Addendum to the BenMAP User's Manual Appendices (October 2012)
Created 1/11/2013
The purpose of this addendum is to update the BenMAP User's Manual Appendices to incorporate the
information applied in the 2012 PM NAAQS RIA (U.S. EPA, 2012).
Appendix E: Particulate Matter Health Impact Functions in U.S. Setup
E.l Long-term Mortality
Table E-l. Health Impact Functions for Particulate Matter and Long-Term Mortality
Effect
Author
Year
Location
Age
Metric
Beta
Std Err
Form
Notes
Mortality, All Cause
Lepeule et
al.
2012
6 Cities
25-
99
Annual
0.013103
0.000107
log-
linear

E.1.7 Lepeule et al. (2012)
Lepeule et al. (2012) evaluated the sensitivity of previous Six Cities results to model specifications, lower
exposures, and averaging time using eleven additional years of cohort follow-up that incorporated
recent lower exposures. The authors found significant associations between PM2.5 exposure and
increased risk of all-cause, cardiovascular and lung cancer mortality. The authors also concluded that the
concentration-response relationship was linear down to PM2.5 concentrations of 8 ng/m3, and that
mortality rate ratios for PM2.5 fluctuated over time, but without clear trends, despite a substantial drop
in the sulfate fraction.
E.2 Chronic / Severe Illness
Table E-6. Health Impact Functions for Particulate Matter and Chronic Illness
Effect
Author
Year
Location
Age
Metric
Beta
Std Err
Form
Notes
Stroke
Miller
et al.
2007
36 U.S.
Metropolitan
Cities
50-79

D24HourMean
0.0247
0.0116
Log-
linear
E.2.2 Adjustment (Update): Based on recent data from the Agency for Healthcare Research and
Quality's Healthcare Utilization Project National Inpatient Sample database (AHRQ, 2009), we identified
death rates for adults hospitalized with acute myocardial infarction stratified by age (e.g., 1.852% for
ages 18-44, 2.8188% for ages 45-64, and 7.4339% for ages 65+). These rates show a clear downward
trend over time between 1994 and 2009 for the average adult and thus replace the 93% survival rate
previously applied across all age groups from Rosamond et al. (1999).
E.4.4 Miller et al. (2007)
Miller et al. (2007) examined the effects of long-term exposure to PM2 5 with cardiovascular events in
postmenopausal women (50-79 years old) in 36 U.S. metropolitan cities from 1994-1998. In particular,
coronary heart disease, cerebrovascular disease, myocardial infarction, coronary revascularization, and
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stroke were examined as the cardiovascular outcomes. 65,893 women without previous cardiovascular
disease were assessed in relation to their exposure to PM25 using the monitor located nearest to each
woman's residence. After adjusting for age, race, smoking status, educational level, household income,
body-mass index, diabetes, hypertension, and hypercholesterolemia, hazard ratios were estimated for
the first cardiovascular event. Each increase of 10 ug/m3 of PM25 was associated with a 24% increase in
the risk of any cardiovascular event (95% CI: 1.09-1.41) and a 76% increase in the risk of death from
cardiovascular disease (95% CI: 1.25-2.47). Also, the risk of cerebrovascular events was associated with
increased levels of PM25with a hazard ratio of 1.35 (95% CI: 1.08-1.68).
Cardiovascular Events, Stroke
In a single-pollutant model the coefficient and standard error were estimated from the hazard ratio
(1.28) and 95% confidence interval (95% CI: 1.02-1.61) for a 10 ug/m3 increase in the annual mean PM25
concentration in postmenopausal women 50-79 years old (Miller et al., 2007, Table 3).
E.3 Hospitalizations
Table E-7. Health Impact Functions for Particulate Matter and Hospital Admissions
Effect
Author
Year
Location
Age
Metric
Beta
Std Err
Form
Notes
All
Respiratory
Kloog et
al.
2012
New
England
65-
99
D24HourMean
0.0007
0.0010
Log-
linear

