

risk) lag: 

Secondary sulfate: 16.0% 0 

Traffic: 13.2% 1 

Copper (Cu) smelter: 12.0% 0 

Sea salt: 10.2% 5 

Biomass/wood combustion: 8.6% 3 

December 2009 E-350 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ostro et al. (2006, 087991) 

Period of Study: Jan 1999-Dec 2002 

Location: 9 California counties 

(CALFINE) 

Outcome (ICD10): Mortality: 

Total mortality (respiratory, 

cardiovascular, ischemic heart disease, 

diabetes) 

Respiratory (J00-J98) 

Cardiovascular (I00-I99) 

Ischemic heart disease (I20-I25) 

Diabetes (E10-E14) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

splines and penalized splines 

Age Groups: All ages 

>65 yr 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 

Contra Costa: 14 

Fresno: 23 

Kern: 22 

Los Angeles: 21 

Orange: 21 

Riverside: 29 

Sacramento: 14 

Santa Clara: 15 

San Diego: 16 

Range (Min, Max): 

Contra Costa: (1, 77) 

Fresno: (1, 160) 

Kern: (1, 155) 

Los Angeles: (4, 85) 

Orange: (4, 114) 

Riverside: (2, 120) 

Sacramento: (1, 108) 

Santa Clara: (2, 74) 

San Diego: (0, 66) 

Copollutant (correlation): 

NO2 r = 0.56 

CO r = 0.60 

O3 (1h) r = -0.14 

O3 (8h) r = -0.22 

Increment: 10 μg/m3 

% Increase (Lower CI, Upper CI) lag: 

Penalized splines 

All ages: 

All-cause: 

0.2% (-0.2, 0.7) 2 

0.6% (0.2, 1.0) 0-1 

Cardiovascular: 

0.3% (-0.1, 0.7) 2 

0.6% (0.0, 1.1) 0-1 

Respiratory: 

1.3% (0.1, 2.6) 2 

2.2% (0.6, 3.9) 0-1 

>65: 

All-cause: 

0.2% (-0.2, 0.7) 2 

0.7% (0.2, 1.1) 0-1 

Ischemic heart disease: 

0.3% (-0.5, 1.0) 0-1 

Males: 0.5% (-0.2, 1.2) 0-1 

Females: 0.8% (0.3, 1.3) 0-1 

Whites: 0.8% (0.2, 1.3) 0-1 

Blacks: 0.1% (-0.9, 1.2) 0-1 

Hispanics: 0.8% (-0.1, 1.6) 0-1 

In hospital: 0.6% (-0.1, 1.3) 0-1 

Out of hospital: 0.6% (0.1, 1.1) 0-1 

High school graduates: 

0.4% (0.0, 0.8) 0-1 

Non-high school graduates: 

0.9% (-0.1, 1.9) 0-1 

Natural splines 

All cause 

4 df: 0.5% (-0.1, 1.1) 0-1 

8 df: 0.4% (-0.1, 0.9) 0-1 

12 df: 0.3% (-0.1, 0.7) 0-1 

Cardiovascular 

4 df: 0.4% (-0.2, 0.9) 0-1 

8 df: 0.1% (-0.5, 0.6) 0-1 

12 df: 0.0% (-0.6, 0.6) 0-1 

Respiratory 

4 df: 2.1% (0.2, 4.1) 0-1 

8 df: 1.6% (-0.5, 3.6) 0-1 

12 df: 1.3% (-0.3, 2.9) 0-1 

>65 

All cause 

4 df: 0.7% (0.0, 1.3) 0-1 

8 df: 0.4% (-0.1, 0.9) 0-1 

12 df: 0.3% (-0.1, 0.8) 0-1 

December 2009 E-351 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ostro et al. (2007, 091354) 

Period of Study: PM2.5 speciation 

analysis: Jan 2000-Dec 2003. PM2.5

analysis: Jan 1999-Dec 2003 

Location: 6 California counties 

(2000-2003). 9 California counties 

(1999-2003) (CALFINE) 

Outcome (ICD10): Mortality: 

Total (nonaccidental) mortality 

Respiratory (J00-J98) 

Cardiovascular (I00-I99) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

splines 

Age Groups: >65 

Pollutant: PM2.5 

Averaging Time: 24-h avg 

Mean (SD): 

2000-2003: 19.28 

1999-2003: 18.6 

Range (Min, Max): NR 

Copollutant (correlation): 

EC: r = 0.53 

OC: r = 0.62 

NO3: r = 0.65 

SO4: r = 0.32 

Al: r = 0.02 

Br: r = 0.54 

Ca: r = 0.23 

Cl: r = 0.15 

Cu: r = 0.23 

Fe: r = 0.38 

K: r = 0.52 

Mn: r = 0.21 

Ni: r = 0.11 

Pb: r = 0.27 

S: r = 0.35 

Si: r = 0.16 

Ti: r = 0.24 

V: r = 0.20 

Zn: r = 0.51 

Increment: 14.6 μg/m3

% Increase (Lower CI, Upper CI) 

lag: 

Cardiovascular 

1.6% (0.0, 3.1) 

3 

Notes: The study does not present all 

estimates quantitatively. 

Reference: Ostro et al. (2008, 097971) 

Period of Study: Jan 2000-Dec 2003 

Location: 6 California counties 

Outcome (ICD10): Mortality: 

Cardiovascular (I00-I99) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

cubic splines and natural splines 

Age Groups: 

Pollutant: PM2.5, EC, OC, NO3, SO4, 

Ca, Cl, Cu, Fe, K, S, Si, Ti, Zn 

Averaging Time: 24-h avg 

Mean (SD): 

PM2.5: 19.28 

EC: 0.966 

OC: 7.129 

NO3: 5.415 

SO4: 1.908 

Ca: 0.080 

Cl: 0.094 

Cu: 0.007 

Fe: 0.124 

K: 0.117 

S: 0.648 

Si: 0.168 

Ti: 0.009 

Zn: 0.012 

Range (95th): PM2.5: 46.91 

EC: 2.57 

OC: 15.91 

NO3: 17.46 

SO4: 5.18 

Ca: 0.20 

Cl: 0.41 

Cu: 0.02 

Fe: 0.34 

K: 0.26 

S: 1.70 

Si: 0.43 

Ti: 0.02 

Zn: 0.04 

The study does not present quantitative 

results. 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: Respiratory mortality 

Study Design: Cohort 

Covariates: Temperature, humidity 

Statistical Analysis: Autoregressive 

Poisson regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM2.5-1

Averaging Time: 24 h 

Mean (SD) Unit: 5.5 (3.8) μg/m3

Range (Min, Max): 0.6, 45.5 

Copollutant: PM10-2.5, PM1

Increment: 10 μg/m3

Odds Ratio (95%CI) lag 

Avg L0-1: 0.998 (0.849-1.174), 

p = 0.981 

L1: 1.014 (0.886-1.161), p = 0.838 

L2: 1.295 (1.141-1.470), p = 0.000 

Multi-pollutant Model 

Avg L0-1: 0.987 (0.806-1.208), 

p = 0.898 

L1: 1.022 (0.859-1.214), p = 0. 

L2: 1.206 (1.028-1.416), p = 0.022 

December 2009 E-352 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: Cardiovascular mortality 

Study Design: Cohort 

Covariates: Temperature, humidity 

Statistical Analysis: Autoregressive 

Poisson regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM2.5-1

Averaging Time: 24 h 

Mean (SD) Unit: 5.5 (3.8) μg/m3

Range (Min, Max): 0.6, 45.5 

Copollutant: PM10-2.5, PM1

Increment: 10 μg/m3

Odds Ratio (95%CI) lag 

Avg L0-1: 1.100 (1.002-1.207), 

p = 0.046 

L1: 1.112 (1.031-1.200), p = 0.006 

L2: 1.078 (0.999-1.163), p = 0.052 

Multi-pollutant Model 

Avg L0-1: 0.994 (0.885-1.116), 

p = 0.920 

L1: 0.984 (0.892-1.086), p = 0.754 

L2: 0.981 (0.891-1.079), p = 0.688 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: Cerebrovascular mortality 

Study Design: Cohort 

Covariates: Temperature, humidity 

Statistical Analysis: Autoregressive 

Poisson regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM2.5-1

Averaging Time: 24 h 

Mean (SD) Unit: 5.5 (3.8) μg/m3

Range (Min, Max): 0.6, 45.5 

Copollutant: PM10-2.5, PM1

Increment: 10 μg/m3

Odds Ratio (95%CI) lag 

Avg L0-1: 1.083 (0.897-1.307), 

p = 0.406 

L1: 1.121 (0.964-1.303), p = 0.140 

L2: 0.984 (0.841-1.152), p = 0.839 

Multi-pollutant Model 

Avg L0-1: 0.899 (0.712-1.135), 

p = 0.371 

L1: 0.905 (0.743-1.102), p = 0.321 

L2: 0.868 (0.711-1.060), p = 0.165 

Reference: Rainham et al. (2005, 

088676) 

Period of Study: 1981-1999 

Location: Toronto, Canada 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiorespiratory (390-459 

480-519) 

Other-causes 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 

All yr: 17.0 (8.7) 

Winters (Dec-Feb): 17.2 (6.8) 

Summers (Jun-Aug): 18.8 (10.2) 

Range (Min, Max): NR 

Copollutant: 

CO 

NO2

SO2

O3

Increment: NR 

% Increase (Lower CI, Upper CI) lag: 

Winter and Winter Synoptic Events 

Winter 

Total: 0.998% (0.997, 1.000) 2 

Cardiorespiratory: 

0.998 (0.996, 1.000) 2 

Other: 0.998% (0.996, 1.000) 2 

Dry Moderate 

Total: 1.001% (0.996, 1.007) 1 

Cardiorespiratory: 

1.005 (0.998, 1.011) 1 

Other: 0.997% (0.989, 1.006) 0 

Dry Polar 

Total: 0.998% (0.995, 1.001) 2 

Cardiorespiratory: 

0.995 (0.991, 0.999) 2 

Other: 1.002% (0.998, 1.005) 1 

Moist Moderate 

Total: 0.998% (0.993, 1.002) 2 

Cardiorespiratory: 

1.003 (0.995, 1.010) 1 

Other: 0.997% (0.991, 1.004) 1 

Moist Polar 

Total: 1.001% (0.998, 1.005) 1 

Cardiorespiratory: 

1.002 (0.997, 1.007) 2 

Other: 1.003% (0.999, 1.007) 0 

Moist Tropical 

Total: 1.007% (0.965, 1.203) 0 

Cardiorespiratory: 

1.123 (1.031, 1.224) 2 

Other: 1.248% (1.123, 1.387) 0 

Transition 

Total: 1.003% (0.996, 1.009) 1 

Cardiorespiratory: 

0.996 (0.987, 1.004) 0 

Other: 0.997% (0.990, 1.004) 0 

Summer and summer Synoptic Events 

Summer 

Total: 1.000% (1.000, 1.001) 0 

Cardiorespiratory: 

1.001 (1.000, 1.002) 0 

December 2009 E-353 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Other: 1.001% (1.000, 1.002) 0 

Dry Moderate 

Total: 1.001% (0.999, 1.002) 2 

Cardiorespiratory: 

1.002 (0.999, 1.004) 2 

Other: 0.999% (0.997, 1.002) 0 

Dry Polar 

Total: 1.002% (0.999, 1.005) 2 

Cardiorespiratory: 

0.996 (0.991, 1.000) 0 

Other: 1.003% (0.999, 1.007) 2 

Dry Tropical 

Total: 1.016% (1.006, 1.027) 0 

Cardiorespiratory: 

1.017 (1.005, 1.030) 2 

Other: 1.017% (1.003, 1.031) 0 

Moist Moderate 

Total: 1.002% (1.000, 1.004) 2 

Cardiorespiratory: 

1.003 (0.999, 1.006) 2 

Other: 1.004% (1.001, 1.006) 0 

Moist Polar 

Total: 1.005% (0.998, 1.011) 1 

Cardiorespiratory: 

1.008 (0.997, 1.018) 0 

Other: 1.003% (0.995, 1.011) 1 

Moist Tropical 

Total: 0.999% (0.997, 1.001) 2 

Cardiorespiratory: 

0.996 (0.993, 1.000) 2 

Other: 0.998% (0.995, 1.001) 1 

Transition 

Total: 1.005% (0.996, 1.014) 1 

Cardiorespiratory: 

1.007 (0.994, 1.020) 1 

Other: 1.002% (0.996, 1.008) 2 

December 2009 E-354 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rosenthal et al. (2008, 

156925) 

Period of Study: Jul 2002-Jul 2006 

Location: Indianapolis, Indiana 

Outcome: Non-Dead on Arrival (DOA) 

Out-of-Hospital Cardiac Arrests (OHCA)

Witnessed non-DOA OHCA 

Study Design: Case-crossover 

Statistical Analyses: Time-stratified 

conditional logistic regression 

Age Groups: All ages 

Study Population: Non-DOA OHCA: 

1,374 

Witnessed non-DOA OHCA: 511 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Hourly 

Mean (SD): 

NR 

IQR (25th, 75th): 

All non-DOA 

All heart rhythms: (9.4, 19.5) 

OHCA: (9.6, 19.5) 

Referents: (9.3, 19.5) 

Asystole: (9.2, 19.4) 

OHCA: (9.2, 19.7) 

Asystole: (9.2, 19.2) 

Witnessed non-DOA hourly 

All heart rhythms: (8.8, 20.7) 

OHCA: (8.8, 21.9) 

Referents: (8.8, 20.4) 

Asystole: (8.5, 19.8) 

OHCA: (9.4, 21.3) 

Referents: (8.3, 19.1) 

Copollutant (correlation): NR 

Increment: 10 μg/m3

Hazard Ratio (Lower CI, Upper CI) 

lag: 

Out-of-Hospital non-DOA Cardiac 

Arrests 

All 

1.02 (0.94, 1.11) 0 

1.00 (0.92, 1.08) 1 

0.98 (0.90, 1.06) 2 

1.00 (0.92, 1.08) 3 

1.02 (0.92, 1.12) 0-1 avg 

1.01 (0.91, 1.12) 0-2 avg 

1.02 (0.91, 1.14) 0-3 avg 

Asystole 

1.03 (0.91, 1.17) 0 

1.00 (0.89, 1.13) 1 

1.01 (0.90, 1.13) 2 

0.98 (0.87, 1.10) 3 

1.03 (0.90, 1.18) 0-1 avg 

1.05 (0.90, 1.22) 0-2 avg 

1.04 (0.88, 1.22) 0-3 avg 

Vfib 

1.08 (0.92, 1.28) 0 

1.02 (0.87, 1.21) 1 

0.96 (0.80, 1.14) 2 

1.10 (0.93, 1.31) 3 

1.06 (0.88, 1.28) 0-1 avg 

1.01 (0.82, 1.25) 0-2 avg 

1.05 (0.83, 1.32) 0-3 avg 

PEA 

0.92 (0.77, 1.08) 0 

0.98 (0.83, 1.15) 1 

0.96 (0.82, 1.14) 2 

0.95 (0.82, 1.10) 3 

0.96 (0.80, 1.17) 0-1 avg 

0.98 (0.80, 1.21) 0-2 avg 

0.98 (0.78, 1.21) 0-3 avg 

Witnessed Out-of-Hospital non-DOA 

Cardiac Arrests (lag represents h in 

which or h before OHCA occurred) 

All: 1.12 (1.01, 1.25) 0 

White: 1.18 (1.03, 1.35) 0 

60-75: 1.25 (1.05, 1.49) 0 

Asystole: 1.22 (1.01, 1.59) 0 

Reference: Schwartz et al. (2002, 

025312) 

Period of Study: 1979-Late 1980’s 

Location: 6 U.S. cities 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Study Design: Time-series 

Statistical Analyses: Hierarchical 

modeling: 

1. Poisson GAM, LOESS 

2. Multivariate modeling 

Age Groups: All ages 

Pollutant: PM2.5, PM2.5 sources (Traffic, 

Coal, Residual Oil) 

Averaging Time: 24-h avg 

Mean (SD): 

PM2.5 Range: (Madison: 11.3 to 

Steubenville: 30.5) 

Traffic Range: (Steubenville: 1.5 to 

Boston: 4.8) 

Coal Range: (Madison: 4.9 to 

Steubenville: 19.2) 

Residual Oil Range: (Boston: 0.5 to 

Steubenville: 0.9) 

Range (Min, Max): NR 

The study does not present quantitative 

results. 

December 2009 E-355 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Simpson et al. (2005, 

087438) 

Period of Study: Jan 1996-Dec 1999 

Location: 4 Australian cities 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (390-459) 

Respiratory (460-519) 

Study Design: Time-series 

meta-analysis 

Statistical Analyses: Poisson GAM, 

natural splines 

Poisson GLM, natural splines 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 

Brisbane: PM2.5: 7.50 

Sydney: PM2.5: 9.00 

Melbourne: PM2.5: 9.30 

Perth: PM2.5: 9.0 μg/m3 

Range (Min, Max): 

Brisbane: PM2.5: (1.9, 19.7) 

Sydney: PM2.5: (2.4, 35.3) 

Melbourne: PM2.5: (2.7, 35.1) 

Perth: PM2.5: (2.8, 37.3) 

Copollutant: CO, NO2

Increment: 10 μg/m3 

% Increase (Lower CI, Upper CI) lag: 

PM2.5

0.9% (-0.7, 2.5) 

Reference: Slaughter et al. (2005, 

073854) 

Period of Study: Jan 1995-Dec 1999 

Location: Spokane, Washington 

Outcome: Mortality: 

Nonaccidental (<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (9th, 95th): PM2.5: (4.2, 20.2) 

Copollutant (correlation): 

PM2.5: r = 0.95 

PM10: r = 0.62 

PM10-2.5: r = 0.31 

CO: r = 0.62 

Increment: 

PM2.5: 10 μg/m3 

PM10: 25 μg/m3

Relative Risk (Lower CI, Upper CI) 

lag: 

PM2.5

(0.97, 1.04) 1 

0.99 (0.96, 1.03) 2 

1.00 (0.97, 1.03) 3 

Reference: Stieb et al. (2002, 025205) 

Period of Study: Publication dates of 

studies: 1985-Dec 2000 Mortality 

series: 1958-1999 

Location: 40 cities (11 Canadian cities, 

19 U.S. cities, Santiago, Amsterdam, 

Erfurt, 7 Korean cities) 

Outcome: Mortality: 

All-cause (nonaccidental) 

Study Design: Meta-analysis 

Statistical Analyses: Random effects 

model 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: NR 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant: Varied between studies: 

O3

SO2

NO2

CO 

Increment: PM2.5: 18.3 μg/m3 

% Increase (Lower CI, Upper CI) lag: 

Single-pollutant models 

18 studies 

PM2.5: 2.0% (1.2, 2.7) 

Multipollutant models 

8 studies 

PM2.5: 1.3% (0.6, 1.9) 

Reference: Sullivan et al. (2003, 

043156) 

Period of Study: 1985-1994 

Location: Western Washington 

Outcome: Out-of-hospital cardiac 

arrest 

Study Design: Case-crossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: 19-79 

Study Population: Out-of-hospital 

cardiac arrests: 1,206 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Median (SD) unit: 

PM10

Lag 0: 28.05 

Lag 1: 27.97 

Lag 2: 28.40 

Range (Min, Max): PM10: (7.38, 89.83) 

Copollutant (correlation): SO2, CO 

Notes: Study used nephelometry to 

measure particles and equated the 

measurements to PM2.5 concentrations. 

Increment: 

PM10: 16.51 μg/m3 

PM2.5: 13.8 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

Overall 

PM10

1.05 (0.87, 1.27) 0 

0.91 (0.75, 1.11) 1 

1.03 (0.82, 1.28) 2 

PM2.5

0.94 (0.88, 1.01) 0 

0.94 (0.88, 1.02) 1 

1.00 (0.93, 1.08) 2 

PM2.5: Stratified by subject 

characteristics 

≤ 55 

0.95 (0.76, 1.18) 0 

0.89 (0.71, 1.12) 1 

0.95 (0.75, 1.20) 2 

>55 

0.94 (0.88, 1.02) 0 

0.95, (0.88, 1.03) 1 

1.01 (0.93, 1.10) 2 

Male 

0.95 (0.87, 1.03) 0 

0.96 (0.88, 1.04) 1 

1.01 (0.93, 1.10) 2 

Female 

0.93 (0.82, 1.06) 0 

0.92 (0.80, 1.07) 1 

0.98 (0.83, 1.15) 2 

White 

December 2009 E-356 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0.93 (0.86, 1.01) 0 

0.95 (0.88, 1.03) 1 

1.03 (0.95, 1.12) 2 

Non-White 

1.09 (0.88, 1.36) 0 

0.96 (0.75, 1.22) 1 

0.88 (0.68, 1.14) 2 

Current Smoker 

1.05 (0.92, 1.19) 0 

0.98 (0.86, 1.12) 1 

1.06 (0.92, 1.22) 2 

Nonsmoker 

0.93 (0.85, 1.01) 0 

0.93 (0.85, 1.02) 1 

0.97 (0.89, 1.07) 2 

Drinker 

1.13 (0.92, 1.39) 0 

1.15 (0.94, 1.41) 1 

1.16 (0.92, 1.45) 2 

Nondrinker 

0.94 (0.86, 1.03) 0 

0.93 (0.85, 1.02) 1 

1.00 (0.92, 1.10) 2 

Activity Level-Unrestricted 

0.96 (0.89, 1.03) 0 

0.96 (0.89, 1.04) 1 

1.01 (0.93, 1.10) 2 

Activity Level-Limited 

0.82 (0.56, 1.20) 0 

0.70 (0.45, 1.09) 1 

0.97 (0.65, 1.43) 2 

PM2.5: Stratified by disease state 

Heart disease 

0.95 (0.87, 1.04) 0 

0.97 (0.89, 1.07) 1 

1.06 (0.96, 1.16) 2 

Ischemic Heart Disease 

0.91 (0.80, 1.04) 0 

0.97 (0.84, 1.11) 1 

1.09 (0.95, 1.26) 2 

Active Angina 

0.98 (0.81, 1.20) 0 

1.07 (0.88, 1.31) 1 

1.08 (0.89, 1.32) 2 

Congestive Heart Failure 

0.91 (0.80, 1.03) 0 

0.99 (0.87, 1.13) 1 

1.11 (0.97, 1.26) 2 

Supraventricular tachycardia 

1.41 (0.97, 2.04) 0 

1.55 (1.07, 2.25) 1 

1.23 (0.84, 1.82) 2 

Bradycardia 

0.97 (0.64, 1.46) 0 

1.29 (0.85, 1.96) 1 

1.30 (0.84, 2.01) 2 

Asthma 

(0.80, 1.27) 0 

0.92 (0.71, 1.19) 1 

0.93 (0.71, 1.22) 2 

COPD 

1.00 (0.86, 1.17) 0 

1.04 (0.88, 1.23) 1 

1.08 (0.92, 1.28) 2 

PM2.5: Persons with prior recognized 

heart disease stratified by smoking 

status 

All heart disease 

Current smoker 

1.08 (0.92, 1.26) 0 

1.06 (0.89, 1.26) 1 

1.29 (1.06, 1.55) 2 

Nonsmoker 

0.91 (0.82, 1.02) 0 

0.94 (0.84, 1.05) 1 

0.99 (0.88, 1.11) 2 

Ischemic Heart Disease 

December 2009 E-357 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Current smoker 

1.06 (0.84, 1.34) 0 

0.99 (0.75, 1.30) 1 

1.39 (1.04, 1.86) 2 

Nonsmoker 

0.86 (0.73, 1.02) 0 

0.93 (0.78, 1.11) 1 

0.99 (0.83, 1.18) 2 

Active Angina 

Current smoker 

1.28 (0.88, 1.86) 0 

1.26 (0.79, 2.01) 1 

1.57 (0.99, 2.48) 2 

Nonsmoker 

0.87 (0.68, 1.12) 0 

0.93 (0.72, 1.21) 1 

0.91 (0.70, 1.17) 2 

Congestive Heart Failure 

Current smoker 

1.00 (0.79, 1.28) 0 

1.03 (0.78, 1.35) 1 

1.46 (1.10, 1.96) 2 

Nonsmoker 

0.88 (0.76, 1.03) 0 

0.96 (0.82, 1.12) 1 

0.99 (0.84, 1.17) 2 

Supraventricular tachycardia 

Current smoker 

12.80 (1.05, 156.57) 0 

2.56 (0.82, 7.99) 1 

1.15 (0.46, 2.86) 2 

Nonsmoker 

1.19 (0.74, 1.90) 0 

1.35 (0.87, 2.10) 1 

1.15 (0.73, 1.82) 2 

Bradycardia 

Nonsmoker 

0.84 (0.14, 4.95) 0 

0.42 (0.03, 5.34) 1 

0.51 (0.05, 5.79) 2 

Nonsmoker 

0.99 (0.63, 1.55) 0 

1.42 (0.90, 2.24) 1 

1.39 (0.88, 2.20) 2 

Reference: Thurston et al. (2005, 

097949) 

Period of Study: Washington, DC: Aug 

1988-Dec 1997. Phoenix, Arizona: 

1995-1997 

Location: Washington, DC and 

surrounding counties 

Phoenix, Arizona 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardiovascular (390-448) 

Study Design: Time-series 

Source-apportionment 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: Washington, DC: All ages

Phoenix, Arizona: ≥ 65 

Pollutant: 

PM2.5, and source apportioned PM2.5: 

Crustal 

Traffic 

Secondary SO4

Secondary NO3

Wood 

Oil 

Salt 

Incinerator 

Averaging Time: 24-h avg 

Median (SD) unit: NR 

Range (Min, Max): NR 

Copollutant: PM2.5 species (Na, Mg, Al, 

Si, P, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, 

Co, Ni, Cu, Zn, Ga, Ge, As, Se, Br, Rb, 

Sr, Y, Zr, Mo, Rh, Pd, Ag, Cd, Sn, Sb, 

Te, I, Cs, Ba, La, W, Au, Hg, Pb, OC, 

EC) 

Increment: 10 μg/m3

% Increase: 

Total (nonaccidental): 

Secondary sulfate: 

Phoenix: 5.2% 

Washington, DC: 3.8% 

Motor vehicles: 

Phoenix: 0.9% 

Washington, DC: 4.2% 

December 2009 E-358 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Villeneuve et al. (2003, 

055051) 

Period of Study: 1986-1999 

Location: Vancouver, Canada 

Outcome: Mortality: 

Nonaccidental (<800) 

Cardiovascular (401-440) 

Respiratory (460-519) 

Cancer (140-239) 

Study Design: Time-series 

Statistical Analyses: Poisson, natural 

splines 

Age Groups: ≥ 65 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): 

Daily 

PM2.5: 7.9 

Every 6th Day 

PM2.5: 11.6 

Range (Min, Max): 

Daily 

PM2.5: (2.0, 32.0) 

Every 6th Day 

PM2.5: (1.8, 43.0) 

Copollutant: 

SO2

CO 

NO2

O3

Increment: 

PM2.5 (Daily): 9.0 μg/m3 

PM2.5 (6th Day): 15.7 μg/m3

% Increase (Lower CI, Upper CI) lag: 

Nonaccidental 

PM2.5 (Daily) 

-0.1% (-5.1, 5.2) 0-2 avg 

-0.1% (-4.1, 4.1) 0 

-0.3% (-4.2, 3.7) 1 

0.5% (-3.3, 4.4) 2 

PM2.5 (6th Day) 

-2.8% (-7.5, 2.1) 0 

2.0% (-2.6, 7.0) 1 

4.5% (-0.3, 9.5) 2 

Cardiovascular 

PM2.5 (Daily) 

1.5% (-6.1, 9.7) 0-2 avg 

4.3% (-1.7, 10.7) 0 

-1.0% (-7.0, 5.4) 1 

-0.5% (-6.5, 5.9) 2 

PM2.5 (6th Day) 

-1.5% (-8.9, 6.5) 0 

-2.0% (-9.3, 5.8) 1 

3.0% (-4.2, 10.8) 2 

Respiratory 

PM2.5 (Daily) 

-0.7% (-13.1, 13.4) 0-2 avg 

6.7% (-3.7, 18.3) 0 

-3.0% (-12.8, 7.9) 1 

-5.8% (-15.2, 4.7) 2 

PM2.5 (6th Day) 

10.0% (-4.7, 26.8) 0 

8.3% (-5.4, 24.0) 1 

0.3% (-12.4, 14.9) 2 

Cancer 

PM2.5 (Daily) 

-0.3% (-9.4, 9.8) 0-2 avg 

-4.5% (-11.2, 2.8) 0 

2.7% (-5.0, 11.0) 1 

2.5% (-5.1, 10.7) 2 

PM2.5 (6th Day) 

-5.1% (-13.8, 4.5) 0 

-0.3% (-9.7, 11.0) 1 

0.2% (-9.1, 10.4) 2 

Reference: Wilson et al. (2007, 

157149) 

Period of Study: 1995-1997 

Location: Phoenix, Arizona 

Outcome: Cardiovascular 

Study Design: Time-series 

Statistical Analyses: Poisson GAM, 

nonparametric smoothing spline 

Age Groups: >25 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

% Excess Risk (Lower CI, Upper CI) 

lag: 

Central Phoenix: 

11.5% (2.8, 20.9) 0-5 ma 

6.6% (1.1, 12.5) 1 

2.0% (-3.2, 7.5) 2 

Middle Phoenix: 

2.9% (-4.9, 11.4) 0-5 ma 

6.4% (1.1, 11.9) 2 

Outer Phoenix: 

1.6% (-6.2, 10.0) 0-5 ma 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-359 
Table E-19. Short-term exposure-mortality - other PM size fractions. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: Respiratory mortality 

Study Design: Cohort 

Covariates: Temperature, humidity 

Statistical Analysis: Autoregressive 

Poisson regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM1

Averaging Time: 24 h 

Mean (SD) Unit: 20.0 (10.3) μg/m3

Range (Min, Max): 1.9, 80.1 

Copollutant: PM10-2.5, PM2.5-1

Increment: 10 μg/m3

Odds Ratio (95%CI) lag 

Avg L0-1: 1.005 (0.960-1.053), 

p = 0.824 

L1: 1.012 (0.969-1.056), p = 0.599 

L2: 1.042 (0.998-1.087), p = 0.063 

Multi-pollutant Model 

Avg L0-1: 1.007 (0.957-1.059), 

p = 0.799 

L1: 1.008 (0.961-1.058), p = 0.739 

L2: 1.010 (0.963-1.059), p = 0.678 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: Cardiovascular mortality 

Study Design: Cohort 

Covariates: temperature, Humidity 

Statistical Analysis: Autoregressive 

Poisson regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM1

Averaging Time: 24 h 

Mean (SD) Unit: 20.0 (10.3) μg/m3

Range (Min, Max): 1.9, 80.1 

Copollutant: PM10-2.5, PM2.5-1

Increment: 10 μg/m3

Odds Ratio (95%CI) lag 

Avg L0-1: 1.028 (1.000-1.057), 

p = 0.054 

L1: 1.029 (1.003-1.056), p = 0.030 

L2: 1.023 (0.996-1.050), p = 0.091 

Multi-pollutant Model 

Avg L0-1: 1.025 (0.995-1.057), 

p = 0.688 

L1: 1.028 (1.000-1.058), p = 0.053 

L2: 1.024 (0.995-1.053), p = 0.110 

Reference: Perez et al. (2008, 156020) 

Period of Study: Mar 2003-Dec 2005 

Location: Barcelona, Spain 

Outcome: Cerebrovascular mortality 

Study Design: Cohort 

Covariates: Temperature, humidity 

Statistical Analysis: Autoregressive 

Poisson regression models 

Statistical Package: NR 

Age Groups: All deaths 

Pollutant: PM1

Averaging Time: 24 h 

Mean (SD) Unit: 20.0 (10.3) μg/m3

Range (Min, Max): 1.9, 80.1 

Copollutant: PM10-2.5, PM2.5-1

Increment: 10 μg/m3

Odds Ratio (95%CI) lag 

Avg L0-1: 1.037 (0.981-1.097), 

p = 0.202 

L1: 1.056 (1.003-1.113), p = 0.039 

L2: 1.020 (0.968-1.075), p = 0.460 

Multi-pollutant Model 

Avg L0-1: 1.042 (0.981-1.107), 

p = 0.179 

L1: 1.063 (1.004-1.124), p = 0.035 

L2: 1.034 (0.976-1.095), p = 0.255 

Reference: Slaughter et al. (2005, 

073854) 

Period of Study: Jan 995-Dec 1999 

Location: Spokane, Washington 

Outcome: Mortality: Nonaccidental 

(<800) 

Study Design: Time-series 

Statistical Analyses: Poisson GLM, 

natural splines 

Age Groups: All ages 

Pollutant: PM1

Averaging Time: 24-h avg 

Mean (SD): NR 

Range (9th, 95th) 

PM1: (3.3, 17.6) 

Copollutant (correlation): 

PM1

PM2.5: r = 0.95 

PM10: r = 0.50 

PM10-2.5: r = 0.19 

CO: r = 0.63 

This study does not present quantitative 

results for PM1. 

Reference: Stölzel et al. (2007, 091374) 

Period of Study: Sept 1995-Aug 2001 

Location: Erfurt, Germany 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardio-respiratory (390-459, 460-519, 

785, 786) 

Study Design: Time-series 

Statistical Analyses: Poisson GAM 

Age Groups: All ages 

Pollutant: MC0.1-0.5, MC0.01-2.5

Averaging Time: 24-h avg 

Mean (SD): 

MC0.1-0.5: 17.6 (14.8) 

MC0.01-2.5: 22.3 (19.2) 

IQR (25th, 75th): 

MC0.1-0.5: (8.4, 21.5) 

MC0.01-2.5: (10.5, 27.3) 

Copollutant (correlation): 

MC0.1-0.5

NO: r = 0.52 

NO2: r = 0.60 

CO: r = 0.58 

MC0.01-2.5

NO: r = 0.51 

NO2: r = 0.58 

CO: r = 0.57 

Increment: 

MC0.1-0.5: 13.1 μg/m3 

MC0.01-2.5: 16.8 μg/m3

 

Relative Risk (Lower CI, Upper CI) 

lag: 

Total (nonaccidental) 

MC0.1-0.5

1.010 (0.986 

1.034) 

0 

1.006 (0.983 

1.029) 

1 

1.007 (0.985 

1.029) 

2 

0.994 (0.973 

1.016) 

3 

December 2009 E-360 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1.002 (0.981 

1.023) 

4 

0.997 (0.976 

1.018) 

5 

MC0.01-2.5

1.007 (0.985 

1.030) 

0 

1.005 (0.984 

1.026) 

1 

1.003 (0.983 

1.023) 

2 

0.989 (0.970 

1.009) 

3 

1.002 (0.982 

1.022) 

4 

0.998 (0.979 

1.018) 

5 

Cardio-respiratory 

MC0.1-0.5 

1.004 (0.977 

1.031) 

0 

1.004 (0.979 

1.029) 

1 

1.001 (0.978 

1.026) 

2 

0.991 (0.967 

1.014) 

3 

1.000 (0.977 

1.023) 

4 

1.000 (0.976 

1.023) 

5 

MC0.01-2.5 

1.001 (0.977 

1.026) 

0 

0.999 (0.976 

1.022) 

1 

0.998 (0.976 

1.021) 

2 

0.985 (0.964 

1.007) 

3 

1.001 (0.980 

1.022) 

4 

1.003 (0.981 

1.024) 

5 

December 2009 E-361 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Yamazaki et al. (2007, 

090748) 

Period of Study: 1995-1998 

Location: Hong Kong, China 

Outcome: Mortality: 

Intracerebral hemorrhage (431) 

Ischaemic stroke (434) 

Study Design: Time-stratified casecrossover 

Statistical Analyses: Conditional 

logistic regression 

Age Groups: ≥ 65 

Pollutant: PM7 

Averaging Time: 1-h avg 

Mean (SD): 

Warmer Months (Apr-Sep): 

40.3 

Colder Months (Oct-Mar): 

39.4 

Range (Min, Max): NR 

Copollutant (correlation): 

Warmer Months 

NO2: r = 0.46-0.63 

Ox: r = -0.14 to 0.20 

Colder Months 

NO2: 0.42-0.79 

Ox: r = -0.36 to -0.14 

Increment: 30 μg/m3

Odds Ratio (Lower CI, Upper CI) lag: 

24-h avg concentrations 

Intracerebral hemorrhage 

Warmer months: 1.041 (0.984, 1.102) 0 

Colder months: 1.005 (0.951, 1.061) 0 

Ischaemic stroke 

Warmer months: 1.027 (0.993, 1.062) 0 

Colder months: 1.005 (0.973, 1.039) 0 

Exposure measured jointly as 24-h and 

1-h mean concentrations 

Warmer months 

Intracerebral hemorrhage 

1-h with 200 μg/m3

 threshold: 

2.397 (1.476, 3.892) 2 h 

24-h: 1.019 (0.960, 1.082) 0 

Ischaemic stroke 

1-h with 200 μg/m3

 threshold: 

1.051 (0.750, 1.472) 2 h 

24-h: 1.018 (0.983, 1.055) 0 

Warmer months 

Intracerebral hemorrhage 

1-h with 200 μg/m3

 threshold: 

0.970 (0.712, 1.322) 2 h 

24-h: 1.015 (0.958, 1.075) 0 

Ischaemic stroke 

1-h with 200 μg/m3

 threshold: 

1.040 (0.855, 1.265) 2 h 

24-h: 1.003 (0.968, 1.039) 0 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-362 
E.4.Long-Term Exposure and Cardiovascular Outcomes 

Table E-20. Long-term exposure - cardiovascular morbidity outcomes - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Baccarelli et al. (2008, 

157984) 

Period of Study: 1995-2005 

Location: Italy (Lombardy region) 

Outcome (ICD9 and ICD10): Deep 

Vein Thrombosis (DVT) 

Prothrombin time (PT) 

Activated partial thromboplastin time 

(aPTT) 

Age Groups: 18-84yrs

Study Design: Case-control (DVT 

outcome) 

Cross-sectional (PT and aPTT 

outcomes) 

N: 871 cases 

1210 controls (randomly selected from 

friends and nonblood relatives of cases 

Frequency matched by age to cases) 

Statistical Analyses: Unconditional 

logistic regression (DVT outcome) 

Linear regression (PT and aPTT 

outcomes) 

Covariates: Sex, area of residence, 

education, factor V Leiden or G20210A 

prothrombin mutation, current use of 

oral contraceptives or hormone therapy 

(Variables controlled using penalized 

regression splines with 4 df) age, BMI, 

day of yr (for seasonality), index date, 

ambient temperature 

Season: covariate 

Dose-response Investigated? Yes 

Statistical Package: STATA v9.0 and R 

v2.2.0 

Pollutant: PM10

Averaging Time: 1 yr (immediately 

preceding the diagnosis date for cases 

or the date of examination for controls) 

assessed other averaging periods 

presented in supplements (90 days, 180 

days, 270 days, 2 yr) 

Mean (SD): NR 

Percentiles: NR 

Range (Min, Max): 

Range for tertiles of exposure: 

1: 12.0-44.2 

2: 44.3-48.1 

3: 48.2-51.5 

Monitoring Stations: Monitors from 53 

sites 

exposure assigned by dividing area into 

9 regions 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Estimated changes of PT associated 

with PM10: 

Among DVT cases: -0.12 (-0.23, 0.00), 

p = 0.04 

Among Controls: -0.06 (-0.11, 0.00) , 

p = 0.04 

Estimated changes of aPTT 

associated with PM10: 

Among Controls: -0.09 (-0.19, 0.01) , 

p = 0.07 

Among DVT cases: 0.01 (-0.03, 0.04) , 

p = 0.78 

Risk of DVT associated with PM10

(avg of 1 yr preceding 

diagnosis/exam date): | 

All subjects: 

1.70 (1.30, 2.23), p < 0.001 

Sex: 

Male: 2.07 (1.50, 2.84) , p < 0.001 

Female: 1.40 (1.02, 1.92) , p = 0.04 

P for interaction: p = 0.02

Age: 

18-35yrs: 1.57 (1.11, 2.24), p = 0.01 

36-50yrs: 1.97 (1.41, 2.77) , p < 0.001 

51-84yrs: 1.54 (0.90, 2.63) , p = 0.12 

P for interaction: p = 

0.99Premenopausal women with 

current use of oral contraceptives: 

No: 1.53 (0.86, 2.72) , p = 0.14 

Yes: 0.87 (0.46, 1.67), p = 0.68 

P for interaction: p = 

0.11Postmenopausal women with 

current use of hormone therapy: 

No: 1.60 (0.72, 3.54), p = 0.24 

Yes: 0.85 (0.29, 2.45), p = 0.76 

P for interaction: p = 0.27Current use 

of oral contraceptive or hormone 

replacement therapy: 

No: 1.64 (1.05, 2.57), p = 0.03 

Yes: 0.97 (0.58, 1.61), p = 0.89 

P for interaction: p = 0.048

Body Mass Index: 

13.3-22.0: 1.47 (0.97, 2.23), p = 0.07; 

22.1-24.9: 1.72 (1.17, 2.54), p = 0.006 

25.0-53.3: 1.83 (1.03, 3.24), p = 0.04 

P for interaction: p = 0.37 

Education: Elementary/middle school: 

1.93 (1.35, 2.76), p < 0.001 

High school: 1.72 (1.24, 2.39), 

p = 0.001 

College: 1.35 (0.74, 2.45), p = 0.33 

P for interaction: p = 0.21 

Deficiencies of natural anticoagulant 

proteins: 

None: 1.66 (1.26, 2.18), p < 0.001 

Any: 2.56 (0.91, 7.18), p = 0.07 

P for interaction: p = 0.41 

Factor V Leiden or G20210A 

prothrombin mutation: 

None: 1.69 (1.27, 2.23), p < 0.001 

Any: 1.79 (1.05, 3.05), p = 0.03 

P for interaction: p = 0.83 

Hyperhomocysteinemia: 

December 2009 E-363 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

No: 1.66 (1.26, 2.19), p < 0.001 

Yes: 2.19 (1.33, 3.61), p = 0.002 

P for interaction: p = 0.25 

Any cause of thrombophilia: 

No: 1.59 (1.19, 2.13), p = 0.002 

Yes: 1.96 (1.34, 2.87), p < 0.001 

P for interaction: p = 0.27 

Year of diagnosis: 

1995-97: 1.61 (1.06, 2.46), p = 0.03 

1998-00: 1.34 (0.90, 1.99), p = 0.15 

2001-05: 2.14 (1.04, 4.39), p = 0.04 

P for interaction: p = 0.12 

Risk of DVT associated with PM10

over varying averaging times: 

90 days: 0.91 (0.80, 1.03), p = 0.12 

180 days: 0.96 (0.82, 1.13), p = 0.63 

270 days: 1.26 (1.01, 1.57), p = 0.04 

365 days: 1.70 (1.30, 2.23), p = 0.0001 

2 yr: 1.47 (1.01, 2.14), p = 0.04 

Risk of DVT associated with PM10 (yr 

preceding diagnosis/exam date) 

sensitivity analysis to evaluate the 

effect of different methods for 

adjusting for long-term trends: 

Handling of long-term time trends: 

Ignored: 1.13 (0.89, 1.42), p = 0.31 

Dummy variable for each yr: 

1.78 (1.31, 2.44), p = 0.0003 

Linear term: 1.32 (1.02, 1.69), p = 0.03 

Penalized spline, 2 df: 1.54 (1.19, 2.00), 

p = 0.001 

Penalized spline, 3 df: 1.64 (1.26, 2.14), 

p = 0.0002 

Penalized spline, 4 df: 1.70 (1.30, 2.23), 

p = 0.0001 

Penalized spline, 5 df: 1.70 (1.29, 2.22), 

p = 0.0002 

Penalized spline, 6 df: 1.66 (1.26, 2.19), 

p = 0.0003 

Penalized spline, 7 df: 1.60 (1.21, 2.13), 

p = 0.001 

Penalized spline, 8 df: 1.55 (1.15, 2.10), 

p = 0.004 

Reference: Baccarelli et al. (2009, 

188183) 

Period of Study: Jan 1995-Sept 2005 

Location: Lombardia Region, Italy 

Outcome: Deep Vein Thrombosis 

Study Design: Case-control 

Covariates: Age, Sex, area of 

residence, BMI, education, medication 

use 

Statistical Analysis: Logistic 

regression 

Statistical Package: Stata 

Pollutant: PM10

Risk of DVT measured with regards to 

distance of residence from major road. 

Specific levels of PM10 not given. 

Increment: NA 

Relative Risk (95%CI) of DVT

All subjects, age-adjusted: 

1.33 (1.03-1.71), p = 0.03 

All subjects, adjusted for covariates: 

1.47 (1.10-1.96), p = 0.008 

All subjects, adjusted for covariates and 

background PM10 exposure: 1.47 (1.11-

1.96), p = 0.008

December 2009 E-364 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Calderon-Garciduenas et 

al. (2008, 156317) 

Period of Study: Children recruited 

between Jul 2003 and Dec 2004 

Location: Mexico (northeast or 

southwest Mexico city or Polotitlan) 

Outcome (ICD9 and ICD10): Plasma 

Endothelin-1 (ET-1) and pulmonary 

arterial pressure (PAP) 

Age Groups: 6-13 yr 

7.9 ± 1.3 yr

Study Design: Cross-sectional 

N: 81 children 

Statistical Analyses: Analysis of 

variance by parametric one-way 

analysis of variance and the NewmanKeuls multiple comparison post test, 

Pearson’s correlation 

Covariates: Doesn’t appear to have 

performed multivariable analyses 

However, collected information on age, 

place and length of residency, daily 

outdoor time, household cooking 

methods, parents’ occupational history, 

family history of atopic illnesses and 

respiratory disease, and personal 

history of otolaryngologic and 

respiratory symptoms 

Season: No 

Dose-response Investigated? No 

Statistical Package: STATA v8.3, or 

GraphPad Software, Inc. 

Pollutant: PM10 (μg/m3) 

Exposures assessed quantitatively in 

Mexico City only 

No monitors in Polotitlan 

Averaging Time: 1, 2, and 7 days 

before the exam 

Pollutant concentrations between 0700 

and 1900 h were used for the estimates 

Mean (SD): Presented only in figures 

Percentiles: NR 

Range (Min, Max): Presented only in 

figures 

Monitoring Stations: 4 (2 in northeast 

and 2 in southwest Mexico City) 

Residence and school within 5 mi of 

one of these monitors) 

Copollutant (correlation): O3

PM Increment: NA

Effect Estimate [Lower CI, Upper CI]: 

No health effects models with measured 

PM concentrations were presented 

Used city of residence to assign 

exposure 

No multivariable analyses presented 

Authors presented (statistically 

significantly) elevated ET-1 levels 

among children residing in both areas 

of Mexico City as compared to 

Polotitlan (control city): 

Mean ± SE (pg/mL) 

Control: 1.23 ± 0.06 

Southwest Mexico City: 2.40 ± 0.14 

Northeast Mexico City: 2.09 ± 0.10 

Mexico City (overall): 2.24 ± 0.12 

Authors presented (statistically 

significantly) elevated PAP levels 

among children residing in both areas 

of Mexico City as compared to 

Polotitlan (control city): 

Mean ± SE (mmHg) 

Control: 14.6 ± 0.4 

Southwest Mexico City: 16.7 ± 0.6 

Northeast Mexico City: 18.6 ± 0.9 

Mexico City (overall): 17.3 ± 0.5 

Correlation between ET-1 and time 

spent outdoors: r = 0.31, p = 0.0012 

Correlation between PAP and time 

spent outdoors: r = 0.42, p = 0.0008 

December 2009 E-365 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Diez Roux et al. (2008, 

156401) 

Period of Study: Baseline data 

collected Jun 2000-Aug 2002 

Exposure assessed retrospectively 

between Aug 1982 and baseline date 

Location: USA (6 field centers: 

Baltimore, MD 

Chicago, IL 

Forsyth Co, NC 

Los Angeles, CA 

New York, NY 

St. Paul, MN 

Outcome (ICD9 and ICD10): Three 

measures of subclinical atherosclerosis 

(common carotid intimal-medial 

thickness (CIMT), coronary artery 

calcification, and ankle-brachial index 

(ABI)) 

Age Groups: 44-84 yr (MESA cohort)

Study Design: Cross-sectional 

retrospective cohort 

N: 5172 for coronary calcium analysis 

5037 for CIMT analysis 

5110 for ABI analysis 

Statistical Analyses: Generalized 

Additive Models (Binomial regression: 

presence of calcification 

Linear regression: CIMT, ABI, amount of 

calcium among persons with non-zero 

calcification)

Covariates: Age, sex, race/ethnicity, 

socioeconomic factors, cardiovascular 

risk factors (BMI, hypertension, high 

density lipoprotein and low density 

lipoprotein cholesterol, smoking, 

diabetes, diet, physical activity 

models presented with and without 

adjustment for cardiovascular RFs) 

Season: NA 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM10 (μg/m3) 

Averaging Time: 20-yr imputed mean 

Mean (SD): 34.1 (7.5) 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: A spatio-temporal 

model was used to predict monthly 

PM2.5 exposures based on the 

geographic location of each 

participant’s residence. 

Copollutant (correlation with 20-yr 

imputed mean): 

PM10 20-yr observed mean 

r = 0.93 

PM2.5 20-yr imputed mean 

r = 0.73 

PM10 2001 imputed mean 

r = 0.75 

PM10 2001 observed mean 

r = 0.80 

PM2.5 2001 mean 

r = 0.86 

PM Increment: 21.0 μg/m3 (approx. 

10th-90th percentile) 

Effect Estimate [Lower CI, Upper CI]: 

CIMT: 

Relative difference (95% CI): 

1.01 (1.00, 1.02) 

Adj. for additional CVD RFs: 

1.02 (1.00, 1.03) 

ABI: 

Mean difference (95% CI): 

0.002 (-0.005, 0.009) 

Adj. for additional CVD RFs: 

0.001 (-0.006, 0.009) 

Coronary calcium: 

Relative prevalence (95% CI): 

1.02 (0.96, 1.07) 

Adj. for additional CVD RFs: 

1.02 (0.96, 1.08) 

Coronary calcium (in those with 

calcium): 

Relative difference (95% CI): 

0.98 (0.84, 1.13) 

Adj. for additional CVD RFs: 

1.01 (0.86, 1.18) 

Found no clear heterogeneity by age, 

sex, lipid status, smoking status, 

diabetes status, BMI, education or study 

site. 

December 2009 E-366 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Maheswaran et al. (2005, 

088683) 

Period of Study: 1994-1998 

Location: Sheffield, United Kingdom 

Outcome (ICD9 and ICD10): Stroke 

mortality (ICD9: 430-438) and 

Emergency hospital admissions (ICD10: 

I60-I69) 

Age Groups: ≥ 45 yr

Study Design: Small area ecological 

cross-sectional 

N: 1030 census enumeration districts 

(CEDs) 

108 CEDs excluded from PM analyses 

due to artifacts in the modeled 

emissions data. The analysis was 

based on 2979 deaths, 5122 

admissions and a population of 199,682

Statistical Analyses: Poisson 

regression 

Covariates: Age, sex, socioeconomic 

deprivation, and smoking prevalence 

(some models also included age-bydeprivation interaction) 

Season: NA 

Dose-response Investigated? Yes, 

examined quintiles of exposure 

Statistical Package: SAS 

Pollutant: PM10 (μg/m3) 

Averaging Time: 5-yr avg 

Mean (SD): Presented mean values 

and ranges for each quintile of 

exposure: 

1: 16.0 (<16.8) 

2: 17.5 (≥ 16.8, <18.2) 

3: 18.8 (≥ 18.2, <19.3) 

4: 19.8 (≥ 19.3, <20.6) 

5: 23.3 (≥ 20.6) 

Monitoring Stations: Used air pollution 

model incorporating point, line and grid 

sources of pollution and meteorological 

data. 

Copollutant (correlation): 

CO (r = 0.82) 

NOX (r = 0.87) 

PM Increment: NA 

Effect Estimate [Lower CI, Upper CI]: 

Rate Ratios (95%CI) for stroke 

mortality adjusted for overdispersion 

by quintile of PM10 level 

Adjusted for sex and age: 

1: 1 (ref) 

2: 0.95 (0.84, 1.08) 

3: 1.12 (0.99, 1.27) 

4: 1.16 (1.03, 1.32) 

5: 1.39 (1.23, 1.58) 

Adjusted for sex, age, deprivation, and 

smoking: 

1: 1 (ref) 

2: 0.94 (0.83, 1.07) 

3: 1.08 (0.94, 1.24) 

4: 1.12 (0.97, 1.29) 

5: 1.33 (1.14, 1.56) 

Rate Ratios (95%CI) for emergency 

hospital admissions because of 

stroke by quintile of PM10 level 

Adjusted for sex and age: 

1: 1 (ref) 

2: 1.06 (0.95, 1.17) 

3: 1.10 (0.99, 1.23) 

4: 1.25 (1.12, 1.38) 

5: 1.40 (1.26, 1.55) 

Adjusted for sex, age, deprivation, and 

smoking: 

1: 1 (ref) 

2: 1.01 (0.91, 1.13) 

3: 0.98 (0.87, 1.10) 

4: 1.08 (0.96, 1.22) 

5: 1.13 (0.99, 1.29) 

Rate Ratios (95%CI) for stroke 

mortality in relation to spatially 

smoothed (using a 1-km radius) 

modeled outdoor air pollution 

quintiles 

Adjusted for sex, age, socioeconomic 

deprivation, age by deprivation 

interaction, and smoking prevalence: 

1: 1 (ref) 

2: 0.86 (0.75, 0.98) 

3: 1.05 (0.92, 1.21) 

4: 1.03 (0.89, 1.19) 

5: 1.24 (1.05, 1.47) 

Rate Ratios (95%CI) for emergency 

hospital admissions because of 

stroke in relation to spatially 

smoothed modeled outdoor air 

pollution quintiles 

Adjusted for sex, age, socioeconomic 

deprivation, age by deprivation 

interaction, and smoking prevalence: 

1: 1 (ref) 

2: 1.05 (0.94, 1.17) 

3: 1.07 (0.95, 1.20) 

4: 1.06 (0.94, 1.20) 

5: 1.15 (1.01, 1.31) 

December 2009 E-367 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Maheswaran et al. (2005, 

090769) 

Period of Study: 1994-1998 

Location: Sheffield, United Kingdom 

Outcome (ICD9 and ICD10): Coronary 

Heart Disease (CHD) mortality (ICD9: 

410-414) and Emergency hospital 

admissions (ICD10: I20-I25) 

Age Groups: ≥ 45 yr

Study Design: Small area ecological 

cross-sectional 

N: 1030 census enumeration districts 

(CEDs) 

108 CEDs excluded from PM analyses 

due to artifacts in the modeled 

emissions data. Results based on 6857 

deaths, 11407 hospital admissions and 

199,682 people aged ≥ 45 yr 

Statistical Analyses: Poisson 

regression 

Covariates: Age, sex, socioeconomic 

deprivation, and smoking prevalence 

(some models also included age-bydeprivation interaction) 

Season: NA 

Dose-response Investigated? Yes, 

examined quintiles of exposure 

Statistical Package: SAS 

Pollutant: PM10 (μg/m3) 

Averaging Time: 5-yr avg 

Mean (SD): Presented mean values 

and ranges for each quintile of 

exposure: 

1: 16.0 (<16.8) 

2: 17.5 (≥ 16.8, <18.2) 

3: 18.8 (≥ 18.2, <19.3) 

4: 19.8 (≥ 19.3, <20.6) 

5: 23.3 (≥ 20.6) 

Monitoring Stations: Study used an air 

pollution model incorporating points, 

lines, and grids as sources of pollution, 

and meteorological data. 

Copollutant (correlation): 

CO (r = 0.82) 

NOX (r = 0.87) 

PM Increment: NA 

Effect Estimate [Lower CI, Upper CI]: 

Rate Ratios (95%CI) for CHD 

mortality in relation to modeled 

outdoor air pollution quintiles, 

adjusted for overdispersion 

Adjusted for sex and age: 

1: 1 (ref) 

2: 1.06 (0.98, 1.16) 

3: 1.10 (1.01, 1.21) 

4: 1.23 (1.13, 1.35) 

5: 1.30 (1.19, 1.43) 

Adjusted for sex, age, deprivation, and 

smoking: 

1: 1 (ref) 

2: 1.03 (0.94, 1.12) 

3: 1.00 (0.90, 1.11) 

4: 1.08 (0.98, 1.20) 

5: 1.08 (0.96, 1.20) 

Adjusted for sex, age, deprivation, and 

smoking (spatially smoothed using a 

1km radius): 

1: 1 (ref) 

2: 0.97 (0.89, 1.07) 

3: 1.00 (0.90, 1.10) 

4: 1.03 (0.93, 1.15) 

5: 1.07 (0.96, 1.21) 

Rate Ratios (95%CI) for emergency 

hospital admissions from CHD in 

relation to modeled outdoor air 

pollution quintiles 

Adjusted for sex and age: 

1: 1 (ref) 

2: 1.08 (0.98, 1.19) 

3: 1.11 (1.01, 1.22) 

4: 1.17 (1.07, 1.29) 

5: 1.36 (1.23, 1.50) 

Adjusted for sex, age, deprivation, and 

smoking: 

1: 1 (ref) 

2: 1.03 (0.93, 1.13) 

3: 0.96 (0.86, 1.07) 

4: 0.97 (0.87, 1.08) 

5: 1.01 (0.90, 1.14) 

Adjusted for sex, age, deprivation, and 

smoking (spatially smoothed using a 

1km radius): 

1: 1 (ref) 

2: 1.01 (0.92, 1.11) 

3: 1.04 (0.93, 1.15) 

4: 0.97 (0.87, 1.08) 

5: 1.07 (0.95, 1.20) 

December 2009 E-368 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: O’Neill et al. (2007, 

156006) 

Period of Study: 2000-2004 

Location: USA (6 field centers: 

Baltimore, MD 

Chicago, IL 

Forsyth Co, NC 

Los Angeles, CA 

New York, NY 

St. Paul, MN 

Outcome (ICD9 and ICD10): 

Creatinine adjusted urinary albumin 

excretion 

Assessed 2 ways: continuous log 

urinary albumin/creatine ration (UACR) 

and clinically defined micro- or macroalbuminuria (UACR ≥ 25 mg/g) vs. 

normal levels 

Age Groups: 44-84 yr 

Study Design: Cross-sectional 

analyses and prospective cohort 

analyses 

N: 3901 participants free of clinical CVD 

at baseline 

Statistical Analyses: At baseline: 

multiple linear regression (continuous 

outcome) 

Binomial regression (dichotomous 

outcome) 

3-yr change: repeated measures model 

with random subject effects (estimate 3-

yr change in log UACR by levels of 

exposure) 

Covariates: Age, gender, race, BMI, 

cigarette status, ETS, percent dietary 

protein 

For repeated measures models: time 

Time x PM10

Season: NA 

Dose-response Investigated? Yes, 

examined quartiles of exposure 

Statistical Package: SAS 

Pollutant: PM10 

Averaging Time: Avg of previous 

month, avg of previous 2 mo (recent 

exposures) 

20-yr directly monitored PM10 avg, 

20-yr imputed PM10 avg (longer-term 

exposures) 

Mean (SD): 

Previous 20 yr: 34.7 (7.0) 

Previous month: 27.5 (7.9) 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: NR (used closest 

monitor to residence to assign exposure

20-yr imputed PM10 was derived using a 

space-time model) 

Copollutant (correlation): PM2.5

PM Increment: 10 μg/m3 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted mean differences in log 

UACR (mg/g) per increase in PM10

among participants seen at baseline 

Previous 30 days 

Full sample: -0.42 (-0.085, 0.002) 

Within 10 km: -0.023 (-0.079, 0.034) 

Previous 60 days 

Full sample: -0.056 (-0.106 to -0.005) 

Within 10 km: -0.040 (-0.106, 0.025) 

20 yr PM10 (nearest monitors) 

Full sample: -0.019 (-0.072, 0.033) 

Within 10 km: 0.009 (-0.067, 0.085) 

Imputed 20 yr exposure 

Full sample: -0.002 (-0.038, 0.035) 

Within 10 km: 0.016 (-0.033, 0.066) 

Adjusted relative prevalence of 

microalbuminuria vs. high-normal 

and normal levels (below 25 mg/g) 

per increase in PM10 among 

participants without 

macroalbuminuria during the 

baseline visit 

Previous 30 days: 0.88 (0.76, 1.02) 

Previous 60 days: 0.83 (0.70, 0.99) 

20 yr PM10 (nearest monitors): 

0.92 (0.77, 1.08) 

Imputed 20 yr exposure: 

0.98 (0.87, 1.10) 

Adjusted mean 3-yr change (SE) in 

log UACR (mg/g) by quartiles of 

1982-2002 exposure to PM10 from 

ambient monitors among 

participants seen in 2000-20004 

Full sample 

Quartile: 

18.5 to <29.3: 0.147 (0.024) 

29.3 to <33.1: 0.159 (0.024) 

33.1 to <36.3: 0.163 (0.024) 

36.3 to 55.7: 0.174 (0.023) 

p-trend: 0.42 

Within 10 km 

Quartile: 

18.5 to <29.3: 0.159 (0.030) 

29.3 to <33.1: 0.155 (0.031) 

33.1 to <36.3: 0.167 (0.028) 

36.3 to 55.7: 0.152 (0.036) 

p-trend: 0.99 

Interactions with either 20 yr or shorterterm PM exposure were not significant 

(p < 0.01) by gender, age, city, 

race/ethnicity or study site. 

Reference: Puett et al, (2008, 156891) 

Period of Study: 1992-2002 

Location: Northeastern metropolitan 

U.S. 

Outcome: Nonfatal myocardial 

infarction 

Study Design: Cohort 

Covariates: Age in months, state of 

residence, yr and season

Statistical Analysis: Cox proportional 

hazard

Statistical Package: SAS 

Age Groups: 30-55 

Pollutant: PM10

Averaging Time: 3-, 12-, 24-, 36- and 

48-mo ma 

Mean (SD) Unit: NR

Range (Min, Max): NR

Copollutant (correlation): NR 

Increment: 10 μg/m3

Hazard Ratio, 95% CI, 12 month ma

0.94 (0.77-1.15) 

December 2009 E-369 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rosenlund et al. (2006, 

114678) 

Period of Study: 1992-1994 

Location: Stockholm County, Sweden 

Outcome (ICD9 and ICD10): 

Myocardial infarction (MI) 

Age Groups: 45-70 yr

Study Design: Case-control 

N: 1397 cases 

1870 controls 

Statistical Analyses: Logistic 

regression (main analysis) 

Also performed multinomial logistic 

regression to assess cases as nonfatal, 

fatal in the hospital within 28 days, and 

out-of-hospital death within 28 days with 

all controls as reference 

Covariates: Age, sex, and hospital 

catchment area (frequency matched 

variables) 

Smoking, physical inactivity, diabetes, 

SES 

Also assessed but did not include 

hypertension, BMI, job strain, diet, 

passive smoking, alcohol consumption, 

coffee intake, and occupational 

exposure to motor exhaust and other 

combustion products 

Season: NA 

Dose-response Investigated? No 

Statistical Package: STATA v8.2 

Pollutant: PM10 

(modeled traffic-related pollution; also 

modeled PM2.5, but since the PM 

correlation was high (r = 0.998) only 

PM10 results were presented) (μg/m3

) 

Averaging Time: 30 yr (PM only 

assessed during 2000, thus assumed 

constant levels during 1960-2000)

Median (5th-95th percentile): 

Cases: 2.6 (0.5-6.0) 

Controls: 2.4 (0.6-5.9) 

Range (Min, Max): NR 

Monitoring Stations: NR 

Copollutant (correlation): 

NO2 (r = 0.93) 

CO (r = 0.66) 

SO2

PM Increment: 5 μg/m3 (5th to 95th 

percentile distribution among controls) 

Effect Estimate [Lower CI, Upper CI]: 

Association of 30-yr avg exposure to air 

pollution from traffic with MI 

Logistic regression 

All cases: 1.00 (0.79, 1.27) 

Multinomial logistic regression 

Nonfatal cases: 0.92 (0.71, 1.19) 

Fatal cases: 1.39 (0.94, 2.07) 

In-hospital death: 1.21 (0.75, 1.94) 

Out-of-hospital death: 1.84 (1.00, 3.40) 

After adjustment for heating-related 

SO2, the estimate for fatal MI was 1.40 

(0.86-2.26) for PM10. 

December 2009 E-370 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zanobetti & Schwartz 

(2007, 091247) 

Period of Study: 1985-1999 

Location: 21 U.S. cities (Birmingham, 

Alabama 

Boulder, Colorado 

Canton, Ohio 

Chicago, Illinois 

Cincinnati, Ohio 

Cleveland, Ohio 

Colorado Springs, Colorado 

Columbus, Ohio 

Denver, Colorado 

Detroit, Michigan 

Honolulu, Hawaii 

Houston, Texas 

Minneapolis-St. Paul, Minnesota 

Nashville, Tennessee 

New Haven, Connecticut 

Pittsburgh, Pennsylvania 

Provo-Orem, Utah 

Salt Lake City, Utah 

Seattle, Washington 

Steubenville, Ohio 

and Youngstown, Ohio) 

Outcome (ICD9 and ICD10): Death, 

subsequent myocardial infarction (MI 

ICD9 codes 410.0-410.9), and a first 

admission for congestive heart failure 

(CHF 

ICD9 code 428) 

Age Groups: ≥ 65 yr

Study Design: Cohort 

N: 196,000 persons discharged alive 

following an acute MI 

Statistical Analyses: Cox’s 

Proportional Hazards Regression 

Meta-regression for city-specific results 

Covariates: Age, sex, race, type of MI, 

number of days of coronary care and 

intensive care, previous diagnoses for 

atrial fibrillation, and secondary or 

previous diagnoses for COPD, 

diabetes, and hypertension, and for 

season of initial event (time period, and, 

sex, race, and type of MI were treated 

as stratification variables) 

Season: Assessed as a confounder 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: Yearly avg of 

pollution for that yr and lags up to the 3 

previous yr (distributed lag)

Mean (SD): 28.8 (all cities 

SD not reported) 

Percentiles: 10, 50, and 90 percentiles 

listed individually for each city (Table 2) 

Range (Min, Max): NR 

Monitoring Stations: NR (obtained 

data from the U.S. EPA Aerometric 

Information Retrieval System) 

Copollutant (correlation): None 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Hazard ratio (95%CI) for an increase in 

PM for the yr of failure and for the 

distributed lag from the yr of failure up 

to 3 previous yr 

Death 

PM10 annual: 1.11 (1.05, 1.19), 

p = 0.001 

Distributed lag model 

 Lag 0: 1.04 (0.96, 1.14), p = 0.336 

 Lag 1: 1.07 (0.99, 1.14), p = 0.070 

 Lag 2: 1.14 (1.10, 1.18), p = 0.000 

 Lag 3: 1.06 (0.99, 1.12), p = 0.077 

 Sum lags 0-3: 1.34 (1.14, 1.52), 

p = 0.000 

CHF 

PM10 annual: 1.11 (1.03, 1.21), 

p = 0.009 

Distributed lag model 

 Lag 0: 1.09 (1.01, 1.18), p = 0.030 

 Lag 1: 1.09 (1.01, 1.19), p = 0.038 

 Lag 2: 1.13 (1.02, 1.25), p = 0.014 

 Lag 3: 1.04 (0.97, 1.12), p = 0.260 

 Sum lags 0-3: 1.41 (1.19, 1.66), 

p = 0.000 

2nd MI 

PM10 annual: 1.17 (1.05, 1.31), 

p = 0.003 

Distributed lag model 

 Lag 0: 1.09 (0.92, 1.30), p = 0.325 

 Lag 1: 1.12 (0.97, 1.30), p = 0.108 

 Lag 2: 1.15 (1.08, 1.23), p = 0.000 

 Lag 3: 1.01 (0.94, 1.09), p = 0.783 

 Sum lags 0-3: 1.43 (1.12, 1.82), 

p = 0.005 

Hazard Ratio (95%CI) for an increase in 

PM (sum of the previous 3 yr distributed 

lag) for the sensitivity analyses 

Death

Subjects with follow-up starting after 

2nd MI: 

1.33 (1.15, 1.55), p = 0.000 

Subjects admitted between 1985-1996: 

1.45 (1.26, 1.68), p = 0.000 

2nd cohort definition (yr defined at time 

of MI): 

1.29 (1.15, 1.44), p = 0.000 

CHF

Subjects with follow-up starting after 

2nd MI: 

1.42 (1.22, 1.65), p = 0.000 

Subjects admitted between 1985-1996: 

1.51 (1.26, 1.81), p = 0.000 

2nd MI 

Subjects admitted between 1985-1996: 

1.62 (1.23, 2.13), p = 0.001 

Note: Age and sex effect modification 

results presented in Fig 1 

Used meta-regression to examine 

predictors of heterogeneity across city 

and found that most predictors were not 

significant modifiers of PM (Table 7) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-371 
Table E-21. Long-term effects-cardiovascular- PM2.5 (including PM components/sources). 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Allen et al. (2009, 156209) 

Period of Study: Oct 2000-Sep 2002 

(exposure averaging period) 

outcome assessed in 2002 

Location: 5 U.S. communities 

(Chicago, Illinois 

Forsyth County, North Carolina 

Los Angeles, California 

Northern Manhattan and the Bronx, 

New York 

and St. Paul, Minnesota) 

part of MESA (Multi-ethnic Study of 

Atherosclerosis) 

Outcome (ICD9 and ICD10): 

Abdominal aortic calcium (AAC), a 

marker of systemic atherosclerosis 

(quantitative measure of interest was 

the Agatston score) 

Age Groups: 46-88 yr

Study Design: Cross-sectional 

N: 1,147 participants (sensitivity 

analysis among 1,269 participants) 

Statistical Analyses: 2-part modeling 

approach: 

1) Modeled relative risk of having any 

AAC using a log link and a Gaussian 

error model 

Sensitivity analysis used modified 

Poisson regression with robust error 

variance 

2) Multiple linear regression of the logtransformed AAC Agatston score 

(among those with AAC>0) 

Sensitivity analysis modeled all 

participants by adding 1 prior to logtransforming 

Covariates: Age, gender, race/ethnicity, 

BMI, smoking status, pack-yr of 

smoking, diabetes, education, annual 

income, blood lipid concentration, blood 

pressure, and medications 

Assessed impact of gender, age, 

diabetes, obesity, use of lipid-lowering 

medications, education, income, 

race/ethnicity, and employment status 

on heterogeneity of effects (or in 

sensitivity analyses) 

Season: NA 

Dose-response Investigated? NR 

Statistical Package: SAS v9.1 

Pollutant: PM2.5 

Averaging Time: 2-yr averaging period 

(Oct 2000-Sep 2002)

Mean (SD): 15.8 (3.6) μg/m3

 

Percentiles: NR 

Range (Min, Max): 10.6-24.7 μg/m3 

Monitoring Stations: All monitors with 

1) the objective of “population 

exposure,” “regional transport,” or 

“general/background; ) and 2) at least 

50% data reporting in each of 8 3-

month periods over the averaging time 

Used monitors located within 50 km of a 

study participant’s residence 

Copollutant (correlation): 

Assessed traffic by roadway proximity 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Results for fully adjusted models under 

different participant inclusion, 

employment status, and roadway 

proximity criteria.

Presence/Absence of Calcium RR 

(95% CI) 

Inclusion criteria: <10yrs at address: 

1.04 (0.89, 1.22) 

≥ 10yrs at address: 1.06 (0.96, 1.16) 

≥ 10yrs at address & <10km from 

monitor: 1.08 (0.98, 1.18) 

≥ 20yrs at address: 1.10 (0.99, 1.22) 

≥ 20yrs at address & <10km from 

monitor: 1.11 (1.00, 1.24) 

<10yrs at address & employed: 

1.02 (0.87, 1.20) 

≥ 20yrs at address & employed: 

1.07 (0.89, 1.27) 

<10yrs at address & not employed: 

1.10 (1.00, 1.22) 

≥ 20yrs at address & not employed: 

1.16 (1.02, 1.31) 

<10yrs at address & near major road: 

0.85 (0.69, 1.05) 

≥ 20yrs at address & not near major 

road: 1.10 (0.99, 1.23)

Log-transformed Agatston Score 

(Agatston >0) 

% Change (95% CI) 

Inclusion criteria: <10yrs at address: 

-6.6 (-64.0, 50.9) 

≥ 10yrs at address: 8.0 (-29.7, 45.7) 

≥ 10yrs at address & <10km from 

monitor: 19.7 (-19.6, 58.9) 

≥ 20yrs at address: 14.4 (-32.8, 61.7) 

≥ 20yrs at address & <10km from 

monitor: 24.6 (-24.6, 73.8) 

<10yrs at address & employed: 

29.1 (-25.7, 83.8) 

≥ 20yrs at address & employed: 

43.8 (-32.4, 119.9) 

<10yrs at address & not employed: 

-15.1 (-66.3, 36.1) 

≥ 20yrs at address & not employed: 

-14.1 (-72.6, 44.4) 

<10yrs at address & near major road: 

34.0 (-44.2, 112.1) 

≥ 20yrs at address & not near major 

road: 3.9 (-39.9, 47.8) 

Log-transformed Agatston Score (all)

% Change (95% CI) 

Inclusion criteria: <10yrs at address: -

8.5 (-81.3, 64.2) 

≥ 10yrs at address: 40.7 (-11.5, 92.8) 

≥ 10yrs at address & <10km from 

monitor: 60.7 (5.9, 115.4) 

≥ 20yrs at address: 64.1 (-1.73, 129.9) 

≥ 20yrs at address & <10km from 

monitor: 79.2 (10.1, 148.3) 

<10yrs at address & employed: 

33.5 (-35.9, 102.9) 

≥ 20yrs at address & employed: 

55.8 (-37.2, 148.7) 

<10yrs at address & not employed: 

54.8 (-23.8, 133.4) 

≥ 20yrs at address & not employed: 

89.3 (-3.7, 182.3) 

<10yrs at address & near major road: 

-30.6 (-141.3, 80.1) 

≥ 20yrs at address & not near major 

December 2009 E-372 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

road: 51.3 (-8.3, 110.8) 

Exploratory/sensitivity analyses 

(also presented in figures): 

Detectable AAC RR (95%CI): 

Among women: 1.14 (1.00, 1.30) 

Among persons >65yrs: 

1.10 (1.01, 1.19) 

Among users of lipid-lowering 

medications: 1.14 (1.00, 1.30) 

Among Hispanics: 1.22 (1.03, 1.45) 

Imputing missing covariates among 

residentially stable participants: 

1.08 (0.98, 1.19) 

Agatston score % change (95%CI): 

Among Hispanics: 64 (-4, 133)

Among persons earning >$50,000: 72 

(5, 139) 

Agatston score including those with 

Agatston = 0 

% change (95%CI): 

Fully adjusted model: 41 (-12, 93) 

Among persons >65yrs: 75 (8, 143) 

Among diabetics: 149 (29, 270) 

Among users of lipid-lowering 

medications: 121 (25, 217) 

Among Hispanics: 141 (45, 236) 

Imputing missing 

Covariates: 49 (1.3, 100.1) 

December 2009 E-373 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Auchincloss et al. (2008, 

156234) 

Period of Study: Jul 2000-Aug 2002 

Location: 6 U.S. communities 

(Baltimore City and Baltimore County, 

Maryland 

Chicago, Illinois 

Forsyth County, North Carolina 

Los Angeles, California 

Northern Manhattan and the Bronx, 

New York 

and St. Paul, Minnesota) 

part of MESA (Multi-ethnic Study of 

Atherosclerosis) 

Outcome (ICD9 and ICD10): Blood 

pressure: systolic (SBP), diastolic 

(DBP), mean arterial (MAP), pulse 

pressure (PP) 

Avg of 2nd and 3rd BP measurement 

used for analyses 

Age Groups: 45-84 yr 

Study Design: Cross-sectional (MultiEthnic Study of Atherosclerosis baseline 

examination) 

N: 5,112 persons (free of clinically 

apparent cardiovascular disease) 

Statistical Analyses: Linear regression

Secondary analyses used log binomial 

models to fit a binary hypertension 

outcome 

Covariates: Age, sex, race/ethnicity, 

per capita family income, education, 

BMI, diabetes status, cigarette smoking 

status, exposure to ETS, high alcohol 

use, physical activity, BP medication 

use, meteorology variables, and 

copollutants 

Examined site as a potential 

confounder and effect modifier 

Heterogeneity of effects also examined 

by traffic-related exposures, age, sex, 

type 2 diabetes, hypertensive status, 

cigarette use 

Season: Adjusted for temperature and 

barometric pressure to adjust for 

seasonality (because seasons vary by 

the study sites) 

Also performed sensitivity analyses 

adjusting for season to examine the 

potential for residual confounding not 

accounted for by weather variables 

Dose-response Investigated? 

Assessed nonlinear relationships-no 

evidence of strong threshold/nonlinear 

effects for PM2.5

Statistical Package: NR 

Pollutant: PM2.5

Averaging Time: 5 exposure metrics 

constructed: prior day, avg of prior 2 

days, prior 7 days, prior 30 days, and 

prior 60 days 

Mean (SD): Prior day: 17.0 (10.5) 

Prior 2 days: 16.8 (9.3) 

Prior 7 days: 17.0 (6.9) 

Prior 30 days: 16.8 (5.0) 

Prior 60 days: 16.7 (4.4) 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: Used monitor 

nearest the participant’s residence to 

calculate exposure metrics 

Copollutant (correlation): 

SO2

NO2

CO 

Traffic-related exposures (straight-line 

distance to a highway; total road length 

around a residence) 

PM Increment: 10 μg/m3 (approx. 

equivalent to difference between 90th 

and 10th percentile for prior 30 day 

mean) 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted mean difference (95% CI) in 

PP and SBP (mmHg) per 10 μg/m3

increase in PM2.5 (avg for the prior 30 

days) 

Pulse Pressure 

Adjustment variables: Person-level 

Covariates: 1.04 (0.25, 1.84) 

Person-level cov., weather: 

1.12 (0.28, 1.97) 

Person-level cov., weather, gaseous 

copollutants: 2.66 (1.61, 3.71) 

Person-level cov., study site: 

0.93 (-0.04, 1.90) 

Person-level cov., study site, weather: 

1.11 (0.01, 2.22) 

Person-level cov., study site, weather, 

gaseous copollutants: 1.34 (0.10, 2.59) 

Systolic Blood Pressure 

Adjustment variables: Person-level 

Covariates: 0.66 (-0.41, 1.74) 

Person-level cov., weather: 

0.99 (-0.15, 2.13) 

Person-level cov., weather, gaseous 

copollutants: 2.8 (1.38, 4.22) 

Person-level cov., study site: 

0.86 (-0.45, 2.17) 

Person-level cov., study site, weather: 

1.32 (-0.18, 2.82) 

Person-level cov., study site, weather, 

gaseous copollutants: 1.52 (-0.16, 3.21) 

Additional results: Associations 

became stronger with longer averaging 

periods up to 30 days. For example: 

Adjusted (personal covariates and 

weather) mean differences in PP: Prior 

day: -0.38 (-0.76, 0.00) 

Prior 2 days: -0.22 (-0.65, 0.21) 

Prior 7 days: 0.52 (-0.08, 1.11) 

Prior 30 days: 1.12 (0.28, 1.97) 

Prior 60 days: 1.08 (0.11, 2.05) 

(Pattern held for additional adjustments 

and for SBP results. Therefore, only 

results for 30-day mean differences 

were presented) 

Additional results (not presented): 

None of DBP results were statistically 

significant. Rresults for MAP were 

similar to SBP, though weaker and 

generally not significant 

Effect modification: associations 

between PM2.5 and BP were stronger 

for persons taking medications, with 

hypertension, during warmer weather, 

in the presence of high NO2, residing ≤

300m from a highway, and surrounded 

by a high density of roads (Fig 1) 

Associations were not modified for age, 

sex, diabetes, cigarette smoking, study 

site, high levels of CO or SO2, season , 

nor residence ≤ 400m fro a highway 

Note: supplementary material available 

on-line 

December 2009 E-374 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Calderón-Garcidueñas et 

al. (2009, 192107) 

Period of Study: Sept 2004-Jan 2005 

Location: Mexico City and Polotitlan, 

Mexico 

Outcome: Flow cytometry 

Study Design: Panel 

Covariates: NR 

Statistical Analysis: Pearson’s 

Correlation 

Statistical Package: Stata 

Age Groups: 9.7 ± 1.2 yr 

Pollutant: PM2.5

Averaging Time: 1-, 2- and 7-day avg 

Mean (SD) Unit: 35.89 ± 0.93 μg/m3

Range (Min, Max): NR 

Copollutant: PM10, O3

Increment: NR 

Flow cytometry results and their 

statistical significance in control vs. 

exposed children

CD3 

Exposed: 62.9±1.8 

Control: 67.1±1.7 

P = 0.1 

CD4 

Exposed: 39.3±1.3 

Control: 38.2±1.4 

P = 0.57 

CD8 

Exposed: 24.0±0.95 

Control: 27.3±1.0 

P = 0.02 

CD4/CD8 

Exposed: 1.7±0.14 

Control: 1.4±0.07 

P = 0.09 

CD3-/CD19+ 

Exposed: 11.8±1.0 

Control: 14.8±1.0 

P = 0.04 

CD56+ 

Exposed: 11.5±1.2 

Control: 12.4±1.5 

P = 0.63 

CD56+/CD3-NK 

Exposed: 14.0±9.5 

Control: 7.0±2.7 

P = 0.003 

HLA-DR+ 

Exposed: 27.5±4.2 

Control: 17.0±2.4 

P = 0.04 

mCD14+ 

Exposed: 66.5±2.3 

Control: 80.6±1.8 

P = <0.001 

CD14/CD69 

Exposed: 0.20±0.07 

Control: 1.0±0.26 

P = <0.001 

CD4/CD69 

Exposed: 0.08±0.03 

Control: 3.1±0.65 

P = <0.001 

December 2009 E-375 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Diez Roux et al. (2008, 

156401) 

Period of Study: Baseline data 

collected Jun 2000-Aug 2002 

Exposure assessed retrospectively 

between Aug 1982 and baseline date 

Location: USA (6 field centers: 

Baltimore, MD 

Chicago, IL 

Forsyth Co, NC 

Los Angeles, CA 

New York, NY 

St. Paul, MN 

Outcome (ICD9 and ICD10): Three 

measures of subclinical atherosclerosis 

(common carotid intimal-medial 

thickness (CIMT), coronary artery 

calcification, and ankle-brachial index 

(ABI)) 

Age Groups: 44-84 yr

Study Design: Cross-sectional 

N: 5172 for coronary calcium analysis 

5037 for CIMT analysis 

5110 for ABI analysis 

Statistical Analyses: Generalized 

Additive Models (Binomial regression: 

presence of calcification 

Linear regression: CIMT, ABI, amount of 

calcium)

Covariates: Age, sex, race/ethnicity, 

socioeconomic factors, cardiovascular 

risk factors (BMI, hypertension, high 

density lipoprotein and low density 

lipoprotein cholesterol, smoking, 

diabetes, diet, physical activity 

Models presented with and without 

adjustment for cardiovascular RFs) 

Season: NA 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM2.5 

Averaging Time: 20-yr imputed mean 

Mean (SD): 21.7 (5.0) 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: NR 

Long-term exposure to PM estimated 

based on residential history reported 

retrospectively 

all addresses geocoded 

ambient AP obtained from U.S. EPA 

Copollutant (correlation): 

PM10 20-yr observed mean 

r = 0.64 

PM10 20-yr imputed mean 

r = 0.73 

PM10 2001 mean 

r = 0.43 

PM2.5 2001 mean 

r = 0.64 

Due to high correlation among PM 

exposures, only results of mean 20-yr 

exposures are reported. 

