The 2019 PM ISA determined that a "likely to be causal" relationship exists between long-term PM2.5 exposure and cancer (U.S. EPA, 2019b ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote>), a change in the causality determination from the 2009 ISA (U.S. EPA, 2009 ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2009</Year><RecNum>6</RecNum><DisplayText>U.S. EPA, 2009</DisplayText><record><rec-number>6</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="0">6</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Particulate Matter (Final Report).</title></titles><edition>December 2009</edition><keywords><keyword>ISA</keyword></keywords><dates><year>2009</year></dates><pub-location>Research Triangle Park, NC</pub-location><publisher>Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA-600/R-08-139F</isbn><urls><related-urls><url>Available at: https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=216546</url></related-urls></urls></record></EndNote>). Specifically, the ISA found evidence of generally consistent positive associations between long-term PM2.5 exposure and lung cancer incidence. Additional details regarding potential pathways of disease development are summarized in the biological plausibility diagram provided by the ISA (section <IP_ADDRESS>.1.3).
For an outcome such as lung cancer, there is an expected time lag between changes in pollutant exposure in a given year and the reduction in lung cancer incidence, known as the latency period. The time between exposure and diagnosis can be quite long, on the order of years to decades. We discuss methods used to account for the latency period and other economic considerations relevant to this health endpoint in section 5.3.6. Importantly, we include this health endpoint to assess impacts of living with a lung cancer diagnosis, prior to disease resolution or death.
Available Epidemiologic Literature
We limited our pool of available studies to those of lung cancer incidence, excluding those assessing lung cancer mortality as that endpoint is included in the long-term exposure-attributable all-cause mortality endpoint (section <IP_ADDRESS>.3.1). This resulted in four study options.
Identifying Suitable Studies for Use in Benefits Assessments
The four available studies varied in terms of population demographics included and country. Two of the four studies took place entirely in Canada. Of the two U.S.-based studies, one included all ages, sexes, and demographics and was restricted to non- and never-smokers, although it included some participants living in Canada. The identified study was most suitable as it took place in the U.S., included both males and females, and was restricted to non- and never-smokers (Gharibvand et al., 2017 ADDIN EN.CITE <EndNote><Author>Gharibvand</Author><Year>2017</Year><RecNum>1198</RecNum><DisplayText>Gharibvand et al., 2017</DisplayText><record><rec-number>1198</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1604071026">1198</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gharibvand, L.</author><author>Shavlik, D.</author><author>Ghamsary, M.</author><author>Beeson, W. L.</author><author>Soret, S.</author><author>Knutsen, R.</author><author>Knutsen, S. F.</author></authors></contributors><auth-address>Adventist Health Study-2, School of Public Health, Loma Linda University, Loma Linda, California, USA.</auth-address><titles><title>The Association between Ambient Fine Particulate Air Pollution and Lung Cancer Incidence: Results from the AHSMOG-2 Study</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>378-384</pages><volume>125</volume><number>3</number><edition>2016/08/16</edition><keywords><keyword>Air Pollutants/*analysis</keyword><keyword>Air Pollution/*statistics & numerical data</keyword><keyword>Environmental Exposure/*statistics & numerical data</keyword><keyword>Humans</keyword><keyword>Incidence</keyword><keyword>Lung Neoplasms/*epidemiology</keyword><keyword>Particulate Matter/*analysis</keyword></keywords><dates><year>2017</year><pub-dates><date>Mar</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>27519054</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/27519054</url></related-urls></urls><custom2>PMC5332173</custom2><electronic-resource-num>10.1289/EHP124</electronic-resource-num></record></EndNote>).
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Gharibvand et al., 2017 ADDIN EN.CITE <EndNote><Author>Gharibvand</Author><Year>2017</Year><RecNum>1198</RecNum><DisplayText>Gharibvand et al., 2017</DisplayText><record><rec-number>1198</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1604071026">1198</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gharibvand, L.</author><author>Shavlik, D.</author><author>Ghamsary, M.</author><author>Beeson, W. L.</author><author>Soret, S.</author><author>Knutsen, R.</author><author>Knutsen, S. F.</author></authors></contributors><auth-address>Adventist Health Study-2, School of Public Health, Loma Linda University, Loma Linda, California, USA.</auth-address><titles><title>The Association between Ambient Fine Particulate Air Pollution and Lung Cancer Incidence: Results from the AHSMOG-2 Study</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>378-384</pages><volume>125</volume><number>3</number><edition>2016/08/16</edition><keywords><keyword>Air Pollutants/*analysis</keyword><keyword>Air Pollution/*statistics & numerical data</keyword><keyword>Environmental Exposure/*statistics & numerical data</keyword><keyword>Humans</keyword><keyword>Incidence</keyword><keyword>Lung Neoplasms/*epidemiology</keyword><keyword>Particulate Matter/*analysis</keyword></keywords><dates><year>2017</year><pub-dates><date>Mar</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>27519054</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/27519054</url></related-urls></urls><custom2>PMC5332173</custom2><electronic-resource-num>10.1289/EHP124</electronic-resource-num></record></EndNote> evaluated whether positive associations exist between PM2.5 exposure and incidence of lung cancer in non-smokers among the Adventist Health and Smog Study-2 (AHSMOG-2), a group of health-conscious individuals of which 81% are never smokers. Authors collected ambient air pollution data (PM2.5 and O3) from the US EPA Air Quality system over two years (January 2000-December 2001). Three a priori factors were added to the models as covariates: time spent outdoors, residence length, and moving distance during follow-up. Authors modeled the association between PM2.5 exposure and incidence of lung cancer using a Cox proportional hazards regression, with attained age as the time variable. The authors conducted both a single and a two-pollutant (PM2.5 and O3) analyses. The study concluded that each 10 ug/m[3] increase in ambient PM2.5 concentrations was positively associated with increased lung cancer risks within the single-pollutant and two-pollutant multivariable models with O3. The identified hazard ratio of 1.46 (95% CI: 1.13-1.89) for each 10 ug/m[3] increase in mean monthly ambient PM2.5 concentrations came from a two-pollutant multivariable model with O3 (including a priori covariates).
Alzheimer's Disease
Evidence connecting long-term PM2.5 exposure to nervous system effects led to the 2019 PM ISA concluding a "likely to be causal" relationship exists (U.S. EPA, 2019b ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote>) and various clinically relevant nervous system endpoints were called out in the biological plausibility section, including Alzheimer's disease, Parkinson's disease, autism spectrum disorder, cognitive decline, and dementia (section <IP_ADDRESS>.1.3). Regarding biological plausibility, the ISA stated that "neuroinflammation and neurodegeneration provide biological plausibility for epidemiologic results of increased hospital admissions or emergency department visits for Alzheimer's and Parkinson's disease."
There were over a dozen epidemiologic studies in the 2019 PM ISA evaluating cognitive-related outcomes (U.S. EPA, 2019b, sections 8.2.5-8.2.7). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote> However, due to the nature of the endpoint, many of the outcomes were defined using scales and scores from cognitive tests. As we are currently unable to transfer that type of result into a clinically relevant population level outcome, we focused on the more clearly defined outcomes of Alzheimer's disease and Parkinson's Disease. These endpoints were also specifically called out in the ISA, as "epidemiologic studies also provide evidence of cognitive impairment and Alzheimer's and Parkinson's disease in association with exposure to PM2.5" (U.S. EPA, 2019b ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote>, section 8.2.6).
Available Epidemiologic Literature
One epidemiologic study of Alzheimer's disease met our minimum required identification criteria (section 2.1.1).
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Kioumourtzoglou et al., 2016 ADDIN EN.CITE <EndNote><Author>Kioumourtzoglou</Author><Year>2016</Year><RecNum>1104</RecNum><DisplayText>Kioumourtzoglou et al., 2016</DisplayText><record><rec-number>1104</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732551">1104</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kioumourtzoglou, M. A.</author><author>Schwartz, J.</author><author>James, P.</author><author>Dominici, F.</author><author>Zanobetti, A.</author></authors></contributors><titles><title></title><secondary-title>Epidemiology</secondary-title><alt-title>Epidemiology</alt-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><alt-periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</alt-periodical><pages>221-227</pages><volume>27</volume><number>2</number><dates><year>2016</year></dates><isbn>ISSN 1044-3983
EISSN 1531-5487</isbn><accession-num>26600257</accession-num>3079253<urls><related-urls><url>http://dx.doi.org/10.1097/EDE.0000000000000422</url></related-urls></urls><electronic-resource-num>10.1097/EDE.0000000000000422</electronic-resource-num><language>English</language></record></EndNote> evaluated the potential impact of long-term PM2.5 exposure on first hospital admission for dementia, Alzheimer's, or Parkinson's diseases among Medicare beneficiaries (>= 65 years old) in 50 cities in the northeastern U.S. (Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Washington, D.C.). Authors retrieved medical data from the Center for Medicaid and Medicare from the years 1999-2010. The study followed enrollees as a cohort, which included annual follow-up records identifying the first hospital admissions for dementia (ICD-9 290), Alzheimer's (ICD-9 331.0), Parkinson's (ICD-9 332), and other cardiovascular comorbidities. With respect to Alzheimer's disease, the study evaluated 9,817,806 Medicare enrollees and included 266,725 cause-specific hospital admissions indicating disease onset. Annual average PM2.5 concentrations were estimated for each city using data from the U.S. EPA Air Quality System database. Kioumourtzoglou et al., 2016 ADDIN EN.CITE <EndNote><Author>Kioumourtzoglou</Author><Year>2016</Year><RecNum>1104</RecNum><DisplayText>Kioumourtzoglou et al., 2016</DisplayText><record><rec-number>1104</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732551">1104</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kioumourtzoglou, M. A.</author><author>Schwartz, J.</author><author>James, P.</author><author>Dominici, F.</author><author>Zanobetti, A.</author></authors></contributors><titles><title></title><secondary-title>Epidemiology</secondary-title><alt-title>Epidemiology</alt-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><alt-periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</alt-periodical><pages>221-227</pages><volume>27</volume><number>2</number><dates><year>2016</year></dates><isbn>ISSN 1044-3983