E.3.11 Kloog et al. (2012)
Kloog et al. (2012) examined the relationship between both short-term and long-term PM2 5 exposure
and emergent hospital admissions for respiratory (ICD-9 codes 460-519) and cardiovascular (ICD-9 codes
390-429) diseases in the New-England states of Connecticut, Maine, Massachusetts, New Hampshire,
Rhode Island and Vermont. The study used hospital admission data from the U.S. Medicare program for
only patients that were at least 65 years old. Short-term exposure models looked at the mean 24-hour
PM2.s concentration on the day of a patient's hospital admission, while long-term exposure was defined
to be the mean PM2 5 concentration over the entire study period (2000-2006). Results of the study
showed an association between PM2 5 and hospital admissions for all disease types in both the short and
long term.
Hospital Admissions, Respiratory (ICD Codes 460-519)
In a single pollutant model for patients over the age of 65, the coefficient and standard error were
estimated from the percent change (0.70%) and 95% confidence interval (0.35%-1.05%) for a 10 ug/m3
increase in same day (0 lag) 24-hour mean PM2 5 concentration.
E.4 Emergency Room Visits
Table E-8. Health Impact Functions for Particulate Matter and Emergency Room Visits
Effect
Author
Year
Location
Age
Metric
Beta
Std Err
Form
Notes
Asthma
Glad et
al.
2012
Pittsburgh,PA
18-
64
D24HourMean
0.0052
0.0032
Logistic
All
Races
Cardiovascular
Mathes
et al.
2011
Detroit,Ml
2-
18
D24HourMean
0.0039
0.0011
Logistic
all
year
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Cardiovascular
Tolbert et
2007
Atlanta, GA
0-
D24HourMean
0.0005
0.0005
Log-


al.


99



linear

Cardiovascular
Metzger
2004
Atlanta, GA
0-
D24HourMean
0.0032
0.0011
Log-


et al.