PM Increment: 12.5 μg/m3 (approx. 

10th-90th percentile) 

Effect Estimate [Lower CI, Upper CI]: 

CIMT: 

Relative difference (95% CI): 

1.01 (1.00, 1.01) 

Adj. for additional CVD RFs: 

1.01 (1.00, 1.02) 

1.02 ABI: 

Mean difference (95% CI): 

0.000 (-0.006, 0.006) 

Adj. for additional CVD RFs: 

-0.001 (-0.006, 0.006) 

Coronary calcium: 

Relative prevalence (95% CI): 

1.01 (0.96, 1.05) 

Adj. for additional CVD RFs: 

1.01 (0.96, 1.06) 

1.02 Coronary calcium (in those with 

calcium): 

Relative difference (95% CI): 

0.99 (0.88, 1.12) 

Adj. for additional CVD RFs: 

1.01 (0.89, 1.14) 

December 2009 E-376 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hoffman et al. (2007, 

091163) 

Period of Study: 2000-2003 

Location: Ruhr area of Germany (3 

large cities: Essen, Mulheim, and 

Bochum) 

Outcome (ICD9 and ICD10): Coronary 

artery calcification (CAC) 

Age Groups: 45-74 yr

Study Design: Cross-sectional 

N: 4494 participants 

Statistical Analyses: Linear regression 

(outcome = natural logarithm of CAC 

score + 1) 

Logistic regression (outcome = CAC 

score above/below the age- and 

gender-specific 75th percentile) 

Covariates: City and area of residence, 

age, sex, education, smoking, ETS, 

physical inactivity, waist-to-hip ratio, 

diabetes, blood pressure, and lipids 

(and household income in a subset) 

Season: NA 

Dose-response Investigated? Yes, 

PM was also categorized into quartiles 

for analyses 

Statistical Package: NR 

Pollutant: PM2.5 

Averaging Time: 1 yr (2002, midpoint 

of the study) 

Mean (SD): Total: 

22.8 (1.5) 

High traffic exposure (≤ 100m): 

22.9 (1.4) 

Low traffic exposure (>100m): 

22.8 (1.5) 

Percentiles: 

Q1: 21.54 

Q2: 22.59 

Q3: 23.75 

10th-90th percentile: 3.91 

Range (Min, Max): NR 

Monitoring Stations: Daily mean PM2.5

values for 2002 were estimated with the 

EURAD model using data from official 

emission inventories, meteorological 

information, and regional topographical 

data. 

Copollutant (correlation): None 

(Traffic was assessed using distance to 

roadways) 

Correlation between modeled daily avg 

of PM2.5 and measured PM2.5: 0.86-

0.88, depending on season. 

PM Increment: 3.91 μg/m3 (10th-90th 

percentile) 

Effect Estimate [Lower CI, Upper CI]: 

Percent change (95%CI) in CAC 

associated with an increase in PM2.5 

Unadjusted: 12.7 (-7.0, 36.4) 

Model 1 (adjusted for distance to major 

road): 12.3 (-7.3, 35.9) 

Model 2 (model 1 + city and area of 

residence): 29.7 (0, 68.3) 

Model 3 (model 2 + age, sex, 

education): 24.2 (0, 55.1) 

Model 4 (model 3 + smoking, ETS, 

physical inactivity, waist-to-hip ratio): 

17.9 (-5.3, 46.7) 

Model 5 (model 4 + diabetes, blood 

pressure, LDL, HDL, triglycerides): 

17.2 (-5.6, 45.5) 

Adjusted ORs (95%CI) for the 

association between the top quarter 

of PM exposure vs. the low quarter 

of PM exposure and a CAC score 

above the age- and sex-specific 75th 

percentiles

All: 1.22 (0.96, 1.54) 

No CHD: 1.22 (0.95, 1.57) 

Men: 1.09 (0.78, 1.53) 

Women: 1.34 (0.97, 1.87) 

Age <60 yr: 1.18 (0.83, 1.68) 

Age >60 yr: 1.27 (0.93, 1.75) 

Nonsmokers: 1.17 (0.89, 1.53) 

Current smokers: 1.30 (0.83, 2.05) 

Educational level 

Low: 1.16 (0.86, 1.57) 

Medium: 1.30 (0.83, 2.05) 

High: 1.62 (0.81, 3.25) 

Additional notes: 

No clear dose-response relationship 

demonstrated when exposure assessed 

in quartiles (Fig 2) 

Participants who had not been working 

full-time during the last 5 yr showed 

stronger effects, with possible doseresponse between PM2.5 and CAC 

(results presented in Fig 3) 

Reference: Hoffman et al. (2006, 

091162) 

Period of Study: Dec 2000-Jul 2003 

Location: Ruhr area of Germany (2 

large cities: Essen, Mulheim) 

Outcome (ICD9 and ICD10): Clinically 

manifest CHD (defined as self-reported 

history of a ‘hard’ coronary event, i.e. 

myocardial infarction or application of a 

coronary stent or angioplasty or bypass 

surgery) 

Age Groups: 45-75 yr

Study Design: Cross-sectional 

(German Heinz Nixdorf RBCALL study) 

N: 3399 participants 

Statistical Analyses: Multivariable 

logistic regression 

Covariates: Sex, diabetes, 

hypertension, smoking status, ETS, 

educational level, physical activity, BMI, 

triglycerides, age, cigarettes smoked 

per day, WHR, LDL, HDL, HbAIc, 

indicator variable for cities, indicator 

variable for living in northern part of 

cities. 

Statistical Package: SAS v8.2 

Pollutant: PM2.5 (μg/m3) 

Averaging Time: Yearly mean 

estimated with model for yr 2002 (on a 

spatial scale of 5 km)

Mean (SD): 

Total: 23.3 (1.4) 

High traffic: 23.4 (1.4) 

Low traffic: 23.3 (1.4) 

Percentiles: NR 

Range (Min, Max): NR

Monitoring Stations: NR 

Copollutant (correlation): None 

(Traffic was assessed using distance to 

roadways) 

Effect Estimate [Lower CI, Upper CI]: 

Model 1: PM2.5 + high traffic exposure 

0.92 (0.36, 2.39) 

Model 2: model 1 + age, sex 

0.83 (0.31, 2.27) 

Model 3: model 2 + education, diabetes, 

HbAIc, BMI, WHR, smoking status, 

ETS, physical activity, city, area of 

residence 

0.56 (0.16, 2.01) 

Model 4: model 3 + hypertension, lipids 

0.55 (0.14, 2.11) 

Modeled vs. Measured: r = 0.86-0.88, 

depending on season 

December 2009 E-377 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hoffmann et al, (2009, 

190376) 

Period of Study: 2000-2003 

Location: Ruhr area, Germany 

Outcome: Peripheral Arterial Disease 

Study Design: 

Covariates: Height, weight, medication 

use, diabetes, physical activity level, 

smoking, socioeconomic status, 

education, population density 

Statistical Analysis: NR 

Statistical Package: NR 

Age Groups: 45-75 yr 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD) Unit: 22.96 (0.85)

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 3.91 μg/m3

Odds Ratio (95%CI) for prevalence of 

peripheral arterial disease

0.87 (0.57-1.34) 

Reference: Kunzli et al. (2005, 087387) 

Period of Study: 1998-2003 

Location: Los Angeles Basin 

Outcome (ICD9 and ICD10): Carotid 

intima-media thickness (CIMT) 

Age Groups: Less than 40 yr excluded 

Mean age = 59.2 ± 9.8

Study Design: Cross-sectional 

N: 798 participants 

Statistical Analyses: Linear regression

Covariates: Age, sex, education, 

income, smoking, ETS, blood pressure, 

LDL cholesterol, treatment with 

antihypertensives or lipid-lowering 

medications 

Season: NA 

Dose-response Investigated? Yes, 

assessed PM2.5 in quartiles 

Statistical Package: NR 

Pollutant: PM2.5 (μg/m3) 

Averaging Time: GIS/geostatics model 

to estimate ‘long-term mean ambient 

concentrations of PM2.5’ derived from 

data collected in 2000, including data 

from 23 state and local monitoring 

stations.

Mean (SD): 20.3 ± 2.6 

Percentiles: NR 

Range (Min, Max): 5.2, 26.9 

Monitoring Stations: 23 monitors 

Copollutant (correlation): None 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Percent change (95%CI) in CIMT 

associated with an increase in PM2.5

concentration 

Based on a linear model with log intimamedia thickness as dependent variable 

Total population: 

Unadjusted: 5.9 (1.0, 10.9) , p = 0.018 

Adjusted for age, sex, education, 

income: 

4.4 (0.0, 9.0) , p = 0.056 

Adjusted for above + smoking, ETS, 

multivitamins, alcohol: 

4.2 (-0.2, 8.9) , p = 0.064 

Among Females ≥ 60 yr: 

Unadjusted: 19.2 (8.8, 30.5) , p = 0.001 

Adjusted for age, sex, education, 

income: 

15.7 (5.7, 26.6) , p = 0.002 

Adjusted for above + smoking, ETS, 

multivitamins, alcohol: 

13.8 (4.0, 24.5) , p = 0.002 

Among those taking lipid-lowering 

therapy: 

Unadjusted: 15.8 (2.1, 31.2) , p = 0.024 

Adjusted for age, sex, education, 

income: 

13.3 (0, 28.5) , p = 0.031 

Adjusted for above + smoking, ETS, 

multivitamins, alcohol: 

13.3 (-0.3, 28.8) , p = 0.060 

For the observed contrast between 

lowest and highest exposure: 

Approximately 20 μg/ m3 Æ 12.1% (2.0-

231%) increase in CIMT. 

Among nonsmokers: 6.6% (1.0-12.3%). 

The estimate was small and not 

significant in current and former 

smokers.

Women: In the range of 6-9% per 10 

μg/m3 

Unadjusted means of CIMT across 

quartiles of exposure were 734, 753, 

758, and 774 μm 

Adjusted means trend across exposure 

groups, p = 0.041 

Stratified results presented in figures 

Reference: Miller et al. (2007, 090130) 

Period of Study: 1994-2003 

Location: 36 U.S. metropolitan areas 

(Women’s Health Initiative) 

Outcome (ICD9 and ICD10): First 

cardiovascular event (myocardial 

infarction, coronary revascularization, 

stroke, and death from either coronary 

heart disease [categorized as “definite” 

or “possible”] or cerebrovascular 

disease) 

Age Groups: 50-79 yr (median age at 

Pollutant: PM2.5 (μg/m3) 

Averaging Time: Annual avg 

concentration in 2000 (used to 

represent long-term exposure)

Mean (SD): 

Individual exposure: 13.5 (3.7) 

Citywide avg exposure: 13.5 (3.3) 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Estimated Hazards Ratio (95%CI) for 

the time to the first cardiovascular event 

or death associated with an increase in 

PM2.5

Any cardiovascular event (first event) 

Overall: 1.24 (1.09, 1.41) 

December 2009 E-378 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

enrollment: 63)

Study Design: Cohort (median followup of 6 yr) 

N: 65,893 postmenopausal women 

without previous cardiovascular disease

Statistical Analyses: Cox-proportional 

hazards regression

Covariates: Age, race/ethnicity, 

smoking status, the number of 

cigarettes smoked per day, the number 

of yr of smoking, systolic blood pressure, education level, household 

income, BMI, and presence or absence 

of diabetes, hypertension, or hypercholesterolemia (also evaluated ETS, 

occupation, physical activity, diet, 

alcohol consumption, waist circumference, waist-to-hip ratio, medical 

history, medications, and presence or 

absence of a family history of cardiovascular disease as possible 

confounders in extended models) 

Season: NA 

Dose-response Investigated? 

Statistical Package: SAS v8.0, STATA 

v8.0 

Median: 13.4 

Percentiles: 

Quintile ranges: 

1: 3.4, 10.9 

2: 11.0, 12.4 

3: 12.5, 14.2 

4: 14.3, 16.4 

5: 16.5, 28.3 

IQR: 11.6-18.3 

10th-90th 

Personal: 9.1-18.3 

City-wide: 9.3-17.8 

Range (Min, Max): 

Personal exposure: 3.4, 28.3 

Citywide exposure: 4.0, 19.3 

Monitoring Stations: 573 monitors 

The nearest monitor to the location of 

each residence was used to assign 

exposure (monitor within 30 mi of 

residence 

Median of 20 monitors per city (range: 

4-78)) 

Copollutant (correlation): 

PM10

SO2

NO2

CO 

O3

Between cities: 1.15 (0.99, 1.32) 

Within cities: 1.64 (1.24, 2.18) 

Coronary heart disease (first event): 

Overall: 1.21 (1.04, 1.42) 

Between cities: 1.13 (0.95, 1.35) 

Within cities: 1.56 (1.11, 2.19) 

Cerebrovascular disease (first event): 

Overall: 1.35 (1.08, 1.68) 

Between cities: 1.20 (0.94, 1.54) 

Within cities: 2.08 (1.28, 3.40) 

MI (first event): 

Overall: 1.06 (0.85, 1.34) 

Between cities: 0.97 (0.75, 1.25) 

Within cities: 1.52 (0.91, 2.51) 

Coronary revascularization (first event): 

Overall: 1.20 (1.00, 1.43) 

Between cities: 1.14 (0.93, 1.39) 

Within cities: 1.45 (0.98, 2.16) 

Stroke (first event): 

Overall: 1.28 (1.02, 1.61) 

Between cities: 1.12 (0.87, 1.45) 

Within cities: 2.08 (1.25, 3.48) 

Any death from cardiovascular cause: 

Overall: 1.76 (1.25, 2.47) 

Between cities: 1.63 (1.10, 2.40) 

Within cities: 2.28 (1.10, 4.75) 

Coronary heart disease death (definite 

diagnosis): 

Overall: 2.21 (1.17, 4.16) 

Between cities: 2.22 (1.06, 4.62) 

Within cities: 2.17 (0.60, 7.89) 

Coronary heart disease death (possible 

diagnosis): Overall: 1.26 (0.62, 2.56) 

Between cities: 1.20 (0.54, 2.63) 

Within cities: 1.57 (0.29, 8.51) 

Cerebrovascular disease death: 

Overall: 1.83 (1.11, 3.00) 

Between cities: 1.58 (0.90, 2.78) 

Within cities: 2.93 (1.03, 8.38) 

Estimated Hazard Ratios for 

cardiovascular events associated with 

an increase in PM2.5 according to 

selected characteristics (presented 

adjusted H and adjusted H including 

adjustment for city) 

Any cardiovascular event: 

H: 1.24 (1.09, 1.41) 

H (city): 1.69 (1.26, 2.27) 

Household income <$20,000: 

H: 1.30 (1.10, 1.53) 

H (city): 1.75 (1.28, 2.40) 

Household income $20,000-49,999: 

H: 1.23 (1.08, 1.41) 

H (city): 1.69 (1.25, 2.27) 

Household income ≥ $50,000: 

H: 1.20 (1.02, 1.40) 

6 

H (city): 1.66 (1.22, 2.26) 

P for trend: HR: p = 0.34 

HR (city): p = 0.54 

Education: Not high-school graduate: 

H: 1.40 (1.11, 1.75) 

H (city): 1.88 (1.32, 2.67) 

Education: High school grad/trade 

school/GED: H: 1.33 (1.14, 1.55) 

H (city): 1.79 (1.32, 2.44) 

Education: Some college or associate 

degree: H: 1.26 (1.09, 1.44) 

December 2009 E-379 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

H (city): 1.74 (1.29, 2.34) 

Education: Bachelor’s degree or higher: 

H: 1.11 (0.94, 1.31) 

H (city): 1.54 (1.13, 2.10) 

P for trend: H: p = 0.07 

H (city): p = 0.15 

Age <60 yr: H: 1.21 (0.84, 1.73) 

H (city): 1.66 (1.05, 2.61) 

Age 60-69 yr: H: 1.14 (0.93, 1.39) 

H (city): 1.53 (1.09, 2.14) 

Age ≥ 70 yr: H: 1.34 (1.11, 1.63) 

H (city): 1.85 (1.34, 2.56) 

P for trend: H: p = 0.20 

H (city): p = 0.20 

Current smoker: H: 1.68 (1.06, 2.66) 

H (city): 2.28 (1.33, 3.92) 

Former smoker: H: 1.24 (1.01, 1.52) 

H (city): 1.71 (1.23, 2.39) 

Never smoked: H: 1.18 (0.99, 1.40) 

H (city): 1.60 (1.16, 2.21) 

Living with smoker currently: 

H: 1.28 (0.84, 1.97) 

H (city): 1.65 (0.99, 2.76) 

Living with smoker formerly: 

H: 1.18 (1.00, 1.38) 

H (city): 1.59 (1.16, 2.16) 

Living with smoker never: 

H: 1.39 (1.07, 1.80) 

H (city): 1.90 (1.31, 2.78) 

BMI <22.5: H: 0.99 (0.80, 1.21) 

H (city): 1.35 (0.96, 1.88) 

BMI 22.5-24.7: H: 1.16 (0.96, 1.40) 

H (city): 1.58 (1.14, 2.19) 

BMI 24.8-27.2: H: 1.24 (1.05, 1.45) 

H (city): 1.69 (1.24, 2.30) 

BMI 27.3-30.9: H: 1.38 (1.18, 1.61) 

H (city): 1.88 (1.38, 2.56) 

BMI >30.9: H: 1.35 (1.12, 1.64) 

H (city): 1.84 (1.33, 2.55) 

P for trend: H: p = 0.003 

H (city): p = 0.007 

Waist-to-hip ratio <0.74: 

H: 1.07 (0.90, 1.29) 

H (city): 1.45 (1.05, 2.00) 

Waist-to-hip ratio 0.74-0.77: 

H: 1.12 (0.95, 1.31) 

H (city): 1.51 (1.11, 2.06)

Waist-to-hip ratio 0.78-0.80: 

H: 1.24 (1.07, 1.44) 

H (city): 1.68 (1.23, 2.27)

Waist-to-hip ratio 0.81-0.86: 

H: 1.30 (1.13, 1.50) 

H (city): 1.76 (1.30, 2.38)

Waist-to-hip ratio >0.86: 

H: 1.29 (1.11, 1.50) 

H (city): 1.75 (1.29, 2.37) 

Waist circumference <73 cm: 

H: 1.05 (0.86, 1.27) 

H (city): 1.43 (1.02, 1.99) 

Waist circumference 73-78 cm: 

H: 1.20 (1.02, 1.41) 

H (city): 1.63 (1.19, 2.23) 

Waist circumference 79-85 cm: 

H: 1.22 (1.05, 1.41) 

H (city): 1.66 (1.22, 2.24) 

Waist circumference 86-95 cm: 

H: 1.33 (1.15, 1.53) 

H (city): 1.80 (1.33, 2.43) 

Waist circumference >95 cm: 

H: 1.27 (1.07, 1.51) 

H (city): 1.73 (1.26, 2.36) 

P for trend: H: p = 0.06 

H (city): p = 0.07

Hormone-replacement therapy-Current 

Use: H: 1.33 (1.09, 1.61) 

H (city): 1.85 (1.32, 2.58) 

Hormone-replacement therapy-No 

Current Use: H: 1.16 (0.98, 1.39) 

December 2009 E-380 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

H (city): 1.57 (1.14, 2.17) 

Diabetes-yes: H: 0.96 (0.67, 1.37) 

H (city): 1.24 (0.78, 1.96) 

Diabetes-no: H: 1.28 (1.12, 1.47) 

H (city): 1.75 (1.30, 2.36) 

Hypertension-yes: H: 1.22 (1.02, 1.45) 

H (city): 1.65 (1.09, 2.27) 

Hypertension-no: H: 1.26 (1.05, 1.51) 

H (city): 1.74 (1.25, 2.40) 

Hypercholesterolemia-yes: 

H: 1.25 (0.94, 1.67) 

H (city): 1.71 (1.15, 2.54) 

Hypercholesterolemia-no: 

H: 1.23 (1.07, 1.42) 

H (city): 1.69 (1.25, 2.28) 

Family history of CVD- yes: 

H (city): 1.80 (1.32, 2.44) 

Family history of CVD- no: 

H: 1.07 (0.83, 1.37) 

H (city): 1.46 (1.00, 2.12) 

Time lived in current state: ≥ 20 yr: 

H: 1.21 (1.06, 1.39) 

H (city): 1.66 (1.23, 2.23) 

Time lived in current state: 10-19 yr: 

H: 1.39 (1.12, 1.72)’ 

H (city): 1.97 (1.40, 2.79) 

Time lived in current state: ≤ 9 yr: 

H: 1.54 (1.06, 2.26) 

H (city): 2.24 (1.39, 3.59) 

Health insurance coverage-yes: 

H: 1.22 (1.07, 1.39) 

H (city): 1.71 (1.27, 2.30) 

Health insurance coverage-no: 

H: 1.82 (0.81, 4.10) 

H (city): 2.65 (1.12, 6.28) 

Time spent outdoors: <30 min: 

H: 1.09 (0.86, 1.39) 

H (city): 1.56 (1.05, 2.31) 

Time spent outdoors: ≥ 30 min 

H: 1.26 (1.05, 1.50) 

H (city): 1.82 (1.29, 2.57) 

Reference: O'Neill et al. (2007, 

156006) 

Period of Study: 2000-2004 

Location: USA (6 field centers: 

Baltimore, MD 

Chicago, IL 

Forsyth Co, NC 

Los Angeles, CA 

New York, NY 

St. Paul, MN 

Outcome (ICD9 and ICD10): 

Creatinine adjusted urinary albumin 

excretion 

Assessed 2 ways: continuous log 

urinary albumin/creatine ration (UACR) 

and clinically defined micro- or macroalbuminuria (UACR ≥ 25 mg/g) vs. 

normal levels 

Age Groups: 44-84 yr 

Study Design: Prospective cohort 

analyses (MESA cohort) 

N: 3901 participants, free of clinical 

CVD at baseline 

Statistical Analyses: Multiple linear 

regression (continuous outcome) 

Binomial regression (dichotomous 

outcome) 

Covariates: Age, gender, race, BMI, 

cigarette status, ETS, percent dietary 

protein 

Season: NA 

Dose-response Investigated? Yes, 

examined quartiles of exposure 

Statistical Package: SAS 

Pollutant: PM2.5 (μg/m3) 

Averaging Time: Avg of previous 

month, avg of previous 2 mo (recent 

exposures) 

20-yr imputed PM2.5 avg (longer-term 

exposures) 

Mean (SD): Previous month: 

16.5 (4.8) 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: NR (used closest 

monitor to residence to assign value for 

recent exposures 

20-yr PM2.5 exposures were imputed 

using a space-time model.) 

Copollutant (correlation): PM10

PM Increment: 10 μg/m3 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted mean differences in log 

UACR (mg/g) per increase in PM2.5

among participants seen at baseline 

Previous 30 days 

Full sample: -0.017 (-0.087, 0.052) 

Within 10 km: 0.026 (-0.067, 0.119) 

Previous 60 days 

Full sample: -0.040 (-0.121, 0.042) 

Within 10 km: -0.013 (-0.122, 0.097) 

Imputed 20 yr exposure 

Full sample: 0.002 (-0.048, 0.052) 

Within 10 km: -0.012 (-0.076, 0.053) 

Adjusted relative prevalence of 

microalbuminuria vs. high-normal 

and normal levels (below 25 mg/g) 

per increase in PM2.5 among 

participants without 

macroalbuminuria during the 

baseline visit 

Previous 30 days: 0.94 (0.77, 1.16) 

Previous 60 days: 0.90 (0.71, 1.14) 

Imputed 20 yr exposure: 

0.98 (0.84, 1.14) 

December 2009 E-381 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Solomon et al. (2003, 

156994) 

Period of Study: Exposures measures 

1966-1969 

Health endpoints assessed via 

questionnaire, yr not reported but 

apparently 30 yr after exposure 

assessment (given the 30 yr residency 

requirement) 

Location: United Kingdom 

Outcome (ICD9 and ICD10): Ischemic 

heart disease (a self-reported history of 

medically diagnosed angina or heart 

attack) 

Age Groups: 45 yr and older

Study Design: Cross-sectional 

N: 1,166 women 

Statistical Analyses: Log linear 

modeling 

Covariates: Smoking, passive smoking 

in childhood, tenancy, social class, 

worked in industry with respiratory 

hazard, childhood hospital admission 

for chest problem, diabetes, BMI 

Season: NA 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: Black smoke (μg/m3) 

Averaging Time: Exposure measures 

performed 1966-1969 

women had to live within 5 miles of their 

current address for the past 30 yr to be 

included

Mean (SD): 11 wards with pollution 

measures were categorized into high 

(mean >120 μg/m3

) and low (mean 

<50 μg/m3

) exposure categories when 

classified according to their black 

smoke levels during 1966-69 

SD not reported 

Percentiles: NR 

Range (Min, Max): NR 

Monitoring Stations: NR 

Copollutant (correlation): SO2 (health 

results not presented) 

PM Increment: Categorical 

Effect Estimate [Lower CI, Upper CI]: 

Association of particulate pollution in 

place of residence and ischemic heart 

disease 

Low (ref): 1.0 

High: 1.0 (0.7, 1.4) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-382 
E.5.Long-Term Exposure and Respiratory Outcomes 

Table E-22. Long-term exposure - respiratory morbidity outcomes - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ackermann-Liebrich et al. 

(1997, 077537) 

Period of Study: 1991-1993 

Location: Switzerland (Aarau, Basel, 

Davos, Geneva, Lugano, Montana, 

Payerne, Wald) 

Outcome: Pulmonary function 

Age Groups: 18-60 yr 

Study Design: Cross-sectional

N: 9651 people 

Statistical Analyses: Regression 

analysis 

Covariates: Age, sex, height, weight, 

education level, nationality, workplace 

exposure 

Season: NR 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: Continuously 

measured, 12-mo. avg. used 

Mean (SD): 21.2 (7.4) 

Range: (10.1-33.4) 

Copollutant (correlation): 

SO2: r = 0.93 

NO2: r = 0.91 

O3: r = -0.55 

Summer Daytime 

O3: r = 0.31 

Excess O3: r = 0.67 

Altitude: r = -0.77 

PM Increment: 10 μg/m3

Regression Coefficient β (Lower CI, 

Upper CI) for air pollutants as 

predictors of pulmonary function 

FVC: -0.0345 (-0.0407 to -0.0283) 

p < 0.001 

FEV1: -0.0160 (-0.0225 to -0.0095) 

p < 0.001 

Percent Change (Lower CI, Upper CI) 

associated with increase in avg 

annual air pollution concentration 

Healthy Never-smokers 

FVC: -3.39 

p < 0.001 

FEV1: -1.59 

p < 0.001 

All Never-smokers 

FVC: -3.14 

p < 0.001 

FEV1: -1.06 

p < 0.001 

Former Smokers 

FVC: -3.03 

p < 0.001 

FEV1: -0.42 

Current Smokers 

FVC: -3.21 

p < 0.001 

FEV1: -1.35 

p < 0.001 

All 

FVC: -3.14 

p < 0.001 

FEV1: -1.03 

p < 0.001 

Long-term Residents 

FVC: -3.16 

p < 0.001 

FEV1: -0.96 

p < 0.001 

Reference: Avol et al. (2001, 020552) 

Period of Study: 1993-1998 

Location: Southern California 

Outcome: FVC, FEV1, MMEF, PEFR 

Age Groups: 10 yr 

Study Design: cohort

N: 110 

Statistical Analyses: Linear regression 

Covariates: Sex, race, cohort entry yr, 

annual avg change in height, weight, 

BMI 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 24-h PM10 avgd over 

1994 

Mean (SD): 15.0-66.2 

PM Increment: 10 μg/m3

Mean Change (Lower CI, Upper CI) 

FVC: -1.8 (-9.1, 5.5) 

FEV1: -6.6 (-13.5, 0.3) 

MMEF: -16.6 (-32.1 to -1.1) 

PEFR: -34.9 (-59.8 to -10.0) 

December 2009 E-383 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bayer-Oglesby et al. (2005, 

086245) 

Period of Study: 1992-2001 

Location: Switzerland (Lugano, Zurich, 

Bern, Geneva, Anieres, Biel, Langnau, 

Payerne, & Montana) 

Outcome: Respiratory symptoms 

(chronic cough, bronchitis, cold, dry 

cough, conjunctivitis, wheeze, 

sneezing, asthma, & hay fever) 

Age Groups: 6-15 yr 

Study Design: Cross-sectional

N: 9,591 children 

Statistical Analyses: Logistic 

regression models 

Covariates: Age, sex, nationality, 

parental education, number of siblings, 

farming status, low birth weight, breast 

feeding, smoking, family history of 

asthma, bronchitis and/or atopy, mother 

who smokes, indoor humidity, mode of 

cooking & heating, carpeting, pets, 

removal of carpets/pets for health 

reasons, completed questionnaire & 

month, days max temperature <0°C, 

mother’s belief of association between 

environmental exposures & respiratory 

health 

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM10

Averaging Time: 12-mo avg 

Mean (SD): NR 

Range (Min, Max): NR 

Monitoring Stations: 9 

Copollutant (correlation): NR 

PM Increment: 10 μg/m3

“Fig 2 shows that declining levels of 

PM10 were associated with declining 

prevalence of chronic cough, bronchitis, 

common cold, nocturnal dry cough, and 

conjunctivitis symptoms. For wheezing, 

sneezing, asthma, and hay fever, no 

significant association could be seen 

with declining PM10 levels.” 

“Fig 3 illustrates that, on an aggregate 

level, across regions the mean change 

in PM10 levels (r pearson = 0.81, 

p = 0.008). The strongest decline of 

adjusted prevalence of nocturnal dry 

cough was observed in Geneva, 

Lugano, and Anieres, where the 

strongest reduction of PM10 had also 

been achieved.” 

Reference: Burr et al. (2004, 087809) 

Period of Study: 3 wk in Jul and Jan 

1997 and 2 wk in Nov 1996 and Apr 

1997 

Location: North Wales, England 

Outcome: Self-report of symptoms only 

for wheeze, cough, phlegm, rhinitis, and 

itchy eyes. 

Age Groups: all 

Study Design: Repeated measures

N: 386 persons in congested streets 

and 425 in the uncongested streets in 

1996/1997. Of these, 165 and 283 

completed the second phase of the 

study. 

Pollutant: PM10

Averaging Time: Mean hourly 

concentrations 

Mean (SD): SD NR 

Congested streets - 

1996-97 35.2 

1998-99 27.2 

Uncongested Streets 

1996-97 11.6 

1998-99 8.2 

Monitoring Stations: 1 in congested 

street and 1 in uncongested 

Percent change PM10 in congested 

streets: 22.7 

Percent change PM10 in 

uncongested streets: 28.9 

Uncongested street sampling site was 

20 m from the congested street 

sampler. 

The opening of the by-pass produced a 

reduction in pollution in the congested 

streets. The health effects of these 

changed is likely to be greater for nasal 

and ocular symptoms than for lower 

respiratory symptoms. Uncertainty 

about the causality arises from low 

response rates and conflicting trends in 

respiratory and nasal symptoms. 

December 2009 E-384 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Calderón-Garcidueñas et 

al. (2006, 091253) 

Period of Study: 1999, 2000 

Location: Southwest Mexico City & 

Tlaxcala, Mexico 

Outcome: Hyperinflation, interstitial 

markings-measured by chest 

radiograph, and lung function-FVC, 

FEV1, PEF, FEF25-75, measured using 

spirometry tests 

Age Groups: 5-13 yr 

Study Design: Cohort 

N: 249 (total), 230 (Southwest Mexico 

City), 19 (Tlaxcala) 

Statistical Analyses: Bayes test, 

Spearman rank correlation, multiple 

regression 

Covariates: Age, sex 

Dose-response Investigated? No 

Statistical Package: SAS 8.2 

Pollutant: PM10

Averaging Time: 1 yr 

Mean (SD): 

Mexico City 

1999-48 

2000-45 

Tlaxacala: 

1994-2000: <NAAQS std 

Monitoring Stations: Southwest 

Mexico City-2 

Tlxacala-periodic air monitoring data 

Copollutant: O3

PM Increment: NR 

% Change: 

% of children with FEV1 <80% expected 

value: 

Mexico City (n = 77): 7.8% 

Tlaxacala (n = 19): 0% 

% children with hyperinflation: 

Mexico City: 65.6% 

No hyperinflation: 79 

Mild: 72 

Moderate: 56 

Severe: 23 

Tlaxacala: 5.3% 

No hyperinflation: 18 

Mild: 1 

Moderate: 0 

Severe: 0 

% children with interstitial markings: 

Mexico City: 52.6% 

Number with: 

No interstitial markings: 19 

Mild: 0 

Moderate: 0 

Severe: 0 

Tlaxacala: 0% 

No interstitial markings: 109 

Mild: 112 

Moderate: 9 

Severe: 0 

Reference: Calderon-Garciduenas, et 

al. (2003, 156316) 

Period of Study: Jan 1999-Jun 2000 

Location: Mexico City, Tuxpam, and 

Tlaxcala, Mexico 

Outcome: Respiratory system changes 

Age Groups: 5-17 yr 

Study Design: Case-control of subjects 

examined for this study

N: 174 cases, 27 controls, children 

Statistical Analyses: Chi-square test 

with Yates correction, Spearman’s rank 

correlation test. 

Dose-response Investigated? No 

Statistical Package: SAS 8.2 

Pollutant: PM10

Averaging Time: 12 h (daytime 08: 00-

20: 00) and nighttime (20: 00-08: 00) 

Mean (SD): Mexico City 

Day/Night 

Jan-Jun 1999 76.0/50.0 

Jul-Dec 1999 42.8/22.5 

Jan-Jun 2000 75.2/47.5 

Daily ambient exposure of children to a 

complex mixture of air pollutants 

produces significant chest X-ray 

abnormalities, a decrease in predicted 

values of FEF25-75, FEF75, and the 

FEV1/FVC ratio in association with 

interstitial marking on chest X-rays, a 

mild restrictive pattern by spirometry, 

peripheral blood abnormalities, and an 

imbalance of serum cytokines. 

Reference: Cavanagh et al. (2007, 

189802) 

Period of Study: Mar-Aug 2004 

Location: Christchurch, New Zealand 

Outcome: A clinical study of excretion 

of 1-hydroypyrene (1-OHP) as a marker 

of PAH exposure 

Age Groups: Non-smoking males aged 

12-18 yr 

Study Design: Comparison of 2 high 

pollution events and 2 low pollution 

events

N: 89 male students in a boarding 

school 

Statistical Analyses: Wilcoxon signed 

rank test for paired observations, MannWhitney U test 

Season: Winter 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Fall Low 

Outdoor 19 Indoor NA 

Winter I 

Outdoor 43 Indoor 38 

Winter II 

Outdoor 72 Indoor 84 

Winter Low 

Outdoor 12 Indoor 16 

Monitoring Stations: One inside the 

boarding house, and one outside 

Urinary 1-OHP were raised after highpollutions events. Peaks were slightly 

higher than for U.S. non-smokers of 

similar ages and slightly lower than for 

German non-smokers of similar ages. 

Urinary 1-OHP was slightly higher in 

asthmatics compared to nonasthmatics. 

There were no indoor sources of PAHs 

(wood-burning stoves, tobacco smoke). 

Diet is another source of PAHs, but all 

students ate in the boarding house. 

These results suggest 1-OHP could be 

used as a biomarker of ambient air 

pollution. 

December 2009 E-385 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Downs et al. (2007, 

092853) 

Period of Study: 1991, 2002 

Location: Switzerland 

Outcome: FEV1, FEV1 as % of FVC, 

FEF25-75 

Age Groups: 18-60 yr 

Study Design: Prospective Cohort

N: 4742 people 

Statistical Analyses: Linear random 

effects models 

Covariates: Age, sex, height, parental 

smoking, season, education, nationality, 

occupational exposure, smoking 

(status, pack-yr), atopy, BMI 

Dose-response Investigated? 

Yes-linear fit best 

Statistical Package: SAS 9.1, STATA 

8.2, R 2.4 

Pollutant: PM10

Averaging Time: Annual 

Mean: 

Mean interval exposure: 238 μg/m3/yr 

Percentiles: 

25th: 197 

75th: 287 

PM Increment: 10 μg/m3 reduction in 

annual mean 

Percent / absolute reduction in annual 

decline in lung function over 11-yr 

period (95% CI): 

Annual decline in FEV1 reduced by 9% / 

3.1 mL (0.03-6.2) 

Annual decline in FEF25-75 reduced by 

16% / 11.3 mL/second (4.3-18.2) 

Annual decline in FEV1 as a percentage 

of FVC of 0.06 (0.01-0.12) 

A reduction in interval exposure of 109 

μg per m3

 cubic meter-yr (equivalent to 

a reduction of 10 μg/m3

 in the annual 

avg during the mean follow-up time of 

10.9 yr) was associated with: 

A reduction of 6.9 mL (95% CI, 2.1 to 

11.7) in the annual decline in FEV1 

A 22% reduction in the annual decline 

in FEF25-75 (i.e., by 14.0 mL per 

second 95% CI, 3.1 to 24.8) 

Reference: Gauderman et al. (2000, 

012531) 

Period of Study: 1993-1997 

Location: Southern California 

Outcome: FVC, FEV1, MMEF, FEF75 

Age Groups: Fourth, seventh, or tenth 

graders 

Study Design: Cohort

N: 3035 subjects 

Statistical Analyses: Linear regression

Covariates: Height, weight, BMI, 

asthma, smoking, exercise, room 

temperature, barometric pressure 

Dose-response Investigated? Yes 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24-h avg PM10 

Mean (SD): PM10 51.5 

Copollutant (correlation): 

PM2.5 r = 0.96 

O3 r = -0.32 

PM10-2.5 r = 0.92 

NO2 r = 0.65 

Inorg. Acid r = 0.68 

PM10 Increment: 51.5 μg/m3

% Change (Lower CI, Upper CI) 

PM10-4th grade 

FVC -0.58 (-1.14 to -0.02) 

FEV1 -0.85 (-1.59 to -0.10) 

MMEF -1.32 (-2.43 to -0.20) 

FEF75 -1.63 (-3.14 to -0.11) 

PM10-7th grade 

FVC -0.45 (-1.03, 0.13) 

FEV1 -0.44 (-1.10, 0.23) 

MMEF -0.48 (-2.51, 1.59) 

FEF75 -0.50 (-2.26, 1.29) 

PM10-10th grade 

FVC 0.07 (-0.99, 1.13) 

FEV1 -0.46 (-1.84, 0.94) 

MMEF -0.71 (-4.87, 3.63) 

FEF75 -1.54 (-5.61, 2.71) 

Reference: Gauderman et al. (2002, 

026013) 

Period of Study: 1996-2000 

Location: Southern California 

Outcome: Lung function development: 

FEV1, maximal midexpiratory flow 

(MMEF) 

Age Groups: Fourth grade children 

(avg age = 9.9 yr) 

Study Design: Cohort study

N: 1678 children, 12 communities 

Statistical Analyses: Mixed model 

linear regression 

Covariates: Height, BMI, doctordiagnosed asthma and cigarette 

smoking in previous yr, respiratory 

illness and exercise on day of test, 

interaction of each of these variables 

with sex, barometric pressure, 

temperature at test time, indicator 

variables for field technician and 

spirometer 

Dose-response Investigated? Yes 

Statistical Package: SAS (10) 

Pollutant: PM10

Averaging Time: Annual 24-h avg 

Mean (SD): The avg levels were 

presented in an online data supplement 

(Fig E1) 

Monitoring Stations: 12 

Copollutant (correlation): 

O3 (10 AM to 6 PM) r = 0.13 

O3 r = -0.37 

NO2 r = 0.64 

Acid vapor r = 0.79 

PM2.5 r = 0.95 

PM10-2.5 r = 0.95 

EC r = 0.86 

OC r = 0.97 

PM Increment: 51.5 μg/m3

Association Estimate: 

None of the pulmonary function tests 

had a statistically significant correlation 

with PM10

FEV1 r = -0.12 p = 0.63 

MMEF r = -0.22 p = 0.30 

December 2009 E-386 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Gauderman et al. (2004, 

056569) 

Period of Study: Air pollution data 

ascertainment: 1994-2000. Spirometry 

testing: Spring 2001-Spring 2003 

Location: 12 Communities in Southern 

California 

Outcome: Lung function 

FVC, FEV1, MMEF (Maximal 

midexpiratory flow rate) 

Age Groups: Children, Avg age 10 yr 

Study Design: Prospective Cohort 

Study

N: 12 Communities 

2,034 Children 

24,972 child-months 

Statistical Analyses: Linear regression 

of changes in sex-and-community 

specific lung growth function and PM 

Covariates: Random effect for 

communities 

Season: ALL (except for PM2.5) 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24-h measurements 

over each yr used to create annual avg 

Mean: Means are presented in figures 

only. 

Range (Min, Max): ~15, ~65 

Monitoring Stations: 12 

Copollutant (correlation): 

O3: r = 0.18 

NO2: r = 0.67 

PM2.5: r = 0.95 

EC: r = 0.85 

OC: r = 0.97 

PM Increment: Most to least polluted 

community 

Range: 

PM10: 51.4 μg/m3 

EC: 1.2 μg/m3 

OC: 10.5 μg/m3

Difference in Lung Growth [Lower CI, 

Upper CI]; 

FVC -60.2 (-190.6 to 70.3) 

FEV1 -82.1 (-176.9 to 12.8) 

MMEF -154.2 (-378.3 to 69.8) 

EC: 

FVC -77.7 (-166.7 to 11.3) 

FEV1 -87.9 (-146.4 to -29.4) 

MMEF -165.5 (-323.4 to -7.6) 

OC: 

FVC -58.6 (-196.1 to 78.8) 

FEV1 -86.2 (-185.6 to 13.3) 

MMEF -151.2 (-389.4 to 87.1) 

Correlation with % below 80% predicted 

Lung function (p-value) 

PM10: 0.66 (0.02) 

EC: 0.74 (0.006) 

Reference: Gauderman et al. (2007, 

090121) 

Period of Study: 1993-2004 

Location: 12 Southern California 

Communities 

Outcome: pulmonary function tests 

FVC, FEV1, MMEF/FEF25.75 

Age Groups: Children (mean age 10 at 

recruitment, followed for 8 yr) 

Study Design: Cohort Study 

(Children’s Health Study)

N: 3677 children 

(1718 in cohort 1 recruited 1993 and 

1959 in cohort 2 recruited 1996) 

22686 pulmonary function tests. 

Statistical Analyses: Hierarchical 

mixed effects model with linear splines 

Covariates: Adjustments for height, 

height squared, BMI, BMI squared, 

present asthma status, exercise or 

respiratory illness on day of test, 

smoking in previous yr, field technician, 

traffic indicator (distance from freeway, 

distance from major roads), random 

effects for participant and community. 

Dose-response Investigated? no 

Statistical Package: SAS 

Pollutant: PM10

Monitoring Stations: 1 in each 

community 

PM Increment: 51.4 μg/m3

Pollutant effect reported as difference in 

8 yr lung function growth from least to 

most polluted community. Negative 

difference indicates growth deficits 

associated with exposure. For PM10

FEV growth deficit is -111 

December 2009 E-387 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Goss et al. (2004, 055624) 

Period of Study: 1999-2000 

Location: USA 

Outcome: Cystic Fibrosis pulmonary 

exacerbations, FEV1

Age Groups: > 6 

Study Design: Cohort

N: 11484 patients 

Statistical Analyses: Logistic 

regression, t-tests, Mann-Whitney tests, 

Chi-squared tests, polytomous 

regression, multiple linear regression 

Covariates: Age, sex, lung function, 

weight, insurance status, pancreatic 

insufficiency, airway colonization, 

genotype, median household income by 

census tract, zipcode. 

Dose-response Investigated? No 

Statistical Package: STATA, SAS 

Pollutant: PM10

Averaging Time: Annual mean of 24-h 

avg 

Mean (SD): 24.8(7.8) mg/m3

Percentiles: 25th: 20.3 

50th(Median): 24.0 

75th: 28.9 

Monitoring Stations: 626 

PM Increment: 10 μg/m3

Odds Ratio Estimate [Lower CI, 

Upper CI]: 

Odds of having 2 or more pulmonary 

exacerbations as compared to 1 or less 

in 2000 

1.08 (1.02 -1.15) 

Odds of having 2 or more pulmonary 

exacerbations as compared to no 

exacerbations in 2000 

1.09 (1.02 -1.17) 

Decrease in FEV1 38ml(18-58) 

Reference: Hanigan et al, (2008, 

156518) 

Period of Study: Fire Season (AprNov) from 1996-2005 

Location: Darwin, Australia 

Outcome: Respiratory admissions 

Study Design: Time-series 

Covariates: Race, age 

Statistical Analysis: Over-dispersed 

Poisson generalized linear models 

Statistical Package: R 

Age Groups: All 

Pollutant: PM10

Averaging Time: Daily levels estimated 

from visibility data 

Mean Unit: *Only reported for 2005* 

15.31 μg/m3

Range (Min, Max): 6.93, 31.12 

Copollutant (correlation): NR 

Increment: 10 μg/m3

Percent Increase (95% CI) 

*Full results reported visually in Fig 3* 

Total Respiratory Admissions 

4.81 % (-1.04-11.01) 

Indigenous Respiratory Admissions, No 

Lag 

9.40% (1.04-18.46) 

Non-Indigenous Respiratory 

Admissions, No Lag 

3.14% (-2.99-9.66) 

Indigenous Respiratory Admissions, 

Lag 3 

15.02% (3.73-27.54) 

Non-Indigenous Respiratory 

Admissions, Lag 3 

0.67% (-7.55-9.61) 

Indigenous Asthma Admissions, Lag 1 

16.27% (3.55-40.17) 

Non-Indigenous Asthma Admissions, 

Lag 1 

8.54% (-5.60-24.80) 

Reference: Ho et al. (2007, 093265) 

Period of Study: Oct 1995-Mar 1996 

Location: Taiwan, Republic of China 

Outcome: Asthma 

Age Groups: 10-17 yr 

Study Design: Screened junior high 

students for asthma, collected 

meteorological data to determine the 

relationship. 

N: 69,367 

Statistical Analyses: Logistic 

regression model, the maximum 

likelihood estimation with Fisher’s 

scoring algorithm, stepwise regression 

model, Wald statistic, Akaike criteria. 

GEE, GENMOD 

Covariates: Wind, barometric pressure, 

temperature, rain, humidity

Season: Fall-spring 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: Monthly 

Monitoring Stations: 72 

Odds Ratio from stepwise regression 

model: 

Females (n = 32, 648) 

0.993 [0.990-0.997] 

Males: NS 

Higher PM10 concentration resulted in 

less asthma prevalence. However, a 

higher number of rain days seemed to 

reduce asthma prevalence 

Rain days might interact with PM10. 

December 2009 E-388 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hong et al. (2004, 156565) 

Period of Study: 2001 

Location: Kerinci, SP7, and Pelalawan, 

Indonesia 

Outcome: Respiratory symptoms 

Age Groups: <12 yr 

Study Design: Disproportionate 

random sampling was used to select 

100 households from each village. An 

interviewer interviewed all children 

through the caregiver/parent to obtain 

symptoms in the past 2 wk (cough, cold, 

phlegm) and the last 12 mo. 

N: 382 children 

Statistical Analyses: Chi-square test, 

analysis of variance, prevalence rates, 

adjusted odds ratios, multivariate 

adjusted odds ratios from multiple 

logistic regression models, allowing for 

clustering. 

Covariates: Age, gender, no. of 

children in household, household 

income, floor area of house, fuel for 

cooking, no. of smokers in household, 

personal and family medical history. 

Dose-response Investigated? No 

Statistical Package: SPSS STATA v.7 

Pollutant: PM10

Averaging Time: 24-h measurements 

were taken daily from 2 wk before he 

field survey to 1 mo after the survey 

Mean (SD): 

Kerinci 102.9 (49.6) μg/m3

SP7 73.7 (41.7) 

Pelalawan 26.1 (14.5) 

P<0.01 

Range (Min, Max): 

Kerinci 25, 184 

SP7 13, 138 

Pelalawan 10, 66 

Monitoring Stations: 3 

PM Increment: Low (Pelalawan), 

Medium (SP7), & High (Kerinci) PM 

Exposure 

Odds Ratios (95% CI) for Symptoms 

by village: 

Cough/cold past 2 wks 

Pelalawan 1.00 

SP7 2.03 (1.04, 3.96) 

Kerinci 3.17 (1.43, 7.07) 

Respiratory symptoms last 12 mo 

Pelalawan 1.00 

SP7 1.15 (0.58, 2.26) 

Kerinci 1.42 (0.62, 3.25) 

Ever had rhinitis w/o flu 

Pelalawan 1.00 

SP7 2.17 (0.57, 8.29) 

Kerinci 0.56 (0.11, 2.83) 

Ever had wheezing 

Pelalawan 1.00 

SP7 0.85 (0.35, 2.08) 

Kerinci 1.18 (0.46, 3.01) 

December 2009 E-389 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Horak et al. (2002, 034792) 

Period of Study: 1994-1997 

Location: Lower Austria 

Outcome: 

Lung function growth measured by 

changes in: 

1. FVC (forced vital capacity) 

2. FEV1

3. MEF25-75 (midexpiratory flow 

between 25-75% of the forced vital 

capacity) 

Age Groups: 2-3 grade schoolchildren 

(mean age = 8) 

Study Design: Prospective cohort with 

repeated measures

N: 975 children 

Statistical Analyses: Linear regression 

GEE, nonstationary M-dependent 

correlation structure 

Covariates: Gender, atopy, ETS 

exposure, baseline lung function, first 

height, height difference, school site

Season: Winter, summer 

Dose-response Investigated? No 

Pollutant: PM10

Mean (SD): 

Winter: 21.0 (4.8) 

Summer: 17.4 (2.8) 

Range (Min, Max): 

Winter: 9.4-30.5 

Summer: 11.7-28.9 

Monitoring Stations: 

NR, stations were located in the 

immediate vicinity of each of the 8 

elementary schools 

Copollutant (correlation): 

Winter 

O3: (r = -0.581) 

SO2 (r = 0.520) 

NO2 (r = 0.595) 

Summer 

O3 (r = -0.429) 

SO2 (r = 0.335) 

NO2 (r = 0.412) 

PM Increment: 1 μg/m3

Mean per unit increase in PM (p-value) 

Outcome: difference per day of FVC 

(mL/day) 

Summer: 0.001 (0.938) 

Winter: 0.008 (0.042) 

Controlling for temperature: 

Summer: -0.007 (0.417) 

Winter: -0.003 (0.599) 

Controlling for O3: 

Summer: 0.001 (0.911) 

Winter: 0.010 (0.019) 

Controlling for NO2: 

Summer: -0.018 (0.056) 

Winter: 0.015 (0.000) 

Controlling for SO2: 

Summer: 0.005 (0.575) 

Winter: 0.004 (0.492) 

In non-asthmatic children: 

Summer: -0.003 (0.710) 

Winter: 0.009 (0.030) 

In group not exposed to ETS: 

Summer: 0.014 (0.154) 

Winter: 0.012 (0.0018) 

In group exposed to ETS: 

Summer: 0.022 (0.088) 

Winter: 0.003 (0.656) 

Outcome: difference per day of FEV1

(mL/day) 

Summer: -0.023 (0.003) 

Winter: 0.001 (0.885) 

Controlling for temperature: 

Summer: -0.034 (0.000) 

Winter: -0.011 (0.016) 

Controlling for O3: 

Summer: -0.022 (0.008) 

Winter: 0.004 (0.338) 

Controlling for NO2: 

Summer: -0.038 (0.000) 

Winter: 0.011 (0.005) 

Controlling for SO2: 

Summer: -0.022 (0.010) 

Winter: -0.005 (0.358)

Outcome: difference per day MEF25-75

(mL/day) 

Summer: -0.090 (0.000) 

Winter: -0.008 (0.395) 

Controlling for temperature: 

Summer: -0.112 (0.000) 

Winter: -0.013 (0.295) 

Controlling for O3: 

Summer: -0.087 (0.000) 

Winter: -0.008 (0.434) 

Controlling for NO2: 

Summer: -0.102 (0.000) 

Winter: 0.005 (0.610) 

Controlling for SO2: 

Summer: -0.095 (0.000) 

Winter: -0.011 (0.474) 

December 2009 E-390 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hwang et al. (2006, 

088971) 

Period of Study: 2001 

Location: Taiwan 

Outcome: Peak expiratory flow rate 

(PEFR), Forced Expiratory Volume in 1 

second (FEV1), Forced Vital Capacity 

(FVC), Self reported “frequent 

coughing,” Self reported “shortness of 

breath,” Self reported “ irritation of 

respiratory tract” 

Age Groups: 24-55 yr (mean = 40) 

Study Design: Cohort

N: 120 men (60 traffic policemen and 

60 controls) 

Statistical Analyses: ANOVA, odds 

ratios calculated from 2X2 table 

Dose-response Investigated? No 

Pollutant: PM10

Mean (SD): 55.58 (16.57) 

Percentiles: 25th: 42.96 

50th(Median): 53.81 

75th: 70.37 

Range (Min, Max): 29.36, 99.58 

Monitoring Stations: 22 

Copollutant (correlation): 

NOX (r = 0.34) 

SO2 (r = 0.58) 

CO (r = 0.27) 

O3 (r = 0.28) 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

Single pollutant model: 1.00 [0.99, 1.02]

Controlling for NOX: 0.99 [0.97, 1.00] 

Controlling for CO: 1.00 [0.99, 1.01] 

Controlling for O3: 1.00 [0.99, 1.02] 

Reference: Hwang et al, (2008, 

134420) 

Period of Study: 2001-2003 

Location: Taiwan 

Outcome: Oral Cleft 

Study Design: Case-control 

Covariates: Maternal age, plurality, 

gestational age, population density and 

season of conception 

Statistical Analysis: Logistic 

regression 

Age Groups: Infants 

Pollutant: PM10

Averaging Time: hourly 

Mean (SD) Unit: 

Avg: 54.83 ± 13.07 μg/m3

Spring: 64.44 ± 16.21 μg/m3

Summer: 39.11 ± 8.31 μg/m3

Fall: 47.76 ± 11.77 μg/m3

Winter: 68.00 ± 21.88 μg/m3 

Range (Min, Max): 

Avg: 20.75-78.05 μg/m3

Spring: 23.33-94.33 μg/m3

Summer: 17.33-60.00 μg/m3

Fall: 21.00-72.00 μg/m3

Winter: 21.33-116.00 μg/m3 

Copollutant (correlation): 

CO: -0.19 

NOX: 0.56 

O3: 0.39 

SO2: 0.50 

Increment: 10 μg/m3

Odds Ratio (Min CI, Max CI); 

Single Pollutant Model 

Month 1: 1.01 (0.96-1.06) 

Month 2: 1.00 (0.95-1.05) 

Month 3: 0.99 (0.95-1.05) 

Two Pollutant Model (O3 + PM10) 

Month 1: 0.99 (0.94-1.04) 

Month 2: 0.99 (0.94-1.04) 

Month 3: 0.98 (0.93-1.04) 

Two Pollutant Model (CO + PM10) 

Month 1: 1.01 (0.96-1.06) 

Month 2: 1.00 (0.95-1.05) 

Month 3: 0.99 (0.95-1.05) 

Two Pollutant Model (NOX + PM10) 

Month 1: 1.02 (0.97-1.08) 

Month 2: 1.01 (0.95-1.07) 

Month 3: 1.01 (0.95-1.07) 

Three Pollutant Model (O3 + CO + 

PM10) 

Month 1: 0.99 (0.94-1.04) 

Month 2: 0.99 (0.94-1.04) 

Month 3: 0.99 (0.93-1.04) 

Three Pollutant Model (O3 + NOX + 

PM10) 

Month 1: 1.00 (0.94-1.06) 

Month 2: 0.98 (0.92-1.05) 

Month 3: 1.00 (0.93-1.06) 

December 2009 E-391 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ingle et al. (2005, 089014) 

Period of Study: May 2003-Apr 2004 

Location: Jalgaon City, India 

Outcome: Peak expiratory flow rate 

(PEFR), Forced Expiratory Volume in 1 

second (FEV1), Forced Vital Capacity 

(FVC), Self reported “frequent 

coughing,” Self reported “shortness of 

breath,” Self reported “ irritation of 

respiratory tract” Age Groups: 24-55 yr 

(mean = 40) 

Study Design: Cohort

N: 120 men (60 traffic policemen and 

60 controls) 

Statistical Analyses: ANOVA, odds 

ratios calculated from 2X2 table 

Dose-response Investigated? No 

Pollutant: PM10

Mean (SD): Location-specific means: 

Prabhat: 224 (27) 

Ajanta: 269 (41) 

Icchdevi: 229 (24) 

Monitoring Stations: 3 

OR Estimate [p-value] 

Self reported frequent coughing 

2.96 [p < 0.05] 

Self reported shortness of breath 

1.22 [p < 0.05] 

Self reported irritation in respiratory 

tract 

7.5 [p < 0.05] 

Observed/expected lung function 

p-value for difference between groups: 

FVC (L) 

Traffic policemen: 0.82 

Controls: 0.99 

Traffic policemen: 

Obs = 3.03 ± 1.7 Exp = 3.70 ± 2.8 

Controls: 

Obs = 3.18 ± 0.91 Exp = 3.19 ± 1.71 

FEV1 (L) 

Traffic policemen: 0.73 

Controls: 1.18 

Traffic policemen: 

Obs = 2.27 ± 1.05 Exp = 3.08 ± 2.7 

Controls: 

Obs = 3.61 ± 0.90 Exp = 3.06 ± 0.91 

PEFR (L/s) 

Traffic policemen: 0.66 

Controls: 0.92 

Traffic policemen: 

Obs = 6.05 ± 2.15 Exp = 9.21 ± 0.47 

Controls: 

Obs = 5.54 ± 1.85 Exp = 6.11 ± 2.31 

Reference: Islam et al. (2007, 090697) 

Period of Study: 2006

Location: 12 California communities 

Outcome: Respiratory symptoms, 

Asthma

Study Design: Longitudinal study 

cohort 

Statistical Analyses: Cox proportional 

hazards regression 

Age Groups: 

7-9 

10-11 

>11 

Pollutants: PM10 

Averaging Time: 24-h avg 

Copollutants (correlation): 

O3

NO2

EC 

OC 

The study doesn’t present quantitative 

results on PM10. 

December 2009 E-392 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Janssen et al. (2003, 

133555) 

Period of Study: Apr 1997-Jul 1998 

Location: Netherlands-24 schools 

Outcome: Symptoms of asthma and 

allergic disease (asthma, conjunctivitis, 

hay fever, itchy rash, eczema, phlegm, 

bronchitis), skin prick test (SPT) 

reaction to allergens, lung function 

(forced vital capacity [FVC], forced 

expiratory volume in 1 second [FEV1], 

and positive test for fall in FEV1 ≥ 15% 

after inhalation of maximal 23 mL 

hypertonic saline [BHR = bronchial 

hyper-responsiveness]) 

Age Groups: 7-12 yr old 

Study Design: Cohort 

N: 24 schools (see notes) 

Statistical Analyses: Multilevel model 

Covariates: Age, sex, non-Dutch 

nationality, cooking on gas, current 

parental smoking, current pet 

possession, parental education level, 

number of persons in the household, 

presence of an unvented water heater 

in kitchen, questionnaire not filled out 

by the mother, presence of mold stains 

in kitchen or living room or bedroom, 

parental respiratory symptoms, distance 

of home to motorway, cough or cold at 

time of lung function measurement, 

bronchitis or severe cold or flu in 3 wk 

preceding measurement, season 

Dose-response Investigated? No 

Statistical Package: MLwiN 

Pollutant: PM2.5

Averaging Time: Annual 

Mean (SD): 20.5 μg/m3 (2.2) 

Percentiles: 

25th: 18.6 

50th (Median): 20.4 

75th: 22.1 

Range (Min, Max): 

17.3, 24.4 

PM Increment: ‘Difference between the 

maximum and the minimum of the 

exposure indicator’ (3.5 μg/m3

) 

RR Estimate [Lower CI, Upper CI] 

lag: 

Current wheeze 1.51 (0.90, 2.53) 

Asthma ever 1.03 (0.59, 1.82) 

Current conjunctivitis 2.08 (1.17, 3.71) 

Hay fever ever 2.28 (1.13, 4.57) 

Current itchy rash 1.63 (0.91, 2.89) 

Eczema ever 1.31 (0.94, 1.83) 

Current phlegm 1.53 (0.74, 3.19) 

Current bronchitis 1.71 (0.84, 3.50) 

Elevated total IgE 1.45 (0.74, 2.84) 

Any allergen (spt reactivity) 1.33 (0.83, 

2.11) 

Indoor allergens (spt reactivity) 1.17 

(0.70, 1.94) 

Outdoor allergens (spt reactivity) 1.90 

(1.06, 3.40) 

FVC < 85% predicted 0.54 (0.29, 1.00) 

FEV1 < 85% predicted 0.88 (0.37, 2.09) 

BHR 0.93 (0.51, 1.68) 

Notes: 

Fig 1 of the article illustrates the 

association between exposures, 

including PM2.5, and various respiratory 

symptoms among children with and 

without a positive SPT and positive 

BHR. In general, the association 

between PM2.5 and respiratory 

symptoms were higher for children with 

a positive SPT or BHR, except for the 

outcome of current phlegm. This effect 

appeared to be the strongest for 

children with a positive BHR, 

particularly for current wheeze and 

current bronchitis. 

The authors also reported separate 

analyses for children with SPT reactivity 

for indoor and outdoor allergens, but did 

not report any clear differences 

between the two groups. The authors 

did report, in the text, that the OR of 

PM2.5 exposure for children sensitized 

for outdoor allergens was 7.64 for 

current itchy rash (p < 0.05). 

December 2009 E-393 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kan, et al. (2007, 091383) 

Period of Study: 1987-1992 

Location: Four Communities in the 

U.S.: Forsyth County, North Carolina 

Jackson, Mississippi 

northwest suburbs of Minneapolis, 

Minnesota 

and Washington County, Maryland. 

Outcome: FEV1 and FVC 

Age Groups: Middle-aged (mean age 

was 54.2 yr) 

Study Design: Hierarchical regression 

N: 15,792 

Statistical Analyses: SAS PROC 

MIXED 

Covariates: Distance to major roads, 

traffic exposure, age, ethnicity, sex, 

smoking, environmental tobacco smoke 

exposure, occupation, education, 

medical history, BMI. 

Dose-response Investigated? No 

Statistical Package: 

SPSS Version 11 for traffic density, 

SAS Version 9.1.2 for statistical 

analysis 

Pollutant: PM10

Averaging Time: 24-h PM10 averaged 

over study period 

PM Component: Vehicle emissions 

Monitoring Stations: 0 

Copollutant: 

NO2 

O3

RR Estimate (Lower CI, Upper CI): 

(Note: for ARIC participants living <150 

meters from major roads)

Women 

FEV1(mL) 

Age-adjusted model 

-29.5 (-52.2 to -6.9) 

Multivariate model 

-15.7 (-34.4 to -2.9) 

FVC (mL) 

Age-adjusted model 

-33.2 (-60.4 to -5.9) 

Multivariate model 

-24.2 (-46.2,-2.3) 

FEV1/FVC (%) 

Age-adjusted model 

-0.1(-0.5,0.2) 

Multivariate model 

0.1 (-0.3,0.4) 

Men 

FEV1(mL) 

Age-adjusted model 

-38.4 (-76.7,0.6) 

Multivariate model 

-6.4 (-38.1,25.3) 

FVC (mL) 

Age-adjusted model 

-17.0(-62.0,28.0) 

Multivariate model 

10.9(-24.7,46.5) 

FEV1/FVC (%) 

Age-adjusted model 

-0.05 (-0.9,0.0) 

Multivariate model 

-0.3 (-0.7,0.2) 

Reference: Kim et al. (2005, 087418) 

Period of Study: Mar and Dec 2000 

Location: Incheon & Ganghwa, Korea 

Outcome: Lung function (FEV1, FVC) 

Age Groups: Middle school students 

Study Design: Panel

N: 368 children 

Statistical Analyses: Generalized liner 

model 

Covariates: Gender, grade

Season: Spring and fall 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: Monthly 

Mean (SD): 

Incheon 

Mar 64 

Dec 54 

Ganghwa 

Mar 64 

Dec 53 

Range (Min, Max): NR 

PM Increment: NR 

OR Estimate [Lower CI, Upper CI]: 

‘‘The present study showed that the 

values of FEV1 and FVC were greater in 

Dec than in Mar for both male and 

female students at all academic 

yr...Because only the level of PM10 was 

significantly higher for Mar than for Dec 

in both areas, the authors suggest that 

decrements of pulmonary function in 

Mar for both areas are associated with 

the increased level of PM10‘‘ 

Reference: Kim et al. (2004, 087383) 

Period of Study: Mar-Jun (spring) 

2001 

Sep-Nov (fall) 2001 

Location: Alameda County, CA 

Outcome: Asthma, bronchitis 

Age Groups: Children (in grades 3-5) 

Study Design: Cross-sectional

N: 1109 children, 871 (long term 

resident children), 462 (long term 

related females), 403 (long term related 

males) 

Statistical Analyses: 2-stage multiple 

logistic regression model 

Covariates: Respiratory illness before 

age of 2, household mold/moisture, 

pests, maternal history of asthma (for 

asthma) Season: Spring and fall 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.2 

Pollutant: PM10

Averaging Time: 9 wk 

Mean (SD): Study Avg 30 

Monitoring Stations: 10 

Copollutant (correlation): r2 is 

approximately 0.9 for all copollutants –

BC, PM2.5, NOX, NO2, NO (NOX-NO2) 

PM Increment: 1.4 (IQR) 

OR Estimate [Lower CI, Upper CI]: 

Bronchitis 

All subjects: 1.03 [0.99, 1.07] 

LTR subjects: 1.02 [0.98, 1.07] 

LTR females: 1.04 [1.01, 1.09] 

LTR males: 1.01 [0.95, 1.06] 

Asthma 

All subjects: 1.02 [0.96, 1.09] 

LTR subjects: 1.04 [0.97, 1.12] 

LTR females: 1.09 [0.92, 1.29] 

LTR males: 1.02 [0.94, 1.10] 

Asthma excluding outlier school having 

a larger proportion of Hispanics 

All subjects: 1.06 [0.97, 1.16] 

LTR subjects: 1.08 [0.98, 1.19] 

LTR females: 1.09 [0.96, 1.24] 

LTR males: 1.08 [0.97, 1.19] 

December 2009 E-394 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kumar et al. (2004, 

089873) 

Period of Study: 1999-2001 

Location: Mandi Gobindgarh and 

Morinda, Punjab State, northern India 

Outcome: Chronic respiratory 

symptoms & Spirometric ventilatory 

defect 

Age Groups: >15 yr 

Study Design: Cross-sectional 

N: 3603 individuals 

Statistical Analyses: Logistic 

regression 

Covariates: Age, gender, migration, 

SES, smoking, type of cooking fuel use 

Dose-response Investigated? No 

Pollutant: PM10

Mean (SD): Study town 112.8 (17.9) 

Reference town 75.8 (2.9) 

PM10 Increment: 

Low vs. High 

OR (Lower CI, Upper CI) 

p-value 

Chronic respiratory symptoms 

Low 1.00 (ref) 

High 1.5 (1.2, 1.8) 

<0.001 

Spirometric ventilatory defect 

Low 1.00 (ref) 

High 2.4 (2.0-2.9) 

<0.001 

Reference: Leonardi et al. (2000, 

010272) 

Period of Study: 1996 

Location: 17 cities of Central Europe 

(Bulgaria, Czech Republic, Hungary , 

Poland, Romania, Slovakia) 

Outcome: Immune biomarkers 

Age Groups: 9-11 

Study Design: Cross-sectional 

N: 366 school children 

Statistical Analyses: Linear regression

Covariates: Age, gender, parental 

smoking, laboratory of analysis, recent 

respiratory illness 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM10

Averaging Time: Annual PM10

Mean (SD): PM10: 65 (14) 

Range (Min, Max): 

PM10: (41, 96) 

5th, median, & 95th percentile 

PM10: 41, 63, 90 

% Change (Lower CI, Upper CI) 

p-value 

PM10

Neutrophils -5 (-33, 36) 

>.20 

Total lymphocytes 20 (-6, 54); .150 

B lymphocytes 42 (-3, 107); .067 

Total T lymphocytes 30 (-2, 73); .072 

CD4+ 28 (-10, 82); .177 

CD8+ 29 (-5, 75); .097 

CD4/CD8 7 (-20, 43) 

>.20 

NK 33 (-10, 97); .157 

Total IgG 11 (-10, 38) 

>.20 

Total IgM 5 (-21, 39) 

>.20 

Total IgA11 (-16, 46) 

>.20 

Total IgE -8 (-62, 123) 

>.20 

Reference: Lichtenfels et al, (2007, 

097041) 

Period of Study: 2001-2003 

Location: São Paulo, Brazil 

Outcome: Secondary sex ratio 

Study Design: Retrospective Cohort 

Covariates: NR 

Statistical Analysis: Correlation 

Coefficient 

Age Groups: Infants 

Pollutant: PM10

Averaging Time: Annual 

Mean (SD) Unit: 

2001: 49.8 (10.5) μg/m3

2002: 48.5 (11.4) μg/m3

2003: 49.4 (14.4) μg/m3

Range (Min, Max): 31.71-60.96 μg/m3

Copollutant (correlation): NR 

Increment: NR 

Correlation Coefficient: 

R2 = 0.7642, P = 0.13 

Reference: Lubinski, et al. (2005, 

087563) 

Period of Study: 1993-1997 

Location: Poland 

Outcome: Pulmonary function 

TLC: total lung capacity 

ITGV: interthoracic gas volume 

ITGV%TLC: ITGV percent total lung 

capacity 

Raw: airway resistance 

FVC: forced vital capacity 

FEV1: forced expiratory volume, 1 

second 

FEV1%FVC: FEV1 percent forced vital 

capacity 

PEF: peak expiratory flow 

FEF50: forced expiratory flow 

Age Groups: 18-23 males, healthy 

Study Design: Ecological crosssectional study

N: 1278 subjects 

Statistical Analyses: Multiple linear 

regression, ANOVA 

Covariates: Report unclear on whether 

or not there was covariate control, but 

may include NO2 and SO2

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 12 mo 

Mean (SD): 

A: Highest Pollution Region 

Katowice 67-125 

Krakow 41-49 

B: Moderate Pollution Region 

Bielsko-Biala 29-48 

Opole 18-45 

Lodz 23-38 

Warsaw 35-45 

Wroclaw 28-76 

Zagan 5-35 

C: Lowest Pollution Region 

Gizycko 5-18 

Hel 12-18 

Ostroda 23-33 

Swinoujscie 7-16 

Ustka 12-26 

Copollutant: NO2, SO2

PM Increment: 1 μg/m3

Slope, multiple regression 

TLC 

PM10: -0.05 

+SO2: 0.03 

+NO2: -0.06 

ITGV 

PM10: 0.01 

+SO2: -0.07 

+NO2: -0.07 

ITGV%TLC 

PM10: -0.06 

+SO2: 0.08 

+NO2: 0.00 

Raw 

PM10: 0.075 

+SO2: -0.08 

+NO2: 0.127 

FVC 

PM10: 0.045 

+SO2: 0.045 

+NO2: -0.14 

FEV1

PM10: 0.031 

+SO2: -0.08 

+NO2: -0.12 

FEV1%FVC 

PM10: 0.00 

+SO2: -0.14 

+NO2: -0.048 

PEF 

PM10: -0.18 

+SO2: 0.056 

+NO2: -0.09 

FEF50 

PM10: 0.031 

+SO2: -0.11 

+NO2: -0.04 

December 2009 E-395 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: McConnell et al. (1999, 

007028) 

Period of Study: 1993 

Location: Southern California 

Outcome: Bronchitis, chronic cough, 

phlegm 

Age Groups: Children: 4th, 7th, & 10th 

graders 

Study Design: Cross-sectional

N: 3676 people 

Statistical Analyses: Logistic 

regression 

Covariates: Age, sex, race, grade, 

health insurance 

Dose-response Investigated? Yes 

Pollutant: PM10

Averaging Time: Yearly avg 24 h PM10

Mean (SD): 34.8 

Range (Min, Max): 13.0, 70.7 

Copollutant (correlation): 

NO2 r = 0.74 

O3 r = 0.32 

Acid r = 0.54 

PM2.5 r = 0.90 

NO2 r = 0.83 

O3 r = 0.50 

Acid r = 0.71 

PM10 Increment: 19 μg/m3

Children w/ asthma 

Bronchitis: 1.4 (1.1,1.8) 

Phlegm: 2.1 (1.4, 3.3) 

Cough: 1.1 (0.8, 1.7) 

Children w/ wheeze, no asthma 

Bronchitis: 0.9 (0.7, 1.3) 

Phlegm: 0.9 (0.6, 1.4) 

Cough: 1.2 (0.9, 1.8) 

Children w/ no wheeze, no asthma 

Bronchitis: 0.7 (0.4, 1.0) 

Phlegm: 0.8 (0.6, 1.3) 

Cough: 0.9 (0.7, 1.2) 

Reference: McConnell et al. (2003, 

049490) 

Period of Study: 1993-1999 

Location: 12 Southern CA communities 

Outcome: Bronchitis symptoms 

Age Groups: 9-19 

Study Design: Communities selected 

on basis of historic levels of criteria 

pollutants and low residential mobility.

N: 475 children 

Statistical Analyses: 3 stage 

regression combined to give a logistic 

mixed effects model 

Covariates: Sex, ethnicity, allergies 

history, asthma history, SES, insurance 

status, current wheeze, current 

exposure to ETS, personal smoking 

status, participation in team sports, in 

utero tobacco exposure through 

maternal smoking, family history of 

asthma, amount of time routinely spent 

outside by child during 2-6 pm. 

Dose-response Investigated? No 

Statistical Package: SAS Glimmix 

macro 

Pollutant: PM10

Averaging Time: 4-yr avg 

Mean (SD): .30.8(13.4) μg/m3

Range (Min, Max): 15.7-63.5 

PM Component: particulate OC and EC 

Copollutant (correlation): 

PM2.5: r = 0.79 

PM10-2.5: r = 0.79 

Inorganic acid: r = 0.72 

Organic Acid: r = 0.59 

EC: r = 0.71 

OC: r = 0.70 

NO2: r = 0.20 

O3: r = 0.64 

PM Increment: 

Between community range 47.8 μg/m3

Between community unit 1 μg/m3

Within community 1 μg/m3

OR Estimate [Lower CI, Upper CI] 

Between community per range 

1.72(0.93-3.20)| 

Between Community per unit 1.01(1.00-

1.02)| 

Within community per unit 1.04(0.99-

1.10) 

Reference: McConnell et al. (2002, 

023150) 

Period of Study: 1993-1998 

Location: 12 communities in Southern 

California (grouped into either high and 

low pollution communities) 

Outcome: Asthma (new diagnosis) 

Age Groups: 9-12 yr, 12-13 yr, 15-16 yr

Study Design: Cohort 

N: 3535 

Statistical Analyses: Multivariate 

proportion hazard model 

Covariates: Sex, age, ethnic origin, 

BMI, child history of allergies and 

asthma history, SES, maternal smoking, 

time spent outside, history of wheezing, 

ownership of insurance (yes/no), 

number and type of sports played 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.1 

Pollutant: PM10

Averaging Time: 4 yr 

Mean (SD): Low pollution communities: 

21.6 (3.8) 

High pollution communities: 43.3 

(12.0) 

Percentiles: Low pollution 

communities: 50th(Median): 20.8 

High pollution communities: 

50th(Median): 43.3 

Range (Min, Max): Low pollution 

communities: 16.62, 27.3 

High pollution communities: 33.5, 66.9 

Monitoring Stations: 12 

Copollutant (correlation): 

PM2.5: r = 0.96 

NO2: r = 0.65 

O3

RR Estimate [Lower CI, Upper CI] 

lag: 

Low PM communities: 1.0 [ref] 0 sport 

1.5 [1.0, 2.2] 1 sport 

1.2 [0.7, 1.9] 2 sports 

1.7 [0.9, 3.2] ≥ 3 sports 

High PM communities: 1.0 [ref] 0 sport 

1.1 [0.7, 1.7] 1 sport 

0.9 [0.5, 1.7] 2 sports 

2.0 [1.1, 3.6] ≥3 sports 

High vs. Low PM10 communities: 0.8 

(0.6, 1.0) 

Incidence-N (incidence) number of 

sports: 

Low PM communities: 49 (0.023) 0 

54 (0.032) 1 

22 (0.024) 2 

13 (0.033) ≥3 

High PM communities: 55 (0.021) 0 

36 (0.021) 1 

14 (0.018) 2 

16 (0.033) ≥3 

December 2009 E-396 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: McConnell, et al. (2006, 

180226) 

Period of Study: 1996-1999 

Location: 12 Southern California 

communities 

Outcome: Prevalence of bronchitic 

symptoms (yrly). 

Age Groups: 10-15-yr-old 

Study Design: Longitudinal cohort

N: 475 asthmatic children 

Statistical Analyses: Multilevel logistic 

mixed effects models. 

Covariates: Age, second-hand smoke 

Personal smoking history 

Sex, race. 

Dose-response Investigated? No 

Statistical Package: SAS with 

GLIMMIX macro 

Pollutant: PM10

Averaging Time: 365 days 

Percentiles: Community by yr 

(n = 48 = 12 communities · 4 yr) 

25th: NR 

50th(Median): 3.4 

75th: NR 

Range (Min, Max): 

Community by yr (n = 48 = 12 

communities · 4 yr): 

(0.89, 8.7) 

Monitoring Stations: 12 

Copollutant: O3, NO2, EC, OC, 

Acid vapor (acetic and formic acid) 

PM Increment: 6.1 μg/m3

OR Estimate [Lower CI, Upper CI] 

PM10

Dog (n = 292): 1.60 [1.12: 2.30] 

No dog (n = 183): 0.89 [0.57: 1.39] 

PM10*Dog interaction p-value: 0.02 

Cat (n = 202): 1.47 [0.96: 2.24] 

No Cat (n = 273): 1.20 [0.83: 1.73] 

PM10*Cat interaction p-value: 0.41 

Neither pet (n = 112): 0.91 [0.53: 1.56] 

Cat only (n = 71): 0.84 [0.42: 1.66] 

Dog only (n = 161): 1.41 [0.91: 2.19] 

Both pets (n = 131): 1.89 [1.15: 3.10] 

Results suggest that dog ownership, a 

source of residential exposure to 

endotoxin, may worsen the severity of 

respiratory symptoms from exposure to 

air pollutants in asthmatic children. 