EISSN 1531-5487</isbn><accession-num>26600257</accession-num>3079253<urls><related-urls><url>http://dx.doi.org/10.1097/EDE.0000000000000422</url></related-urls></urls><electronic-resource-num>10.1097/EDE.0000000000000422</electronic-resource-num><language>English</language></record></EndNote> fit a time-varying Cox proportional hazards model for each city, using the city-wide annual PM2.5 concentrations as the time-varying exposure of interest and a linear term for the calendar year. This eliminated the impact of PM2.5 variation by city and any PM2.5 trends within cities. The model adjusted for cardiovascular comorbidities, and incorporated a counting process extension which created an observation for each year of follow-up per person. The results were then pooled across individuals and cities. A single-pollutant model was used to develop the identified hazard ratio of 1.15 (95% CI: 1.11-1.19) for a 1 ug/m[3] increase in the average annual PM2.5 concentrations.
Parkinson's Disease
Evidence connecting long-term PM2.5 exposure to nervous system effects led to the 2019 ISA concluding a "likely to be causal" relation exists (U.S. EPA, 2019b ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote>) and various clinically relevant nervous system endpoints were called out in the biological plausibility section, including Alzheimer's disease, Parkinson's disease, autism spectral disorder, cognitive decline, and dementia (section <IP_ADDRESS>.1.3). Regarding biological plausibility, the ISA stated that "neuroinflammation and neurodegeneration provide biological plausibility for epidemiologic results of increased hospital admissions or emergency department visits for Alzheimer's and Parkinson's disease."
There were over a dozen epidemiologic studies in the 2019 PM ISA evaluating cognitive-related outcomes (U.S. EPA, 2019b, sections 8.2.5-8.2.7). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote> However, due to the nature of the endpoint, many of the outcomes were defined using scales and scores from cognitive tests. As we are currently unable to transfer that type of result into a clinically relevant disease incidence, we focused on the more clearly defined outcomes of Alzheimer's disease and Parkinson's Disease. These endpoints were also specifically called out in the ISA, as "epidemiologic studies also provide evidence of cognitive impairment and Alzheimer's and Parkinson's disease in association with exposure to PM2.5" (U.S. EPA, 2019b ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2019</Year><RecNum>320</RecNum><DisplayText>U.S. EPA, 2019c</DisplayText><record><rec-number>320</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1573071075">320</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>U.S. EPA </author></secondary-authors></contributors><titles><title>Integrated Science Assessment (ISA) for Particulate Matter (Final Report)</title></titles><edition>December 2019</edition><dates><year>2019</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment</publisher><isbn>EPA/600/R-19/188</isbn><urls><related-urls><url>Available at: https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review</url></related-urls></urls></record></EndNote>, section 8.2.6).
Available Epidemiologic Literature
Three epidemiologic studies of Parkinson's disease were identified in the 2019 PM ISA. All evaluated relatively low PM2.5 concentrations and included participants from multiple states, however there were differences with respect to the ages and sexes evaluated, number of overall participants, and exposure estimation technique.
Identifying Suitable Studies for Use in Benefits Assessments
The prospective study with the lowest mean PM2.5 concentrations and most recent timespan included over 14 times the number of participants as the other two studies combined. It was also the only study to include participants over the age of 71, which is relevant as Parkinson's disease prevalence rises with age (Pringsheim et al., 2014 ADDIN EN.CITE <EndNote><Author>Pringsheim</Author><Year>2014</Year><RecNum>1211</RecNum><DisplayText>Pringsheim et al., 2014</DisplayText><record><rec-number>1211</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1604508927">1211</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Pringsheim, T.</author><author>Jette, N.</author><author>Frolkis, A.</author><author>Steeves, T. D.</author></authors></contributors><auth-address>Department of Clinical Neurosciences, University of Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Alberta, Canada; Department of Community Health Sciences, University of Calgary, Alberta, Canada.</auth-address><titles><title>The prevalence of Parkinson's disease: a systematic review and meta-analysis</title><secondary-title>Mov Disord</secondary-title></titles><periodical><full-title>Mov Disord</full-title></periodical><pages>1583-90</pages><volume>29</volume><number>13</number><edition>2014/07/01</edition><keywords><keyword>Humans</keyword><keyword>Parkinson Disease/*epidemiology</keyword><keyword>Parkinson's disease/Parkinsonism</keyword><keyword>prevalence studies</keyword><keyword>risk factors in epidemiology</keyword></keywords><dates><year>2014</year><pub-dates><date>Nov</date></pub-dates></dates><isbn>1531-8257 (Electronic)
0885-3185 (Linking)</isbn><accession-num>24976103</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/24976103</url></related-urls></urls><electronic-resource-num>10.1002/mds.25945</electronic-resource-num></record></EndNote>).
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Kioumourtzoglou et al., 2016 ADDIN EN.CITE <EndNote><Author>Kioumourtzoglou</Author><Year>2016</Year><RecNum>1104</RecNum><DisplayText>Kioumourtzoglou et al., 2016</DisplayText><record><rec-number>1104</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732551">1104</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kioumourtzoglou, M. A.</author><author>Schwartz, J.</author><author>James, P.</author><author>Dominici, F.</author><author>Zanobetti, A.</author></authors></contributors><titles><title></title><secondary-title>Epidemiology</secondary-title><alt-title>Epidemiology</alt-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><alt-periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</alt-periodical><pages>221-227</pages><volume>27</volume><number>2</number><dates><year>2016</year></dates><isbn>ISSN 1044-3983
EISSN 1531-5487</isbn><accession-num>26600257</accession-num>3079253<urls><related-urls><url>http://dx.doi.org/10.1097/EDE.0000000000000422</url></related-urls></urls><electronic-resource-num>10.1097/EDE.0000000000000422</electronic-resource-num><language>English</language></record></EndNote> evaluated the potential impact of long-term PM2.5 exposure on first hospital admission for dementia, Alzheimer's, or Parkinson's diseases among Medicare beneficiaries (>= 65 years old) in 50 cities in the northeastern U.S. (Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Washington, D.C.). Authors retrieved medical data from the Center for Medicaid and Medicare from the years 1999-2010. The study followed enrollees as a cohort, which included annual follow-up records identifying the first hospital admissions for dementia (ICD-9 290), Alzheimer's (ICD-9 331.0), Parkinson's (ICD-9 332), and other cardiovascular comorbidities. With respect to Parkinson's disease, the study evaluated 9,817,806 Medicare enrollees and included 119,425 cause-specific hospital admissions indicating disease onset. Annual average PM2.5 concentrations were estimated for each city using data from the US EPA Air Quality System database. Kioumourtzoglou et al., 2016 ADDIN EN.CITE <EndNote><Author>Kioumourtzoglou</Author><Year>2016</Year><RecNum>1104</RecNum><DisplayText>Kioumourtzoglou et al., 2016</DisplayText><record><rec-number>1104</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732551">1104</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kioumourtzoglou, M. A.</author><author>Schwartz, J.</author><author>James, P.</author><author>Dominici, F.</author><author>Zanobetti, A.</author></authors></contributors><titles><title></title><secondary-title>Epidemiology</secondary-title><alt-title>Epidemiology</alt-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><alt-periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</alt-periodical><pages>221-227</pages><volume>27</volume><number>2</number><dates><year>2016</year></dates><isbn>ISSN 1044-3983
EISSN 1531-5487</isbn><accession-num>26600257</accession-num>3079253<urls><related-urls><url>http://dx.doi.org/10.1097/EDE.0000000000000422</url></related-urls></urls><electronic-resource-num>10.1097/EDE.0000000000000422</electronic-resource-num><language>English</language></record></EndNote> fit a time-varying Cox proportional hazards model for each city, using the city-wide annual PM2.5 concentrations as the time-varying exposure of interest and a linear term for the calendar year. This eliminated the impact of PM2.5 variation by city and any PM2.5 trends within cities. The model adjusted for cardiovascular comorbidities, and incorporated a counting process extension which created an observation for each year of follow-up per person. The results were then pooled across individuals and cities. A single-pollutant model was used to develop the identified hazard ratio of 1.08 (1.04  -  1.12) for a 1 ug/m[3] increase in the average annual PM2.5 concentrations.
O3
The following sections of the 2020 O3 ISA correspond to health endpoints judged as having a "causal" or "likely causal" relationship with O3 exposure:
 Appendix 3: Health Effects  -  Respiratory, 3.1 Short-Term Ozone Exposure;
 Appendix 3: Health Effects  -  Respiratory, 3.2 Long-Term Ozone Exposure;
 Appendix 5: Health Effects  -  Metabolic Effects, 5.1 Short-Term Ozone Exposure;
 Appendix 6: Health Effects  -  Mortality, 6.1 Short-Term Ozone Exposure and Mortality; and
 Appendix 6: Health Effects  -  Mortality, 6.2 Long-Term Ozone Exposure and Mortality.
Following the approach to identifying available epidemiologic literature (section 2.2), we began with the 1,678 studies cited by the 2020 O3 ISA (U.S. EPA, 2020b). Of these, 130 morbidity studies evaluate health endpoints the 2020 O3 ISA determined as having a "causal" or "likely causal" relationship with O3 exposure (sections 2.2.1 and 2.2.2). 77 studies remained after the required minimum criteria were applied, and that number decreased to 27 when broad hospital admissions and emergency department endpoints were identified. No studies of short-term O3 exposure metabolic effects meeting the minimum required criteria (section 2.1.1) were identified in the ISA.
Table 7. O3 Study and Risk Estimate Identification Diagram
                       O3 Endpoint and Exposure Duration
                               Studies Available
                               Studies Included
                                     Ages
                           Risk Estimates Available
                            Risk Estimates Included
Respiratory Mortality (LT)
                                       4
                                       1
                            Adults and older adults
                                       2
                                       1
Respiratory Mortality (ST)
                                       6
                                       2
                      Children, adults, and older adults
                                      16
                                       1