99



linear

E.4.4 Glad et al. (2012)
Glad et al. (2012) examined the relationship between air pollution and emergency department visits for
asthma (ICD-9 code 493) in six Pittsburgh, PA hospitals between 2002 and 2005. The study includes a
total of 6,979 individuals with a primary discharge diagnosis of asthma. Using a case-crossover
methodology, which controls for the effects of subject-specific covariates such as gender and race, a
2.5% increase was observed in asthma ED visits for each 10 ppb increase in the 1-hour maximum ozone
level on day 2 (odds ratio [OR] = 1.025, p <0.05). Particulate matter with an aerodynamic diameter
<2.5nm (PM2 5) had an effect both on the total population on day 1 after exposure (1.036, p <0.05), and
on African Americans for day-1 lag (OR =1.055; 95% CI, 1.001-1.112), day-2 lag (OR=1.067; 95% CI,
1.015-1.122), day-3 lag (OR=1.053; 95% CI, 1.002-1.106), and the 6-day average (OR =1.088; 95% CI,
1.001-1.184). PM2.5 had no significant effect on Caucasian Americans alone. The disparity in risk
estimates by race may reflect differences in residential characteristics, exposure to ambient air
pollution, or a differential effect of pollution by race.
Emergency Room Visits, Asthma (ICD-9 Code 493) - by Age and Racial Group
In a single pollutant model for patients of all ages and all races, the coefficient and standard error were
estimated from the odds ratio (1.04) and 95% confidence interval (0.984 - 1.10) for a 10 ng/m3 increase
in 24-hour mean PM25 concentration averaged over lags 0-6 days (Glad et al., 2012, Table 3).
In a single pollutant model for African American patients of all ages, the coefficient and standard error
were estimated from the odds ratio (1.088) and 95% confidence interval (1.001 - 1.184) for a 10 ng/m3
increase in 24-hour mean PM25 concentration averaged over lags 0-6 days (Glad et al., 2012, Table 3).
In a single pollutant model for Caucasian American patients of all ages, the coefficient and standard
error were estimated from the odds ratio (0.975) and 95% confidence interval (0.904 - 1.053) for a 10
Hg/m3 increase in 24-hour mean PM2 5 concentration averaged over lags 0-6 days (Glad et al., 2012,
Table 3).
In a single pollutant model for patients of ages 18-64 and all races, the coefficient and standard error
were estimated from the odds ratio (1.053) and 95% confidence interval (0.988- 1.122) for a 10 ng/m3
increase in 24-hour mean PM2 5 concentration averaged over lags 0-6 days (Glad et al., 2012, Table 4).
In a single pollutant model for African American patients of ages 18-64, the coefficient and standard
error were estimated from the odds ratio (1.095) and 95% confidence interval (0.995- 1.205) for a 10
Hg/m3 increase in 24-hour mean PM2 5 concentration averaged over lags 0-6 days (Glad et al., 2012,
Table 4).
In a single pollutant model for Caucasian American patients of ages 18-64, the coefficient and standard
error were estimated from the odds ratio (0.992) and 95% confidence interval (0.908- 1.084) for a 10
Hg/m3 increase in 24-hour mean PM2 5 concentration averaged over lags 0-6 days (Glad et al., 2012,
Table 4).
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E.4.5 Mathes et al. (2011)
Mathes et al. (2011) examined the association between particulate matter (PM2.5), hospitalization/
emergency department visits for cardiovascular disease in 11 New York City hospitals between the years
of 2004 and 2006. The study divided ED visits into two categories: Syndrome 1 (ICD-9 codes 410-429),
and Syndrome 2 (ICD-9 codes 405-441). The authors only included emergency department records for
patients over the age of 40, and excluded records which were missing a chief complaint description.
Three Poisson-generalized linear models were used to show temporal differences: a cold season model
(October - March), a warm season model (April-September), and an all-year model. Models were also
included to test for day-of -week and holiday patterns. All models included lag periods of 0, 1, 2, and 3
days. Results of the study showed the strongest associations between PM2 5and CVD health outcomes in
cold season models that used same-day PM2 5 concentrations.
Emergency Department Visits, Cardiovascular (ICD-9 Codes 405-441, 785-786)1 - by Season
In a single pollutant model for patients over the age of 40, the coefficient and standard error were
estimated from the percent excess risk (0.8%) and 95% confidence intervals (0.0%, 1.6%) for a 10 ng/m3
increase in same day 24-hour mean PM25 concentration all year (results obtained through
communication with the first author).
In a single pollutant model for patients over the age of 40, the coefficient and standard error were
estimated from the percent excess risk (2.1%) and 95% confidence intervals (0.9%, 3.3%) for a 10 ng/m
increase in same day 24-hour mean PM2 5 concentration in the cold season during October through
March (Mathes et al., 2011, Page 6).
In a single pollutant model for patients over the age of 40, the coefficient and standard error were
estimated from the percent excess risk (0.6%) and 95% confidence intervals (-0.5%, 1.6%) for a 10 ng/m3
increase in 24-hour mean PM2 5 concentration of lag 3-day in the warm season during April through
September (results obtained through communication with the first author).
E.4.6 Metzger et al. (2004)
Metzger et al. (2004) examined the relationship between emergency room visits for cardiovascular
conditions and ambient air pollution (N02, CO, organic carbon, elemental carbon, oxygenated
hydrocarbons, S02, 03, PMi0, and coarse PM) in Atlanta, Georgia from January 1, 1993 to August 31,
2000. Poisson generalized linear models controlling for long-term temporal trends and meteorological
conditions with cubic splines were used to evaluate the relative risk of all cardiovascular disease (ICD-9
codes 410-414, 427-428, 433-437, 440, 443-444, 451-453), dysrhythmia (ICD-9 code 427), congestive
heart failure (ICD-9 code 428), and peripheral and cerebrovascular disease (ICD-9 codes 433-437, 440,
443-444, and 451-453) emergency room visits associated with air pollution. Using a 3-day moving