Reference: Meng et al. (2007, 093275) 

Period of Study: Nov 2000 and Sep 

2001 (collection of health data) 

Location: Los Angeles and San Diego 

counties 

Outcome: Poorly controlled asthma vs. 

controlled asthma 

Age Groups: 18-64, 65+ 

Study Design: Long-term exposure 

study 

Comparison of cases and controls 

N: 1,609 adults (represented individuals 

age 18+ who reported ever having been 

diagnosed as having asthma by a 

physician and had their address 

successfully geocoded) 

Statistical Analyses: Logistic 

regression to evaluate associations 

between TD (traffic density) and annual 

avg air pollution concentrations and 

poorly controlled asthma. Used sample 

weights that adjusted for unequal 

probabilities of selection into the CHIS 

sample. 

Covariates: Age, sex, race/ethnicity, 

family federal poverty level, county, 

insurance status, delay in care for 

asthma, taking medications, smoking 

behavior, self-reported health status, 

employment, physical activity 

Dose-response Investigated? yes 

Pollutant: PM10

Averaging Time: 24 h over 1 yr 

Copollutant (correlation): 

O3: r = -0.72 

NO2: r = 0.83 

PM2.5: r = 0.84 

CO: r = 0.42 

TD: r = 0.14 

PM Increment: Continuous data: per 

10 μg/m3

OR Estimate [Lower CI, Upper CI] 

lag: 

All Adults: 1.08 [0.82, 1.43] 

Non-Elederly Adults: 1.14 [0.84, 1.55] 

Elderly: 0.84 [0.41, 1.73] 

Women: 1.38 [0.99, 1.94] 

December 2009 E-397 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Millstein et al. (2004, 

088629) 

Period of Study: Mar-Aug, 1995, and 

Sep 1995-Feb 1996 

Data were taken from the Children’s 

Health Study 

Location: Alpine, Atascadero, Lake 

Arrowhead, Lake Elsinore, Lancaster, 

Lompoc, Long Beach, Mira Loma, 

Riverside, San Dimas, Santa Maria, and 

Upland, CA 

Outcome: Wheezing & asthma 

medication use (ICD9 NR) 

Age Groups: 4th grade students, 

mostly 9 yr at the time of the study 

Study Design: Cohort Study, stratified 

into 2 seasonal groups/

N: 2081 enrolled, 2034 provided parentcompleted questionnaire. 

Statistical Analyses: Multilevel, mixedeffects logistic model. 

Covariates: Contagious respiratory 

disease, ambient airborne pollen and 

other allergens, temperature, sex, age 

race, allergies, pet cats, carpet in home, 

environmental tobacco smoke, heating 

fuel, heating system, water damage in 

home, education level of questionnaire 

signer, physician diagnosed asthma. 

Season: Mar-Aug, 1995, and Sep, 

1995 to Feb, 1996 

Statistical Package: GLIMMIX SAS 

8.00 macro for generalized linear mixed 

models. 

Lags Considered: 14 

Pollutant: PM10

Averaging Time: Monthly means for 

PM10. 

PM Component: Nitric acid, formic 

acid, acetic acid 

Monitoring Stations: 

1 central location in each community 

Copollutant (correlation): 

O3: r = 0.76 

NO2: r = 0.39 

PM2.5: r = 0.91 

PM Increment: IQR 13.39 μg/m3

Odds Ratio [lower CI, Upper CI] 

Annual 

PM10: 0.93 [0.67, 1.27] 

Mar-Aug 

PM10: 0.91 [0.46, 1.80] 

Sep-Feb 

PM10: 0.65 [0.40, 1.06] 

Reference: Neuberger et al. (2004, 

093249) 

Period of Study: Jun 1999-Jun 2000 

Location: Austria (Vienna and a rural 

area near Linz) 

Outcome: Questionnaire derived 

asthma score, and a 1-5 point 

respiratory health rating by parent 

Age Groups: 7-10 yr 

Study Design: Cross-sectional survey 

N: about 2000 children 

Statistical Analyses: Mixed models 

linear regression-used factor analysis to 

develop the “asthma score” 

Covariates: Pre-existing respiratory 

conditions, temperature, rainy days, # 

smokers in household, heavy traffic on 

residential street, gas stove or heating, 

molds, sex, age of child, allergies of 

child, asthma in other family members 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 4 week avg 

(preceding interview) 

Pollutant: PM10

Averaging Time: 24 h 

Copollutant (correlation): 

PM2.5 (r = 0.94) in Vienna 

PM Increment: 10 μg/m3 

Change in mean associated unit 

increase in PM (p-value) lag 

Respiratory Health score 

Vienna: 0.005 (p>0.05) 

lag 4 week avg 

Rural area: 0.008 (p>0.05) 

lag 4 week avg 

Asthma score 

Vienna: 0.006 (p>0.05) 

lag 4 week avg 

Rural area: -0.001 (p>0.05) 

lag 4 week avg 

Reference: Oftedal et al. (2008, 

093202) 

Period of Study: 2001-2002 

Location: Oslo, Norway 

Outcome: Lung function (PEF, 

FEF25%, FEF50%, FEV1, FVC) 

Age Groups: 9-10 yr 

Study Design: Cross-sectional 

N: 1847 children 

Statistical Analyses: Linear regression

Covariates: Height, age, BMI, birth 

weight, temperature, maternal smoking, 

sex 

Dose-response Investigated? Yes 

Statistical Package: 

SPSS, STATA, S-Plus 

Lags Considered: 1-3 

Pollutant: PM10

IQR: 

PM10 in 1st yr of life: 10.3 

PM10 lifetime: 5.8 

PM Increment: Per IQR 

β (Lower CI, Upper CI) 

PM10 in 1st yr of life 

PEF -72.5 (-122.3 to -22.7) 

FEF25% -77.4 (-133.4 to -21.4) 

FEF50% -53.9 (-102.6. to -5.2) 

FEV1 -6.7 (-24.1, 10.7) 

FVC 0.5 (-18.5, 19.6) 

PM10 lifetime exposure 

PEF -66.4 (-109.5 to -23.3) 

FEF25% -61.5 (-110.0 to -13.1) 

FEF50% -45.6 (-87.7 to -3.5) 

FEV1 -7.3 (-22.4, 7.7) 

FVC -2.1 (-18.6, 14.4) 

December 2009 E-398 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Parker et al. (2009, 

192359) 

Period of Study: 1999-2005 

Location: U.S. 

Outcome: Respiratory allergy/hayfever 

Study Design: Cohort 

Covariates: Survey yr, age, family 

structure, usual source of care, health 

insurance, family income relative to 

federal poverty level, race/ethnicity 

Statistical Analysis: Logistic 

regression 

Statistical Package: SUDAAN 

Age Groups: 73,198 children aged 

3-17 yr 

Pollutant: PM10

Averaging Time: NR 

Median: 24.1 μg/m3

IQR: 20.8-28.7 

Copollutant (correlation): 

Summer O3: 0.26 

SO2: -0.19 

NO2: 0.48 

PM2.5: 0.51 

PM10-2.5: 0.86 

Increment: 10 μg/m3

Odds Ratio (95% CI) 

Single Pollutant Model, variable N 

Adjusted: 1.04 (0.99-1.09) 

Reference: Penard-Morand et al. 

(2005, 087951) 

Period of Study: Mar 1999-Oct 2000 

Mean concentrations of NO2, SO2, 

PM10, and O3 were taken from Jan 

1998-Dec 2000 

Location: 6 French cities: Bordeaux, 

Clermont-Ferrand, Creteil, Marseille, 

Strasbourg, Reims. 

Outcome: 

Flexural dermatitis 

Asthma (493) 

Rhinoconjunctivitis 

Atopic dermatitis 

Wheeze 

Allergic rhinitis 

Atopy 

EIB (exercise-induced bronchial 

reactivity) 

Age Groups: 9-11 yr 

Study Design: Cross-sectional

N: 9615 Children (6672 complete 

examination and questionnaire info) 

Statistical Analyses: Logistic 

regression 

Marginal Model (GENMOD) 

Covariates: Age, Sex, Family history of 

allergy, Passive smoking 

Parental education 

Season: All 

Excluding end of spring and during 

summer for clinical examinations 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 3 yr 

Mean (SD): Low concentrations: 26.9 

High Concentrations: 23.8 

Range (Min, Max): 

Low concentrations: 10-20 

High concentrations: 21.5-29.5 

Copollutant (correlation): 

\NO2: r =.46 

SO2: r =.76 

O3: r = -.02 

Monitoring Stations: 16 

PM Increment: 10 μg/m3 (IQR) 

OR Estimate [Lower CI, Upper CI]: 

EIB (during exam): 1.43 (1.02-2.01) 

Flexural dermatitis (during exam): 

0.79 (0.59-1.07) 

Wheeze (past yr): 1.05 (0.72-1.54) 

Asthma (past yr): 1.23 (0.77-1.95) 

Rhinoconjunctivitis (past yr): 

1.17 (0.86-1.59) 

Atopic dermatitis (past yr): 

1.28 (0.96-1.71) 

Asthma (lifetime): 1.32 (0.96-1.81) 

Allergic rhinitis (lifetime): 

1.32 (1.04-1.68) 

Atopic dermatitis (lifetime): 

1.09 (0.88-1.36) 

Atopy (lifetime): 0.98(0.80-1.22) 

Pollen: 1.14 (0.85-1.53) 

Indoor: 0.91 (0.72-1.15) 

Moulds: 1.00 (0.53-1.88) 

Highest correlated pollutant 

adjustments: 

EIB (during exam): 1.16 (0.72-1.85) 

Flexural dermatitis (during exam): 

0.93 0(.60-1.43) 

Wheeze (past yr): 1.31 (0.71-2.36) 

Asthma (past yr): 1.25 (0.66-2.37) 

Rhinoconjunctivitis (past yr): 

1.22 (0.98-1.68) 

Atopic dermatitis (past yr): 

1.63 (1.07-2.49) 

Asthma (lifetime): 1.11 (0.70-1.74) 

Allergic rhinitis (lifetime): 

1.19 (0.94-1.59) 

Atopic dermatitis (lifetime): 

1.47 (1.07-2.00) 

Atopy (lifetime): 0.93(0.69-1.26) 

Pollen: 1.30 (0.98-1.57) 

Indoor: .83 (0.63-1.12) 

Molds: 1.62 (0.64-4.09) 

Reference: Peters et al., (1999, 

087237) 

Period of Study: 1986-1990, 1994 

Location: Southern California 

Outcome: Asthma, cough, bronchitis, 

wheeze 

Age Groups: 4th, 7th, & 10th graders 

Study Design: Cohort

N: 3676 children 

Statistical Analyses: Stepwise logistic 

regression 

Covariates: Community, grade, race, 

sex, height, BMI, asthma in parents, 

hay fever, health insurance, plants in 

home, mildew in home, passive smoke 

exposure, pest infestation, carpet, 

vitamin supplements, active smoking, 

pets, gas stove, air conditioner 

Dose-response Investigated? Yes 

Pollutant: PM10

Averaging Time: 

24-h PM10 averaged over 1994 

Mean based on data collected during 

1986-1990, 1994: 

Alpine 37.4, 21.3 

Atascadero 28.0, 20.7 

Lake Elsinore 59.5, 34.7 

Lake Gregory 38.3, 24.2 

Lancaster 47.0, 33.6 

Lompoc 30.0, 13.0 

Long Beach 49.5, 38.8 

Mira Loma 84.9, 70.7 

Riverside 84.9, 45.2 

San Dimas 67.0, 36.7 

Santa Maria 28.0, 29.2 

Upland 75.6, 49.0 

PM Increment: 25 μg/m3

OR (Lower CI, Upper CI) for 

respiratory illness 

Based on 1986-1990 pollutant levels 

Ever asthma 0.93 (0.76, 1.13) 

Current asthma 1.09 (0.86, 1.37) 

Bronchitis 0.94 (0.74, 1.19) 

Cough 1.06 (0.93, 1.21) 

Wheeze 1.05 (0.89, 1.25) 

Based on 1994 pollutant levels 

Ever asthma 0.87 (0.67, 1.14) 

Current asthma 1.11 (0.81, 1.54) 

Bronchitis 0.90 (0.65, 1.26) 

Cough 1.14 (0.96, 1.35) 

Wheeze 1.01 (0.79, 1.29) 

December 2009 E-399 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Pierse, et al. (2006, 

088757) 

Period of Study: 2 yr (once in 1998 

and once in 2001—surveys) 

Location: Leicestershire, UK 

Outcome: Cough without a cold 

Night time cough 

Current wheeze 

Age Groups: 1-5 yr 

Study Design: Cross-sectional 

(cohorts)

N: 4400 children 

Statistical Analyses: Binomial 

generalized linear models (compared 

with likelihood ratio tests) 

Spatial variograms (due to the spatial 

concerns) 

Covariates: Age, Gender 

Mother/father has asthma 

Coal heating the home, Smoking by 

household member in the home, Either 

parent continued education past 16 yr 

of age, Pre-term birth, Breast feeding, 

Gas cooking, Presence of pets, Number 

of cigarettes smoked by mother, 

Overcrowding, Single parenthood, Diet 

Dose-response Investigated? Yes 

(Fig. 2 shows evidence of doseresponse effect based on surveys, 

states in discussion). 

Statistical Package: SAS 8.2 

S-Plus 6.1 

Pollutant: PM10

Averaging Time: Annual PM10

Mean (SD): 

1998: 1.47 

2001: 1.33 

Percentiles: 

25th: 1998 (.73) and 2001 (.8) 

75th: 1998 (1.93) and 2001 (1.84) 

PM Increment: 10 μg/m3 (IQR) 

Unadjusted OR estimates [Lower CI, 

Upper CI]: 

Cough without cold (1998): 

1.22 (1.10 to 1.36) 

Cough without cold (2001): 

1.46 (1.27 to 1.68) 

Night-time cough (1998): 

1.11 (1.01 to 1.23) 

Night-time cough (2001): 

1.25 (1.09 to 1.43) 

Current wheeze (1998): 

0.99 (0.89 to 1.10) 

Current wheeze (2001): 

1.09 (0.93 to 1.30) 

Adjusted OR Estimate [Lower CI, 

Upper CI]: 

Cough without cold (1998): 

1.21 (1.07 to 1.38) 

Cough without cold (2001): 

1.56 (1.32 to 1.84) 

Night-time cough (1998): 

1.06 (0.94 to 1.19) 

Night-time cough (2001): 

1.25 (1.06 to 1.47) 

Current wheeze (1998): 

0.99 (0.88 to 1.12) 

Current wheeze (2001): 

1.28 (1.04 to 1.58) 

When the child was originally 

asymptomatic in 1998: 

Unadjusted OR estimates [Lower CI, 

Upper CI]: 

Cough without cold (2001): 

1.68 (1.39 to 2.03) 

Night-time cough (2001): 

1.21 (1.00 to 1.46) 

Current wheeze (2001): 

1.22 (0.92 to 1.62) 

Adjusted OR Estimate [Lower CI, 

Upper CI]: 

Cough without cold (2001): 

1.62 (1.31 to 2.00) 

Night-time cough (2001): 

1.19 (0.96 to 1.47) 

Current wheeze (2001): 

1.42 (1.02 to 1.97) 

December 2009 E-400 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Qian et al. (2005, 093283) 

Period of Study: 1990-1992 

Location: Forsythe, NC 

Minneapolis, MN 

Jackson, MS. 

Outcome: FVC, FEV1, FEV1/FVC 

Age Groups: Middle aged (avg 56.8 yr) 

Study Design: Cross-sectional

N: 10,240 people 

Statistical Analyses: Regression 

equations, multiple linear regression 

analyses 

Covariates: Smoking status, recent use 

of respiratory medication, current 

respiratory symptoms, chronic lung 

diseases, field center 

Dose-response Investigated? No 

Statistical Package: SAS software, 

version 9.1 

Pollutant: PM10

Averaging Time: Annual 

Mean (SD): 27.9 (2.8) 

Percentiles: 25th: 25.8 

50th(Median): 27.5 

75th: 30.2 

Range (Maximum-Minimum): 12.2 

Monitoring Stations: 

3 (Minneapolis, MN) 

5 (Jackson, MS) 

and 9 (Forsythe, NC) 

Copollutant: O3

PM Increment: 2.8 μg/m3 (1 SD) 

Effect Estimate: 

In Never Smokers 

FVC ß = -0.0108, SE = 0.0026, 

p =.0001 

FEV1 ß = -0.0082, SE = 0.0029, 

p =.0047 

FEV1/FVC ß = -0.0024, SE = 0.0023, 

p =.2787 

Smoking status 

Current n = 2377, FVC = -1.96, 

FEV1 = -2.23, FEV1/FVC = -0.94 

Former n = 3858, FVC = -1.25, 

FEV1 = -1.10, FEV1/FVC = -0.30 

Never n = 4005, FVC = -1.12, 

FEV1 = -0.63, FEV1/FVC = 0.06 

Recent Use of Respiratory Medication 

Yes n = 424, FVC = -2.65, 

FEV1 = -3.89, FEV1/FVC = -3.00 

No n = 9816, FVC = -1.41, 

FEV1 = -1.20, FEV1/FVC = -0.24 

Current Respiratory Symptoms 

Yes n = 4340, FVC = -1.68, 

FEV1 = -1.70, FEV1/FVC = -0.63 

No n = 5900, FVC = -1.05, 

FEV1 = -0.63, FEV1/FVC = 0.05 

Chronic Lung Diseases 

Yes n = 1374, FVC = -1.95, 

FEV1 = -2.31, FEV1/FVC = -1.18 

No n = 8866, FVC = -1.35, 

FEV1 = -1.10, FEV1/FVC = -0.19 

Field Center 

Forsythe, NC n = 3504, FVC = -0.03, 

FEV1 = 0.05, FEV1/FVC = -0.33 

Minneapolis, MN n = 3793, FVC = 0.50, 

FEV1 = 0.54, FEV1/FVC = -0.30 

Jackson, MS n = 2943, FVC = -0.01, 

FEV1 = 0.17, FEV1/FVC = -0.32 

Reference: Rios et al. (2004, 087800) 

Period of Study: 1998-2000 

Location: the metropolitan area of Rio 

de Janiero, Brazil, Duque de Caxias 

(DC) and Seropedica (SR) 

Outcome: Wheezing, asthma, cough at 

night 

Age Groups: 13-14 yr 

Study Design: Cohort 

N: 4064 students 

Statistical Analyses: Cchi-squared 

Covariates: Sex, type of school, time of 

residence, domestic smoking, residents 

per home 

Dose-response Investigated? Yes 

Statistical Package: EpiInfo 

Pollutant: PM10

Averaging Time: Weekly 

measurements used to create annual 

PM estimate 

Mean (SD): 

DC 

1998: 147 

1999: 115 

2000: 110 

Total: 124 

SR 

1998: 37 

1999: 31 

2000: 37 

Total: 35 

Monitoring Stations: NR 

PM Increment: High vs. Low 

Global Cut-Off Score %, p-val: 

DC 

Male: 15.0 

Female: 22.3, p < .05† 

Private School: 16.6 

Public School: 19.4, p < .05* 

<5yr residence: 20.9 

>5yr residence: 16.8 

No domestic smoking exposure: 17.6 

Domestic smoking exposure: 20.4, p < 

.05† 

<5 residents per home: 18.4 

5+ residents per home: 19.5 

SR 

Male: 12.3 

Female: 19.7, p < .05† 

Private School: 28.3, p < .05*† 

Public School: 14.7 

<5yr residence: 10.8 

>5yr residence: 16.5 

No domestic smoking exposure: 14.8 

Domestic smoking exposure: 18.3 

<5 residents per home: 15.6 

5+ residents per home: 17.4 

Notes: The Global Cut-off Score 

encompasses replies to the asthma 

component of ISAAC’s written 

questionnaire that establishes a cut-off 

from which is defined the presence of 

asthma for the Brazilian population. 

*Comparing the cities in the same 

controlled variable 

†Comparing the controlled variable in 

the same city 

December 2009 E-401 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rojas-Martinez et al. (2007, 

091064) 

Period of Study: 1996-1999 

Location: Mexico City, Mexico 

Outcome: Lung function: FEV1, FVC, 

FEF25-75% 

Age Groups: Children 8 yr old at time 

of cohort recruitment 

Study Design: School-based “dynamic” 

cohort study 

N: 3170 children 

14,545 observations 

Statistical Analyses: Three-level 

generalized linear mixed models with 

unstructured variance-covariance matrix

Covariates: Age, body mass index, 

height, height by age, weekday spent 

outdoors, environmental tobacco 

smoke, previous-day mean air pollutant 

concentration, time since first test 

Dose-response Investigated? No 

Statistical Package: SA 

Pollutant: PM10

Averaging Time: 6 mo 

Mean (SD): 6-mo averaging 

SD: NR 

Mean: 75.6 

Percentiles: 6-mo averaging 

25th: 55.8 

50th(Median): 67.5 

75th: 92.2 

Monitoring Stations: 5 sites for PM10, 

10 for other pollutants 

Copollutant: 

O3

NO2

PM Increment: IQR 6-LC: 36.4 

Slope [Lower CI, Upper CI] 

Girls 

One-pollutant model 

FVC: -39 [-47: -31] 

FEV: -29 [-36: -21] 

FEF25-75%: -17 [-36: 1] 

FEV1/FVC: 0.12 [0.07: 0.17] 

Two-pollutant model: PM10, 6-LC & O3

FVC: -30 [-39: -22] 

FEV: -24 [-31: -16] 

FEF25-75%: -9 [-26: 9] 

FEV1/FVC: 0.10 [0.06: 0.15] 

PM10, 6-LC & NO2

FVC: -21 [-30: -13] 

FEV: -17 [-25: -8] 

FEF25-75%: -23 [-43: -4] 

FEV1/FVC: 0.07 [0.02: 0.13] 

Multipollutant model: PM10, 6-LC, O3, & 

NO2

FVC: -14 [-23: -5] 

FEV: -11 [-20: -3] 

FEF25-75%: -7 [-27: 12] 

FEV1/FVC: 0.08 [0.03: 0.13] 

Boys 

One-pollutant model 

FVC: -33 [-41: -25] 

FEV: -27 [-34: -19] 

FEF25-75%: -18 [-34: -2] 

FEV1/FVC: 0.04 [-0.01: 0.09] 

Two-pollutant model: PM10, 6-LC & O3

FVC: -28 [-36: -19] 

FEV: -22 [-30: -15] 

FEF25-75%: -10 [-27: 7] 

FEV1/FVC: 0.04 [-0.01: 0.09] 

FEV1/FVC: 0.24 [0.13: 0.34] 

PM10, 6-LC & NO2

FVC: -16 [-26: -7] 

FEV: -19 [-27: -10] 

FEF25-75%: -26 [-44: -9] 

FEV1/FVC: 0.005 [-0.06: 0.05] 

Multipollutant model PM10, 6-LC, O3, & 

NO2

FVC: -12 [-22: -3] 

FEV: -15 [-23: -6] 

FEF25-75%: -12 [-30: 6] 

FEV1/FVC: -0.002 [-0.06: 0.05] 

Reference: Schikowski et al. (2005, 

088637) 

Period of Study: 1985-1994 

Location: Rhine-Ruhr Basin of 

Germany [Dortmund (1985, 1990), 

Duisburg (1990), Gelsenkirchen (1986, 

1990), and Herne (1986)] 

Outcome: Respiratory symptoms & 

pulmonary function 

Age Groups: Age 54-55 

Study Design: Cross-sectional 

N: 4757 women 

Statistical Analyses: Linear & Logistic 

regressions, including random effects 

model 

Covariates: Age, smoking, SES, 

occupational exposure, form of heating, 

BMI, height

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags Considered: NR 

Pollutant: PM10

Averaging Time: NR 

Min, P25, Median, Mean, P75, Max 

Annual Mean 

35, 40, 43, 44, 47, 53 

5-yr Mean 

39, 43, 47, 48, 53, 56 

Monitoring Stations: 7 

Copollutant (correlation): NR 

PM Increment: 7 μg/m3

OR (Lower CI, Upper CI) for asthma 

symptoms 

Annual means 

Chronic bronchitis 1.00 (0.85, 1.18) 

Chronic cough 1.03 (0.87, 1.23) 

Frequent cough 1.01 (0.93, 1.10) 

COPD 1.37 (0.98, 1.92) 

p < 0.1 

FEV1 0.953 (0.916, 0.989) 

p < 0.1 

FVC 0.966 (0.940, 0.992) 

p < 0.1 

FEV1/FVC 0.989 (0.978, 1.000) 

p < 0.1 

Five yr means 

Chronic bronchitis 1.13 (0.95, 1.34) 

Chronic cough 1.11 (0.93, 1.31) 

Frequent cough 1.05 (0.94, 1.17) 

COPD 1.33 (1.03, 1.72) 

p < 0.1 

FEV1 0.949 (0.923, 0.975) 

p < 0.05 

FVC 0.963 (0.945, 0.982) 

p < 0.05 

FEV1/FVC 0.989 (0.980, 0.997) 

p < 0.1 

Reference: Schindler et al, (2009, Outcome: Respiratory Symptoms Pollutant: PM10 Increment: 10 μg/m3

December 2009 E-402 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

191950) 

Period of Study: 1991-2002 

Location: Switzerland 

Study Design: Prospective Cohort 

Statistical Analysis: Logistic 

Regression Model 

Age Groups: Adults, 18-60 yr of age at 

start of study 

Covariates: Sex, age, level of 

education, Swiss citizenship, BMI, 

parental smoking, parental history of 

asthma/atopy, early respiratory 

infection, smoking status, pack yr, daily 

number of cigarettes, yr since smoking 

cessation, passive smoking in 

general/at work, occupational exposure 

to airbourne irritants 

Averaging Time: Annual 

Mean (SD) Unit: 

Range (Min, Max): 

Copollutant (correlation): NR 

Odds Ratio (95%CI) of reporting 

symptoms at second interview

Entire Sample, New Reports 

Regular Cough: 0.77 (0.62-0.97) 

Regular Phlegm: 0.74 (0.56-0.99) 

Chronic Cough or Phlegm: 

0.78 (0.62-0.98) 

Wheezing: 1.01 (0.74-1.39) 

Wheezing with Dyspnea: 

0.70 (0.49-1.01) 

Wheezing without Cold: 

1.06 (0.76-1.50) 

Entire Sample, Persistent Reports 

Regular Cough: 0.55 (0.39-0.78) 

Regular Phlegm: 0.82 (0.52-1.33) 

Chronic Cough or Phlegm: 

0.67 (0.40-1.15) 

Wheezing: 0.50 (0.32-0.80) 

Wheezing with Dyspnea: 

0.59 (0.30-1.23) 

Wheezing without Cold: 0.61- (0.35-

1.12) 

Persistent Non-Smokers, New Reports 

Regular Cough: 0.86 (0.63-1.19) 

Regular Phlegm: 0.70 (0.49-0.99) 

Chronic Cough or Phlegm: 

0.71 (0.52-0.99) 

Wheezing: 0.93 (0.60-1.46) 

Wheezing with Dyspnea: 

0.77 (0.50-1.20) 

Wheezing without Cold: 

1.11 (0.66-1.92) 

Persistent Non-Smokers, 

Persistent Reports 

Regular Cough: 0.28 (0.14-0.60) 

Regular Phlegm: 0.87 (0.43-1.84) 

Chronic Cough or Phlegm: 

0.35 (0.16-0.81) 

Wheezing: 0.53 (0.28-1.08) 

Wheezing with Dyspnea: 

0.76 (0.30-2012) 

Wheezing without Cold: 

0.61 (0.26-1.52) 

Gender-specific odds ratio (95%CI) 

of reporting symptoms at second 

interview

New Reports 

Regular Cough, p = 0.73 

Men: 0.75 (0.53-1.06) 

Women: 0.81 (0.58-1.15) 

Regular Phlegm, p = 0.41 

Men: 0.85 (0.60-1.20) 

Women: 0.68 (0.46-1.00) 

Chronic Cough or Phlegm: 0.36 

Men: 0.87 (0.63-1.21) 

Women: 0.71 (0.51-0.97) 

Wheezing, p = 0.20 

Men: 0.83 (0.57-1.20) 

Women: 1.20 (0.78-1.87) 

Wheezing with Dyspnea, p = 0.11 

Men: 0.56 (0.36-0.87) 

Women: 1.00.57-1.842 

Wheezing without Cold, p = 0.43 

Men: 0.95 (0.63-1.42) 

Women: 1.25 (0.72-2.17) 

Persistent Reports 

Regular Cough, p = 0.02 

Men: 0.75 (0.48-1.18) 

Women: 0.31 (0.17-0.56) 

Regular Phlegm, p = 0.33 

Men: 0.65 (0.37-1.12) 

Women: 1.04 (0.47-2.34) 

Chronic Cough or Phlegm: 0.47 

Men: 0.68 (0.39-1.20) 

Women: 0.47 (0.20-1.11) 

Wheezing, p = 0.29 

Men: 0.34 (0.17-0.72) 

December 2009 E-403 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Women: 0.57 (0.32-1.01) 

Wheezing with Dyspnea, p = 0.63 

Men: 0.56 (0.16-1.95) 

Women: 0.37 (0.13-1.05) 

Wheezing without Cold, p = 0.57 

Men: 0.34 (0.12-0.91) 

Women: 0.49 (0.21-1.15) 

Odds Ratio (95%CI) of reporting 

symptoms at second interview with 

additional adjustment for annual 

outdoor PM exposure at baseline

Entire Sample 

Regular Cough, p = 0.0003 

New Reports: 0.77 (0.61-0.97) 

Persistent Reports: 0.55 (0.39-0.78) 

Regular Phlegm, p = 0.13 

New Reports: 0.77 (0.59-1.02) 

Persistent Reports: 0.79 (0.46-1.33) 

Chronic Cough or Phlegm, p = 0.02 

New Reports: 0.78 (0.62-0.98) 

Persistent Reports: 0.64 (0.40-1.02) 

Wheezing, p = 0.002 

New Reports: 0.91 (0.63-1.33) 

Persistent Reports: 0.47 (0.31-0.72) 

Wheezing with Dyspnea, p = 0.03 

New Reports: 0.65 (0.43-0.98) 

Persistent Reports: 0.55 (0.28-1.10) 

Severe Wheezing, p = 0.28 

New Reports: 0.96 (0.66-1.40) 

Persistent Reports: 0.62 (0.34-1.12) 

Non-Smokers 

Regular Cough, p < 0.001 

New Reports: 0.87 (0.63-1.19) 

Persistent Reports: 0.29 (0.16-0.52) 

Regular Phlegm, p = 0.07 

New Reports: 0.70 (0.50-0.99) 

Persistent Reports: 0.67 (0.34-1.33) 

Chronic Cough or Phlegm, p = 0.008 

New Reports: 0.72 (0.52-0.99) 

Persistent Reports: 0.38 (0.17-0.84) 

Wheezing, p = 0.07 

New Reports: 0.87 (0.52-1.48) 

Persistent Reports: 0.48 (0.25-0.91) 

Wheezing with Dyspnea, p = 0.36 

New Reports: 0.76 (0.48-1.19) 

Persistent Reports: 0.70 (0.27-1.82) 

Severe Wheezing, p = 0.57 

New Reports: 1.11 (0.64-1.93) 

Persistent Reports: 0.64 (0.26-1.54) 

Reference: Sharma et al. (2004, 

156974) 

Period of Study: Nov 2002-Apr 2003 

Location: 3 sections in Kanpur City, 

India: 

1) Indian Institute of Technology Kanpur 

(IITK) 

2) Vikas Nagar (VN) 

3) Juhilal Colony (JC) 

Outcome: Lung function 

Age Groups: 20-55 yr 

Study Design: Cohort

N: 91 people 

Statistical Analyses: Linear regression

Covariates: NR 

Season: Fall, Winter, spring 

Dose-response Investigated? No 

Statistical Package: Microsoft Excel 

Lags Considered: 1-day lag & 5-day ma 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

IITK 184 (40) 

VN 295 (58) 

JC 293 (90) 

PM Component: Lead, Nickel, 

Cadmium, Chromium, Iron, Zinc 

Benzene soluble fraction (includes 

polycyclic aromatic hydrocarbons 

[PAHs]) 

Copollutant (correlation): 

ΔPEF = mean daily deviations in PEF 

PM10-ΔPEF: (-0.52) 

PM10-PM2.5: (0.67) 

PM10-PM10 (1-day lag): (0.45) 

PM10-PM2.5 (1-day lag): (0.46) 

PM Increment: 1 μg/m3

ΔPEF (difference or change in peak 

expiratory flow) 

-0.0318 L/min 

December 2009 E-404 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Tager et al. (2005, 087538) 

Period of Study: Apr 2000-Jun 2000, 

Feb 2001-Jun 2001, 

Feb 2002-Jun 2002 

Location: 

Los Angeles, California 

San Francisco, California 

Outcome: Lung Function (FEV1, FVC, 

PEFR, FEF75, FEF25-75, 

FEF25-75/FVC ratio) 

Age Groups: 16-21+ y/o 

College Freshman 

Study Design: Retrospective cohort

N: 255 students 

108 Men (M) 

147 Women (W) 

Statistical Analyses: Multivariate 

Linear Regression 

Covariates: Sex, height, weight, area 

of residence, age, race, ETS exposure, 

respiratory disease history 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: Cumulative lifetime 

exposure 

Median: 

Prior to 1987: M: 73 

W: 71 

1987 and later: M: 36 

W: 34 

Lifetime: M: 48 

W: 45 

Range (Min, Max): 

Prior to 1987: M: 34, 117 

W: 31, 124 

1987 and later: M: 18, 68 

W: 20, 61 

Lifetime: M: 21, 80 

W: 18, 71 

Monitoring Stations: Between 1 and 3 

Copollutant (correlation): 

O3 prior to 1987: r = 0.68 

O3 1987 and later: r = 0.81 

O3-Lifetime: r = 0.57 

PM Increment: 1 μg/m3

Parameter Estimates (SD) 

(Lifetime PM10, Interaction PM10 

FEF25-75/FVC) 

LnFEF75: 

M: -0.009 (0.0009), 0.009 (0.007) 

W: -0.010 (0.0007), 0.008 (0.0005) 

Reference: Tamura et a. (2003, 

087445) 

Period of Study: 1998-1999 

Location: Bangkok, Thailand 

Outcome: Non-specific respiratory 

disease (Chronic bronchitis, acute 

bronchitis, bronchial asthma, dyspnea 

and wheezing) 

Age Groups: Adults 

Study Design: Cross-sectional 

N: 1603 policemen 

Statistical Analyses: Multiple logistic 

regression 

Covariates: Age, smoking status 

Dose-response Investigated? Yes 

Statistical Package: SPSS 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

Heavily Polluted 80-190 

Moderately Polluted 60-69 

Control 59 

Monitoring Stations: 13 

PM Increment: Heavily Polluted vs. 

Moderately Polluted vs. Control 

Number and Prevalence (%) of 

respiratory disease among heavily 

polluted, moderately polluted, and 

control areas. 

Heavily Polluted 

Chronic bronchitis 16 (3.0) 

Acute bronchitis 19 (3.5) 

Bronchial asthma 5 (0.9) 

Dyspnea & wheezing 49 (9.2) 

Any 1 of above 69 (13.0) 

Persistent cough 11 (2.1) 

Persistent phlegm 27 (1.3) 

Cough & phlegm 6 (1.1) 

Moderately Polluted 

Chronic bronchitis 8 (2.4) 

Acute bronchitis 12 (9.0) 

Bronchial asthma 2 (0.6) 

Dyspnea & wheezing 23 (6.8) 

Any 1 of above 37 (10.9) 

Persistent cough 1 (0.3) 

Persistent phlegm 11 (3.3)| 

Cough & phlegm 1 (0.3) 

Control 

Chronic bronchitis 6 (1.9) 

Acute bronchitis 11 (3.3) 

Bronchial asthma 0 (0.0) 

Dyspnea & wheezing 23 (7.2) 

Any 1 of above 31 (9.4) 

Persistent cough 1 (0.3) 

Persistent phlegm 8 (2.4) 

Cough & phlegm 1 (0.3) 

December 2009 E-405 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Wheeler and Ben-Schlomo 

(2005, 188766) 

Period of Study: 1995-1997 

Location: England 

Outcome: FEV1

Age Groups: 16-79 yr 

Study Design: Data from Health 

Survey for England were coupled 

geographically with air pollution 

measurements on a 1 km grid.

N: 26,426 households with 39,251 

adults 

Statistical Analyses: Logistic 

regression, least squares regression 

Covariates: Age, sex, height, body 

mass index, smoking status, household 

passive smoke exposure, inhaler use in 

the previous 24-h, doctor diagnosis of 

asthma. 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: 1996 annual mean 

Mean (SD): 23.95 (3.58) 

Range (Min, Max): 17.87-43.37 

β (95%CI) for Height-age 

standardized FEV1 by ambient air 

quality index 

p-value 

Male 

Good (ref) 

Poor -0.023 (-0.030 to -0.016) 

<0.001 

Female 

Good (ref) 

Poor -0.019 (-0.026 to -0.013) 

<0.001 

Reference: Zhang et al., (2002, 

034814) 

Period of Study: 1993-1996 

Location: 4 Chinese cities (urban and 

suburban location in each city): 

Guangzhou, Wuhan, Lanzhou, 

Chongqing 

Outcome: Interview-self reports of 

symptoms: Wheeze (ever wheezy when 

having a cold) 

Asthma (diagnosis by doctor) 

Bronchitis (diagnosis by doctor), 

Hospitalization due to respiratory 

disease (ever) 

Persistent cough (coughed for at least 1 

month per yr with or apart from colds) 

Persistent phlegm (brought up phlegm 

or mucus from the chest for at least 1 

month per yr with or apart from colds) 

Age Groups: Elementary school 

students 

age range: 5.4-16.2 

Study Design: Cross-sectional

N: 7,557 returned questionnaires 

7,392 included in first stage of analysis 

Statistical Analyses: 2-stage 

regression approach: Calculated odds 

ratios and 95% CIs of respiratory 

outcomes and covariates Second stage 

consisted of variance-weighted linear 

regressions that examined associations 

between district-specific adjusted 

prevalence rates and district-specific 

ambient levels of each pollutant. 

Covariates: Age, gender, breast-fed, 

house type, number of rooms, sleeping 

in own or shared room, sleeping in own 

or shared bed, home coal use, 

ventilation device used, homes 

smokiness during cooking, eye irritation 

during cooking, parental smoking, 

mother’s education level, mother’s 

occupation, father’s occupation, 

questionnaire respondent, yr of 

questionnaire administration, season of 

questionnaire administration, parental 

asthma prevalence 

Pollutant: PM10

Averaging Time: 2 yr 

Mean (SD): 151 (56) 

IQR: 87 

Range (Min, Max): 

Gives range (max.-min.): 

80 

Monitoring Stations: 

2 types: municipal monitoring stations 

over a period of 4 yr (1993-1996) 

Schoolyards of participating children 

over a period of 2 yr (1995-1996) 

PM Increment: Interquartile range 

corresponded to 1 unit of change. 

RR Estimate [Lower CI, Upper CI] 

lag: 

Association between persistent phlegm 

and PM10: 3.21 (1.55, 6.67) 

p < 0.05 

Between and within city modeled ORs, 

scaled to interquartile range of 

concentrations for each pollutant. 

No associations between any type of 

respiratory outcome and PM10

When scaled to an increment of 

50 μg/m3

 of PM10, ORs were: 

Wheeze: 1.07 

Asthma: 1.18 

Bronchitis: 1.53 

Hospitalization: 1.17 

Persistent cough: 1.20 

Persistent phlegm: 1.95 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-406 
Table E-23. Long-term exposure - respiratory morbidity outcomes - PM10-2.5. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chattopadhyay et al. (2007, 

147471) 

Period of Study: NR 

Location: Three different points in 

Kolkata, India: North, South, and 

Central 

Outcome: pulmonary function tests 

(respiratory impairments) 

Age Groups: All ages 

Study Design: Cross-sectional 

N: 505 people studied for PFT 

total population of Kolkata not given 

Statistical Analyses: 

Frequencies 

Covariates: Meteorologic data (i.e. 

temperature, wind direction, wind 

speed, and humidity) 

Dose-response Investigated? No 

Pollutant: PM<3.3-0.4 

Averaging Time: 8 h 

Mean (SD): 

North Kolkata: 266.1 

Central Kolkata: 435.3 

South Kolkata: 449.1 

Unit (i.e. μg/m3

): μg/m3

Monitoring Stations: 1 

Copollutant (correlation): 

PM10

PM<10-3.3 

PM Increment: NR 

Respiratory impairments (SD): 

North Kolkata 

Male (n=137) 

Restrictive: 4 (2.92) 

Obstructive: 5 (3.64) 

Combined Res. And Obs.: 6 (4.37) 

Total: 15 (10.95) 

Female (n=152) 

Restrictive: 3 (1.97) 

Obstructive: 5 (3.28) 

Combined Res. And Obs.: 0 

Total: 8 (5.26) 

Total (n=289) 

Restrictive: 7 (2.42) 

Obstructive: 10 (3.46) 

Combined Res. And Obs.: 6 (2.07) 

Total: 23 (7.96) 

Central Kolkata 

Male (n=44) 

Restrictive: 6 (13.63) 

Obstructive: 1 (2.27) 

Combined Res. And Obs.: 1 (2.27) 

Total: 8 (18.18) 

Female (n=50) 

Restrictive: 3 (6.00) 

Obstructive: 2 (4.00) 

Combined Res. And Obs.: 0 

Total: 5 (10.00) 

Total (n=94) 

Restrictive: 9 (9.57) 

Obstructive: 3 (3.19) 

Combined Res. And Obs.: 1 (1.06) 

Total: 13 (13.82) 

South Kolkata 

Male (n=52) 

Restrictive: 1 (1.92) 

Obstructive: 2 (3.84) 

Combined Res. And Obs.: 3 (5.76) 

Total: 6 (11.53) 

Female (n=70) 

Restrictive: 2 (2.85) 

Obstructive: 1 (1.42) 

Combined Res. And Obs.: 0 

Total: 3 (4.28) 

Total (n=122) 

Restrictive: 3 (2.45) 

Obstructive: 3 (2.45) 

Combined Res. And Obs.: 3 (2.45) 

Total: 9 (7.37) 

December 2009 E-407 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chattopadhyay et al. (2007, 

147471) 

Period of Study: NR 

Location: Three different points in 

Kolkata, India: North, South, and 

Central 

Outcome: Pulmonary function tests 

(respiratory impairments) 

Age Groups: All ages 

Study Design: Cross-sectional 

N: 505 people studied for PFT 

Total population of Kolkata not given 

Statistical Analyses: Frequencies 

Covariates: Meteorologic data (i.e. 

temperature, wind direction, wind 

speed, and humidity) 

Dose-response Investigated? No 

Pollutant: PM<10-3.3 

Averaging Time: 8 h 

Mean (SD): 

North Kolkata: 269.8 

Central Kolkata: 679.2 

South Kolkata: 460.1 

Monitoring Stations: 1 

Copollutant (correlation): 

PM10

PM<3.3-0. 

PM Increment: NR 

Respiratory impairments (SD): 

North Kolkata 

Male (n=137) 

Restrictive: 4 (2.92) 

Obstructive: 5 (3.64) 

Combined Res. And Obs.: 6 (4.37) 

Total: 15 (10.95) 

Female (n=152) 

Restrictive: 3 (1.97) 

Obstructive: 5 (3.28) 

Combined Res. And Obs.: 0 

Total: 8 (5.26) 

Total (n=289) 

Restrictive: 7 (2.42) 

Obstructive: 10 (3.46) 

Combined Res. And Obs.: 6 (2.07) 

Total: 23 (7.96) 

Central Kolkata 

Male (n=44) 

Restrictive: 6 (13.63) 

Obstructive: 1 (2.27) 

Combined Res. And Obs.: 1 (2.27) 

Total: 8 (18.18) 

Female (n=50) 

Restrictive: 3 (6.00) 

Obstructive: 2 (4.00) 

Combined Res. And Obs.: 0 

Total: 5 (10.00) 

Total (n=94) 

Restrictive: 9 (9.57) 

Obstructive: 3 (3.19) 

Combined Res. And Obs.: 1 (1.06) 

Total: 13 (13.82) 

South Kolkata 

Male (n=52) 

Restrictive: 1 (1.92) 

Obstructive: 2 (3.84) 

Combined Res. And Obs.: 3 (5.76) 

Total: 6 (11.53) 

Female (n=70) 

Restrictive: 2 (2.85) 

Obstructive: 1 (1.42) 

Combined Res. And Obs.: 0 

Total: 3 (4.28) 

Total (n=122) 

Restrictive: 3 (2.45) 

Obstructive: 3 (2.45) 

Combined Res. And Obs.: 3 (2.45) 

Total: 9 (7.37) 

Reference: Dales et al., (2008, 

156378) 

Period of Study: Location: Windsor, 

ON 

Outcome: Pulmonary function and 

inflammation 

Age Groups: Grades 4-6 

Study Design: Cross-sectional 

prevalence design 

Statistical Analyses: Multivariate linear 

regression 

Covariates: Ethnic background, 

smokers at home, pets at home, acute 

respiratory illness, medication use 

Pollutant: PM10-2.5

Averaging Time: Annual 

Mean: 7.25 

5th: 6.02 

95th: 8.23 

Copollutant: 

SO2

NO2

Increment: Tertiles of exposure 

FEV1: 

<7.04: 2.18 ± 0.01 

7.04-7.53: 2.19 ± 0.02 

>7.53: 2.14 ± 0.01 

FVC: 

<7.04: 2.52 ± 0.02 

7.04-7.53: 2.53 ± 0.02 

>7.53: 2.48 ± 0.02 

eNO: 

<7.04: 15.48 ± 0.63 

7.04-7.53: 16.73 ± 0.76 

>7.53: 16.59 ± 0.79 

December 2009 E-408 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Gauderman et al. (2000, 

012531) 

Period of Study: 1993-1997 

Location: Southern California 

Outcome: FVC, FEV1, MMEF, FEF75 

Age Groups: Fourth, seventh, or tenth 

graders 

Study Design: Cohort

N: 3035 subjects 

Statistical Analyses: Linear regression

Covariates: Height, weight, BMI, 

asthma, smoking, exercise, room 

temperature, barometric pressure 

Dose-response Investigated? Yes 

Statistical Package: SAS 

Pollutant: PM10-2.5

Averaging Time: 24-h avg PM10 & 

annual avg of 2-wk avg PM2.5

Mean (SD): PM10-2.5 25.6 

Copollutant (correlation): 

O3 r = -0.29 

NO2 r = 0.44 

Inorg. Acid r = 0.43 

Increment: 25.6 μg/m3

% Change (Lower CI, Upper CI) 

PM10-2.5-4th grade 

 FVC -0.57 (-1.20 to -0.06) 

 FEV1 -0.90 (-1.71 to -0.09) 

 MMEF -1.37 (-2.57 to -0.15) 

 FEF75 -1.62 (-3.24, 0.04) 

PM10-2.5-7th grade 

 FVC -0.35 (-1.02, 0.31) 

 FEV1 -0.49 (-1.21, 0.24) 

 MMEF -0.64 (-2.83, 1.60) 

 FEF75 -0.74 (-2.65, 1.20) 

PM10-2.5-10th grade 

 FVC -0.17 (-1.32, 0.99) 

 FEV1 -0.68 (-2.15, 0.81) 

 MMEF -1.41 (-5.85, 3.25) 

 FEF75 -2.32 (-6.60, 2.17) 

Reference: Gauderman et al. (2002, 

026013) 

Period of Study: 1996-2000 

Location: Southern California 

Outcome: Lung function development: 

FEV1, maximal mid-expiratory flow 

(MMEF) 

Age Groups: Fourth grade children 

(avg age = 9.9 yr) 

Study Design: Cohort study

N: 1678 children, 12 communities 

Statistical Analyses: Mixed model 

linear regression 

Covariates: Height, BMI, doctordiagnosed asthma and cigarette 

smoking in previous yr, respiratory 

illness and exercise on day of test, 

interaction of each of these variables 

with sex, barometric pressure, 

temperature at test time, indicator 

variables for field technician and 

spirometer 

Dose-response Investigated? Yes 

Statistical Package: SAS (10) 

Pollutant: PM10-2.5

Averaging Time: Annual 24-h avg 

Mean (SD): The avg levels were 

presented in an online data supplement 

(Fig E1) 

Monitoring Stations: 12 

Copollutant (correlation): 

O3 (10 AM to 6 PM) r = 0.10 

O3 r = -0.31 

NO2 r = 0.46 

Acid vapor r = 0.63 

PM10 r = 0.95 

PM10-2.5 r = 0.81 

EC r = 0.71 

OC r = 0.96 

PM Increment: 29.1 μg/m3

Association Estimate: 

PM10-2.5 was not correlated with any of 

the pulmonary function tests that were 

analyzed 

Reference: Leonardi et al. (2000, 

010272) 

Period of Study: 1996 

Location: 17 cities of Central Europe 

(Bulgaria, Czech Republic, Hungary , 

Poland, Romania, Slovakia) 

Outcome: Immune biomarkers 

Age Groups: 9-11 

Study Design: Cross-sectional 

N: 366 school children 

Statistical Analyses: Linear regression

Covariates: Age, gender, parental 

smoking, laboratory of analysis, recent 

respiratory illness 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM10-2.5

Averaging Time: Subtracting PM2.5

from PM10 provides avg PM10-2.5

Mean (SD): PM10-2.5: 20 (5) 

Range (Min, Max): 

PM10-2.5: (12, 38) 

5th, median, & 95th percentile 

PM10-2.5: 12, 19, 29 

% Change (Lower CI, Upper CI) 

p-value 

PM10-2.5

Neutrophils 1 (-27, 38) 

>.20 

Total lymphocytes 8 (-15, 38) 

>.20 

B lymphocytes 22 (-16, 76) 

>.20 

Total T lymphocytes 2 (-25, 37) 

>.20 

CD4+ -1 (-30, 41) 

>.20 

CD8+ 3 (-25, 41) 

>.20 

CD4/CD8 0 (-23, 30) 

>.20 

NK 1 (-33, 51) 

>.20 

Total IgG -3 (-21, 18) 

>.20 

Total IgM 19 (-9, 55) 

>.20 

Total IgA 16 (-12, 52) 

>.20 

Total IgE -29 (-70, 70) 

>.20 

December 2009 E-409 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: McConnell et al. (2003, 

049490) 

Period of Study: 1993-1999 

Location: 12 Southern CA communities 

Outcome: Bronchitic symptoms 

Age Groups: 9-19 

Study Design: Communities selected 

on basis of historic levels of criteria 

pollutants and low residential mobility.

N: 475 children 

Statistical Analyses: 3 stage 

regression combined to give a logistic 

mixed effects model 

Covariates: Sex, ethnicity, allergies 

history, asthma history, SES, insurance 

status, current wheeze, current 

exposure to ETS, personal smoking 

status, participation in team sports, in 

utero tobacco exposure through 

maternal smoking, family history of 

asthma, amount of time routinely spent 

outside by child during 2-6 pm. 

Dose-response Investigated? No 

Statistical Package: SAS Glimmix 

macro 

Pollutant: PM10-2.5

Averaging Time: 4-yr avg 

Mean (SD): 17.0(6.4) 

Range (Min, Max): 10.2-35.0 

Copollutant (correlation): 

PM2.5: r = 0.24 

PM10: r = 0.79 

Inorganic acid: r = 0.38 

Organic Acid: r = 0.35 

EC: r = 0.30 

OC: r = 0.27 

NO2: r = -0.22 

O3: r = 0.29 

PM Increment: Between community 

range 24.8 μg/m3

Between community unit 1 μg/m3

Within community 1 μg/m3

OR Estimate [Lower CI, Upper CI] 

Between community per range 

1.38(0.65-2.92) 

Between Community per unit 

1.01(0.98-1.04) 

Within community per unit 

1.02(0.95-1.10) 

Reference: Millstein et al. (2004, 

088629) 

Outcome: Wheezing & asthma 

medication use 

Period of Study: Mar-Aug, 1995, and 

Sep 1995-Feb 1996 

Age Groups: 4th grade students, 

mostly 9 yr at the time of the study 

Study Design: Cohort Study, stratified 

into 2 seasonal groups/

N: 2081 enrolled, 2034 provided parentcompleted questionnaire. 

Statistical Analyses: Multilevel, mixedeffects logistic model. 

Covariates: Contagious respiratory 

disease, ambient airborne pollen and 

other allergens, temperature, sex, age 

race, allergies, pet cats, carpet in home, 

environmental tobacco smoke, heating 

fuel, heating system, water damage in 

home, education level of questionnaire 

signer, physician diagnosed asthma. 

Data were taken from the Children’s 

Health Study 

Location: Alpine, Atascadero, Lake 

Arrowhead, Lake Elsinore, Lancaster, 

Lompoc, Long Beach, Mira Loma, 

Riverside, San Dimas, Santa Maria, and 

Upland, CA 

Season: Mar-Aug, 1995, and Sep, 

1995 to Feb, 1996 

Statistical Package: SAS 8.00 

Lags Considered: 14 

Pollutant: PM10-2.5

Averaging Time: monthly 

PM Component: Nitric acid, formic 

acid, acetic acid 

Monitoring Stations: 1 central location 

in each community 

Copollutant (correlation): 

NO2: r = 0.29 

O3: r = 0.77 

PM2.5: r = -0.08 

PM Increment: IQR 11.44 μg/m3

Odds Ratio [lower CI, Upper CI] 

Annual 

PM10-2.5: 0.96 [0.74, 1.25] 

Mar-Aug 

PM10-2.5: 0.93 [0.54, 1.59] 

Sep-Feb 

PM10-2.5: 0.68 [0.46, 1.01] 

Reference: (Parker et al., 2009, 

192359) 

Period of Study: 1999-2005 

Location: U.S. 

Outcome: Respiratory allergy/hayfever 

Study Design: Cohort 

Covariates: Survey yr, age, family 

structure, usual source of care, health 

insurance, family income relative to 

federal poverty level, race/ethnicity 

Statistical Analysis: Logistic 

regression 

Statistical Package: SUDAAN 

Age Groups: 73,198 children aged 

3-17 yr 

Pollutant: PM10-2.5

Averaging Time: NR 

Median: 11.2 μg/m3

IQR: 8.2-15.2 

Copollutant (correlation): 

Summer 

O3: 0.16 

SO2: -0.33 

NO2: 0.29 

PM2.5: 0.02 

PM10: 0.86 

Increment: 10 μg/m3

Odds Ratio (95% CI) 

Single Pollutant Model, variable N 

Adjusted: 1.01 (0.95-1.07) 

Single Pollutant Model, constant N 

Adjusted: 1.13 (1.04-1.46) 

Multi-pollutant Model: 1.16 (1.06-1.24) 

December 2009 E-410 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zhang et al. (2002, 

034814) 

Period of Study: 1993-1996 

Location: 4 Chinese cities (urban and 

suburban location in each city): 

Guangzhou, Wuhan, Lanzhou, 

Chongqing 

Outcome: Interview-self reports of 

symptoms: Wheeze (ever wheezy when 

having a cold) 

Asthma (diagnosis by doctor) 

Bronchitis (diagnosis by doctor), 

Hospitalization due to respiratory 

disease (ever) 

Persistent cough (coughed for at least 1 

month per yr with or apart from colds) 

Persistent phlegm (brought up phlegm 

or mucus from the chest for at least 1 

month per yr with or apart from colds) 

Age Groups: Elementary school 

students 

age range: 5.4-16.2 

Study Design: Cross-sectional

N: 7,557 returned questionnaires 

7,392 included in first stage of analysis 

Statistical Analyses: 2-stage 

regression approach: Calculated odds 

ratios and 95% CIs of respiratory 

outcomes and covariates Second stage 

consisted of variance-weighted linear 

regressions that examined associations 

between district-specific adjusted 

prevalence rates and district-specific 

ambient levels of each pollutant. 

Covariates: Age, gender, breast-fed, 

house type, number of rooms, sleeping 

in own or shared room, sleeping in own 

or shared bed, home coal use, 

ventilation device used, homes 

smokiness during cooking, eye irritation 

during cooking, parental smoking, 

mother’s education level, mother’s 

occupation, father’s occupation, 

questionnaire respondent, yr of 

questionnaire administration, season of 

questionnaire administration, parental 

asthma prevalence 

Pollutant: PM10-2.5 

Averaging Time: 2 yr 

Mean (SD): 59 (28) 

Percentiles: 

25th: NR 

50th(Median): NR 

75th: NR 

IQR: 42 

Range (Min, Max): 

Gives range (max.-min.): 80 

Monitoring Stations: 

2 types: municipal monitoring stations 

over a period of 4 yr (1993-1996) 

Schoolyards of participating children 

over a period of 2 yr (1995-1996) 

PM Increment: Interquartile range 

corresponded to 1 unit of change. 

RR Estimate [Lower CI, Upper CI] 

lag: 

Association between bronchitis and 

PM10-2.5: 2.20 (1.14, 4.26) 

p < 0.05 

Association between persistent cough 

and PM10-2.5: 1.46 (1.12, 1.90) 

p < 0.05 

Between and within city associations: 

Bronchitis: 3.18 (between city) 

Persistent phlegm (between city): 2.78 

When scaled to an increment of 

50 μg/m3

 of PM10-2.5 associations (ORs) 

between respiratory outcome and PM10-

2.5 were: 

 Wheeze: 1.14 

Asthma: 1.34 

Bronchitis: 2.56 

Hospitalization: 1.58 

Persistent cough: 1.57 

Persistent phlegm: 3.45 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-411 
Table E-24. Long-term exposure - respiratory morbidity outcomes - PM2.5 (including PM 

components/sources). 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: AnnesiMaesano et al.(2007, 

091348) 

Period of Study: Mar 

1999-Oct 2000 

Location: France 

(Bordeaux, ClermontFerrand, Creteil, 

Marseille, Strasbourg,, & 

Reims) 

Outcome: EIB, Flexural atopic 

dermatitis, asthma, rhiniconjuctivitis, 

allergic rhinitis 

Age Groups: Children mean 

10.4 ± 0.7 yr 

Study Design: Semi-individual 

design

N: 5338 

Statistical Analyses: Logistic 

regression 

Covariates: Age, sex, family history 

of allergy, passive smoking 

Season: NR 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM2.5

Averaging Time: 5-day mean 

(Mon.-Fri.) over a 13-wk to 24-wk 

span 

Residential Proximity Level 

Mean (SD): 

Low conc: 8.7 

High conc: 20.7 

Range (Min, Max): 

Low conc: (1.6, 12.2) 

High conc: (12.5, 54.0) 

City Level 

Mean (SD): 

Low conc: 9.6 

High conc: 23.0 

Range (Min, Max): 

Low conc: (4.7, 12.7) 

High conc: (13.0, 54.5) 

PM Increment: High vs. Low 

Allergic and respiratory morbidity OR Estimate (Lower CI, 

Upper CI) 

Proximity Level 

EIB (C) 1.35 (1.10, 1.67) 

Fl. Atopic dermatitis (C) 2.51 (2.06, 3.06) 

Asthma (P) 1.11 (0.88, 1.39) 

Atopic asthma (P) 1.43 (1.07, 1.91) 

Non-atopic asthma (P) 0.73 (0.49, 1.07) 

Rhiniconjunctivitis (P) 0.94 (0.77, 1.15) 

Atopic dermatitis (P) 1.05 (0.88, 1.27) 

Asthma (L) 1.00 (0.82, 1.22) 

Allergic Rhinitis (L) 1.09 (0.93, 1.27) 

Atopic dermatitis (L) 0.94 (0.82, 1.09) 

City Level 

EIB (C) 1.43 (1.15, 1.78) 

Fl. Atopic dermatitis (C) 2.06 (1.69, 2.51) 

Asthma (P) 1.31 (1.04, 1.66) 

Atopic asthma (P) 1.58 (1.17, 2.14) 

Non-atopic asthma (P) 1.00 (0.68, 1.49) 

Rhiniconjunctivitis (P) 0.98 (0.80, 1.20) 

Atopic dermatitis (P) 1.08 (0.90, 1.30) 

Asthma (L) 1.09 (0.89, 1.33) 

Allergic Rhinitis (L) 1.13 (0.97, 1.33) 

Atopic dermatitis (L) 0.95 (0.82, 1.09) 

Notes: C = Current 

P = Past yr 

L = Lifetime 

Allergic sensitization OR Estimate (Lower CI, Upper CI) 

Proximity Level 

All allergens 1.19 (1.04, 1.36) 

Indoor allergens 1.29 (1.11, 1.50) 

Outdoor allergens 1.02 (0.85, 1.23) 

Moulds 1.13 (0.78, 1.65) 

City Level 

All allergens 1.32 (1.15, 1.51) 

Indoor allergens 1.51 (1.29, 1.76) 

Outdoor allergens 1.06 (0.88, 1.28) 

Molds 1.00 (0.69, 1.46) 

Reference: Bakke et al. 

(2004, 156246) 

Period of Study: Jan 

1989-Jun 2002 

Location: One of 

Norway’s major 

construction companies 

Outcome: Spirometric 

measurements 

Age Groups: All ages, mean = 39 

yr 

Study Design: Cohort

N: 651 male construction workers 

Statistical Analyses: Multiple 

linear regression models 

Covariates: Age, yr for nonsmokers and ever smokers 

Dose-response Investigated? No 

Statistical Package: SYSTAT 10.0 

and SPSS 11.0 

Pollutant: Respirable dust 

Averaging Time: 5-8 h 

Mean (SD): 

Drill and blast workers: 6.3 (2.8) 

Tunnel concrete workers: 6.1 (3.1) 

Shotcreting operators: 19 (11) 

TBM workers: 16 (6.6) 

Outdoor concrete workers: 1.4 

(0.73) 

Foremen: 0.28 (0.48) 

Engineers: 0.09 (0.28) 

Unit (i.e. μg/m3): mg·y/m3

Monitoring Stations: 16 tunnel 

sites visited with sampling 

equipment 

Copollutant (correlation): 

Total dust: r = 0.99 

α quartz: r = 0.48 

NO2: r = 0.75 

CO: r = 0.61 

Oil mist: r = 0.83 

Oil vapor: r = 0.68 

VOC: r = 0.89 

PM Increment: NR-exposure respirable dust 

Effect Estimate (Lower CI, Upper CI): 

Lung function changes predicted by multiple linear regression 

models using one exposure variable adjusted for age and 

observation time by non-smokers and ever smokers 

Non-smokers: ß = -16.0 

(-24- -6.8) 

SE = 4.5 

Ever smokers: ß = -9.3 

(-17- -1.6) 

SE = 4.0 

December 2009 E-412 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bakke et al. 

(2004, 156246) 

Period of Study: Jan 

1989-Jun 2002 

Location: One of 

Norway’s major 

construction companies 

Outcome: Spirometric 

measurements 

Age Groups: All ages, mean = 39 

yr 

Study Design: Cohort

N: 651 male construction workers 

Statistical Analyses: Multiple 

linear regression models 

Covariates: Age, yr for nonsmokers and ever smokers 

Dose-response Investigated? 

No 

Statistical Package: 

SYSTAT 10.0 and SPSS 11.0 

Pollutant: Total dust 

Averaging Time: 5-8 h 

Mean (SD): 

Drill and blast workers: 18 (7.8) 

Tunnel concrete workers: 21 (11) 

Shotcreting operators: 73 (41) 

TBM workers: 48 (20) 

Outdoor concrete workers: 6.5 (3.4) 

Foremen: 0.78 (1.3) 

Engineers: 0.27 (0.78) 

Unit (i.e. μg/m3): mg·y/m3 

Monitoring Stations: 16 tunnel 

sites visited with sampling 

equipment 

Copollutant (correlation): 

Respirable dust: r = 0.99 

α quartz: r = 0.42 

NO2: r = 0.67 

CO: r = 0.49 

Oil mist: r = 0.81 

Oil vapor: r = 0.64 

VOC: r = 0.91 

PM Increment: NR-exposure expirable dust 

Lung function changes predicted by multiple linear regression 

models using one exposure variable adjusted for age and 

observation time by non-smokers and ever smokers 

Non-smokers: ß = -4.0 (-6.5-1.4) 

SE = 1.3 

Ever smokers: ß = -2.0 (-4.2-0.23) 

SE = 1.1 

Reference: Bennett et al. 

(2007, 156268) 

Period of Study: 

1992-2005 

Location: Melbourne, 

Australia 

Outcome: Respiratory symptoms 

(from questionnaire) 

Age Groups: All ages, mean = 37.2 

yr 

Study Design: Cohort

N: 1446 

Statistical Analyses: Logistic 

regression models 

Covariates: Age, gender, use of 

ß2-agonists, use of inhaled 

corticosteroids, smoking, yr of data 

collection, and avg daily exposure 

to PM2.5 in the 12 mo corresponding 

to the time frame of symptoms 

Dose-response Investigated? No 

Statistical Package: STATA, 

version 9 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): 6.8 

Range (Min, Max): (1.8-73.3) 

Monitoring Stations: up to 3 

PM Increment: NR 

Effect Estimate [Lower CI, Upper CI]: 

Respiratory symptoms in last 12 mo and exposure to ambient 

PM2.5 over the same period 

Within-person (longitudinal) effects 

Wheeze: OR = 1.08 (0.79-1.48), p = 0.62 

SOB on waking: OR = 1.34 (0.84-2.16), p = 0.22 

Cough (AM): OR = 0.74 (0.47-1.15), p = 0.18 

Phlegm (AM): OR = 1.55 (0.95-2.53), p = 0.08 

Cough w/ phlegm (AM): OR = 1.28 (0.70-2.33), p = 0.42 

Asthma attack: OR = 0.91 (0.55-1.49), p = 0.69 

Between-person (cross-sectional) effects 

Wheeze: OR = 1.32 (0.82-2.10), p = 0.25 

SOB on waking: OR = 1.29 (0.46-3.60), p = 0.63 

Cough (AM): OR = 0.21 (0.07-0.62), p = 0.01 

Phlegm (AM): OR = 0.49 (0.16-1.44), p = 0.19 

Cough w/ phlegm (AM): OR = 0.28 (0.08-0.97), p = 0.05 

Asthma attack: OR = 0.52 (0.17-1.59), p = 0.26 

December 2009 E-413 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Brauer et 

al., 2007, 090691) 

Period of Study: 

1999-2000 

Location: The 

Netherlands 

Outcome: 

Allergen sensitivity (any, indoor, 

outdoor, food, total) IgE>100 IU/mL 

Asthma (probable, MD-diagnosed, 

ever MD-diagnosed) 

Bronchitis (MD-diagnosed, ever 

MD-diagnosed) 

Dry cough at night 

Itchy rash 

Itchy rash/eczema 

Ear/Nose/Throat (ENT) infection 

Eczema, MD-diagnosed 

Eczema, ever MD-diagnosed 

Flu/serious cold, MD-diagnosed 

Wheeze (ever, early, early frequent, 

persistent) 

Age Groups: Very young children 

(<4-yr-old) enrolled prenatally 

Study Design: Prospective birth 

cohort study 

N: ~4000 subjects 

Statistical Analyses: Multiple 

logistic regression 

Dose-response Investigated? No 

Pollutant: PM2.5

Averaging Time: 12 mo 

Mean (SD): SD: NR 

16.9 

Percentiles: 25th: 14.8 

50th(Median): 17.3 

75th: 18.1 

Range (Min, Max): (13.5, 25.2) 

Monitoring Stations: 40 

Copollutant (correlation): Soot: r 

= 0.97 

NO2: r = 0.93 

PM Increment: IQR 3.3 μg/m3

Notes: Traffic-related pollution (PM2.5, soot, NO2) was 

associated with respiratory infections, asthma, and allergic 

sensitization in children during the first 4 yr of life. 

Symptom At 4-Yr-Old 

Wheeze 

4-yr-old: 1.23 [1.00: 1.51] 

Early-life: 1.20 [0.99: 1.46] 

Asthma, MD-diagnosed 

4-yr-old: 1.15 [0.82: 1.62] 

Early-life: 1.32 [0.96: 1.83] 

Dry cough at night 

4-yr-old: 1.11 [0.94: 1.31] 

Early-life: 1.14 [0.98: 1.33] 

Bronchitis, MD-diagnosed 

4-yr-old: 0.88 [0.66: 1.18] 

Early-life: 0.86 [0.66: 1.11] 

ENT infection 

4-yr-old: 1.13 [0.98: 1.31] 

Early-life: 1.17 [1.02: 1.34] 

Flu/serious cold, MD-diagnosed 

4-yr-old: 1.21 [1.02: 1.42] 

Early-life: 1.25 [1.07: 1.46] 

Itchy rash 

4-yr-old: 0.96 [0.82: 1.11] 

Early-life: 0.98 [0.85: 1.14] 

Eczema, MD-diagnosed 

4-yr-old: 1.00 [0.88: 1.21] 

Early-life: 0.98 [0.82: 1.17] 

Allergen Sensitivity At 4-Yr-Old 

Allergen, any: 1.55 [1.13: 2.11] 

Allergen, indoor: 1.03 [0.69: 1.55] 

Allergen, outdoor: 0.93 [0.54: 1.58] 

Allergen, food: 1.75 [1.23: 2.47] 

Allergen, total IgE>100 IU/mL: 0.84 [0.59: 1.18] 

Cumulative Allergy/Asthma Symptoms At 4-Yr-Old 

Wheeze, ever: 1.22 [1.06: 1.41] 

Asthma, ever MD-diagnosed: 1.32 [1.04: 1.69] 

Asthma, probable: 1.08 [0.90: 1.30] 

Wheeze, early: 1.16 [1.00: 1.34] 

Wheeze, persistent: 1.19 [0.96: 1.48] 

Wheeze, early frequent: 1.19 [0.96: 1.47] 

Bronchitis, ever MD-diagnosed: 0.96 [0.81: 1.13] 

Itchy rash/eczema: 0.99 [0.88: 1.13] 

Eczema, ever MD-diagnosed: 0.98 [0.85: 1.13] 

December 2009 E-414 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Brauer et 

al., 2007, 090691) 

Period of Study: 

1999-2000 

Location: The 

Netherlands 

Outcome: Allergen sensitivity (any, 

indoor, outdoor, food, total) IgE>100 

IU/mL 

Asthma (probable, MD-diagnosed, 

ever MD-diagnosed) 

Bronchitis (MD-diagnosed, ever 

MD-diagnosed) 

Dry cough at night 

Itchy rash 

Itchy rash/eczema 

Ear/Nose/Throat (ENT) infection 

Eczema, MD-diagnosed 

Eczema, ever MD-diagnosed 

Flu/serious cold, MD-diagnosed 

Wheeze (ever, early, early frequent, 

persistent) 

Age Groups: Very young children 

(<4-yr-old) enrolled prenatally 

Study Design: Prospective birth 

cohort study 

N: ~4000 subjects 

Statistical Analyses: Multiple 

logistic regression 

Dose-response Investigated? No 

Pollutant: Soot (as PM2.5

absorbance) 

Averaging Time: 12 mo 

Mean (SD): 1.71 

Percentiles: 

25th: 1.33 

50th(Median): 1.78 

75th: 1.91 

Range (Min, Max): (0.77, 3.68) 

Unit (i.e. μg/m3): 1E-5/m 

Monitoring Stations: 40 

Copollutant (correlation): 

NO2: r = 0.96 

PM2.5: r = 0.97 

PM Increment: IQR 0.58 E-5/m 

Notes: Traffic-related pollution (PM2.5, soot, NO2) was 

associated with respiratory infections, asthma, and allergic 

sensitization in children during the first 4 yr of life. 

Symptom At 4-Yr-Old 

Wheeze 

4-yr-old: 1.18 [0.98: 1.41] 

Early-life: 1.18 [1.00: 1.40] 

Asthma, MD-diagnosed 

4-yr-old: 1.15 [0.85: 1.55] 

Early-life: 1.30 [0.98: 1.71] 

Dry cough at night 

4-yr-old: 1.13 [0.97: 1.30] 

Early-life: 1.14 [1.00: 1.31] 

Bronchitis, MD-diagnosed 

4-yr-old: 0.90 [0.69: 1.16] 

Early-life: 0.88 [0.69: 1.11] 

ENT infection 

4-yr-old: 1.15 [1.01: 1.31] 

Early-life: 1.16 [1.03: 1.31] 

Flu/serious cold, MD-diagnosed 

4-yr-old: 1.18 [1.02: 1.36] 

Early-life: 1.19 [1.04: 1.37] 

Itchy rash 

4-yr-old: 0.94 [0.82: 1.08] 

Early-life: 0.97 [0.85: 1.10] 

Eczema, MD-diagnosed 

4-yr-old: 0.99 [0.84: 1.17] 

Early-life: 0.97 [0.83: 1.14] 

Allergen Sensitivity At 4-Yr-Old 

Allergen, any: 1.45 [1.11: 1.91] 

Allergen, indoor: 1.02 [0.71: 1.46] 

Allergen, outdoor: 0.95 [0.59: 1.52] 

Allergen, food: 1.64 [1.21: 2.23] 

Allergen, total IgE>100 IU/mL: 0.80 [0.59: 1.09] 

Cumulative Allergy/Asthma Symptoms At 4-Yr-Old 

Wheeze, ever: 1.18 [1.04: 1.34] 

Asthma, ever MD-diagnosed: 1.26 [1.02: 1.56] 

Asthma, probable: 1.06 [0.90: 1.24] 

Wheeze, early: 1.11 [0.97: 1.26] 

Wheeze, persistent: 1.18 [0.98: 1.42] 

Wheeze, early frequent: 1.14 [0.95: 1.37] 

Bronchitis, ever MD-diagnosed: 0.95 [0.82: 1.10] 

Itchy rash/eczema: 0.99 [0.89: 1.11] 

Eczema, ever MD-diagnosed: 0.99 [0.87: 1.12] 

Reference: Brauer et al. 

(2002, 035192) 

Period of Study: NR 

Location: The 

Netherlands 

Outcome: Questionnaire derived 

wheezing, dry nighttime cough, ear, 

nose and throat infections, skin rash

Physician diagnosed asthma, 

bronchitis, influenza, eczema 

Age Groups: age 2 

Study Design: Prospective cohort

N: 4146 children 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, maternal 

smoking, mattress cover (allergenfree), maternal education, paternal 

education, gender, gas stove, gas 

water heater, any other siblings, 

ethnicity, breastfeeding, mold at 

home, pets, allergies in mother, 

allergies in father 

Dose-response Investigated? No 

Pollutant: PM2.5 

Averaging Time: 4 2-wk periods 

dispersed throughout 1 yr, adjusted 

for temporal trend 

Mean (SD): 16.9 

Percentiles: 

10th: 14.0 

25th: 15.0 

50th(Median): 17.3 

75th: 18.2 

90th: 19.1 

Range (Min, Max): 13.5, 25.2

Monitoring Stations: 40

Copollutant (correlation): 

Soot: r = 0.99 

NO2: r = 0.97 

PM Increment: 3.2 μg/m3

OR Estimate [Lower CI, Upper CI]; 

Unadjusted 

Wheeze 1.14 (0.99-1.30) 

Asthma 1.08 (0.84-1.37) 

Dry cough at night 1.10 (0.95-1.27) 

Bronchitis 1.00 (0.85-1.18) 

E, N, T infections 1.14 (0.99-1.33) 

Flu 1.15 (1.03-1.28) 

Itchy rash 1.07 (0.95-1.20) 

Eczema 1.02 (0.90-1.16) 

Adjusted 

Wheeze 1.14 (0.98-1.34) 

Asthma 1.12 (0.84-1.50) 

Dry cough at night 1.04 (0.88-1.23) 

Bronchitis 1.04 (0.85-1.26) 

E, N, T infections 1.20 (1.01-1.42) 

Flu 1.12 (1.00-1.27) 

Itchy rash 1.01 (0.88-1.16) 

Eczema 0.95 (0.83-1.10) 

December 2009 E-415 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Brauer et al. 

(2002, 035192) 

Period of Study: NR 

Location: The 

Netherlands 

Outcome: Questionnaire derived 

wheezing, dry nighttime cough, ear, 

nose and throat infections, skin rash

Physician diagnosed asthma, 

bronchitis, influenza, eczema 

Age Groups: Age 2 

Study Design: Prospective cohort

N: 4146 children 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, maternal 

smoking, mattress cover (allergenfree), maternal education, paternal 

education, gender, gas stove, gas 

water heater, any other siblings, 

ethnicity, breastfeeding, mold at 

home, pets, allergies in mother, 

allergies in father 

Dose-response Investigated? No 

Pollutant: PM2.5 “soot” 

Averaging Time: 4 2-wk periods 

dispersed throughout 1 yr, adjusted 

for temporal trend 

Mean (SD): 16.9 10-5/m 

Percentiles: 10th: 1.16 

25th: 1.38 

50th(Median): 1.78 

75th: 1.92 

90th: 2.19 

Range (Min, Max): 0.77, 3.68 

Unit (i.e. μg/m3): 10-5/m 

Monitoring Stations: 40 

Copollutant (correlation): 

PM2.5 (r = 0.99) 

NO2 (r = 0.96) 

PM Increment: 0.54 x 10-5/m (equivalent to 0.8 μg/m3 EC) 

OR Estimate [Lower CI, Upper CI] 

Unadjusted 

Wheeze 1.11 [0.99-1.24] 

Asthma 1.07 [0.87-1.31] 

Dry cough at night 1.08 [0.95-1.21] 

Bronchitis 0.98 [0.85-1.12] 

E, N, T infections 1.12 [0.99-1.27] 

Flu 1.13 [1.03-1.23] 

Itchy rash 1.07 [0.97-1.19] 

Eczema 1.01 [0.91-1.13] 

Adjusted 

Wheeze 1.11 [0.97-1.26] 

Asthma 1.12 [0.88-1.43] 

Dry cough at night 1.02 [0.88-1.17] 

Bronchitis 0.99 [0.84-1.17] 

E, N, T infections 1.15 [1.00-1.33] 

Flu 1.09 [0.98-1.21] 

Itchy rash 1.02 [0.91-1.15] 

Eczema 0.96 [0.85-1.08] 

Reference: Brauer et al. 

(2006, 090757) 

Period of Study: 

1997-2001 

Location: Germany 

The Netherlands 

Outcome: Otitis Media (parental 

report of doctor’s diagnosis prior to 

age 2 yr) 

Age Groups: 0-2 yr 

Study Design: Prospective Cohort 

Study

N: 4,379 children total 

The Netherlands: 3,714 

Germany: 665 

Statistical Analyses: Logistic 

regression 

Covariates: Sex, parental atopy, 

maternal education, siblings, 

maternal smoking during 

pregnancy, ETS exposure at home, 

use of gas for cooking, indoor 

moulds and dampness, number of 

siblings, breast-feeding, and 

presence of pets in the home

Season: All 

Dose-response Investigated? No 

Pollutant: PM2.5

PM Component: EC (EC) 

Averaging Time: 8 wk (4 2-week 

periods dispersed throughout 1 yr, 

adjusted for temporal trends) 

Mean: 

The Netherlands: 

PM2.5: 16.9 

EC: 1.72 

Germany: 

PM2.5: 13.4 

EC: 1.76 

Range (Min, Max): 

The Netherlands: 

PM2.5: 13.5, 25.2 

EC: 0.77, 3.68 

Germany: 

PM2.5: 12.0, 21.9 

EC: 1.40, 4.39 

Monitoring Stations: 80 (40 for 

each cohort) 

PM Increment: PM2.5: 3 μg/m3 (~ IQR) 

EC: ~0.5 μg/m3

 (~ IQR) 

OR Estimate [Lower CI, Upper CI] 

The Netherlands: 

PM2.5: At age 1: 1.13 (0.98-1.32) 

At age 2: 1.13 (1.00-1.27) 

EC: 

At age 1: 1.11 (0.98-1.26) 

At age 2: 1.10 (1.00-1.22) 

Germany: 

PM2.5: 

At age 1: 1.19 (0.73-1.92) 

At age 2: 1.24 (0.84-1.83) 

EC: 

At age 1: 1.12 (0.83-1.51) 

At age 2: 1.10 (0.86-1.41) 

Reference: Burr et al. 

(2004, 087809) 

Period of Study: 3 wk in 

Jul and Jan 1997 and 2 

wk in Nov 1996 and Apr 

1997 

Location: North Wales, 

England 

Outcome: Self-report of symptoms 

only for wheeze, cough, phlegm, 

rhinitis, and itchy eyes. 

Age Groups: All 

Study Design: Repeated measures

N: 386 persons in congested 

streets and 425 in the uncongested 

streets in 1996/1997. Of these, 165 

and 283 completed the second 

phase of the study. 