                                      120
                                       1
Respiratory Hospital Admissions (ST)
                                       3
                                       1
                                 Older adults
                                       7
                                       1
Respiratory Emergency Department Visits (ST)
                                       7
                                       1
                      Children, adults, and older adults
                                      45
                                       5
Asthma Onset (LT)
                                       4
                                       1
                                   Children
                                       8
                                       1
Asthma Symptoms (ST)
                                       4
                                       1
                                   Children
                                      160
                                       1
Minor Restricted Activity Days
                                      NA
                                       1
                                    Adults
                                      NA
                                       1
Allergic Rhinitis
                                       1
                                       1
                                   Children
                                       5
                                       1
School Loss Days
                                      NA
                                       2
                                   Children
                                      NA
                                       1

                                      NA
                                       1
NA- not applicable due to the absence of additional ISA evidence. Risk estimates identified in the 2015 Ozone NAAQS RIA will continue to be utilized.
Respiratory Mortality
We separate respiratory mortality impacts resulting from short- and long-term exposures for several reasons. Firstly, the biological pathways of short- and long-term O3-attributable health effects may differ in ways that affect the manner in which this endpoint is quantified (section <IP_ADDRESS>.2.1). For example, some impacts of long-term exposure to O3 may be incremental to impacts attributable to short-term exposure. Conversely, some impacts associated with long-term exposure to O3 may include impacts attributable to short-term exposure. However, we lack the evidence to determine the extent to which these risks are mutually exclusive or overlapping. Secondly, the level of support for respiratory mortality effects of short- and long-term O3 exposures may differ. Therefore, we continue to include risk estimates of respiratory mortality from both short- and long-term exposures to present a range of health impact estimates.
Respiratory Mortality Attributable to Short-Term Exposures
The 2020 O3 ISA determined that there exists a "causal" relationship between short-term O3 exposure and respiratory outcomes (U.S. EPA, 2020b). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote> The short-term exposure causality determination "was made on the basis of a strong body of evidence integrated across controlled human exposure, animal toxicological, and epidemiologic studies, in addition to established findings from previous [Air Quality Criteria Documents], demonstrating respiratory effects due to short-term exposure to ozone." While the ISA found that "recent epidemiological evidence for respiratory mortality is limited, but there remains evidence of consistent, positive associations, specifically in the summer months" and "when recent evidence is considered in the context of the larger number of studies evaluated in the 2013 Ozone ISA, there remains consistent evidence of an association between short-term ozone exposure and respiratory mortality." Due to the strength of the ISA evidence relating short-term exposures to respiratory mortality, estimates of respiratory mortality impacts are included in the main benefits assessment of O3-attributable health impacts.
Separately, 2020 ISA determined that the relationship between short-term O3 exposure and total mortality is "suggestive of, but not sufficient to infer, a causal relationship" (U.S. EPA, 2020b). By comparison, the 2013 ISA identified this endpoint as "likely to be causal" (U.S. EPA, 2013). Evidence supporting a relationship between short-term O3 exposure and total mortality included consistent epidemiologic evidence from multiple high-quality studies at relevant ozone concentrations, some support for an independent O3 association, and biological plausibility from studies of respiratory morbidity. In contrast, uncertainties remain regarding geographic heterogeneity in O3 mortality associations and there is limited biological plausibility from studies of cardiovascular morbidity. Regarding the biological plausibility of cardiovascular effects, while animal toxicological studies provide evidence of cardiovascular effects, recent controlled human exposure studies do not provide evidence to support potential biological pathways. Additionally, there is a lack of coherence with epidemiologic studies of cardiovascular morbidity, specifically, cardiovascular-related emergency department visits and hospital admissions, to support cardiovascular mortality. Due to limitations in ISA evidence relating short-term exposures to total mortality, estimates of all-cause mortality impacts will not be calculated when estimating benefits attributable to changes in O3 exposure.
Available Epidemiologic Literature
There were six North American studies of short-term O3-attributable respiratory mortality identified in the 2020 O3 ISA, one of which was new to this review but took place entirely in (U.S. EPA, 2020b). Of the U.S.-based studies, two were single-city. The other three studies were fairly equally geographically and demographically representative, although one was a meta-analysis.
Identifying Suitable Studies for Use in Benefits Assessments
Of the six studies of short-term O3-attributable respiratory mortality, all but one study period ended during or before the year 2000 and the individual study that extended into the 2000s was geographically limited to a single city. This list also included a meta-analysis and a study that took place entirely in Canada. Two U.S.-based, nationally representative studies were identified as best characterizing risk across the U.S. for this endpoint.
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
As Zanobetti and Schwartz, 2008 ADDIN EN.CITE <EndNote><Author>Zanobetti</Author><Year>2008</Year><RecNum>1184</RecNum><DisplayText>Zanobetti and Schwartz, 2008</DisplayText><record><rec-number>1184</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603988156">1184</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Zanobetti, A.</author><author>Schwartz, J.</author></authors></contributors><auth-address>Department of Environmental Health, Exposure Epidemiology and Risk Program, Harvard School of Public Health, 401 Park Drive, Landmark Center, Suite 415, P.O. Box 15698, Boston, MA 02215, USA<EMAIL_ADDRESS>displacement in the association of ozone with mortality: an analysis of 48 cities in the United States</title><secondary-title>Am J Respir Crit Care Med</secondary-title></titles><periodical><full-title>American Journal of Respiratory and Critical Care Medicine</full-title>Am. J. Respir. Crit. Care Med.Am J Respir Crit Care Med</periodical><pages>184-9</pages><volume>177</volume><number>2</number><edition>2007/10/13</edition><keywords><keyword>Cause of Death</keyword><keyword>Cities</keyword><keyword>Confidence Intervals</keyword><keyword>Environmental Exposure/*adverse effects</keyword><keyword>Humans</keyword><keyword>*Mortality</keyword><keyword>Oxidants, Photochemical/*adverse effects</keyword><keyword>Ozone/*adverse effects</keyword><keyword>Seasons</keyword><keyword>United States/epidemiology</keyword></keywords><dates><year>2008</year><pub-dates><date>Jan 15</date></pub-dates></dates><isbn>1535-4970 (Electronic)
1073-449X (Linking)</isbn><accession-num>17932375</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/17932375</url></related-urls></urls><electronic-resource-num>10.1164/rccm.200706-823OC</electronic-resource-num></record></EndNote> investigated the effects of short-term O3 exposure on mortality (all-cause, cardiovascular, stroke, and respiratory) in an unrestricted population of children, adults, and older adults (aged 0-99 years), it remained a superior analysis of short-term O3-attributable respiratory mortality. Between 1998 and 2000, the authors collected mortality data from the National Center for Health Statistic in 48 cities across the United States. Along with eight-hour ozone concentrations and meteorological data obtained from US EPA's Air Quality System Technology Transfer Network, the authors utilized a generalized linear model with quasi-Poisson link functions to estimate the effects of short-term ozone on respiratory mortality. The model adjusted for season, day of the week, and temperature. Since ozone concentrations vary between seasons, the authors decided to restrict their analysis to ozone warm season (June - August). The identified single-pollutant, warm season excess risk estimate of 0.83% (95% CI: 0.38-1.28%) for an increase of 10 ppb in DA8 O3 concentrations over a summed lag structure of zero to three days.
Katsouyanni et al., 2009 also used time series methods to examine the relationship between short-term O3 exposures and mortality across the U.S for all ages. The study utilized mortality data from the National Center for Health Statistics (www.cdc.gov/nchs) for years 1987 through 1996, excluding accidental deaths (i.e., International Classification of Diseases (ICD]-9 800). 90 U.S. cities with population sizes varying from about 250,000 to above 9 million with the largest populations were included. Daily number of deaths ranged from 5 to 198. All 90 cities had daily summer O3 measurements. Investigators conducted extensive simulation studies to test 1) the choice of the smoothing method and basic functions used to estimate the smooth function of time in the city-specific models, and 2) the number of degrees of freedom to be used in the smooth function of time. The investigators also evaluated whether each city should be assigned the same model specification or whether each city-specific model should depend on city-specific characteristics. For the former, the same degrees of freedom (ranging from 1 to 20 df/year of data) were assigned to the smooth function of time for every city. The range was determined by choosing the minimum possible degrees of freedom per year up to a maximum degrees of freedom per year that essentially removed all variation in the data beyond time scales of one week. Also, the collective experience of the investigators indicated that using more than 20 df/year does not substantially affect the risk estimates. For the latter approach, the degrees of freedom for the smooth function of time were chosen separately for each city using a fit criterion, such as the Akaike Information Criterion (AIC), or by minimizing the partial autocorrelation function (PACF) of the residuals. Nonparametric methods underestimated the standard error of the air pollution regression coefficient, penalized splines gave relatively small bias, and PACF in combination with penalized splines performed relatively well in terms of bias. Therefore, the identified risk estimate was a summer-only penalized spline estimate of respiratory mortality of 0.73 (-0.39, 1.85) per 10 ug/m[3] increase in O3 from distributed lag days was identified.
The two risk estimates identified are not directly comparable to previous estimates of short-term exposure-related mortality as previous estimates were of nonaccidental mortality and current estimates are of respiratory mortality.
Respiratory Mortality Attributable to Long-Term Exposures
The 2020 O3 ISA determined that there exists a "likely to be causal" relationship between long-term O3 exposure and respiratory outcomes (U.S. EPA, 2020b). The overall "likely to be causal" determination for long-term exposures "was based on epidemiologic evidence of associations between long-term ozone exposure and asthma development, respiratory symptoms in children with asthma, and respiratory mortality." More specifically, the ISA found that "there is strong coherence between animal toxicological studies of changes in lung morphology and epidemiologic studies reporting positive associations between long-term ozone exposure and new onset asthma, respiratory symptoms in children with asthma, and respiratory mortality" and the "several multicity studies and a multi-continent study reported associations between short-term increases in ozone concentrations and increases in respiratory mortality." Overall, the 2020 O3 ISA concluded there was "some evidence that long-term ozone exposure is associated with respiratory mortality, but the evidence is not consistent across studies." Due to the strength of the ISA evidence relating long-term exposures to respiratory mortality, estimates of respiratory mortality impacts are included when estimating benefits attributable to changes in O3 exposure.
Available Epidemiologic Literature
There were four North American studies of long-term O3-attributable respiratory mortality identified in the 2020 O3 ISA, three of which were new to this review (U.S. EPA, 2020b). All four studies evaluated either the ACS CSP-II or the Canadian Census Health and Environment Cohort (CanCHEC) prospective cohorts, differing in study size, timespan, exposure estimation technique, and specific risk models analyzed.
Identifying Suitable Studies for Use in Benefits Assessments
Three of the four studies evaluating long-term O3-attributable respiratory mortality assessed the ACS CSP-II prospective cohort and the fourth evaluated the Canadian Census Health and Environment Cohort (CanCHEC) prospective cohort. Two of the three ACS CSP-II analyses were nationwide, with the third focusing on California. One of the two nationwide ACS CSP-II analyses included a longer and more recent study period, utilized hybrid exposure estimates, and included a larger number of participants.
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Turner et al., 2016 examined the relationship between long-term O3 exposure (1982-2004) and mortality (all-cause, cause-specific) in American Cancer Society Cancer Prevention Study-II participants (aged 30-99 years). A hierarchal Bayesian space-time model based on National Air Monitoring Stations, State and Local Air Monitoring Stations, and Community Multi-Scale Air Quality model data estimated daily eight-hour maximum ozone concentrations at the participant's address. The models considered meteorological data and levels of other ambient pollutants (PM2.5, both regional and near-source, and NO2). Turner et al., 2016 ADDIN EN.CITE <EndNote><Author>Turner</Author><Year>2016</Year><RecNum>544</RecNum><DisplayText>Turner et al., 2016</DisplayText><record><rec-number>544</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732084">544</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Turner, M. C.</author><author>Jerrett, M.</author><author>Pope, A., III</author><author>Krewski, D.</author><author>Gapstur, S. M.</author><author>Diver, W. R.</author><author>Beckerman, B. S.</author><author>Marshall, J. D.</author><author>Su, J.</author><author>Crouse, D. L.</author><author>Burnett, R. T.</author></authors></contributors><titles><title>Long-term ozone exposure and mortality in a large prospective study</title><secondary-title>American Journal of Respiratory and Critical Care Medicine</secondary-title><alt-title>Am J Respir Crit Care Med</alt-title></titles><periodical><full-title>American Journal of Respiratory and Critical Care Medicine</full-title>Am. J. Respir. Crit. Care Med.Am J Respir Crit Care Med</periodical><alt-periodical><full-title>American Journal of Respiratory and Critical Care Medicine</full-title>Am. J. Respir. Crit. Care Med.Am J Respir Crit Care Med</alt-periodical><pages>1134-1142</pages><volume>193</volume><number>10</number><dates><year>2016</year></dates><isbn>ISSN 1073-449X