average in single-pollutant models, they found that cardiovascular disease visits were associated with
daily 1-hour maximum N02 and CO and 24-hour average PM2 5, organic carbon, elemental carbon and
oxygenated hydrocarbons, with a secondary analysis indicating the strongest effect for same-day
pollution levels. S02 and 03 were not found to be associated with an increase in emergency room visits
for cardiovascular disease.
Emergency Room Visits, All Cardiovascular (ICD-9 codes 410-414, 427-428, 433-37, 440, 443-444, 451-
453)
1 This outcome is labeled as Syndrome 2 ED visits in the paper.
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In a single-pollutant model, the coefficient and standard error are estimated from the relative risk
(1.033) and 95% confidence interval (95% CI: 1.01-1.056) for a 10 ug/m3 increase in daily 24-hour mean
PM2.5 (Metzger et al., 2004, Table 4).
Emergency Room Visits, Congestive Heart Failure (ICD-9 code 428)
In a single-pollutant model, the coefficient and standard error are estimated from the relative risk
(1.055) and 95% confidence interval (95% CI: 1.006-1.105) for a 10 ug/m3 increase in same-day daily 24-
hour mean PM2 5 (Metzger et al., 2004, Table 4).
Emergency Room Visits, Dysrhythmia (ICD-9 codes 427)
In a single-pollutant model, the coefficient and standard error are estimated from the relative risk
(1.015) and 95% confidence interval (95% CI: 0.976-1.055) for a 10 ug/m3 increase in same-day daily 24-
hour mean PM2 5 (Metzger et al., 2004, Table 4).
Emergency Room Visits, Ischemic Heart Disease (ICD-9 codes 410-414)
In a single-pollutant model, the coefficient and standard error are estimated from the relative risk
(1.023) and 95% confidence interval (95% CI: 0.983-1.064) for a 10 ug/m3 increase in same-day daily 24-
hour mean PM25 (Metzger et al., 2004, Table 4).
Emergency Room Visits, Peripheral Vascular and Cerebrovascular Disease (ICD-9 codes 433-437, 440,
443-444, 451-453)
In a single-pollutant model, the coefficient and standard error are estimated from the relative risk (1.05)
and 95% confidence interval (95% CI: 1.008-1.093) for a 10 ug/m3 increase in same-day daily 24-hour
mean PM2 5 (Metzger et al., 2004, Table 4).
E.4.7 Tolbert et al. (2007)
Tolbert et al. (2007) examined the relationship between emergency room visits for respiratory (ICD-9
codes 493, 786.07, 786.09, 491, 492, 496, 460-465, 460.0, 477, 480-486, 466.1, 466.11, 466.19) and
cardiovascular (ICD-9 codes 410-414, 427, 428, 433-437, 440, 443-445, 451-453) conditions and ambient
air pollution (PMi0, 03, N02, S02, CO, PM2 5) in metropolitan Atlanta, Georgia from 1993-2004. Poisson
generalized linear models were used to examine outcome counts in relation to 3-day moving average
concentrations of the pollutants. For cardiovascular visits, associations were observed with CO, N02,
and PM2.5 elemental carbon and organic carbon. In multi-pollutant models, CO was the strongest
predictor. For respiratory visits, associations were observed with ozone, PM10, CO, and N02 in single-
pollutant models. In multi-pollutant models, PM10 and ozone persisted as predictors, with ozone the
stronger predictor. Caveats and considerations in interpreting the multi-pollutant model results were
discussed.
Emergency Room Visits, Cardiovascular (ICD-9 codes 410-414, 427, 428, 433-437, 440, 443-445, 451-
453)
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In a single-pollutant model, the coefficient and standard error are estimated from the risk ratio (1.005)
and 95% confidence interval (95% CI: 0.993-1.017) for a 10.96 ug/m3 increase in daily 24-hour mean
PM2 5 across a 3-day moving average (Tolbert et al., 2007, Table 4).
Emergency Room Visits, All Respiratory (ICD-9 codes 460-465, 466.1, 466.11, 466.19, 477, 491, 492,
493, 496, 786.07, 786.09)
In a single-pollutant model, the coefficient and standard error are estimated from the risk ratio (1.005)
and 95% confidence interval (95% CI: 0.995-1.015) for a 10.96 ug/m3 increase in daily 24-hour mean
PM2 5 across a 3-day moving average (Tolbert et al., 2007, Table 4).
References:
Agency for Healthcare Research and Quality (AHRQ). 2009. HCUPnet, Healthcare Cost and Utilization
Project. Rockville, MD. Available on the Internet at http://hcupnet.ahrq.gov
Glad, J.A., L.L. Brink, E.O. Talbott, P.C. Lee, X. Xu, M. Saul, and J. Rager. 2012. The Relationship of
Ambient Ozone and PM2.5 Levels and Asthma Emergency Department Visits: Possible Influence of
Gender and Ethnicity. Archives of Environmental & Occupational Health. Vol 62 (2): 103-108.
Kloog, I., B.A. Coull, A. Zanobetti, P. Koutrakis, J.D. Schwartz. 2012. Acute and Chronic Effects of Particles
on Hospital Admissions in New-England. PLoS ONE. Vol 7 (4): 1-8.
Mathes, R.W., K. Ito, and T. Matte. 2011. Assessing Syndromic Surveillance of Cardiovascular Outcomes
from Emergency Department Chief Complaint Data in New York City. PloS ONE. Vol 6(2): 1-10.
Metzger, K. B., P. E. Tolbert, et al. 2004. "Ambient air pollution and cardiovascular emergency
department visits." Epidemiology 15(1): 46-56.
Miller, Kristin A., David S. Siscovick, Lianne Sheppard, Kristen Shepherd, Jeffrey H. Sullivan, Garnet L.
Anderson, and Joel D. Kaufman. 2007. "Long-Term Exposure to Air Pollution and Incidence of
Cardiovascular Events in Women." New England Journal of Medicine. 356 (5) : 447-458.
Rosamond, W., G. Broda, E. Kawalec, S. Rywik, A. Pajak, L. Cooper, and L. Chambless. 1999. "Comparison
of Medical Care and Survival of Hospitalized Patients with Acute Myocardial Infarction in Poland and the
United States." American Journal of Cardiology 83:1180-1185.
Tolbert, P. E., M. Klein, et al. 2007. "Multipollutant modeling issues in a study of ambient air quality and
emergency department visits in Atlanta." J Expo Sci Environ Epidemiol 17 Suppl 2: S29-35.
U.S. Environmental Protection Agency (U.S. EPA). 2012. Regulatory Impact Analysis for the Final
Revisions to the National Ambient Air Quality Standards for Particulate Matter. EPA-452/R-12-003.
Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. December.
Available at http://www.epa.gov/pm/2012/finalria.pdf.
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