Pollutant: PM2.5

Averaging Time: Mean hourly 

concentrations 

Mean (SD): 

Congested Streets 

1996-97 21.2 

1998-99 16.2 

Uncongested Streets 

1996-97 6.7 

1998-99 4.9 

Monitoring Stations: 1 in 

congested street and 1 in 

uncongested 

% change PM10 in congested streets: 23.6 

% change PM10 in uncongested streets: 26.6 

Uncongested street sampling site was 20 m from the 

congested street sampler. 

The opening of the by-pass produced a reduction in pollution 

in the congested streets. The health effects of these changed 

are likely to be greater for nasal and ocular symptoms than for 

lower respiratory symptoms. Uncertainty about the causality 

arises from low response rates and conflicting trends in 

respiratory and nasal symptoms. 

December 2009 E-416 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: CalderónGarcidueñas et al. (2006, 

091253) 

Period of Study: 

1999-2000 

Location: Southwest 

Mexico City & Tlaxcala, 

Mexico 

Outcome: Hyperinflation, interstitial 

markings-measured by chest 

radiograph, and lung function-FVC, 

FEV1, PEF, FEF25-75, measured 

using spirometry tests 

Age Groups: 5-13 yr 

Study Design: Cohort1999- 

N: 249 (total), 230 (Southwest 

Mexico City), 19 (Tlaxcala) 

Statistical Analyses: Bayes test, 

Spearman rank correlation, multiple 

regression 

Covariates: Age, sex 

Dose-response Investigated? No 

Statistical Package: SAS 8.2 

Pollutant: PM2.5

Averaging Time: 1 yr 

Mean (SD): 21 

2000-19 

Tlaxacala: 

1994-2000: <NAAQS std 

Mexico City 

Monitoring Stations: 

Southwest Mexico City-2 

Tlxacala-periodic air monitoring 

data 

Copollutant: O3

PM Increment: NR 

% Change: 

% of children with FEV1 <80% expected value: 

Mexico City (n = 77): 7.8% 

Tlaxacala (n = 19): 0% 

% children with hyperinflation: Mexico City: 65.6% 

Number with: 

No hyperinflation: 79 

Mild: 72 

Moderate: 56 

Severe: 23 

Tlaxacala: 5.3% 

Number with: 

No hyperinflation: 18 

Mild: 1 

Moderate: 0 

Severe: 0 

% children with interstitial markings: 

Mexico City: 52.6% 

Number with: 

No interstitial markings: 19 

Mild: 0 

Moderate: 0 

Severe: 0 

Tlaxacala: 0% 

Number with: 

No interstitial markings: 109 

Mild: 112 

Moderate: 9 

Severe: 0 

Reference: Cesaroni et 

al. (2008, 156326) 

Period of Study: Data 

on PM emissions 

collected in 2002 

cross-sectional survey 

carried out in 1995 

Location: Rome, Italy 

Outcome: Self-reported chronic 

bronchitis or emphysema, asthma, 

and rhinitis 

Age Groups: 25-59 yr 

Study Design: Cross-sectional

N: 9,488 subjects who had been 

residents in same place for at least 

3 yr and who had participated in an 

extension of the ISAAC initiative in 

Italy in 1994 & 1995 

Statistical Analyses: GEE with a 

logit link 

Covariates: Sex, age, smoking 

habits, education level, and variable 

to account for correlation of data for 

members of the same family 

Effect Modifiers: stratified analysis 

by smoking status (only presented 

for the traffic score variable) 

Also stratified by education level 

(data not shown)

Dose-response Investigated: 

Wald test to calculate p for trend 

Pollutant: PM emissions 

(estimated) 

Emissions estimated using a 

model/method based on factors 

such as vehicle park, driving 

conditions, emission factors, fuel 

consumption, fuel properties, road 

gradients, and climatic conditions 

Mean: 0.12 kg/km2

SD: 0.081 

Odds Ratios for quartiles of PM emissions: 

Chronic bronchitis or emphysema (n = 397): 

1st: 1.00 

2nd: 0.96 (0.71, 1.30) 

3rd: 0.90 (0.66, 1.23) 

4th: 1.05 (0.77, 1.42) 

p-trend = 0.871 

Asthma (n = 472): 

1st: 1.00 

2nd: 1.10 (0.84, 1.44) 

3rd: 0.94 (0.71, 1.24) 

4th: 1.06 (0.80, 1.39) 

p-trend = 0.980 

Rhinitis (n = 1227): 

1st: 1.00 

2nd: 1.41 (1.17, 1.69) 

3rd: 1.11 (0.92, 1.34) 

4th: 1.37 (1.14, 1.64) 

p-trend = 0.018 

December 2009 E-417 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dales et al., 

(2008, 156378) 

Period of Study:

Location: Windsor, ON 

Outcome: Pulmonary function and 

inflammation 

Age Groups: Grades 4-6 

Study Design: Cross-sectional 

prevalence design 

Statistical Analyses: Multivariate 

linear regression 

Covariates: Ethnic background, 

smokers at home, pets at home, 

acute respiratory illness, medication 

use 

Pollutant: PM2.5

Averaging Time: Annual 

Mean: 15.4 

5th: 14.2 

95th: 17.2 

Copollutant: 

SO2

NO2

Increment: Tertiles of exposure 

FEV1: <15.19: 2.16 ± 0.01 

15.19-15.96: 2.17 ± 0.02 

>15.96: 2.18 ± 0.01 

FVC: 

<15.19: 2.51 ± 0.02 

15.19-15.96: 2.50 ± 0.02 

>15.96: 2.52 ± 0.02 

eNO: 

<15.19: 16.08 ± 0.70 

15.19-15.96: 15.80 ± 0.76 

>15.96: 16.79 ± 0.72 

Reference: Gauderman 

et al. (2000, 012531) 

Period of Study: 

1993-1997 

Location: Southern 

California 

Outcome: FVC, FEV1, MMEF, 

FEF75 

Age Groups: Fourth, seventh, or 

tenth graders 

Study Design: Cohort

N: 3035 subjects 

Statistical Analyses: Linear 

regression 

Covariates: Height, weight, BMI, 

asthma, smoking, exercise, room 

temperature, barometric pressure 

Dose-response Investigated? Yes

Statistical Package: SAS 

Pollutant: PM2.5

Averaging Time: Annual avg of 

2-wk avg PM2.5

Mean (SD): PM2.5 25.9 

Copollutant (correlation): 

03: r = -0.32 

PM10-2.5: r = 0.76 

NO2: r = 0.74 

Inorg. Acid: r = 0.79 

Increment: 25.9 μg/m3

% Change (Lower CI, Upper CI) 

PM2.5-4th grade 

 FVC -0.47 (-0.94, 0.01) 

 FEV1 -0.64 (-1.28, 0.01) 

 MMEF -1.03 (-1.95 to -0.09) 

 FEF75 -1.31 (-2.57 to -0.03) 

PM2.5-7th grade 

 FVC -0.42 (-0.89, 0.05) 

 FEV1 -0.32 (-0.88, 0.24) 

 MMEF -0.29 (-1.99, 1.44) 

 FEF75 -0.26 (-1.75, 1.25) 

PM2.5-10th grade 

 FVC 0.19 (-0.68, 1.07) 

 FEV1 -0.25 (-1.41, 0.93) 

 MMEF -0.17 (-3.66, 3.46) 

 FEF75 -0.79 (-4.27, 2.82) 

Reference: Gauderman 

et al. (2002, 026013) 

Period of Study: 

1996-2000 

Location: Southern 

California 

Outcome: Lung function 

development: FEV1, maximal 

midexpiratory flow (MMEF) 

Age Groups: Fourth grade children 

(avg age = 9.9 yr) 

Study Design: Cohort study

N: 1678 children, 12 communities 

Statistical Analyses: Mixed model 

linear regression 

Covariates: Height, BMI, doctordiagnosed asthma and cigarette 

smoking in previous yr, respiratory 

illness and exercise on day of test, 

interaction of each of these 

variables with sex, barometric 

pressure, temperature at test time, 

indicator variables for field 

technician and spirometer 

Dose-response Investigated? Yes

Statistical Package: SAS (10) 

Pollutant: PM2.5

Averaging Time: Annual 24-h avg 

Mean (SD): The avg levels were 

presented in an online data 

supplement (Fig E1) 

PM Component: EC and OC. 

Monitoring Stations: 12 

Copollutant (correlation): 

O3: (10 AM to 6 PM) r = 0.14 

O3: r = -0.39 

NO2: r = 0.77 

Acid vapor: r = 0.87 

PM10: r = 0.95 

PM10-2.5: r = 0.81 

EC: r = 0.93 

OC: r = 0.89 

PM Increment: 22.2 μg/m3

Association Estimate: 

Non-statistically significant negative correlation between PM2.5

and FEV1and FVC growth rates were observed. MMEF growth 

rates had a negative correlation with PM2.5 (r = -0.43 p = 0.05). 

PM2.5 was not significantly correlated to FEV1 (r = -0.31 

p = 0.25) 

December 2009 E-418 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Gauderman 

et al., 2004, 056569) 

Period of Study: Air 

pollution data 

ascertainment: 

1994-2000. Spirometry 

testing: spring 

2001-spring 2003 

Location: 12 

Communities in Southern 

California 

Outcome: Lung function 

FVC, FEV1, MMEF (Maximal 

midexpiratory flow rate) 

Age Groups: Children, Avg age 10 

yr 

Study Design: Prospective Cohort 

Study

N: 12 Communities 

2,034 children 

24,972 child-mo 

Statistical Analyses: Linear 

regression of changes in sex-andcommunity specific lung growth 

function and PM 

Correlation between % with low 

attained FEV1 and PM. 

Covariates: Random effect for 

communities 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM2.5 

Averaging Time: 2-wk 

measurements used to create 

annual avg 

Mean: Means are presented in 

figures only. 

Range (Min, Max): ~6, ~27 

Monitoring Stations: 12 

Copollutant (correlation): 

PM10: r = 0.95 

O3: r = 0.18 

NO2: r = 0.79 

EC: r = 0.91 

OC: r = 0.91 

PM Increment: Most to least polluted community Range: 

22.8 μg/m3

Difference in Lung Growth [Lower CI, Upper CI]; 

FVC -60.1 (-166.1 to 45.9) 

FEV1 -79.7 (-153.0 to ¡6.4) 

MMEF -168.9 (-345.5 to 7.8) 

Correlation with % below 80% predicted Lung function (pvalue) 

PM2.5: 0.79 (0.002) 

Reference: Gauderman 

et al. (2007, 090121) 

Period of Study: 

1993-2004 

Location: 12 Southern 

California Communities 

Outcome: Pulmonary function tests 

FVC, FEV1, MMEF/FEF25.75 

Age Groups: Children (mean age 

10 at recruitment, followed for 8 yr) 

Study Design: Cohort Study 

(Children’s Health Study)

N: 3677 children (1718 in cohort 1 

recruited 1993 and 1959 in cohort 2 

recruited 1996) 

22686 pulmonary function tests. 

Statistical Analyses: Hierarchical 

mixed effects model with linear 

splines 

Covariates: Adjustments for height, 

height squared, BMI, BMI squared, 

present asthma status, exercise or 

respiratory illness on day of test, 

smoking in previous yr, field 

technician, traffic indicator (distance 

from freeway, distance from major 

roads), random effects for 

participant and community. 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM2.5

Monitoring Stations: 1 in each 

community 

PM Increment: 22.8 μg/m3

Pollutant effect reported as difference in 8 yr lung function 

growth from least to most polluted community. Negative 

difference indicate growth deficits associated with exposure. 

For PM2.5 FEV growth deficit is -100 

Reference: Gehring et 

al. (2002, 036250) 

Period of Study: 

1995-2002 

Location: Munich, 

Germany 

Outcome: Wheezing, cough 

without infection, dry cough at night, 

obstructive, spastic or asthmoid 

bronchitis, respiratory infections, 

sneezing, runny/stuffed nose 

Age Groups: 0-2 yr 

Study Design: Prospective cohort

N: 1756 infants 

Statistical Analyses: Logistic 

regression 

Covariates: Sex, parental atopy 

(yes/no), maternal education, 

siblings (y/n), environmental 

tobacco smoke at home (y/n), use 

of gas for cooking (y/n), home 

dampness (y/n), indoor moulds 

Pollutant: PM2.5

Mean (SD): PM2.5 mass: 13.4 

PM2.5 absorb. 1.77 * 10-5/m 

Percentiles: PM2.5 mass: 

10th: 12.2 

25th: 12.5 

50th(Median): 13.1 

75th: 14.0 

90th: 14.9 

PM2.5 absorbance: 

10th: 1.47 * 10-5 

25th: 1.54 * 10-5 

PM Increment: 

PM2.5 mass: 1.5 μg/m3 

PM2.5 absorb. 0.4 * 10-5/m (IQR) 

RR Estimate [Lower CI, Upper CI] 

Wheeze (PM2.5 mass) 

Age of 1 yr: All: 0.91 (0.76-1.09) 

Males: 0.91 (0.72-1.16) 

Females: 0.94 (0.70-1.27) 

Age of 2 yr: All: 0.96 (0.83-1.12) 

Males: 0.93 (0.76-1.14) 

Females: 1.04 (0.83-1.30) 

Cough W/O Infection (PM2.5 mass) 

Age of 1 yr: All: 1.34 (1.11-1.61) 

Males: 1.43 (1.14-1.80) 

Females: 1.19 (0.84-1.70) 

Dry Cough At Night (PM2.5 mass) 

Age of 1 yr: All: 1.31 (1.07-1.60) 

Males: 1.39 (1.08-1.78) 

Females: 1.17 (0.81-1.68) 

December 2009 E-419 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

(y/n), keeping of dogs (y/n) and cats 

(y/n) study (GINI or LISA) 

Dose-response Investigated? No 

50th(Median): 1.70 * 10-5 

75th: 1.88 * 10-5 

90th: 2.13 * 10-5 

Range (Min, Max): 

PM2.5 mass: 11.9, 21.9 

PM2.5 absorbance: 

1.38 to 4.39 * 10-5 

PM2.5 mass: 

PM2.5 absorbance: 1/m 

PM Component: PM2.5 mass 

PM2.5 absorbance (as a marker of 

diesel soot) 

Monitoring Stations: 40 

Copollutant (correlation): 

NO2: r = 0.99 

PM2.5 absorbance and NO2: r = 0.95

PM2.5 mass and PM2.5 absorbance: 

r = 0.96 

Age of 2 yr: All: 1.20 (1.02-1.42) 

Males: 1.25 (1.01-1.55) 

Females: 1.13 (0.86-1.48) 

Bronchitis (PM2.5 mass) 

Age of 1 yr: All: 0.98 (0.80-1.20) 

Males: 0.97 (0.76-1.25) 

Females: 0.98 (0.68-1.41) 

Age of 2 yr: All: 0.92 (0.78-1.09) 

Males: 0.92 (0.74-1.14) 

Females: 0.91 (0.68-1.21) 

Resp Infections (PM2.5 mass) 

Age of 1 yr: All: 1.04 (0.91-1.19) 

Males: 1.04 (0.87-1.25) 

Females: 1.06 (0.87-1.31) 

Age of 2 yr: All: 0.98 (0.80-1.20) 

Males: 0.99 (0.74-1.31): Females: 0.98 (0.73-1.31) 

Sneezing/Runny Nose (PM2.5 mass) 

Age of 1 yr: All: 1.01 (0.85-1.20)

Males: 0.97 (0.77-1.24) 

Females: 1.08 (0.84-1.41) 

Age of 2 yr: All: 0.96 (0.82-1.12) 

Males: 0.91 (0.73-1.12) 

Females: 1.04 (0.83-1.31) 

Wheeze (PM2.5 absorbance) 

Age of 1 yr: All: 0.93 (0.78-1.12) 

Males: 0.91 (0.71-1.15) 

Females: 1.01 (0.74-1.37) 

Age of 2 yr: All: 0.98 (0.84-1.14) 

Males: 0.92 (0.75-1.13) 

Females: 1.07 (0.85-1.36) 

Cough W/O Infection (PM2.5 absorbance) 

Age of 1 yr: All: 1.32 (1.10-1.59) 

Males: 1.38 (1.11-1.71) 

Females: 1.25 (0.87-1.78) 

Dry Cough At Night (PM2.5 absorbance) 

Age of 1 yr: All: 1.27 (1.04-1.55) 

Males: 1.31 (1.04-1.67) 

Females: 1.16 (0.79-1.71) 

Age of 2 yr: All: 1.16 (0.98-1.37) 

Males: 1.17 (0.95-1.44) 

Females: 1.12 (0.84-1.48) 

Bronchitis (PM2.5 absorbance) 

Age of 1 yr: All: 0.99 (0.81-1.22) 

Males: 1.00 (0.78-1.27) 

Females: 0.94 (0.63-1.39) 

Age of 2 yr: All: 0.94 (0.79-1.12) 

Males: 0.91 (0.72-1.13) 

Females: 0.95 (0.71-1.28) 

Resp Infections (PM2.5 absorbance) 

Age of 1 yr: All: 1.03 (0.90-1.18) 

Males: 1.03 (0.86-1.23) 

Females: 1.05 (0.85-1.30) 

Age of 2 yr: All: 0.99 (0.80-1.22) 

Males: 0.96 (0.73-1.26) 

Females: 1.04 (0.75-1.43) 

Sneezing/Runny Nose (PM2.5 absorbance) 

Age of 1 yr: All: 0.95 (0.79-1.14)

Males: 0.90 (0.70-1.16) 

Females: 1.06 (0.80-1.39)

Age of 2 yr: All: 0.92 (0.78-1.09) 

Males: 0.83 (0.66-1.05) 

Females: 1.06 (0.83-1.34)) 

December 2009 E-420 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Goss et al. 

(2004, 055624) 

Period of Study: 

1999-2000 

Location: USA 

Outcome: Cystic Fibrosis 

pulmonary exacerbations, FEV1

Age Groups: Children and adults 

over the age of 6 

Study Design: Ccohort

N: 11484 patients 

Statistical Analyses: Logistic 

regression, t-tests, Mann-Whitney 

tests, Chi-squared tests, 

polytomous regression, multiple 

linear regression 

Covariates: Age, sex, lung 

function, weight, insurance status, 

pancreatic insufficiency, airway 

colonization, genotype, median 

household income by census tract, 

zipcode. 

Dose-response Investigated? No 

Statistical Package: STATA, SAS 

Pollutant: PM2.5

Averaging Time: Annual mean of 

24-h avg 

Mean (SD): 13.7(4.2) 

Percentiles: 25th: 11.8 

50th(Median): 13.9 

75th: 15.9 

Monitoring Stations: 713 

PM Increment: 10 μg/m3

Odds Ratio Estimate [Lower CI, Upper CI]: 

Odds of having 2 or more pulmonary exacerbations as 

compared to 1 or less in 2000 

1.21 (1.07 -1.33) 

Odds of having 1 pulmonary exacerbation as compared to no 

exacerbations in 2000 

0.70 (0.59-0.98) 

Decrease in FEV1 155ml(115-194) 

Decrease in FEV1 in 2000 after adjusting for FEV1 in 1999 

24ml(7-40) 

Reference: HertzPicciotto et al. (2005, 

088678) 

Period of Study: May 

1994-Mar 1999 

Location: Teplice and 

Prachatice, Czech 

Republic 

Outcome: Developmental 

immunotoxicity as assessed by 

neonatal immunophenotypes 

Age Groups: Not specified: every 

woman who delivered in the two 

aforementioned districts were asked 

to participate 

Study Design: Cohort study

N: 1397 mother-infant pairs 

Statistical Analyses: Multiple 

linear regression with lymphocyte 

percentage as responding variable 

and pollutant exposure to 14day 

averaging period before the date of 

cord blood collection 

Covariates: Season, length of 

labor, parity, number of previous 

stillbirths, medication during 

delivery, working status of mother, 

maternal education, exposure to 

active and secondhand smoke, 

family history of allergy, self-reports 

of workplace exposure to dust 

during pregnancy, self-reported 

maternal chronic or severe 

respiratory diseases during 

pregnancy. Ambient temperature 

and season were controlled for. 

Dose-response Investigated? Yes

Statistical Package: SUDAAN 

(version 8) 

Pollutant: PM2.5

Averaging Time: 24 h 

14 day avg 

Mean (SD): Overall 24 h: 24.8 

14-day avg: 

Teplice: 30.1 

Prachatice 19.8 

PM Component: PAHs 

Monitoring Stations: 2 stations: 

Teplice and Prachatice 

PM Increment: 25 μg/m3

Adjusted for 3-day temperature and season, PM2.5 exposure 

during the 14 days before birth was associated with reduced 

T-lymphocyte fractions CD4+, CD3+ and an increase in Blymphocyte fraction (CD19+). 

The associations were not quantitatively reported anywhere 

else in the paper other than in Fig 2 and Table 3 

December 2009 E-421 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (HertzPicciotto et al., 2007, 

135917) 

Period of Study: 

1994-98 + follow-ups at 

up to 4.5 yr of age for 

child 

Location: Czech 

Republic districts of 

Teplice and Prachatice 

Outcome: Lower respiratory 

illnesses, majority being acute 

laryngitis, tracheitis, bronchitis. 

ICD10 codes J04 and J20 

Age Groups: Birth-4.5 yr of age. 

Study Design: Longitudinal follow 

up of a stratified random sample of 

mother-infant pairs from previous 

Pregnancy Outcome Study. Low 

birth weight and preterm births 

sampled at higher fractions.

N: 1133 children 

Statistical Analyses: Generalized 

linear longitudinal models, GEE to 

adjust for within subject 

correlations, robust variance 

estimates were obtained. Model fit 

judged using Akaike Information 

criterion. 

Covariates: Age of child, breast 

feeding, environmental tobacco 

smoke, season, day of week, yr of 

birth, gender, birth weight, 

pregnancy data including age at 

delivery, length of gestation, 

maternal hypertension and 

diabetes, infant APGAR score, 

maternal work history, 

demographics, lifestyle, 

reproductive and medical histories, 

temperature, fuel type, other 

children in household 

Dose-response Investigated? No 

Statistical Package: SUDAAN 

version 8 

Pollutant: PM2.5

Averaging Time: Used 3-, 7-, 14-, 

30- and 45-day avg 

Mean (SD): Daily mean 22.3 

(sd 16 for 3-day avg, 11 for 45-day 

avg) 

PM Increment: 25 μg/m3

RR Estimate [Lower CI, Upper CI] lag: 

Bronchitis, birth-23 mo of age 

Categorical model 

High 30-day avg PM2.5 (greater than 50 μg/m3

) 

2.26(1.81-2.82) 

Medium 30-day avg PM2.5 (between 25 and 50 μg/m3) 

1.48(1.32-1.65) 

Continuous model 

1.30(1.08-1.58) 

Bronchitis, 2-4.5 yr of age 

Categorical model 

High 30-day avg PM2.5 (greater than 50 μg/m3

) 

3.66(2.07-6.48) 

Medium 30-day avg PM2.5 (between 25 and 50 μg/m3

) 

1.60(1.41-1.82) 

Continuous model 

1.23(0.94-1.62) 

Notes: Results of other averaging periods shown in plots. 

Reference: (Hogervorst 

et al., 2006, 156559) 

Period of Study: NR 

Location: Maastricht, the 

Netherlands (six schools 

selected) 

Outcome: 

Decreased lung function 

Age Groups: 8-13 yr old 

Study Design: Multivariate linear 

regression (enter method) analysis

N: 342 children 

Statistical Analyses: ANOVA, Chi 

square 

Covariates: Independent variables: 

Age, height, gender, smoking at 

home by parents, pets, use of 

ventilation hoods during cooking, 

presence of unvented geysers, 

tapestry in the home, indoor/outdoor 

time, education level of parents. 

Dependent variables: lung function 

indices 

Dose-response Investigated? No 

Pollutant: PM2.5

Averaging Time: Daily 

Mean (SD): 19.0 (3.2) 

Monitoring Stations: 6 

Copollutant: 

PM10

TSP 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] lag: 

FEV 

3.62 [0.50,7.63] 

FVC 

1.80 [-2.10, 5.80] 

FEF 

5.93 [-2.34, 14.89] 

December 2009 E-422 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Islam et al. 

(2007, 090697) 

Period of Study: 

1993-2001 

Location: 12 

communities in Southern 

California, U.S. 

Outcome: New onset asthma 

Age Groups: 9-10 yr 

Study Design: Cohort

N: 2057 

Statistical Analyses: Cox 

proportional hazard model 

Covariates: Community, sex, 

race/ethnicity

Season: All 

Dose-response Investigated? No 

Statistical Package: SAS V 9.1 

Lags Considered: 0-2 yr 

Pollutant: PM2.5

Range (Min, Max): 

“Low” PM2.5 Communities 

(5.7-8.5) 

“High” PM2.5 Communities 

(13.7-29.5) 

Monitoring Stations: 12 

Copollutant: NO2, acid vapor, PM10

and elemental and OC correlated 

as a “non-O3 package” of pollutants 

with a similar pattern relative to 

each other across the 12 

communities. 

PM Increment: NR 

IR Estimate [Lower CI, Upper CI] 

Low PM 

FVC ≤ 90: 19.4 (7.5, 50.5) 

FVC 90-110: 16.8 (7.0, 40.1) 

FVC >110: 7.9 (2.9, 21.9) 

FEV1 ≤ 90: 23.7 (9.4, 59.4) 

FEV1 90-110: 15.6 (6.5, 37.4) 

FEV1 >110: 6.5 (2.3, 18.7) 

FEF25-75 ≤ 90: 21.1 (8.8, 50.5) 

FEF25-75 90-110: 11.9 (4.7, 30.0) 

FEF25-75 >110: 6.4 (2.3, 18.2) 

Overall: 14.2 (7.0, 28.7) 

High PM 

FVC ≤ 90: 14.2 (5.1, 39.6) 

FVC 90-110: 25.6 (11.1, 59.2) 

FVC >110: 16.7 (6.5, 42.9) 

FEV1 ≤ 90: 20.8 (8.0, 54.0) 

FEV1 90-110: 23.1 (10.0, 53.7) 

FEV1 >110: 18.8 (7.5, 47.3) 

FEF25-75 ≤ 90: 23.8 (10.2, 55.6) 

FEF25-75 90-110: 23.9 (9.9, 57.7) 

FEF25-75 >110: 15.9 (6.3, 40.5) 

Overall: 18.4 (9.4, 35.9) 

Reference: Karr et al. 

(2007, 090719) 

Period of Study: 

1995-2000 

Location: South Coast 

Air Basin of southern 

California 

Outcome: Bronchioloitis 

Study Design: Case-control. 

Cases included subjects with a 

record of a single hospitalization 

with a discharge diagnosis of acute 

bronchiolitis.10 controls per case 

were matched on birth date and 

gestational age. 

N: 18,595 cases 

169,472 controls 

Statistical Analyses: Conditional 

logistic regression to estimate 

relative risk of hospitalization for 

bronchiolitis. 

Covariates: Confounders included 

in the model were: gender, parity, 

chronic lung disease, cardiac and 

pulmonary anomalies, SES 

covariates 

Age, Gestational age, and season 

of birth were controlled for by 

matching 

Dose-response Investigated? Yes

Statistical Package: STATA 

(Version 8) 

Pollutant: PM2.5 

Averaging Time: 24 h (lifetime 

monthly avg from birth & 30 days 

preceding cases hospitalization) 

Mean (SD): 25 

Percentiles: 25th: 19 

50th(Median): 23 

75th: 29 

Range (Min, Max): 6 to 111 

Monitoring Stations: 17 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

Sub-chronic and chronic exposure: OR = 1.09 (1.04-1.14) 

Adjusted for adjusted: Sub-chronic OR = 1.10 (1.04, 1.16) 

Chronic OR = 1.09 (1.03-1.15) 

Adjusted for CO and NO2: Sub-chronic OR = 1.14 (1.07, 1.21) 

Chronic OR = 1.12 (1.06, 1.20) 

Adjusted for O3, CO, and NO2: Chronic OR = 1.15 (1.08, 1.22) 

Sub-chronic OR = 1.13 (1.06, 1.21) 

Reference: (Kim et al., 

2004, 087383) 

Period of Study: 

Mar-Jun (spring) 2001 

Sep-Nov (fall) 2001 

Location: Alameda 

County, CA 

Outcome: Asthma, bronchitis 

Age Groups: Children (grades 3-5) 

Study Design: Cross-sectional

N: 1109 children, 871 (long term 

resident children), 462 (long term 

related females), 403 (long term 

related males) 

Statistical Analyses: 2-stage 

multiple logistic regression model 

Covariates: Respiratory illness 

before age of 2, household 

mold/moisture, pests, maternal 

history of asthma (for asthma) 

Season: spring and fall 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.2 

Pollutant: PM2.5

Averaging Time: 10 wk 

Mean (SD): Study Avg 12 

Monitoring Stations: 10 

Copollutant (correlation): r2 is 

approximately 0.9 for all 

copollutants-Black Carbon (BC), 

PM10, NOX, NO2, NO (NOX-NO2) 

PM Increment: 0.7 (IQR) 

OR Estimate [Lower CI, Upper CI]: 

Bronchitis 

All subjects: 1.02 [1.00, 1.08] 

LTR subjects: 1.03 [1.01, 1.08] 

LTR females: 1.04 [1.02, 1.05] 

LTR males: 1.02 [0.99, 1.05] 

Asthma 

All subjects: 1.00 [0.96, 1.12] 

LTR subjects: 1.01 [0.97, 1.06] 

LTR females: 1.06 [0.99, 1.15] 

LTR males: 0.99 [0.95, 1.04] 

Asthma excluding outlier school having a larger proportion of 

Hispanics 

All subjects: 1.04 [0.96, 1.12] 

LTR subjects: 1.03 [0.94, 1.13] 

LTR females: 1.03 [0.91, 1.17] 

LTR males: 1.03 [0.94, 1.18] 

December 2009 E-423 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Leonardi et 

al. (2000, 010272) 

Period of Study: 1996 

Location: 17 cities of 

Central Europe (Bulgaria, 

Czech Republic, Hungary 

, Poland, Romania, 

Slovakia) 

Outcome: Immune biomarkers 

Age Groups: 9-11 

Study Design: Cross-sectional 

N: 366 school children 

Statistical Analyses: Linear 

regression 

Covariates: Age, gender, parental 

smoking, laboratory of analysis, 

recent respiratory illness 

Dose-response Investigated? No 

Statistical Package: STATA 

Pollutant: PM2.5

Averaging Time: Annual PM2.5

Mean (SD): PM2.5: 46 (10) 

Range (Min, Max): 

PM2.5: (29, 67) 

5th, median, & 95th percentile 

PM2.5: 29, 44, 67 

% Change (Lower CI, Upper CI) p-value 

PM2.5

Neutrophils -10 (-45, 46) 

>.20 

Total lymphocytes 49 (11, 101); .008 

B lymphocytes 63 (4, 155); .034 

Total T lymphocytes 72 (32 

123) 

<.001 

CD4+ 80 (34 

143) 

<.001 

CD8+ 61 (17, 119); .003 

CD4/CD8 16 (-17, 62) 

>.20 

NK 63 (3, 158); .035 

Total IgG 24 (2, 52); .034 

Total IgM -9 (-32, 22) 

>.20 

Total IgA -1 (-25, 32) 

>.20 

Total IgE -4 (-61, 137) 

>.20 

Reference: McConnell 

(1999, 007028) 

Period of Study: 1993 

Location: Southern 

California 

Outcome: Bronchitis, chronic 

cough, phlegm 

Age Groups: Children: 4th, 7th, & 

10th graders 

Study Design: Cross-sectional

N: 3676 people 

Statistical Analyses: Logistic 

regression 

Covariates: Age, sex, race, grade, 

health insurance 

Dose-response Investigated? Yes

Pollutant: PM2.5

Averaging Time: Yearly 2-wk avg 

Mean (SD): 15.3 

Range (Min, Max): 6.7, 31.5 

Copollutant (correlation): 

NO2 r = 0.83 

O3 r = 0.50 

Acid r = 0.71 

Child Respiratory symptoms OR Estimate (Lower CI, 

Upper CI) 

PM2.5 Increment: 15 μg/m3

Children w/ asthma 

Bronchitis: 1.4 (0.9, 2.3) 

Phlegm: 2.6 (1.2, 5.4) 

Cough: 1.3 (0.7, 2.4) 

Children w/ wheeze, no asthma 

Bronchitis: 0.9 (0.6, 1.4) 

Phlegm: 1.0 (0.6, 1.8) 

Cough: 1.1 (0.6, 1.9) 

Children w/ no wheeze, no asthma 

Bronchitis: 0.5 (0.3, 1.0) 

Phlegm: 0.8 (0.4, 1.5) 

Cough: 0.9 (0.6, 1.3) 

Reference: McConnell et 

al. (2003, 049490) 

Period of Study: 

1993-1999 

Location: 12 Southern 

CA communities 

Outcome: Bronchitic symptoms 

Age Groups: 9-19 

Study Design: Communities 

selected on basis of historic levels 

of criteria pollutants and low 

residential mobility.

N: 475 children 

Statistical Analyses: 3 stage 

regression combined to give a 

logistic mixed effects model 

Covariates: Sex, ethnicity, allergies 

history, asthma history, SES, 

insurance status, current wheeze, 

current exposure to ETS, personal 

smoking status, participation in 

team sports, in utero tobacco 

exposure through maternal 

smoking, family history of asthma, 

amount of time routinely spent 

outside by child during 2-6 pm. 

Dose-response Investigated? No 

Statistical Package: SAS Glimmix 

macro 

Pollutant: PM2.5

Averaging Time: 4-yr avg 

Mean (SD): 13.8(7.7) 

Range (Min, Max): 5.5-28.5 

Copollutant (correlation): 

PM10: r = 0.79 

PM10-2.5: r = 0.24 

Inorganic acid: r = 0.76 

Organic Acid: r = 0.58 

EC: r = 0.83 

OC: r = 0.84 

NO2: r = 0.54 

O3: r = 0.72 

PM Increment: Between community range 23 μg/m3

Between community unit 1 μg/m3

Within community 1 μg/m3

OR Estimate [Lower CI, Upper CI] 

Between community per range 

1.81(1.14-2.88) 

Between Community per unit 

1.03(1.01-1.05) 

Within community per unit 

1.09(1.01-1.17) 

December 2009 E-424 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: McConnell et 

al. (2003, 049490) 

Period of Study: 

1993-1999 

Location: 12 Southern 

CA communities 

Outcome: Bronchitic symptoms 

Age Groups: 9-19 

Study Design: Communities 

selected on basis of historic levels 

of criteria pollutants and low 

residential mobility.

N: 475 children 

Statistical Analyses: 3 stage 

regression combined to give a 

logistic mixed effects model 

Covariates: Sex, ethnicity, allergies 

history, asthma history, SES, 

insurance status, current wheeze, 

current exposure to ETS, personal 

smoking status, participation in 

team sports, in utero tobacco 

exposure through maternal 

smoking, family history of asthma, 

amount of time routinely spent 

outside by child during 2-6 pm. 

Dose-response Investigated? No 

Statistical Package: SAS Glimmix 

macro 

Pollutant: EC 

Averaging Time: 4-yr avg 

Mean (SD): 0.71(0.41) 

Range (Min, Max): 0.1-1.2 

Copollutant (correlation): 

PM2.5: r = 0.83 

PM10: r = 0.71 

PM10-2.5: r = 0.30 

Inorganic acid: r = 0.82 

Organic Acid: r = 0.66 

OC: r = 0.88 

NO2: r = 0.54 

O3: r = 0.68 

PM Increment: Between community range 1.1 μg/m3

Between community unit 1 μg/m3

Within community 1 μg/m3

OR Estimate [Lower CI, Upper CI] 

Between community per range 

1.64(1.06-2.54) 

Between Community per unit 

1.55(1.05-2.30) 

Within community per unit 

2.63(0.83-8.33) 

Reference: McConnell et 

al. (2003, 049490) 

Period of Study: 

1993-1999 

Location: 12 Southern 

CA communities 

Outcome: Bronchitic symptoms 

Age Groups: 9-19 

Study Design: Communities 

selected on basis of historic levels 

of criteria pollutants and low 

residential mobility.

N: 475 children 

Statistical Analyses: 3 stage 

regression combined to give a 

logistic mixed effects model 

Covariates: Sex, ethnicity, allergies 

history, asthma history, SES, 

insurance status, current wheeze, 

current exposure to ETS, personal 

smoking status, participation in 

team sports, in utero tobacco 

exposure through maternal 

smoking, family history of asthma, 

amount of time routinely spent 

outside by child during 2-6 pm. 

Dose-response Investigated? No 

Statistical Package: SAS Glimmix 

macro 

Pollutant: OC 

Averaging Time: 4-yr avg 

Mean (SD): 4.5(2.7) 

Range (Min, Max): 1.4-11.6 

Copollutant (correlation): 

PM2.5: r = 0.84 

PM10: r = .70 

PM10-2.5: r = 0.27 

Inorganic acid: r = 0.83 

Organic Acid: r = 0.69 

EC: r = 0.88 

NO2: r = 0.67 

O3: r = 0.81 

PM Increment: Between community range 10.2 μg/m3

Between community unit 1 μg/m3

Within community 1 μg/m3

OR Estimate [Lower CI, Upper CI] 

Between community per range 

1.74(0.89-3.4) 

Between Community per unit 

1.06(0.99-1.13) 

Within community per unit 

1.41(1.12-1.78) 

December 2009 E-425 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: McConnell, 

et al. (2006, 180226) 

Period of Study: 

1996-1999 

Location: 12 Southern 

California communities 

Outcome: 

Prevalence of bronchitic symptoms 

(yrly). 

Age Groups: 10-15-yr-old 

Study Design: Longitudinal cohort

N: 475 asthmatic children 

Statistical Analyses: Multilevel 

logistic mixed effects models. 

Covariates: Age, second-hand 

smoke 

Personal smoking history 

Sex, race. 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: PM2.5

Averaging Time: 365 days 

Percentiles: Community by yr 

(n = 48 = 12 communities · 4 yr) 

25th: NR 

50th(Median): 3.4 

75th: NR 

Range (Min, Max): Community by 

yr (n = 48 = 12 communities · 4 yr): 

(0.89, 8.7) 

Monitoring Stations: 12 

Copollutant: 

O3

NO2

EC 

OC 

Acid vapor (acetic and formic acid) 

PM Increment: 3.4 μg/m3

OR Estimate [Lower CI, Upper CI] 

PM2.5

Dog (n = 292): 1.56 [1.15: 2.12] 

No dog (n = 183): 1.03 [0.71: 1.49] 

PM2.5*Dog interaction p-value: 0.06 

Cat (n = 202): 1.30 [0.90: 1.88] 

No Cat (n = 273): 1.36 [0.99: 1.83] 

PM2.5*Cat interaction p-value: 0.87 

Neither pet (n = 112): 1.11 [0.71: 1.74] 

Cat only (n = 71): 0.85 [0.46: 1.57] 

Dog only (n = 161): 1.53 [1.04: 2.25] 

Both pets (n = 131): 1.58 [1.02: 2.46] 

Results suggest that dog ownership, a source of residential 

exposure to endotoxin, may worsen the severity of respiratory 

symptoms from exposure to air pollutants in asthmatic 

children. 

Although PM2.5 was associated at a statistically significant 

level with ownership of both cats and dogs, it appears that dog 

ownership (with or without a cat) specifically worsens the 

association between PM2.5 and respiratory symptoms in 

asthmatic children. 

Reference: (Meng et al., 

2007, 093275) 

Period of Study: Nov 

2000 and Sep 2001 

Location: Los Angeles 

and San Diego counties 

Outcome: Poorly controlled asthma 

vs. controlled asthma 

ICD9NR 

Age Groups: 18-64, 65+ 

Study Design: Long-term exposure 

study 

comparison of cases and controls 

N: 1,609 adults (represented 

individuals age 18+ who reported 

ever having been diagnosed as 

having asthma by a physician and 

had their address successfully 

geocoded) 

Statistical Analyses: Logistic 

regression to evaluate associations 

between TD (traffic density) and 

annual avg air pollution 

concentrations and poorly 

controlled asthma. Used sample 

weights that adjusted for unequal 

probabilities of selection into the 

CHIS sample. 

Covariates: Age, sex, 

race/ethnicity, family federal poverty 

level, county, insurance status, 

delay in care for asthma, taking 

medications, smoking behavior, 

self-reported health status, 

employment, physical activity 

Dose-response Investigated? yes 

Pollutant: PM2.5

Averaging Time: 24 h 

Copollutant (correlation): 

O3: r = -0.76 

NO2: r = 0.87 

PM10: r = 0.84 

CO: r = 0.52 

TD: r = 0.13 

Results for PM2.5 were nonsignificant and not reported 

quantitatively. 

December 2009 E-426 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Millstein, J et 

al. (2004, 088629) 

Period of Study: 

Mar-Aug 1995, and Sep 

1995-Feb 1996 

Data were taken from the 

Children’s Health Study 

Location: Alpine, 

Atascadero, Lake 

Arrowhead, Lake 

Elsinore, Lancaster, 

Lompoc, Long Beach, 

Mira Loma, Riverside, 

San Dimas, Santa Maria, 

and Upland, CA 

Outcome: Wheezing & asthma 

medication use (ICD 9 NR) 

Age Groups: 4th grade students, 

mostly 9 yr at the time of the study 

Study Design: Cohort Study, 

stratified into 2 seasonal groups/

N: 2081 enrolled, 2034 provided 

parent-completed questionnaire. 

Statistical Analyses: Multilevel, 

mixed-effects logistic model. 

Covariates: Contagious respiratory 

disease, ambient airborne pollen 

and other allergens, temperature, 

sex, age race, allergies, pet cats, 

carpet in home, environmental 

tobacco smoke, heating fuel, 

heating system, water damage in 

home, education level of 

questionnaire signer, physician 

diagnosed asthma. 

Season: Mar-Aug, 1995, and Sep, 

1995 to Feb, 1996 

Statistical Package: GLIMMIX 

SAS 8.00 macro for generalized 

linear mixed models. 

Lags Considered: 14 

Pollutant: PM2.5

Averaging Time: Integrated values 

for successive 2-wk periods 

PM Component: Nitric acid, formic 

acid, acetic acid 

Monitoring Stations: 1 central 

location in each community 

Copollutant (correlation): 

O3: r = 0.09 

NO2: r = 0.28 

PM10: r = 0.33 

PM10-2.5: r = -0.08 

PM Increment: IQR: 5.24 μg/m3

Odds Ratio [lower CI, Upper CI] 

Annual 

PM2.5: 1.04 [0.83, 1.29] 

Mar-Aug 

PM2.5: 0.91 [0.64, 1.30] 

Sep-Feb 

PM2.5: 1.18 [0.89, 1.58] 

Reference: Morgenstern 

et al. (2007, 090747) 

Period of Study: Mar 

1999-Jul 2000 

Location: Munich, 

Germany 

Outcome: Asthma, wheezing, 

spastic/obstructive bronchitis. Dry 

cough at night, respiratory 

infections, sneezing, runny/stuffed 

nose without a cold. 

Age Groups: at 1 yr & at 2 yr 

Study Design: Cohort

N: 3577 children for the prediction 

models. Respiratory data available 

for 3129 children at 1 yr. 

Statistical Analyses: Pearson’s 

correlation coefficient, prediction 

error expressed as root mean 

squared error (RMSE), multiple 

logistic regression with confounding 

factors, odds ratios 

Covariates: Sex, Parental atopy 

(genetic predisposition to allergies), 

environmental tobacco smoke at 

home, maternal education >or <12 

yr, sibling, gas stove, home 

dampness, indoor mold, pets. Since 

it was not feasible to measure 

personal exposure to NO2, PM2.5, 

and PM2.5 absorbance, exposure 

modeling was used. 

Statistical Package: SAS V.8.02 

Pollutant: PM2.5

Averaging Time: Annual 

Mean (SD): 12.8 

Percentiles: 25th: 12.5 

50th(Median): 12.9 

75th: 13.3 

Range (Min, Max): 6.8, 15.3 

Monitoring Stations: 40: traffic, 

n = 17 and background, n = 23. 

Copollutant (correlation): 

PM2.5 absorbance r = 0.49 

NO2 r = 0.45 

PM Increment: 1.04 μg/m3

Odds Ratio [Lower CI, Upper CI] 

Adjusted OR for PM2.5 and: sneezing, runny/stuffed nose 

during the first yr of life was 1.16 [1.01, 1.34] 

At age 1 yr 

For wheezing 1.01 [0.87, 1.18] 

For cough without infection 1.05 [0.88, 1.25] 

For dry cough at night1.08 [0.86, 1.27] 

For asthmatic, spastic, or obstructive bronchitis 

1.04 [0.90, 1.29] 

For respiratory infection1.05 [0.88, 1.22] 

For sneezing, runny or stuffed nose 1.16 [1.01, 1.34] 

At age 2 yr 

For wheezing 1.10 [0.96, 1.25] 

For cough without infection NA, insufficient sample 

For dry cough at night 1.03 [0.86, 1.19] 

For asthmatic, spastic, or obstructive bronchitis 

1.05 [0.92, 1.20] 

For respiratory infection 1.09 [0.94, 1.07] 

For sneezing, runny or stuffed nose 1.19 [1.04, 1.36] 

December 2009 E-427 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Morgenstern 

et al. (2007, 090747) 

Period of Study: May 

1999-Jul 2000 

Location: Munich, 

Germany 

Outcome: Asthma, wheezing, 

spastic/obstructive bronchitis. Dry 

cough at night, respiratory 

infections, sneezing, runny/stuffed 

nose without a cold. 

Age Groups: at 1 yr & at 2 yr 

Study Design: Cohort

N: 3577 children for the prediction 

models. Respiratory data were 

available for 3129 children at 1 yr. 

Statistical Analyses: Pearson’s 

correlation coefficient, prediction 

error expressed as root mean 

squared error (RMSE), multiple 

logistic regression with confounding 

factors, odds ratios 

Covariates: Sex, Parental atopy 

(genetic predisposition to allergies), 

environmental tobacco smoke at 

home, maternal education >or <12 

yr, sibling, gas stove, home 

dampness, indoor mold, pets. Since 

it was not feasible to measure 

personal exposure to NO2, PM2.5, 

and PM2.5 absorbance, exposure 

modeling was used. 

Statistical Package: SAS V.8.02 

Pollutant: PM2.5 Absorbance (PM2.5

ab) 

Averaging Time: Annual 

Mean (SD): 1.7 10 -5 m -1, 

Percentiles: 25th: 1.6 10 -5 m -1 

50th(Median): 1.7 10 -5 m -1 

75th: 1.8 10 -5 m -1 

Range (Min, Max): 

1.3, 3.2 10 -5 m -1 

Unit (i.e. μg/m3): 10 -5 m -1 

Monitoring Stations: 40: traffic, 

n = 17 and background, n = 23. 

PM Increment: 0.22 x 10 -5 

Odds Ratio [Lower CI, Upper CI] 

no lag 

At age 1 yr 

For wheezing 0.97 [0.77, 1.23] 

For cough without infection 1.16 [0.87, 1.54] 

For dry cough at night1.09 [0.78, 1.51] 

For asthmatic, spastic, or obstructive bronchitis 

1.14 [0.88, 1.48] 

For respiratory infections1.03 [0.86, 1.24] 

For sneezing, runny or stuffed nose 1.30 [1.03, 1.65] 

At age 2 yr 

For wheezing 1.09 [0.90, 1.33] 

For cough without infection NR insufficient data 

For dry cough at night1.18 [0.93, 1.50] 

For asthmatic, spastic, or obstructive bronchitis 

0.85 [0.30, 2.34] 

For respiratory infections1.05 [0.79, 1.39] 

For sneezing, runny or stuffed nose 

1.27 [1.04, 1.56] 

Reference: Oftedal et al. 

(2008, 093202) 

Period of Study: 

2001-2002 

Location: Oslo, Norway 

Outcome: Lung function (PEF, 

FEF25%, FEF50%, FEV1, FVC) 

Age Groups: 9-10 yr 

Study Design: Cross-sectional 

N: 1847 children 

Statistical Analyses: Linear 

regression 

Covariates: Height, age, BMI, birth 

weight, temperature, maternal 

smoking, se 

Dose-response Investigated? Yes

Statistical Package: SPSS, 

STATA, S-Plus 

Lags Considered: 1-3 

Pollutant: PM2.5

IQR: 

PM2.5 in 1st yr of life: 6.2 

PM2.5 lifetime: 3.6 

PM Increment: Per IQR 

β (Lower CI, Upper CI) 

PM2.5 in 1st yr of life 

PEF -76.1 (-122.2 to -30.0) 

FEF25% -75.6 (-127.4 to -23.8) 

FEF 50% -62.4 (-107.4 to -17.4) 

FEV1 -12.7 (-28.8, 3.4) 

FVC -2.9 (-20.5, 14.7) 

PM2.5 lifetime exposure 

PEF -57.7 (-94.4 to -21.1) 

FEF25% -51.8 (-93.1 to -10.6) 

FEF 50% -48.4 (-84.2 to -12.6) 

FEV1 -10.4 (-23.2, 2.4) 

FVC -3.9 (-17.9, 10.1) 

Reference: (Parker et 

al., 2009, 192359)

Period of Study: 1999-

2005 

Location: U.S. 

Outcome: Respiratory 

allergy/hayfever 

Study Design: Cohort 

Covariates: Survey yr, age, family 

structure, usual source of care, 

health insurance, family income 

relative to federal poverty level, 

race/ethnicity 

Statistical Analysis: Logistic 

regression 

Statistical Package: SUDAAN 

Age Groups: 73,198 children aged 

3-17 yr 

Pollutant: PM2.5

Averaging Time: NR 

Median: 13.1 

IQR: 10.9-15.2 

Copollutant (correlation): 

Summer O3: 0.10 

SO2: 0.21 

NO2: 0.53 

PM10-2.5: 0.02 

PM10: 0.51 

Increment: 10 μg/m3

Odds Ratio (95% CI) 

Single Pollutant Model, variable N 

Adjusted: 1.16 (1.04-1.30) 

Single Pollutant Model, constant N 

Adjusted: 1.23 (1.04-1.46) 

Multi-pollutant Model: 1.29 (1.07-1.56)

December 2009 E-428 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sekine et al. 

(2004, 090762) 

Period of Study: 

1987-1994 

Location: Nine districts 

in the Tokyo, Japan 

metropolitan area: Chuo 

ward, Ohta ward, 

Shibuya ward, Itabashi 

ward, Hachioji City, 

Tachikawa City, Ome 

City, Machida City, 

Tanashi City 

Outcome: Pulmonary function tests

Age Groups: 30-59 yr 

Study Design: Cross-sectional and 

longitudinal

N: 500 females 

Statistical Analyses: Multiple 

logistic regression analysis 

Covariates: Group (classification 

by air pollution level), pulmonary 

function at initial test, age and 

height at the time of the initial test, 

number of yr investigated, yr of 

residence in the area, type of 

heater, housing structure, and job 

status. 

Dose-response Investigated? No 

Statistical Package: SAS 

Pollutant: Suspended PM (SPM) 

Averaging Time: Measured each 

month for three consecutive days 

(72 h) 

Mean (SD): 28.1-63.3 

Range (Min, Max): 3.4-140.6 

Copollutant (correlation): NO2

Results of multiple logistic regression analysis for respiratory 

symptoms 

Persistent cough 

Group 3: OR = 1.00 

Group 2: OR = 1.02 (0.70-1.48) 

Group 1: OR = 1.07 (0.67-1.70) 

Persistent phlegm 

Group 3: OR = 1.00 

Group 2: OR = 1.51 (1.11-2.04) 

Group 1: OR = 1.78 (1.26-2.53) 

Asthma 

Group 3: OR = 1.00 

Group 2: OR = 1.99 (0.82-4.83) 

Group 1: OR = 2.66 (0.98-7.19) 

Wheeze 

Group 3: OR = 1.00 

Group 2: OR = 1.39 (0.95-2.01) 

Group 1: OR = 1.34 (0.85-2.11) 

Breathlessness 

Group 3: OR = 1.00 

Group 2: OR = 0.84 (0.47-1.50) 

Group 1: OR = 2.70 (1.48-4.91) 

Reference: Sharma et 

al. (2004, 156974) 

Period of Study: Nov 

2002-Apr 2003 

Location: 3 sections in 

Kanpur City, India 

1) Indian Institute of 

Technology Kanpur (IITK) 

2) Vikas Nagar (VN) 

3) Juhilal Colony (JC) 

Outcome: Lung function 

Age Groups: 20-55 yr 

Study Design: Cohort

N: 91 people 

Statistical Analyses: Linear 

regression 

Covariates: NR 

Season: Fall, Winter, spring 

Dose-response Investigated? No 

Statistical Package: 

Microsoft Excel 

Lags Considered: 1 day lag & 

5-day ma 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD): IITK 158 (22) 

VN 85 (30) 

JC 59 (9) 

PM Component: Lead, Nickel, Cadmium, Chromium, Iron, Zinc

Benzene soluble fraction (includes 

polycyclic aromatic hydrocarbons 

[PAHs]) 

Copollutant (correlation): 

ΔPEF = mean daily deviations in 

PEF 

PM2.5-ΔPEF: -0.30 

PM2.5-PM10: 0.67 

PM2.5-PM10 (1-day lag): 0.49 

PM2.5-PM2.5 (1-day lag): 0.88 

PM Increment: 1 μg/m3

ΔPEF (difference or change in peak expiratory flow) 

-0.0297 L/min 

Reference: (Singh et al., 

2003, 052686) 

Period of Study: NR 

Location: Jaipur, India 

Outcome: Lung function (peak 

expiratory flow variability) 

Age Groups: Medical school-aged 

students 

Study Design: Cross sectional

N: 313 nonsmoker students 

Statistical Analyses: Amplitude % 

mean was used as the measure of 

PEF variability. Mean value of 

amplitude % mean of peak flow 

variability were compared for in the 

two groups by application of 

Student’s t-test. The two groups 

were: living on campus and 

commuters. 

Dose-response Investigated? Yes

Pollutant: Respirable suspended 

PM (RSPM) 

Averaging Time: 8 h 

Mean (SD): Roadside: 1,666 

Campus: 177 

Monitoring Stations: 2 

It appears that no associations between particulates and the 

outcome of interest were calculated and reported in this study 

December 2009 E-429 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Solomon et 

al., 2003, 087441) 

Period of Study: 

1966-1997 

Location: United 

Kingdom: Northern 

England, North-West 

Midlands, and Wales. 

Outcome: Cardio-respiratory 

morbidity 

Age Groups: 45 yr and older 

Study Design: Cross-sectional

N: 1,166 women 

Statistical Analyses: Prevalence 

ratios were reported for ischemic 

heart disease, asthma, productive 

cough, wheeze, and use of an 

inhaler for asthma or other breathing 

problems. 

Covariates: Smoked, passive 

smoking in childhood, tenancy, SES, 

worked in industry with respiratory 

hazards, childhood admission to 

hospital for chest problem, diabetes, 

BMI were all controlled for as 

potential confounders. 

Dose-response Investigated? yes 

Statistical Package: STATA 

Pollutant: Black Smoke 

Averaging Time: Annual 

RR Estimate [Lower CI, Upper CI] 

The findings provide no indication that prolonged residence in 

places that have had relatively high levels of particulate air 

pollution causes an important increase in cardio-respiratory 

morbidity. 

Prevalence ratios are based on high vs. low pollution with low 

as referent. 

Particulate pollution in place of residence: 

Rr = 1.0 (0.7-1.4) for ischemic heart disease; 

Rr = 0.7 (0.5-1.0) for asthma 

Rr = 1.0 (0.7 -1.5) for productive cough 

Reference: Suglia et al. 

(2008, 157027) 

Period of Study: Mar 

1986-Oct 1992 

Location: Boston, MA 

Outcome: Lung function 

Age Groups: 18-42 

Study Design: Prospective cohort

N: 272 women of childbearing age 

Statistical Analyses: Linear 

regression 

Covariates: Height, age, weight, 

race/ethnicity, yr, education 

Dose-response Investigated? 

yes-tertiles of exposure 

Statistical Package: SAS v. 9.0 

Pollutant: Black Carbon (BC) 

Averaging Time: Annual 

Mean (SD): 0.62 (0.15) 

PM Increment: 0.22 μg/m3 (IQR) 

Effect Estimate [Lower CI, Upper CI] 

FEV1: -1.08 (-2.5, 0.3) 

FVC: -0.62 (-1.9, 0.6) 

FEF25-75%: -2.97 (-5.8 to -0.2) 

Current Smokers: 

FEV1: 0.62 (-2.1, 3.4) 

FVC: 0.64 (-2.0, 3.3) 

FEF25-75%: -2.63 (-3.7, 8.9) 

Former Smokers: 

FEV1: -4.40 (-7.8 to -1.0) 

FVC: -3.11 (-6.1 to -0.2) 

FEF25-75%: -8.78 (-14.7 to -2.9) 

Nonsmokers: 

FEV1: -0.98 (-2.9, 0.9) 

FVC: -0.32 (-2.0, 1.4) 

FEF25-75%: -4.39 (-8.1 to -0.6) 

Exposure-response relationship presented graphically in Fig 

1: the highest BC exposure group had decreases in FEV1, 

FVC, and FEF25-75% compared with the lowest tertile group, 

although these differences were not statistically significant. 

Reference: (Sunyer et 

al., 2006, 089771) 

Period of Study: initial 

selection: 1991-1993, 

follow-up Jun 2000-Dec 

2001 

Location: 21 centers in 

10 European countries 

Outcome: Chronic bronchitis 

Age Groups: Mean age (range) 

Males- 42.62 (38.12-45.62) 

Females- 42.57 (39.92-45.69) 

Study Design: Hierarchical models

N: 6924 

Statistical Analyses: General 

additive models (GAM) 

Covariates: Smoking, age at end of 

education, occupational group, 

occupational exposures, respiratory 

infections during childhood, rhinitis, 

asthma, traffic intensity at household 

level. 

Statistical Package: STATA-8 

Pollutant: PM2.5

Averaging Time: 18 mo 

Mean (SD): 3.7-44.9 

Copollutants: NO2, SO2 

PM Increment: NR 

Odds ratio [Lower CI, Upper CI] 

Chronic phlegm prevalence at follow up 

Males: 0.97 [0.70,1.35] 

December 2009 E-430 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Zhang et al. 

(2002, 034814) 

Period of Study: 

1993-1996 

Location: 4 Chinese 

cities (urban and 

suburban location in 

each city): Guangzhou, 

Wuhan, Lanzhou, 

Chongqing 

Outcome: Interview-self reports of 

symptoms: Wheeze (ever wheezy 

when having a cold) 

Asthma (diagnosis by doctor) 

Bronchitis (diagnosis by doctor) 

Hospitalization due to respiratory 

disease (ever) 

Persistent cough (coughed for at 

least 1 month per yr with or apart 

from colds) 

Persistent phlegm (brought up 

phlegm or mucus from the chest for 

at least 1 month per yr with or apart 

from colds). 

Age Groups: Elementary school 

students 

age range: 5.4-16.2 

Study Design: Cross-sectional

N: 7,557 returned questionnaires 

7,392 included in first stage of 

analysis 

Statistical Analyses: 2-stage 

regression approach: 

Calculated odds ratios and 95% CIs 

of respiratory outcomes and covariates Second stage consisted of variance-weighted linear regressions 

that examined associations between 

district-specific adjusted prevalence 

rates and district-specific ambient 

levels of each pollutant. 

Covariates: Age, gender, breast-fed, 

house type, number of rooms, 

sleeping in own or shared room, 

sleeping in own or shared bed, home 

coal use, ventilation device used, 

homes smokiness during cooking, 

eye irritation during cooking, parental 

smoking, mother’s education level, 

mother’s occupation, father’s 

occupation, questionnaire 

respondent, yr of questionnaire 

administration, season of questionnaire administration, parental asthma 

prevalence. 

Pollutant: PM2.5

Averaging Time: 2 yr 

Mean (SD): 92 (31) 

Percentiles: 

25th: NR 

50th(Median): NR 

75th: NR 

IQR: 39 

Range (Min, Max): 

Gives range (max.-min.): 

PM2.5-98 

Monitoring Stations: 2 types: 

municipal monitoring stations over 

a period of 4 yr (1993-1996) 

schoolyards of participating 

children over a period of 2 yr 

(1995-1996) 

PM Increment: Interquartile range corresponded to 1 unit of 

change. 

RR Estimate [Lower CI, Upper CI] 

lag: 

No association between PM2.5 and any type of respiratory 

morbidity. 

No between or within city association between PM2.5 and any 

type of respiratory morbidity. 

When scaled to an increment of 50 μg/m3

 increase in PM2.5, 

association (ORs) between respiratory outcome and PM2.5

was: 

Wheeze: 1.06 

Asthma: 1.29 

Bronchitis: 1.68 

Hospitalization: 1.08 

Persistent cough: 1.24 

Persistent phlegm: 3.09 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-431 
Table E-25. Long-term exposure - respiratory morbidity outcomes - other PM size fractions. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: El-Zein et al. (2007, 

093043) 

Period of Study: 2000-2004 

Location: Beirut, Lebanon

ED Admissions 

Outcome: Acute respiratory symptoms: 

asthma, URTI, pneumonia, bronchitis 

Age Groups: <17 

Study Design: Ecological (natural 

experiment comparing admissions 

before and after ban on diesel fuel)

N: 5 hospitals, 7573 admissions OctFeb, 4303 admissions Oct-Dec 

Statistical Analyses: T-test, Poisson 

regression 

Covariates: Month of Year, 

temperature, humidity, orthogonalized 

rainfall 

Season: Oct-Dec (excluding flu 

season) and Oct-Feb 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: 1-2 yr before the 

ban compared to 1-2 yr after the ban 

Pollutant: PM from diesel 

Range (Min, Max): NR 

PM Component: NR 

Monitoring Stations: 1 

Notes: Did not look at specific 

exposure data 

looked at outcome with respect to a 

timeline that plotted admissions before 

and after a ban on diesel fuel. 

Copollutant: NR 

PM Increment: NA 

β (p-value): 

2-yr pre-ban vs. 2-yr post-ban 

Oct to Feb 

All Resp: 0.128 (0.32) 

Asthma: -0.176 (0.16) 

Bronchitis: 0.505 (0.02) 

Pneumonia: 0.287 (0.17) 

URTI: -0.265 (0.41) 

Oct to Dec 

All Resp: -0.022 (0.87) 

Asthma: -0.21 (0.07) 

Bronchitis: 0.2 (0.35) 

Pneumonia: -0.065 (0.78) 

URTI: -0.628 (0.05) 

2-yr pre-ban vs. 1-yr post-ban 

Oct-Feb 

All Resp: -0.093 (0.45) 

Asthma: -0.208 (0.05) 

Bronchitis: 0.286 (0.32) 

Pneumonia: -0.07 (0.76) 

URTI: -0.715 (0.11) 

Oct to Dec 

All Resp: -0.147 (0.02) 

Asthma: -0.147 (0.00) 

Bronchitis: -0.011 (0.96) 

Pneumonia: -0.214 (0.15) 

URTI: -0.885 (0.06) 

1-yr pre-ban vs. 1-yr post-ban 

Oct-Feb 

All Resp: -0.165 (0.04) 

Asthma: -0.212 (0.09) 

Bronchitis: 0.059 (0.85) 

Pneumonia: -0.034 (0.84) 

URTI: -1.023 (0.00) 

Oct to Dec 

All Resp: -0.17 (0.00) 

Asthma: -0.131 (0.00) 

Bronchitis: -0.145 (0.001) 

Pneumonia: -0.168 (0.12) 

URTI: -1.036 (0.00) 

Reference: Kasamatsu et al. (2006, 

156627) 

Period of Study: 2001-2002 

Location: Shenyang, China 

Outcome: FVC, FEV1, PEF, FEF75 

Age Groups: School Children aged 8-

10 

Study Design: Children in three 

schools in three types of areas 

(commercial city area, residential city 

area, residential suburban area) invited 

to participate

N: 322 children participated, 244 have 

complete data. 

Statistical Analyses: Genralized 

estimating equations 

Covariates: Age, height, 

Dose-response Investigated? No 

Statistical Package: SAS 

Lags: Considered: previous quarter. 

Pollutant: PM7 

Averaging Time: Avg of 4 separate 2-7 

consecutive day measurements within 

each designated measurement month 

of the quarter 

Mean (SD): 

School A 

7/2001 86.4(14.2) 

10/2001 114.1(35.1) 

1/2002 118.2(28.2) 

4/2002 182.7(102.1) 

School B 

7/2001 90.1(8.3) 

10/2001 161.5(45.7) 

1/2002 118.8(28.2) 

4/2002 152.0(31.3) 

School C 

7/2001 78.1(16.9) 

10/2001 131.2(29.6) 

1/2002 142.2(37.6) 

4/2002 173.6(121.5) 

PM Component: mainly pollutants 

associated with coal heating 

Monitoring Stations: 1 at each location

PM Increment: 63.0 μg/m3

Mean change of pulmonary function 

value [Lower CI, Upper CI] at lag 0 

Boys 

FVC -0.095(-0.170,-0.019) 

FEV1 -0.088(-0.158,-0.019) 

PEF -0.170(-0.365,0.032) 

FEF75 -0.063(-0.183,0.050) 

Girls 

FVC -0.082(-0.145,-0.019) 

FEV1 -0.069(-0.126,-0.006) 

PEF 0.095(-0.095,0.290) 

FEF75 -0.032(-0.151,0.082) 

Mean change of pulmonary function 

value [Lower CI, Upper CI] at lag 

1(previous quarter) 

Boys 

FVC -0.145(-0.189,-0.095) 

FEV1 -0.095(-0.139,-0.057) 

PEF -0.082(-0.208,0.050) 

FEF75 0.013(-0.063,0.088) 

Girls 

FVC -0.126(-0.170,-0.088) 

FEV1 -0.101(-0.139,-0.063) 

PEF -0.101(-0.227,0.025) 

FEF75 -0.057(-0.132,0.019) 

December 2009 E-432 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Kasamatsu et al.(2006, 

156627) 

Period of Study: 2001-2002 

Location: Shenyang, China 

Outcome: FVC, FEV1, PEF, FEF75 

Age Groups: School Children aged 8-

10 

Study Design: Children in three 

schools in three types of areas 

(commercial city area, residential city 

area, residential suburban area) invited 

to participate

N: 322 children participated, 244 have 

complete data. 

Statistical Analyses: Genralized 

estimating equations 

Covariates: Age, height, 

Dose-response Investigated? no 

Statistical Package: SAS 

Lags: Considered: previous quarter. 

Pollutant: PM2.1

Averaging Time: Avg of 4 separate 2-7 

consecutive day measurements within 

each designated measurement month 

of the quarter 

Mean (SD): 

School A 

7/2001 47.6(6.4) 

10/2001 54.2(20.5) 

1/2002 68.9(15.8) 

4/2002 115.8(76.7) 

School B 

7/2001 45.6(6.5) 

10/2001 74.4(27.1) 

1/2002 63.3(17.9) 

4/2002 96.3(27.6) 

School C 

7/2001 42.5(9.5) 

10/2001 59.7(13.1) 

1/2002 76.4(22.1) 

4/2002 123.0(100.9) 

PM Component: mainly pollutants 

associated with coal heating 

Monitoring Stations: 1 at each location

PM Increment: 42.1 μg/m3

Mean change of pulmonary function 

value [Lower CI, Upper CI] at lag 0 

Boys 

FVC -0.126(-0.181,-0.076) 

FEV1 -0.122(-0.173,-0.076) 

PEF -0.164(-0.303,-0.025) 

FEF75 -0.046(-0.131,0.038) 

Girls 

FVC -0.110(-0.156,-0.067) 

FEV1 -0.101(-0147,-0.059) 

PEF 0.008(-0.131,0.147) 

FEF75 -0.055(-0.139,0.030) 

Mean change of pulmonary function 

value [Lower CI, Upper CI] at lag 

1(previous quarter) 

Boys 

FVC -0.099(-0.145,-0.053) 

FEV1 -0.059(-0.106,-0.020) 

PEF -0.040(-0.158,0.086) 

FEF75 0.026(-0.046,0.092) 

Girls 

FVC -0.086(-0.125,-0.046) 

FEV1 -0.066(-0.106,-0.026) 

PEF -0.079(-0.198,0.040) 

FEF75 -0.033(-0.106,0.040) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-433 
E.6.Long-Term Exposure and Cancer 

Table E-26. Long-term exposure - cancer outcomes - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Abbey et al., 1999, 

047559) 

Period of Study: 1977-1992 

Location: California 

Outcome (ICD9): Lung Cancer 

Mortality (162) 

Age Groups: 27-95 at baseline 

Study Design: Cohort (AHSMOG)

N: 6,338 nonsmoking CA Seventh-Day 

Adventists 

Statistical Analyses: Time-dependent, 

gender-specific, Cox proportional 

hazards regression models 

Covariates: Age, smoking, education, 

occupation, BMI 

Pollutant: PM10

Averaging Time: Monthly estimates 

from 1966-1992 

Mean (SD): 51.24 (16.63) 

Percentiles: IQR: 24.08 

Range (Min, Max): 0, 83.9 

Correlations: 

SO4: r = 0.68) 

SO2: r = 0.31 

O3: r = 0.77 

NO2: r = 0.56 

Lag: 3 yr 

PM Increment: 24.08 (IQR) 

RR, males: 3.36 [1.57, 7.19] 

RR, females: 1.33 [0.60, 2.96] 

PM10 above 100μg/m3

 (days per yr)

IQR: 43 days/yr 

Males: 2.38 (1.42, 3.97) 

Females: 1.08 (0.55, 2.13) 

Reference: Beeson et al. (1998, 

048890) 

Period of Study: 1977-1992 

Location: California 

Outcome (ICD9: Lung Cancer Mortality 

(ICDO-1: 162, ICDO-2: C34.0-C34.9) 

Age Groups: 27-95 at baseline 

Study Design: Cohort (AHSMOG)

N: 6,338 nonsmoking CA Seventh-Day 

Adventists (non-Hispanic white) 

Statistical Analyses: Time-dependent, 

gender-specific, Cox proportional 

hazards regression models 

Covariates: Smoking, Education, Age, 

Alcohol 

Statistical Package: SAS 

Lags Considered: 3 yr 

Pollutant: PM10

Averaging Time: Averaged monthly 

estimates from 1966-1992 

Mean (SD): 51 (16.52) 

Percentiles: IQR: 24 

Range (Min, Max): 0, 84 

PM Increment: 24 (IQR) 

RR, males: 5.21 [1.94, 13.99] 

RR, females: Positive, but not 

statistically significant 

Reference: Binkova et al. (2007, 

156273) 

Period of Study: Feb 2001 

Location: Prague, Czech Republic 

Outcome: Total DNA adducts (bulky 

aromatic PAH-DNA adducts and ... 

Age Groups: 22-50 yr 

Study Design: Case Control

N: 53 occupationally exposed 

policemen and 52 control policemen 

Statistical Analyses: Multivariate 

logistic regression, Mann-Whitney u-test

Covariates: Smoking. Vitamin C, 

polymorphisms of XPD repair gene in 

exon 23 and 6 and GSTM 1 and 

XRCC1 genes 

Season: Winter 

Pollutant: PM10

Range (Min, Max): 32-55 

Monitoring Stations: 2 (and personal 

monitors) 

No relationship between short term 

exposure to C-PAHs evaluated by 

personal monitors and DNA adduct 

level. Genetic damage was observed in 

city policemen working in winter 

outdoors in the Prague downtown area 

they had slightly elevated aromatic DNA 

adduct levels, which was statistically 

significant for a distinct DNA adduct 

spot that could originate from ambient 

exposure to B[α]P. 

Total PAH-DNA adducts: p = 0.065 

Exposed: 0.92 ± 0.28 adducts/108 

nucleotids 

Control: 0.82 ± 0.23 adducts/108 

nucleotids 

B[α]P-like adducts: 

Exposed: 0.122 ± 0.36 adducts/108 

nucleotids 

Control: 0.099 ± 0.035 adducts/108 

nucleotids 

Multiple regression “like” B[α]P-DNA 

adduct for air pollution exposure group: 

B = 0.016, p = 0.01 

December 2009 E-434 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Liu et al., 2009, 190292) 

Period of Study: 1995-2005 

Location: Taiwan 

Outcome: Bladder Cancer Mortality 

(ICD-9 188) 

Age Groups: 50-69 

Study Design: Case-crossover 

Statistical Analysis: Multiple Logistic 

Regression 

Statistical Package: NR 

Covariates: none 

Dose-response Investigated? No 

Pollutant: PM10

Averaging Time: Annual mean of 24-h 

avg 

Tertiles (median): 

T1: ≤52.80 

T2: 53.04-71.72 

T3: 72.24-90.29 

Copollutant: O3, CO, NO2, SO2

Copollutant (correlation): NR 

Monitoring Sattions: 64 

Increment: 

Odds Ratio (Min CI, Max CI) 

Lag 

T1 vs. T1: 1.00 (ref) 

T2 vs. T1: 1.08 (0.83-1.41) 

T3 vs. T1: 1.39 (1.06-1.83) 

P for trend = .020 

Reference: (Pope et al., 2002, 024689) 

Period of Study: 1982-1998 

Location: 50 U.S. states, District of 

Columbia, and Puerto Rico 

Outcome (ICD9): Lung cancer mortality 

(162)

Age Groups: Ages >30 yr Study 

Design: Longitudinal cohort (Cancer 

Prevention Study II)

N: 1.2 million people 

Statistical Analyses: Cox proportional 

hazard, generalized additive 

Covariates: Age, sex, race, education, 

smoking status, marital status, 

occupational exposure, diet, body-mass 

index, alcohol consumption 

Pollutant: PM10 

Mean (SD): 1982-1998: 28.8(5.9) 

Effect estimates: Effect estimates were 

recorded in Fig 5 and not presented 

quantitatively anywhere else 

Reference: Sram et al, (2007, 188457) 

Period of Study: Jan and Mar of 2004 

Location: Prague, Czech Republic 

Outcome: Chromosomal aberrations 

Study Design: Panel 

Covariates: Urinary cotinine, plasma 

levels of vitamins A, E and C, folate, 

total cholesterol, HDL and LDL 

cholesterols, and triglycerides 

Statistical Analysis: Bivariate 

correlations, ANOVA, Mann-Whitney, 

Kruskal-Wallis and Spearman rank 

correlation 

Statistical Package: STATISTICA 

Age Groups: 61 city policemen, aged 

34 ± 8 yr, spending 8+ h outdoors 

Pollutant: PM10

Averaging Time: NR 

Mean (SD) Unit: 

Jan: 55.6 μg/m3

Mar: 36.4 μg/m3

Copollutant: PM2.5

Results not given by PM increment. 

Reference: Sram et al, (2007, 188457) 

Period of Study: Jan and Mar of 2004 

Location: Prague, Czech Republic 

Outcome: Chromosomal aberrations 

Study Design: Panel 

Covariates: Urinary cotinine, plasma 

levels of vitamins A, E and C, folate, 

total cholesterol, HDL and LDL 

cholesterols, and triglycerides 

Statistical Analysis: Bivariate 

correlations, ANOVA, Mann-Whitney, 

Kruskal-Wallis and Spearman rank 

correlation 

Statistical Package: STATISTICA 

Age Groups: 61 city policemen, aged 

34 ± 8 yr, spending 8+ h outdoors 

Pollutant: PM2.5

Averaging Time: NR 

Mean (SD) Unit: 

Jan: 44.4 μg/m3

Mar: 24.8 μg/m3

Copollutant: PM10

Results not given by PM increment. 

December 2009 E-435 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Tarantini et al., 2009, 

192010)Period of Study: NR 

Location: Brescia, Italy 

Outcome: DNA methylation content 

estimated by Alu, LINE-1 and iNOS 

analysis 

Study Design: Panel 

Covariates: age, BMI, smoking, 

number of cigarettes/day 

Statistical Analysis: Mixed effects 

models 

Statistical Package: NR 

Age Groups: 63 male workers between 

27 and 55 yr, mean age 44. 

Pollutant: PM10

Averaging Time: NR 

Mean (SD) Unit: NR 

Individual Exposure Range: 73.4-

1220 μg/m3

Copollutant (correlation): NR 

Difference in DNA Methylation before 

and after work exposure, mean (SE) 

Alu (%5mC): 0.00 (0.08), p = 0.99 

LINE-1 (%5mC): 0.02 (0.11), p = 0.89 

iNOS (%5mC): -0.61 (0.26), p = 0.02 

Reference: (Vineis et al., 2006, 

192089) 

Period of Study: 1990-1999 

Location: 10 European countries 

Outcome: Lung cancer 

Study Design: Nested case-control 

Covariates: Age, sex, country, smoking 

status, time since recruitment, 

education, BMI, physical activity, intake 

of fruit, vegetables, meat, alcohol and 

energy 

Statistical Analysis: Conditional 

logistic regression models 

Statistical Package: NR 

Age Groups: 35-74 at recruitment 

Pollutant: PM10

Averaging Time: NR 

Mean by Country (μg/m3): 

France 

Ile-de-France 

1990-1994: 22.3 

1995-1999: 19.9 

Northeast France 

1990-1994: 30.2 

1995-1999: 29.5 

Italy 

Turin 

1990-1994: 73.4 

1995-1999: 61.1 

Florence 

1990-1994: 40.4 

1995-1999: 33.3 

United Kingdom 

Oxford 

1990-1994: 29.0 

1995-1999: 25.5 

Cambridge 

1990-1994: NR 

1995-1999: 25.4 

The Netherlands 

Utrecht 

1990-1994: 42.8 

1995-1999: 40.0 

Bilthoven 

1990-1994: 39.0 

1995-1999: 37.2 

Germany 

Heidelberg 

1990-1994: NR 

1995-1999: 27.0 

Potsdam 

1990-1994: 32.0 

1995-1999: 28.9 

Range (Min, Max): NR 

Copollutant: NO2, O3, SO2

Increment: 10 μg/m3

Odds Ratios (Min CI, Max CI) for 

increase in lung cancer per 

increment increase in PM10

0.91 (0.70-1.18) 

Reference: (Wei et al., 2009, 192361)

Period of Study: Nov 2006-Jan 2007 

Location: Peking, China 

Outcome: Urinary 8-OHdG increase 

Study Design: Panel 

Covariates: NR 

Statistical Analysis: Analysis of 

variance model with autoregressive 

terms 

Statistical Package: SAS 

Age Groups: Two nonsmoking security 

guards, ages 18 and 20 

Pollutant: PM2.5

Averaging Time: 24 h 

Median: 154.87 μg/m3

IQR: 166.29 

Copollutant (correlation): NA 

Increment: 166.29 μg/m3

8-OHdG Concentrations, pre and 

post-work shift, subjects avgd

Pre-work: 1.83 

Post-work: 6.92 

Concentration Changes (95%CI) of 8-

OHdG per IQR Increase

Pre-work: 0.256 (0.040, 0.472), p = 

0.021 

Post-work: 2.370 (0.907, 3.833), p = 

0.002 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-436 
Table E-27. Long-term exposure - cancer outcomes - PM2.5 (including PM components/sources). 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Baccarelli et al, (2009, 

188183) 

Period of Study: Jan 1999-Jun 2007 

Location: Boston, Massachusetts 

Outcome: DNA methylation of LINE-1 

and Alu 

Study Design: Panel 

Covariates: age, BMI, smoking status, 

pack-yr, statin use, fasting blood 

glucose, diabetes mellitus, percent 

lymphocytes and neutrophils in 

differential blood count, day of the 

week, season, temperature 

Statistical Analysis: Mixed effects 

models 

Statistical Package: SAS 

Age Groups: 719 elderly individuals, 

mean age 73.3, range 55-100 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean (SD) Unit: 

4h: 12.2 (7.7) μg/m3

1 day: 10.9 (6.3) μg/m3

2 day: 10.6 (5.2) μg/m3

3 day: 10.4 (4.8) μg/m3

4 day: 10.3 (4.3) μg/m3

5d: 10.2 (3.9) μg/m3

6d: 10.3 (3.5) μg/m3

7d: 10.3 (3.3) μg/m3

Copollutants: Black carbon, Sulfate 

Increment: SD for each lag 

Correlation Coefficient (95% CI) 

Lag for LINE-1 Methylation 

4h: -0.07 (-0.13, -0.01), p = 0.03 

1 day: -0.09 (-0.16, -0.02), p = 0.008 

2 day: -0.10 (-0.17, -0.03), p = 0.003 

3 day: -0.10 (-0.17, --0.04), p = 0.003 

4 day: -0.10 (-0.16, -0.03), p = 0.004 

5d: -0.10 (-0.16, -0.03), p = 0.004 

6d: -0.11 (-0.17, -0.04), p = 0.001 

7d: -0.13 (-0.19, -0.06), p < 0.001 

Correlation Coefficient (95% CI) 

Lag for Alu Methylation 

4h: 0.03 (-0.03, 0.09), p = 0.28 

1 day: -0.01 (-0.07, 0.05), p = 0.74 

2 day: -0.01 (-0.07, 0.05), p = 0.82 

3 day: -0.01 (-0.07, 0.05), p = 0.78 

4 day: -0.01 (-0.07, 0.05), p = 0.75 

5d: -0.01 (-0.07, 0.05), p = 0.84 

6d: -0.01 (-0.07, 0.05), p = 0.74 

7d: -0.01 (-0.07, 0.05), p = 0.71 

Correlation Coefficient (95% CI) 

LINE-1 Methylation and ma of 

pollutant levels 

4h: -0.04 (-0.11, 0.03), p = 0.24 

7d: -0.11 (-0.18, -0.05), p = 0.001 

Reference: Binkova et al. (2007, 

156273) 

Period of Study: Feb 2001 

Location: Prague, Czech Republic 

Outcome: Bulky aromatic PAH-DNA 

adducts 

Age Groups: 22-50 yr 

Study Design: Case Control

N: 53 exposed policemen and 52 

control policemen 

Statistical Analyses: Multivariate 

logistic regression, Mann-Whitney, 

Rank-Sum U-test 

Covariates: Smoking. Vitamin C, 

polymorphisms of XPD repair gene in 

exon 23 and 6 and GSTM 1 gene 

Season: Winter 

Pollutant: PM2.5 

Range (Min, Max): 27-38 

c-PAHs: range = 18-22 ng/m3

B[a]P: range = 2.5-3.1 ng/m3

Monitoring Stations: 2 

Genetic damage was observed in city 

policemen working in winter outdoors in 

the Prague downtown area 

They had slightly elevated aromatic 

DNA adduct levels, which was more 

pronounced for a distinct DNA adduct 

spot that could originate from ambient 

exposure to B[α]P. 