EISSN 1535-4970</isbn><accession-num>26680605</accession-num>3060878<urls><related-urls><url>http://dx.doi.org/10.1164/rccm.201508-1633OC</url></related-urls></urls><electronic-resource-num>10.1164/rccm.201508-1633OC</electronic-resource-num><language>English</language></record></EndNote> utilized Cox proportional hazard models adjusted a priori for individual, socio-demographic, and ecological variables. The hazard ratio of 1.12 (1.08  -  1.16) from a multi-pollutant, all-year model of respiratory mortality for a 10-ppb increase in the annual average of daily 8-hour maximum ozone concentrations was likely the most comprehensive risk estimate. This study also provided a warm-season specific hazard ratio of 1.08 (1.06-1.11) per 10 ppb increase in seasonal average of daily 8-hour maximum O3 concentrations, which will be used when air quality surfaces are only available for the summer season. Notably, the study compared annual mortality with warm-season O3 exposures, so full-year baseline incidence rates will be used with risk estimates from this study.
The identified risk estimate of long-term exposure associated mortality is larger than the risk estimate used in previous benefits assessments (Jerrett et al., 2009), but differs in many aspects including study size, included study locations, and exposure estimation technique.
Respiratory Hospital Admissions
After considering the relationships between specific and broad respiratory hospital admission endpoints, the 2020 O3 ISA stated that "studies conducted in diverse locations with a variety of exposure assignment techniques continue to provide evidence of an association between ozone and both hospital admissions and emergency department visits for combined respiratory diseases" (3432020a3430xd5s9009txfw1eafstv220i5ds2wvtpwf5d1581631219">343</U.S. EPA, 2020b, section 3.1.8).
Available Epidemiologic Literature
Three epidemiologic studies of respiratory hospital admission were identified in the 2020 O3 ISA, which varied considerably with respect to the timespans evaluated and study population locations (U.S. EPA, 2020b). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote>
Identifying Suitable Studies for Use in Benefits Assessments
The two older studies either included only Canadian participants or included U.S., Canadian, and some European participants. Therefore, we identified the most recent and only entirely U.S.-based study as best characterizing risk across the U.S.
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Katsouyanni et al., 2009 used time series methods to examine the relationship between daily O3 concentrations and hospital admissions in North America. For U.S. benefits estimation purposes, we focus on analyses performed using the U.S hospital admission datasets. These datasets included 14 cities with populations between 291,000 and 5,377,000 between 1987-1996 with city-wide MDA1 O3 concentrations ranging from ~34-60 ug/m[3]. The authors used a first stage analysis protocol that used generalized linear models with either penalized or natural splines to adjust for seasonality, with varying degrees of freedom. The number of degrees of freedom were also chosen by minimizing the partial autocorrelation function of the model's residuals. Model specification approach accounted for seasonal patterns, weekend and vacation effects, and epistemics of respiratory disease. Data were also analyzed to detect potential thresholds in the concentration-response relationships. The second stage analysis used pooling approaches and assessed potential effect modification by sociodemographic characteristic and indicators of the pollution mixture across study regions. The identified percent change in respiratory disease admission for those aged >64 was from a copollutant model including PM10 is 0.28 (-0.07, 0.62) per 10 ug/m[3] increase in O3.
Respiratory Emergency Department Visits
After considering the relationships between specific and broad respiratory emergency department visit endpoints, the 2020 O3 ISA stated that "studies conducted in diverse locations with a variety of exposure assignment techniques continue to provide evidence of an association between ozone and both hospital admissions and emergency department visits for combined respiratory diseases" and "there is some evidence, previously characterized in the 2013 O3 ISA, that daily 8 hour max, 1 hour max, and daytime average O3 concentrations may be most strongly associated with respiratory emergency department visits" (3432020a3430xd5s9009txfw1eafstv220i5ds2wvtpwf5d1581631219">343</U.S. EPA, 2020b, section 3.1.8).
Available Epidemiologic Literature
Seven U.S.-based studies of respiratory emergency department visits were identified in the 2020 O3 ISA (U.S. EPA, 2020b). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote> As is common with hospital admission and emergency department health endpoints, the specific ICD codes varied across all studies, making pooling difficult. Most studies evaluated only a single city or state and took place in a similar time period, including the early 2000s.
Identifying Suitable Studies for Use in Benefits Assessments
Available studies varied most widely by geographic area, exposure estimation method, population age range, and O3 season. While most studies focused on a specific city, state or region, one study included five different multi-county areas. In addition, it included a recent time period, all ages, current O3 concentrations, and was one of only two studies based on hybrid exposure techniques.
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Barry et al., 2019 investigated the effects of short-term ozone exposure on emergency department visits for respiratory disease (ICD-9 493, 786.07, 460-466, 477, 491, 492, 496, 480 - 486, 466.1, 466.11, 466.19) in an unrestricted population of children, adults, and older adults (aged zero-99 years) within five cities (Atlanta, GA, Birmingham, AL, Dallas, TX, Pittsburgh, PA, and St. Louis, MO-IL) across the United States. Authors obtained individual-level health data from hospitals and hospital associations in each of the five cities. Models fusing air quality monitor data with Community Multi-Scale Air Quality modeled data at 12 x 12-km grids were used to estimate ozone exposure. Barry et al., 2019 assessed associations with short-term ozone exposure with daily eight-hour maximum ozone concentrations. The authors implemented Poisson log-linear models to estimate risk values with three day moving averages. They identified single-pollutant rate ratios of 1.03 (95% CI: 1.01-1.05) in Atlanta, GA, 1.03 (95% CI: 1.00-1.06) in Birmingham, AL, 1.05 (95% CI: 1.02-1.07) in Dallas TX, 1.03 (95% CI: 1.01-1.05) in Pittsburgh, PA, and 1.02 (95% CI: 1.01-1.04) in St. Louis, MO-IL for an increase of 25 ppb in full-year MDA8 O3 concentrations (three day moving average). Results from individual cities are pooled.
Asthma Onset
The 2020 O3 ISA concluded that "recent epidemiologic studies provide generally consistent evidence for associations of long-term ozone exposure with the development of asthma in children" (U.S. EPA, 2020b, section IS.4.3). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote> The ISA also found that "recent animal toxicological studies demonstrate effects on airway development in rodents...and build on and expand the evidence for long-term ozone exposure-induced effects that may lead to asthma development" and asthma onset was called out as a key population level clinically relevant health endpoint in the biological plausibility pathways (section <IP_ADDRESS>.2.1, Figure 9). More specifically, the O3 ISA stated that a "limited number of recent epidemiologic studies provide generally consistent evidence that long-term ozone exposure is associated with the development of asthma in children" (3432020a3430xd5s9009txfw1eafstv220i5ds2wvtpwf5d1581631219">343</U.S. EPA, 2020b, section 3.2.6).
Available Epidemiologic Literature
The 2020 O3 ISA identified children as the population in which this health effect was observed, so we began with the four ISA-identified studies of people <21 (U.S. EPA, 2020b). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote>
Identifying Suitable Studies for Use in Benefits Assessments
Three studies evaluated prospective cohorts, two of which included more recent timespans and likely lower O3 concentrations. One of those studies took place entirely in Canada but included a substantially larger study size (>200 times larger) than the other. As the asthma onset endpoint is consistent between studies, pooling may be appropriate.
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Tetreault et al., 2016 ADDIN EN.CITE <EndNote><Author>Tetreault</Author><Year>2016</Year><RecNum>1183</RecNum><DisplayText>Tetreault et al., 2016</DisplayText><record><rec-number>1183</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603988120">1183</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Tetreault, L. F.</author><author>Doucet, M.</author><author>Gamache, P.</author><author>Fournier, M.</author><author>Brand, A.</author><author>Kosatsky, T.</author><author>Smargiassi, A.</author></authors></contributors><auth-address>Department of Environmental and Occupational Health, School of Public Health University of Montreal, Montreal, Quebec, Canada.</auth-address><titles><title>Childhood Exposure to Ambient Air Pollutants and the Onset of Asthma: An Administrative Cohort Study in Quebec</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>1276-82</pages><volume>124</volume><number>8</number><edition>2016/01/06</edition><keywords><keyword>Air Pollutants/analysis</keyword><keyword>Asthma/*epidemiology</keyword><keyword>Environmental Exposure/analysis/*statistics & numerical data</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Nitrogen Dioxide/analysis</keyword><keyword>Particulate Matter/analysis</keyword><keyword>Proportional Hazards Models</keyword><keyword>Quebec/epidemiology</keyword></keywords><dates><year>2016</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>26731790</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/26731790</url></related-urls></urls><custom2>PMC4977042</custom2><electronic-resource-num>10.1289/ehp.1509838</electronic-resource-num></record></EndNote> investigated the effects of long-term O3 exposure on asthma onset in children (aged zero-12 years) from Québec, Canada. The study followed participants from the Québec Integrated Chronic Disease Surveillance System open birth cohort between 1999 and 2011. The authors defined new cases of asthma based on hospital discharge reports and physician diagnoses (two diagnoses within a two-year span). Monitor data (Canadian National Air Pollution Surveillance network) and land-use mixed effect models estimated warm season (June to August) O3 exposures. Authors assessed associations with asthma onset with both time of birth and time-varying exposure models and adjusted for year of birth, sex, and indices of social and material deprivation. Tetreault et al., 2016 ADDIN EN.CITE <EndNote><Author>Tetreault</Author><Year>2016</Year><RecNum>1183</RecNum><DisplayText>Tetreault et al., 2016</DisplayText><record><rec-number>1183</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603988120">1183</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Tetreault, L. F.</author><author>Doucet, M.</author><author>Gamache, P.</author><author>Fournier, M.</author><author>Brand, A.</author><author>Kosatsky, T.</author><author>Smargiassi, A.</author></authors></contributors><auth-address>Department of Environmental and Occupational Health, School of Public Health University of Montreal, Montreal, Quebec, Canada.</auth-address><titles><title>Childhood Exposure to Ambient Air Pollutants and the Onset of Asthma: An Administrative Cohort Study in Quebec</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>1276-82</pages><volume>124</volume><number>8</number><edition>2016/01/06</edition><keywords><keyword>Air Pollutants/analysis</keyword><keyword>Asthma/*epidemiology</keyword><keyword>Environmental Exposure/analysis/*statistics & numerical data</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Nitrogen Dioxide/analysis</keyword><keyword>Particulate Matter/analysis</keyword><keyword>Proportional Hazards Models</keyword><keyword>Quebec/epidemiology</keyword></keywords><dates><year>2016</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>26731790</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/26731790</url></related-urls></urls><custom2>PMC4977042</custom2><electronic-resource-num>10.1289/ehp.1509838</electronic-resource-num></record></EndNote> used Cox proportional hazard models to observe associations between long-term O3 exposure and asthma onset in children. The identified single-pollutant, warm-season hazard ratio was 1.07 (95% CI: 1.06-1.08) for a 3.26 ppb (interquartile range) increase in annual O3 concentrations.
As the physiology and etiology of lung development in children is similar in children 6-17 (Baena-Cagnani et al., 2007, Guerra et al., 2004, Ochs et al., 2004, Sparrow et al., 1991, Trivedi and Denton, 2019), we apply the 4-12 year age-stratified effect estimate from Tetreault et al., 2016 ADDIN EN.CITE <EndNote><Author>Tetreault</Author><Year>2016</Year><RecNum>1183</RecNum><DisplayText>Tetreault et al., 2016</DisplayText><record><rec-number>1183</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603988120">1183</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Tetreault, L. F.</author><author>Doucet, M.</author><author>Gamache, P.</author><author>Fournier, M.</author><author>Brand, A.</author><author>Kosatsky, T.</author><author>Smargiassi, A.</author></authors></contributors><auth-address>Department of Environmental and Occupational Health, School of Public Health University of Montreal, Montreal, Quebec, Canada.</auth-address><titles><title>Childhood Exposure to Ambient Air Pollutants and the Onset of Asthma: An Administrative Cohort Study in Quebec</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>1276-82</pages><volume>124</volume><number>8</number><edition>2016/01/06</edition><keywords><keyword>Air Pollutants/analysis</keyword><keyword>Asthma/*epidemiology</keyword><keyword>Environmental Exposure/analysis/*statistics & numerical data</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Nitrogen Dioxide/analysis</keyword><keyword>Particulate Matter/analysis</keyword><keyword>Proportional Hazards Models</keyword><keyword>Quebec/epidemiology</keyword></keywords><dates><year>2016</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>26731790</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/26731790</url></related-urls></urls><custom2>PMC4977042</custom2><electronic-resource-num>10.1289/ehp.1509838</electronic-resource-num></record></EndNote> to children ages 4-17.
Asthma Symptoms
Asthma symptoms/exacerbation is identified as a health effect of short-term O3 exposure (section <IP_ADDRESS>.2.1). Overall, the ISA found that "evidence from recent epidemiologic and experimental studies continues to support an association between ozone and asthma exacerbation" with "associations...observed across a range of ozone concentrations, and...consistent in models with measured or modeled concentrations" (3432020a3430xd5s9009txfw1eafstv220i5ds2wvtpwf5d1581631219">343</U.S. EPA, 2020b, section <IP_ADDRESS>).
Available Epidemiologic Literature
Four epidemiologic studies of asthma symptoms meeting our minimum criteria (section 2.1.1) were identified in the 2020 O3 ISA (U.S. EPA, 2020b). ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote> Most studies took place in the late nineties and very early 2000s, and although no study included >1000 participants, there was appreciable geographic representation. There were also differences regarding the ozone season. Only the oldest study specifically evaluated a warm season, although a more recent study did skew slightly toward warmer seasons, evaluating eight seasons over a four-year timespan (two Summers, three Springs, two Falls, and one Winter).