Total DNA-adduct level

Exposed: 0.92±0.28 adducts/108 

nucleotides 

Control: 0.82±0.23 adducts/108 

nucleotides 

p = 0.065 

“Like” B[α]P-derived DNA adducts

Exposed: 0.122±0.036 

Control: 0.101±0.035 

p < 0.01 

Multiple Regression (exposed vs. 

control) 

B = 0.016, p = 0.011 

December 2009 E-437 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Brunekreef et al, (2009, 

191947) 

Period of Study: 1987-1996 

Location: The Netherlands 

Outcome: Air pollution related lung 

cancer deaths (ICD-9 162) 

Study Design: Case-cohort 

Covariates 

Individual: Sex, age, Quetelet index, 

smoking status, passive smoking 

status, educational level, occupation, 

occupational exposure, marital status, 

alcohol use, intake of vegetables, fruits, 

energy, saturatured and 

monounsaturated fatty acids, trans fatty 

acids, total fiver, folic acid and fish 

Area-level: Percent of population with 

income below the 40th percentile and 

above the 80th percentile 

Statistical Analysis: Cox proportional 

hazards 

Statistical Package: Stata, SPSS, R 

Age Groups: 120,000 adults aged 55-

69 yr at enrollment 

Pollutant: PM2.5, estimated from PM10

levelsf 

Averaging Time: 24 h 

50th Percentile: 28 μg/m3 

Range (Min, Max): 23-37 

Copollutant (correlation): 

NO2: 0.75 

Black Smoke: 0.84 

NO: 0.69 

SO2: 0.43 

Increment: 10 μg/m3

Relative Risk (95% CI) for 

associations between PM2.5 and lung 

cancer incidence 

Case Cohort 

Unadjusted: 0.93 (0.71-1.22) 

Adjusted: 0.67 (0.41-1.10) 

Unadjusted Complete: 0.87 (0.60-1.25) 

Full Cohort 

Unadjusted: 0.96 (0.79-1.18) 

Adjusted: 0.81 (0.63-1.04) 

Unadjusted Complete: 0.92 (0.74-1.15) 

Reference: Liu et al. (2008, 156708) 

Period of Study: 1995-2005 

Location: Taiwan 

Outcome: Brain cancer deaths 

ICD9: 191 

Age Groups: 29 yr of age or younger 

Study Design: Matched case-control 

by sex, yr of birth and death

N: 340 matched pairs 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Age, gender, urbanization 

level of residence, nonpetrochemical air 

pollution exposure level 

No direct measures of pollutants 

used an index to assign petrochemical 

air pollution exposure (each municipality 

was assigned an exposure by dividing 

the number of workers per municipality 

employed in the petrochemical industry 

by the municipalities total population). 

Study participants divided into tertiles 

based on this index. 

People who lived in the group of 

municipalities with the highest levels of 

air pollutants arising from petrochemical 

sources were at a statistically significant 

increased risk for brain cancer 

development compared to the group 

living in municipalities with the lowest 

petrochemical air pollution exposure 

index. 

Effect Measure: OR (95%CI) 

Tertile 1: 1. ?0 

Tertile 2: 1.54 (0.98-2.42) 

Tertile 3: 1.65 (1.00-2.73) 

P for trend <0.01 

Reference: Nafstad et al. (2004, 

087949) 

Period of Study: 1972-1998 

Location: Oslo, Norway 

Outcome: Lung cancer 

ICD7 162.1-162.9 

Age Groups: 40-49 yr old men

Study Design: Cohort

N: 16,209 males 

Statistical Analyses: Cox regression 

models (proportional hazards) 

Covariates: Age at inclusion, smoking 

habits, education 

Season: all yr 

PM values had small variations in 

exposure level, and strong correlations 

with another pollutant of interest (SO2) 

and were not considered in analyses. 

Copollutants: 

SO2

NOX

No effect estimates for PM 

Reference: (Pope and Burnett, 2007, 

090928) 

Period of Study: 1982-1998 

Location: 50 U.S. states, District of 

Columbia, and Puerto Rico 

Outcome: Lung cancer mortality (162)

Age Groups: >30 yr 

Study Design: Longitudinal cohort 

(Cancer Prevention II Study)

N: 415,000 CPS II patients with 

information involving PM10

Statistical Analyses: Cox proportional 

hazard, incorporating a spatial randomeffects component 

Covariates: Age, sex, race, education, 

ETS, smoking status, marital status, 

occupational exposure, diet, body-mass 

index, alcohol consumption 

Pollutant: PM2.5

Mean (SD): 1979-1983: 21.1(4.6) 

1999-2000: 14.0(3.0) 

Avg: 17.7(3.7) 

Averaging time: 1982-1998 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] 

lag: 

Lung Cancer: 1979-1983: 1.08[1.01, 

1.16] 

1999-2000: 1.13[1.04, 1.22] 

Avg: 1.14[1.04, 1.23] 

RR results were also presented in Fig 

2-5. Authors found that PM2.5 had the 

strongest association with increased 

risk of all-cause, cardiopulmonary, and 

lung cancer mortality. 

December 2009 E-438 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Sram et al, (2007, 188457) 

Period of Study: Feb 2001 

Location: Prague, Czech Republic 

Outcome: Chromosomal aberrations 

Study Design: Panel 

Covariates: Urinary cotinine, plasma 

levels of vitamins A, E and C 

Statistical Analysis: Bivariate 

correlations, ANOVA, Mann-Whitney, 

Kruskal-Wallis and Spearman rank 

correlation 

Statistical Package: STATISTICA, 

SAS 

Age Groups: 53 city policemen, aged 

22-50 yr, spending 8+ h outdoors 

Pollutant: PM10

Averaging Time: NR 

Range: 32-55μg/m3 

Copollutant: PM2.5

Results not given by PM increment. 

Reference: Sram et al, (2007, 188457) 

Period of Study: Feb 2001 

Location: Prague, Czech Republic 

Outcome: Chromosomal aberrations 

Study Design: Panel 

Covariates: Urinary cotinine, plasma 

levels of vitamins A, E and C 

Statistical Analysis: Bivariate 

correlations, ANOVA, Mann-Whitney, 

Kruskal-Wallis and Spearman rank 

correlation 

Statistical Package: STATISTICA, 

SAS 

Age Groups: 53 city policemen, aged 

22-50 yr, spending 8+ h outdoors 

Pollutant: PM2.5

Averaging Time: NR 

Range: 27-38μg/m3 

Copollutant: PM10

Results not given by PM increment. 

Reference: Tovalin et al. (Tovalin et al., 

2006, 091322) 

Period of Study: Apr-May 2002

Location: Mexico City and Puebla 

Outcome: DNA damage (comet tail 

length) 

Age Groups: 18-60

Study Design: Panel Study

N: 55 male workers 

Statistical Analyses: Mann-Whitney 

test, Chi-square, Spearman’s 

correlation, logistic regression

Statistical Package: SPSS and STATA 

Pollutant: PM2.5

Personal monitoring values observed in 

this study reported in Tovalin et al. 2003

Median Personal Exposure to PM2.5: 

Mexico City 

Outdoor Worker: 133 μg/m3

Indoor Worker: 86.6 μg/m3

Puebla 

Outdoor Worker: 122 μg/m3

Indoor Worker: 78.3 μg/m3

OR for being a highly damaged worker: 

1.02 (1.01-1.04), p = 0.03 

Correlation between comet tail length 

and PM 2.5: 0.57, p = 0.000 

OR for being a highly damaged worker: 

1.03, p ≤ 0.07 

Comet Tail Length 

Outdoor Worker: 46.80 μm 

Indoor Worker: 30.11 μm 

p < 0.01 

Percent Highly DNA Damaged Cells 

Outdoor Worker: 68% 

Indoor Worker: 20% 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-439 
Table E-28. Long-term exposure - cancer outcomes - other PM size fractions. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Pope et al., 2002, 024689) 

Period of Study: 1982-1998 

Location: 50 U.S. states, District of 

Columbia, and Puerto Rico 

Outcome: Lung cancer mortality (162)

Age Groups: Ages >30 yr who were 

members of a household with at least 1 

individual ≥45yrs. 

Study Design: Longitudinal cohort 

(Cancer Prevention Study II)

N: 359,000 CPS II participants with 

information regarding PM15 and 

PM15-PM2.5

Statistical Analyses: Cox proportional 

hazard, incorporating a spatial randomeffects component 

Covariates: Age, sex, race, education, 

ETS, smoking status, marital status, 

occupational exposure, diet, body-mass 

index, alcohol consumption 

Smoking covariates adjusted for: 

Indicator: current smoker, former 

smoker, pipe or cigar smoker, started 

smoking before or after age 18 

Continuous, current and former 

smokers: yr smoked, yr smoked 

squared, cigarettes per day, cigarettes 

per day squared, number of h per day 

exposed to passive cigarette smoke. 

Pollutant: PM15 

Mean (SD): 1979-1983: 40.3(7.7) 

Pollutant: PM15-2.5 

Mean (SD): 1979-1983: 19.2(6.1) 

Averaging Time: 1979-1983 

Relative risks effect estimates were 

recorded in Fig 5 and not presented 

quantitatively anywhere else. 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-440 
E.7. Long-Term Exposure and Reproductive Effects 

Table E-29. Long-term exposure - reproductive outcomes - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Bell at al. (2007, 091059)

Period of Study: 1999-2002 

Location: Connecticut-Fairfield, 

Hartford, New Haven, New London, 

Windham, Massachusetts-Barnstable, 

Berkshire, Bristol, Essex, Hampden, 

Middlesex, Norfolk, Plymouth, Suffolk, 

Worcester 

Outcome: Low birth weight 

Age Groups: Neonates 

Study Design: Cross-sectional

N: 358,504 births 

Statistical Analyses: Multiple logistic 

and linear regressions

Covariates: Child’s sex, mother’s 

education, tobacco use, mother’s 

marital status, mother’s race, time 

prenatal care began, mother’s age, birth 

order, gestation length 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 22.3 (5.3) 

Monitoring Stations: NR 

Copollutant: NO2, CO, SO2

Gestation exposure correlation: 

PM2.5: r = 0.77 

NO2: r = 0.55 

PM Increment: 7.4 μg/m3 (IQR) 

Difference in birth weight [Lower CI, 

Upper CI] 

per IQR for the gestational period: -8.2 

[-11.1 to -5.3]

Difference in birth weight by race of 

mother [Lower CI, Upper CI]: 

Black: -7.9 [-16.0, 0.2] 

White: -9.0 [-12.2 to -5.9] 

Range among trimester models for 

change in birth weight per IQR 

increase (min, max) 

trimester: -6.6 to -4.7 

3rd 

OR Estimate for birth weight <2500 g 

[Lower CI, Upper CI] 

per IQR for the gestational period: 

1.027 [0.991, 1.064] 

Notes: Analyses using first births alone 

yielded similar results. Two pollutant 

models for uncorrelated pollutants were 

analyzed but not presented quantitatively. 

Reference: Brauer et al. (2008, 

156292) 

Period of Study: 1999-2002 

Location: Vancouver, BC 

Outcome: Preterm birth, SGA, LBW

Age Groups: Study Design: Crosssectional

N: 70,249 births 

Statistical Analyses: Logistic 

regression 

Covariates: Sex, parity, month and yr 

of birth, maternal age and smoking, 

neighborhood level income and 

education

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24-h 

Mean (SD): 12.7 

Range (Min, Max): 5.6, 35.4 

Monitoring Stations: 19 

Copollutant: 

NO 

NO2

CO 

SO2

O3

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI] 

pollutant assessed for entire 

pregnancy period: 

SGA: 1.02 (0.99, 1.05) 

LBW: 1.01 (0.95, 1.08) 

Preterm (<30 wk): 1.13 (0.95, 1.35) 

December 2009 E-441 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Chen et al. (2002, 024945)

Period of Study: 1991-1999

Location: Washoe County, Nevada 

Outcome: Birth weight

Age Groups: Sngle births with 

gestational age between 37-44 wk and 

maternal all ages

Study Design: Cross-sectional

N: 33,859 single births

Statistical Analyses: multiple linear 

and logistic regression

Covariates: infant sex, maternal 

residential city, education, medical risk 

factors, active tobacco use, drug use, 

alcohol use, prenatal care, mother’s 

age, race and ethnicity of mothers and 

weight gain of mothers 

Dose-response Investigated? No 

Statistical Package: SPSS 10.0 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 31.53 (22.32) 

Percentiles: 25th: 16.80

50th(Median): 26.30

75th: 39.35 

Range (Min, Max): (0.97-157.32)

Monitoring Stations: 4

Copollutant: CO 

O3

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Using continuous pollutant variables 

Model 1-PM10

1 trimester 

Crude model: ß = -0.186 (0.225) 

Adjusted model: ß = -0.082 (0.221) 

2 trimester 

Crude model: ß = 0.045 (0.223) 

Adjusted model: ß = -0.020 (0.221) 

3 trimester 

Crude model: ß = -0.509 (0.231) 

Adjusted model: ß = -0.395 (0.227) 

Whole 

Crude model: ß = -0.823 (0.459) 

Adjusted model: ß = -0.726 (0.483) 

Model 2 

CO and PM10

3 trimester 

Crude model: ß = -1.044 (0.457) 

Adjusted model: ß = -1.078 (0.445) 

O3 and PM10

3 trimester 

Crude model: ß = -1.035 (0.385) 

Adjusted model: ß = -0.966 (0.378) 

Model 3 

PM10, O3, and CO 

3 trimester 

Crude model: ß = -1.070 (0.458) 

Adjusted model: ß = -1.102 (0.446) 

Whole 

Crude model: ß = -1.413 (0.733) 

Adjusted model: ß = -1.332 (0.738) 

Using categorical pollutant variables-3 

trimester 

Model 1-PM10

Adjusted model: ß = -10.243 (5.235) 

Model 2 

PM10 and CO 

Adjusted model: ß = -11.883 (6.108) 

PM10 and O3 Adjusted model: 

ß = -9.144 (5.860) 

Model 3 

PM10, CO, and O3 Adjusted model: 

ß = -10.937 (6.222) 

Using logistic regression 

(ref value = <19.72 μg/m3

Exposure to PM10 at 3 trimester at 

>44.74 μg/m3

: OR = 

1.105 (0.714-1.709) 

Between 19.72-44.74 μg/m3

: 

OR = 1.050 (0.811-1.360) 

Notes: Crude model: model with airpollutant variables controlled with 

gestational age only. Adjusted model: 

model with air-pollutant variables 

controlled with confounding variables 

including gestational age, infant sex, 

maternal residential city, education, 

medical risk factors, active tobacco use, 

drug use, alcohol use, the trimester begins 

prenatal visits, total prenatal visits, 

mother’s age, race and ethnicity of mother, 

and weight gain of mother. 

December 2009 E-442 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dales et al. (2004, 087342) 

Period of Study: Jan 1984-Dec 1999 

Location: Canada (12 cities) 

Outcome: SIDS (a sudden, 

unexplained death of a child <1 yr of 

age for which a clinical investigation 

and autopsy fail to reveal a cause of 

death) 

Age Groups: Infants <1 yr 

Study Design: Time-series

N: Total population of 12 cities: 

10,310,309 

1556 cases of SIDS over study period 

Statistical Analyses: Random-effects 

regression model for count data (a 

linear association between air pollution 

and the incidence of SIDS was 

assumed on the logarithmic scale) 

Covariates: Weather factors (daily 

mean temp, daily mean relative 

humidity, maximum change in 

barometric pressure, all measured on 

the day of death), length of time-period 

adjustment, seasonal indicator 

variables, and size-fractionated PM 

Season: Used piece-wise constant 

functions in time that varied by 3, 6, or 

12 mo 

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM10 

Averaging Time: 24-hs (PM measures 

every 6 days 

gaseous pollutants every day) 

Mean (IQR): PM10: 23.43 (15.56) 

Range (Min, Max): IQR presented 

above 

Monitoring Stations: When data were 

available from more than 1 monitoring 

site, they were avgd 

Copollutant: 

PM2.5

PM10

CO 

NO2

O3

SO2

Notes: The abstract reports no 

association between increased daily rates 

of SIDS and fine particles measured every 

sixth day. However, no effect estimates 

presented for PM (only gaseous pollutants 

adjusted for PM). 

December 2009 E-443 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Dugandzic et al. (2006, 

088681) 

Period of Study: Jan 1988-Dec 2000 

Location: Nova Scotia, Canada 

Outcome: Low birth weight (LBW) 

(<2500 grams) 

Age Groups: Babies born ≥ 37 wk (full 

term) 

Study Design: Cross-sectional

N: 74,284 births 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, parity, prior 

fetal death, prior neonatal death, prior 

low birth weight infant, smoking during 

pregnancy, neighborhood family 

income, infant gender, gestational age, 

weight change, yr of birth 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24-h 

Mean (SD): 

Percentiles: 25th: 14

50th(Median): 16

75th: 19 

Range (Min, Max): Max: 53 

Monitoring Stations: 18 

Copollutant: SO2, O3

Notes: Only 3 stations monitored more 

than 1 pollutant. Daily data were 

available for gaseous pollutants while 

particulate levels were measured every 

sixth day. 

PM Increment: 

1) IQR (5 μg/m3) 

2) Quartiles (first quartile is the reference) 

Exposure period: first trimester 

Unadjusted model 

2nd quartile: 1.24 (0.95, 1.62) 

3rd quartile: 1.25 (0.96, 1.62) 

4th quartile: 1.28 (1.00, 1.65) 

Per IQR: 1.09 (1.00, 1.18) 

Adjusted model 

2nd quartile: 1.24 (0.94, 1.64) 

3rd quartile: 1.24 (0.95, 1.64) 

4th quartile: 1.33 (1.02, 1.74) 

Per IQR: 1.09 (1.00, 1.19) 

Adjusted for Birth Year model 

2nd quartile: 1.14 (0.86, 1.52) 

3rd quartile: 1.08 (0.82, 1.44) 

4th quartile: 1.11 (0.84, 1.48) 

Per IQR: 1.03 (0.94, 1.14) 

Exposure period: second trimester 

Unadjusted model 

2nd quartile: 0.98 (0.76, 1.28) 

3rd quartile: 1.09 (0.84, 1.40) 

4th quartile: 1.00 (0.77, 1.28) 

Per IQR: 1.00 (0.91, 1.09) 

Adjusted model 

2nd quartile: 1.02 (0.77, 1.34) 

3rd quartile: 1.16 (0.89, 1.51) 

4th quartile: 1.09 (0.83, 1.42) 

Per IQR: 1.02 (0.93, 1.12) 

Adjusted for Birth Year model 

2nd quartile: 0.99 (0.75, 1.31) 

3rd quartile: 1.10 (0.84, 1.45) 

4th quartile: 1.01 (0.76, 1.34) 

Per IQR: 1.00 (0.90, 1.10) 

Exposure period: third trimester 

Unadjusted model 

2nd quartile: 0.93 (0.72, 1.20) 

3rd quartile: 1.07 (0.83, 1.37) 

4th quartile: 0.92 (0.71, 1.18) 

Per IQR: 0.95 (0.87, 1.05) 

Adjusted model 

2nd quartile: 0.96 (0.73, 1.26) 

3rd quartile: 1.14 (0.88, 1.48) 

4th quartile: 1.03 (0.79, 1.35) 

Per IQR: 0.99 (0.89, 1.09) 

Adjusted for Birth Year model 

2nd quartile: 0.92 (0.70, 1.21) 

3rd quartile: 1.04 (0.80, 1.36) 

4th quartile: 0.92 (0.69, 1.22) 

Per IQR: 0.94 (0.85, 1.05) 

Reference: Gilboa, et al. (2005, 

087892)

Period of Study: Jan 1996-Dec 2000 

Location: Seven Counties in Texas, 

USA: (Bexar, Dallas, El Paso, Harris, 

Hidalgo, Tarrant, Travis) 

Outcome: Birth defects 

Age Groups: Newborn babies

Study Design: Case-control

N: 5,338 newborn babies 

4574 controls 

Statistical Analyses: Logistic 

regression 

Covariates: Alcohol consumption 

during pregnancy, attendant of delivery 

(i.e., the person who delivered the baby 

(physician/nursemaid-wife vs. other)), 

gravidity, marital status, maternal age, 

maternal education, maternal illness, 

maternal race/ethnicity, parity, place of 

delivery, plurality, prenatal care, season 

of conception, and tobacco use during 

pregnancy 

Control frequency matched to cases by 

vital status, yr and maternal county of 

residence 

Pollutant: PM10

Averaging Time: NR 

Percentiles: 25th: <19.5

50th(Median): 19.5-<23.8

75th: 23.8-<29.0 

100th: ≥ 29.0

Monitoring Stations: The 

Environmental Protection Agency 

provided raw data or hourly (for gases) 

or daily (for PM) air pollution 

concentrations for the seven study 

counties 

Copollutant: CO, NO2, O3, SO2

PM Increment: calculated as quartiles of 

avg concentration during wk 3-8 of 

pregnancy 

Isolated Cardiac Defects 

Aortic artery and valve defects: 

25th: 0.40 (0.15, 1.03) 

50th: 0.45 (0.18, 1.13) 

75th: 0.68 (0.28, 1.65) 

Atrial Sepal defects: 

25th: 1.41 (0.86, 2.31) 

50th: 2.13 (1.34, 3.37) 

75th: 2.27 (1.43, 3.60) 

Pulmonary artery and valve defects: 

25th: 1.14 (0.62, 2.10) 

50th: 0.79 (0.41, 1.55) 

75th: 0.68 (0.33, 1.40) 

Ventricular Sepal defects: 

25th: 0.83 (0.61, 1.11) 

50th: 1.12 (0.85, 1.48) 

75th: 0.98 (0.73, 1.32) 

Multiple Cardiac Defects 

Conotruncal defects: 

25th: 1.13 (0.79, 1.62) 

50th: 1.20 (0.84, 1.72) 

75th: 1.26 (0.86, 1.84) 

December 2009 E-444 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Season: Covariate in model

Dose-response Investigated? Yes 

Statistical Package: SAS v 8.2 

Endocardial cushion and mitral valve 

defects: 

25th: 0.82 (0.54, 1.25) 

50th: 0.66 (0.42, 1.05) 

75th: 0.63 (0.38, 1.03) 

Isolated Oral Clefts 

Cleft lip with or without palate: 

25th: 1.29 (0.90, 1.85) 

50th: 1.45 (1.01, 2.07) 

75th: 1.37 (0.94,2.00) 

Cleft palate: 

25th: 0.99 (0.55, 1.78) 

50th: 1.14 (0.64, 2.03) 

75th: 1.11 (0.60, 2.06) 

Individual Birth Defects 

Aortic valve stenosis: 

25th: 0.91 (0.53, 1.57) 

50th: 0.86 (0.50, 1.50) 

75th: 1.12 (0.63, 1.99) 

Atrial Sepal defects: 

25th: 1.10 (0.89, 1.35) 

50th: 1.28 (1.04, 1.57) 

75th: 1.26 (1.03, 1.55) 

Coarctation of the aorta: 

25th: 0.78 (0.53, 1.15) 

50th: 0.68 (0.45, 1.02) 

75th: 0.75 (0.48, 1.15) 

Endocardial cushion defects: 

25th: 0.87 (0.49, 1.55) 

50th: 1.12 (0.64, 1.96) 

75th: 0.89 (0.47, 1.65) 

Ostium secundum: 

25th: 1.15 (0.85, 1.55) 

50th: 1.13 (0.83, 1.53) 

75th: 1.06 (0.77, 1.48) 

Pulmonary artery atresia without 

ventricular Sepal defects: 

25th: 1.93 (1.08, 3.45) 

50th: 2.01 (1.11, 3.64) 

75th: 0.86 (0.41, 1.83) 

Pulmonary valve stenosis: 

25th: 1.16 (0.88, 1.55) 

50th: 1.25 (0.94, 1.66) 

75th: 1.27 (0.94, 1.71) 

Tetralogy of Fallot: 

25th: 1.21 (0.72, 2.01) 

50th: 1.40 (0.84, 2.33) 

75th: 1.45 0.85, 2.48) 

Ventricular Sepal defects: 

25th: 1.06 (0.90, 1.24) 

50th: 1.10 (0.94, 1.29) 

75th: 1.08 (0.92, 1.27) 

December 2009 E-445 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Gouveia et al. (2004, 

055613)

Period of Study: 1997

Location: São Paulo, Brazil 

Outcome: Birth weight

Age Groups: Singleton full term live 

births within 1000 g to 5500 g

Study Design: Cross sectional study

N: 179,460 live births

Statistical Analyses: GAM and 

Logistic regression models 

Covariates: Maternal age, length of 

gestation, season, infant gender, 

maternal education, number of 

antenatal care visits, parity, and the 

type of delivery

Season: All seasons

Dose-response Investigated? Yes 

Statistical Package: S-Plus 2000 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 60.3 (25.2) 

Range (Min, Max): (25.5-153.0)

Monitoring Stations: maximum of 12 

sites

Copollutant (correlation): 

CO: r = 0.9 

SO2

NO2

O3

PM Increment: 10 μg/m3

Mean [Lower CI, Upper CI]: 

Changes in birth weight (in g) 

First trimester = -13.7 (-27.0, -0.4) 

Second trimester = -4.4 (-18.9, 10.1) 

Third trimester = 14.6 (0.0, 29.2) 

RR Estimate [Lower CI, Upper CI]: 

(RR estimates are adjusted odds ratios for 

low birth weight according to quartiles of 

air pollution in each trimester of 

pregnancy.) 

1st quartile 

First trimester = 1 (REF) 

Second trimester = 1 (REF) 

Third trimester = 1 (REF) 

2nd quartile 

First trimester = 1.105 (0.994, 1.229) 

Second trimester = 1.003 (0.904, 1.113) 

Third trimester = 1.004 (0.914, 1.104) 

3rd quartile 

First trimester = 1.049 (0.903, 1.219) 

Second trimester = 1.074 (0.920, 1.254) 

Third trimester = 1.003 (0.861, 1.169) 

4th quartile 

First trimester = 1.144 (0.878, 1.491) 

Second trimester = 1.252 (1.028, 1.525) 

Third trimester = 0.970 (0.780, 1.205) 

Multiple linear regression coefficients (SE) 

obtained from single, dual, and three 

pollutant models 

Single pollutant model = -1.37 (0.68) 

Two pollutant (PM10 and CO) = -0.51 

(0.87) 

Two pollutant (PM10 and SO2) = -0.94 

(0.75) 

Three pollutant = -0.47 (0.88) 

Reference: Ha et al. (2003, 042552) 

Period of Study: Jan 1995-Dec 1999 

Location: Seoul, South Korea 

Outcome: Post-neonate total and 

respiratory mortality 

Age Groups: 1 month-1 yr 

2 yr-65 yr, >65 yr 

Study Design: Time-series

N: 1045 post-neonate deaths, 67,597 2-

65 yr old deaths, 100,316 >65 yr old 

deaths 

Statistical Analyses: Generalized 

additive model 

Covariates: Seasonality, temperature, 

relative humidity, day of the week 

Dose-response Investigated? No

Statistical Package: S Plus 

Lags Considered: 0, 1, 2, 3, 4, 5, 6, 7, 

ma from 1-5 days 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 69.2 (31.6) 

Percentiles: 25th: 44.8 

50th(Median): 64.2 

75th: 87.7 

Range (Min, Max): 10.5 μg/m3, 

245.4 μg/m3

Monitoring Stations: 27

Copollutant (correlation): 

NO2: r = 0.73 

SO2: r = 0.62 

O3: r = -0.02 

CO: r = 0.63 

PM Increment: 42.9 μg/m3 

RR Estimate [Lower CI, Upper CI] lag: 

Total Mortality: 

1 month-1 yr (post-neonates): 

1.142 [1.096, 1.190] lag 0 

2 yr-65 yr: 

1.008 [1.006, 1.010] lag 0 

>65 yr (elderly): 

1.023 [1.023, 1.024] lag 0 

Respiratory Mortality: 

1 month-1 yr (post-neonates): 

2.018 [1.784, 2.283] lag 0 

2 yr-65 yr: 

1.066 [1.044, 1.090] lag 0 

>65 yr (elderly): 

1.063 [1.055, 1.072] lag 0 

December 2009 E-446 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Hansen, et al. (2006, 

089818)

Period of Study: Jul 2000-Jun 2003

Location: Brisbane, Australia 

Outcome: Pre-term birth (<37 wk) 

Age Groups: Newborn babies

Study Design: Cross-sectional

N: 1583 live pre-terms births 

28,200 singleton live births 

Statistical Analyses: Multiple logistic 

regression models 

Covariates: Neonate gender, mother’s 

age, parity, indigenous status, number 

of antenatal visits, marital status, 

number of previous 

abortions/miscarriages, type of delivery, 

and index of SES 

Season: all

Dose-response Investigated? Yes 

Statistical Package: SAS version 8.2 

Pollutant: PM10

Averaging Time: recorded hourly, avgd 

daily

Mean (SD): 19.6 (9.4) 

Range (Min, Max): 4.9, 171.7 

Monitoring Stations: 5

Copollutant (correlation): 

Fine PM or bsp, 0.1 to <2.5 μg in 

diameter (0.58 to 0.76) 

O3 (0.54 to 0.83) 

NO2 (0.54 to 0.75) 

PM10 (0.80 to 0.93) 

Note: Correlations presented are for 

the individual pollutant across 

monitoring stations (not correlations 

between PM10 and the pollutant.) 

PM Increment: Trimester One 

4.5 μg/m3

Last 90 days prior to birth 

5.7 μg/m3

Odds Ratio [Lower CI, Upper CI]: 

Trimester 1 

1.15 [1.06, 1.25]

Last 90 days prior to birth 

1.04 [0.92, 1.16] 

Reference: Hansen et al. (2007, 

090703) 

Period of Study: Jul 2000-Jun 2003 

Location: Brisbane, Australia 

Outcome: Birth weight and Small for 

Gestational Age (SGA 

<10th percentile for age and gender) 

Head circumference (HC) and crownheel length (CHL) among subsample 

Study Design: Cross-sectional

N: 26,617 births (birth weight analysis) 

and 21,432 (HC and CHL analyses) 

Statistical Analyses: Logistic (SGA) 

and linear (birth weight, HC, CHL) 

regressions 

Covariates: Gender, gestational age 

(with a quadratic term), maternal age, 

parity, number of previous 

abortions/miscarriages, marital status, 

indigenous status, number of antenatal 

visits, type of delivery, an index of SES, 

and season of birth 

Season: Assessed as a covariate 

Dose-response Investigated? Yes, 

assessed exposures as quartiles 

Statistical Package: SAS v8.2 

Pollutant: PM10

Averaging Time: Trimester and 

monthly avg were used in analyses 

(calculated as the mean of daily values 

Hourly data was use to calculate daily 

means 

City-wide avg used) 

Mean (SD): 19.6 (9.4) 

Percentiles: 

25th: 14.6 

50th: 18.1 

75th: 22.7 

Range (Min, Max): (4.9, 171.7) 

Monitoring Stations: 5 

Copollutant (correlation): 

By trimesters: 

PM10 T1: 

PM10 T2: r = 0.12 

PM10 T3: r = -0.55 

O3 T1: r = 0.77 

O3 T2: r = 0.28 

O3 T3: r = -0.61 

NO2 T1: r = 0.32 

NO2 T2: r = -0.65 

NO2 T3: r = -0.17 

visibility reducing particles (bsp) 

T1: r = 0.82 

visibility reducing particles (bsp) 

T2: r = -.15 

visibility reducing particles (bsp) 

T3: r = -0.50 

PM10 T1: r = 0.12 

PM10 T2: 

PM10 T3: r = 0.04 

O3 T1: r = -0.11 

O3 T2: r = 0.80 

O3 T3: r = 0.18 

NO2 T1: r = 0.77 

NO2 T2: r = 0.25 

NO2 T3: r = -0.72 

visibility reducing particles (bsp) 

T1: r = 0.23 

visibility reducing particles (bsp) 

T2: r = 0.80 

visibility reducing particles (bsp) 

T3: r = -0.24 

PM10 T1: r = -0.55 

PM10 T2: r = 0.04 

PM10 T3: 

PM Increment: IQR (8.1 μg/m3)

Effect Estimate [Lower CI, Upper CI]: 

Change (β) in mean birth weight (g) 

associated with trimester-specific 

exposures 

Trimester 1: 

Continuous exposure: -3.2 (-11.9, 5.5) 

Quartiles of exposure: 

1: Ref 

2: -4.7 (-19.7, 10.2) 

3: 4.2 (-12.9, 21.3) 

4: -0.2 (-19.2, 18.8) 

p-trend: 0.864 

Trimester 2: 

Continuous exposure: 0.4 (-9.4, 10.2) 

Quartiles of exposure: 

1: Ref 

2: 12.7 (-2.3, 27.6) 

3: 7.6 (-10.6, 25.7) 

4: 1.0 (-18.7, 20.7) 

p-trend: 0.922 

Trimester 3: 

Continuous exposure: 3.6 (-6.9, 14.0) 

Quartiles of exposure: 

1: Ref 

2: 2.9 (-12.8, 18.7) 

3: 18.5 (0.0, 36.9) 

4: 4.3 (-15.8, 24.4) 

p-trend: 0.524 

ORs for SGA associated with trimesterspecific exposures 

Trimester 1: 

Continuous exposure: 1.04 (0.96, 1.12) 

Quartiles of exposure: 

1: Ref 

2: 1.23 (1.07, 1.42) 

3: 1.12 (0.95, 1.31) 

4: 1.12 (0.94, 1.34) 

p-trend: 0.361 

Trimester 2: 

Continuous exposure: 0.95 (0.88, 1.04) 

Quartiles of exposure: 

1: Ref 

2: 0.96 (0.83, 1.11) 

3: 1.06 (0.89, 1.25) 

4: 0.98 (0.81, 1.18) 

p-trend: 0.962 

3: -0.02 (-0.08, 0.04) 

4: -0.02 (-0.08, 0.05) 

p-trend: 0.605 

Trimester 2: 

Continuous exposure: -0.01 (-0.04, 0.02) 

December 2009 E-447 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

O3 T1: r = -0.56 

O3 T2: r = -0.18 

O3 T3: r = 0.81 

NO2 T1: r = -0.20 

NO2 T2: r = 0.75 

NO2 T3: r = 0.22 

visibility reducing particles (bsp) 

T1: r = -0.62 

visibility reducing particles (bsp) 

T2: r = 0.19 

visibility reducing particles (bsp) 

T3: r = 0.79 

Quartiles of exposure: 

1: Ref 

Trimester 3: 

Continuous exposure: 0.93 (0.85, 1.03) 

Quartiles of exposure: 

1: Ref 

2: 0.90 (0.78, 1.04) 

3: 0.81 (0.68, 0.96) 

4: 0.86 (0.71, 1.04) 

p-trend: 0.098 

Change (β) in mean head 

circumference (HC 

cm) associated with trimester-specific 

exposures 

Trimester 1: 

Continuous exposure: -0.01 (-0.04, 0.02) 

Quartiles of exposure: 

1: Ref 

2: -0.02 (-0.07, 0.04) 

2: 0.03 (-0.02, 0.08) 

3: 0.00 (-0.06, 0.06) 

4: -0.01 (-0.08, 0.05) 

p-trend: 0.538 

Trimester 3: 

Continuous exposure: 0.02 (-0.02, 0.05) 

Quartiles of exposure: 

1: Ref 

2: 0.02 (-0.04, 0.07) 

3: 0.07 (0.01, 0.13) 

4: 0.04 (-0.03, 0.11) 

p-trend: 0.171 

Change (β) in mean crown-heel length 

(CHL 

cm) associated with trimester-specific 

exposures 

Trimester 1: 

Continuous exposure: 0.00 (-0.05, 0.05) 

Quartiles of exposure: 

1: Ref 

2: 0.02 (-0.07, 0.11) 

3: 0.01 (-0.10, 0.11) 

4: 0.04 (-0.07, 0.16) 

p-trend: 0.511 

Trimester 2: 

Continuous exposure: 0.07 (0.01, 0.13) 

Quartiles of exposure: 

1: Ref 

2: 0.10 (0.01, 0.18) 

3: 0.11 (0.00, 0.21) 

4: 0.13 (0.01, 0.24) 

p-trend: 0.049 

Trimester 3: 

Continuous exposure: -0.01 (-0.07, 0.05) 

Quartiles of exposure: 

1: Ref 

2: -0.02 (-0.11, 0.07) 

3: 0.10 (-0.01, 0.21) 

4: -0.01 (-0.13, 0.10) 

p-trend: 0.883 

December 2009 E-448 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Hansen et al., 2009, 

192362)

Period of Study: Jan 1997-Dec 2004 

Location: Brisbane, Australia 

Outcome: Birth defects- artery and 

valve, atrial and ventricular Sepal, 

conotruncal, endocardial cushion and 

mitral valve, cleft lip and palate 

Study Design: Case-control 

Covariates: Mother’s age, marital 

status, indigenous status, previous 

pregnancies, last menstrual period, 

area-level socioeconomic status, 

distance to a pollution monitor 

Statistical Analysis: Conditional 

logistic regression 

Statistical Package: R 

Age Groups: Neonates 

Pollutant: PM10

Averaging Time: daily 

Mean (SD) Unit: 18.0 μg/m3

Range (Min, Max): (4.4, 151.7) 

Copollutant (correlation): NR 

Increment: 4μg/m3

Odds Ratios (95% CI) for risk of defect 

Aortic Artery and Valve Defects 

All Births, Matched: 1.10 (0.76-1.56) 

Births ≤ 12km to Monitor: 

1.83 (1.16-2.98)

Births ≤ 6km to Monitor: 

1.43 (0.73-2.90) 

All Births, Unmatched: 1.09 (0.84-1.39) 

Atrial Sepal Defects 

All Births, Matched: 1.06 (0.86-1.30) 

Births ≤ 12km to Monitor: 

1.07 (0.84-1.37) 

Births ≤ 6km to Monitor: 

0.88 (0.60-1.27) 

All Births, Unmatched: 1.14 (0.98-1.33) 

Pulmonary Artery and Valve Defects 

All Births, Matched: 0.90 (0.61-1.29) 

Births ≤ 12km to Monitor: 0.69 

(0.43-1.08) 

Births ≤ 6km to Monitor: 

1.46 (0.76-2.73) 

All Births, Unmatched: 0.99 

(0.78-1.24) 

Ventricular Sepal Defects 

All Births, Matched: 0.87 (0.73-1.04) 

Births ≤ 12km to Monitor: 

0.85 (0.69-1.03) 

Births ≤ 6km to Monitor: 

0.90 (0.68-1.18) 

All Births, Unmatched: 1.15 (1.02-1.30) 

Conotruncal Defects 

All Births, Matched: 0.80 (0.54-1.19) 

Births ≤ 12km to Monitor: 0.94 (0.55-1.49) 

Births ≤ 6km to Monitor: 0.66 (0.27-1.45) 

All Births, Unmatched: 0.97 (0.74-1.24) 

Endocardial Cushion and Mitral Valve 

Defects 

All Births, Matched: 1.29 (0.82-2.04) 

Births ≤ 12km to Monitor: 

1.28 (0.75-2.19) 

Births ≤ 6km to Monitor: 

0.90 (0.44-1.86) 

All Births, Unmatched: 0.94 (0.68-1.26) 

Cleft Lip 

All Births, Matched: 1.05 (0.72-1.51) 

Births ≤ 12km to Monitor: 

1.16 (0.72-1.82) 

Births ≤ 6km to Monitor: 

1.03 (0.56-1.82) 

All Births, Unmatched: 1.01 (0.79-1.27) 

Cleft Palate 

All Births, Matched: 0.69 (0.50-0.93) 

Births ≤ 12km to Monitor: 

0.53 (0.29-0.87) 

Births ≤ 6km to Monitor: 

0.71 (0.49-1.00) 

All Births, Unmatched: 0.89 (0.72-1.10) 

Cleft Lip with or without Cleft Palate 

All Births, Matched: 1.05 (0.84-1.30) 

Births ≤ 12km to Monitor: 

1.03 (0.79-1.34) 

Births ≤ 6km to Monitor: 

0.83 (0.58-1.19) 

All Births, Unmatched: 1.04 (0.89-1.21)\ 

December 2009 E-449 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Jalaludin et al. (2007, 

156601) 

Period of Study: 1998-2000 

Location: Sydney, Australia 

Outcome: Gestational age 

(categorized: preterm birth: <37 wk 

term birth: ≥ 37 wk but <42 wk) 

Age Groups: Infants 

Study Design: Cross-sectional

N: 123,840 singleton births of >20 wk 

gestation 

Statistical Analyses: Logistic 

regression 

Covariates: Sex of child, maternal age, 

maternal smoking during pregnancy, 

gestational age at first antenatal visit, 

whether mother identifies as being 

Aboriginal or Torres Strait Islander, 

whether first pregnancy, season of 

conception, SES, (temperature and 

relative humidity were not significant in 

single variable models and therefore, 

were not included) 

Season: Examined as covariate and 

effect modifier 

Dose-response Investigated? No 

Statistical Package: SAS v8 

Pollutant: PM10

Averaging Time: 24 h avg used to 

calculate the mean concentration over 

the first trimester, the 3 mo preceding 

birth, the first month after the estimated 

date of conception, and the month prior 

to delivery 

Mean (SD): (24 h avg) 

All yr: 16.3 (6.38) 

Summer: 18.2 (7.20) 

Fall: 17.0 (6.23) 

Winter: 14.5 (5.57) 

Spring: 15.7 (5.82) 

Monitoring Stations: 14 stations within 

the Sydney metropolitan area (levels 

avgd to provide 1 estimate for the entire 

study area) 

Copollutant (correlation): 

PM10

PM2.5 (r = 0.83) 

CO (r = 0.28) 

NO2 (r = 0.48) 

O3 (r = 0.50) 

SO2 (r = 0.42) 

Notes: Correlations between 

monitoring stations measuring PM10

ranged from 0.67 to 0.91 

PM Increment: 1 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

ORs (air pollutant concentration during the 

1st trimester and preterm birth by season) 

Fall: 1.462 (1.267, 1.688) 

Winter: 1.343 (1.190, 1.516) 

Spring: 1.119 (0.973, 1.288) 

Summer: 0.913 (0.889, 0.937) 

ORs (air pollutant concentrations during 

different exposure periods and preterm 

birth 

for all of Sydney and among only those 

residing within 5 km of a monitoring 

station) 

1 month preceding birth 

Sydney: 0.991 (0.979, 1.003) 

5km: 1.008 (0.993, 1.022) 

3 mo preceding birth 

Sydney: 0.989 (0.975, 1.004) 

5km: 1.012 (0.995, 1.030) 

1st month of gestation 

Sydney: 0.983 (0.973, 0.993) 

5km: 0.957 (0.914, 1.002) 

1st trimester 

Sydney: 0.987 (0.973, 1.001) 

5km: 1.009 (0.978, 1.041) 

Notes: Authors note that effect of PM10 on 

preterm birth for infants conceived during 

the fall did not remain in 2 pollutant 

models (ORs between 0.77 and 1.04) 

Reference: Kaiser et al. (2004, 

076674) 

Period of Study: 1995-1997 

Location: 25 U.S. counties (23 

metropolitan areas): Jackson, AL 

Fresno, CA 

Los Angeles, CA 

Sacramento, CA 

San Diego, CA 

San Francisco, CA 

Denver, CO 

Hartford, CT 

Cook, IL 

Baltimore, MD 

Wayne, MI 

St. Louis, MO 

Bronx, NY 

Kings, NY 

New York, NY 

Philadelphia, PA 

El Paso, TX 

Harris, TX 

Dallas, TX 

Oklahoma, OK 

Tulsa, OK 

Providence, RI 

Salt Lake City, UT 

King, WA 

Milwaukee, WI 

Outcome: Postneonatal death: 

All cause, SIDS (798.0) 

Respiratory disease (460-519) 

Age Groups: Infants between 1-12 mo 

Study Design: Attributable risk 

assessment

N: 700,000 infants (# deaths NR) 

Statistical Analyses: Risk assessment 

methods described in: Kunzli et al. 

Public-health impact of outdoor and 

traffic-related air pollution: a European 

assessment. Lancet 2000, 356: 795-

801. 

Covariates: Maternal education, 

maternal ethnicity, parental marital 

status, maternal smoking during 

pregnancy, infant’s month and yr of 

birth, avg temperature in the first 2 mo 

of life 

Season: All 

adjusted for month/yr of birth 

Dose-response Investigated? NR 

Statistical Package: NR 

Lags Considered: Annual, county-level 

mean 

Pollutant: PM10

Averaging Time: “annual mean levels” 

in each county 

Mean (SD): 28.4 

Range (Min, Max): 

County range: 18.0, 44.8 

Monitoring Stations: NR 

Notes: 14 out of 25 counties had PM10

levels >25 μg/m3

PM Increment: Analysis 1: 

16.4 μg/m3

 (difference between reference 

level of 12 μg/m3

 and observed mean level 

of 28.4 μg/m3) 

Analysis 2: 

13 μg/m3

 (difference between reference 

level of 12 μg/m3 and 25 μg/m3) 

AR Estimate [Lower CI, Upper CI]: 

Analysis 1: 

All cause 6% [3, 11] 

SIDS 16% [9, 23] 

Respiratory 24% [7, 44] 

Attributable # deaths per 100,000 infants: 

All cause 14.7 [7.3, 25.6] 

SIDS 11.7 [6.8, 16.6] 

Respiratory 2.3 [0.7, 4.1] 

Analysis 2: 

All cause 5% [2, 8] 

SIDS 12% [7, 18] 

Respiratory 19% [6, 34] 

Attributable # deaths per 100,000 infants: 

All cause 10.9 [5.5, 19.1] 

SIDS 9.0 [5.3, 12.8] 

Respiratory 1.8 [0.5, 3.2] 

Notes: -Authors did not extrapolate 

attributable cases below 12 μg/m3

 (i.e., 

reference level was set at 12 μg/m3

) 

-Attributable risks are based on the RRs 

reported by Woodruff et al, 1997 for a 

10 μg/m3

 increase: 

 All cause 1.04 [1.02-1.07] 

 SIDS 1.12 [1.07, 1.17] 

 Respiratory 1.20 [1.06, 1.36] 

Reference: (Kim et al., 2007, 156642) 

Period of Study: May 2001-May 2004 

Outcome (ICD9 and ICD10): LBW (low 

birth weight, less than 2500 g at later 

than gestational week 37), premature 

delivery (birth before the completion of 

Pollutant: PM10

Averaging Time: Used hourly 

exposure levels to calculate avg 

PM increment: 10 μg/m3

Preterm: 

1st Trimester Odds Ratios: 

December 2009 E-450 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Location: Seoul, Korea the 37th week), stillbirth (intrauterine 

fetal death), IUGR (birth weight lower 

than the 10th percentile for the given 

gestational age), and congenital 

anomaly (a defect in the infant’s body 

structure) 

Age Groups: Infants 

Study Design: Cross-sectional (women 

visiting the clinic for prenatal care were 

recruited with follow-up until discharge 

after delivery)

N: 1514 observations (births) 

Statistical Analyses: Multiple logistic 

and linear regression (in addition, for 

birth weight, used generalized additive 

model to account for long-term trends 

and nonlinear relationships between the 

response variable and the predictors, 

and to produce smoothed plots of the 

relationship between PM and birth 

weight) 

Covariates: Adjustment 1: infant sex, 

infant order, maternal age and 

education, paternal education, season 

of birth 

Adjustment 2: adjustment 1 factors plus 

alcohol, maternal BMI, maternal weight 

prior to delivery 

(collected information on smoking, ETS, 

parity, past history of illnesses, history 

of illnesses during pregnancy but did 

not use in analyses due to small 

numbers or non-significance) 

Season: Adjusted for season of 

delivery 

Dose-response Investigated? Yes 

Statistical Package: SAS 8.01, S-Plus 

2000 

exposure levels at each trimester, each 

month of pregnancy, and 6 wk before 

delivery from the nearest monitoring 

station (based on home address of 

mother) 

Also created categories within each 

pregnancy period (<25th percentile 

[referent], 25th to 50th percentile, and 

>50th percentile) 

Mean (SD): Range of PM means 

across pregnancy periods: 88.7-89.7 

Monitoring Stations: 27 stations 

Crude: 0.95 (0.90, 1.01) 

Adj 1: 0.93 (0.87, 1.00) 

Adj 2: 0.93 (0.85, 1.01) 

2nd Trimester Odds Ratios: 

Crude: 0.99 (0.94, 1.06) 

Adj 1: 0.98 (0.92, 1.04) 

Adj 2: 1.00 (0.93, 1.07) 

3rd Trimester Odds Ratios: 

Crude: 1.02 (0.98, 1.06) 

Adj 1: 1.05 (1.00, 1.10) 

Adj 2: 1.05 (0.99, 1.11) 

LBW: 

1st Trimester Odds Ratios: 

Crude: 1.02 (0.93, 1.12) 

Adj 1: 1.03 (0.93, 1.14) 

Adj 2: 1.07 (0.96, 1.19) 

2nd Trimester Odds Ratios: 

Crude: 1.03 (0.94, 1.14) 

Adj 1: 1.04 (0.93, 1.17) 

Adj 2: 1.07 (0.94, 1.22) 

3rd Trimester Odds Ratios: 

Crude: 1.04 (0.97, 1.11) 

Adj 1: 1.05 (0.97, 1.14) 

Adj 2: 1.05 (0.96, 1.16) 

IUGR: 

1st Trimester Odds Ratios: 

Crude: 1.07 (0.97, 1.19) 

Adj 1: 1.07 (0.95, 1.21) 

Adj 2: 1.14 (0.99, 1.31) 

2nd Trimester Odds Ratios: 

Crude: 0.97 (0.85, 1.12) 

Adj 1: 0.97 (0.82, 1.13) 

Adj 2: 0.93 (0.77, 1.13) 

3rd Trimester Odds Ratios: 

Crude: 0.82 (0.68, 0.99) 

Adj 1: 0.88 (0.72, 1.08) 

Adj 2: 0.85 (0.67, 1.08) 

Birth defect: 

1st Trimester Odds Ratios: 

Crude: 1.08 (0.98, 1.20) 

Adj 1: 1.12 (1.00, 1.25) 

Adj 2: 1.08 (0.95, 1.22) 

2nd Trimester Odds Ratios: 

Crude: 1.09 (0.99, 1.21) 

Adj 1: 1.11 (0.98, 1.26) 

Adj 2: 1.16 (1.00, 1.34) 

3rd Trimester Odds Ratios: 

Crude: 1.00 (0.90, 1.11) 

Adj 1: 0.97 (0.86, 1.08) 

Adj 2: 0.97 (0.87, 1.10) 

Stillbirth: 

1st Trimester Odds Ratios: 

Crude: 0.83 (0.76, 0.90) 

Adj 1: 0.93 (0.85, 1.02) 

Adj 2: 0.95 (0.85, 1.02) 

2nd Trimester Odds Ratios: 

Crude: 0.99 (0.93, 1.05) 

Adj 1: 1.03 (0.95, 1.11) 

Adj 2: 1.07 (0.98, 1.17) 

3rd Trimester Odds Ratios: 

Crude: 1.14 (1.10, 1.18) 

Adj 1: 1.09 (1.04, 1.15) 

Adj 2: 1.08 (1.02, 1.14) 

LBW (categorical PM exposure): 

1st Trimester ORs: 

<25th: 1.0 

25th-50th: 0.5 (0.1, 3.2) 

>50th: 1.0 (0.3, 3.8) 

3rd Trimester ORs: 

<25th: 1.0 

25th-50th: 1.3 (0.2, 10.4) 

>50th: 3.0 (0.5, 18.5) 

6 wk before birth ORs: 

<25th: 1.0 

25th-50th: 3.2 (0.3, 33.7) 

>50th: 5.2 (0.6, 47.6) 

Changes in Birth Weight (95%CI) per 

10 μg/m3 increase in PM concentration: 

December 2009 E-451 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1st trimester: 7.8 (1.2, 14.5) 

2nd trimester: -0.3 (-7.3, 6.8) 

3rd trimester: -2.1 (-7.5, 3.4) 

1st month: 4.4 (-1.0, 9.8) 

2nd month: 6.4 (0.6, 12.2) 

3rd month: 4.3 (-1.5, 10.2) 

4th month: 3.0 (-3.7, 9.6) 

5th month: -3.9 (-10.5, 2.7) 

6th month: 0.1 

(-5.7, 5.8) 

7th month: 0.1 (-5.1, 5.3) 

8th month: 0.0 (-4.5, 4.5) 

9th month: 1.8 (-2.3, 5.9) 

Last 6 wk: -4.8 (-9.9, 0.4) 

Reference: Lee et al. (2003, 043202) 

Period of Study: Jan 1996-Dec 1998 

Location: Seoul, South Korea 

Outcome: Low birth weight (LBW), 

<2500 g 

Age Groups: Child-bearing age women 

and their newborn children-delivered at 

37-44 gestational wk

Study Design: Cross-section

N: 388,905 full-term single births 

Statistical Analyses: Generalized 

additive model, LOESS, Akaike’s 

criterion, 

Covariates: Infant sex, birth order, 

maternal age, parental education level, 

time trend and gestational age. 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: Arithmetic avg of 

hourly measurements at 20 stations 

Mean (SD): 71.1 (30.1) 

Percentiles: 

25th: 47.4 

50th(Median): 67.6 

75th: 89.3 

Range (Min, Max): 18.4, 236.9 

Monitoring Stations: 20 

Copollutant (correlation): 

1st trimester: 

PM10-CO: 0.47 

PM10-SO2: 0.78 

PM10-NO2: 0.66 

2nd trimester: 

PM10-CO: 0.68 

PM10-SO2: 0.82 

PM10-NO2: 0.81 

3rd trimester: 

PM10-CO: 0.69 

PM10-SO2: 0.85 

PM10-NO2: 0.80 

PM Increment: IQR, 41.9 

RR Estimate [Lower CI, Upper CI]: 

1st trimester: 1.03 [1.00, 1.07] 

2nd trimester: 1.04 [1.00, 1.08] 

3rd trimester: 1.00 [0.95, 1.04] 

All trimesters: 1.06 [1.01, 1.10] 

Low exposure in last 5 mo using IQR 

during last 5 mo: 0.94 [0.85, 1.05] 

Low exposure in first 5 mo using IQR 

during first 5 mo: 1.04 [1.01, 1.08] 

Notes: Birth weight was decreased by 

19.6 g for an IQR increase in the 2nd 

trimester. 

The OR for LBW increased for female 

children, fourth or higher order child, 

mother <20 yr of age, and low parental 

education level. 

Reference: Leem et al. (2006, 089828) 

Period of Study: 2001-2002 

Location: Incheon, Korea 

Outcome (ICD9 and ICD10): Age 

Groups: Pre-term delivery

Study Design: Cross-sectional

N: Cases: 2,082 

Controls: 50,031 

Statistical Analyses: Log-binomial 

regression (corrected for overdispersion

Used the log link function) 

Covariates: Maternal age, parity, sex, 

season of birth, and education level of 

each parent 

Season: Controlled as a covariate 

Dose-response Investigated? Yes, 

assessed quartiles of exposure 

Statistical Package: NR

Pollutant: PM10

Averaging Time: Trimesters (daily 

hourly data used to calculate) 

Range (Min, Max): Reported ranges 

within quartiles by trimester: 

1st Trimester: 

4: 64.57-106.39 

3: 53.84-64.56 

2: 45.95-53.83 

1: 26.99-45.94 

3rd Trimester: 

4: 65.63-95.91 

3: 56.07-65.62 

2: 47.07-56.06 

1: 33.12-47.06 

Monitoring Stations: 27 monitoring 

stations 

Pollutant levels for each area were 

predicted from the levels recorded at 

the monitors using ordinary block 

kriging 

Copollutant (correlation): 

SO2 (r = 0.13) 

NO2 (r = 0.37) 

CO (r = 0.27) 

Effect Estimate [Lower CI, Upper CI]: 

Crude and Adjusted RR for preterm 

delivery and exposure during the 1st 

trimester 

Crude 

Quartiles of exposure: 

4: 1.07 (0.95, 1.21) 

3: 1.02 (0.90, 1.15) 

2: 1.06 (0.94, 1.20) 

1: 1.00 

Adjusted 

Quartiles of exposure: 

4: 1.27 (1.04, 1.56) 

3: 1.13 (0.94, 1.37) 

2: 1.14 (0.97, 1.34) 

1: 1.00 

p-trend: 0.39 

Crude and Adjusted RR for preterm 

delivery and exposure during the 3rd 

trimester 

Crude 

Quartiles of exposure: 

4: 1.06 (0.94, 1.20) 

3: 1.06 (0.94, 1.19) 

2: 1.05 (0.93, 1.18) 

1: 1.00 

Adjusted 

Quartiles of exposure: 

4: 1.09 (0.91, 1.30) 

3: 1.04 (0.90, 1.21) 

2: 1.05 (0.91, 1.20) 

1: 1.00 

p-trend: 0.33 

December 2009 E-452 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Lin et al. (2004, 095787) 

Period of Study: Jan 1998-Dec 2000 

Location: São Paulo, Brazil 

Outcome: Neonatal death 

Age Groups: Neonates (infants 0-28 

days after birth) 

Study Design: Time series

N: 1096 days, 6697 deaths 

Statistical Analyses: Poisson 

regression (GAM) 

Covariates: Non-parametric LOESS 

smoothers to control for: time (long term 

trend), temperature, humidity, and day 

of week 

Also controlled for holidays with linear 

term 

Season: All 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: Lag 0, “ma from 2 to 

7 days” 

Notes: No explicit control for season 

apart from temperature 

Pollutant: PM10

Averaging Time: Daily values 

Mean (SD): 48.62 (21.18) 

Range (Min, Max): 13.9, 157.3

Monitoring Stations: NR (indicated 

more than 1) 

Copollutant (correlation): 

CO r = 0.71 

NO2 r = 0.76 

SO2 r = 0.80 

O3 r = 0.36 

PM Increment: 1 μg/m3

Log relative rate (standard error) lag 

Single pollutant model 

0.0017 (0.0008) lag 0 

This translates to a 4.0% [95% CI: 0.3, 

7.9] increase in neonatal mortality for a 

23.3 μg/m3

 increase in PM10 

Two-pollutant model 

0.0000 (0.0011) lag 0 

Notes: -In two-pollutant model with PM10

and SO2 (which are highly correlated), 

effect of PM disappeared and effect of 

SO2 remained constant 

- Results from pollutant ma from 2-7 days 

not reported, authors indicate effects only 

found for lag 0 (same day levels) 

- Confidence intervals reported in abstract 

are incompatible with βs/standard errors 

and plotted results in text: abstract 

indicates a 4% increase in mortality with 

95% CI: 2-6 for a 23.3 μg/m3

 increase in 

PM10

Reference: (Lin et al., 2004, 089827) 

Period of Study: 1995-1997 

Location: Taipei and Kaoshiung, 

Taiwan 

Outcome: Low birth weight (<2500 

grams) 

Age Groups: Newborns 

Study Design: Cross-sectional

N: 92,288 infants 

Statistical Analyses: Logistic 

regression 

Covariates: Gender, birth order, 

gestational weeks, season of birth, 

maternal age, maternal education, 

copollutants 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: The 9-month 

pregnancy period for each infant, and 

each trimester 

Pollutant: PM10

Averaging Time: NR, “daily 

measurements” 

Mean (SD): Reported by monitoring 

station: Taipei: 

1. 48.78 

2. 46.29 

3. 48.79 

4. 50.80 

5. 52.54 

Kaohsiung 

1. 69.99 

2. 63.39 

3. 64.89 

4. 75.79 

5. 77.27 

Monitoring Stations: 

10 (5 in each city)

Notes: All pregnant women/infants 

included in study lived within 3 km of an 

air quality monitoring station 

Pollution assigned based on nearest air 

quality station to the maternal residence

Co-pollutant: CO, SO2, O3, NO2

PM Increment: Tertiles 

Entire pregnancy 

T1: <46.4 ppb 

T2: 46.4-63.1 ppb 

T3: >63.1 ppb 

First trimester 

T1: <45.8 ppb 

T2: 45.8-67.6 ppb 

T3: >67.6 ppb 

Second trimester 

T1: <44.6 ppb 

T2: 44.6-64.2 ppb 

T3: >64.2 ppb 

Third trimester 

T1: <43.7 ppb 

T2: 43.7-63.7 ppb 

T3: >63.7 ppb 

RR Estimate [Lower CI, Upper CI] 

Entire pregnancy 

T1: 1.00 

T2: 0.96 [0.83, 1.11] 

T3: 0.87 [0.71, 1.05] 

First trimester 

T1: 1.00 

T2: 0.96 [0.84, 1.09] 

T3: 0.97 [0.80, 1.17] 

Second trimester 

T1: 1.00 

T2: 1.03 [0.90, 1.17] 

T3: 1.00 [0.83, 1.21] 

Third trimester 

T1: 1.00 

T2: 1.02 [0.90, 1.16] 

T3: 0.97 [0.81, 1.17] 

Notes: RR for births in Kaoshiung vs. 

Taipei: 1.13 [1.03, 1.24] 

Reference: Lipfert et al. (2000, 004103) 

Period of Study: 1990 

Location: U.S. 

Outcome: Infant mortality 

Including respiratory mortality 

(traditional definition, ICD9 460-519), 

expanded definition (adds ICD9 769 

and 770) 

Age Groups: Infants 

Study Design: Cross-sectional

N: 2,413,762 infants in 180 counties 

Pollutant: PM10

Averaging Time: Yearly avg used 

Mean (SD): 33.1 (9.17) (based on 180 

counties) 

Range (Min, Max): (16.9, 59) 

Monitoring Stations: NR 

Copollutant (correlation): 

PM Increment: NR (present regression 

coefficients) 

Effect Estimate [Lower CI, Upper CI]: 

Presented regression coefficients 

(standard errors) 

(3 PM exposures regressed jointly) 

bold = p <0.05 

Cause of death: All 

Birth weight: All 

PM10: 0.0114 (0.0015) 

December 2009 E-453 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

(Ns differ for various models) 

Statistical Analyses: Logistic 

regression 

Covariates: Mother’s smoking, 

education, marital status, and race 

Month of birth 

And county avg heating degree days 

Dose-response Investigated? NR 

Statistical Package: NR 

PM10

SO4

2– (r = 0.10) 

NSPM10-non-sulfate portion of PM10

(r = 0.91) 

CO (r = 0.27) 

SO2 (r = 0.04) 

Notes: TSP-based sulfate was adjusted 

for compatibility with the PM10-based 

data 

SO4

2–: -0.0002 (0.0061) 

NSPM10: 0.0115 (0.0014) 

Cause of death: All 

Birth weight: LBW 

PM10: 0.0088 (0.0019) 

SO4

2–: 0.0265 (0.0080) 

NSPM10: 0.0086 (0.0020) 

Cause of death: All 

Birth weight: normal 

PM10: 0.0092 (0.0024) 

SO4

2–: -0.0488 (0.0098) 

NSPM10: 0.0096 (0.0024) 

Cause of death: All neonatal 

Birth weight: All 

PM10: 0.0126 (0.0018) 

SO4

2–: 0.0267 (0.0076) 

NSPM10: 0.0126 (0.0018) 

Cause of death: All neonatal 

Birth weight: LBW 

PM10: 0.0086 (0.0022) 

SO4

2–: 0.0388 (0.0088) 

NSPM10: 0.0093 (0.0022) 

Cause of death: All neonatal 

Birth wt: normal 

PM10: 0.0123 (0.0041) 

SO4

2–: -0.0334 (0.0169) 

NSPM10: 0.0125 (0.0040) 

Cause of death: All post neonatal 

Birth wt: All 

PM10: 0.0091 (0.0024) 

SO4

2–: -0.0474 (0.0100) 

NSPM10: 0.0096 (0.0024) 

Cause of death: All post neonatal 

Birth wt: LBW 

PM10: 0.0096 (0.0043) 

SO4

2–: -0.0247 (0.0173) 

NSPM10: 0.0101 (0.0042) 

Cause of death: All post neonatal 

Birth wt: normal 

PM10: 0.0074 (0.0030) 

SO4

2–: -0.0569 (0.0121) 

NSPM10: 0.0080 (0.0029) 

Cause of death: SIDS 

Birth weight: All 

PM10: 0.0138 (0.0038) 

SO4

2–: -0.1078 (0.0151) 

NSPM10: 0.0149 (0.0037) 

Cause of death: SIDS 

Birth weight: LBW 

PM10: 0.0115 (0.0088) 

SO4

2–: -0.1378 (0.0337) 

NSPM10: 0.0146 (0.0085) 

Cause of death: SIDS 

Birth weight: normal 

PM10: 0.0137 (0.0042) 

SO4

2–: -0.0995 (0.0168) 

NSPM10: 0.0147 (0.0041) 

Cause of death: All respiratory (ICD9: 460-

519, 769, 770) 

Birth weight: All 

PM10: 0.0168 (0.0034) 

SO4

2–: 0.0706 (0.0146) 

NSPM10: 0.0166 (0.0034) 

Cause of death: All respiratory (ICD9: 460-

519, 769, 770) 

Birth weight: LBW 

PM10: 0.0144 (0.0038) 

SO4

2–: 0.0821 (0.0158) 

NSPM10: 0.0139 (0.0038) 

Cause of death: All respiratory (ICD9: 460-

519, 769, 770) 

Birth weight: normal 

PM10: 0.0177 (0.0091) 

SO4

2–: 0.0001 (0.0392) 

NSPM10: 0.0118 (0.0090) 

Cause of death: Respiratory disease 

(ICD9: 460-519) 

Birth weight: All 

December 2009 E-454 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

PM10: 0.0133 (0.0089) 

SO4

2–: 0.0093 (0.0384) 

NSPM10: 0.0134 (0.0089) 

Cause of death: Respiratory disease 

(ICD9: 460-519) 

Birth weight: LBW 

PM10: 0.0092 (0.0137) 

SO4

2–: 0.0434 (0.0580) 

NSPM10: 0.0089 (0.0138) 

Cause of death: Respiratory disease 

(ICD9: 460-519) 

Birth weight: normal 

PM10: 0.0126 (0.0120) 

SO4

2–: -0.0177 (0.0509) 

NSPM10: 0.0128 (0.0119) 

Associations with SIDS by smoking status 

Smoking status: Yes 

Birth weight: Normal 

PM10: 0.0202 (0.0073) 

SO4

2–: -0.0722 (0.0284) 

NSPM10: 0.0206 (0.0071) 

Smoking status: No 

Birth weight: Normal 

PM10: 0.0104 (0.0051) 

SO4

2–: -0.114 (0.021) 

NSPM10: 0.0117 (0.005) 

Smoking status: Yes 

Birth weight: LBW 

PM10: 0.0322 (0.0130) 

SO4

2–: -0.0958 (0.0483) 

NSPM10: 0.0345 (0.0125) 

Smoking status: No 

Birth weight: LBW 

PM10: -0.0044 (0.012) 

SO4

2–: -0.0172 (0.047) 

NSPM10: -0.0007 (0.012) 

Mean risks (95%CI) between post 

neonatal SIDS among normal birth weight 

babies 

pollutants regressed one at a time 

PM10: 1.20 (1.02, 1.42) 

SO4

2–: 0.43 (0.37, 0.51) 

NSPM10: 1.33 (1.18, 1.50) 

Reference: Maisonet et al. (2001, 

016624) 

Period of Study: 1994-1996 

Location: Northeastern U.S. (6 cities: 

Boston, Hartford, Philadelphia, 

Pittsburgh, Springfield, Washington DC) 

Outcome: Low birth weight (LBW): 

infants with a birth weight <2,500 g and 

having a gestational age between 37 

and 44 wk 

Age Groups: Term live births 

(singleton) 

Study Design: Cross-sectional

N: 89,557 infants 

Statistical Analyses: Logistic 

regression (LBW) and linear regression 

(for reductions in birth weight) 

Covariates: Gestational age, gender, 

birth order, maternal age, race/ethnicity, 

yr of education, marital status, 

adequacy of prenatal care, previous 

induced or spontaneous abortions, 

weight gain during pregnancy, maternal 

prenatal smoking, and alcohol 

consumption 

Season 

Season: Yes, as covariate 

Dose-response Investigated? Yes, 

categorical exposure variables 

assessed 

Statistical Package: STATA 

Pollutant: PM10

Averaging Time: Trimester avg 

calculated using 24-h measurements 

taken every 6 days 

Range (Min, Max): Ranges for 

categories of exposure: 

1st Trimester 

<25th: <24.821 

25 to <50th: 24.821, 30.996 

50 to <75th: 30.997, 36.142 

75 to <95th: 36.143, 46.547 

≥ 95th: ≥ 46.548 

2nd Trimester 

<25th: <24.702 

25 to <50th: 24.702, 30.294 

50 to <75th: 30.295, 35.410 

75 to <95th: 35.411, 43.928 

≥ 95th: ≥ 43.929 

3rd Trimester 

<25th: <24.702 

25 to <50th: 24.702, 30.162 

50 to <75th: 30.163, 35.642 

75 to <95th: 35.643, 43.588 

≥ 95th: ≥ 43.589 

Monitoring Stations: 3-4 per city 

Copollutants: CO, SO2

PM Increment: 10 μg/m3 for analyses 

assessing exposures continuously 

Effect Estimate [Lower CI, Upper CI]: 

ORs for term LBW by trimester 

1st Trimester Crude 

<25th: 1.00 

25 to <50th: 1.02 (0.90, 1.14) 

50 to <75th: 0.90 (0.65, 1.24) 

75 to <95th: 0.87 (0.58, 1.30) 

≥ 95th: 0.89 (0.60, 1.33) 

Continuous: 0.93 (0.77, 1.13) 

1st Trimester Adjusted 

<25th: 1.00 

25 to <50th: 1.02 (0.94, 1.11) 

50 to <75th: 0.90 (0.78, 1.03) 

75 to <95th: 0.85 (0.73, 1.00) 

≥ 95th: 0.83 (0.70, 0.97) 

Continuous: 0.93 (0.85, 1.00) 

2nd Trimester Crude 

<25th: 1.00 

25 to <50th: 1.01 (0.93, 1.10) 

50 to <75th: 0.90 (0.66, 1.21) 

75 to <95th: 0.92 (0.62, 1.34) 

≥ 95th: 0.90 (0.61, 1.33) 

Continuous: 0.95 (0.78, 1.16) 

2nd Trimester Adjusted 

<25th: 1.00 

25 to <50th: 1.06 (0.97, 1.15) 

50 to <75th: 0.95 (0.85, 1.07) 

75 to <95th: 0.91 (0.79, 1.05) 

≥ 95th: 0.77 (0.63, 0.95) 

Continuous: 0.93 (0.85, 1.02) 

3rd Trimester Crude 

<25th: 1.00 

December 2009 E-455 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

25 to <50th: 0.94 (0.85, 1.05) 

50 to <75th: 0.86 (0.58, 1.25) 

75 to <95th: 0.86 (0.57, 1.29) ≥ 95th: 0.92 (0.61, 1.38) 

Continuous: 0.95 (0.75, 1.20) 

3rd Trimester Adjusted 

<25th: 1.00 

25 to <50th: 0.98 (0.87, 1.10) 

50 to <75th: 0.92 (0.76, 1.11) 

75 to <95th: 0.88 (0.75, 1.04) ≥ 95th: 0.91 (0.77, 1.07) 

Continuous: 0.96 (0.88, 1.06) 

Adjusted ORs by race/ethnicity 

Whites: 

1st Trimester 

<25th: 1.00 

25 to <50th: 1.13 (0.96, 1.33) 

50 to <75th: 1.00 (0.92, 1.08) 

75 to <95th: 1.00 (0.91, 1.09) ≥ 95th: 0.92 (0.81, 1.04) 

Continuous: 0.94 (0.90, 0.98) 

2nd Trimester 

<25th: 1.00 

25 to <50th: 0.88 (0.77, 1.02) 

50 to <75th: 0.95 (0.89, 1.02) 

75 to <95th: 0.95 (0.84, 1.07) ≥ 95th: 0.89 (0.64, 1.26) 

Continuous: 0.96 (0.89, 1.04) 

3rd Trimester 

<25th: 1.00 

25 to <50th: 0.84 (0.64, 1.11) 

50 to <75th: 0.91 (0.83, 1.01) 

75 to <95th: 0.80 (0.71, 0.90) ≥ 95th: 1.03 (0.86, 1.24) 

Continuous: 0.95 (0.90, 1.00) 

African Americans: 

1st Trimester 

<25th: 1.00 

25 to <50th: 1.01 (0.98, 1.05) 

50 to <75th: 0.88 (0.79, 0.98) 

75 to <95th: 0.83 (0.70, 0.97) ≥ 95th: 0.81 (0.67, 0.99) 

Continuous: 0.93 (0.85, 1.01) 

2nd Trimester 

<25th: 1.00 

25 to <50th: 1.10 (0.93, 1.30) 

50 to <75th: 0.95 (0.80, 1.12) 

75 to <95th: 0.88 (0.69, 1.11) ≥ 95th: 0.75 (0.54, 1.03) 

Continuous: 0.92 (0.80, 1.05) 

3rd Trimester 

<25th: 1.00 

25 to <50th: 1.08 (0.92, 1.27) 

50 to <75th: 0.89 (0.70, 1.12) 

75 to <95th: 0.94 (0.75, 1.18) ≥ 95th: 0.83 (0.71, 0.97) 

Continuous: 0.99 (0.87, 1.11) 

Hispanics: 

1st Trimester 

<25th: 1.00 

25 to <50th: 0.83 (0.64, 1.06) 

50 to <75th: 0.86 (0.70, 1.05) 

75 to <95th: 0.79 (0.68, 0.93) ≥ 95th: 1.36 (1.06, 1.75) 

Continuous: 0.96 (0.84, 1.09) 

2nd Trimester 

<25th: 1.00 

25 to <50th: 1.16 (0.84, 1.61) 

50 to <75th: 0.86 (0.63, 1.19) 

75 to <95th: 0.98 (0.71, 1.34) ≥ 95th: 0.68 (0.38, 1.21) 

Continuous: 0.92 (0.81, 1.05) 

3rd Trimester 

<25th: 1.00 

25 to <50th: 0.77 (0.55, 1.07) 

50 to <75th: 1.12 (0.76, 1.66) 

75 to <95th: 0.93 (0.65, 1.31) ≥ 95th: 0.90 (0.55, 1.47) 

December 2009 E-456 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Continuous: 0.96 (0.80, 1.15) 

Reference: Mannes et al.(2005, 

087895)

Period of Study: Jan 1998-Dec 2000

Location: Metropolitan Sydney, 

Australia 

Outcome: Risk of SGA and birth weight

Age Groups: All singleton births >20 

wk and ≥ 400 grams birth weight and 

maternal all ages 

Study Design: Cross-sectional

N: 138,056 singleton births

Statistical Analyses: Logistic and 

linear regression models

Covariates: Sex of child, maternal age, 

gestational age, maternal smoking, 

gestational age at first antenatal visit, 

maternal indigenous status, whether 

first pregnancy, season of birth, 

socioeconomic status 

Season: All seasons 

Included as covariate

Dose-response Investigated? No 

Statistical Package: SAS v8.02

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 16.8 (7.1) 

25th: 12.3

50th(Median): 15.7

75th: 19.9 

Range (Min, Max): (3.8-104.0)

Monitoring Stations: up to 14

Copollutants (correlations): 

CO: r = 0.26 

NO2: r = 0.47 

O3: r = 0.52 

PM2.5: r = 0.81 

PM Increment: 1 μg/m3

Risk of SGA 

All births 

One month before birth: 

OR = 1.01 (1.00-1.03) 

Third trimester: OR = 1.00 (0.99-1.013) 

Second trimester: 

OR = 1.01 (1.00-1.04) 

First trimester: OR = 1.00 (0.98-1.02) 

5 km births 

One month before birth: OR = 1.00 (0.99-

1.02) 

Third trimester: OR = 1.01 (0.99-1.02) 

Second trimester: 

OR = 1.02 (1.01-1.03) 

First trimester: OR = 1.01 (0.99-1.02) 

Change in birth weight 

All births 

One month before birth: 

ß = -1.21 (-2.31- -0.11) 

Third trimester: ß = -0.95 (-2.30-0.40) 

Second trimester: 

ß = -2.05 (-3.36- -0.74) 

First trimester: ß = -0.14 (-1.37- 1.09) 

5 km births 

One month before birth: 

ß = -2.98 (-4.25- -1.71) 

Third trimester: ß = -3.84 (-5.35- -2.33) 

Second trimester: 

ß = -4.28 (-5.79- -2.77) 

First trimester: ß = -2.57 (-4.04- -1.10) 

Key second trimester findings 

Single pollutant model: 

ß = -4.28 (-5.79- -2.77) 

2 pollutant (PM10 and CO): 

ß = -3.72 (-6.29- -1.15) 

2 pollutant (PM10 and NO2): 

ß = -2.65 (-4.32- -0.98) 

2 pollutant (PM10 and O3): 

ß = -5.47 (-7.06- -3.88) 

4 pollutant (PM10, NO2, CO and O3 ): ß = -

3.27 (-7.05-0.51) 

Controlling for exposures in other 

pregnancy periods: 

ß = -3.03 (-4.85- -1.21) 

Reference: Pereira et al. (1998, 

007264) 

Period of Study: Jan 1991-Dec 1992 

Location: Sao Paulo, Brazil 

Notes: Paper does not focus on PM as 

a pollutant of interest. 

Outcome: Intrauterine mortality 

(fetuses over 28 wk of pregnancy)

Study Design: Time-series

N: 730 days with PM measures 

Statistical Analyses: Poisson 

regression 

Covariates: Season, day of the week 

and weather (temperature and relative 

humidity) 

Season: Assessed by including 24 

indicator variables for month and yr 

Dose-response Investigated? No 

Statistical Package: NR 

Lags Considered: Paper focuses on 

other pollutants (lags for PM not 

reported) 

Pollutant: PM10

Averaging Time: 24 h mean

Mean (SD): 65.04 (27.28) 

Range (Min, Max): (14.80, 192.80)

Monitoring Stations: 13 (avgd to 

provide city-wide pollutant level) 

Copollutants (correlation): 

NO2 (r = 0.45) 

SO2 (r = 0.74) 

CO (r = 0.41) 

O3 (r = 0.25) 

PM Increment: NR (reported only 

regression coefficients for PM) 

Effect Estimate [Lower CI, Upper CI]: 

Regression coefficients (standard errors) 

for pollutants when considered separately 

and simultaneously in the completed 

model: 

Separately: 0.0008 (0.0006) 

Simultaneously: -0.0005 (0.0010) 

December 2009 E-457 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ritz et al. (2000, 012068) 

Period of Study: 1989-1993 

Location: Southern California 

Outcome: Preterm birth (treated 

dichotomously as birth at <37 wk 

gestation 

Also analyzed continuously) 

Age Groups: Infants (born vaginally 

between 26-44 wk of gestation) 

Study Design: Cross-sectional

N: 97,158 births 

Statistical Analyses: Logistic and 

linear regression 

Covariates: Maternal age, race, 

education, parity, interval since the 

previous live birth, access to prenatal 

care, infant sex, previous low weight or 

preterm births, smoking (reported as 

“pregnancy complications”) 

To examine effect modification, authors 

conducted stratified analysis by region, 

birth and conception seasons, maternal 

age, race, education, and infant gender 

Season: Some models included 

season of birth or conception 

Also assessed as effect modifier in 

stratified analyses 

Dose-response Investigated? 