Identifying Suitable Studies for Use in Benefits Assessments
Two of the studies evaluated much higher O3 concentrations (~50 ppb vs 30 ppb). Of the two studies evaluating lower pollutant concentrations, one employed a prospective study design and clearly defined the specific asthma symptoms evaluated (e.g., wheeze).
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Lewis et al., 2013 studied the effects of short-term O3 exposure on frequency of asthma symptoms in an asthmatic population of primarily lower-income, African American and Latino children (aged five-12 years) in East and Southwest Detroit, MI. Authors obtained health and demographic data through questionnaires filled out by parents or guardians for 14 consecutive days in each studied season. Questionnaires highlighted participant's asthma symptoms (cough, wheeze, shortness of breath, chest tightness), demographic information, medication use, and presence of second-hand smoke. The authors acquired maximum one-hour and maximum 8-hour O3 concentrations and meteorological data from two community-level monitors placed on East and Southwest Detroit, MI school rooftops. Lewis et al., 2013 implemented a combination of generalized estimating equations and alternative logistic regression models to estimate the associations between short-term O3 exposure and rate of asthma symptoms. Models adjusted for age, sex, location (Eastside or Southwest), race, household income, smoker in the home, season, and variables for companion home intervention study (control or intervention), time (pre- or post-intervention), and the interaction between intervention group status and time. Lewis et al., 2013 observed positive associations between short-term O3 exposure and asthma symptoms, including the identified single-pollutant, all year odds ratios of 1.12 (95% CI: 0.99-1.25) for cough, 1.13 (95% CI: 0.99-1.28) for wheeze, 1.20 (95% CI: 1.02-1.40) for chest tightness, and 1.07 (95% CI: 0.95-1.21) for shortness of breath, all for a 16 ppb (interquartile range) increase in 8-hour maximum O3 concentrations (five-day average lag).
Minor Restricted Activity Days
No new epidemiologic studies of minor restricted activity days (MRADs) were identified in the 2020 O3 ISA (U.S. EPA, 2020b).
 ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote>
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Ostro and Rothschild, 1989 ADDIN EN.CITE <EndNote><Author>Ostro</Author><Year>1989</Year><RecNum>1372</RecNum><DisplayText>Ostro and Rothschild, 1989</DisplayText><record><rec-number>1372</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1608588120">1372</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Ostro, B. D.</author><author>Rothschild, S.</author></authors></contributors><auth-address>California Public Health Foundation, Berkeley 94704.</auth-address><titles><title>Air pollution and acute respiratory morbidity: an observational study of multiple pollutants</title><secondary-title>Environ Res</secondary-title></titles><periodical><full-title>Environmental Research</full-title>Environ. Res.Environ Res</periodical><pages>238-47</pages><volume>50</volume><number>2</number><edition>1989/12/01</edition><keywords><keyword>Adolescent</keyword><keyword>Adult</keyword><keyword>Aged</keyword><keyword>Air Pollutants/adverse effects</keyword><keyword>Air Pollution/*adverse effects/statistics & numerical data</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Information Systems</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Ozone/adverse effects</keyword><keyword>Regression Analysis</keyword><keyword>Respiratory Tract Diseases/epidemiology/*mortality</keyword><keyword>United States</keyword></keywords><dates><year>1989</year><pub-dates><date>Dec</date></pub-dates></dates><isbn>0013-9351 (Print)
0013-9351 (Linking)</isbn><accession-num>2583069</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/2583069</url></related-urls></urls><electronic-resource-num>10.1016/s0013-9351(89)80004-0</electronic-resource-num></record></EndNote> estimated the impact of PM2.5 and O3 on the incidence of minor restricted activity days (MRADs) and respiratory-related restricted activity days (RRADs) in a national sample of the adult working population, ages 18 to 65, living in metropolitan areas. The study population is based on the Health Interview Survey (HIS), conducted by the National Center for Health Statistics. In publications from this ongoing survey, non-elderly adult populations are generally reported as ages 18-64. From the study, it is not clear if the age range stops at or includes those aged 65. We apply the risk estimate function to individuals ages 18-64 for consistency with other studies estimating impacts to non-elderly adult populations. The annual national survey results used in this analysis were conducted in the period 1976-1981, controlling for PM2.5, two-week average O3.
Allergic Rhinitis (Hay Fever/Respiratory Allergies)
The 2020 O3 ISA stated that "cross-sectional epidemiologic studies provide generally consistent evidence that ozone concentrations are associated with hay fever/rhinitis" and included "allergic responses" in the biological plausibility diagram for long-term O3-attributal respiratory effects (U.S. EPA, 2020b ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote>, section <IP_ADDRESS>.2.1). Although cross sectional analyses do not establish a temporal sequence, they can be used to estimate benefits associated with changes in air quality.
Available Epidemiologic Literature
The 2020 O3 ISA identified one epidemiologic study of long-term O3 exposure and allergic rhinitis.
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Parker et al., 2009 ADDIN EN.CITE <EndNote><Author>Parker</Author><Year>2009</Year><RecNum>1247</RecNum><DisplayText>Parker et al., 2009</DisplayText><record><rec-number>1247</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1608146211">1247</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Parker, J. D.</author><author>Akinbami, L. J.</author><author>Woodruff, T. J.</author></authors></contributors><auth-address>National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland 20782, USA<EMAIL_ADDRESS>pollution and childhood respiratory allergies in the United States</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>140-7</pages><volume>117</volume><number>1</number><edition>2009/01/24</edition><keywords><keyword>Adolescent</keyword><keyword>*Air Pollution</keyword><keyword>Child</keyword><keyword>Child, Preschool</keyword><keyword>Humans</keyword><keyword>Hypersensitivity/*epidemiology</keyword><keyword>United States/epidemiology</keyword><keyword>United States Environmental Protection Agency</keyword><keyword>allergy</keyword><keyword>children</keyword><keyword>hay fever</keyword><keyword>ozone</keyword><keyword>particulate matter</keyword></keywords><dates><year>2009</year><pub-dates><date>Jan</date></pub-dates></dates><isbn>0091-6765 (Print)
0091-6765 (Linking)</isbn><accession-num>19165401</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/19165401</url></related-urls></urls><custom2>PMC2627858</custom2><electronic-resource-num>10.1289/ehp.11497</electronic-resource-num></record></EndNote> investigated the associations between long-term O3 exposure and respiratory allergies in an unrestricted population of children (aged 3-17 years) sampled from the United States National Health Interview Survey. Authors obtained symptom data from participant parents, who reported respiratory allergies on annual surveys. Parker et al., 2009 ADDIN EN.CITE <EndNote><Author>Parker</Author><Year>2009</Year><RecNum>1247</RecNum><DisplayText>Parker et al., 2009</DisplayText><record><rec-number>1247</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1608146211">1247</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Parker, J. D.</author><author>Akinbami, L. J.</author><author>Woodruff, T. J.</author></authors></contributors><auth-address>National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland 20782, USA<EMAIL_ADDRESS>pollution and childhood respiratory allergies in the United States</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>140-7</pages><volume>117</volume><number>1</number><edition>2009/01/24</edition><keywords><keyword>Adolescent</keyword><keyword>*Air Pollution</keyword><keyword>Child</keyword><keyword>Child, Preschool</keyword><keyword>Humans</keyword><keyword>Hypersensitivity/*epidemiology</keyword><keyword>United States/epidemiology</keyword><keyword>United States Environmental Protection Agency</keyword><keyword>allergy</keyword><keyword>children</keyword><keyword>hay fever</keyword><keyword>ozone</keyword><keyword>particulate matter</keyword></keywords><dates><year>2009</year><pub-dates><date>Jan</date></pub-dates></dates><isbn>0091-6765 (Print)
0091-6765 (Linking)</isbn><accession-num>19165401</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/19165401</url></related-urls></urls><custom2>PMC2627858</custom2><electronic-resource-num>10.1289/ehp.11497</electronic-resource-num></record></EndNote> placed all study participants reporting symptoms of respiratory allergies or hay fever into a combined rhinitis group. Parker et al., 2009 ADDIN EN.CITE <EndNote><Author>Parker</Author><Year>2009</Year><RecNum>1247</RecNum><DisplayText>Parker et al., 2009</DisplayText><record><rec-number>1247</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1608146211">1247</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Parker, J. D.</author><author>Akinbami, L. J.</author><author>Woodruff, T. J.</author></authors></contributors><auth-address>National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland 20782, USA<EMAIL_ADDRESS>pollution and childhood respiratory allergies in the United States</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>140-7</pages><volume>117</volume><number>1</number><edition>2009/01/24</edition><keywords><keyword>Adolescent</keyword><keyword>*Air Pollution</keyword><keyword>Child</keyword><keyword>Child, Preschool</keyword><keyword>Humans</keyword><keyword>Hypersensitivity/*epidemiology</keyword><keyword>United States/epidemiology</keyword><keyword>United States Environmental Protection Agency</keyword><keyword>allergy</keyword><keyword>children</keyword><keyword>hay fever</keyword><keyword>ozone</keyword><keyword>particulate matter</keyword></keywords><dates><year>2009</year><pub-dates><date>Jan</date></pub-dates></dates><isbn>0091-6765 (Print)
0091-6765 (Linking)</isbn><accession-num>19165401</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/19165401</url></related-urls></urls><custom2>PMC2627858</custom2><electronic-resource-num>10.1289/ehp.11497</electronic-resource-num></record></EndNote> linked annual averages of SO2, NO2, PM2.5, and PM2.5-10 and warm season (May to September) O3 averages to participant's addresses through ambient air pollution and meteorological data collected from US EPA Air Quality System monitors. The authors adjusted models for survey year, poverty-level, race/ethnicity, age, family structure, insurance coverage, usual source of care, education of adult, urban-rural status, region, and median county-level income. Through multi-pollutant, logistic regression models, the odds ratio of 1.18 (95% CI: 1.09-1.27) for a 10-ppb increase in 24-hour mean, warm season O3 and respiratory allergies was identified.
School Loss Days
No new studies of work loss days (WLDs) were identified in the 2020 O3 ISA (U.S. EPA, 2020b).
 ADDIN EN.CITE <EndNote><Author>U.S. EPA</Author><Year>2020</Year><RecNum>343</RecNum><DisplayText>U.S. EPA, 2020a</DisplayText><record><rec-number>343</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1581631219">343</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>U.S. EPA,</author></authors><secondary-authors><author>Office of Research and Development</author></secondary-authors></contributors><titles><title>Integrated Science Assessment for Ozone and Related Photochemical Oxidants</title></titles><dates><year>2020</year></dates><pub-location>Washington, DC</pub-location><publisher>U.S. Environmental Protection Agency</publisher><isbn>EPA/600/R-20/012</isbn><urls><related-urls><url>Available at: https://www.epa.gov/isa/integrated-science-assessment-isa-ozone-and-related-photochemical-oxidants</url></related-urls></urls></record></EndNote>
Studies and Risk Estimates Identified as Most Suitable for Use in Benefits Assessments
Gilliland et al., 2001 ADDIN EN.CITE <EndNote><Author>Gilliland</Author><Year>2001</Year><RecNum>1377</RecNum><DisplayText>Gilliland et al., 2001</DisplayText><record><rec-number>1377</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1609171575">1377</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gilliland, Frank D</author><author>Berhane, Kiros</author><author>Rappaport, Edward B</author><author>Thomas, Duncan C</author><author>Avol, Edward</author><author>Gauderman, W James</author><author>London, Stephanie J</author><author>Margolis, Helene G</author><author>McConnell, Rob</author><author>Islam, K Talat</author></authors></contributors><titles><title>The effects of ambient air pollution on school absenteeism due to respiratory illnesses</title><secondary-title>Epidemiology</secondary-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><pages>43-54</pages><dates><year>2001</year></dates><isbn>1044-3983</isbn><urls></urls></record></EndNote> examined the association between air pollution and school absenteeism among fourth grade school children (aged nine to 10) in 12 southern Californian communities. The study was conducted from January through June 1996. The authors used school records to collect daily absence data and parental telephone interviews to identify causes. They defined illness- related absences as respiratory or non-respiratory. A respiratory illness was defined as an illness that included at least one of the following: runny nose/sneezing, sore throat, cough, earache, wheezing, or asthma attack. The authors used 15- and 30-day distributed lag models to quantify the association between O3 and incident school absences. O3 levels were positively associated with all school absence measures and significantly associated with all illness-related school absences (non-respiratory illness, respiratory illness, URI and LRI). The health impact function for ozone is based on the results of the single pollutant model.
Gilliland et al., 2001 ADDIN EN.CITE <EndNote><Author>Gilliland</Author><Year>2001</Year><RecNum>1377</RecNum><DisplayText>Gilliland et al., 2001</DisplayText><record><rec-number>1377</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1609171575">1377</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gilliland, Frank D</author><author>Berhane, Kiros</author><author>Rappaport, Edward B</author><author>Thomas, Duncan C</author><author>Avol, Edward</author><author>Gauderman, W James</author><author>London, Stephanie J</author><author>Margolis, Helene G</author><author>McConnell, Rob</author><author>Islam, K Talat</author></authors></contributors><titles><title>The effects of ambient air pollution on school absenteeism due to respiratory illnesses</title><secondary-title>Epidemiology</secondary-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><pages>43-54</pages><dates><year>2001</year></dates><isbn>1044-3983</isbn><urls></urls></record></EndNote> defines an incident absence as an absence that followed attendance on the previous day and the incidence rate as the number of incident absences on a given day over the population at risk for an absence on a given day (i.e., those children who were not absent on the previous day). Since school absences due to air pollution may last longer than one day, an estimate of the average duration of school absences could be used to calculate the total avoided school loss days from an estimate of avoided new absences. A simple ratio of the total absence rate divided by the new absence rate would provide an estimate of the average duration of school absences, which could be applied to the estimate of avoided new absences as follows:

Duration=TotalAbsencesNewAbsences

∆TotalAbsences= -incidences xe-βxO3-1xdurationxpop

Since the function is log-linear, the baseline incidence rate (in this case, the rate of new absences) is multiplied by duration, which reduces to the total school absence rate. Therefore, the same result would be obtained by using a single estimate of the total school absence rate in the risk estimate. Using this approach, we assume that the same relationship observed between pollutant and new school absences in the study would be observed for total absences on a given day. As a result, the total school absence rate is used in the function below. The derivation of this rate is described in the section on baseline incidence rate estimation.
For all absences, the coefficient and standard error are based on a percent increase of 16.3 percent (95% CI -2.6 percent, 38.9 percent) associated with a 20-ppb increase in eight-hour average ozone concentration (2001, Table 6, p. 52).
A scaling factor is used to adjust for the number of school days in the ozone season. In the modeling program, the function is applied to every day in the ozone season (May 1 - September 30), however, in reality, school absences will be avoided only on school days. We assume that children are in school during weekdays for all of May, two weeks in June, one week in August, and all of September. This corresponds to approximately 2.75 months out of the five-month season, resulting in an estimate of 39.3% of days (2.75/5*5/7).
In addition, not all children are at-risk for a new school absence, as defined by the study. On average, 5.5% of school children are absent from school on a given day (NCES, 1996 ADDIN EN.CITE <EndNote><Author>NCES</Author><Year>1996</Year><RecNum>1375</RecNum><DisplayText>NCES, 1996</DisplayText><record><rec-number>1375</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1609171139">1375</key></foreign-keys><ref-type name="Government Document">46</ref-type><contributors><authors><author>NCES, </author></authors><secondary-authors><author>U.S. Department of Education</author></secondary-authors></contributors><titles><title>The Condition of Education 1996, Indicator 42: Student Absenteeism and Tardiness</title></titles><dates><year>1996</year></dates><pub-location>Washington, DC</pub-location><publisher>Office of Educational Research and Improvement</publisher><isbn>NCES 96-304</isbn><urls><related-urls><url>Available at: https://nces.ed.gov/pubs96/96304.pdf</url></related-urls></urls></record></EndNote>, Table 42-1). Only those who are in school on the previous day are at risk for a new absence (1-0.055 = 94.5%). As a result, a factor of 94.5% is used in the function to estimate the population of school children at-risk for a new absence.
Identified Study and Risk Estimates for Benefits Assessments
While we begin with studies identified in ISAs, the goals of an ISA differ greatly from those of benefits assessments. ISAs evaluate the overall state of the science and develop overarching conclusions relating exposure to health effects. This includes analyses of specific subgroups, such as people with pre-existing conditions, that may not be transferrable to the entire U.S. population.
In an effort to make our study and risk estimate identification process as transparent and reproducible as possible, we have explicitly stated the criteria used in our approach (section 0) as well as the available epidemiologic studies evaluated (section 2.2). However, even with such detailed information, expert judgment can be required if multiple estimates meet the required criteria, satisfy a similar number of preferred criteria, and are unable to be statistically aggregated into a single risk estimate (i.e., pooling).
The two tables in this section provide information on the health endpoints and risk estimates identified for use in PM2.5 and O3 benefits estimation (Table 10 and Table 11) using the systematic approach described above (sections 2.1 and 2.2).
Health Endpoints
These summary tables provided an overview of the PM2.5 and O3 health endpoints included in the main benefits analysis. They are the outcome of the systematic approach described above, which involved consideration of recent ISA conclusions along with the availability of clinically relevant epidemiologic risk estimates (Table 8 and Table 9).
PM2.5
Table 8. Set of Health Endpoints for Main PM2.5 Benefits Assessments
                                Endpoint Group
                                 Endpoint Type
                                   Endpoint
                                   Exposure
                                     Ages
Mortality
Mortality
All cause
                                      LT
Adults and older adults (18-99 and 65-99 years)

                                      ST
Infants (1-12 months)
Cardiovascular Effects
Hospital Admissions
Cardiovascular Outcomes
                                      ST
Older adults (65-99 years)

Emergency Department Visits
Cardiovascular Outcomes
                                      ST
Children, adults, and older adults (0-99 years)

Incidence
Acute Myocardial Infarction
                                      ST
Older adults (65-99 years)

Stroke[a]
                                      LT
Older adults (65-99 years)

Cardiac Arrest[a]
                                      ST
Children, adults and older adults (0-99 years)
Respiratory Effects
Hospital Admissions
Respiratory Outcomes
                                      ST
Children and older adults (65-99 years)

Emergency Department Visits
Respiratory Outcomes
                                      ST
Children, adults, and older adults (0-99 years)

Incidence
Asthma Onset[a]
                                      LT
Children (0-17 years)

Asthma Symptoms
                                      ST
Children (6-17 years)

Allergic Rhinitis[a]
                                      LT
Children (3-17 years)

Minor Restricted Activity Days
                                      NA
Adults and older adults (18-64 years)

Work Loss Days
                                      NA
Adults and older adults (18-64 years)
Cancer
Incidence
Lung Cancer[a]
                                      LT
Adults and older adults (30-99 years)
Nervous System Effects
Hospital Admissions
Alzheimer's Disease[a]
                                      LT
Older adults (65-99 years)

Parkinson's Disease[a]
                                      LT
Older adults (65-99 years)
[a]New health endpoint.