Examined adequacy of linear or loglinear relation using indicator terms for 

pollutant-avg quartiles 

Results presented in Fig 2 (doseresponse demonstrated for last 6 wk 

exposure period) 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: 24-h avg at 6 day 

intervals 

avgd pollutant measures for 1, 2, 4, 6, 

8, 12, and 26 wk before birth and the 

whole pregnancy period 

Mean (SD): 6 wk before birth: 47.5 

(15.0) 

1st month of pregnancy: 49.3 (16.9) 

Range (Min, Max): 6 wk before birth: 

12.3-152.3 

1st month of pregnancy: 9.5-178.8 

Monitoring Stations: 17 stations (PM 

measured at only 8 stations) 

Copollutants (correlations): 

6 wk before birth: 

CO (r = 0.43) 

NO2 (r = 0.74) 

O3 (r = 0.20) 

1st month of pregnancy: 

CO (r = 0.37) 

NO2 (r = 0.71) 

O3 (r = 0.23) 

Notes: Avgd pollutant measures taken 

at the air monitoring station closest to 

the residence 

PM Increment: 50 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

All 8 stations 

6 wk before birth 

Crude: 1.20 (1.09, 1.33) 

2 exposure periods: 1.18 (1.07, 1.31) 

Other risk factors: 1.15 (1.04, 1.26) 

Other RFs plus season: 1.15 (1.03, 1.29) 

Multipollutant model: 1.19 (1.01, 1.40) 

1st month of pregnancy 

Crude: 1.16 (1.06, 1.26) 

2 exposure periods: 1.13 (1.04, 1.24) 

Other risk factors: 1.09 (1.00, 1.19) 

Other RFs plus season: 1.09 (0.99, 1.20) 

Multipollutant model: 1.12 (0.97, 1.29) 

Coastal stations only 

6 wk before birth 

Crude: 1.22 (1.00, 1.49) 

2 exposure periods: 1.28 (1.04, 1.56) 

Other risk factors: 1.13 (0.93, 1.38) 

Other RFs plus season: 1.18 (0.92, 1.51) 

Multipollutant model: 1.42 (097, 2.01) 

1st month of pregnancy 

Crude: 1.28 (1.06, 1.54) 

2 exposure periods: 1.32 (1.09, 1.59) 

Other risk factors: 1.17 (0.97, 1.40) 

Other RFs plus season: 0.99 (0.79, 1.24) 

Multipollutant model: 1.09 (0.83, 1.41) 

Inland stations only 

6 wk before birth 

Crude: 1.27 (1.12, 1.44) 

2 exposure periods: 1.27 (1.11, 1.44) 

Other risk factors: 1.19 (1.05, 1.35) 

Other RFs plus season: 1.27 (1.10, 1.48) 

Multipollutant model: 1.18 (0.97, 1.43) 

1st month of pregnancy 

Crude: 1.16 (1.04, 1.29) 

2 exposure periods: 1.16 (1.04, 1.29) 

Other risk factors: 1.09 (0.98, 1.21) 

Other RFs plus season: 1.09 (0.97, 1.24) 

Multipollutant model: 1.11 (0.93, 1.33) 

Crude estimates for last 6 wk exposure 

by season 

Fall: 1.08 (0.88, 1.31) 

Summer: 1.06 (0.87, 1.29) 

Winter: 1.33 (1.07, 1.65) 

Spring: 1.81 (1.41, 2.31) 

Reduction in mean gestation length for 

each increase in PM10 during last 6 wk 

before birth (linear regression analysis)

Crude: 0.66 (± 0.24) days 

Adj: 0.90 (± 0.27) days 

Notes: Effect estimates remain stable 

when excluding SGA or LBW children or 

when restricting preterm births to SGA or 

LBW children only (results not presented) 

December 2009 E-458 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ritz, et al. (2002, 023227)

Period of Study: 1987-1993

Location: Southern California 

(Jul 1990-Jul 1993 for Los Angeles, 

1989 for Riverside, 1988-1989 for San 

Bernardino, and 1987-1989 for Orange 

counties 

Outcome: 

1) Aortic defects 

2) Defects of the atrium and atrium 

Sepum 

3) Endocardial and mitral valve defects 

4) Pulmonary artery and valve defects 

5) Conotruncal defects including 

tetralogy of Fallot, transposition of great 

vessels, truncus arteriosus communis, 

double outlet right ventricle, and 

aorticopulmonary window 

and 6) Ventricular Sepal defects not 

included in the conotruncal category. 

Age Groups: All live born infants and 

fetal deaths diagnosed between 20 wk 

of gestation and 1 yr after birth 

Study Design: Case-control

N: 10,649 infants and fetuses 

Statistical Analyses: Hierarchical (twolevel) regression model, polytomous 

logistic regression, linear model 

Covariates: Gender, no prenatal care, 

multiple births, no siblings, maternal 

race, maternal age, maternal education, 

born before 1990, season of 

conception, 

Season: All

Dose-response Investigated? Yes, for 

O3 and CO, study found a clear doseresponse pattern for aortic Sepum and 

valve and ventricular Sepal defects and 

possibly for conotruncal and pulmonary 

artery and valve defects 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24 h (every 6 days)

PM Component: vehicle emissions

Monitoring Stations: 11 (for PM10)

Copollutants (correlations): 

CO: r = 0.32 

NO2(NR) 

O3 (NR) 

Notes: The authors did not observe 

consistently increased risks and doseresponse patterns for PM10 after 

controlling for the effects of CO and O3 on 

these cardiac defects. (Quantitative results 

not shown). 

December 2009 E-459 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ritz et al. (2006, 089819)

Period of Study: 1989-2000

Location: 389 South Coast Air Basin 

(SoCAB) zip codes 

Outcome: Total infant deaths during the 

first yr of life as well as all respiratory 

causes of death (ICD-9 codes 460-519, 

769, 770.4, 770.7, 770.8, and 770.9 

and ICD-10 codes J00-J98, P22.0, 

P22.9, P27.1, P27.9, P28.0, P28.4, 

P28.5, and P28.9) and sudden infant 

death syndrome (SIDS) (ICD-9 code 

798.0 and ICD-10 code R95).

Age Groups: Infants 0-1 yr

Study Design: Case-control

N: 2,975,059 births and 19,664 infant 

deaths 

Cases, n = 13,146 

Controls, n = 151,015 

Statistical Analyses: Conditional 

logistic regression analysis 

Covariates: Risk factors available on 

birth and/or death certificates (maternal 

age, race/ethnicity, and education, level 

of prenatal care, infant gender, parity, 

birth country, and death season) 

Season: Death season (spring, 

summer, fall, winter)

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 

2 wk before death: 46.2

1 month before death: 46.3 

2 mo before death: 46.3 

6 mo before death: 46.3 

Range (Min, Max): 

2 wk before death: (21.0-83.5) 

1 month before death: (25.0-77.2) 

2 mo before death: (27.6-74.2) 

6 mo before death: (31.3-69.5) 

Monitoring Stations: maximum of 31 

Copollutants (correlation): 

2 wk before death 

CO: r = 0.33 

NO2: r = 0.48 

O3: r = 0.12 

1 month before death 

CO: r = 0.33 

NO2: r = 0.48 

O3: r = 0.12 

2 mo before death 

CO: r = 0.32 

NO2: r = 0.48 

O3: r = 0.12 

6 mo before death 

CO: r = 0.29 

NO2: r = 0.44 

O3: r = 0.16 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

All-cause death 

2 mo before death 

Single-pollutant model: 

<25th = 1.04 (1.01-1.06) 

25th-75th = 0.96 (0.89-1.04) 

>75th = 1.14 (1.03-1.27) 

Multiple-pollutant model: 

<25th = 1.02 (0.99-1.05) 

25th-75th = 0.92 (0.84-1.00) 

>75th = 1.07 (0.95-1.20) 

SIDS 

2 mo before death: 

Single-pollutant model: 

<25th = 1.03 (0.99-1.08) 

25th-75th = 0.94 (0.81-1.08) 

>75th = 1.13 (0.93-1.36) 

Multiple-pollutant model: 

<25th = 1.01 (0.95-1.07) 

25th-75th = 0.90 (0.76-1.06) 

>75th = 0.99 (0.80-1.24) 

Respiratory death 

2 wk before death 

Postneonatal deaths (28 days to 1 y) 

Single-pollutant model: 

<25th = 1.05 (1.01-1.10) 

25th-75th = 1.13 (1.01-1.10) 

>75th = 1.46 (1.13-1.88) 

Multiple-pollutant model: 

<25th = 1.04 (0.98-1.09) 

25th-75th = 1.09 (0.86-1.38) 

>75th = 1.40 (1.03-1.89) 

Postneonatal deaths (28 days to 3 mo) 

Single-pollutant model: 

<25th = 1.01 (0.95-1.08) 

25th-75th = 1.16 (0.82-1.63) 

>75th = 1.44 (0.96-2.17) 

Multiple-pollutant model: 

<25th = 1.00 (0.92-1.09) 

25th-75th = 0.97 (0.67-1.42) 

>75th = 1.23 (0.76-2.00) 

Post neonatal deaths (4-12 mo) 

Single-pollutant model: 

<25th = 1.12 (1.02-1.23) 

25th-75th = 1.08 (0.81-1.44) 

>75th = 1.41 (1.02-1.96) 

Multiple-pollutant model: 

<25th = 1.07 (1.00-1.15) 

25th-75th = 1.02 (0.75-1.40) 

>75th = 1.36 (0.92-2.01) 

December 2009 E-460 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rogers et al. (2006, 

091232) 

Period of Study: 1986-1988

Location: Georgia, USA 

Outcome: VLBW 

Term, AGA, Preterm AGA, Preterm, 

SGA 

Age Groups: Newborns and their 

mothers (<19 to ≥ 35-yr-old) 

Study Design: Case-control

N: 325 infants (69 preterm SGA 

59 preterm AGA 

197 term AGA) and their mothers

Statistical Analyses: Logistic 

regression

Covariates: Maternal age, maternal 

race, maternal education, active and 

passive smoking, birth season, 

prepregnancy weight, pregnancy weight 

gain, maternal toxemia, anemia, 

asthma 

Dose-response Investigated? Yes, 

used

Statistical Package: SUDAAN 

Cochran-Armitage test for trend to 

determine whether the observed 

proportions of cases and controls 

differed in a linear manner across 

exposure categories. 

Pollutant: PM10

Averaging Time: annual 

Preterm SGA: 

50th(Median): 3.38 

Preterm AGA: 

50th(Median): 7.84 

Term AGA: 

50th(Median): 3.23 

Monitoring Stations: NR

Percent Mothers Residing In County 

With Industrial Point Source 

Preterm SGA: 60.9% 

Preterm AGA: 79.7% 

Term AGA: 60.4% 

Percent Mothers Residing In PM10

Quartile (based on environmental 

transport model) 

Preterm SGA 

1st quartile (<1.48): 31.9% 

2nd quartile (1.48-3.74): 18.8% 

3rd quartile (3.75-15.07): 26.1% 

4th quartile (>15.07): 23.2% 

Preterm AGA 

1st quartile (<1.48): 16.9% 

2nd quartile (1.48-3.74): 22.1% 

3rd quartile (3.75-15.07): 28.8% 

4th quartile (>15.07): 32.2% 

Term AGA 

1st quartile (<1.48): 24.7% 

2nd quartile (1.48-3.74): 28.4% 

3rd quartile (3.75-15.07): 27.9% 

4th quartile (>15.07): 19.3% 

PM Increment: Quartile 

Notes: Statistically significant increases in 

the odds of VLBW and preterm AGA births 

are associated with living in a county with 

a PM10 point source. Preterm AGA births 

are also associated with living in an area 

with very high (4th quartile) estimated 

PM10 exposure. 

Delivery of VLBW vs. Term AGA infant 

County with point source 

2.54 [1.46, 4.22] 

PM10 quartile 

1st quartile: reference 

2nd quartile: 

0.81 [0.42, 1.55] 

3rd quartile: 

0.85 [0.45, 1.16] 

4th quartile: 

1.94 [0.98, 3.83] 

Delivery of Preterm AGA vs. Term AGA 

infant 

County with point source 

4.31 [1.88: 9.87] 

PM10 quartile 

1st quartile: reference 

2nd quartile: 

1.56 [0.56: 4.35] 

3rd quartile: 

1.19 [0.44: 3.23] 

4th quartile: 

3.68 [1.44: 9.44] 

Delivery of Preterm AGA vs. Preterm SGA 

infant 

County with point source 

2.07 [0.83: 5.16] 

PM10 quartile 

1st quartile: reference 

2nd quartile: 

1.96 [0.59: 6.43] 

3rd quartile: 

2.10 [0.66: 6.73] 

4th quartile: 

2.58 [0.78: 8.51] 

December 2009 E-461 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Romieu et al. (2004, 

093074) 

Period of Study: 1997-2001 

Location: Ciudad Juarez, Mexico 

Outcome: Respiratory-related infant 

mortality ICD9 (460-519) 

ICD10 (J00-J99)

Age Groups: 1 month to 1 yr 

Study Design: Case crossover

N: 216 respiratory-related deaths 

N = 412 other causes and N = 628 total 

deaths 

Statistical Analyses: The acute effects 

of air pollution was modeled on both 

total and respiratory-related mortality as 

a function of the pollution levels on the 

same day and preceding days and over 

2- and 3-day avg before the date of 

death. Case-crossover with semisymmetric bidirectional referent 

selection was the approach used. Data 

were stratified by day of the week and 

calendar month. Data were analyzed 

with conditional logistic regression. 

Second and third polynomial distributed 

lag models were used to study lag 

structure. BIC was used to determine 

lag length. 

Covariate: Temperature, season 

Dose-response Investigated? Yes 

Statistical Package: STATA 7.0 

Lags Considered: 1-15 days 

Pollutant: PM10

Averaging Time: 24 h 

Mean (SD): 

1997: 33.04 (20.67) μg/m3

1998: 35.25 (17.32) μg/m3

1999: 45.92 (28.69) μg/m3

2000: 43.38 (23.77) μg/m3

2001: 39.46 (29.43) μg/m3

Monitoring Stations: 5 stations in 

Ciudad Juarez 

2 stations in El Paso (close to U.S.-

Mexico border) 

Copollutant (correlation): O3: r = 0.01 

Notes: Ciudad Juarez monitors 

measured PM10 every 6 days while El 

Paso monitors measured on a daily 

basis. 

PM Increment: 20 μg/m3

RR Estimate [Lower CI, Upper CI] lag: 

Total mortality: 

OR = 1.02 (0.94-1.11) lag 1 

OR = 1.03 (0.95-1.12) lag 2 

OR = 1.03 (0.94-1.13 ac2 

OR = 1.04 (0.95-1.15) ac3 

Respiratory mortality 

OR = 0.95 (0.83-1.09) lag 1 

OR = 1.04 (0.91-1.19) lag 2 

OR = 0.98 (0.81-1.19) ac2 

OR = 0.97 (0.74-1.26) ac3 

Higher SES 

OR = 0.82 (0.59, 1.14) lag 1 

OR = 1.08 (0.84, 1.40) lag 2 

OR = 0.89 (0.58, 1.35) ac2 

OR = 0.97 (0.52, 1.82) ac3 

Medium SES 

OR = 0.99 (0.79, 1.27) lag 1 

OR = 1.11 (0.86, 1.43) lag 2 

OR = 1.03 (0.73, 1.45) ac2 

OR = 1.17 (0.72, 1.90) ac3 

Lower SES 

OR = 1.61 (0.97-2.66) lag 1 

OR = 1.07 (0.65, 1.75) lag 2 

OR = 2.56 (1.06-6.17) ac2 

OR = 1.76 (0.59, 5.23) ac3 

Notes: 

ac2 and ac3 represent cumulative PM10

ambient levels over 2 or 3 days before 

death. 

Reference: Sagiv et al. (2005, 087468) 

Period of Study: Jan 1997-Dec 2001 

Location: Allegheny county, Beaver 

county, Lackawanna county, 

Philadelphia county, Pennsylvania, 

U.S.A. 

Outcome: Preterm birth (<36 wk) 

Age Groups: Babies born between 20 

and 44 wk 

Study Design: Time series

N: 3704 observation days, 187,997 

births 

Statistical Analyses: Poisson 

regression 

Multivariable mixed-effects model with a 

random intercept for each county to 

incorporate count-level information. 

Covariates: Temperature, dew point 

temperature, mean 6-week level of 

copollutants (CO, NO2, and SO2), longterm preterm birth trends 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: 1, 2, 3, 4, 5, 6, 7 

Pollutant: PM10

Averaging Time: Daily used to 

calculate 6-week period 

Mean (SD): 6-week period 

27.1 (8.3) 

Daily 

25.3 (14.6) 

Percentiles: 6-week period 

50th (Median): 26.0 Daily 

50th (Median): 21.6 

Range (Min, Max): 6-week period: 8.7, 

68.9 

Daily: 2.0, 156.3 

Monitoring Stations: NR 

Copollutant (correlation): Daily 

PM10-daily SO2: r = 0.46 

Also considered CO, NO2 and O3 as 

copollutants. 

PM Increment: 1) 50 μg/m3 2) Quartiles 

(first quartile is the reference) 

Exposure period: 6 wk before birth 

Per 50 μg/m3: 1.07 (0.98, 1.18) 

2nd quartile: 1.00 (0.95, 1.05) 

3rd quartile: 1.04 (0.99, 1.09) 

4th quartile: 1.03 (0.98, 1.08) 

Exposure period: 1-day acute time 

windows Per 50 μg/m3: 2-day lag: 1.10 

(1.00, 1.21) 

5-day lag: 1.07 (0.98, 1.18) 

Notes: Within the article, authors provide 

a Fig 1 displaying a graph of the relative 

risk (RR) and 95% confidence i 

ntervals (CI) for 1- to 7-day lags. While the 

authors report the 2- and 5-day lag RRs 

and 95% CIs in the text, the others are not 

specifically reported. However, the Fig 

shows the approximate RRs per 50 μg/m3

as indicated below: 

1-day lag: 1.05 

3-day lag: 1.05 

4-day lag: 1.00 

6-day lag: 0.97 

7-day lag: 1.03 

December 2009 E-462 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Salam et al., 2005, 

087885)

Period of Study: 1975-1987 

Location: Southern California 

Outcome: Birth weight 

Low birth weight (LBW 

<2500 g) 

Intrauterine growth retardation (IUGR) 

Age Groups: Children born full-term 

(between 37 and 44 wk) 

Study Design: Cohort study

N: 3901 children 

Statistical Analyses: Linear mixedeffects 

Logistic regression 

Covariates: Maternal age, months 

since last live birth, parity, maternal 

smoking during pregnancy, SES, marital 

status at childbirth, gestational diabetes, 

child’s sex, child’s race/ethnicity, child’s 

grade in school (4th, 7th, and 10th), 

Julian day of birth 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: Monthly 

Mean (SD): 

Entire pregnancy: 45.8 (12.9) 

First trimester: 46.6 (15.9) 

Second trimester: 45.4 (14.8) 

Third trimester: 45.4 (15.5) 

Monitoring Stations: 1 or 3 (See 

notes) 

Copollutant (correlation): 

Entire pregnancy 

PM10-O3[10-6]: r = 0.54 

PM10-O3[24 h): r = 0.20 

PM10-NO2: r = 0.55 

PM10-CO: r = 0.41 

First trimester 

PM10-O3[10-6]: r = 0.54 

PM10-O3[24 h]: r = 0.34 

PM10-NO2: r = 0.48 

PM10-CO: r = 0.29 

Second trimester 

PM10-O3[10-6): r = 0.50 

PM10-O3(24 h): r = 0.27 

PM10-NO2: r = 0.53 

PM10-CO: r = 0.35 

Third trimester 

PM10-O3[10-6]: r = 0.52 

PM10-O3[24 h]: r = 0.31 

PM10-NO2: r = 0.52 

PM10-CO: r = 0.37 

Notes: Exposure estimates were 

calculated by spatially interpolated 

monthly avg which were based off of 

three monitoring stations located within 

50 km of the ZIP code region of 

maternal birth residences. 

PM Increment: IQR (interquartile range) 

Outcome: birth weight (g) 

Single-pollutant model 

Entire pregnancy 

18 μg/m3

: -19.9 (-43.6, 3.8) 

First trimester 

20 μg/m3: -3.0 (-22.7, 16.7) 

Second trimester 

19 μg/m3

: -15.7 (-36.1, 4.7) 

Third trimester 

20 μg/m3

: -21.7 (-42.2 to -1.1) 

Multipollutant model 

(Included O3

(24 h) in model 

Third trimester exposure) 

20 μg/m3

: -10.8 (-31.8, 10.2) 

Outcome: IUGR (ORs) 

Single-pollutant model 

Entire pregnancy 

18 μg/m3

: 1.1 (0.9, 1.3) 

First trimester 

20 μg/m3: 1.0 (0.9, 1.2) 

Second trimester 

19 μg/m3

: 1.0 (0.9, 1.2) 

Third trimester 

20 μg/m3

: 1.1 (0.9, 1.3) 

Outcome: LBW 

Single-pollutant model 

Entire pregnancy 

18 μg/m3

: 1.3 (0.8, 2.2) 

First trimester 

20 μg/m3

: 1.0 (0.7, 1.5) 

Second trimester 

19 μg/m3: 1.2 (0.8, 1.7) 

Third trimester 

20 μg/m3

: 1.3 (0.9, 1.9) 

Notes: Numbers reported for birth weight 

outcome are the effects on birth weight 

outcome (the change in birth weight in 

grams) across the IQR (which vary 

depending on air pollutant and duration of 

exposure measurement). 

Reference: (Sokol et al., 2006, 098539) 

Period of Study: Jan 1996-Dec 1998 

Location: Los Angeles, California 

Outcome: Semen Quality 

Study Design: Panel 

Statistical Analysis: Univariate and 

Multivariate Regression 

Statistical Package: SAS 

Age Groups: Males ranging 19-35 in 

age 

Pollutant: PM10

Averaging Time: 0-9d, 10-14d and 70-

90d 

Mean (SD) Unit: 35.74 ± 13.83 μg/m3

Copollutant (correlation): 

O3, NO2, CO 

PM10 specific results are given in Fig 3-. 

PM10 was not significantly correlated with 

sperm quality. 

Reference: (Suh et al., 2007, 157028) 

Period of Study: 2001-2004

Location: Seoul, Korea 

Outcome: Birth weight

Age Groups: Prenatal follow-up for 

newborns 

Study Design: based prospective 

cohort study

N: 199 pregnant mothers 

Statistical Analyses: ANCOVA, 

generalized linear models 

Covariates: infant’s sex, maternal age, 

maternal and paternal education, parity, 

presence of illness during pregnancy, 

delivery month, gestational age 

(squared) 

Dose-response Investigated? Yes

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24-h

Mean (SD): 1st trimester: 76.41 (28.80) 

2nd trimester: 77.84 (31.63) 

3rd trimester: 95.61 (26.15) 

Percentiles: 1st trimester 

25th: 55.28 

50th(Median): 71.09 

75th: 92.38 

2nd trimester 

25th: 48.65 

50th(Median): 72.36 

75th: 108.00 

3rd trimester 

25th: 77.10 

50th(Median): 96.35 

75th: 116.68 

Range (Min, Max): 

1st trimester (21.00, 151.65) 

2nd trimester (31.45, 139.13) 

PM Increment: Trimester ≥ 90th 

percentile compared to <90thpercentile 

Least-square (ANCOVA) mean (SE) 

All Genotypes 

1st trimester 

<90th , N(%): 

158 (90.3%): 3253 (37) 

≥ 90th percentile, N(%): 17 (9.7%): 2841 

(145) 

P-Value for mean birth weight for ≥ 90th 

percentile PM10 vs. for <90th percentile 

PM10

Adjusted: 0.009 

Adjusted, with CO: 0.041 

Adjusted, with NO2: 0.092 

Adjusted, with SO2: 0.012 

2nd trimester 

<90th percentile, N(%): 

153 (89.5%): 3253 (39) 

≥ 90th percentile, N(%): 

18 (10.5%): 3026 (157) 

P-Value for mean birth weight for ≥ 90th 

December 2009 E-463 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

3rd trimester (23.45, 172.75) 

Monitoring Stations: 27 

Copollutant: 

CO 

SO

2

NO

2

percentile PM10 vs. for <90th percentile 

PM10

Adjusted: 0.177 

Adjusted, with CO: 0.203 

Adjusted, with NO

2: 0.151 

Adjusted, with SO

2: 0.151 

3rd trimester 

<90th percentile, N(%): 

162 (90.5%): 3226 (38) ≥ 90th percentile, N(%): 17 (9.5%): 3122 

(140) 

P-Value for mean birth weight for ≥ 90th 

percentile PM10 vs. for <90th percentile 

PM10

Adjusted: 0.487 

Adjusted, with CO: 0.748 

Adjusted, with NO

2: 0.420 

Adjusted, with SO

2: 0.466 

Genotype MspI TT 

1st trimester 

<90th percentile, N(%): 60 (34.3%): 3350 

(64) ≥ 90th percentile, N(%): 5 (2.9%): 3001 

(229) 

P-Value for mean birth weight for ≥ 90th 

percentile PM10 vs. for <90th percentile 

PM10

Adjusted: 0.147 

Adjusted, with CO: 0.186 

Adjusted, with NO

2: 0.430 

Adjusted, with SO

2: 0.155 

2nd trimester 

<90th percentile, N(%): 59 (34.5%): 3335 

(66) ≥ 90th percentile, N(%): 6 (3.5%): 3281 

(249) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.833 

Adjusted, with CO: 0.833 

Adjusted, with NO

2: 0.778 

Adjusted, with SO

2: 0.806 

3rd trimester 

<90th percentile, N(%): 61 (34.1%): 3327 

(65) ≥ 90th percentile, N(%): 6 (3.4%): 3227 

(300) 

p-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.749 

Adjusted, with CO: 0.980 

Adjusted, with NO

2: 0.635 

Adjusted, with SO

2: 0.687 

Genotype MspI TC/CC 

1st trimester 

<90th percentile, N(%): 98 (56.0%): 3193 

(48) ≥ 90th percentile, N(%): 12 (6.9%): 2799 

(169) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.033 

Adjusted, with CO: 0.073 

Adjusted, with NO

2: 0.150 

Adjusted, with SO

2: 0.036 

2nd trimester 

<90th percentile, N(%): 94 (55.0%): 3200 

(52) ≥ 90th percentile, N(%): 12 (7.0%): 2933 

(176) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.161 

Adjusted, with CO: 0.172 

December 2009 E-464 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Adjusted, with NO

2: 0.152 

Adjusted, with SO

2: 0.158 

3rd trimester 

<90th percentile, N(%): 101 (56.4%): 3165 

(49) ≥ 90th percentile, N(%): 11 (6.2%): 3087 

(147) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.626 

Adjusted, with CO: 0.978 

Adjusted, with NO

2: 0.551 

Adjusted, with SO

2: 0.614 

Genotype NcoI IleIle 

1st trimester 

<90th percentile, N(%): 87 (49.7%): 3244 

(52) ≥ 90th percentile, N(%): 7 (4.0%): 2983 

(232) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.289 

Adjusted, with CO: 0.344 

Adjusted, with NO

2: 0.641 

Adjusted, with SO

2: 0.293 

2nd trimester 

<90th percentile, N(%): 82 (48.0%): 3243 

(55) ≥ 90th percentile, N(%): 11 (6.4%): 3185 

(207) 

p-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.790 

Adjusted, with CO: 0.783 

Adjusted, with NO

2: 0.707 

Adjusted, with SO

2: 0.733 

3rd trimester 

<90th percentile, N(%): 90 (50.3%): 3239 

(53) ≥ 90th percentile, N(%): 9 (5.0%): 2944 

(198) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.161 

Adjusted, with CO: 0.279 

Adjusted, with NO

2: 0.134 

Adjusted, with SO

2: 0.150 

Genotype NcoI IleVal/ValVal 

1st trimester 

<90th percentile, N(%): 71 (40.6%): 3262 

(56) ≥ 90th percentile, N(%): 10 (5.7%): 2773 

(171) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.009 

Adjusted, with CO: 0.031 

Adjusted, with NO

2: 0.058 

Adjusted, with SO

2: 0.010 

2nd trimester 

<90th percentile, N(%): 71 (41.5%): 3264 

(61) ≥ 90th percentile, N(%): 7 (4.1%): 2862 

(208) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.076 

Adjusted, with CO: 0.093 

Adjusted, with NO

2: 0.063 

Adjusted, with SO

2: 0.061 

3rd trimester 

<90th percentile, N(%): 72 (40.2%): 3207 

December 2009 E-465 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

(58) 

≥ 90th percentile, N(%): 8 (4.5%): 3262 

(180) 

P-Value for mean birth weight for 

≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.777 

Adjusted, with CO: 0.607 

Adjusted, with NO2: 0.843 

Adjusted, with SO2: 0.791 

Reference: Tsai et al. (2006, 090709) 

Period of Study: 1994-2000 

Location: Kaohsiung, Taiwan 

Outcome: Post neonatal mortality 

Age Groups: Infants more than 27 

days and less than 1 yr

Study Design: Case-crossover study

N: 207 deaths

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, humidity

Dose-response Investigated? No 

Statistical Package: SAS, version 8.2 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 81.45 μg/m3

Percentiles: 25th: 44.50

50th(Median): 79.20

75th: 111.50 

Range (Min, Max): (20.50-232.00)

Monitoring Stations: 6

Copollutant: 

SO2

NO2

CO 

O3

PM Increment: 67.00 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

OR = 1.040 (0.340-3.177) 

Note: Air pollution levels at the dates of 

infant death were compared with air 

pollution levels 1 week before and 1 week 

after death 

A cumulative lag up to 2 previous days 

was used to assign exposure.

Reference: Wilhelm and Ritz (2005, 

088668) 

Period of Study: 1994-2000 

Location: Los Angeles County, 

California, U.S. 

Outcome: Term low birth weight (LBW) 

(<2500 g at ≥ 37 completed wk 

gestation), Vaginal birth <37 completed 

wk gestation 

Age Groups: LBW: ≥ 37 completed wk 

Preterm births: <37 completed wk 

Study Design: Cross-sectional

N: For LBW: 136,134 

For preterm birth: 

106,483 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, maternal 

race, maternal education, parity, interval 

since previous live birth, level of 

prenatal care, infant sex, previous LBW 

or preterm infant, birth season, other 

pollutants (CO, NO2, O3, PM10), 

gestational age (in birth weight analysis)

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: 

24 h (every 6 days) 

Entire pregnancy 

Trimesters of pregnancy 

Months of pregnancy 

6 wk before birth 

Mean (SD): 

First trimester: 42.2 

Third trimester: 41.5 

6 wk before birth: 39.1 

Range (Min, Max): 

First trimester: 26.3, 77.4 

Third trimester: 25.7, 74.6 

6 wk before birth: 13.0, 103.7 

Monitoring Stations: 

Zip-code-level analysis: 8 

Address-level analysis: 6 

Copollutant (correlation): 

First trimester: 

PM10-CO: r = 0.12 

PM10-NO2: r = 0.29 

PM10-O3: r = -0.01 

PM10-PM2.5: r = 0.43 

Third trimester: 

PM10-CO: r = 0.32 

PM10-NO2: r = 0.45 

PM10-O3: r = -0.08 

PM10-PM2.5: r = 0.52 

6 wk before birth: 

PM10-CO: r = 0.36 

PM10-NO2: r = 0.49 

PM10-O3: r = -0.16 

PM10-PM2.5: r = 0.60 

PM Increment: 

1) 10 μg/m3

2) 3 levels: 

a) <25 percentile (reference) 

b) 25%-75 percentile 

c) ≥ 75 percentile 

Incidence of LBW (third trimester 

exposure) 

<32.8 μg/m3: 2.0 (1.8, 2.2) 

32.8 to <43.4 μg/m3

: 2.0 (1.9, 2.1) 

≥ 43.4 μg/m3

: 2.2 (2.0, 2.4) 

Incidence of preterm birth (first 

trimester exposure) 

<32.9 μg/m3: 8.7 (8.3, 9.2) 

32.9 to <43.9 μg/m3

: 8.8 (8.5, 9.1) 

≥ 43.9 μg/m3

: 8.6 (8.1, 9.0) 

Incidence of preterm birth (6 wk before 

birth exposure) 

<31.8 μg/m3: 8.8 (8.4, 9.3) 

31.8 to <44.1 μg/m3

: 8.6 (8.3, 8.9) 

≥ 44.1 μg/m3

: 8.8 (8.4, 9.2) 

Outcome: LBW 

Exposure Period: Third trimester 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3

: 1.22 (1.05, 1.41) 

33.4 to <44.7 μg/m3

: 1.08 (0.76, 1.52) 

≥ 44.7 μg/m3

: 1.48 (1.00, 2.19) 

Multipollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3

: 1.36 (1.12, 1.65) 

33.4 to <44.7 μg/m3

: 1.16 (0.77, 1.74) 

≥ 44.7 μg/m3

: 1.58 (0.95, 2.62) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 0.98 (0.90, 1.06) 

33.4 to <44.7 μg/m3

: 0.95 (0.80, 1.13) 

≥ 44.7 μg/m3

: 0.96 (0.78, 1.18) 

Multipollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.02 (0.92, 1.14) 

33.4 to <44.7 μg/m3

: 0.93 (0.77, 1.12) 

≥ 44.7 μg/m3

: 1.02 (0.79, 1.32) 

Single-pollutant model: 

December 2009 E-466 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

2 <distance ≤ 4 mile 

Per 10 μg/m

3

: 1.03 (0.99, 1.08) 

33.9 to <45.0 μg/m

3

: 1.04 (0.96, 1.14) 

≥ 45.0 μg/m

3

: 1.08 (0.97, 1.20) 

Multipollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m

3

: 1.04 (0.98, 1.09) 

33.9 to <45.0 μg/m

3

: 1.02 (0.92, 1.12) 

≥ 45.0 μg/m

3

: 1.06 (0.93, 1.21) 

Zip-code-level analysis 

Single-pollutant model: 

Per 10 μg/m

3

: 1.03 (0.97, 1.09) 

33.2 to <43.6 μg/m

3

: 0.98 (0.86, 1.11) 

≥ 43.6 μg/m

3

: 1.03 (0.88, 1.21) 

Multipollutant model: 

Per 10 μg/m

3

: 1.07 (0.99, 1.15) 

33.2 to <43.6 μg/m

3

: 0.97 (0.85, 1.12) 

≥ 43.6 μg/m

3

: 1.09 (0.90, 1.31) 

Outcome: LBW 

Exposure Period: Entire pregnancy 

period 

Address-level analysis: 

Multipollutant model: 

Per 10 μg/m

3

: 1.24 (0.91, 1.70) 

Outcome: Preterm Birth 

Exposure Period: First trimester of 

pregnancy 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.00 (0.93, 1.09) 

33.3 to <45.1 μg/m

3

: 1.07 (0.90, 1.26) 

≥ 45.1 μg/m

3

: 1.12 (0.91, 1.38) 

Multipollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.00 (0.90, 1.12) 

33.3 to <45.1 μg/m

3

: 1.12 (0.92, 1.36) 

≥ 45.1 μg/m

3

: 1.17 (0.90, 1.50) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m

3

: 1.01 (0.97, 1.05) 

33.7 to <45.3 μg/m

3

: 1.03 (0.95, 1.12) 

≥ 45.3 μg/m

3

: 1.07 (0.97, 1.19) 

Multipollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m

3

: 1.04 (0.99, 1.10) 

33.7 to <45.3 μg/m

3

: 1.07 (0.98, 1.17) 

≥ 45.3 μg/m

3

: 1.13 (1.00, 1.27) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m

3

: 1.01 (0.99, 1.03) 

34.1 to <45.5 μg/m

3

: 1.03 (0.99, 1.08) 

≥ 45.5 μg/m

3

: 1.02 (0.96, 1.07) 

Multipollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m

3

: 0.99 (0.97, 1.02) 

34.1 to <45.5 μg/m

3

: 0.99 (0.95, 1.04) 

≥ 45.5 μg/m

3

: 0.94 (0.89, 1.01) 

Zip-code-level analysis 

Single-pollutant model: 

Per 10 μg/m

3

: 0.99 (0.96, 1.01) 

33.3 to <44.2 μg/m

3

: 1.01 (0.95, 1.08) 

≥ 44.2 μg/m

3

: 0.98 (0.90, 1.05) 

Multipollutant model: 

Per 10 μg/m

3

: 0.99 (0.96, 1.03) 

33.3 to <44.2 μg/m

3

: 1.03 (0.97, 1.11) 

≥ 44.2 μg/m

3

: 1.01 (0.92, 1.11) 

Outcome: Preterm birth 

Exposure Period: 6 wk before birth 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.02 (0.95, 1.10) 

December 2009 E-467 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

32.5 to <44.8 μg/m3: 1.09 (0.92, 1.29) 

≥ 44.8 μg/m3

: 1.12 (0.92, 1.37) 

Multipollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3

: 1.06 (0.97, 1.16) 

32.5 to <44.8 μg/m3

: 1.09 (0.90, 1.31) 

≥ 44.8 μg/m3

: 1.17 (0.91, 1.49) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.00 (0.96, 1.03) 

32.3 to <45.3 μg/m3

: 0.99 (0.91, 1.07) 

≥ 45.3 μg/m3: 0.99 (0.89, 1.10) 

Multipollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.01 (0.97, 1.06) 

32.3 to <45.3 μg/m3

: 1.00 (0.92, 1.10) 

≥ 45.3 μg/m3

: 1.02 (0.91, 1.16) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 0.99 (0.98, 1.01) 

33.1 to <45.3 μg/m3

: 1.00 (0.96, 1.05) 

≥ 45.3 μg/m3

: 0.98 (0.93, 1.03) 

Multipollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 1.00 (0.98, 1.02) 

33.1 to <45.3 μg/m3

: 1.01 (0.96, 1.05) 

≥ 45.3 μg/m3: 0.98 (0.92, 1.04) 

Zip-code-level analysis 

Single-pollutant model: 

Per 10 μg/m3

: 1.02 (0.99, 1.04) 

32.1 to <44.3 μg/m3

: 1.01 (0.95, 1.07) 

≥ 44.3 μg/m3: 1.04 (0.96, 1.12) 

Multipollutant model: 

Per 10 μg/m3

: 1.02 (0.99, 1.06) 

32.1 to <44.3 μg/m3: 1.02 (0.95, 1.09) 

≥ 44.3 μg/m3

: 1.04 (0.95, 1.14) 

Notes: multipollutant model adds CO,NO2, 

and O3 in addition to the main pollutant of 

interest, PM10. 

Reference: Woodruff et al. (1997, 

084271) 

Period of Study: 1989-1991 

Location: 86 Metropolitan Statistical 

Areas in the U.S. (counties with 

populations less than 100,000 were 

excluded) 

Outcome: Postneonatal mortality 

(death of an infant between 1 month 

and 1 yr of age) 

1) All post neonatal deaths 

2) Normal birth weight (NBW, ≥ 2500 g) 

SIDS deaths 

3) NBW respiratory deaths 

4) Low birth weight (LBW) respiratory 

death 

Respiratory deaths: ICD9 codes 460-

519 

SIDS: ICD9 code 798.0 

Age Groups: Infants (1 month-1yr of 

age) 

Study Design: Cross-sectional

N: 3,788,079 infants 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal education, 

maternal race, parental marital status, 

maternal smoking during pregnancy 

Avg temperature during the first 2 mo of 

life 

Infant’s month and yr of birth 

Assessed race as an effect modifier (pval for interaction terms >0.2) 

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: Mean of 1st 2 mo of 

life 

analyzed as tertiles of exposure and as 

continuous exposure 

Mean (SD): 31.4 (7.8) 

Range (Min, Max): 

Overall: 11.9-68.8 

Low category: <28.0 

Medium category: 28.1-40.0 

High category: >40.0 

Monitoring Stations: NR 

PM Increment: 10 μg/m3 (for continuous 

exposure analysis)

Adjusted ORs for cause-specific post 

neonatal mortality by pollution 

category (tertiles) 

All causes 

Low: Ref 

Medium: 1.05 (1.01, 1.09) 

High: 1.10 (1.04, 1.16) 

SIDS, NBW: 

Low: Ref 

Medium: 1.09 (1.01, 1.17) 

High: 1.26 (1.14, 1.39) 

Respiratory death, NBW: 

Low: Ref 

Medium: 1.08 (0.87, 1.33) 

High: 1.40 (1.05, 1.85) 

Respiratory death, LBW: 

Low: Ref 

Medium: 0.93 (0.73, 1.18) 

High: 1.18 (0.86, 1.61) 

All other causes: 

Low: Ref 

Medium: 1.03 (0.97, 1.08) 

High: 0.97 (0.90, 1.04) 

Adjusted ORs for a continuous 

10 μg/m3

 change in exposure 

All causes: 1.04 (1.02, 1.07) 

SIDS, NBW: 1.12 (1.07, 1.17) 

Respiratory death 

NBW: 1.20 (1.06, 1.36) 

Respiratory death 

LBW: 1.05 (0.91, 1.22) 

All other causes: 1.00 (0.99, 1.00) 

December 2009 E-468 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Woodruff et al. (2008, 

098386) 

Period of Study: 1999-2002 

Location: U.S. counties with >250,000 

residents (96 counties) 

Outcome: Postneonatal deaths 

Respiratory mortality (ICD10: J000-99, 

plus bronchopulmonary dysplasia [BPD] 

P27.1) 

SIDS (ICD10: R95) 

Ill-defined causes (R99); 

All other deaths evaluated as a control 

category 

Age Groups: Infants aged >28 days 

and <1 yr 

Study Design: Cross-sectional

N: 3,583,495 births (6,639 post 

neonatal deaths) 

Statistical Analyses: Logistic GEE 

(exchangeable correlation structure) 

Covariates: Maternal race/ethnicity, 

marital status, age, education, 

primiparity, county-level poverty and per 

capita income levels, yr and month of 

birth dummy variables to account for 

time trend and seasonal effects, and 

region of the country 

Sensitivity analyses performed among 

only those mothers with smoking 

information (adjustment for smoking 

had no effect on the estimates) 

Season: Adjusted for yr and month of 

birth dummy variables to account for 

time trend and seasonal effects 

Dose-response Investigated? 

Evaluated the appropriateness of a 

linear form from analysis based on 

quartiles of exposure and concluded 

that linear form was appropriate (data 

not shown) 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: Measured 

continuously for 24 h once every 6 days

exposure assigned by calculating avg 

concentration of pollutant during first 2 

mo of life 

Median and IQR (25th-75th 

percentile): Survivors: 28.9 (23.3-34.4) 

All causes of death: 29.1 (23.9-34.5) 

Respiratory: 29.8 (24.3-36.5) 

SIDS: 28.6 (23.5-33.8) 

SIDS + ill-defined: 28.8 (23.9-33.9) 

Other causes: 29.2 (23.9-34.5) 

Percentiles: see above 

PM Component: Not assessed, but 

controlled for region of the country to 

account for PM composition variation 

Monitoring Stations: NR 

Copollutant (correlation): 

PM10 

PM2.5 (r = 0.34) 

CO (r = 0.18) 

SO2 (r = 0.00) 

O3 (r = 0.20) 

Notes: Monthly avg calculated if there 

were at least 3 available measures for 

PM 

Assigned exposures using the avg 

concentration of the county of residence

PM Increment: IQR (11 μg/m3) 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted ORs for single pollutant models 

All causes: 1.04 (0.99, 1.10) 

Respiratory: 1.18 (1.06, 1.31) 

SIDS: 1.02 (0.89, 1.16) 

Ill-defined + SIDS: 1.06 (0.97, 1.16) 

Other causes: 1.02 (0.96, 1.07) 

Adjusted ORs for multipollutant models 

(including CO, O3, SO2) 

Respiratory: 1.16 (1.04, 1.30) 

SIDS: 1.02 (0.90, 1.16) 

OR for deaths coded as BPD per increase 

in IQR: 1.19 (0.85, 1.65) 

OR for respiratory post neonatal death 

stratified by birth weight 

NBW only: 1.19 (1.05, 1.36) 

LBW only: 1.12 (0.95, 1.31) 

OR for respiratory deaths removing region 

of U.S. as a confounding variable: 1.30 

(1.04, 1.61) 

OR for respiratory deaths assessing 

exposure as quartiles 

Highest vs. Lowest quartile: 

1.31 (1.00, 1.71) 

OR for respiratory deaths among only 

those deaths that occurred during the first 

90 days (most closely matched exposure 

metric of the avg over the first 2 mo of 

life): 1.25 (1.06, 1.47) 

Reference: (Suh et al., 2007, 157028) 

Period of Study: 2001-2004

Location: Seoul, Korea 

Outcome: Birth weight

Age Groups: Prenatal follow-up for 

newborns 

Study Design: Based prospective 

cohort study

N: 199 pregnant mothers 

Statistical Analyses: ANCOVA, 

generalized linear models 

Covariates: Infant’s sex, maternal age, 

maternal and paternal education, parity, 

presence of illness during pregnancy, 

delivery month, gestational age 

(squared) 

Dose-response Investigated? Yes

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: 24-h

Mean (SD): 

1st trimester: 76.41 (28.80) 

2nd trimester: 77.84 (31.63) 

3rd trimester: 95.61 (26.15) 

Percentiles: 

1st trimester 

25th: 55.28 

50th(Median): 71.09 

75th: 92.38 

2nd trimester 

25th: 48.65 

50th(Median): 72.36 

75th: 108.00 

3rd trimester 

25th: 77.10 

50th(Median): 96.35 

75th: 116.68 

Range (Min, Max): 

1st trimester (21.00, 151.65) 

2nd trimester (31.45, 139.13) 

3rd trimester (23.45, 172.75) 

Monitoring Stations: 27 

Copollutant: 

CO 

SO2

PM Increment: Trimester ≥ 90th 

percentile compared to <90th percentile 

Least-square (ANCOVA) mean (SE) 

All Genotypes 

1st trimester 

<90th percentile, N(%): 

158 (90.3%): 3253 (37) 

≥ 90th percentile, N(%): 17 (9.7%): 2841 

(145) 

P-Value for mean birth weight for 

≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.009 

Adjusted, with CO: 0.041 

Adjusted, with NO2: 0.092 

Adjusted, with SO2: 0.012 

2nd trimester 

<90th percentile, N(%): 

153 (89.5%): 3253 (39) 

≥ 90th percentile, N(%): 

18 (10.5%): 3026 (157) 

p-Value for mean birth weight for 

≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.177 

Adjusted, with CO: 0.203 

Adjusted, with NO2: 0.151 

Adjusted, with SO2: 0.151 

3rd trimester 

<90th percentile, N(%): 

December 2009 E-469 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

NO

2 162 (90.5%): 3226 (38) ≥ 90th percentile, N(%): 17 (9.5%): 3122 

(140) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.487 

Adjusted, with CO: 0.748 

Adjusted, with NO

2: 0.420 

Adjusted, with SO

2: 0.466 

Genotype MspI TT 

1st trimester 

<90th percentile, N(%): 60 (34.3%): 3350 

(64) ≥ 90th percentile, N(%): 5 (2.9%): 3001 

(229) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.147 

Adjusted, with CO: 0.186 

Adjusted, with NO

2: 0.430 

Adjusted, with SO

2: 0.155 

2nd trimester 

<90th percentile, N(%): 59 (34.5%): 3335 

(66) ≥ 90th percentile, N(%): 6 (3.5%): 3281 

(249) 

p-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.833 

Adjusted, with CO: 0.833 

Adjusted, with NO

2: 0.778 

Adjusted, with SO

2: 0.806 

3rd trimester 

<90th percentile, N(%): 61 (34.1%): 3327 

(65) ≥ 90th percentile, N(%): 6 (3.4%): 3227 

(300) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.749 

Adjusted, with CO: 0.980 

Adjusted, with NO

2: 0.635 

Adjusted, with SO

2: 0.687 

Genotype MspI TC/CC 

1st trimester 

<90th percentile, N(%): 98 (56.0%): 3193 

(48) ≥ 90th percentile, N(%): 12 (6.9%): 2799 

(169) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.033 

Adjusted, with CO: 0.073 

Adjusted, with NO

2: 0.150 

Adjusted, with SO

2: 0.036 

2nd trimester 

<90th percentile, N(%): 94 (55.0%): 3200 

(52) ≥ 90th percentile, N(%): 12 (7.0%): 2933 

(176) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.161 

Adjusted, with CO: 0.172 

Adjusted, with NO

2: 0.152 

Adjusted, with SO

2: 0.158 

3rd trimester 

<90th percentile, N(%): 

101 (56.4%): 3165 (49) ≥ 90th percentile, N(%): 11 (6.2%): 3087 

(147) 

P-Value for mean birth weight for 

December 2009 E-470 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.626 

Adjusted, with CO: 0.978 

Adjusted, with NO

2: 0.551 

Adjusted, with SO

2: 0.614 

Genotype NcoI IleIle 

1st trimester 

<90th percentile, N(%): 87 (49.7%): 3244 

(52) ≥ 90th percentile, N(%): 7 (4.0%): 2983 

(232) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.289 

Adjusted, with CO: 0.344 

Adjusted, with NO

2: 0.641 

Adjusted, with SO

2: 0.293 

2nd trimester 

<90th percentile, N(%): 82 (48.0%): 3243 

(55) ≥ 90th percentile, N(%): 11 (6.4%): 3185 

(207) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.790 

Adjusted, with CO: 0.783 

Adjusted, with NO

2: 0.707 

Adjusted, with SO

2: 0.733 

3rd trimester 

<90th percentile, N(%): 90 (50.3%): 3239 

(53) ≥ 90th percentile, N(%): 9 (5.0%): 2944 

(198) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.161 

Adjusted, with CO: 0.279 

Adjusted, with NO

2: 0.134 

Adjusted, with SO

2: 0.150 

Genotype NcoI IleVal/ValVal 

1st trimester 

<90th percentile, N(%): 71 (40.6%): 3262 

(56) ≥ 90th percentile, N(%): 10 (5.7%): 2773 

(171) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.009 

Adjusted, with CO: 0.031 

Adjusted, with NO

2: 0.058 

Adjusted, with SO

2: 0.010 

2nd trimester 

<90th percentile, N(%): 71 (41.5%): 3264 

(61) ≥ 90th percentile, N(%): 7 (4.1%): 2862 

(208) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.076 

Adjusted, with CO: 0.093 

Adjusted, with NO

2: 0.063 

Adjusted, with SO

2: 0.061 

3rd trimester 

<90th percentile, N(%): 72 (40.2%): 3207 

(58) ≥ 90th percentile, N(%): 8 (4.5%): 3262 

(180) 

P-Value for mean birth weight for ≥ 90th percentile PM10 vs. for <90th 

percentile PM10

Adjusted: 0.777 

Adjusted, with CO: 0.607 

December 2009 E-471 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Adjusted, with NO2: 0.843 

Adjusted, with SO2: 0.791 

Reference: Tsai et al. (2006, 098312)

Period of Study: 1994-2000 

Location: Kaohsiung, Taiwan 

Outcome: Post neonatal mortality 

Age Groups: Infants more than 27 

days and less than 1 yr

Study Design: Case-crossover study

N: 207 deaths

Statistical Analyses: Conditional 

logistic regression 

Covariates: Temperature, humidity

Dose-response Investigated? No 

Statistical Package: SAS, version 8.2 

Pollutant: PM10

Averaging Time: 24 h

Mean (SD): 81.45 μg/m3

Percentiles: 25th: 44.50

50th(Median): 79.20

75th: 111.50 

Range (Min, Max): (20.50-232.00)

Monitoring Stations: 6

Copollutant: 

SO2

NO2

CO 

O3

PM Increment: 67.00 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

OR = 1.040 (0.340-3.177) 

Note: Air pollution levels at the dates of 

infant death were compared with air 

pollution levels 1 week before and 1 week 

after death 

A cumulative lag up to 2 previous days 

was used to assign exposure.

Reference: Wilhelm and Ritz (2005, 

088668) 

Period of Study: 1994-2000 

Location: Los Angeles County, 

California, U.S. 

Outcome: Term low birth weight (LBW) 

(<2500 g at ≥ 37 completed wk 

gestation), Vaginal birth <37 completed 

wk gestation 

Age Groups: LBW: ≥ 37 completed wk 

Preterm births: <37 completed wk 

Study Design: Cross-sectional

N: For LBW: 136,134 

For preterm birth: 

106,483 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, maternal 

race, maternal education, parity, interval 

since previous live birth, level of 

prenatal care, infant sex, previous LBW 

or preterm infant, birth season, other 

pollutants (CO, NO2, O3, PM10), 

gestational age (in birth weight analysis)

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: 

24 h (every 6 days) 

Entire pregnancy 

Trimesters of pregnancy 

Months of pregnancy 

6 wk before birth 

Mean (SD): First trimester: 42.2 

Third trimester: 41.5 

6 wk before birth: 39.1 

Range (Min, Max): 

First trimester: 26.3, 77.4 

Third trimester: 25.7, 74.6 

6 wk before birth: 13.0, 103.7 

Monitoring Stations: 

Zip-code-level analysis: 8 

Address-level analysis: 6 

Copollutant (correlation): 

First trimester: PM10-CO: r = 0.12 

PM10-NO2: r = 0.29 

PM10-O3: r = -0.01 

PM10-PM2.5: r = 0.43 

Third trimester: PM10-CO: r = 0.32 

PM10-NO2: r = 0.45 

PM10-O3: r = -0.08 

PM10-PM2.5: r = 0.52 

6 wk before birth: 

PM10-CO: r = 0.36 

PM10-NO2: r = 0.49 

PM10-O3: r = -0.16 

PM10-PM2.5: r = 0.60 

PM Increment: 

1) 10 μg/m3

2) 3 levels: 

a) <25 percentile (reference) 

b) 25%-75 percentile 

c) ≥ 75 percentile 

Incidence of LBW (third trimester 

exposure) 

<32.8 μg/m3: 2.0 (1.8, 2.2) 

32.8 to <43.4 μg/m3

: 2.0 (1.9, 2.1) 

≥ 43.4 μg/m3

: 2.2 (2.0, 2.4) 

Incidence of preterm birth (first 

trimester exposure) 

<32.9 μg/m3: 8.7 (8.3, 9.2) 

32.9 to <43.9 μg/m3: 8.8 (8.5, 9.1) 

≥ 43.9 μg/m3

: 8.6 (8.1, 9.0) 

Incidence of preterm birth (6 wk before 

birth exposure) 

<31.8 μg/m3: 8.8 (8.4, 9.3) 

31.8 to <44.1 μg/m3

: 8.6 (8.3, 8.9) 

≥ 44.1 μg/m3: 8.8 (8.4, 9.2) 

Outcome: LBW 

Exposure Period: Third trimester 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3: 1.22 (1.05, 1.41) 

33.4 to <44.7 μg/m3

: 1.08 (0.76, 1.52) 

≥ 44.7 μg/m3

: 1.48 (1.00, 2.19) 

Multipollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3

: 1.36 (1.12, 1.65) 

33.4 to <44.7 μg/m3

: 1.16 (0.77, 1.74) 

≥ 44.7 μg/m3

: 1.58 (0.95, 2.62) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 0.98 (0.90, 1.06) 

33.4 to <44.7 μg/m3

: 0.95 (0.80, 1.13) 

≥ 44.7 μg/m3

: 0.96 (0.78, 1.18) 

Multipollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.02 (0.92, 1.14) 

33.4 to <44.7 μg/m3

: 0.93 (0.77, 1.12) 

≥ 44.7 μg/m3

: 1.02 (0.79, 1.32) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 1.03 (0.99, 1.08) 

33.9 to <45.0 μg/m3: 1.04 (0.96, 1.14) 

≥ 45.0 μg/m3

: 1.08 (0.97, 1.20) 

Multipollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 1.04 (0.98, 1.09) 

33.9 to <45.0 μg/m3

: 1.02 (0.92, 1.12) 

≥ 45.0 μg/m3

: 1.06 (0.93, 1.21) 

Zip-code-level analysis 

Single-pollutant model: 

December 2009 E-472 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

Per 10 μg/m

3

: 1.03 (0.97, 1.09) 

33.2 to <43.6 μg/m

3

: 0.98 (0.86, 1.11) 

≥ 43.6 μg/m

3

: 1.03 (0.88, 1.21) 

Multipollutant model: 

Per 10 μg/m

3

: 1.07 (0.99, 1.15) 

33.2 to <43.6 μg/m

3

: 0.97 (0.85, 1.12) 

≥ 43.6 μg/m

3

: 1.09 (0.90, 1.31) 

Outcome: LBW 

Exposure Period: Entire pregnancy 

period 

Address-level analysis: 

Multipollutant model: 

Per 10 μg/m

3

: 1.24 (0.91, 1.70) 

Outcome: Preterm Birth 

Exposure Period: First trimester of 

pregnancy 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.00 (0.93, 1.09) 

33.3 to <45.1 μg/m

3

: 1.07 (0.90, 1.26) 

≥ 45.1 μg/m

3

: 1.12 (0.91, 1.38) 

Multipollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.00 (0.90, 1.12) 

33.3 to <45.1 μg/m

3

: 1.12 (0.92, 1.36) 

≥ 45.1 μg/m

3

: 1.17 (0.90, 1.50) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m

3

: 1.01 (0.97, 1.05) 

33.7 to <45.3 μg/m

3

: 1.03 (0.95, 1.12) 

≥ 45.3 μg/m

3

: 1.07 (0.97, 1.19) 

Multipollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m

3

: 1.04 (0.99, 1.10) 

33.7 to <45.3 μg/m

3

: 1.07 (0.98, 1.17) 

≥ 45.3 μg/m

3

: 1.13 (1.00, 1.27) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m

3

: 1.01 (0.99, 1.03) 

34.1 to <45.5 μg/m

3

: 1.03 (0.99, 1.08) 

≥ 45.5 μg/m

3

: 1.02 (0.96, 1.07) 

Multipollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m

3

: 0.99 (0.97, 1.02) 

34.1 to <45.5 μg/m

3

: 0.99 (0.95, 1.04) 

≥ 45.5 μg/m

3

: 0.94 (0.89, 1.01) 

Zip-code-level analysis 

Single-pollutant model: 

Per 10 μg/m

3

: 0.99 (0.96, 1.01) 

33.3 to <44.2 μg/m

3

: 1.01 (0.95, 1.08) 

≥ 44.2 μg/m

3

: 0.98 (0.90, 1.05) 

Multipollutant model: 

Per 10 μg/m

3

: 0.99 (0.96, 1.03) 

33.3 to <44.2 μg/m

3

: 1.03 (0.97, 1.11) 

≥ 44.2 μg/m

3

: 1.01 (0.92, 1.11) 

Outcome: Preterm birth 

Exposure Period: 6 wk before birth 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.02 (0.95, 1.10) 

32.5 to <44.8 μg/m

3

: 1.09 (0.92, 1.29) 

≥ 44.8 μg/m

3

: 1.12 (0.92, 1.37) 

Multipollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m

3

: 1.06 (0.97, 1.16) 

32.5 to <44.8 μg/m

3

: 1.09 (0.90, 1.31) 

≥ 44.8 μg/m

3

: 1.17 (0.91, 1.49) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m

3

: 1.00 (0.96, 1.03) 

32.3 to <45.3 μg/m

3

: 0.99 (0.91, 1.07) 

≥ 45.3 μg/m

3

: 0.99 (0.89, 1.10) 

Multipollutant model: 

December 2009 E-473 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.01 (0.97, 1.06) 

32.3 to <45.3 μg/m3: 1.00 (0.92, 1.10) 

≥ 45.3 μg/m3

: 1.02 (0.91, 1.16) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 0.99 (0.98, 1.01) 

33.1 to <45.3 μg/m3

: 1.00 (0.96, 1.05) 

≥ 45.3 μg/m3: 0.98 (0.93, 1.03) 

Multipollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 1.00 (0.98, 1.02) 

33.1 to <45.3 μg/m3

: 1.01 (0.96, 1.05) 

≥ 45.3 μg/m3

: 0.98 (0.92, 1.04) 

Zip-code-level analysis 

Single-pollutant model: 

Per 10 μg/m3: 1.02 (0.99, 1.04) 

32.1 to <44.3 μg/m3

: 1.01 (0.95, 1.07) 

≥ 44.3 μg/m3

: 1.04 (0.96, 1.12) 

Multipollutant model: 

Per 10 μg/m3: 1.02 (0.99, 1.06) 

32.1 to <44.3 μg/m3

: 1.02 (0.95, 1.09) 

≥ 44.3 μg/m3: 1.04 (0.95, 1.14) 

Notes: multipollutant model adds CO,NO2, 

and O3 in addition to the main pollutant of 

interest, PM10. 

Reference: Woodruff et al. (1997, 

084271) 

Period of Study: 1989-1991 

Location: 86 Metropolitan Statistical 

Areas in the U.S. (counties with 

populations less than 100,000 were 

excluded) 

Outcome: Postneonatal mortality 

(death of an infant between 1 month 

and 1 yr of age 

1) All post neonatal deaths 

2) Normal birth weight (NBW, ≥ 2500 g) 

SIDS deaths 

3) NBW respiratory deaths 

4) Low birth weight (LBW) respiratory 

death 

Respiratory deaths: ICD9 codes 

460-519 

SIDS: ICD9 code 798.0 

Age Groups: Infants (1 month-1yr of 

age) 

Study Design: Cross-sectional

N: 3,788,079 infants 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal education, 

maternal race, parental marital status, 

maternal smoking during pregnancy 

Avg temperature during the first 2 mo of 

life 

Infant’s month and yr of birth 

Assessed race as an effect modifier 

(p-val for interaction terms >0.2) 

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM10

Averaging Time: Mean of 1st 2 mo of 

life 

analyzed as tertiles of exposure and as 

continuous exposure 

Mean (SD): 31.4 (7.8) 

Range (Min, Max): 

Overall: 11.9-68.8 

Low category: <28.0 

Medium category: 28.1-40.0 

High category: >40.0 

Monitoring Stations: NR 

PM Increment: 10 μg/m3 (for continuous 

exposure analysis)

Adjusted ORs for cause-specific post 

neonatal mortality by pollution 

category (tertiles) 

All causes 

Low: Ref 

Medium: 1.05 (1.01, 1.09) 

High: 1.10 (1.04, 1.16) 

SIDS, NBW: 

Low: Ref 

Medium: 1.09 (1.01, 1.17) 

High: 1.26 (1.14, 1.39) 

Respiratory death, NBW: 

Low: Ref 

Medium: 1.08 (0.87, 1.33) 

High: 1.40 (1.05, 1.85) 

Respiratory death, LBW: 

Low: Ref 

Medium: 0.93 (0.73, 1.18) 

High: 1.18 (0.86, 1.61) 

All other causes: 

Low: Ref 

Medium: 1.03 (0.97, 1.08) 

High: 0.97 (0.90, 1.04) 

Adjusted ORs for a continuous 

10 μg/m3

 change in exposure 

All causes: 1.04 (1.02, 1.07) 

SIDS, NBW: 1.12 (1.07, 1.17) 

Respiratory death, NBW: 1.20 (1.06, 1.36) 

Respiratory death, LBW: 1.05 (0.91, 1.22) 

All other causes: 1.00 (0.99, 1.00) 

December 2009 E-474 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Woodruff et al. (2008, 

098386) 

Period of Study: 1999-2002 

Location: U.S. counties with >250,000 

residents (96 counties) 

Outcome: Postneonatal deaths 

Respiratory mortality (ICD10: J000-99, 

plus bronchopulmonary dysplasia [BPD] 

P27.1) 

SIDS (ICD10: R95) 

Ill-defined causes (R99); 

All other deaths evaluated as a control 

category 

Age Groups: Infants aged >28 days 

and <1 yr 

Study Design: Cross-sectional

N: 3,583,495 births (6,639 post 

neonatal deaths) 

Statistical Analyses: Logistic GEE 

(exchangeable correlation structure) 

Covariates: Maternal race/ethnicity, 

marital status, age, education, 

primiparity, county-level poverty and per 

capita income levels, yr and month of 

birth dummy variables to account for 

time trend and seasonal effects, and 

region of the country 

Sensitivity analyses performed among 

only those mothers with smoking 

information (adjustment for smoking 

had no effect on the estimates) 

Season: Adjusted for yr and month of 

birth dummy variables to account for 

time trend and seasonal effects 

Dose-response Investigated? 

Evaluated the appropriateness of a 

linear form from analysis based on 

quartiles of exposure and concluded 

that linear form was appropriate (data 

not shown) 

Statistical Package: SAS 

Pollutant: PM10

Averaging Time: Measured 

continuously for 24 h once every 6 days

exposure assigned by calculating avg 

concentration of pollutant during first 2 

mo of life 

Median and IQR (25th-75th 

percentile): 

Survivors: 28.9 (23.3-34.4) 

All causes of death: 29.1 (23.9-34.5) 

Respiratory: 29.8 (24.3-36.5) 

SIDS: 28.6 (23.5-33.8) 

SIDS + ill-defined: 28.8 (23.9-33.9) 

Other causes: 29.2 (23.9-34.5) 

Percentiles: see above 

PM Component: Not assessed, but 

controlled for region of the country to 

account for PM composition variation 

Monitoring Stations: NR 

Copollutant (correlation): 

PM10 

PM2.5 (r = 0.34) 

CO (r = 0.18) 

SO2 (r = 0.00) 

O3 (r = 0.20) 

Notes: Monthly avg calculated if there 

were at least 3 available measures for 

PM 

Assigned exposures using the avg 

concentration of the county of residence

PM Increment: IQR (11 μg/m3) 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted ORs for single pollutant models 

All causes: 1.04 (0.99, 1.10) 

Respiratory: 1.18 (1.06, 1.31) 

SIDS: 1.02 (0.89, 1.16) 

Ill-defined + SIDS: 1.06 (0.97, 1.16) 

Other causes: 1.02 (0.96, 1.07) 

Adjusted ORs for multipollutant models 

(including CO, O3, SO2) 

Respiratory: 1.16 (1.04, 1.30) 

SIDS: 1.02 (0.90, 1.16) 

OR for deaths coded as BPD per increase 

in IQR: 1.19 (0.85, 1.65) 

OR for respiratory post neonatal death 

stratified by birth weight 

NBW only: 1.19 (1.05, 1.36) 

LBW only: 1.12 (0.95, 1.31) 

OR for respiratory deaths removing region 

of U.S. as a confounding variable: 1.30 

(1.04, 1.61) 

OR for respiratory deaths assessing 

exposure as quartiles 

Highest vs. Lowest quartile: 1.31 (1.00, 

1.71) 

OR for respiratory deaths among only 

those deaths that occurred during the first 

90 days (most closely matched exposure 

metric of the avg over the first 2 mo of 

life): 1.25 (1.06, 1.47) 

December 2009 E-475 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Jedrychowski, et al., (2007, 

156607) 

Period of Study: Jan 2001-Feb 2004 

Location: Krakow, Poland 

Outcome: Birth weight (grams), birth 

length (cm) 

Age Groups: Pregnant women 18-35 

yr

Study Design: Prospective cohort

N: 493 women 

Statistical Analyses: Linear regression

Covariates: Environmental tobacco 

smoke (# cigarettes smoked daily in 

presence of pregnant woman), season 

of birth, size of mother, parity, 

gestational age, gender of child, vitamin 

A intake 

Season: All 

Dose-response Investigated? Yes 

Statistical Package: NR 

Lags Considered: Two consecutive 

days in the second trimester 

Pollutant: PM2.5 

Averaging Time: 48 h period 

Percentiles: 50th(Median): 35.3 

Range (Min, Max): 10.3, 294.9 

Monitoring Stations: No stations, 

personal monitoring 

Notes: PM measured during a 2 day 

period in the second trimester by 

Personal Environmental Monitoring 

Sampler (PEMS) 

PM Increment: in 1 μg/m3 and tertiles 

T1: <27.0 μg/m3

 

T2: 27.0-46.2 μg/m3 

T3: ≥ 46.2 μg/m3

 

Mean [Lower CI, Upper CI]: 

Birth weight (g) 

For ln unit PM: β = -172.39 (p = 0.02) 

Tertiles: 

T1: ref 

T2: β = -16.510 [-94.630, 61.610] 

T3: β = -109.956 [-196.649 to -23.263] 

In low Vitamin A group (<1,378 μg) 

T1: ref 

T2: β = -68.354 [-165.643, 28.935] 

T3: β = -185.070 [-293.393 to -76.747] 

In high Vitamin A group (>1,378 μg) 

T1: ref 

T2: β = 64.262 [-70.464, 198.988] 

T3: β = 38.593 [-109.853, 187.039] 

Birth length (cm) 

For ln unit PM: β = -1.39 (p = 0.00) 

Tertiles: 

T1: ref 

T2: β = -0.288 [-0.790, 0.214] 

T3: β = -0.810 [-1.367 to -0.253] 

In low Vitamin A group (<1,378 μg) 

T1: ref 

T2: β = -0.514 [-1.114, 0.086] 

T3: β = -1.100 [-1.768 to -0.432] 

In high Vitamin A group (>1,378 μg) 

T1: ref 

T2: β = 0.039 [-0.896, 0.974] 

T3: β = -0.301 [-1.326, 0.724] 

Reference: (Lipfert et al., 2000, 

004103)

Period of Study: 1990 

Location: U.S. 

Outcome (ICD9 and ICD10): Infant 

mortality 

Including respiratory mortality 

(traditional definition, ICD9 460-519), 

expanded definition (adds ICD9 769 

and 770) 

Age Groups: Infants 

Study Design: Cross-sectional

N: 2,413,762 infants in 180 counties 

(Ns differ for various models) 

Statistical Analyses: Logistic 

regression 

Covariates: Mother’s smoking, 

education, marital status, and race 

Month of birth 

And county avg heating degree days 

Dose-response Investigated? NR 

Statistical Package: NR 

Pollutant: SO4

2–/ NSPM10 (regressed 

jointly) 

Averaging Time: Yearly avg used 

Mean (SD): 33.1 (9.17) (based on 180 

counties) 

Range (Min, Max): (16.9, 59) 

Monitoring Stations: NR 

Copollutant: 

PM10

NSPM10

CO 

SO2 

Notes: TSP-based sulfate was adjusted 

for compatibility with the PM10-based 

data 

PM Increment: NR (present regression 

coefficients) 

Effect Estimate [Lower CI, Upper CI]: 

Presented regression coefficients 

(standard errors) 

(3 PM exposures regressed jointly) 

bold = p <0.05 

Cause of death: All 

Birth weight: All 

SO4

2–: -0.0002 (0.0061) 

NSPM10: 0.0115 (0.0014) 

Cause of death: All 

Birth weight: LBW 

SO 2–

4 : 0.0265 (0.0080) 

NSPM10: 0.0086 (0.0020) 

Cause of death: All 

Birth weight: normal 

SO4

2–: -0.0488 (0.0098) 

NSPM10: 0.0096 (0.0024) 

Cause of death: All neonatal 

Birth weight: All 

SO4

2–: 0.0267 (0.0076) 

NSPM10: 0.0126 (0.0018) 

Cause of death: All neonatal 

Birth weight: LBW 

SO 2–

4 : 0.0388 (0.0088) 

NSPM10: 0.0093 (0.0022) 

Cause of death: All neonatal 

Birth wt: normal 

SO4

2–: -0.0334 (0.0169) 

NSPM10: 0.0125 (0.0040) 

Cause of death: All post neonatal 

Birth wt: All 

PM10: 0.0091 (0.0024) 

SO 2–

4 : -0.0474 (0.0100) 

NSPM10: 0.0096 (0.0024) 

Cause of death: All post neonatal 

Birth wt: LBW 

SO4

2–: -0.0247 (0.0173) 

NSPM10: 0.0101 (0.0042) 

Cause of death: All post neonatal 

Birth wt: normal 

SO4

2–: -0.0569 (0.0121) 

December 2009 E-476 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

NSPM10: 0.0080 (0.0029) 

Cause of death: SIDS 

Birth weight: All 

SO

4

2–: -0.1078 (0.0151) 

NSPM10: 0.0149 (0.0037) 

Cause of death: SIDS 

Birth weight: LBW 

SO

4

2–: -0.1378 (0.0337) 

NSPM10: 0.0146 (0.0085) 

Cause of death: SIDS 

Birth weight: normal 

PM10: 0.0137 (0.0042) 

SO

4

2–: -0.0995 (0.0168) 

NSPM10: 0.0147 (0.0041) 

Cause of death: All respiratory (ICD9: 460-

519, 769, 770) 

Birth weight: All 

SO

4

2–: 0.0706 (0.0146) 

NSPM10: 0.0166 (0.0034) 

Cause of death: All respiratory (ICD9: 460-

519, 769, 770) 

Birth weight: LBW 

SO

4

2–: 0.0821 (0.0158) 

NSPM10: 0.0139 (0.0038) 

Cause of death: All respiratory (ICD9: 460-

519, 769, 770) 

Birth weight: normal 

PM10: 0.0177 (0.0091) 

SO

4

2–: 0.0001 (0.0392) 

NSPM10: 0.0118 (0.0090) 

Cause of death: Respiratory disease 

(ICD9: 460-519) 

Birth weight: All 

PM10: 0.0133 (0.0089) 

SO

4

2–: 0.0093 (0.0384) 

NSPM10: 0.0134 (0.0089) 

Cause of death: Respiratory disease 

(ICD9: 460-519) 

Birth weight: LBW 

PM10: 0.0092 (0.0137) 

SO

4

2–: 0.0434 (0.0580) 

NSPM10: 0.0089 (0.0138) 

Cause of death: Respiratory disease 

(ICD9: 460-519) 

Birth weight: normal 

SO

4

2–: -0.0177 (0.0509) 

NSPM10: 0.0128 (0.0119) 

Associations with SIDS by smoking status 

Smoking status: Yes 

Birth weight: Normal 

SO

4

2–: -0.0722 (0.0284) 

NSPM10: 0.0206 (0.0071) 

Smoking status: No 

Birth weight: Normal 

SO

4

2–: -0.114 (0.021) 

NSPM10: 0.0117 (0.005) 

Smoking status: Yes 

Birth weight: LBW 

SO

4

2–: -0.0958 (0.0483) 

NSPM10: 0.0345 (0.0125) 

Smoking status: No 

Birth weight: LBW 

SO

4

2–: -0.0172 (0.047) 

NSPM10: -0.0007 (0.012) 

Mean risks (95%CI) between post 

neonatal SIDS among normal birth weight 

babies 

pollutants regressed one at a time 

SO

4

2–: 0.43 (0.37, 0.51) 

NSPM10: 1.33 (1.18, 1.50) 

December 2009 E-477 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Liu et al., 2007, 090429) 

Period of Study: 1985-2000

Location: 3 Canadian cities: Calgary, 

Edmonton, and Montreal 

Outcome: Intrauterine growth 

restriction (IUGR)

Age Groups: Singleton term live births

(37-42 wks gestation)

Study Design: Retrospective cohort

N: 386,202 singleton live births

Statistical Analyses: Multiple logistic 

regression

Covariates: Maternal age, parity, infant 

gender, season, and city of residence at 

time period of birth

Season: All seasons

Dose-response Investigated? No 

Statistical Package: NR 

Pollutant: PM2.5

Averaging Time: 24 h (6-day schedule)

Mean (SD): 12.2 

Percentiles: 25th: 6.3

50th(Median): 9.7

75th: 15 

PM Component: metals and organic 

matter such as polycyclic aromatic 

hydrocarbons

Monitoring Stations: Calgary (4), 

Edmonton (2), and Montreal (8)

Copollutant (correlation): 

SO2: r = 0.44, p < 0.0001 

NO2: r = 0.41, p < 0.0001 

CO: r = 0.31, p < 0.0001 

O3: r = -0.14, p < 0.0001 

PM Increment: 10 μg/m3

Effect Estimate 

Single-pollutant model [Lower CI, 

Upper CI]: 

1st trimester 

OR = 1.07 (1.03-1.10) 

2nd trimester 

OR = 1.06 (1.03-1.10) 

3rd trimester 

OR = 1.06 (1.03-1.10) 

Effect Estimate 

multi-pollutant model [Lower CI, Upper 

CI]: 

1st trimester 

OR= 1.03 (0.99-1.06) 

2nd trimester 

OR= 1.01 (0.98-1.05) 

3rd trimester 

OR= 1.03 (0.99-1.06) 

Note: ORs and CIs estimated from Fig. 6 

and 7 

Reference: Loomis et al. (1999, 

087288) 

Period of Study: Jan 1993-Jul 1995 

Location: Mexico City (southwestern 

section) 

Outcome (ICD9 and ICD10): Infant 

mortality (daily counts of deaths) 

All ICD9 codes, excluding accidents, 

poisoning, and violence (ICD9 ≥800) 

Age Groups: Children <1 yr of age 

Study Design: Time-series

N: 942 deaths (days were the unit of 

observation) 

Statistical Analyses: Poisson 

regression (generalized additive model) 

Covariates: Final models controlled for 

mean temp of 3 days before death and 

nonparametrically smoothed periodic 

cycles 

Season: Yes (considered)

Dose-response Investigated? Loess 

smoother 

Statistical Package: NR 

Lags Considered: 0-5 (also 

considered lags with avg exposure 

levels during “windows” of 2 to 4 days) 

Pollutant: PM2.5 

Averaging Time: 24-h 

Mean (SD): 27.4 (10.5) 

Percentiles: Lower quartile: 20 

Median: 26 

Upper quartile: 34 

Range (Min, Max): 4, 85 

Monitoring Stations: 1 

Copollutant: 

O3

NO2

NO 

NOX

SO2

Notes: Pearson correlation coefficients 

ranging from 0.52 to 0.71 

PM Increment: 10 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

%Change in infant mortality 

Lags 0-5 (single day) presented in Fig 1: 

Lag0,1,2: No association (results not 

presented) 

Lag3: 4.8 (0.97, 8.61) 

Lag4: 4.2 (0.37, 7.93) 

%Change in mortality when avg exposure 

levels during “windows” of 2 to 4 days 

were considered 

2 Days: 

No lag: -1.36 (-5.51, 2.8) 

Lag1: -0.95 (-5.10, 3.20) 

Lag2: 2.78 (-1.33, 6.89) 

Lag3: 4.93 (0.86, 9.01) 

3 Days: 

No lag: -0.81 (-5.29, 3.67) 

Lag1: 1.99 (-2.46, 6.45) 

Lag2: 4.54 (0.12, 8.96) 

Lag3: 6.87 (2.48, 11.26) 

4 Days: 

No lag: 1.95 (-2.76, 6.66) 

Lag1: 3.74 (-0.95, 8.42) 

Lag2: 5.87 (1.21, 10.53) 

Multipollutant models (3-day mean w/ 3-

day lag) 

1 pollutant model: 

6.87 (2.48, 11.26) 

2 pollutant models: 

w/ O3: 6.24 (1.35, 11.14) 

w/ NO2: 5.91 (-0.76, 12.59) 

3 Pollutant model (w/ O3 and NO2): 

6.30 (-0.54, 13.15) 

December 2009 E-478 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Mannes et al. (2005, 

087895)

Period of Study: Jan 1998-Dec 2000

Location: metropolitan Sydney, 

Australia 

Outcome: Risk of small for gestational 

age (SGA) and birth weight

Age Groups: All singleton births >20 

wk and ≥ 400 grams birth weight and 

maternal all ages 

Study Design: Cross-sectional

N: 138,056 singleton births

Statistical Analyses: Logistic and 

linear regression models

Covariates: Sex of child, maternal age, 

gestational age, maternal smoking, 

gestational age at first antenatal visit, 

maternal indigenous status, whether 

first pregnancy, season of birth, and 

socioeconomic status (SES)

Season: All seasons 

included as covariate.

Dose-response Investigated? No 

Statistical Package: SAS System for 

Windows v8.02

Pollutant: PM2.5

Averaging Time: 24 h

Mean (SD): 9.4 (5.1) 

Percentiles: 25th: 6.5

50th(Median): 8.4

75th: 11.2 

Range (Min, Max): (2.4- 82.1)

Monitoring Stations: up to 14

Copollutant (correlation): 

CO: r = 0.53 

NO2: r = 0.66 

O3: r = 0.36 

PM10: r = 0.81 

PM Increment: 1 μg/m3

Risk of SGA 

All births 

1 month before birth: 

OR = 1.01 (0.99-1.03) 

Third trimester: OR = 0.99 (0.97-1.02) 

Second trimester: 

OR = 1.03 (1.01-1.05) 

First trimester: OR = 0.99 (0.97-1.01) 

5 km births 

1 month before birth: 

OR = 1.01 (0.97-1.04) 

Third trimester: OR = 1.00 (0.95-1.05) 

Second trimester: 

OR = 1.00 (0.96-1.05) 

First trimester: OR = 0.99 (0.94-1.04) 

Change in birth weight 

All births 

1 month before birth: 

 ß = -2.48 (-4.58- -0.38) 

Third trimester: ß = -0.98 (-3.74-1.78) 

Second trimester: 

ß = -4.10 (-6.79- -1.41) 

First trimester: ß = 0.36 (-2.29- 3.01) 

5 km births 

1 month before birth: 

ß = -2.70 (-6.80- 1.40) 

Third trimester: ß = -2.83 (-9.00-3.34) 

Second trimester: ß = 1.54 (-4.59-7.67) 

First trimester: ß = 1.89 (-1.99-5.77) 

Reference: Parker et al. (2005, 

087462)

Period of Study: 1999-2000

Location: California 

Outcome: Small for gestational age 

(SGA) and birth weight

Age Groups: Infants delivered at 40 wk 

gestation 

maternal all ages

Study Design: Cross-sectional

N: 18,247 singleton births

Statistical Analyses: Linear and 

logistic regression models

Covariates: Maternal race, maternal 

Hispanic origin, marital status, parity, 

maternal education, and maternal age

Season: Season of delivery (covariate)

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM2.5

Averaging Time: NR (measurement 

taken every 6 days)

Mean (SD): 15.42 (5.08) 

PM Component: metals, polycyclic 

aromatic hydrocarbons

Monitoring Stations: 40

Copollutant (correlation): 

PM2.5-CO: r = 0.6

Notes: Mean calculated for 9-month 

exposure. The following means (SDs) 

are calculated for trimester: 

First: 15.70 (6.26) 

Second: 15.40 (6.53) 

Third: 14.29 (6.35) 

PM categorized into quartiles: 

Q1: <11.9 

Q2: 11.9-13.9 

Q3: 13.9-18.4 

Q4: >18.4 

PM Increment: <11.9 μg/m3|

Referent PM Increment: 11.9-13.9 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

First Trimester 

Birth weight: ß = -5.7 (-27.9-16.5) 

SGA: OR = 1.02 (0.84-1.23) 

Second Trimester 

Birth weight: ß = 11.3 (-12.2-34.9) 

SGA: OR = 0.89 (0.73-1.09) 

Third Trimester 

Birth weight: ß = 8.3 (-13.1-29.8) 

SGA: OR = 1.00 (0.83-1.19) 

PM Increment: 13.9-18.4 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

First Trimester 

Birth weight: ß = -2.5 (-24.5-19.5) 

SGA: OR = 1.12 (0.93-1.34) 

Second Trimester 

Birth weight: ß = -17.2 (-39.4-4.9) 

SGA: OR = 1.05 (0.88-1.26) 

Third Trimester 

Birth weight: ß = -8.1 (-30.2-13.9) 

SGA: OR = 0.98 (0.82-1.18) 

PM Increment: >18.4 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

First Trimester 

Birth weight: ß = -35.8 (-58.4--13.3) 

SGA: OR = 1.26 (1.04-1.51) 

Second Trimester 

Birth weight: ß = -46.6 (-68.6- -24.6) 

SGA: OR = 1.24 (1.04-1.49) 

Third Trimester 

Birth weight: ß = -31.6 (-52.0- -11.1) 

SGA: OR = 1.21 (1.02-1.43) 

December 2009 E-479 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Parker and Woodruff 

(2008, 156846) 

Period of Study: 2001-2003

Location: U.S. 

Outcome: Low birth weight

Study Design: Cohort

N: 785,965 Singleton births delivered at 

40 wk gestation

Statistical Analyses: GEE regression 

models 

linear and logistic regression

Covariates: Race/ethnicity, parity, 

maternal age

Season: Season of delivery

Statistical Package: SUDAAN 

Pollutant: PM2.5

Averaging Time: 9 mo

Mean (SD): 14.5 

25th: 12.1 

75th: 17.6 

Copollutant (correlation): 

SO2, NO2 CO O3

PM Increment: 10 μg/m3

Change in Birth weight (9 month 

exposure): 

Unadjusted: 19.4 (9.8, 29.0) 

Adjusted for maternal factors: 

18.4 (9.2, 27.7) 

Stratified by region: 

Industrial Midwest: -15.3 (-43.4, 12.9) 

Northeast: -9.8 (-11.9, 26.6) 

Northwest: 27.5 (5.5, 49.4) 

Southern CA: 5.5 (-9.6, 20.5) 

Southeast: 7.3 (-11.9, 26.6) 

Southwest: 72.3 (34.0, 110.5) 

Upper Midwest: -0.7 (-62.0, 60.6) 

Multipollutant models: 

PM2.5 +PM10-2.5: 14.2 (4.3, 24.1) 

PM2.5 +PM10-2.5+SO2+CO+NO2+O3: 28.6 

(14.2, 43.0) 

December 2009 E-480 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Rich et al. (2009, 180122) 

Period of Study: 1999-2003 

Location: New Jersey, United States 

Outcome: Small for gestational age 

Study Design: Retrospective Cohort 

Covariates: Month and calendar yr of 

birth, apparent temperature, pregnancy 

complications 

Statistical Analysis: Polytomous 

logistic regression 

Statistical Package: SAS 

Age Groups: Gestational age 37-42 

wks 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD) Unit: 

*All values are for first trimester, other 

trimesters are available in paper 

Reference Births: 13.8 (2.5) 

SGA Births: 13.9 (2.5) 

VSGA Births: 13.9 (2.4) 

Range (Min, Max): 2.0, 29.0 

Copollutant (correlation): 

*All values are for first trimester, other 

trimesters are available in paper 

NO2: 0.01 

SO2: 0.17 

CO: 0.25 

*All values are for first trimester, other 

trimesters are available in paper 

Increment: 4 μg/m3

Percent Change in Risk (95% CI) 

SGA: 4.5 (0.5-8.7) 

VSGA: 2.6 (-4.4-10.0) 

Percent Change in Risk (95% CI) for 

single and two-pollutant models 

Single, SGA: 4.6 (-0.3-9.8) 

Single, VSGA: 4.5 (-4.0-13.4) 

Two (PM2.5 & NO2), SGA: 4.5 (-0.4-9.7) 

Two (PM2.5 & NO2), VSGA: 3.2 (-5.2-12.4) 

Percent Change in Risk (95% CI) by 

pregnancy complication in third 

trimester 

SGA 

Any Complication 

No: 4.7 (0.6-9.0) 

Yes: 2.2 (-6.1-11.3) 

Placental Abruption 

No: 4.0 (0.3-7.9) 

Yes: 11.7 (-21.7-59.5) 

Placental Praevia 

No: 3.9 (0.2-7.8) 

Yes: 23.2 (-20.9-91.9) 

Pre-eclampsia 

No: 4.2 (0.4-8.2) 

Yes: 2.7 (-13.8-22.3) 

Gestational Hypertension 

No: 4.3 (0.4-8.4) 

Yes: 3.9 (-7.8-17.1) 

Premature Rupture of the Membrane 

No: 3.7 (-0.1-7.7) 

Yes: 14.6 (-3.3-35.9) 

Gestational Diabetes 

No: 4.6 (0.8-8.6) 

Yes: -9.3 (-24.7-9.3) 

VSGA 

Any Complication 

No: 1.5 (-6.1-9.7) 

Yes: 12.6 (0.1-26.7) 

Placental Abruption 

No: 4.1 (-2.6-11.2) 

Yes: 7.6 (-29.8-64.9) 

Placental Praevia 

No: 4.1 (-2.5-11.2) 

Yes: 3.2 (-43.0-86.9) 

Pre-eclampsia 

No: 4.4 (-2.6-11.9) 

Yes: 3.9 (-15.7-28.1) 

Gestational Hypertension 

No: 3.2 (-4.0-10.9) 

Yes: 12.9 (-3.3-31.9) 

Premature Rupture of the Membrane 

No: 3.3 (-3.5-10.5) 

Yes: 21.9 (-3.6-54.2) 

Gestational Diabetes 

No: 4.3 (-2.5-11.5) 

Yes: 1.4 (-27.0-40.9) 

December 2009 E-481 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Ritz et al. (2007, 096146) 

Period of Study: Jan 2003-Dec 2003 

Location: Los Angeles, California 

Outcome: Preterm births (infants 

delivered before 37 wk) 

Age Groups: Births 

Study Design: Case-control nested 

within a birth cohort (cases and controls 

matched on zip code and birth month) 

Phase 1: cross-sectional including all 

birth cohort 

Phase 2: nested case-control of survey 

respondents

N: Phase 1: Birth cohort consisted of 

58,316 eligible births. Phase II: 2,543 

Statistical Analyses: Logistic 

regression 

Covariates: Birth certificate 

information: maternal age, 

race/ethnicity, parity, education, season 

of birth 

survey information: maternal smoking, 

alcohol consumption, living with a 

smoker, and marital status during 

pregnancy 

income (imputed) 

occupation and pregnancy weight gain 

considered but not included in final 

models 

Season: Yes 

Dose-response Investigated? Yes, 

examined categories of exposure 

Statistical Package: NR 

Pollutant: PM2.5 

Averaging Time: daily or every 3rd day 

used to calculate the entire pregnancy, 

the first trimester, and the last 6 wk 

before delivery 

Only reported first trimester exposures 

for PM 

Range (Min, Max): NR 

Ranges for 3 categories reported: 

Low (ref): ≤ 18.63 

Mid: 18.64-21.36 

High: >21.36 

Monitoring Stations: Each zip code 

was linked to the nearest monitoring 

station (number not reported) 

Copollutant (correlation): 

CO 

NO2

O3

Notes: Daily or every 3rd day 

measurements used for mean 

calculations 

PM Increment: Reported analyses using 

exposure categories 

Effect Estimate [Lower CI, Upper CI]: 

Birth cohort (phase I) 

Crude: Low: 1.0 

Mid: 0.96 (0.90, 1.03) 

High: 1.05 (0.99, 1.12) 

Adj for birth cert Covariates: Low: 1.0 

Mid: 1.01 (0.93, 1.09) 

High: 1.10 (1.01, 1.20) 

Survey respondents (phase II) 

Crude: Low: 1.0’ Mid: 1.11 (0.90, 1.36) 

High: 1.27 (1.06, 1.53) 

Adj for birth cert Covariates: Low: 1.0 

Mid: 1.14 (0.90, 1.46) 

High: 1.27 (0.99, 1.64) 

Adj for all Covariates: Low: 1.0 

Mid: 1.15 (0.90, 1.47) 

High: 1.29 (1.00, 1.67) 

Two-phase model: * Low: 1.0 

Mid: 0.98 (0.84, 1.15) 

High: 1.07 (0.85, 1.35) 

*Method to reduce potential selection bias 

and increase statistical efficiency 

Reference: Slama et al. (2007, 093216) 

Period of Study: Jan 1998-Jan 1999 

Location: Munich, Germany 

Outcome: Birth weight offspring at term 

Study Design: Cohort study

N: 1016 births 

Statistical Analyses: Poisson model 

Covariates: Maternal passive smoking, 

maternal age, gestational duration, sex 

of child, parity, maternal education, 

maternal size, prepregnancy weight, 

other pollutants (PM2.5, PM2.5

absorbance, NO2), season of conception

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM2.5 (estimated based on 

larger PM size fractions) 

Averaging Time: Entire pregnancy 

period and trimesters 

Mean (SD): 14.4 

Percentiles: 25th: 13.5

50th(Median): 14.4 

75th: 15.4 

Monitoring Stations: Spatial 

component: 40 

Temporal component: 1 

Copollutant (correlation): 

p.a. = pregnancy avg 

trim. = trimester 

PM2.5 (p.a.)-PM2.5 (1st trim.): 0.85 

PM2.5 (p.a.)-PM2.5 (2nd trim.): 0.77 

PM2.5 (p.a.)-PM2 (3rd trim.): 0.87 .5

PM2.5 (p.a.)-NO2 (p.a.): 0.45 

PM2.5 (p.a.)-NO2 (1st trim.): 0.18 

PM2.5 (p.a.)-NO2 (2nd trim.): 0.32 

PM2.5 (p.a.)-NO2 (3rd trim.): 0.37 

PM2.5 (1st trim.)-PM2.5 (2nd trim.): 0.40 

PM2.5 (1st trim.)-PM2 (3rd trim.): 0.68 .5

PM2.5 (1st trim.)-NO2 (p.a.): 0.48 

PM2.5 (1st trim.)-NO2 (1st trim.): 0.15 

PM2.5 (1st trim.)-NO2 (2nd trim.): 0.41 

PM2.5 (1st trim.)-NO2 (3rd trim.): 0.39 

PM2.5 (2nd trim.)-PM2.5 (3rd trim.): 0.51 

PM2.5 (2nd trim.)-NO2 (p.a.): 0.23 

PM2.5 (2nd trim.)-NO2 (1st trim.): -0.03 

PM2.5 (2nd trim.)-NO2 (2nd trim.): 0.17 

PM2.5 (2nd trim.)-NO2 (3rd trim.): 0.30 

PM Increment: 

1) 1 μg/m3

2) Quartiles: 

a) 1st (reference) (7.2-13.5 μg/m3) 

b) 2nd (13.5-14.4 μg/m3

) 

c) 3rd (14.4-15.4 μg/m3

) 

day) 4th (15.41-17.5 μg/m3) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy 

Single-pollutant models 

Unadjusted models 

2nd quartile: 1.07 (0.65, 1.73); 3rd 

quartile: 1.38 (0.91, 2.09) 

4th quartile: 1.45 (0.92, 2.25) 

Per 1 μg/m3

: 1.06 (0.95, 1.19) 

Adjusted models 

2nd quartile: 1.08 (0.63, 1.82); 3rd 

quartile: 1.34 (0.86, 2.13) 

4th quartile: 1.73 (1.15, 2.69); Per 

1 μg/m3

: 1.13 (1.00, 1.29) 

Multipollutant models 

Adjusted models 

2nd quartile: 1.01 (0.57, 1.85) 

3rd quartile: 1.12 (0.64, 1.87) 

4th quartile: 1.36 (0.72, 2.45); Per 

1 μg/m3

: 1.07 (0.91, 1.26) 

Single-pollutant models (restricted 

analysis to PM2.5 absorbance below the 

median) 

Per 1 μg/m3

: 1.15 (0.89, 1.52) 

Prevalence ratios (PRs) of birth 

weight <3000 g 

Multipollutant models (simultaneous 

December 2009 E-482 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

PM2.5 (3rd trim.)-NO2 (p.a.): 0.39 

PM2.5 (3rd trim.)-NO2 (1st trim.): 0.33 

PM2.5 (3rd trim.)-NO2 (2nd trim.): 0.21 

PM2.5 (3rd trim.)-NO2 (3rd trim.): 0.23 

PM2.5 (p.a.)- PM2.5 absorbance (p.a.): 

0.69 

PM2.5 (p.a.)- PM2.5 abs (1st trim.): 0.33 

PM2.5 (p.a.)- PM2.5 abs (2nd trim.): 0.48 

PM2.5 (p.a.)- PM2.5 abs (3rd trim.): 0.52 

PM2.5 (1st trim.)- PM2.5 abs (p.a.): 0.68 

PM2.5 (1st trim.)- PM2.5 abs (1st trim.): 

0.27 

PM2.5 (1st trim.)- PM2.5 abs (2nd trim.): 

0.53 

PM2.5 (1st trim.)- PM2.5 abs (3rd trim.): 

0.51 

PM2.5 (2nd trim.)- PM2.5 abs(p.a.): 0.41 

PM2.5 (2nd trim.)- PM2.5 abs (1st trim.): 

0.08 

PM2.5 (2nd trim.)- PM2.5 abs (2nd trim.): 

0.29 

PM2.5 (2nd trim.)- PM2.5 abs (3rd trim.): 

0.41 

PM2.5 (3rd trim.)- PM2.5 abs (p.a.): 0.62 

PM2.5 (3rd trim.)- PM2.5 abs (1st trim.): 

0.48 

PM2.5 (3rd trim.)- PM2.5 abs (2nd trim.): 

0.36 

PM2.5 (3rd trim.)- PM2.5 abs (3rd trim.): 

0.37 

Adjustment of 3rd trimester PM2.5 and 

whole pregnancy PM2.5) 

PM2.5 (whole pregnancy) 

Per 1 μg/m3

: 0.96 (0.75, 1.19) 

PM2.5 (3rd trimester) 

Per 1 μg/m3

: 1.17 (0.98, 1.40) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy (adjustment for 

season of conception) 

4th quartile: 1.68 (1.05, 2.75); Per 

1 μg/m3

: 1.12 (0.97, 1.28) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

first trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.14 (0.74, 1.96); 3rd 

quartile: 1.28 (0.84, 2.10) 

4th quartile: 1.65 (1.02, 2.60) 

Per 1 μg/m3

: 1.10 (0.99, 1.20) 

All trimesters adjusted simultaneously 

2nd quartile: 0.97 (0.60, 1.73); 3rd 

quartile: 0.98 (0.57, 1.75) 

4th quartile: 1.22 (0.71, 2.18) 

Per 1 μg/m3

: 1.03 (0.90, 1.17) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

second trimester of pregnancy 

Each trimester separately 

2nd quartile: 0.83 (0.52, 1.32); 3rd 

quartile: 1.08 (0.71, 1.60) 

4th quartile: 0.94 (0.61, 1.47) 

Per 1 μg/m3

: 1.01 (0.92, 1.12) 

All trimesters adjusted simultaneously 

2nd quartile: 0.75 (0.46, 1.24) 

3rd quartile: 0.86 (0.56, 1.30); 

4th quartile: 0.75 (0.48, 1.23) 

Per 1 μg/m3

: 0.94 (0.84, 1.06) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.30 (0.80, 2.17) 

3rd quartile: 1.44 (0.85, 2.27) 

4th quartile: 1.90 (1.20, 2.82) 

Per 1 μg/m3

: 1.14 (1.02, 1.24) 

All trimesters adjusted simultaneously 

2nd quartile: 1.34 (0.79, 2.30) 

3rd quartile: 1.48 (0.86, 2.58) 

4th quartile: 1.91 (1.00, 3.20) 

Per 1 μg/m3

: 1.14 (0.99, 1.29) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

Per 1 μg/m3

: 1.25 (1.04, 1.50) 

Sensitivity analysis(bootstrapped PR)

2nd quartile: 0.98 (0.63, 1.61); 3rd 

quartile: 1.22 (0.82, 2.02) 

4th quartile: 1.57 (1.02, 2.57) 

Per 1 μg/m3

: 1.11 (0.98, 1.27) 

Estimated increments in prevalence 

of birth weight of <3000 g during 

exposure 9 mo after birth 

Per 1 μg/m3: 7% (-7%, 22%)

Reference: (Slama et al., 2007, 

093216) 

Period of Study: Jan 1998-Jan 1999 

Outcome: Birth weight offspring at term 

Study Design: Cohort study

Pollutant: PM2.5 absorbance (estimated)

Averaging Time: Entire pregnancy 

period and trimesters 

PM Increment: 

1) 0.5 * 10-5/m 2) Quartiles: 

a) 1st (reference) (1.29-1.61) 

b) 2nd (1.61-1.72) 

December 2009 E-483 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Location: Munich, Germany N: 1016 births 

Statistical Analyses: Poisson model 

Covariates: Maternal passive smoking, 

maternal age, gestational duration, sex 

of child, parity, maternal education, 

maternal size, prepregnancy weight, 

other pollutants (PM2.5, PM2.5

absorbance, NO2), season of conception

Dose-response Investigated? Yes 

Statistical Package: STATA 

Mean (SD): 1.76 * 

Percentiles: 25th: 1.61* 

50th(Median): 1.72* 

75th: 1.89 * 

Unit (i.e. μg/m3): 10-5/m 

Monitoring Stations: 

Spatial component: 40 

Temporal component: 1 

Copollutant (correlation): 

p.a. = pregnancy avg 

trim. = trimester 

abs = absorbance 

PM2.5 abs (p.a.)-PM2.5 abs (1st trim.): 

0.54 

PM2.5 abs (p.a.)-PM2.5 abs (2nd trim.): 

0.84 

PM2.5 abs (p.a.)-PM2.5 abs (3rd trim.): 

0.55 

PM2.5 abs (p.a.)-PM2.5 (p.a.): 0.69 

PM2.5 abs (p.a.)-PM2.5 (1st trim.): 0.68 

PM2.5 abs (p.a.)-PM2.5 (2nd trim.): 0.41 

PM2.5 abs (p.a.)-PM2.5 (3rd trim.): 0.62 

PM2.5 abs (p.a.)-NO2 (p.a.): 0.67 

PM2.5 abs (p.a.)-NO2 (1st trim.): 0.34 

PM2.5 abs (p.a.)-NO2 (2nd trim.): 0.63 

PM2.5 abs (p.a.)-NO2 (3rd trim.): 0.36 

PM2.5 abs (1st trim.)-PM2.5 abs (2nd 

trim.): 0.32 

PM2.5 abs (1st trim.)-PM2.5 abs (3rd 

trim.): -0.26 

PM2.5 abs (1st trim.)-PM2.5 (p.a.): 0.33 

PM2.5 abs (1st trim.)-PM2.5 (1st trim.): 

0.27 

PM2.5 abs (1st trim.)-PM2.5 (2nd trim.): 

0.08 

PM2.5 abs (1st trim.)-PM2.5 (3rd trim.): 

0.48 

PM2.5 abs (1st trim.)-NO2 (p.a.): 0.29 

PM2.5 abs (1st trim.)-NO2 (1st trim.): 0.84

PM2.5 abs (1st trim.)-NO2 (2nd trim.): 

0.16 

PM2.5 abs (1st trim.)-NO2 (3rd trim.): -

0.39 

PM2.5 abs (2nd trim.)-PM2.5 abs (3rd 

trim.): 0.31 

PM2.5 abs (2nd trim.)-PM2.5 (p.a.): 0.48 

PM2.5 abs (2nd trim.)-PM2.5 (1st trim.): 

0.53 

PM2.5 abs (2nd trim.)-PM2.5 (2nd trim.): 

0.29 

PM2.5 abs (2nd trim.)-PM2.5 (3rd trim.): 

0.36 

PM2.5 abs (2nd trim.)-NO2 (p.a.): 0.61 

PM2.5 abs (2nd trim.)-NO2 (1st trim.): 

0.19 

PM2.5 abs (2nd trim.)-NO2 (2nd trim.): 

0.85 

PM2.5 abs (2nd trim.)-NO2 (3rd trim.): 

0.17 

PM2.5 abs (3rd trim.)-PM2.5 (p.a.): 0.52 

PM2.5 abs (3rd trim.)-PM2.5 (1st trim.): 

0.51 

PM2.5 abs (3rd trim.)-PM2.5 (2nd trim.): 

0.41 

PM2.5 abs (3rd trim.)-PM2.5 (3rd trim.): 

0.37 

PM2.5 abs (3rd trim.)-NO2 (p.a.): 0.40 

PM2.5 abs (3rd trim.)-NO2 (1st 

trim.):-0.34 

PM2.5 abs (3rd trim.)-NO2 (2nd trim.): 

0.21 

PM2.5 abs (3rd trim.)-NO2 (3rd trim.): 

0.88 

c) 3rd (1.72-1.89) 

day) 4th (1.89-3.10)

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy 

Single-pollutant models Unadjusted 

models

2nd quartile: 1.19 (0.74, 1.99) 

3rd quartile: 1.56 (0.98, 2.50); 

4th quartile: 1.52 (0.96, 2.46) 

Per 0.5 * 10-5/m: 1.25 (0.90, 1.70) 

Adjusted models 

2nd quartile: 1.21 (0.73, 1.97) 

3rd quartile: 1.63 (0.98, 2.57); 

4th quartile: 1.78 (1.10, 2.70) 

Per 0.5 * 10-5/m: 1.45 (1.06, 1.87) 

Multipollutant models Adjusted models

2nd quartile: 1.19 (0.70, 2.01) 

3rd quartile: 1.55 (0.80, 2.80); 

4th quartile: 1.46 (0.67, 2.90) 

Per 0.5 * 10-5/m: 1.33 (0.76, 2.38) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy (adjustment for 

season of conception) 

4th quartile: 1.72 (1.08, 2.73) 

Per 0.5 * 10-5/m: 1.38 (0.96, 1.86) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy 

Single-pollutant models 

(Restricted analysis to PM2.5 below the 

median)

Per 0.5 * 10-5/m: 1.67 (0.66, 3.73) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

first trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.15 (0.73, 1.80) 

3rd quartile: 1.01 (0.61, 1.53); 

4th quartile: 1.04 (0.70, 1.57) 

Per 0.5 * 10-5/m: 1.03 (0.82, 1.28) 

All trimesters adjusted simultaneously 

2nd quartile: 0.90 (0.52, 1.58) 

3rd quartile: 0.82 (0.45, 1.31); 

4th quartile: 0.88 (0.53, 1.42) 

Per 0.5 * 10-5/m: 1.02 (0.77, 1.29) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

second trimester of pregnancy 

Each trimester separately

2nd quartile: 1.33 (0.85, 2.22) 

3rd quartile: 1.76 (1.07, 2.91); 

4th quartile: 1.83 (1.11, 2.81) 

Per 0.5 * 10-5/m: 1.27 (1.04, 1.54) 

All trimesters adjusted simultaneously 

2nd quartile: 1.30 (0.77, 2.16) 

3rd quartile: 1.63 (0.93, 2.73); 

4th quartile: 1.99 (1.12, 3.33) 

Per 0.5 * 10-5/m: 1.21 (0.93, 1.54) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.30 (0.85, 2.09) 

3rd quartile: 0.92 (0.55, 1.50); 

4th quartile: 1.50 (1.00, 2.27) 

Per 0.5 * 10-5/m: 1.20 (0.98, 1.44) 

All trimesters adjusted simultaneously 

2nd quartile: 0.99 (0.64, 1.62) 

3rd quartile: 0.71 (0.40, 1.20); 

December 2009 E-484 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

4th quartile: 1.14 (0.68, 1.91) 

Per 0.5 * 10-5/m: 1.15 (0.92, 1.42) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

first trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

4th quartile: 0.73 (0.38, 1.38) 

Per 0.5 * 10-5/m: 0.93 (0.41, 1.32) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

second trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

4th quartile: 2.45 (1.22, 4.77) 

Per 0.5 * 10-5/m: 1.14 (0.70, 1.64) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

4th quartile: 1.19 (0.60, 2.48) 

Per 0.5 * 10-5/m: 1.29 (0.90, 1.75) 

Sensitivity analysis (bootstrapped PR) 

2nd quartile: 1.19 (0.76, 1.91) 

3rd quartile: 1.52 (0.99, 2.34); 

4th quartile: 1.62 (1.06, 2.55) 

Per 0.5 * 10-5/m: 1.35 (1.01, 1.83) 

Estimated increments in prevalence 

of birth weight <3000 g during 

exposure 9 mo after birth 

Per 0.5 * 10-5/m: 18% (-16%, 57%)

Reference: Wilhelm et al. (2005, 

088668) 

Period of Study: 1994-2000 

Location: Los Angeles County, 

California, U.S. 

Outcome: Term low birth weight (LBW) 

(<2500 g at ≥ 37 completed wk 

gestation) 

Vaginal birth <37 completed wk 

gestation 

Age Groups: LBW: ≥ 37 completed wk 

Preterm births: <37 completed wk 

Study Design: Cross-sectional study

N: For LBW: 136,134 

For preterm birth: 

106,483 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, maternal 

race, maternal education, parity, interval 

since previous live birth, level of prenatal 

care, infant sex, previous LBW or 

preterm infant, birth season, other 

pollutants (not specified in birth weight 

analyses, also adjusted for gestational 

age) 

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM2.5 

Averaging Time: 24 h (every 3 days) 

Entire pregnancy 

Trimesters of pregnancy 

Months of pregnancy 

6 wk before birth 

Mean (SD): 

First trimester: 21.9 

Third trimester: 21.0 

6 wk before birth: 21.0 

Range (Min, Max): 

First trimester: 11.8-38.9 

Third trimester: 11.8-.38.9 

6 wk before birth: 9.9-48.5 

Monitoring Stations: 

Zip-code-level analysis: 9 

Address-level analysis: 8 

Copollutant (correlation): 

First trimester 

PM2.5-CO: 0.57 

PM2.5-NO2: 0.73 

PM2.5-O3: -0.55 

PM2.5-PM10: 0.43 

Third trimester: 

PM2.5-CO: 0.67 

PM2.5-NO2: 0.78 

PM2.5-O3: -0.60 

PM2.5-PM10: 0.52 

6 wk before birth: 

PM2.5-CO: 0.63 

PM2.5-NO2: 0.74 

PM2.5-O3: -0.60 

PM2.5-PM10: 0.60 

PM Increment: 

1) 10 μg/m3

2) 3 levels: 

a) <25 percentile (reference) 

b) 25%-75 percentile 

c) ≥ 75 percentile 

Incidence of LBW (third trimester 

exposure) 

<17.1 μg/m3: 2.4 (2.0, 2.8) 

17.1 to <24.0 μg/m3

: 2.2 (2.0, 2.5) 

≥ 24.0 μg/m3

: 2.1 (1.7, 2.4) 

Incidence of preterm birth (first 

trimester exposure) 

<18.0 μg/m3: 10.6 (9.6, 11.7) 

18.0 to <25.4 μg/m3

: 8.8 (8.1, 9.5) 

≥ 25.4 μg/m3

: 9.0 (8.1, 10.0) 

Incidence of preterm birth (6 wk 

before birth exposure) 

<16.5 μg/m3: 8.2 (7.4, 9.1) 

16.5 to <24.7 μg/m3

: 8.8 (8.2, 9.4) 

≥ 24.7 μg/m3

: 9.6 (8.7, 10.5) 

Outcome: Preterm birth 

Exposure Period: First trimester of 

pregnancy 

Address-level analysis: 

Single-pollutant model: Distance ≤ 1 

mile 

Per 10 μg/m3

: 0.85 (0.70, 1.02) 

18.1 to <25.2 μg/m3

: 0.91 (0.72, 1.16) 

≥ 25.2 μg/m3

: 0.83 (0.60, 1.14) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 0.85 (0.74, 0.99) 

18.3 to <25.2 μg/m3

: 0.81 (0.69, 0.94) 

December 2009 E-485 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

≥ 25.2 μg/m3: 0.79 (0.65, 0.97) 

Multipollutant model1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.18 (0.84, 1.65) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 0.83 (0.78, 0.88) 

18.5 to <24.9 μg/m3

: 0.79 (0.74, 0.85) 

≥ 24.9 μg/m3

: 0.76 (0.70, 0.84) 

Zip-code-level analysis: 

Single-pollutant model: 

Per 10 μg/m3: 0.73 (0.67, 0.80) 

18.0 to <25.4 μg/m3

: 0.70 (0.61, 0.80) 

≥ 25.4 μg/m3

: 0.64 (0.53, 0.76) 

Outcome: Preterm birth 

Exposure Period: 6 wk before birth 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3

: 1.09 (0.91, 1.30) 

16.8 to <24.1 μg/m3

: 1.21 (0.97, 1.51) 

≥ 24.1 μg/m3

: 1.25 (0.93, 1.68) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.08 (0.97, 1.21) 

17.2 to <24.5 μg/m3: 0.94 (0.82, 1.08) 

≥ 24.5 μg/m3

: 1.04 (0.87, 1.24) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 1.05 (0.99, 1.10) 

17.3 to <24.6 μg/m3

: 1.06 (1.00, 1.13) 

≥ 24.6 μg/m3: 1.08 (0.99, 1.17) 

Zip-code-level analysis 

Single-pollutant model: Per 10 μg/m3: 

1.10 (1.00, 1.21) 

16.5 to <24.7 μg/m3

: 1.06 (0.94, 1.20) 

≥ 24.7 μg/m3: 1.19 (1.02, 1.40) 

(See Notes) 

Multipollutant model 

Per 10 μg/m3: 1.12 (0.90, 1.40) 

≥ 24.6 μg/m3

: 1.12 (0.82, 1.52) 

Notes: In the table, the 75 percentile is 

noted as 24.7 μg/m3. However, the text 

notes the 75 percentile as 24.3 μg/m3

. 

December 2009 E-486 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Woodruff et al. (2006, 

088758) 

Period of Study: 1999-2000 

Location: California 

Outcome (ICD10): SIDS (R95) 

Respiratory mortality (J00-J99) 

Bronchopulmonary dysplasia (P27.1) 

External accidents (V01-Y98) 

Ill-defined and unspecified causes of 

mortality (R99) 

Age Groups: >28 days old 

Study Design: Matched case-control 

(matched on date of birth and birth 

weight)

N: 3877 infants 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Maternal race, education, 

parity, age, marital status 

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM2.5 

Averaging Time: 24 hrs (every 6 days) 

(time period between birth and post 

neonatal death for the infant who died 

and the same period for its four matched 

surviving infants) 

Percentiles: Infants who died of all 

causes (cases) 

25th: 13.4

50th(Median): 19.2

75th: 23.6 

Matched controls 

25th: 13.5

50th(Median): 18.4

75th: 22.7 

Monitoring Stations: 

73 (from 39 counties) 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] lag: 

All-cause mortality: 

Unadjusted: 1.15 (1.00, 1.32) 

Adjusted: 1.07 (0.93, 1.24) 

Cause-specific mortality: 

Respiratory (all): 

Unadjusted: 2.15 (1.15, 4.02) 

Adjusted: 2.13 (1.12, 4.05) 

Respiratory (excluding deaths due to 

BPD): 

Adjusted: 1.42 (0.66, 3.03) 

Respiratory (BPD alone): 

Unadjusted: 6.00 (1.40, 27.76) 

Respiratory (low birth weight infants 

only): 

Unadjusted: 3.09 (1.14, 8.40) 

Respiratory (normal birth weight infants 

only): 

Unadjusted: 1.66 (0.74, 3.70) 

Respiratory (with matched PM2.5 avgd 

over all monitors in county) 

Adjusted: 2.28 (0.94, 5.52) 

Respiratory (averaging all PM2.5

measurements in county over the 2-yr 

study period): 

Adjusted: 2.26 (0.83, 6.21) 

SIDS: 

Unadjusted: 0.86 (0.61, 1.22) 

Adjusted: 0.82 (0.55, 1.23) 

SIDS (includes ICD10 code R99: illdefined and unspecified causes of 

mortality): 

Adjusted: 1.03 (0.79, 1.35) 

External causes: 

 Unadjusted: 0.91 (0.56, 1.47) 

Adjusted: 0.83 (0.50, 1.39) 

Compare against the lowest quartile, 

estimates for respiratory-specific 

mortality were provided: 

2nd quartile: 1.28 (0.47, 3.51) 

3rd quartile: 1.75 (0.65, 4.72) 

4th quartile: 2.35 (0.85, 6.54) 

December 2009 E-487 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Woodruff et al. (2008, 

098386) 

Period of Study: 1999-2002 

Location: U.S. counties with >250,000 

residents (96 counties) 

Outcome (ICD10): Postneonatal 

deaths: Respiratory mortality (J000-99, 

plus bronchopulmonary dysplasia [BPD] 

P27.1) 

SIDS (R95) 

Ill-defined causes (R99) 

All other deaths evaluated as a control 

category 

Age Groups: Infants aged >28 days 

and <1 yr 

Study Design: Cross-sectional

N: 3,583,495 births (6,639 post neonatal 

deaths) 

Statistical Analyses: Logistic GEE 

(exchangeable correlation structure) 

Covariates: maternal race/ethnicity, 

marital status, age, education, 

primiparity, county-level poverty and per 

capita income levels, yr and month of 

birth dummy variables to account for 

time trend and seasonal effects, and 

region of the country 

sensitivity analyses performed among 

only those mothers with smoking 

information (adjustment for smoking had 

no effect on the estimates) 

Season: Adjusted for yr and month of 

birth dummy variables to account for 

time trend and seasonal effects 

Dose-response Investigated? 

Evaluated the appropriateness of a 

linear form from analysis based on 

quartiles of exposure and concluded that 

linear form was appropriate (data not 

shown) 

Statistical Package: SAS 

Pollutant: PM2.5 

Averaging Time: Measured 

continuously for 24 h once every 6 days 

exposure assigned by calculating avg 

concentration of pollutant during first 2 

mo of life 

Median and IQR (25th-75th 

percentile): 

Survivors: 14.8 (11.7-18.7) 

All causes of death: 14.9 (12.0-18.6) 

Respiratory: 14.8 (11.5-18.5) 

SIDS: 14.5 (12.0-17.5) 

SIDS + ill-defined: 14.8 (12.1-18.5) 

Other causes: 14.9 (12.0-18.6) 

Percentiles: See above 

PM Component: Not assessed, but 

controlled for region of the country to 

account for PM composition variation 

Monitoring Stations: NR 

Copollutant (correlation): 

PM10 (r = 0.34) 

PM2.5

CO (r = 0.35) 

SO2 (r = 0.21) 

O3 (r = -0.10) 

Notes: Monthly avg calculated if there 

were at least 3 available measures for 

PM 

Assigned exposures using the avg 

concentration of the county of residence 

PM Increment: IQR (7 μg/m3) 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted ORs for single pollutant models

All causes: 1.04 (0.98, 1.11) 

Respiratory: 1.11 (0.96, 1.29) 

SIDS: 1.01 (0.86, 1.20) 

Ill-defined + SIDS: 1.06 (0.97, 1.17) 

Other causes: 1.03 (0.96, 1.12) 

Adjusted ORs for multipollutant models 

(including CO, O3, SO2) 

Respiratory: 1.05 (0.89, 1.24) 

SIDS: 1.04 (0.87, 1.23) 

OR for respiratory deaths assessing 

exposure as quartiles 

Highest vs. Lowest quartile: 1.39 (1.04, 

1.85) 

1

All units expressed in μg/m3 unless otherwise specified.

December 2009 E-488 
E.8.Long-Term Exposure and Mortality 

Table E-30. Long-term exposure-mortality - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Breitner et al., 2009, 

188439) 

Period of Study: Oct 1991-Mar 2002 

Location: Efurt, Germany 

Outcome: Mortality, excluding infants 

and ICD-9 ≥ 800 

Study Design: Time-series 

Covariates: Seasonal and weekday 

variations, influenza epidemics, air 

temperature, relative humidity 

Statistical Analysis: Semiparametric 

Poisson regression, polynomial 

distributed lag (PDL) 

Statistical Package: R 

Age Groups: All 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD) Unit: 

1 (10/1/1991-8/31/1995): 

50.6 ± 32.2 μg/m3

2 (9/1/1995-2/28/1998): 

41.1 ± 28.4 μg/m3

3 (3/1/1998-3/31/2002): 

24.3 ± 15.4 μg/m3

Total: 38.0 ±28.3 μg/m3

Range (Min, Max): NR 

Copollutant: NO2, CO, UFP 

Increment: IQR 

Relative Risk (95% CI) Lag 

New City Limits 

6-day IQR: 17.2 

PDL: 0.997 (0.972-1.022) 

Mean of lags 0-5: 0.995 (0.971-1.019) 

Old City Limits 

6-day IQR: 17.2 

PDL: 1.004 (0.978-1.031) 

Mean of lags 0-5: 1.001 (0.976-1.027) 

New City Limits 

15-day IQR: 14.5 

PDL: 1.008 (0.982-1.036) 

Mean of lags 0-14: 1.006 (0.981-1.032) 

Old City Limits 

15-day IQR: 14.5 

PDL: 1.019 (0.991-1.048) 

Mean of lags 0-14: 1.017 (0.990-1.044) 

Multiday Ma, 6-day 

Overall IQR: 24.2 

Overall RR (95% CI): 

0.998 (0.976-1.021) 

Period 1: 0.996 (0.969-1.024) 

Period 2: 1.013 (0.972-1.056) 

Period 3: 0.949 (0.897-1.004) 

Multiday Ma, 15-day 

Overall IQR: 22.3 

Overall RR (95% CI): 

1.020 (0.993-1.093) 

Period 1: 1.017 (0.984-1.051) 

Period 2: 1.012 (0.973-1.071) 

Period 3: 0.978 (0.911-1.051) 

Reference: (Slama et al., 2007, 

093216) 

Period of Study: Jan 1998-Jan 1999 

Location: Munich, Germany 

Outcome: Birth weight offspring at term 

Study Design: Cohort study

N: 1016 births 

Statistical Analyses: Poisson model 

Covariates: Maternal passive smoking, 

maternal age, gestational duration, sex 

of child, parity, maternal education, 

maternal size, prepregnancy weight, 

other pollutants (PM2.5, PM2.5

absorbance, NO2), season of conception

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM2.5 (estimated based on 

larger PM size fractions) 

Averaging Time: Entire pregnancy 

period and trimesters 

Mean (SD): 14.4 

Percentiles: 25th: 13.5

50th(Median): 14.4 

75th: 15.4 

Monitoring Stations: 

Spatial component: 40 

Temporal component: 1 

Copollutant (correlation): 

p.a. = pregnancy avg 

trim. = trimester 

PM2.5 (p.a.)-PM2.5 (1st trim.): 0.85 

PM2.5 (p.a.)-PM2.5 (2nd trim.): 0.77 

PM2.5 (p.a.)-PM2.5 (3rd trim.): 0.87 

PM2.5 (p.a.)-NO2 (p.a.): 0.45 

PM2.5 (p.a.)-NO2 (1st trim.): 0.18 

PM2.5 (p.a.)-NO2 (2nd trim.): 0.32 

PM Increment: 

1) 1 μg/m3

2) Quartiles: 

a) 1st (reference) (7.2-13.5 μg/m3

) 

b) 2nd (13.5-14.4 μg/m3

) 

c) 3rd (14.4-15.4 μg/m3

) 

day) 4th (15.41-17.5 μg/m3

) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy 

Single-pollutant models 

Unadjusted models 

2nd quartile: 1.07 (0.65, 1.73); 3rd 

quartile: 1.38 (0.91, 2.09) 

4th quartile: 1.45 (0.92, 2.25) 

Per 1 μg/m3

: 1.06 (0.95, 1.19) 

Adjusted models 

2nd quartile: 1.08 (0.63, 1.82); 3rd 

quartile: 1.34 (0.86, 2.13) 

4th quartile: 1.73 (1.15, 2.69); Per 

1 μg/m3

: 1.13 (1.00, 1.29) 

Multipollutant models 

Adjusted models 

2nd quartile: 1.01 (0.57, 1.85) 

3rd quartile: 1.12 (0.64, 1.87) 

4th quartile: 1.36 (0.72, 2.45); Per 

1 μg/m3

: 1.07 (0.91, 1.26) 

Single-pollutant models (restricted 

December 2009 E-489 
Study Design & Methods Concentrations

1 Effect Estimates (95% CI) 

PM2.5 (p.a.)-NO

2 (3rd trim.): 0.37 

PM2.5 (1st trim.)-PM2.5 (2nd trim.): 0.40 

PM2.5 (1st trim.)-PM2.5 (3rd trim.): 0.68 

PM2.5 (1st trim.)-NO

2 (p.a.): 0.48 

PM2.5 (1st trim.)-NO

2 (1st trim.): 0.15 

PM2.5 (1st trim.)-NO

2 (2nd trim.): 0.41 

PM2.5 (1st trim.)-NO

2 (3rd trim.): 0.39 

PM2.5 (2nd trim.)-PM2.5 (3rd trim.): 0.51 

PM2.5 (2nd trim.)-NO

2 (p.a.): 0.23 

PM2.5 (2nd trim.)-NO

2 (1st trim.): -0.03 

PM2.5 (2nd trim.)-NO

2 (2nd trim.): 0.17 

PM2.5 (2nd trim.)-NO

2 (3rd trim.): 0.30 

PM2.5 (3rd trim.)-NO

2 (p.a.): 0.39 

PM2.5 (3rd trim.)-NO

2 (1st trim.): 0.33 

PM2.5 (3rd trim.)-NO

2 (2nd trim.): 0.21 

PM2.5 (3rd trim.)-NO

2 (3rd trim.): 0.23 

PM2.5 (p.a.)- PM2.5 absorbance (p.a.): 

0.69 

PM2.5 (p.a.)- PM2.5 abs (1st trim.): 0.33 

PM2.5 (p.a.)- PM2.5 abs (2nd trim.): 0.48 

PM2.5 (p.a.)- PM2.5 abs (3rd trim.): 0.52 

PM2.5 (1st trim.)- PM2.5 abs (p.a.): 0.68 

PM2.5 (1st trim.)- PM2.5 abs (1st trim.): 

0.27 

PM2.5 (1st trim.)- PM2.5 abs (2nd trim.): 

0.53 

PM2.5 (1st trim.)- PM2.5 abs (3rd trim.): 

0.51 

PM2.5 (2nd trim.)- PM2.5 abs(p.a.): 0.41 

PM2.5 (2nd trim.)- PM2.5 abs (1st trim.): 

0.08 

PM2.5 (2nd trim.)- PM2.5 abs (2nd trim.): 

0.29 

PM2.5 (2nd trim.)- PM2.5 abs (3rd trim.): 

0.41 

PM2.5 (3rd trim.)- PM2.5 abs (p.a.): 0.62 

PM2.5 (3rd trim.)- PM2.5 abs (1st trim.): 

0.48 

PM2.5 (3rd trim.)- PM2.5 abs (2nd trim.): 

0.36 

PM2.5 (3rd trim.)- PM2.5 abs (3rd trim.): 

0.37 

Analysis to PM2.5 absorbance below the 

median) 

Per 1 μg/m

3

: 1.15 (0.89, 1.52) 

Prevalence ratios (PRs) of birth 

weight <3000 g 

Multipollutant models (simultaneous 

adjustment of 3rd trimester PM2.5 and 

whole pregnancy PM2.5) 

PM2.5 (whole pregnancy) 

Per 1 μg/m

3

: 0.96 (0.75, 1.19) 

PM2.5 (3rd trimester) 

Per 1 μg/m

3

: 1.17 (0.98, 1.40) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy (adjustment for 

season of conception) 

4th quartile: 1.68 (1.05, 2.75); Per 

1 μg/m

3

: 1.12 (0.97, 1.28) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

first trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.14 (0.74, 1.96); 3rd 

quartile: 1.28 (0.84, 2.10) 

4th quartile: 1.65 (1.02, 2.60) 

Per 1 μg/m

3

: 1.10 (0.99, 1.20) 

All trimesters adjusted simultaneously 

2nd quartile: 0.97 (0.60, 1.73); 3rd 

quartile: 0.98 (0.57, 1.75) 

4th quartile: 1.22 (0.71, 2.18) 

Per 1 μg/m

3

: 1.03 (0.90, 1.17) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

second trimester of pregnancy 

Each trimester separately 

2nd quartile: 0.83 (0.52, 1.32); 3rd 

quartile: 1.08 (0.71, 1.60) 

4th quartile: 0.94 (0.61, 1.47) 

Per 1 μg/m

3

: 1.01 (0.92, 1.12) 

All trimesters adjusted simultaneously 

2nd quartile: 0.75 (0.46, 1.24) 

3rd quartile: 0.86 (0.56, 1.30); 

4th quartile: 0.75 (0.48, 1.23) 

Per 1 μg/m

3

: 0.94 (0.84, 1.06) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.30 (0.80, 2.17) 

3rd quartile: 1.44 (0.85, 2.27) 

4th quartile: 1.90 (1.20, 2.82) 

Per 1 μg/m

3

: 1.14 (1.02, 1.24) 

All trimesters adjusted simultaneously 

2nd quartile: 1.34 (0.79, 2.30) 

3rd quartile: 1.48 (0.86, 2.58) 

4th quartile: 1.91 (1.00, 3.20) 

Per 1 μg/m

3

: 1.14 (0.99, 1.29) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

Per 1 μg/m

3

: 1.25 (1.04, 1.50) 

Sensitivity analysis(bootstrapped PR)

2nd quartile: 0.98 (0.63, 1.61); 3rd 

quartile: 1.22 (0.82, 2.02) 

4th quartile: 1.57 (1.02, 2.57) 

Per 1 μg/m

3

: 1.11 (0.98, 1.27) 

Estimated increments in prevalence 

of birth weight of <3000 g during 

exposure 9 mo after birth 

December 2009 E-490 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Per 1 μg/m3: 7% (-7%, 22%)

Reference: (Slama et al., 2007, 

093216) 

Period of Study: Jan 1998-Jan 1999 

Location: Munich, Germany 

Outcome: Birth weight offspring at term 

Study Design: Cohort study

N: 1016 births 

Statistical Analyses: Poisson model 

Covariates: Maternal passive smoking, 

maternal age, gestational duration, sex 

of child, parity, maternal education, 

maternal size, prepregnancy weight, 

other pollutants (PM2.5, PM2.5

absorbance, NO2), season of conception

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM2.5 absorbance (estimated)

Averaging Time: Entire pregnancy 

period and trimesters 

Mean (SD): 1.76 * 

Percentiles: 25th: 1.61* 

50th(Median): 1.72* 

75th: 1.89 * 

Unit (i.e. μg/m3): 10-5/m 

Monitoring Stations: 

Spatial component: 40 

Temporal component: 1 

Copollutant (correlation): 

p.a. = pregnancy avg 

trim. = trimester 

abs = absorbance 

PM2.5 abs (p.a.)-PM2.5 abs (1st trim.): 

0.54 

PM2.5 abs (p.a.)-PM2.5 abs (2nd trim.): 

0.84 

PM2.5 abs (p.a.)-PM2.5 abs (3rd trim.): 

0.55 

PM2.5 abs (p.a.)-PM2.5 (p.a.): 0.69 

PM2.5 abs (p.a.)-PM2.5 (1st trim.): 0.68 

PM2.5 abs (p.a.)-PM2.5 (2nd trim.): 0.41 

PM2.5 abs (p.a.)-PM2.5 (3rd trim.): 0.62 

PM2.5 abs (p.a.)-NO2 (p.a.): 0.67 

PM2.5 abs (p.a.)-NO2 (1st trim.): 0.34 

PM2.5 abs (p.a.)-NO2 (2nd trim.): 0.63 

PM2.5 abs (p.a.)-NO2 (3rd trim.): 0.36 

PM2.5 abs (1st trim.)-PM2.5 abs (2nd 

trim.): 0.32 

PM2.5 abs (1st trim.)-PM2.5 abs (3rd 

trim.): -0.26 

PM2.5 abs (1st trim.)-PM2.5 (p.a.): 0.33 

PM2.5 abs (1st trim.)-PM2.5 (1st trim.): 

0.27 

PM2.5 abs (1st trim.)-PM2.5 (2nd trim.): 

0.08 

PM2.5 abs (1st trim.)-PM2.5 (3rd trim.): 

0.48 

PM2.5 abs (1st trim.)-NO2 (p.a.): 0.29 

PM2.5 abs (1st trim.)-NO2 (1st trim.): 0.84

PM2.5 abs (1st trim.)-NO2 (2nd trim.): 

0.16 

PM2.5 abs (1st trim.)-NO2 (3rd trim.): -

0.39 

PM2.5 abs (2nd trim.)-PM2.5 abs (3rd 

trim.): 0.31 

PM2.5 abs (2nd trim.)-PM2.5 (p.a.): 0.48 

PM2.5 abs (2nd trim.)-PM2.5 (1st trim.): 

0.53 

PM2.5 abs (2nd trim.)-PM2.5 (2nd trim.): 

0.29 

PM2.5 abs (2nd trim.)-PM2.5 (3rd trim.): 

0.36 

PM2.5 abs (2nd trim.)-NO2 (p.a.): 0.61 

PM2.5 abs (2nd trim.)-NO2 (1st trim.): 

0.19 

PM2.5 abs (2nd trim.)-NO2 (2nd trim.): 

0.85 

PM2.5 abs (2nd trim.)-NO2 (3rd trim.): 

0.17 

PM2.5 abs (3rd trim.)-PM2.5 (p.a.): 0.52 

PM2.5 abs (3rd trim.)-PM2.5 (1st trim.): 

0.51 

PM2.5 abs (3rd trim.)-PM2.5 (2nd trim.): 

0.41 

PM2.5 abs (3rd trim.)-PM2.5 (3rd trim.): 

0.37 

PM2.5 abs (3rd trim.)-NO2 (p.a.): 0.40 

PM2.5 abs (3rd trim.)-NO2 (1st trim.): -

PM Increment: 

1) 0.5 * 10-5/m 

2) Quartiles: 

a) 1st (reference) (1.29-1.61) 

b) 2nd (1.61-1.72) 

c) 3rd (1.72-1.89) 

day) 4th (1.89-3.10)

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy 

Single-pollutant models 

Unadjusted models

2nd quartile: 1.19 (0.74, 1.99) 

3rd quartile: 1.56 (0.98, 2.50); 

4th quartile: 1.52 (0.96, 2.46) 

Per 0.5 * 10-5/m: 1.25 (0.90, 1.70) 

Adjusted models 

2nd quartile: 1.21 (0.73, 1.97) 

3rd quartile: 1.63 (0.98, 2.57); 

4th quartile: 1.78 (1.10, 2.70) 

Per 0.5 * 10-5/m: 1.45 (1.06, 1.87) 

Multipollutant models Adjusted models

2nd quartile: 1.19 (0.70, 2.01) 

3rd quartile: 1.55 (0.80, 2.80); 

4th quartile: 1.46 (0.67, 2.90) 

Per 0.5 * 10-5/m: 1.33 (0.76, 2.38) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy (adjustment for 

season of conception) 

4th quartile: 1.72 (1.08, 2.73) 

Per 0.5 * 10-5/m: 1.38 (0.96, 1.86) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

the whole pregnancy 

Single-pollutant models 

(Restricted analysis to PM2.5 below the 

median)

Per 0.5 * 10-5/m: 1.67 (0.66, 3.73) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

first trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.15 (0.73, 1.80) 

3rd quartile: 1.01 (0.61, 1.53); 

4th quartile: 1.04 (0.70, 1.57) 

Per 0.5 * 10-5/m: 1.03 (0.82, 1.28) 

All trimesters adjusted simultaneously 

2nd quartile: 0.90 (0.52, 1.58) 

3rd quartile: 0.82 (0.45, 1.31); 

4th quartile: 0.88 (0.53, 1.42) 

Per 0.5 * 10-5/m: 1.02 (0.77, 1.29) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

second trimester of pregnancy 

Each trimester separately

2nd quartile: 1.33 (0.85, 2.22) 

3rd quartile: 1.76 (1.07, 2.91); 

4th quartile: 1.83 (1.11, 2.81) 

Per 0.5 * 10-5/m: 1.27 (1.04, 1.54) 

All trimesters adjusted simultaneously 

2nd quartile: 1.30 (0.77, 2.16) 

3rd quartile: 1.63 (0.93, 2.73); 

4th quartile: 1.99 (1.12, 3.33) 

Per 0.5 * 10-5/m: 1.21 (0.93, 1.54) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

Each trimester separately 

2nd quartile: 1.30 (0.85, 2.09) 

3rd quartile: 0.92 (0.55, 1.50); 

December 2009 E-491 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

0.34 

PM2.5 abs (3rd trim.)-NO2 (2nd trim.): 

0.21 

PM2.5 abs (3rd trim.)-NO2 (3rd trim.): 

0.88 

4th quartile: 1.50 (1.00, 2.27) 

Per 0.5 * 10-5/m: 1.20 (0.98, 1.44) 

All trimesters adjusted simultaneously 

2nd quartile: 0.99 (0.64, 1.62) 

3rd quartile: 0.71 (0.40, 1.20); 

4th quartile: 1.14 (0.68, 1.91) 

Per 0.5 * 10-5/m: 1.15 (0.92, 1.42) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

first trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

4th quartile: 0.73 (0.38, 1.38) 

Per 0.5 * 10-5/m: 0.93 (0.41, 1.32) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

second trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

4th quartile: 2.45 (1.22, 4.77) 

Per 0.5 * 10-5/m: 1.14 (0.70, 1.64) 

Prevalence ratios (PRs) of birth 

weight <3000 g during exposure over 

third trimester of pregnancy 

(adjustment for season of 

conception) 

All trimesters adjusted simultaneously 

4th quartile: 1.19 (0.60, 2.48) 

Per 0.5 * 10-5/m: 1.29 (0.90, 1.75) 

Sensitivity analysis (bootstrapped PR) 

2nd quartile: 1.19 (0.76, 1.91) 

3rd quartile: 1.52 (0.99, 2.34); 

4th quartile: 1.62 (1.06, 2.55) 

Per 0.5 * 10-5/m: 1.35 (1.01, 1.83) 

Estimated increments in prevalence 

of birth weight <3000 g during 

exposure 9 mo after birth Per 0.5 * 10-

5/m: 18% (-16%, 57%)

Reference: Wilhelm et al. (2005, 

088668) 

Period of Study: 1994-2000 

Location: Los Angeles County, 

California, U.S. 

Outcome: Term low birth weight (LBW) 

(<2500 g at ≥ 37 completed wk 

gestation) 

Vaginal birth <37 completed wk 

gestation 

Age Groups: LBW: ≥ 37 completed wk 

Preterm births: <37 completed wk 

Study Design: Cross-sectional study

N: For LBW: 136,134 

For preterm birth: 

106,483 

Statistical Analyses: Logistic 

regression 

Covariates: Maternal age, maternal 

race, maternal education, parity, interval 

since previous live birth, level of prenatal 

care, infant sex, previous LBW or 

preterm infant, birth season, other 

pollutants (not specified in birth weight 

analyses, also adjusted for gestational 

age) 

Dose-response Investigated? Yes 

Statistical Package: NR 

Pollutant: PM2.5 

Averaging Time: 24 h (every 3 days) 

Entire pregnancy 

Trimesters of pregnancy 

Months of pregnancy 

6 wk before birth 

Mean (SD): 

First trimester: 21.9 

Third trimester: 21.0 

6 wk before birth: 21.0 

Range (Min, Max): 

First trimester: 11.8-38.9 

Third trimester: 11.8-.38.9 

6 wk before birth: 9.9-48.5 

Monitoring Stations: 

Zip-code-level analysis: 9 

Address-level analysis: 8 

Copollutant (correlation): 

First trimester 

PM2.5-CO: 0.57 

PM2.5-NO2: 0.73 

PM2.5-O3: -0.55 

PM2.5-PM10: 0.43 

Third trimester: 

PM2.5-CO: 0.67 

PM2.5-NO2: 0.78 

PM2.5-O3: -0.60 

PM2.5-PM10: 0.52 

6 wk before birth: 

PM Increment: 

1) 10 μg/m3

2) 3 levels: 

a) <25 percentile (reference) 

b) 25%-75 percentile 

c) ≥ 75 percentile 

Incidence of LBW (third trimester 

exposure) 

<17.1 μg/m3: 2.4 (2.0, 2.8) 

17.1 to <24.0 μg/m3

: 2.2 (2.0, 2.5) 

≥ 24.0 μg/m3

: 2.1 (1.7, 2.4) 

Incidence of preterm birth (first 

trimester exposure) 

<18.0 μg/m3: 10.6 (9.6, 11.7) 

18.0 to <25.4 μg/m3

: 8.8 (8.1, 9.5) 

≥ 25.4 μg/m3

: 9.0 (8.1, 10.0) 

Incidence of preterm birth (6 wk 

before birth exposure) 

<16.5 μg/m3: 8.2 (7.4, 9.1) 

16.5 to <24.7 μg/m3: 8.8 (8.2, 9.4) 

≥ 24.7 μg/m3

: 9.6 (8.7, 10.5) 

Outcome: Preterm birth 

Exposure Period: First trimester of 

pregnancy 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3: 0.85 (0.70, 1.02) 

18.1 to <25.2 μg/m3

: 

December 2009 E-492 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

PM2.5-CO: 0.63 

PM2.5-NO2: 0.74 

PM2.5-O3: -0.60 

PM2.5-PM10: 0.60 

0.91 (0.72, 1.16) 

≥ 25.2 μg/m3

: 0.83 (0.60, 1.14) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 0.85 (0.74, 0.99) 

18.3 to <25.2 μg/m3

: 0.81 (0.69, 0.94) 

≥ 25.2 μg/m3

: 0.79 (0.65, 0.97) 

Multipollutant model1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.18 (0.84, 1.65) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 0.83 (0.78, 0.88) 

18.5 to <24.9 μg/m3

: 0.79 (0.74, 0.85) 

≥ 24.9 μg/m3

: 0.76 (0.70, 0.84) 

Zip-code-level analysis: 

Single-pollutant model: 

Per 10 μg/m3: 0.73 (0.67, 0.80) 

18.0 to <25.4 μg/m3

: 0.70 (0.61, 0.80) 

≥ 25.4 μg/m3

: 0.64 (0.53, 0.76) 

Outcome: Preterm birth 

Exposure Period: 6 wk before birth 

Address-level analysis: 

Single-pollutant model: 

Distance ≤ 1 mile 

Per 10 μg/m3

: 1.09 (0.91, 1.30) 

16.8 to <24.1 μg/m3

: 1.21 (0.97, 1.51) 

≥ 24.1 μg/m3

: 1.25 (0.93, 1.68) 

Single-pollutant model: 

1 <distance ≤ 2 mile 

Per 10 μg/m3

: 1.08 (0.97, 1.21) 

17.2 to <24.5 μg/m3: 0.94 (0.82, 1.08) 

≥ 24.5 μg/m3

: 1.04 (0.87, 1.24) 

Single-pollutant model: 

2 <distance ≤ 4 mile 

Per 10 μg/m3

: 1.05 (0.99, 1.10) 

17.3 to <24.6 μg/m3

: 1.06 (1.00, 1.13) 

≥ 24.6 μg/m3: 1.08 (0.99, 1.17) 

Zip-code-level analysis 

Single-pollutant model: 

Per 10 μg/m3

: 1.10 (1.00, 1.21) 

16.5 to <24.7 μg/m3

: 1.06 (0.94, 1.20) 

≥ 24.7 μg/m3: 1.19 (1.02, 1.40) 

(See Notes) 

Multipollutant model 

Per 10 μg/m3

: 1.12 (0.90, 1.40) 

≥ 24.6 μg/m3

: 1.12 (0.82, 1.52) 

Notes: In the table, the 75 percentile is 

noted as 24.7 μg/m3

. However, the text 

notes the 75 percentile as 24.3 μg/m3

. 

December 2009 E-493 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Woodruff et al. (2006, 

088758) 

Period of Study: 1999-2000 

Location: California 

Outcome (ICD10): SIDS (R95) 

Respiratory mortality (J00-J99) 

Bronchopulmonary dysplasia (P27.1) 

External accidents (V01-Y98) 

Ill-defined and unspecified causes of 

mortality (R99) 

Age Groups: >28 days old 

Study Design: Matched case-control 

(matched on date of birth and birth 

weight)

N: 3877 infants 

Statistical Analyses: Conditional 

logistic regression 

Covariates: Maternal race, education, 

parity, age, marital status 

Dose-response Investigated? Yes 

Statistical Package: STATA 

Pollutant: PM2.5 

Averaging Time: 24 h (every 6 days) 

(time period between birth and post 

neonatal death for the infant who died 

and the same period for its four matched 

surviving infants) Percentiles: Infants 

who died of all causes (cases) 

25th: 13.4

50th(Median): 19.2

75th: 23.6 

Matched controls 

25th: 13.5

50th(Median): 18.4

75th: 22.7 

Monitoring Stations: 

73 (from 39 counties) 

PM Increment: 10 μg/m3

RR Estimate [Lower CI, Upper CI] lag: 

All-cause mortality: 

Unadjusted: 1.15 (1.00, 1.32) 

Adjusted: 1.07 (0.93, 1.24) 

Cause-specific mortality: 

Respiratory (all): 

Unadjusted: 2.15 (1.15, 4.02) 

Adjusted: 2.13 (1.12, 4.05) 

Respiratory (excluding deaths due to 

BPD): 

Adjusted: 1.42 (0.66, 3.03) 

Respiratory (BPD alone): 

Unadjusted: 6.00 (1.40, 27.76) 

Respiratory (low birth weight infants 

only): Unadjusted: 3.09 (1.14, 8.40) 

Respiratory (normal birth weight infants 

only): Unadjusted: 1.66 (0.74, 3.70) 

Respiratory (with matched PM2.5 avgd 

over all monitors in county) 

Adjusted: 2.28 (0.94, 5.52) 

Respiratory (averaging all PM2.5

measurements in county over the 2-yr 

study period): 

Adjusted: 2.26 (0.83, 6.21) 

SIDS: 

Unadjusted: 0.86 (0.61, 1.22) 

Adjusted: 0.82 (0.55, 1.23) 

SIDS (includes ICD10 code R99: illdefined and unspecified causes of 

mortality): 

Adjusted: 1.03 (0.79, 1.35) 

External causes: 

Unadjusted: 0.91 (0.56, 1.47) 

Adjusted: 0.83 (0.50, 1.39) 

Compare against the lowest quartile, 

estimates for respiratory-specific 

mortality were provided: 

2nd quartile: 1.28 (0.47, 3.51) 

3rd quartile: 1.75 (0.65, 4.72) 

4th quartile: 2.35 (0.85, 6.54) 

December 2009 E-494 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Woodruff et al. (2008, 

098386) 

Period of Study: 1999-2002 

Location: U.S. counties with >250,000 

residents (96 counties) 

Outcome (ICD10): Postneonatal 

deaths: Respiratory mortality (J000-99, 

plus bronchopulmonary dysplasia [BPD] 

P27.1) 

SIDS (R95) 

Ill-defined causes (R99) 

All other deaths evaluated as a control 

category 

Age Groups: Infants aged >28 days 

and <1 yr 

Study Design: Cross-sectional

N: 3,583,495 births (6,639 post neonatal 

deaths) 

Statistical Analyses: Logistic GEE 

(exchangeable correlation structure) 

Covariates: Maternal race/ethnicity, 

marital status, age, education, 

primiparity, county-level poverty and per 

capita income levels, yr and month of 

birth dummy variables to account for 

time trend and seasonal effects, and 

region of the country 

sensitivity analyses performed among 

only those mothers with smoking 

information (adjustment for smoking had 

no effect on the estimates) 

Season: Adjusted for yr and month of 

birth dummy variables to account for 

time trend and seasonal effects 

Dose-response Investigated? 

Evaluated the appropriateness of a 

linear form from analysis based on 

quartiles of exposure and concluded that 

linear form was appropriate (data not 

shown) 

Statistical Package: SAS 

Pollutant: PM2.5 

Averaging Time: Measured 

continuously for 24 h once every 6 days 

Exposure assigned by calculating avg 

concentration of pollutant during first 2 

mo of life 

Median and IQR (25th-75th 

percentile): 

Survivors: 14.8 (11.7-18.7) 

All causes of death: 14.9 (12.0-18.6) 

Respiratory: 14.8 (11.5-18.5) 

SIDS: 14.5 (12.0-17.5) 

SIDS + ill-defined: 14.8 (12.1-18.5) 

Other causes: 14.9 (12.0-18.6) 

Percentiles: See above 

PM Component: Not assessed, but 

controlled for region of the country to 

account for PM composition variation 

Monitoring Stations: NR 

Copollutant (correlation): 

PM10 (r = 0.34) 

PM2.5

CO (r = 0.35) 

SO2 (r = 0.21) 

O3 (r = -0.10) 

Notes: Monthly avg calculated if there 

were at least 3 available measures for 

PM 

Assigned exposures using the avg 

concentration of the county of residence 

PM Increment: IQR (7 μg/m3) 

Effect Estimate [Lower CI, Upper CI]: 

Adjusted ORs for single pollutant models

All causes: 1.04 (0.98, 1.11) 

Respiratory: 1.11 (0.96, 1.29) 

SIDS: 1.01 (0.86, 1.20) 

Ill-defined + SIDS: 1.06 (0.97, 1.17) 

Other causes: 1.03 (0.96, 1.12) 

Adjusted ORs for multipollutant models 

(including CO, O3, SO2) 

Respiratory: 1.05 (0.89, 1.24) 

SIDS: 1.04 (0.87, 1.23) 

OR for respiratory deaths assessing 

exposure as quartiles 

Highest vs. Lowest quartile: 1.39 (1.04, 

1.85) 

1

All units expressed in μg/m3 unless otherwise specified.

December 2009 E-495 
E.9.Long-Term Exposure and Mortality 

Table E-31. Long-term exposure-mortality - PM10. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Breitner et al., 2009, 

188439) 

Period of Study: Oct 1991-Mar 2002 

Location: Efurt, Germany 

Outcome: Mortality, excluding infants 

and ICD-9 ≥ 800 

Study Design: Time-series 

Covariates: Seasonal and weekday 

variations, influenza epidemics, air 

temperature, relative humidity 

Statistical Analysis: Semiparametric 

Poisson regression, polynomial 

distributed lag (PDL) 

Statistical Package: R 

Age Groups: All 

Pollutant: PM10

Averaging Time: Daily 

Mean (SD) Unit: 

1 (10/1/1991-8/31/1995): 

50.6 ± 32.2 μg/m3

2 (9/1/1995-2/28/1998): 

41.1 ± 28.4 μg/m3

3 (3/1/1998-3/31/2002): 

24.3 ± 15.4 μg/m3

Total: 38.0 ±28.3 μg/m3

Range (Min, Max): NR 

Copollutant: NO2, CO, UFP 

Increment: IQR 

Relative Risk (95% CI) lag 

New City Limits 

6-day IQR: 17.2 

PDL: 0.997 (0.972-1.022) 

Mean of lags 0-5: 0.995 (0.971-1.019) 

Old City Limits 

6-day IQR: 17.2 

PDL: 1.004 (0.978-1.031) 

Mean of lags 0-5: 1.001 (0.976-1.027) 

New City Limits 

15-day IQR: 14.5 

PDL: 1.008 (0.982-1.036) 

Mean of lags 0-14: 1.006 (0.981-1.032) 

Old City Limits 

15-day IQR: 14.5 

PDL: 1.019 (0.991-1.048) 

Mean of lags 0-14: 1.017 (0.990-1.044) 

Multiday Ma, 6-day 

Overall IQR: 24.2 

Overall RR (95% CI): 0.998 (0.976-

1.021) 

Period 1: 0.996 (0.969-1.024) 

Period 2: 1.013 (0.972-1.056) 

Period 3: 0.949 (0.897-1.004) 

Multiday Ma, 15-day 

Overall IQR: 22.3 

Overall RR (95% CI): 1.020 (0.993-

1.093) 

Period 1: 1.017 (0.984-1.051) 

Period 2: 1.012 (0.973-1.071) 

Period 3: 0.978 (0.911-1.051) 

1

All units expressed in μg/m3 unless otherwise specified.

December 2009 E-496 
Table E-32. Long-term exposure-mortality - PM10-2.5. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: (Chen et al., 2005, 087942) 

Period of Study: 1973-1998 

Location: San Francisco, San Diego, 

Los Angeles, CA 

Outcome: Mortality: CHD 

Study Design: Cohort 

Statistical Analyses: Cox proportion 

hazards model 

Age Groups: >25 

Pollutant: PM10-2.5

Averaging Time: 25 yr 

Mean (SD): 25.4 

Range (Min, Max): NR

Copollutant: 

NO2

O3

SO2

Increment: 10 μg/m3 

Relative Risk (Lower CI, Upper CI) 

lag: 

Males 

PM10-2.5: 0.93 (0.68, 1.29) 0-1 

PM10-2.5+NO2: 0.86 (0.62, 1.20) 0-1 

PM10-2.5+SO2: 0.90 (0.64,1.27) 0-1 

PM10-2.5+O3: 1.01 (0.67,1.51) 0-1 

Females 

PM10-2.5: 1.20 (0.95, 1.53) 0-1 

PM10-2.5+NO2: 1.19 (0.92, 1.54) 0-1 

PM10-2.5+SO2: 1.31 (1.03,1.68) 0-1 

PM10-2.5+O3: 1.47 (1.10,1.96) 0-1 

Reference: Goss et al. (2004, 055624) 

Period of Study: 1999-2000 

Location: United States 

Outcome: Mortality 

Study Design: Cohort Study (Cystic 

Fibrosis Cohort) 

Statistical Analyses: Logistic 

Regression

Age Groups: >6 yr 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD) unit: PM2.5: 13.7 (4.2) 

IQR: PM2.5: 11.8-15.9 

Copollutant: 

O3

NO2

SO2

CO 

Increment: 10 μg/m3

PM2.5: 1.32 (0.91-1.93) 

Reference: Lipert et al. (2009, 

190271) 

Period of Study: 1989-1996 

Location: Various parts of the Untied 

States 

Outcome: Mortality

Study Design: Retrospective Cohort

Statistical Analyses: Cox proportional 

hazards regression

Age Groups: Male U.S. veterans 

between ages of 39 and 63 (Avg. age: 

51) 

Pollutant: PM10-2.5

Mean (SD): 16.0 (5.1) 

Increment: 12 

1.07 (1.01, 1.13)

Reference: McDonnell et al. (2000, 

010319)

Period of Study: 1973-1977

Location: California 

Outcome: Mortality 

Study Design: Cohort (AHSMOG 

airport cohort) 

Statistical Analyses: Cox regression 

models 

Age Groups: Males, 27 yr+ 

Pollutant: PM10-2.5

Averaging Time: Monthly avg

Mean (SD): PM10-2.5: 27.3 (8.6)

IQR: 9.7 

Copollutant: 

O3: 0.70 

SO2: 0.31 

NO2: 0.23 

SO4: 0.47 

Increment: IQR 

All Cause: 1.05 (0.92-1.20) 

Resp: 1.19 (0.88, 1.62) 

Lung Cancer: 1.25 (0.63-2.49) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-497 
Table E-33. Long-term exposure-mortality - PM2.5 (including PM components/sources). 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Reference: Abrahamowicz et al. (2003, 

086292) 

Period of Study: 1982-1989 

Location: 151 Cities 

Outcome: Mortality: All-causes 

Study Design: Case-cohort study 

Statistical Analyses: Cox proportionhazards model flexible regression 

spline generalization 

Age Groups: >18 

Pollutant: PM2.5

Averaging Time: Annual 

Mean (SD): 18.2 

Range (Min, Max): (9.0, 33.5)

Copollutant: Sulfates 

Relative Risk (Min CI, Max CI) 

Estimated from graph (Fig 1): log HR 

for a 24.5 μg/m3

 increase in PM2.5 over 

time 

Yr 

0: 0.5 (-1.1, 1.6) 

2: 0.6 (0.2, 0.9) 

4: 0.6 (0.3, 0.8) 

6: 0.8 (0.3, 1.1) 

8: -1.0 (-1.5, 1.0) 

Reference: Abrahamowicz et al. (2003, 

086292) 

Period of Study: 1982-1989 

Location: 151 Cities 

Outcome: Mortality: All-causes 

Study Design: Case-cohort study 

Statistical Analyses: Cox proportionhazards model flexible regression 

spline generalization 

Age Groups: >18 

Pollutant: Sulfates 

Averaging Time: Annual 

Mean (SD): 18.2 

Range (Min, Max): (9.0, 33.5)

Copollutant: PM2.5

Relative Risk (Min CI, Max CI) 

Estimated from graph (Fig 1): Log HR 

for a 19.9 μg/m3

 increase in Sulfates 

over time 

Yr 

0: 0.1 (-0.2, 0.7) 

2: 0.1 (-0.2, 0.4) 

4: 0.0 (-0.4, 0.3) 

6: 0.3 (-0.1, 0.5) 

8: 0.4 (-0.4, 1.6) 

Reference: Ballester et al. (2008, 

189977) 

Period of Study: 2001-2002 

Location: Europe 

Outcome: Mortality- All-causes 

Study Design: Health Impact 

Assessment 

Statistical Analyses: Aphesis Network 

Age Groups: >30 

Pollutant: PM2.5

Averaging Time: Annual 

Mean (SD): NR

Range (Min, Max): NR

Potential Reduction in the total 

burden of mortality (min CI, max CI) 

for four different decreases in annual 

PM2.5 using a conservative estimate

Reduction to 25 μg/m3

 - 0.4 (0.1, 0.8) 

Reduction to 20 μg/m3

 - 0.8 (0.2, 1.6) 

Reduction to 15 μg/m3 - 1.6 (0.4, 3.1) 

Reduction to 10 μg/m3

 - 3.0 (0.8, 5.8) 

Reference: Beelen et al. (2008, 

156263) 

Period of Study: 1987-1996 

Location: Netherlands 

Outcome: Mortality: 

Total (nonaccidental) (<800) 

Cardio-respiratory (390-448, 490-496, 

487, 480-486, 507) 

Pulmonary (460-519) 

Cardiovascular (400-440) 

Lung Cancer (162) 

Other-causes 

Study Design: Case-cohort study and 

prospective cohort 

Statistical Analyses: Cox proportionhazards model 

Age Groups: 55-69 

Pollutant: PM2.5

Averaging Time: Annual 

Mean (SD): 28.3 (2.1) μg/m3

Range (Min, Max): (23.0, 36.8)

Copollutant (correlation): 

NO2: (>0.8) 

BS: (>0.8) 

SO2: (>0.6) 

Increment: 11 μg/m3 

Relative Risk (Min CI, Max CI) 

RR for the association between 

exposures to PM2.5 and cause 

specific mortality 

Natural Cause: 

Full cohort: 1.06 (0.97, 1.16) 

Case cohort: 0.86 (0.66, 1.13) 

Cardiovascular: 

Full cohort: 1.04 (0.90, 1.21) 

Case cohort: 0.83 (0.60, 1.15) 

Respiratory: 

Full cohort: 1.07 (0.75, 1.52) 

Case cohort: 1.02 (0.56, 1.88) 

Lung Cancer: Full cohort: 1.06 (0.82, 

1.38) 

Case cohort: 0.87 (0.52, 1.47) 

Other cause: F 

Ull cohort: 1.08 (0.96, 1.23) 

Case cohort: 0.85 (0.65, 1.12) 

RR for the association between 

exposures to BS and cause specific 

mortality 

Natural Cause: 

Full cohort: 1.05 (1.00, 1.11) 

Case cohort: 0.97 (0.83, 1.13) 

Cardiovascular: Full cohort: 1.04 (0.95, 

1.13) 

Case cohort: 0.98 (0.81, 1.18) 

Respiratory: 

Full cohort: 1.22 (0.99, 1.50) 

Case cohort: 1.29 (0.91, 1.83) 

Lung Cancer: 

Full cohort: 1.03 (0.88, 1.20) 

Case cohort: 1.03 (0.77, 1.38) 

Other cause: 

Full cohort: 1.04 (0.97, 1.12) 

Case cohort: 0.91 (0.78, 1.07) 

December 2009 E-498 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Breitner et al. (2009, 

188439) 

Outcome: Mortality, excluding infants 

and ICD-9 ≥ 800 

Pollutant: PM2.5

Averaging Time: Daily 

Period of Study: Oct 1991-Mar 2002 Study Design: Time-series Mean (SD) Unit: 

1 (10/1/1991-8/31/1995): Location: Efurt, Germany Covariates: Seasonal and weekday 

variations, influenza epidemics, air 

temperature, relative humidity 

50.6 ± 32.2 μg/m3

2 (9/1/1995-2/28/1998): 

Statistical Analysis: Semiparametric 

Poisson regression, polynomial 

distributed lag (PDL) 

Statistical Package: R 

Age Groups: All 

41.1 ± 28.4 μg/m3

3 (3/1/1998-3/31/2002): 

24.3 ± 15.4 μg/m3

Total: 38.0 ±28.3 μg/m3

Range (Min, Max): NR 

Copollutant: NO2, CO, UFP 

Increment: IQR 

Relative Risk (95% CI) lag 

New City Limits 

6-day IQR: 13.3 

PDL: 1.009 (0.984-1.035) 

Mean of lags 0-5: 1.004 (0.981-1.027) 

Old City Limits 

6-day IQR: 13.3 

PDL: 1.017 (0.990-1.044) 

Mean of lags 0-5: 1.010 (0.986-1.035) 

New City Limits 

15-day IQR: 11.5 

PDL: 1.019 (0.988-1.050) 

Mean of lags 0-14: 1.017 (0.992-1.042) 

Old City Limits 

15-day IQR: 11.5 

PDL: 1.030 (0.997-1.063) 

Mean of lags 0-14: 1.025 (0.999-1.052) 

Multiday Ma, 6-day 

Overall IQR: 13.3 

Overall RR (95% CI): 

1.004 (0.981-1.027) 

Period 1: NR 

Period 2: 1.017 (0.990-1.044) 

Period 3: 0.974 (0.937-1.013) 

Multiday Ma, 15-day 

Overall IQR: 11.5 

Overall RR (95% CI): 

1.017 (0.992-1.042) 

Period 1: NR 

Period 2: 1.016 (0.988-1.045) 

Period 3: 1.016 (0.971-1.063) 

December 2009 E-499 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Brunekreef et al. (2009, 

191947) 

Period of Study: 1987-1996 

Location: The Netherlands 

Outcome: All cause mortality (ICD-9 

400-440, 460-519, > 800) 

Study Design: Case-cohort 

Covariates: 

Individual: sex, age, Quetelet index, 

smoking status, passive smoking 

status, educational level, occupation, 

occupational exposure, marital status, 

alcohol use, intake of vegetables, fruits, 

energy, saturatured and 

monounsaturated fatty acids, trans fatty 

acids, total fiver, folic acid and fish 

Area-level: Percent of population with 

income below the 40th percentile and 

above the 80th percentile 

Statistical Analysis: Cox proportional 

hazards 

Statistical Package: Stata, SPSS, R 

Age Groups: 120,000 adults aged 

55-69 yr at enrollment 

Pollutant: PM2.5, estimated from PM10

levelsf 

Averaging Time: 24 h 

50th Percentile: 28 μg/m3 

Range (Min, Max): 23-37 

Copollutant (correlation): 

NO2: 0.75 

BS: 0.84 

NO: 0.69 

SO2: 0.43 

Increment: 10 μg/m3

Relative Risk (95 % CI) for PM2.5

concentrations and cause specific 

mortality 

Case Cohort 

Natural Cause: 0.86 (0.66-1.13) 

Cardiovascular: 0.83 (0.60-1.15) 

Respiratory: 1.02 (0.56-1.88) 

Lung Cancer: 0.87 (0.52-1.47) 

Noncardiopulmonary, non-lung cancer: 

0.85 (0.65-1.23) 

Full Cohort 

Natural Cause: 1.06 (0.97-1.16) 

Cardiovascular: 1.04 (0.90-1.21) 

Respiratory: 1.07 (0.75-1.52) 

Lung Cancer: 1.06 (0.82-1.38) 

Noncardiopulmonary, non-lung cancer: 

1.08 (0.72-1.19) 

Relative Risk (95%CI) for PM2.5 

concentrations and cause specific 

mortality in full cohort analysis by 

confounder model 

Natural Cause Mortality 

Unadjusted: 1.11 (1.04-1.20) 

Smoking: 1.04 (0.96-1.13) 

Smoking, area-level income: 

1.06 (0.97-1.16) 

Cardiovascular Mortality 

Unadjusted: 1.09 (0.97-1.23) 

Smoking: 1.02 (0.90-1.16) 

Smoking, area-level income: 

1.04 (0.90-1.21) 

Respiratory Mortality 

Unadjusted: 1.23 (0.92-1.65) 

Smoking: 1.10 (0.81-1.50) 

Smoking, area-level income: 

1.07 (0.75-1.52) 

Lung Cancer Mortality 

Unadjusted: 1.17 (0.95-1.46) 

Smoking: 1.06 (0.85-1.33) 

Smoking, area-level income: 

1.06 (0.82-1.38) 

Noncardiopulmonary, Non-Lung Cancer 

Mortality 

Unadjusted: 1.10 (1.00-1.22) 

Smoking: 1.05 (0.94-1.16) 

Smoking, area-level income: 

1.08 (0.96-1.22) 

Reference: Chen et al. (2005, 087942) 

Period of Study: 1973-1998 

Location: San Francisco, San Diego, 

Los Angeles, CA 

Outcome: Mortality: CHD 

Study Design: Cohort 

Statistical Analyses: Cox proportion 

hazards model 

Age Groups: >25 

Pollutant: PM2.5

Averaging Time: 25 yr 

Mean (SD): 29.0 

Range (Min, Max): NR

Copollutant: NO2, O3, SO2

Increment: 10 μg/m3 

Relative Risk (Lower CI, Upper CI) 

lag: 

Males 

PM2.5: 0.89 (0.69, 1.17) 0-1 

PM2.5+NO2: 0.82 (0.61, 1.10); 0-1 

PM2.5+SO2: 0.86 (0.65,1.14) 0-1 

PM2.5+O3: 0.92 (0.65,1.29) 0-1 

Females 

PM2.5: 1.19 (0.96, 1.47) 0-1 

PM2.5+NO2: 1.18 (0.95, 1.47); 0-1 

PM2.5+SO2: 1.36 (1.05,1.74) 0-1 

PM2.5+O3: 1.61 (1.17,2.22) 0-1 

December 2009 E-500 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Eftim et al. (2008, 099104) 

Period of Study: 2000-2002 

Location: USA, Same cities as six 

cities and ACS cohorts 

Outcome (ICD-9): All nonaccidental 

causes (<800)

Study Design: Cross-sectional 

Statistical Analyses: Log-linear 

regression, Poisson 

Age Groups: >65 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): | 

ACS: 13.6 (2.8) 

SCS: 14.1 (3.1) 

Range (Min, Max): 

ACS: (6.0, 25.1); SCS: (9.6, 19.1) 

Increment: 10 μg/m3 

% Increase in Mortality for overall 

exposure period and individual yr 

(95%CI Min, 95%CI Max): 

ACS (adjusted for age, sex) 

Overall: 10.8 (8.6, 13.0) 

2000: 10.9 (7.3, 14.6) 

2001: 9.1 (5.3, 12.7) 

2002: 10.1 (6.0, 14.3) 

SCS (adjusted for age, sex) 

Overall: 20.8 (14.8, 27.1) 

2000: 17.8 (9.8, 26.4) 

2001: 16.5 (7.4, 25.0) 

2002: 33.5 (19.2, 49.3) 

Reference: Enstrom et al. (2005, 

087356) 

Period of Study: 1973-2002 

Location: 25 California Colonies 

11 California Colonies (EPA IPN study) 

Outcome: Mortality: Cardiovascularrespiratory (390-448) 

(480-486, 487, 490-496, 507) 

Study Design: Retrospective cohort 

Statistical Analyses: Cox proportional 

hazards regression model, SAS 

PHREG 

Age Groups: 35 or older 

Pollutant: PM2.5

Averaging Time: Annual

Mean (SD): 23.4 

Range (Min, Max): (13.1 μg/m3

, 36.1)

Relative Risk (Lower CI, Upper CI) 

RR from causes for both sexes by 

county from 1973-2002 

Alameda: 0.962 (0.926,0.999) 

Butte: 0.999 (0.910,1.096) 

Contra Costa: 0.999 (0.943,1.058) 

Fresno: 0.935 (0.872,1.002) 

Humboldt: 0.992 (0.900,1.092) 

Kern: 0.944 (0.872,1.023) 

Marin: 0.939 (0.867,1.016) 

Napa: 0.949 (0.868,1.038) 

Orange: 0.990 (0.948,1.034) 

Riverside: 0.959 (0.906,1.015) 

Sacramento: 0.998 (0.944,1.055) 

San Bernardino: 0.992 (0.938,1.049) 

San Diego: 0.992 (0.954, 1.033) 

San Francisco: 0.963 (0.914,1.014) 

San Joaquin: 0.925 (0.816,1.049) 

San Mateo: 0.949 (0.899, 1.003) 

Santa Barbara: 0.968 (0.878,1.068) 

Santa Clara: 0.955 (0.910,1.003) 

Santa Cruz: 0.890 (0.793,0.999) 

Solano: 0.901 (0.815,0.995) 

Sonoma: 0.968 (0.884,1.060) 

Stanislaus: 0.984 (0.904,1.072) 

Tulare: 1.047 (0.979,1.119) 

Ventura: 0.967 (0.872,1.072) 

RR from all causes for 11 counties 

for both sexes (EPA IPN study) 

Santa Barbara: 0.968 (0.878,1.068) 

Contra Costa: 0.999 (0.943,1.058) 

Alameda: 0.962 (0.926,0.999) 

Butte: 0.999 (0.910,1.096) 

San Francisco: 0.963 (0.914,1.014) 

Santa Clara: 0.955 (0.910,1.003) 

Fresno: 0.935 (0.872,1.002) 

San Diego: 0.992 (0.954,1.033) 

Kern: 0.944 (0.872,1.023) 

Riverside: 0.959 (0.906,1.015) 

Reference: Filleul et al. (2005, 087357) 

Period of Study: 1974-1976 

Location: 7 cities in France 

Outcome: Nonaccidental causes 

(<800), cardiopulmonary disease (401-

440 and 460-519), lung cancer (162)

Age Groups: 25-59 yr 

Study Design: Cohort

N: 14,284 people 

Statistical Analyses: Cox proportional 

hazard, regression 

Covariates: Sex, smoking habits, 

educational level, body-mass index 

(BMI), occupational exposure 

Statistical Package: Proc Phreg SAS 

Pollutant: Total suspended particles 

(TSP) 

Averaging Time: NR 

Mean (SD): NR 

Range (Min, Max): (45, 243) 

PM Component: NR 

Monitoring Stations: 1 station 

Copollutant (correlation): 

BS r = 0.87 

SO2 r = 0.17 

NO r = 0.84 

NO2 r = 0.60 

Increment: 10 μg/m3 

Adjusted mortality rate ratios: 24 areas: 

All nonaccidental causes: 

1.00[0.99, 1.01] 

Lung cancer: 0.97[0.94, 1.01] 

Cardiopulmonary disease: 

1.01[0.99, 1.03] 

18 areas: All nonaccidental causes: 

1.05[1.02, 1.08] 

Lung cancer: 1.00[0.92, 1.10] 

Cardiopulmonary disease: 

1.06[1.01, 1.12] 

December 2009 E-501 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Fuentes et al. (2006, 

097647) 

Period of Study: Jun 2000 

Location: Conterminous U.S. 