O3
Table 9. Set of Health Endpoints for Main O3 Benefits Assessments
                                Endpoint Group
                                 Endpoint Type
                               Specific Endpoint
                                   Exposure
                                     Ages
Mortality
Mortality
Respiratory[a]
                                      ST
Children, adults, and older adults (0-99 years)

                                      LT
Adults and older adults (30-99 years)
Respiratory Effects
Hospital Admissions
Respiratory Outcomes
                                      ST
Older adults (65-99 years)

Emergency Department Visits
Respiratory Outcomes
                                      ST
Children, adults, and older adults (0-99 years)

Incidence
Asthma Onset[a]
                                      LT
Children (0-17 years)

Asthma Symptoms
                                      ST
Children (5-17 years)

Allergic Rhinitis[a]
                                      LT
Children (3-17 years)

Minor Restricted Activity Days
                                      ST
Adults and older adults (18-64 years)

School Loss Days
                                      ST
Children (5-12 years)

                                      ST
Children (9-10 years)
[a]New or updated health endpoint.
Risk Estimates
This section presents the risk estimates identified for the main PM2.5 (section <IP_ADDRESS>) and O3 (section <IP_ADDRESS>) benefits assessments. These lists reflect the application of the available epidemiologic literature (section 2.2) to the identification criteria (section 2.1).
PM2.5
Table 10. Set of Risk Estimates for Main PM2.5 Benefits Assessments
Endpoint
Study Information
Ages
Exposure Duration
Beta Coefficient
(SE)[1]
Mortality
Wu et al., 2020 ADDIN EN.CITE <EndNote><Author>Di</Author><Year>2017</Year><RecNum>536</RecNum><DisplayText>Di et al., 2017b</DisplayText><record><rec-number>536</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732083">536</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Di, Q.</author><author>Wang, Y.</author><author>Zanobetti, A.</author><author>Wang, Y.</author><author>Koutrakis, P.</author><author>Choirat, C.</author><author>Dominici, F.</author><author>Schwartz, J. D.</author></authors></contributors><titles><title>Air pollution and mortality in the Medicare population</title><secondary-title>New England Journal of Medicine</secondary-title><alt-title>N Engl J Med</alt-title></titles><periodical><full-title>New England Journal of Medicine</full-title>New Engl. J. Med.New Engl J Med</periodical><alt-periodical><full-title>N Engl J Med</full-title></alt-periodical><pages>2513-2522</pages><volume>376</volume><number>26</number><edition>June 29, 2017</edition><dates><year>2017</year><pub-dates><date>06</date></pub-dates></dates><isbn>ISSN 0028-4793
EISSN 1533-4406</isbn><accession-num>28657878</accession-num>3841341<urls><related-urls><url>http://dx.doi.org/10.1056/NEJMoa1702747</url></related-urls></urls><electronic-resource-num>10.1056/NEJMoa1702747</electronic-resource-num><language>English</language></record></EndNote>
Older adults (65-99 years)
LT
β = 0.0064 (0.0003)

Pope III et al., 2019
Adults (18-99 years)
LT
β = 0.0113 (0.0016)

Turner et al., 2016 ADDIN EN.CITE <EndNote><Author>Turner</Author><Year>2016</Year><RecNum>544</RecNum><DisplayText>Turner et al., 2016</DisplayText><record><rec-number>544</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732084">544</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Turner, M. C.</author><author>Jerrett, M.</author><author>Pope, A., III</author><author>Krewski, D.</author><author>Gapstur, S. M.</author><author>Diver, W. R.</author><author>Beckerman, B. S.</author><author>Marshall, J. D.</author><author>Su, J.</author><author>Crouse, D. L.</author><author>Burnett, R. T.</author></authors></contributors><titles><title>Long-term ozone exposure and mortality in a large prospective study</title><secondary-title>American Journal of Respiratory and Critical Care Medicine</secondary-title><alt-title>Am J Respir Crit Care Med</alt-title></titles><periodical><full-title>American Journal of Respiratory and Critical Care Medicine</full-title>Am. J. Respir. Crit. Care Med.Am J Respir Crit Care Med</periodical><alt-periodical><full-title>American Journal of Respiratory and Critical Care Medicine</full-title>Am. J. Respir. Crit. Care Med.Am J Respir Crit Care Med</alt-periodical><pages>1134-1142</pages><volume>193</volume><number>10</number><dates><year>2016</year></dates><isbn>ISSN 1073-449X
EISSN 1535-4970</isbn><accession-num>26680605</accession-num>3060878<urls><related-urls><url>http://dx.doi.org/10.1164/rccm.201508-1633OC</url></related-urls></urls><electronic-resource-num>10.1164/rccm.201508-1633OC</electronic-resource-num><language>English</language></record></EndNote>
Adults (30-99 years)
LT
β = 0.0058 (0.0010)

Woodruff et al., 2008 ADDIN EN.CITE <EndNote><Author>Woodruff</Author><Year>2008</Year><RecNum>1154</RecNum><DisplayText>Woodruff et al., 2008</DisplayText><record><rec-number>1154</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732563">1154</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Woodruff, Tracey J</author><author>Darrow, Lyndsey A</author><author>Parker, Jennifer D</author></authors></contributors><titles><title>Air pollution and postneonatal infant mortality in the United States, 1999 - 2002</title><secondary-title>Environmental Health Perspectives</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>110-115</pages><volume>116</volume><number>1</number><dates><year>2008</year></dates><isbn>0091-6765</isbn><urls></urls></record></EndNote>
Infants (1-12 months)
LT
β = 0.0056 (0.00454)
Hospital Admissions, Cardiovascular
Bell et al., 2015  -- ICD 410, omitting 410.x2; 410-414; 426-427; 428; 429; 430-438; and 440-448
Older adults (65-99 years)
ST
β = 0.00065 (0.00009)
Emergency Department Visits, Cardiovascular
Ostro et al., 2016 -- ICD 390-459
Children, adults, and older adults (0-99 years)
ST
β = 0.00061 (0.00042)

 ADDIN EN.CITE <EndNote><Author>Peters</Author><Year>2001</Year><RecNum>1137</RecNum><DisplayText>Peters et al., 2001</DisplayText><record><rec-number>1137</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732560">1137</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Peters, Annette</author><author>Dockery, Douglas W</author><author>Muller, James E</author><author>Mittleman, Murray A</author></authors></contributors><titles><title>Increased particulate air pollution and the triggering of myocardial infarction</title><secondary-title>Circulation</secondary-title></titles><periodical><full-title>Circulation</full-title></periodical><pages>2810-2815</pages><volume>103</volume><number>23</number><dates><year>2001</year></dates><isbn>0009-7322</isbn><urls></urls></record></EndNote>

Acute Myocardial Infarction
Wei et al., 2019 ADDIN EN.CITE <EndNote><Author>Pope III</Author><Year>2006</Year><RecNum>1138</RecNum><DisplayText>Pope III et al., 2006</DisplayText><record><rec-number>1138</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732560">1138</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Pope III, CArden</author><author>Muhlestein, Joseph B</author><author>May, Heidi T</author><author>Renlund, Dale G</author><author>Anderson, Jeffrey L</author><author>Horne, Benjamin D</author></authors></contributors><titles><title>Ischemic heart disease events triggered by short-term exposure to fine particulate air pollution</title><secondary-title>Circulation</secondary-title></titles><periodical><full-title>Circulation</full-title></periodical><pages>2443-2448</pages><volume>114</volume><number>23</number><dates><year>2006</year></dates><isbn>0009-7322</isbn><urls></urls></record></EndNote>
 ADDIN EN.CITE <EndNote><Author>Sullivan</Author><Year>2005</Year><RecNum>1136</RecNum><DisplayText>Sullivan et al., 2005</DisplayText><record><rec-number>1136</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732559">1136</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Sullivan, Jeffrey</author><author>Sheppard, Lianne</author><author>Schreuder, Astrid</author><author>Ishikawa, Naomi</author><author>Siscovick, David</author><author>Kaufman, Joel</author></authors></contributors><titles><title>Relation between short-term fine-particulate matter exposure and onset of myocardial infarction</title><secondary-title>Epidemiology</secondary-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><pages>41-48</pages><dates><year>2005</year></dates><isbn>1044-3983</isbn><urls></urls></record></EndNote>
 ADDIN EN.CITE <EndNote><Author>Zanobetti</Author><Year>2009</Year><RecNum>1140</RecNum><DisplayText>Zanobetti et al., 2009</DisplayText><record><rec-number>1140</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732560">1140</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Zanobetti, Antonella</author><author>Franklin, Meredith</author><author>Koutrakis, Petros</author><author>Schwartz, Joel</author></authors></contributors><titles><title>Fine particulate air pollution and its components in association with cause-specific emergency admissions</title><secondary-title>Environmental Health</secondary-title></titles><periodical><full-title>Environmental Health</full-title>Environ. HealthEnviron Health</periodical><pages>58</pages><volume>8</volume><number>1</number><dates><year>2009</year></dates><isbn>1476-069X</isbn><urls></urls></record></EndNote>
 ADDIN EN.CITE <EndNote><Author>Zanobetti</Author><Year>2006</Year><RecNum>1139</RecNum><DisplayText>Zanobetti and Schwartz, 2006</DisplayText><record><rec-number>1139</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732560">1139</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Zanobetti, Antonella</author><author>Schwartz, Joel</author></authors></contributors><titles><title>Air pollution and emergency admissions in Boston, MA</title><secondary-title>Journal of Epidemiology Community Health</secondary-title></titles><periodical><full-title>Journal of Epidemiology Community Health</full-title></periodical><pages>890-895</pages><volume>60</volume><number>10</number><dates><year>2006</year></dates><isbn>0143-005X</isbn><urls></urls></record></EndNote>
Adults and older adults (18-99 years)
ST
β = 0.02412 (0.00928