Outcome: Mortality: 

Study Design: Time-series 

Statistical Analyses: Generalized

Poisson Regression 

Age Groups: 0-14, 15-64, >65

Covariates: Temperature, pressure, 

dew point, wind speed, elevation, age, 

ethnicity 

Pollutant: PM2.5

Averaging Time: Monthly

Mean (SD): 6.60 (0.76) 

Copollutant: PM10, O3

Increment: 10 μg/m3 

PM2.5: 1.066 (1.064, 1.069) 

PM10: 1.030 (1.028, 1.032) 

Reference: Janes et al. (2007, 090927) 

Period of Study: 2000-2002 

Location: 113 U.S. counties 

Outcome: Mortality: 

Study Design: Time-series 

Statistical Analyses: Cox proportional 

hazards model 

Age Groups: 65-74 

75-84 

85+ 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): NR 

Range (Min, Max): NR 

Increment: 1 μg/m3 

% Increase (Lower CI, Upper CI) lag: 

Overall % Increase by age-sex stratum 

Age Category 

65-74: Male: 1.48 (0.93,2.03) 

Female: 0.83 (0.24,1.43) 

75-84: Male: 0.85 (0.34,1.35) 

Female: 0.77 (0.28,1.27) 

85+: Male: 0.70 (0.03,1.38) 

Female: 0.59 (0.05,1.12) 

National Trend % Increase by age-sex 

stratum 

Age Category 

65-74: Male: 3.55 (2.77,4.34) 

Female: 1.97 (1.12,2.83) 

75-84: Male: 2.48 (1.83,3.14) 

Female: 2.29 (1.66,2.93) 

85+: Male: 1.38 (0.52,2.26) 

Female: 1.65 (1.01,2.29) 

Local Trend % Increase by age-sex 

stratum 

Age Category 

65-74: Male: 0.04 (-0.58,0.67) 

Female: -0.03 (-0.71,0.66) 

75-84: Male: -0.34 (-0.87,0.19) 

Female: -0.31 (-0.82, 0.21) 

85+: Male: <0.01 (-0.71,0.73) 

Female: -0.22 (-0.74,0.31) 

*Local trends are county specific 

deviations from national trends 

Reference: Jerrett et al. (2003, 

087380) 

Period of Study: 1982 

Location: 151 cities from ACS 

Outcome: Mortality

Study Design: Multilevel, individualecologic analysis 

Statistical Analysis: Cox proportional 

hazards model 

Covariates: Smoking, education, 

occupational exposures, BMI, marital 

status, alcohol consumption, gender 

Pollutant: Sulfates

Mean (SD): 10.6 

Range (Min, Max): 3.6,23.5 

Increment: 19.9 (Range)

All Cause: SO4: 1.17 (1.07, 1.27) 

SO4 + CO: 1.16 (1.10, 1.23) 

SO4 + NO2: 1.16 (1.08, 1.24) 

SO4 + O3: 1.17 (1.11, 1.24) 

SO4 + SO2: 1.05 (0.98, 1.12) 

CPD: SO4: 1.25 (1.16, 1.35) 

SO4 + CO: 1.28 (1.18, 1.39) 

SO4 + NO2: 1.29 (1.17, 1.42) 

SO4 + O3: 1.27 (1.17, 1.38) 

SO4 + SO2: 1.13 (1.03, 1.24) 

Lung Cancer: SO4: 1.31 (1.09, 1.58) 

SO4 + CO: 1.26 (1.03, 1.53) 

SO4 + NO2: 1.31 (1.05, 1.65) 

SO4 + O3: 1.30 (1.07, 1.59) 

SO4 + SO2: 1.37 (1.08, 1.73) 

December 2009 E-502 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Jerrett et al. (2005, 

087600) 

Period of Study: 1982-2000 

Location: Los Angeles, California 

Outcome: Mortality: Non- accidental 

(<800) 

IHD (410-414) 

Cardiopulmonary (400-440, 460-519) 

Lung Cancer (162) 

Other Cancers (140-149,160, 161, 163-

239) 

Other causes 

Study Design: Retrospective Cohort 

Statistical Analyses: Cox regression 

hazards model 

kriging, radial basis function 

multiquadric interpolator 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): NR 

Range (Min, Max): NR 

Copollutant: O3

Increment: 10 μg/m3 

Relative Risk (Lower CI, Upper CI) 

All Causes - PM2.5 Only: 

1.24 (1.11,1.37) 

44 Ind. Covariates together+PM2.5: 

1.17 (1.03,1.32) 

44 Ind. Covariates together+ PM2.5+O3: 

1.20 (1.07,1.34) 

44 Ind. Covariates together+intersection 

within freeways within 500 m+ 

PM2.5+O3: 1.17 (1.05,1.31) 

IHD - PM2.5 Only: 1.49 (1.20,1.85) 

44 Ind. Covariates together+PM2.5: 

1.39 (1.12,1.73) 

44 Ind. Covariates together+PM2.5+O3: 

1.45 (1.15,1.82) 

44 Ind. Covariates together+intersection 

within freeways within 500 m+ 

PM2.5+O3: 1.38 (1.11,1.72) 

Cardiopulmonary - PM2.5 Only: 

1.20 (1.04,1.39) 

44 Ind. Covariates together+ PM2.5+O3: 

1.19 (1.02,1.38) 

44 Ind. Covariates together+intersection 

within freeways within 500 m+ 

PM2.5+O3: 1.13 (0.97,1.31) 

Lung Cancer - PM2.5 Only: 1.60 

(1.09,2.33) 

44 Ind. Covariates together+PM2.5: 

1.44 (0.98,2.11) 

44 Ind. Covariates together+intersection 

within freeways within 500 m+ 

PM2.5+O3: 1.46 (0.99,2.16) 

Other Cancers - PM2.5 Only: 

1.09 (0.85,1.40) 

44 Ind. Covariates together+ PM2.5+O3: 

1.08 (0.83,1.39) 

44 Ind. Covariates together+intersection 

within freeways within 500 m+ 

PM2.5+O3: 1.08 (0.83,1.39) 

All Other Causes - PM2.5 Only: 

1.11 (0.74,1.67) 

44 Ind. Covariates together+ PM2.5+O3: 

0.95 (0.64,1.39) 

44 Ind. Covariates together+intersection 

within freeways within 500 m+ 

PM2.5+O3: 1.02 (0.71,1.48) 

December 2009 E-503 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Laden et al. (2006, 087605) 

Period of Study: 1974-1998 

Period 1: 1974-1989 

Period 2: 1990-1998 

Location: Nine U.S. Cities 

Watertown, MA 

Kingston, TN 

Harriman, TN 

St. Louis, MO 

Steubenville, OH 

Portage, WI 

|Wyocena, WI 

Pardeeville, WI 

Topeka, KS 

Outcome: Total mortality 

Nonaccidental (<800) 

Cardiovascular (400-440) 

Respiratory (485-496) 

Lung Cancer (162) 

Other 

Study Design: Prospective Cohort 

Statistical Analyses: Cox proportional 

hazards regression 

Age Groups: 25-74 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): 

Period 1 

Portage: 11.4 

Topeka: 12.4 

Watertown: 15.4 

Harriman: 20.9 

St Louis: 19.2 

Steubenville: 29.0 

Period 2 

Portage: 10.2 

Topeka: 13.1 

Watertown: 12.1 

Harriman: 18.1 

St. Louis: 13.4 

Steubenville: 22.0 

Increment: 10 μg/m3 

Relative Risk (Lower CI, Upper CI) 

lag: 

Period 1: 

Portage: 1.00 

Topeka: 1.06 (0.86, 1.31) 

Watertown: 1.06 (0.87, 1.28) 

Harriman: 1.19 (0.98, 1.44) 

St Louis: 1.15 (0.96, 1.38) 

Steubenville: 1.31 (1.10, 1.57) 

Period 2: 

Portage: NR 

Topeka: 1.01 (0.83, 1.22) 

Watertown: 0.82 (0.67, 1.00) 

Harriman: 1.10 (0.91, 1.33) 

St Louis: 0.96 (0.80, 1.15) 

Steubenville: 1.06 (0.89, 1.27) 

Complete Period: 

Portage: 1.00 

Topeka: 1.03 (0.89, 1.19) 

Watertown: 0.95 (0.83, 1.08) 

Harriman: 1.15 (1.01, 1.32) 

St. Louis: 1.05 (0.93, 1.20) 

Steubenville: 1.18 (1.04, 1.34)

RR for complete follow up avg PM2.5 

Total Mortality: 1.16 (1.07, 1.26) 

Cardiovascular: 1.28 (1.13, 1.44) 

Respiratory: 1.08 (0.79, 1.49) 

Lung Cancer: 1.27 (0.96, 1.69) 

Other: 1.02 (0.90, 1.17) 

RR for Period 1 avg PM2.5

Total Mortality: 1.18 (1.09, 1.27) 

Cardiovascular: 1.28 (1.14, 1.43) 

Respiratory: 1.21 (0.89, 1.66) 

Lung Cancer: 1.20 (0.91, 1.58) 

Other: 1.05 (0.93, 1.19) 

Decrease in avg PM2.5 over the 2 

periods 

Total Mortality: 0.73 (0.57, 0.95) 

Cardiovascular: 0.69 (0.46, 1.01) 

Respiratory: 0.43 (0.16, 1.13) 

Lung Cancer: 1.06 (0.43, 2.62) 

Other: 0.85 (0.56, 1.27) 

Reference: Lipfert et al. (2006, 088756) 

Period of Study: 1989-1996 

Location: Various parts of the Untied 

States 

Outcome: Mortality

Study Design: Retrospective Cohort

Statistical Analyses: Cox proportional 

hazards regression

Age Groups: Male U.S. veterans 

between ages of 39 and 63 (Avg. age: 

51) 

Pollutant: Sulfate 

Mean (SD) from 1976-81: 10.7 (3.6) 

Increment: 8 

1.045 (0.944, 1.157) 

Reference: Lipfert et al. (2006, 088756) 

Period of Study: 1989-1996 

Location: Various parts of the Untied 

States 

Outcome: Mortality

Study Design: Retrospective Cohort

Statistical Analyses: Cox proportional 

hazards regression

Age Groups: Male U.S. veterans 

between ages of 39 and 63 (Avg age 

51) 

Pollutant: PM2.5

Mean (SD): 14.3 (3.2) 

Increment: 8 

1.118 (1.038, 1.203) 

December 2009 E-504 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Lipfert et al. (2006, 088218) 

Period of Study: 1997-2002 

Location: Various parts of the Untied 

States 

Outcome: Mortality: Non- accidental 

(<800) 

Study Design: Retrospective cohort 

Statistical Analyses: Cox proportional 

hazards regression 

AIC 

Age Groups: Male U.S. veterans 

between ages of 39 and 63 (Avg. age: 

51) 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): 15.02 (4.80) μg/m3 (2000-

2003) 

Range (Min, Max): (3.29, 24.96) 

Copollutant (correlation): 

As: r = 0.443 

Cr: r = 0.379 

Cu: r = 0.530 

Fe: r = 0.379; 

Pb: r = 0.489 

Mn: r = 0.389; 

Ni: r = 0.140 

Se: r = 0.312; 

V: r = 0.197 

Zn: r = 0.420; 

OC: r = 0.620 

EC: r = 0.544; | 

SO4: r = 0.827 

NO3: r = 0.649 

NO2: r = 0.641 

Peak CO: r = 0.040 

Peak O3: r = 0.222 

Peak SO2: r = 0.714 

Increment: 10 μg/m3 

% Increase per 10 μg/m3 increase in 

PM2.5 

Single-Pollutant Model 

As: -5.23% 

Cr: -2.11% 

Cu: 2.12% 

Fe: 2.81% 

Pb: -2.40% 

Mn: -1.20% 

Ni: 3.75% 

Se: -0.30% 

V: 5.08% 

Zn: 1.52% 

OC: -0.02% 

EC: 9.16% 

SO4: 3.04% 

NO3: 6.60% 

NO2: 6.92% 

Peak CO: -0.61% 

Peak O3: 4.95% 

Peak SO2: -4.20% 

Multiple Pollutants model- Pollutant 

with traffic density 

NO3: 3.42% 

SO4: -2.73% 

EC: 6.27% 

Ni: 2.51% 

V: 3.27% 

Pollutant with NO3

EC: 5.93% 

Ni: 2.31% 

V: 3.11% 

Pollutant with Peak O3

Traffic density: 2.40% 

EC: 10.79% 

Fe: 5.94% 

NO3: 7.57% 

PM2.5: 8.97% 

V: 4.93% 

Ni: 3.65% 

SO4: 6.75% 

Cu: 1.55% 

OC: 0.21% 

December 2009 E-505 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3

Hazard Ratio (95% CI) 

MSA & DIFF 

Increment Change: 

10.78 (1.043-1.115) 

Change 5-15 μg/m3

: 

1.128 (1.077-1.183) 

Change 10-20 μg/m3

: 

1.079 (1.048-1.112) 

HR (95% CI) 

Los Angeles 

Parsimonious ecologic covariates: 

1.126 (1.014-1.251) 

HR (95% CI) 

15-yr time window 

Group A: 0.98 (0.92-1.06) 

Group B: 1.01 (0.99-1.02) 

HR (95% CI) 

Third follow-up, 7 Ecologic Variables 

1979-1983: 1.044 (1.028-1.060) 

1999-2000: 1.057 (1.036-1.079) 

HR (95% CI) 

Nationwide analysis, 1999-2000 

Standard Cox: 1.03 (1.01-1.05) 

Random Effects Cox: 1.06 (1.04-1.08)

Increment: 1.5 μg/m3

HR (95% CI) 

28 County, 3-yr model 

All 7 ecologic covariates: 

0.977 (0.932-1.025) 

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death from cardiopulmonary 

disease 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3 

Hazard Ratio (95% CI) 

MSA & DIFF 

Increment Change: 1.078 (1.077-1.182) 

Change 5-15 μg/m3

: 

1.208 (1.132-1.290) 

Change 10-20 μg/m3: 

1.127 (1.081-1.174) 

HR (95% CI) 

Los Angeles 

Parsimonious ecologic covariates: 

1.086 (0.939-1.285) 

HR (95% CI) 

15-yr time window 

Group A: 1.00 (0.90-1.11) 

Group B: 1.05 (1.03-1.07) 

HR (95% CI) 

Third follow-up, 7 Ecologic Variables 

1979-1983: 1.094 (1.070-1.118) 

1999-2000: 1.138 (1.106-1.172) 

HR (95% CI) 

Nationwide analysis, 1999-2000 

Standard Cox: 1.09 (1.06-1.12) 

Random Effects Cox: 1.13 (1.10-1.16) 

Increment: 1.5 μg/m3

HR (95% CI) 

28 County, 3-yr model 

All 7 ecologic covariates: 0 

.940 (0.875-1.011) 

December 2009 E-506 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death from ischemic heart 

disease

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3 

Hazard Ratio (95% CI) 

MSA & DIFF 

Increment Change: 1.196 (1.177-1.407) 

Change 5-15 μg/m3

: 

1.484 (1.311-1.680) 

Change 10-20 μg/m3: 

1.283 (1.186-1.387) 

HR (95% CI) 

Los Angeles 

Parsimonious ecologic covariates: 

1.263 (10.22-1.563) 

HR (95% CI) 

Third follow-up, 7 Ecologic Variables 

1979-1983: 1.184 (1.146-1.222) 

1999-2000: 1.242 (1.191-1.295) 

HR (95% CI) 

Nationwide analysis, 1999-2000 

Standard Cox: 1.15 (1.11-1.20) 

Random Effects Cox: 1.24 (1.19-1.29) 

Increment: 1.5 μg/m3

HR (95% CI) 

28 County, 3 yr model 

All 7 ecologic covariates: 

1.072 (0.980-1.172) 

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death from lung cancer 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3 

Hazard Ratio (95% CI) 

MSA & DIFF 

Increment Change: 1.142 (1.057-1.234) 

Change 5-15 μg/m3

: 

1.236 (1.114-1.372) 

Change 10-20 μg/m3

: 

1.143 (1.071-1.221) 

HR (95% CI) 

Los Angeles 

Parsimonious ecologic covariates: 

1.311 (0.897-1.915) 

HR (95% CI) 

15-yr time window 

Group A: 1.08 (0.87-1.35) 

Group B: 1.07 (1.02-1.13) 

HR (95% CI) 

Third follow-up, 7 Ecologic Variables 

1979-1983: 1.092 (1.033-1.154) 

1999-2000: 1.138 (1.057-1.225) 

HR (95% CI) 

Nationwide analysis, 1999-2000 

Standard Cox: 1.11 (1.04-1.18) 

Random Effects Cox: 1.14 (1.06-1.23) 

Increment: 1.5 μg/m3

HR (95% CI) 

28 County, 3-yr model 

All 7 ecologic covariates: 

0.985 (0.832-1.166)

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death from diabetes 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3 

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 1.5 μg/m3

HR (95% CI) 

28 County, 3 yr model 

All 7 ecologic covariates: 

1.083 (0.723-1.621)

December 2009 E-507 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death from endocrine 

disease 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR 

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3 

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 1.5 μg/m3

HR (95% CI) 

28 County, 3-yr model 

All 7 ecologic covariates: 

1.143 (0.835-1.564) 

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death from digestive cancer 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR 

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3 

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3

HR (95% CI) 

Los Angeles 

Parsimonious ecologic covariates: 

1.199 (0.817-1.758)

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Death cancers other than 

lung and digestive 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR 

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3 

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3

HR (95% CI) 

Los Angeles 

Parsimonious ecologic covariates: 

1.012 (0.788-1.299)

Reference: Krewski et al. (2009, 

191193) 

Period of Study: 1979-2000 

Location: 48 contiguous states U.S. 

Outcome: Deaths from causes other 

than CPD, IHD and lung cancer 

Study Design: Cohort 

Covariates: Demographic, 

socioeconomic and ecologic 

characteristics 

Statistical Analysis: Cox proportionalhazards model 

Statistical Package: NR 

Age Groups: Adults of at least 30 yr 

Pollutant: PM2.5

Averaging Time: NR 

Mean Unit: 

1979-1983: 21.20 μg/m3

1999-2000: 14.02 μg/m3 

Range (Min, Max): 

1979-1983: 10.77-30.01 

1999-2000: 5.80-22.20 

Copollutant: 

SO4

2–, SO2, PM15, TSP, O3, NO2, CO 

Increment: 10 μg/m3

Hazard Ratio (95% CI) 

MSA & DIFF 

Increment Change: 1.010 (0.968-1.055) 

Change 5-15 μg/m3

: 

1.026 (0.970-1.085) 

Change 10-20 μg/m3

: 

1.016 (0.981-1.053) 

HR (95% CI) 

Third follow-up, 7 Ecologic Variables 

1979-1983: 0.983 (0.960-1.007) 

1999-2000: 0.953 (0.923-0.984)

Reference: McDonnell et al. (2000, 

010319) 

Period of Study: 1973-1977

Location: California 

Outcome: Mortality

Study Design: Cohort (AHSMOG 

airport cohort)

Statistical Analyses: Cox regression 

models

Age Groups: Males, 27 yr+ 

Pollutant: PM2.5

Averaging Time: Monthly avg

Mean (SD): 31.9 (10.7) 

IQR: 24.3 

Copollutants (correlation): 

O3: 0.68 

SO2: 0.18 

NO2: -0.08; 

SO4: 0.33 

Increment: IQR 

All Cause: 1.22 (0.95-1.58) 

Resp: 1.64 (0.93-2.90) 

Lung Cancer: 2.23 (0.56-8.94) 

December 2009 E-508 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Miller et al. (2007, 090130)

Period of Study: 1994-1998

Location: 36 U.S. Metropolitan Areas 

Outcome: CVD Mortality

Study Design: Prospective Cohort 

(WHI)

Statistical Analyses: Cox proportional 

hazards regression

Age Groups: Postmenopausal women 

ages 50-79 

Pollutant: PM2.5

Averaging Time: Annual avg (2000)

Mean (SD): 13.4

IQR: 11.6, 18.3 

Range: 3.4, 28.3 

Increment: 10 μg/m3 

CVD Death: 1.76 (1.25, 2.47) 

CHD Death: 2.21 (1.17, 4.16) 

CV Death: 1.83 (1.11, 3.00) 

Reference: Naess et al. (2007, 

090736) 

Period of Study: 1992-1998 

Location: Oslo, Norway 

Outcome: Mortality: Nonaccidental 

(<800) 

Lung cancer (162) 

COPD (490-496) 

Cardiovascular (390-459) 

Study Design: Prospective Cohort 

Statistical Analyses: Cox proportional 

hazards regression model 

Age Groups: 51-70, 71-90 

Pollutant: PM2.5

Averaging Time: 4-yr avg 

Mean (SD): PM2.5: 15 

Range (Min, Max): PM2.5: (7, 22) 

Copollutant (correlation): 

NO2: r = 0.95 

Relative Risk (CI min, CI max) 

RR for deaths from all causes 

Men (ages 51-70) PM2.5 exposure 

(in μg/m3

) 

6.56-11.45: 1.00 

11.46-14.25: 0.96 (0.89, 1.04) 

14.26-18.43: 1.12 (1.03, 1.22) 

18.44-22.34: 1.48 (1.36, 1.60) 

Men (ages 71-90) PM2.5 exposure 

(in μg/m3

) 

6.56-11.45: 1.00 

11.46-14.25: 0.99 (0.93, 1.06) 

14.26-18.43: 1.10 (1.03, 1.17) 

18.44-22.34: 1.19 (1.12, 1.27) 

Women (ages 51-70) PM2.5 exposure 

(in μg/m3

) 

6.56-11.45: 1.00 

11.46-14.25: 0.96 (0.87, 1.07) 

14.26-18.43: 1.08 (0.98, 1.20) 

18.44-22.34: 1.44 (1.30, 1.59) 

Women (ages 71-90) PM2.5 exposure 

(in μg/m3

) 

6.56-11.45: 1.00 

11.46-14.25: 1.03 (0.97, 1.09) 

14.26-18.43: 1.07 (1.01, 1.12) 

18.44-22.34: 1.11 (1.05, 1.16) 

Increment: 10 μg/m3 

RR for death from CVD and lung cancer 

Men (ages 51-70) 

CVD- PM2.5: 1.11 (1.06, 1.16) 

COPD- PM2.5: 1.32 (1.17, 1.49) 

Lung Cancer- PM2.5: 1.07 (0.98, 1.17) 

Women (ages 51-70) 

CVD: PM2.5: 1.16 (1.09, 1.24) 

COPD: PM2.5: 1.18 (1.03, 1.34) 

Lung Cancer: PM2.5: 1.23 (1.10, 1.37) 

Men (ages 71-90) 

CVD: PM2.5: 1.06 (1.03, 1.09) 

COPD: PM10: 1.13 (1.04, 1.24) 

PM2.5: 1.14 (1.04, 1.24) 

Lung Cancer: PM2.5: 1.08 (0.98, 1.19) 

Women (ages 71-90) 

CVD: PM2.5: 1.02 (1.00, 1.05) 

COPD: PM2.5: 1.09 (1.00, 1.18) 

Lung Cancer: PM2.5: 1.16 (1.03, 1.31) 

Reference: Naess et al. (2007, 

090736) 

Period of Study: 1992-1998 

Location: Oslo, Norway 

Outcome: Mortality: Lung cancer (162) 

COPD (490-496) 

Cardiovascular (390-459) 

Psychiatric causes (290, 292-302, 304, 

306-319) 

Stomach cancer (151) 

Violence (800-999) 

Study Design: Multilevel cohort 

Statistical Analyses: WinBUGS 

Age Groups: 50-74 

Pollutant: PM2.5

Averaging Time: (Mo-yr) avg 

Range Mean (SD): 14.2 (3.6) 

IQ Range (1st, 4th): (6.6, 22.3) 

Copollutant (correlation): 

PM10: r = 0.95| 

NO2: r = 0.87 

Relative Risk (CI min, CI max) 

RR on All-cause mortality of PM2.5 in 

Men Age 50-74 

Primary Education: 

PM2.5: 1.06 (1.00, 1.11) 

Individual: 1.34 (1.24, 1.43) 

Neighborhood: 1.22 (1.16, 1.28) 

Manual Class: PM2.5: 1.06 (1.01, 1.12) 

Individual: 1.28 (1.20, 1.37) 

Neighborhood: 1.20 (1.14, 1.26) 

Income below median: 

PM2.5: 1.05 (1.00, 1.12) 

Individual: 1.44 (1.35, 1.53) 

Neighborhood: 1.16 (1.11, 1.21) 

Not owner occupied: 

PM2.5: 1.06 (1.00, 1.13) 

Individual: 1.24 (1.12, 1.36) 

Neighborhood: 1.11 (1.05, 1.17) 

Lives in flat dwelling: 

December 2009 E-509 
Concentrations

1 Study Design & Methods Effect Estimates (95% CI) 

PM2.5: 1.04 (0.98, 1.11) 

Individual: 1.19 (1.09, 1.31) 

Neighborhood: 1.10 (1.04, 1.17) 

More than one person per room in 

dwelling: PM2.5: 1.10 (1.02, 1.18) 

Individual: 1.05 (0.98, 1.13) 

Neighborhood: 1.01 (0.96, 1.05) 

RR on All-cause mortality of PM2.5 in 

Women Age 50-74 

Primary Education Only: 

PM2.5: 1.05 (1.00, 1.11) 

Individual: 1.32 (1.23, 1.42) 

Neighborhood: 1.18 (1.12, 1.24) 

Manual Class: PM2.5: 1.07 (1.01, 1.13) 

Individual: 1.27 (1.18, 1.36) 

Neighborhood: 1.18 (1.12, 1.24) 

Income below median: 

PM2.5: 1.05 (1.01, 1.10) 

Individual: 1.52 (1.41, 1.63) 

Neighborhood: 1.13 (1.09, 1.18) 

Not owner occupied: M2.5: 1.07 (1.01, 1.14) 

Individual: 1.24 (1.12, 1.38) 

Neighborhood: 1.08 (1.02, 1.14) 

Lives in a flat dwelling: 

PM2.5: 1.05 (0.99, 1.11) 

Individual: 1.21 (1.09, 1.34) 

Neighborhood: 1.09 (1.02, 1.15) 

More than one person per room in 

dwelling: PM2.5: 1.11 (1.04, 1.19) 

Individual: 1.07 (0.99, 1.14) 

Neighborhood: 1.01 (0.96, 1.05) 

RR for Interquartile Increase (MI) in 

PM2.5 for different causes of death 

CVD: 

Age and sex adjusted: 1.11 (1.07, 1.15) 

Primary education only: 

M1+ Individual: 1.07 (1.04, 1.11) 

M1+ Neighborhood: 1.03 (1.00, 1.07) 

Manual Class: M1+ Individual: 1.08 

(1.04, 1.11) 

M1+ Neighborhood: 1.06 (1.02, 1.10) 

Income below Median: M1+ Individual: 

1.07 (1.03, 1.11) 

M1+ Neighborhood: 1.02 (0.98, 1.05) 

Not owner occupied: 

M1+ Individual: 1.05 (1.01, 1.09) 

M1+ Neighborhood: 1.03 (0.99, 1.07): 

Living in a Flat dwelling 

M1+ Individual: 1.04 (1.00, 1.08) 

M1+ Neighborhood: 1.01 (0.97, 1.05) 

Crowded household: 

M1+ Individual: 1.10 (1.05, 1.14) 

M1+Neighborhood: 1.10 (1.06, 1.15) 

Pulmonary Cancer: Age and sex 

adjusted: 1.12 (1.05, 1.19) 

Primary education only: 

M1+ Individual: 1.09 (1.01, 1.17) 

M1+ Neighborhood: 1.05 (0.98, 1.13) 

Manual Class: 

M1+ Individual: 1.09 (1.01, 1.17) 

M1+ Neighborhood: 1.10 (1.06, 1.13) 

Income below Median: 

M1+ Individual: 1.09 (1.01, 1.17) 

M1+ Neighborhood: 1.02 (0.95, 1.10) 

Not owner occupied: 

M1+ Individual: 1.07 (1.00, 1.15) 

M1+ Neighborhood: 1.04 (0.97, 1.12) 

Living in a Flat dwelling: 

M1+ Individual: 1.03 (0.96, 1.11) 

M1+ Neighborhood: 1.00 (0.92, 1.08) 

Crowded household: 

M1+ Individual: 1.10 (1.03, 1.14) 

M1+Neighborhood: 1.11 (1.04, 1.20) 

COPD: Age and sex adjusted: 

1.17 (1.09, 1.25) 

December 2009 E-510 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Primary education only: 

M1+ Individual: 1.13 (1.05, 1.22) 

M1+ Neighborhood: 1.09 (1.01, 1.19) 

Manual Class: 

M1+ Individual: 1.14 (1.05, 1.23) 

M1+ Neighborhood: 1.12 (1.04, 1.22) 

Income below Median: 

M1+ Individual: 1.13 (1.04, 1.22) 

M1+ Neighborhood: 1.06 (0.97, 1.15) 

Not owner occupied: M1+ Individual: 

1.10 (1.02, 1.19) 

M1+ Neighborhood: 1.07 (0.99, 1.16) 

Living in a Flat dwelling: 

M1+ Individual: 1.08 (1.00, 1.18) 

M1+ Neighborhood: 1.03 (0.95, 1.13) 

Crowded household: 

M1+ Individual: 1.16 (1.07, 1.26) 

M1+Neighborhood: 1.16 (1.07, 1.26) 

Estimates for psychiatric diseases, 

genetic cancer and violent death 

Reference: Nerriere et al. (2005, 

088630) 

Period of Study: 

Grenoble (2001) 

Paris (2002) 

Rouen (2002-2003) 

Strasbourg (2003) 

Location: Four French CitiesGrenoble, Rouen, Paris, and 

Strasbourg 

Outcome: Mortality: Lung Cancer (162)

Study Design: Time-series 

Statistical Analyses: GIS 

Age Groups: 30-71 yr old nonsmoking 

adults 

Pollutant: PM2.5

Averaging Time: 48-h avg 

Mean Range: 17 to 49 μg/m3 

Increment: 10 μg/m3 

% Increase (Lower CI, Upper CI) 

% increase in lung cancer deaths 

attributable to PM2.5 exposure 

France: 8 (1, 16) 

Grenoble: 10 (3, 19) 

Rouen: 10 (2, 19) 

Strasbourg: 24 (4, 40) 

Reference: Ozkaynak and Thurston 

(1987, 072960)

Period of Study: 1980 

Location: U.S. 

Outcome: Total Mortality 

Study Design: Cross-sectional 

Statistical Analyses: Multiple 

regression analysis 

Pollutant: Sulfate 

Averaging Time: Annual avg 

Mean Range: Sulfate: 11.1 (3.5) 

Range of estimated total mortality 

effects of air pollutions: 

Sulfate: 4-9% 

“Sulfate concentration was consistently 

found to be a significant predictor of 

mortality in the models considered. Fine 

particle mass coefficients were also 

often found to be statistically significant 

in the mortality regressions.” 

Reference: Pope et al. (2004, 055880) 

Period of Study: 1982-2000 

Location: Metropolitan areas in all 50 

states in the U.S. 

Outcome: Mortality: Cardiovascular 

Diseases (390-459) 

Diabetes (250) 

Respiratory Disease (460-519) 

Study Design: Prospective Cohort 

Statistical Analyses: Cox proportional 

hazards regression 

Age Groups: >30 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): 17.1 (3.7) 

Range (Min, Max): NR

Increment: 10 μg/m3 

Relative Risk (Lower CI, Upper CI) 

All cardiovascular disease plus 

diabetes: PM2.5: 1.12 (1.08, 1.15) 

Former Smoker: 1.26 (1.23, 1.28) 

Current Smoker: 1.94 (1.90, 1.99) 

Ischemic Heart Disease: PM2.5: 1.18 

(1.14, 1.23) 

Former Smoker: 1.33 (1.29, 1.37) 

Current Smoker: 2.03 (1.96, 2.10) 

Diabetes: PM2.5: 0.99 (0.86, 1.14) 

Former Smoker: 1.05 (0.94, 1.16) 

Current Smoker: 1.35 (1.20, 1.53) 

All other Cardiovascular Diseases: 

PM2.5: 0.84 (0.71, 0.99) 

Former Smoker: 1.22 (1.09, 1.38) 

Current Smoker: 1.78 (1.56, 2.04) 

Diseases of the respiratory system: 

PM2.5: 0.92 (0.86, 0.98) 

Former Smoker: 2.16 (2.04, 2.28) 

Current Smoker: 3.88 (3.66, 4.11) 

COPD: PM2.5: 0.84 (0.77, 0.93) 

Former Smoker: 4.93 (4.48, 5.42) 

Current Smoker: 9.85 (8.95, 10.84) 

All other respiratory diseases: PM2.5: 

0.86 (0.73, 1.02) 

Former Smoker: 1.54 (1.36, 1.74) 

Current Smoker: 1.83 (1.57, 2.12) 

December 2009 E-511 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Pope et al. (2007, 091256) 

Period of Study: 1960-1975 

Location: New Mexico, Arizona, Utah, 

and Nevada 

Outcome (ICD7&8): 

Mortality: Cardiovascular (ICD 7: 400-

468, 331, 332 ICD 8: 390-458) 

Respiratory (ICD 7: 470-527 ICD 8: 

460-519) 

Influenza/ pneumonia (ICD 7: 480-483, 

490-493, ICD 8: 470-474, 480-486) 

Study Design: Retrospective Cohort 

Statistical Analyses: Poisson 

regression model 

GAM 

SAS 

Age Groups: All smelter workers >18 

Pollutant: PM2.5

Averaging Time: 24-h avg 

Mean (SD): NR

Range (Min, Max): NR

The study does not present quantitative 

results 

Results are presented in figures. The 

References found that the strike-related 

estimated percent decrease in mortality 

was 2.5% (1.1-4.0), 

Reference: Pope et al. (2009, 190107) 

Period of Study: 1978-1982, 

1997-2001 

Location: 211 U.S. counties and 51 

metropolitan areas 

Outcome: Increased life expectancy 

Study Design: Cross-sectional 

Statistical Analysis: Cross-sectional 

regression 

Age Groups: Adults ≥45 yr 

Pollutant: PM2.5

Averaging Time: Daily, quarterly and 

annual 

Mean (SD) Unit: 

1979-1983: 20.61 ± 4.36 μg/m3

1999-2000: 14.10 ± 2.86 μg/m3

Range (Min, Max): NR 

Copollutant (correlation): NR 

Increment: 10 μg/m3

Regression Coefficient ± SD

211 County Units 

Intercept: 1.75 ± 0.27 

Reduction in PM2.5: 0.61 ± 0.20 

Change in Income: 0.13 ± 0.01 

Change in Population: 0.06 ± 0.02 

Change in Black Population: 

-2.70 ± 0.64 

Change in Lung Cancer Mortality Rate: 

-0.06 ± 0.02 

Change in COPD Mortality Rate: 

-0.08 ± 0.02 

R: 0.53 

51 Metropolitan Areas 

Intercept: 2.09 ± 0.36 

Reduction in PM2.5: 0.95 ± 0.23 

Change in Income: 0.11 ± 0.02 

Change in Population: 0.05 ± 0.02 

Change in Black Population: 

-5.98 ± 1.99 

Change in Lung Cancer Mortality Rate: 

0.02 ± 0.03 

Change in COPD Mortality Rate: 

-0.19 ± 0.05 

R: 0.74 

December 2009 E-512 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Rainham et al. (2005, 

088676) 

Period of Study: 1981-1999 

Location: Toronto, Canada 

Outcome: Total deaths (ICD9 <800), 

cardiorespiratory (390-459), noncardiorespiratory (ICD9-NR) 

Study Design: Time-series 

Statistical Analyses: Generalized 

linear models were used 

Season: Winter (Dec-Feb) 

Summer (Jun-Aug) 

Statistical Package: S-Plus 6.1 

Pollutant: PM2.5

Averaging Time: NR 

Mean (SD): 

All yr: 17.0 (8.7) μg/m3 

Winters: 17.2 (6.8) 

Summers: 18.8 (10.2) 

Avg Winter values: Dry Moderate: 17.0 

(1.0) 

Dry Polar: 17.5 (0.5) 

Dry Tropical: No Comparison 

Moist Moderate: 17.1 (0.8) 

Moist Polar: 17.5 (0.6) 

Moist Tropical: 16.5 (3.6) 

Transition: 16.7 (1.0) 

Avg summer values: Dry Moderate: 

18.4 (0.9) 

Dry Polar: 19.0 (1.2) 

Dry Tropical: 18.5 (2.4) 

Moist Moderate: 19.2 (1.2) 

Moist Polar: 17.5 (2.0) 

Moist Tropical: 19.8 (1.1) 

Transition: 17.6 (1.5) 

Mortality risk for winter season and 

within winter synoptic weather 

categories 

RR Estimate [Lower CI, Upper CI]: 

Winter: Total: 0.998[0.997, 1.000] 

Cardioresp: 0.998[0.996, 1.000] 

Other: 0.998 [0.996, 1.000] 

Dry Moderate: 

Total: 1.001[0.996, 1.007] 

Cardioresp: 1.005[0.998, 1.011] 

Other: 1.002 [0.998, 1.005] 

Dry Polar: Total: 0.998[0.995, 1.001] 

Cardioresp: 0.995[0.991, 0.999] 

Other: 1.002 [0.998, 1.005] 

Dry Tropical: NA 

Moist Moderate: 

Total: 0.998[0.993, 1.002] 

Cardioresp: 1.003[0.995, 1.010] 

Other: 0.997 [0.991, 1.004] 

Moist Polar: Total: 1.001[0.998, 1.005] 

Cardioresp: 1.002[0.997, 1.007] 

Other: 1.003 [0.999, 1.007] 

Moist Tropical: 

Total: 1.007[0.965, 1.203] 

Cardioresp: 1.123[1.031, 1.224] 

Other: 1.248 [1.123, 1.387] 

Transition Total: 1.003[0.996, 1.009] 

Cardioresp: 0.996[0.987, 1.004] 

Other: 0.997 [0.990, 1.004] 

Mortality risk for summer season and 

within summer synoptic weather 

categories 

RR Estimate [Lower CI, Upper CI]: 

Summer: Total: 1.000[1.000, 1.001] 

Cardioresp: 1.001[1.000, 1.002] 

Other: 1.001[1.000, 1.002] 

Dry Moderate: 

Total: 1.001[0.999, 1.002] 

Cardioresp: 1.002[0.999, 1.004] 

Other: 0.999[0.997, 1.002] 

Dry Polar: Total: 1.002[0.999, 1.005] 

Cardioresp: 0.996[0.991, 1.000] 

Other: 1.003[ 0.999, 1.007] 

Dry Tropical: Total: 1.016[1.006, 1.027] 

Cardioresp: 1.017[1.005, 1.030] 

Other: 1.017 [1.003, 1.031] 

Moist Moderate: 

Total: 1.002[1.000, 1.004] 

Cardioresp: 1.003[0.999, 1.006] 

Other: 1.004 [1.001, 1.006] 

Moist Polar: 

Total: 1.005[0.998, 1.011] 

Cardioresp: 1.008[0.997, 1.018] 

Other: 1.003 [0.995, 1.011] 

Moist Tropical: 

Total: 0.999[0.997, 1.001] 

Cardioresp: 0.996[0.993, 1.000] 

Other: 0.998 [0.995, 1.001] 

Transition: Total: 1.005[0.996, 1.014] 

Cardioresp: 1.007[0.994, 1.020] 

Other: 1.002 [0.996, 1.008] 

Reference: Roman et al. (2008, 

156921) 

Period of Study: 2006 

Location: U.S. 

Outcome: Mortality 

Study Design: Expert Judgment Study 

Statistical Analyses: Standard best 

practices for expert elicitation 

Pollutant: PM2.5

Averaging Time: Annual avg 

Mean (SD): 4-30 

Quantitative results are not presented in 

the text, but can be found graphically in 

Fig 3. 

“Most of the experts’ central estimates 

fall at or above the 2002 ACS median 

(0.6% per μg/m3

) and below the original 

Six Cities median (1.2% per μg/m3).” 

December 2009 E-513 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Schwartz, et al. (2008, 

156921)

Period of Study: 1979-1988

Location: Six U.S. metropolitan areas: 

Boston, Massachusetts 

Knoxville, Tennessee 

St. Louis, Missouri 

Steubenville, Ohio 

Madison, Wisconsin 

and Topeka, Kansas 

Outcome: Mortality 

Study Design: Poisson regression with 

GAM 

Statistical Analyses: Weighted linear 

regression 

Season: all 

Dose-response Investigated? No 

Statistical Package: S-plus 

Pollutant: PM2.5

Averaging Time: Daily

Mean (SD): 

Boston-16.5 

Knoxville-21.1 

St. Louis-19.2 

Steubenville-30.5 

Madison-11.3 

Topeka-12.2 

SD not reported 

Range (Min, Max): (0,35) 

Monitoring Stations: 6 

PM Increment: 10 μg/m3

The difference between mean PM2.5

concentrations of 10 μg/m3 and 20 

μg/m3

 is associated with about a 1.5% 

increase in deaths. 

Reference: (Schwartz et al., 2008, 

156963) 

Period of Study: 1979-1998 

Location: Watertown, MA 

Kingston and Harriman, TN 

St Louis, MO 

Steubenville, OH 

Portage, Wyocena 

Pardeeville WI 

Topeka, KS 

Outcome: Mortality: Nonaccidental 

(<800) 

Study Design: Cross-sectional 

Statistical Analyses: Cox proportional 

hazards regression 

penalized splines 

Bayesian Model Averaging 

Age Groups: >18 

Pollutant: PM2.5

Averaging Time: Annual avg

Mean (SD): 17.5 (6.8) 

Range (Min, Max): (8, 40)

Increment: 10 μg/m3 

Relative Risk (Lower CI, Upper CI)

Estimated from Fig 4: 

All Cause Mortality - Year before Death 

0: 1.10 (1.00, 1.21) 

1: 1.03 (0.98, 1.08) 

2: 1.01 (1.00, 1.02) 

3: 1.00 (0.99, 1.01) 

4: 1.00 (0.99, 1.01) 

5: 1.00 

Lung Cancer Mortality - Year Before 

Death 

Estimated from Fig 5 

0: 1.18 (1.00, 1.48) 

1: 1.12 (0.98, 1.33) 

2: 1.08 (0.92, 1.22) 

3: 1.02 (1.01, 1.03) 

4: 1.01 (1.00, 1.02) 

5: 1.01 

RR per 10 μg/m3

 increase of PM2.5

exposure 

Level Of Increase 

Estimated from Fig 3 

10 μg/m3: 1.15 

20 μg/m3

: 1.29 

30 μg/m3

: 1.46 

40 μg/m3: 1.64 

Reference: Tainio et al. (2005, 087444) 

Period of Study: 1997-Present 

Location: Helsinki, Finland 

Outcome (ICD10): Mortality: 

Cardiopulmonary (I11-I70 and J15-J47) 

Lung Cancer (C34) 

Other causes 

Study Design: Time-series simulation 

Statistical Analyses: Monte Carlo 

Simulation 

Age Groups: All ages 

Pollutant: PM2.5

Averaging Time: 24-h avg

Mean (SD): 10.7 

Range (Min, Max): NR

Estimated Deaths Per Year (Min CI, 

Max CI) Associated with Primary 

PM2.5 

Emissions from buses in Helsinki in 

2020 for different bus strategies 

Cardiopulmonary Mortality 

Current Fleet: 15.9 (0, 46.6) 

Modern Diesel: 7.9 (0, 23.0) 

Diesel with particle trap: 3.9 (0, 12) 

Natural gas bus: 2.3 (0, 6.8) 

Lung Cancer Mortality 

Current Fleet: 2.2 (0, 6.1) 

Modern Diesel: 1.1 (0, 3.0) 

Diesel with particle trap: 0.6 (0, 1.6) 

Natural gas bus: 0.3 (0, 0.9) 

Total Mortality 

Current Fleet: 18.1 (0, 55.0) 

Modern Diesel: 9.0 (0, 27.0) 

Diesel with particle trap: 4.4 (0, 14.1) 

Natural Gas Bus: 2.6 (0, 8.0) 

December 2009 E-514 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Villeneuve et al. (2002, 

042576) 

Period of Study: 1974-1991 

Location: Six U.S. Cities: Steubenville, 

OH, St. Louis, MO, Portage, WI, 

Topeka, KS, Watertown, MA, Kingston/ 

Harriman, TN 

Outcome (ICD10): Mortality: 

Nonaccidental (<800) 

Study Design: Prospective Cohort 

Statistical Analyses: Poisson, 

EPICURE 

Age Groups: All ages 

<60 

≥ 60 

Pollutant: PM2.5

Averaging Time: 24-h avg

Mean (SD): Portage: 10.9 (7.2) 

Topeka: 12.1 (7.1) 

Harriman: 20.7 (9.4) 

Watertown: 14.9 (8.4) 

St. Louis: 18.7 (10.6) 

Steubenville: 28.6 (21.0) 

Overall: 18.6 

Range (Min, Max): NR

Increment: 18.6 μg/m3 

Relative Risk (Min CI, Max CI) 

RR of all cause mortality for exposure of 

PM2.5 by age group

Exposure to PM2.5 remained fixed over 

entire study period 

<60: 1.89 (1.32, 2.69) 

>60: 1.21 (1.02, 1.43) 

Total: 1.31 (1.12, 1.52) 

Exposure to PM2.5 was defined 

according to 13 calendar periods* (no 

smoothing) 

<60: 1.52 (1.15, 2.00) 

>60: 1.11 (0.95, 1.29) 

Total: 1.19 (1.04, 1.36) 

Exposure to PM2.5 was defined 

according to 13 calendar periods* 

(smoothed) 

<60: 1.43 (1.10, 1.85) 

>60: 1.09 (0.93, 1.26) 

Total: 1.16 (1.02, 1.32) 

Time dependent estimate of PM2.5

received during the previous 2 yr 

<60: 1.42 (1.09, 1.82) 

>60: 1.08 (0.94, 1.25) 

Total: 1.16 (1.02, 1.31) 

Time dependent estimate of PM2.5

received 3-5 yr before current yr 

<60: 1.35 (1.08, 1.67) 

>60: 1.08 (0.95, 1.22) 

Total: 1.14 (1.02, 1.27) 

Time dependent estimate of PM2.5

received >5 yr before current yr 

<60: 1.34 (1.11, 1.59) 

>60: 1.09 (0.99, 1.20) 

Total: 1.14 (1.05, 1.23) 

* The calendar periods used were: 

1970-1978, 1979, 1980, 1981, 1982, 

1983, 1984, 1985, 1986, 1987, 1988, 

1989, and 1990+. 

RR of all cause mortality and PM2.5

exposure by city 

Portage: 1.16 (0.96, 1.39) 

Topeka: 1.06 (0.89, 1.27) 

Harriman 

Men: 1.04 (0.79, 1.36) 

Women: 0.96 (0.69, 1.31) 

All: 1.13 (0.95, 1.35) 

Watertown 

Men: 1.20 (0.95, 1.51) 

Women: 1.06 (0.78, 1.43) 

All: 1.32 (1.11, 1.51) 

St. Louis 

Men: 0.97 (0.76, 1.24) 

Women: 1.13 (0.86, 1.49) 

Steubenville 

Men: 1.39 (1.11, 1.74) 

Women: 1.22 (0.93, 1.61) 

Reference: Willis et al. (2003, 089922) 

Period of Study: 1982-1989 

Location: U.S. Metropolitan areas in all 

50 states 

Outcome: Mortality: All causes 

Lung Cancer (162) 

Cardiopulmonary (401-440, 460-519) 

Study Design: Prospective Cohort 

Statistical Analyses: Cox proportional 

hazards model 

Age Groups: All ages 

Pollutant: Sulfates 

Averaging Time: Annual avg 

Mean (SD): 10.6 μg/m3

Range (Min, Max): 3.6, 23.5

Copollutant: CO, NO2, O3, SO2

All Cause, Metropolitan Scale: 1.25 

(1.13, 1.37) 

All Cause, County Scale: 1.50 (1.30, 

1.73) 

CPD, Metropolitan Scale: 1.29 (1.15, 

1.46) 

CPD, County Scale: 1.75 (1.48, 2.08) 

Reference: Zanobetti and Schwartz 

(2009, 188462) 

Period of Study: 1999-2005 

Location: 112 U.S. Cities 

Outcome: Mortality, all causes, 

excluding ICD codes S00-U99 

Study Design: Time-series 

Covariates: Region, season 

Pollutant: PM2.5

Averaging Time: 24 h 

Mean (SD) 

Birmingham AL - 16.5 

Phoenix AZ - 11.4 

LittleRock AR - 14.3 

Increment: 10 μg/m3

Percent Increase (95% CI) in 

mortality by increment of PM2.5, 

combined by season 

All Cause Mortality 

Overall: 0.98 (0.75-1.22) 

December 2009 E-515 
Concentrations

1 Study Design & Methods Effect Estimates (95% CI) 

Statistical Analysis: Poisson 

regression 

Age Groups: All 

Fresno CA - 19.4 

Bakersfield CA - 21.7 

Los Angeles CA - 19.9 

Anaheim CA - 16.3 

Rubidoux CA - 24.9 

Sacramento CA - 13.0 

El Cajon CA - 13.5 

Denver CO - 10.3 

Hartford CT - 11.6 

New Haven CT - 13.7 

Wilmington DE - 15.1 

Davie FL - 8.4 

Miami FL - 9.4 

Jacksonville FL - 10.6 

Pensacola FL - 12.4 

Tampa FL - 11.9 

Orlando FL - 10.3 

Palm beach FL - 7.9 

Pinellas FL - 10.4 

Atlanta GA - 17.6 

Chicago IL - 15.9 

Gary IN - 15.3 

Indianapolis IN - 16.3 

Cedar Rapids IA - 11.0 

Des Moines IA - 10.5 

Davenport IA - 12.3 

Louisville KY - 15.9 

Baton Rouge LA - 13.4 

Avondale LA - 12.3 

New Orleans LA - 12.6 

Baltimore MD - 15.6 

Springfield MA - 12.3 

Boston MA - 12.4 

Worcester MA - 11.3 

Holland MI - 12.1 

Grand Rapids MI - 13.6 

Detroit MI - 16.2 

Minneapolis MN - 11.1 

Kansas MO - 12.0 

St Louis MO - 14.5 

Omaha NE - 10.4 

Elizabeth NJ - 14.7 

Albuquerque NM - 6.7 

New York NY - 14.8 

Bath NY - 9.6 

Durham NC - 14.3 

Winston NC - 14.7 

Greensborough NC - 14.2 

Charlotte NC - 15.3 

Raleigh NC - 14.3 

Middletown OH - 16.4 

Youngstown OH - 15.6 

Cleveland OH - 16.4 

Columbus OH - 16.2 

Cincinnati OH - 17.1 

Steubenville OH - 17.0 

Toledo OH - 14.9 

Dayton OH - 16.2 

Akron OH - 16.0 

Warren OH - 15.3 

Oklahoma OK - 9.9 

Tulsa OK - 11.1 

Bend OR - 7.8 

Medford OR - 9.9 

Klamath OR - 10.6 

Eugene OR - 8.0 

Portland OR - 8.8 

Gettysburg PA - 13.4 

Pittsburgh PA - 15.7 

State College PA - 13.2 

Carlisle PA - 15.1 

Harrisburg PA - 15.5 

Erie PA - 13.1 

Scranton PA - 11.8 

Allentown PA - 14.2 

Wilkes Barre PA - 12.8 

Mercer PA - 14.1 

Easton PA - 14.0 

Winter: 0.56 (0.17-0.94) 

Spring: 2.57 (1.96-3.19) 

Summer: 0.25 (-0.13-0.63) 

Fall: 0.95 (0.56-1.34) 

CVD 

Overall: 0.85 (0.46-1.24) 

Winter: 0.70 (0.04-1.36) 

Spring: 2.18 (1.22-3.15) 

Summer: -0.03 (-0.75-0.69) 

Fall: 0.92 (0.17-1.68) 

MI 

Overall: 1.18 (0.48-1.89) 

Winter: 1.29 (-0.14-2.75) 

Spring: 2.12 (0.53-3.74) 

Summer: -0.03 (-1.46-1.42) 

Fall: 1.24 (0.12-2.36) 

Stroke 

Overall: 1.78 (0.96-2.62) 

Winter: 1.93 (0.34-3.54) 

Spring: 2.04 (-0.02-4.13) 

Summer: 1.64 (0.05-3.26) 

Fall: 1.69 (0.06-3.35) 

Respiratory 

Overall: 1.68 (1.04-2.33) 

Winter: 0.86 (-0.16-1.88) 

Spring: 4.62 (3.08-6.18) 

Summer: 0.78 (-0.49-2.06) 

Fall: 1.45 (0.19-2.72) 

Percent Increase (95% CI) in 

mortality by increment in PM2.5

combined by region 

All Cause Mortality 

Humid Subtropical and Maritime: 

1.02 (0.65-1.38) 

Warm Summer Continental: 

1.19 (0.73-1.64) 

Hot Summer Continental: 

1.14 (0.55-1.73) 

Dry: 1.18 (-0.70-3.10) 

Dry, Continental: 1.26 (-0.21-2.76) 

Mediterranean: 0.50 (0.00-1.01) 

CVD 

Humid Subtropical and Maritime: 

0.78 (0.05-1.51) 

Warm Summer Continental: 

1.43 (0.67-2.19) 

Hot Summer Continental: 

0.43 (-0.53-1.40) 

Dry: 3.11 (-0.02-6.33) 

Dry, Continental: 1.67 (-0.75-4.16) 

Mediterranean: 0.16 (-0.46-0.79) 

MI 

Humid Subtropical and Maritime: 

0.97 (-0.29-2.26) 

Warm Summer Continental: 

1.50 (0.05-2.97) 

Hot Summer Continental: 

0.64 (-0.96-2.28) 

Dry: 4.25 (-2.38-11.33) 

Dry, Continental: 0.60 (-7.42-9.32) 

Mediterranean: 1.85 (-0.66-4.41) 

Stroke 

Humid Subtropical and Maritime: 

2.94 (1.59-4.32) 

Warm Summer Continental: 

1.85 (0.04-3.69) 

Hot Summer Continental: 

0.77 (-1.77-3.38) 

Dry: 1.82 (-6.98-11.45) 

Dry, Continental: 2.49 (-2.32-7.53) 

Mediterranean: 0.95 (-0.66-2.59) 

Respiratory 

Humid Subtropical and Maritime: 

0.91 (-0.25-2.08) 

Warm Summer Continental: 

2.12 (0.89-3.36) 

Hot Summer Continental: 

December 2009 E-516 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Philadelphia PA - 14.5 

Washington PA - 14.7 

Providence RI - 11.5 

Charleston SC - 12.1 

Taylors SC - 15.3 

Columbia SC - 14.0 

Spartanburg SC - 14.2 

Nashville TN - 14.0 

Knoxville TN - 16.0 

Memphis TN - 13.5 

San Antonio TX - 9.4 

Dallas TX - 12.9 

El Paso TX - 9.2 

Houston TX - 12.9 

Port Arthur TX - 11.5 

Ft Worth TX - 12.2 

Austin TX - 10.4 

Salt Lake UT - 11.5 

Provo UT - 9.5 

WDC VA - 15.2 

Annandale VA - 14.0 

Dumbarton VA - 13.6 

Chesapeake VA - 12.7 

Norfolk VA - 12.7 

Richmond VA - 14.3 

Seattle WA - 10.1 

Tacoma WA - 11.2 

Spokane WA - 9.1 

Dodge WI - 11.1 

Milwaukee WI - 13.2 

Waukesha WI - 13.2 

Range (Min, Max): NR 

Copollutant (correlation): NR 

3.36 (1.95-4.79) 

Dry: 5.81 (-0.04-12.00) 

Dry, Continental: -0.31 (-5.89-5.61) 

Mediterranean: 1.06 (-0.36-2.50) 

Reference: Zeger et al. (2007, 157176) 

Period of Study: 2000-2002 

Location: 250 largest U.S. counties 

Outcome: Mortality 

Study Design: Retrospective Cohort 

(MCAPS) 

Statistical Analyses: Log-linear 

regression models (GAM) 

Covariates: Age, gender, race, countylevel SES, education and COPD SMR 

Age Groups: 65+ 

65-74, 75-84, 85+ 

Pollutant: PM2.5

Averaging Time: 3-yr avg 

Increment: 10 μg/m3 

65+: 1.076 (1.044, 1.108) 

Eastern U.S.: 1.125 (1.091, 1.159) 

Central U.S.: 1.196 (1.115, 1.277) 

Western U.S.: 1.029 (0.994, 1.064) 

65-74: 1.156 (1.117, 1.196) 

75-84: 1.081 (1.042, 1.121) 

85+: 0.995 (0.956, 1.035) 

December 2009 E-517 
Concentrations1 Study Design & Methods Effect Estimates (95% CI) 

Reference: Zeger et al. (2008, 191951) 

Period of Study: 2000-2005 

Location: 4568 zip codes in urban areas 

Outcome: Mortality 

Study Design: Retrospective Cohort 

Statistical Analysis: Log-linear 

regression model 

Age Groups: ≥65 

Pollutant: PM2.5 

Averaging Time: Annual 

Median (SD) Unit: 

Eastern: 14.0 μg/m3

Central: 10.7 μg/m3

Western: 13.1 μg/m3

All: 13.2 μg/m3

 

Range (IQR): 

Eastern: 12.3-15.3 

Central: 9.8-12.2 

Western: 10.4-18.5 

All: 11.1-14.9 

Copollutant (correlation): NR 

Increment: 10 μg/m3

Relative Risk (Min CI, Max CI) lag 

Risk estimate for increase in mortality 

per increase in PM2.5 , all ages 

Eastern Region 

Age: 1.155 (1.130-1.180) 

Age + SES: 1.105 (1.084-1.125) 

Age + SES + COPD: 

1.068 (1.049-1.087) 

Central Region 

Age: 1.178 (1.133-1.222) 

Age + SES: 1.089 (1.052-1.125) 

Age + SES + COPD: 

1.132 (1.095-1.169) 

Western Region 

Age: 1.003 (0.981-1.025) 

Age + SES: 0.997 (0.978-1.016) 

Age + SES + COPD: 

0.989 (0.970-1.008) 

Risk estimate for increase in mortality 

per increase in PM2.5, ages 65-74 

Eastern Region 

Age: 31.1 (26.8-35.5) 

Age + SES: 17.3 (14.6-20.0) 

Age + SES + COPD: 11.4 (8.8-14.1) 

Central Region 

Age: 39.0 (29.7-48.2) 

Age + SES: 16.5 (10.9-22.1) 

Age + SES + COPD: 20.4 (15.0-25.8) 

Western Region 

Age: 6.0 (2.3-9.6) 

Age + SES: -2.1 (-5.0-0.8) 

Age + SES + COPD: -1.5 (-4.2-1.1) 

Risk estimate for increase in mortality 

per increase in PM2.5, ages 75-84 

Eastern Region 

Age: 17.6 (14.9-20.4) 

Age + SES: 12.4 (10.1-14.6) 

Age + SES + COPD: 8.9 (6.8-11.0) 

Central Region 

Age: 17.5 (12.7-22.2) 

Age + SES: 8.8 (4.6-13.0) 

Age + SES + COPD: 12.0 (7.6-16.4) 

Western Region 

Age: 0.4 (-2.0-2.7) 

Age + SES: 0.3 (-1.8-2.5) 

Age + SES + COPD: -0.2 (-2.2-1.9) 

Risk estimate for increase in mortality 

per increase in PM2.5, aged ≥85 

Eastern Region 

Age: -1.4 (-3.5-0.8) 

Age + SES: 1.4 (-0.7-3.5) 

Age + SES + COPD: 1.7 (-0.3-3.7) 

Central Region 

Age: -2.1 (-5.9-1.6) 

Age + SES: -0.7 (-4.2-2.8) 

Age + SES + COPD: -0.3 (-4.0-3.3) 

Western Region 

Age: -5.2 (-7.2-3.2) 

Age + SES: 0.9 (-0.8-2.7) 

Age + SES + COPD: -0.5 (-2.5-1.5) 

1

All units expressed in μg/m3 unless otherwise specified. 

December 2009 E-518 
Table E-34. Long-term exposure - central nervous system outcomes - PM. 

Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Author: Calderón-Garcidueñas et al. 

(2008, 192369) 

Period of Study: NR 

Location: Mexico City (polluted city) 

and Tlaxcala and Veracruz (control 

cities), Mexico 

Outcome (ICD9 and ICD10): COX2 

(cyclooxygenase), IL-1β, CD14 in lungs, 

OB (olfactory bulb), frontal cortex, 

hippocampus, substantia nigrae, 

periaqueductal gray and vagus nerves 

Age Groups Analyzed: 

Subjects 2-45 yr of age 

mean=25.1 ± 1.5 yr 

Study Design: 

Cross-sectional 

N: 47 deceased subjects with complete 

autopsies and neuropathological 

examinations (each subject had to be 

considered clinically healthy and 

cognitively and neurologically intact 

prior to death) (primarily cause of death: 

accidents resulting in immediate death) 

Statistical Analyses: NR 

likely used T-tests 

in addition, stated using “parametric 

procedure that considers the 

differences among variances of the 

variables of interest” 

Covariates: Age, gender, place of birth, 

place of residency, occupation, smoking 

habits, clinical histories, cause of death, 

and time between death and autopsy 

Season: NR 

Dose-response Investigated? 

(Yes/No): No 

Statistical package: Stata 

PM Size: No measure of PM 

used Mexico City as the “polluted city” 

and Tlaxcala and Veracruz as the 

“control cities” 

Averaging Time: NA

Mean (SD): NA 

Percentiles: NA 

Range (Min, Max): NA 

Unit (i.e. μg/m3): NA 

Number of Monitoring Stations: NA 

Co-pollutant (correlation): 

NA

PM Increment: NA 

Effect Estimate [Lower CI, Upper CI]: 

RT-PCR sample results from Control 

and Mexico City (MC) lung, CNS, PNS 

(peripheral nervous system) tissues and 

p-value for the difference between the 

means 

Concentrations are normalized to the 

amount of GAPDH cDNA 

COX2 (cyclooxygenase-2) lung 

Controls: 15.9± 6.7 x 106 

MC residents: 42.3± 7.4 x 106

P-value: 0.015 

IL-1β lung 

Controls: 3.08±1.87 x 106 

MC residents: 4.51± 2.6 x 106 

P-value: 0.60 

COX2 OB (olfactory bulb) 

Controls: 12.9± .0 x 105 

MC residents: 38.7± 5.5 x 105 

P-value: 0.0002 

IL-1β OB 

Controls: 3.4± 0.8 x 104 

MC residents: 7.7± 1.0 x 104 

P-value: 0.003 

CD14 OB 

Controls: 0.01± 0.001 

MC residents: 0.04± 0.01 

P-value: 0.04 

COX2 frontal 

Controls: 2.6± 0.4 x 105 

MC residents: 5.0± 0.7 x 105 

P-value: 0.008 

IL-1β frontal 

Controls: 0.6± 0.2 x 104 

MC residents: 6.2± 1.3 x 104 

P-value: 0.0002 

COX2 hippocampus 

Controls: 1.9± 0.5 x 105 

MC residents: 1.6± 8.7 x 105 

P-value: 0.1 

IL-1β hippocampus 

Controls: 1.8±0.2 x 104 

MC residents: 3.0±0.5 x 104 

P-value: 0.06 

COX2 substantia nigrae 

Controls: 0.16± 0.06 

MC residents: 0.97± 0.2 

P-value: 0.03 

IL-1β substanita nigrae 

Controls: 0.01± 0.005 

MC residents: 0.09± 0.03 

P-value: 0.06 

CD14 substantia nigrae 

Controls: 0.02± 0.005 

MC residents: 0.03± 0.007 

P-value: 0.7 

COX2 periaqueductal gray 

Controls: 0.10± 0.03 

MC residents: 0.45± 0.12 

P-value: 0.12 

IL-1β periaqueductal gray 

Controls: 0.009± 0.003 

MC residents: 0.07± 0.02 

P-value: 0.09 

COX2 left vagus 

Controls: 0.65± 0.18 

MC residents: 2.68± 0.82 

P-value: 0.03 

COX2 right vagus 

Controls: 0.43± 0.09 

December 2009 E-519 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

MC residents: 3.68± 0.8 

P-value: 0.0002 

IL-1β left vagus 

Controls: 0.1± 0.03 

MC residents: 1.3± 0.73 

P-value: 0.06 

IL-1 β right vagus 

Controls: 0.15± 0.09 

MC residents: 0.87± 0.53 

p-value: 0.66 

CD14 left vagus 

Controls: 0.07± 0.01 

MC residents: 0.79± 0.41 

P-value: 0.01 

CD14 right vagus 

Controls: 0.05± 0.01 

MC residents: 0.31± 0.1 

P-value: 0.02 

Distribution of subjects with expression 

of Aβ42 as a function of age and 

residency 

Groups: No (%) with Aβ42 expression 

Controls <25yr APOE 3/3 (n=6): 0 (0) 

Controls >25yr APOE 3/3 (n=3): 0 (0) 

MC E2 or E3 <25yr (n=17): 10 (58.82) 

MC E2 or E3 >25yr (n=10): 8 (80) 

MC E4 (n=8): 8 (100) 

Controls E4 (n=3): 2 (66) 

Distribution of subjects with expression 

of α-synuclein as a function of age and 

Residency 

Groups: No (%) with α-synuclein 

expression 

Controls <25yr APOE 3/3 (n=6): 0 (0) 

Controls >25yr APOE 3/3 (n=3): 0 (0) 

MC E2 or E3 <25yr (n=17): 4 (23.5) 

MC E2 or E3 >25yr (n=10): 3 (30) 

MC E4 (n=8): 2 (25) 

Controls E4 (n=3): 0 (0) 

Reference: Chen and Schwartz (2009, 

179945) 

Period of Study: 1989-1991 

Location: U.S. 

Outcome: Change in central nervous 

system function 

Study Design: Panel 

Covariates: Age, sex, race/ethnicity, 

individual socioeconomic position, 

lifestyle factors, household and 

neighborhood characteristics, 

conventional CVD risk factors 

Statistical Analysis: Pearson Chisquare tests and t-tests, as appropriate 

Statistical Package: STATA 

Age Groups: 20-59 yr 

Pollutant: PM10

Averaging Time: 1 yr 

Mean (SD) Unit: 37.2 ± 12.8 μg/m3

Copollutant: O3

Increment: 10 μg/m3

Regression Coefficient β (95% CI)

Crude 

SRTT: 2.14 (-0.08-4.36) 

SDST: 0.08 (0.04-0.13) 

SDLT Trials: 0.22 (0.13-0.31) 

SDLT Total: 0.44 (0.23-0.65) 

Model 1: adjusted for age, sex, 

race/ethnicity 

SRTT: 2.03 (-0.15-4.20) 

SDST: 0.10 (0.05-0.15) 

SDLT Trials: 0.23 (0.14-0.32) 

SDLT Total: 0.48 (0.27-0.68) 

Model 2: Model 1 + socioeconomic 

factors 

SRTT: -0.11 (-2.38-2.16) 

SDST: 0.01 (-0.04-0.06) 

SDLT Trials: 0.01 (-0.08-0.10) 

SDLT Total: -0.07 (-0.27-0.13) 

Model 3: Model 2 + lifestyle factors 

SRTT: -0.36 (-2.58-1.85) 

SDST: 0.00 (-0.04-0.05) 

SDLT Trials: 0.09 (0.00-0.17) 

SDLT Total: 0.12 (-0.07-0.31) 

December 2009 E-520 
Study Design & Methods Concentrations1 Effect Estimates (95% CI) 

Author: Suglia et al. (2008, 157027) 

Period of Study: 1986-2001 

Location: Boston, Massachusetts 

Outcome (ICD9 and ICD10): 

Cognition: 

Kaufman Brief Intelligence Test, K-BIT 

(vocabulary and matrices subscales 

and composite IQ score) 

Wide Range Assessment of Memory 

and Learning, WRAML (psychometric 

instrument with subscales on verbal 

memory, visual memory, learning, and 

overall general index scale) 

All cognition scores have a mean of 100 

and SD=15. 

Age Groups Analyzed: Cognitive tests 

administered when children were 8-11 

yr of age

Study Design: Cross-sectional

N: 202 children 

Statistical Analyses: Linear regression

Covariates: Child’s age at cognitive 

assessment, gender, primary language 

spoken at home, and maternal 

education (model 1 

“Demographic factors”) 

Sensitivity analyses performed with 

further adjustment for in-utero and 

postnatal secondhand tobacco smoke 

exposure (via questionnaire during 

follow-ups and urinary cotinine levels) 

(model 2) 

Birth weight (model 3) and blood lead 

level (model 4) 

Season: Separate land-use regression 

models were fit for the warm (May-Oct) 

and cold (Nov-Apr) seasons 

Used avg of two seasons as measure 

of avg lifetime BC exposure 

Dose-response Investigated? 

(Yes/No): No 

Statistical package: SAS (v9.0) 

PM Size: Black carbon (BC) 

Averaging Time: Lifetime exposure 

Estimated 24 h measures of traffic 

using a spatiotemporal land-use 

regression model using data from >80 

locations in Greater Boston (6021 

pollution measurements from 2127 

unique exposure days) 

Predictors in the land-use regression 

analysis were the BC level at a central 

station (to capture avg concentrations 

on that day), meteorological conditions, 

weekday/weekend, and measure of 

traffic activity (GIS-based measures of 

cumulative traffic density within 100m, 

population density, distance to nearest 

major roadway, % urbanization) 

Used the avg of the cold and warm 

seasons as the measure of avg lifetime 

BC exposure 

Mean (SD): 0.56 (0.13) μg/m3 

Percentiles: NR 

Range (Min, Max): NR 

Unit (i.e. μg/m3): 

Number of Monitoring Stations: >80 

locations 

Co-pollutant (correlation): NA 

PM Increment: 0.4 μg/m3

Effect Estimate [Lower CI, Upper CI]: 

Change in subscale score (95%CI) per 

IQR (0.4 μg/m3

) increase in log BC level

K-BIT 

Vocabulary: 

Adj for demographic factors: -2.0 (-5.3, 

1.3) 

Adj for above factors + secondhand 

smoke: -2.0 (-5.3, 1.4) 

Adj for above factors + birth weight: -

2.0 (-5.4, 1.3) 

Adj for above factors + blood lead level: 

-2.2 (-5.5, 1.1) 

Matrices: 

Adj for demographic factors: 

-4.2 (-7.7, -0.7) 

Adj for above factors + secondhand 

smoke: -4.0 (-7.5, -0.4) 

Adj for above factors + birth weight: 

-4.0 (-7.6, -0.5) 

Adj for above factors + blood lead level: 

-4.0 (-7.6, -0.5) 

Composite: 

Adj for demographic factors: 

-3.4 (-6.6, -0.3) 

Adj for above factors + secondhand 

smoke: -3.3 (-6.4, -0.1) 

Adj for above factors + birth weight: 

-3.3 (-6.5, -0.2) 

Adj for above factors + blood lead level: 

-3.4 (-6.6, -0.3) 

WRAML 

Verbal: 

Adj for demographic factors: 

 -1.1 (-4.6, 2.3) 

Adj for above factors + secondhand 

smoke: -1.2 (-4.7, 2.3) 

Adj for above factors + birth weight: 

-1.3 (-4.7, 2.2) 

Adj for above factors + blood lead level: 

-1.3 (-4.8, 2.2) 

Visual: 

Adj for demographic factors: 

-5.2 (-8.6, -1.7) 

Adj for above factors + secondhand 

smoke: -5.3 (-8.8, -1.8) 

Adj for above factors + birth weight: 

-5.3 (-8.8, -1.8) 

Adj for above factors + blood lead level: 

-5.4 (-8.9, -1.9) 

Learning: 

Adj for demographic factors: 

-2.7 (-6.5, 1.1) 

Adj for above factors + secondhand 

smoke: -2.6 (-6.5, 1.2) 

Adj for above factors + birth weight: 

-2.6 (-6.5, 1.3) 

Adj for above factors + blood lead level: 

-2.8 (-6.6, 1.1) 

General: 

Adj for demographic factors: 

-3.7 (-7.2, -0.2) 

Adj for above factors + secondhand 

smoke: -3.7 (-7.3, -0.1) 

Adj for above factors + birth weight: 

-3.8 (-7.4, -0.2) 

Adj for above factors + blood lead level: 

-3.9 (-7.5, -0.3) 

1

All units expressed in μg/m3 unless otherwise specified.

December 2009 E-521 
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