)
Cardiac Arrest
Ensor et al., 2013 ADDIN EN.CITE <EndNote><Author>Ensor</Author><Year>2013</Year><RecNum>1192</RecNum><DisplayText>Ensor et al., 2013</DisplayText><record><rec-number>1192</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1604004380">1192</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Ensor, K. B.</author><author>Raun, L. H.</author><author>Persse, D.</author></authors></contributors><auth-address>Rice University, Department of Statistics, PO Box 1892, MS 138, Houston, TX 77251-1892, USA.</auth-address><titles><title>A case-crossover analysis of out-of-hospital cardiac arrest and air pollution</title><secondary-title>Circulation</secondary-title></titles><periodical><full-title>Circulation</full-title></periodical><pages>1192-9</pages><volume>127</volume><number>11</number><edition>2013/02/15</edition><keywords><keyword>Adolescent</keyword><keyword>Adult</keyword><keyword>Age Factors</keyword><keyword>Aged</keyword><keyword>Air Pollution/*adverse effects</keyword><keyword>Cross-Over Studies</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Out-of-Hospital Cardiac Arrest/*epidemiology</keyword><keyword>Ozone/*adverse effects</keyword><keyword>Particulate Matter/*adverse effects</keyword><keyword>Retrospective Studies</keyword><keyword>Risk Factors</keyword><keyword>Sex Factors</keyword><keyword>Texas</keyword><keyword>Young Adult</keyword></keywords><dates><year>2013</year><pub-dates><date>Mar 19</date></pub-dates></dates><isbn>1524-4539 (Electronic)
0009-7322 (Linking)</isbn><accession-num>23406673</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/23406673</url></related-urls></urls><electronic-resource-num>10.1161/CIRCULATIONAHA.113.000027</electronic-resource-num></record></EndNote>
Rosenthal et al., 2008
Silverman et al., 2010
Adults and older adults (0-99 years)
ST
β = 0.00638 (0.00282)
β = 0.00198 (0.00502)
β = 0.00392 (0.00222)
Stroke
Kloog et al., 2012 -- ICD 430-436 ADDIN EN.CITE <EndNote><Author>Kloog</Author><Year>2012</Year><RecNum>1170</RecNum><DisplayText>Kloog et al., 2012</DisplayText><record><rec-number>1170</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603987570">1170</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kloog, I.</author><author>Coull, B. A.</author><author>Zanobetti, A.</author><author>Koutrakis, P.</author><author>Schwartz, J. D.</author></authors></contributors><titles><title>Acute and chronic effects of particles on hospital admissions in New-England</title><secondary-title>PLoS ONE</secondary-title><alt-title>PLoS ONE</alt-title></titles><periodical><full-title>PLoS One</full-title></periodical><alt-periodical><full-title>PLoS One</full-title></alt-periodical><pages>e34664</pages><volume>7</volume><number>4</number><dates><year>2012</year></dates><isbn>EISSN 1932-6203</isbn><accession-num>22529923</accession-num>1255201<urls><related-urls><url>http://dx.doi.org/10.1371/journal.pone.0034664</url></related-urls></urls><electronic-resource-num>10.1371/journal.pone.0034664</electronic-resource-num><language>English</language></record></EndNote>
Older adults (65-99 years)
LT
β = 0.00343 (0.00127)
Hospital Admissions, Respiratory
Bell et al., 2015 -- ICD 490-492, 464-466, 480-487, 493
Older adults (65-99 years)
ST
β = 0.00025 (0.00012)

Ostro et al., 2009 -- ICD 460-519
Children (0-18 years)
ST
β = 0.00275 (0.00077)
Emergency Department Visits, Respiratory
Krall et al., 2013 -- ICD 480-486, 491, 492, 496, 460-465, 466, 477, 493, 786.07 ADDIN EN.CITE <EndNote><Author>Krall</Author><Year>2013</Year><RecNum>1197</RecNum><DisplayText>Krall et al., 2013</DisplayText><record><rec-number>1197</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1604066229">1197</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Krall, J. R.</author><author>Anderson, G. B.</author><author>Dominici, F.</author><author>Bell, M. L.</author><author>Peng, R. D.</author></authors></contributors><auth-address>Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.</auth-address><titles><title>Short-term exposure to particulate matter constituents and mortality in a national study of U.S. urban communities</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>1148-53</pages><volume>121</volume><number>10</number><edition>2013/08/06</edition><keywords><keyword>Air Pollutants/*analysis/chemistry</keyword><keyword>*Environmental Monitoring</keyword><keyword>Humans</keyword><keyword>*Mortality</keyword><keyword>Particulate Matter/*analysis/chemistry</keyword><keyword>Regression Analysis</keyword><keyword>Seasons</keyword><keyword>United States</keyword><keyword>Urban Population</keyword></keywords><dates><year>2013</year><pub-dates><date>Oct</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>23912641</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/23912641</url></related-urls></urls><custom2>PMC3801200</custom2><electronic-resource-num>10.1289/ehp.1206185</electronic-resource-num></record></EndNote>
Children, adults, and older adults (0-99 years)
ST
β = 0.00055 (0.00027) (GA)
β = 0.00097 (0.00035) (AL)
β = 0.00083 (0.00033) (MO)
β = 0.00135 (0.00059) (TX)
Asthma Onset
Tetreault et al., 2016 ADDIN EN.CITE <EndNote><Author>Tetreault</Author><Year>2016</Year><RecNum>1183</RecNum><DisplayText>Tetreault et al., 2016</DisplayText><record><rec-number>1183</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603988120">1183</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Tetreault, L. F.</author><author>Doucet, M.</author><author>Gamache, P.</author><author>Fournier, M.</author><author>Brand, A.</author><author>Kosatsky, T.</author><author>Smargiassi, A.</author></authors></contributors><auth-address>Department of Environmental and Occupational Health, School of Public Health University of Montreal, Montreal, Quebec, Canada.</auth-address><titles><title>Childhood Exposure to Ambient Air Pollutants and the Onset of Asthma: An Administrative Cohort Study in Quebec</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>1276-82</pages><volume>124</volume><number>8</number><edition>2016/01/06</edition><keywords><keyword>Air Pollutants/analysis</keyword><keyword>Asthma/*epidemiology</keyword><keyword>Environmental Exposure/analysis/*statistics & numerical data</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Nitrogen Dioxide/analysis</keyword><keyword>Particulate Matter/analysis</keyword><keyword>Proportional Hazards Models</keyword><keyword>Quebec/epidemiology</keyword></keywords><dates><year>2016</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>26731790</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/26731790</url></related-urls></urls><custom2>PMC4977042</custom2><electronic-resource-num>10.1289/ehp.1509838</electronic-resource-num></record></EndNote>
Children (0-17 years)
LT
β = 0.04367 (0.00088)
Allergic Rhinitis
Parker et al., 2009 ADDIN EN.CITE <EndNote><Author>Parker</Author><Year>2009</Year><RecNum>1247</RecNum><DisplayText>Parker et al., 2009</DisplayText><record><rec-number>1247</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1608146211">1247</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Parker, J. D.</author><author>Akinbami, L. J.</author><author>Woodruff, T. J.</author></authors></contributors><auth-address>National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland 20782, USA<EMAIL_ADDRESS>pollution and childhood respiratory allergies in the United States</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>140-7</pages><volume>117</volume><number>1</number><edition>2009/01/24</edition><keywords><keyword>Adolescent</keyword><keyword>*Air Pollution</keyword><keyword>Child</keyword><keyword>Child, Preschool</keyword><keyword>Humans</keyword><keyword>Hypersensitivity/*epidemiology</keyword><keyword>United States/epidemiology</keyword><keyword>United States Environmental Protection Agency</keyword><keyword>allergy</keyword><keyword>children</keyword><keyword>hay fever</keyword><keyword>ozone</keyword><keyword>particulate matter</keyword></keywords><dates><year>2009</year><pub-dates><date>Jan</date></pub-dates></dates><isbn>0091-6765 (Print)
0091-6765 (Linking)</isbn><accession-num>19165401</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/19165401</url></related-urls></urls><custom2>PMC2627858</custom2><electronic-resource-num>10.1289/ehp.11497</electronic-resource-num></record></EndNote>
Children (3-17)
LT
β = 0.02546 (0.00962)
Lung Cancer
Gharibvand et al., 2017 ADDIN EN.CITE <EndNote><Author>Gharibvand</Author><Year>2017</Year><RecNum>1198</RecNum><DisplayText>Gharibvand et al., 2017</DisplayText><record><rec-number>1198</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1604071026">1198</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Gharibvand, L.</author><author>Shavlik, D.</author><author>Ghamsary, M.</author><author>Beeson, W. L.</author><author>Soret, S.</author><author>Knutsen, R.</author><author>Knutsen, S. F.</author></authors></contributors><auth-address>Adventist Health Study-2, School of Public Health, Loma Linda University, Loma Linda, California, USA.</auth-address><titles><title>The Association between Ambient Fine Particulate Air Pollution and Lung Cancer Incidence: Results from the AHSMOG-2 Study</title><secondary-title>Environ Health Perspect</secondary-title></titles><periodical><full-title>Environmental Health Perspectives</full-title>Environ. Health Perspect.Environ Health Perspect</periodical><pages>378-384</pages><volume>125</volume><number>3</number><edition>2016/08/16</edition><keywords><keyword>Air Pollutants/*analysis</keyword><keyword>Air Pollution/*statistics & numerical data</keyword><keyword>Environmental Exposure/*statistics & numerical data</keyword><keyword>Humans</keyword><keyword>Incidence</keyword><keyword>Lung Neoplasms/*epidemiology</keyword><keyword>Particulate Matter/*analysis</keyword></keywords><dates><year>2017</year><pub-dates><date>Mar</date></pub-dates></dates><isbn>1552-9924 (Electronic)
0091-6765 (Linking)</isbn><accession-num>27519054</accession-num><urls><related-urls><url>https://www.ncbi.nlm.nih.gov/pubmed/27519054</url></related-urls></urls><custom2>PMC5332173</custom2><electronic-resource-num>10.1289/EHP124</electronic-resource-num></record></EndNote>
Adults and older adults (>29 years)
LT
β = 0.03784 (0.01312)
Alzheimer's Disease
Kioumourtzoglou et al., 2016 -- ICD 331.0 ADDIN EN.CITE <EndNote><Author>Kioumourtzoglou</Author><Year>2016</Year><RecNum>1104</RecNum><DisplayText>Kioumourtzoglou et al., 2016</DisplayText><record><rec-number>1104</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732551">1104</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kioumourtzoglou, M. A.</author><author>Schwartz, J.</author><author>James, P.</author><author>Dominici, F.</author><author>Zanobetti, A.</author></authors></contributors><titles><title></title><secondary-title>Epidemiology</secondary-title><alt-title>Epidemiology</alt-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><alt-periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</alt-periodical><pages>221-227</pages><volume>27</volume><number>2</number><dates><year>2016</year></dates><isbn>ISSN 1044-3983
EISSN 1531-5487</isbn><accession-num>26600257</accession-num>3079253<urls><related-urls><url>http://dx.doi.org/10.1097/EDE.0000000000000422</url></related-urls></urls><electronic-resource-num>10.1097/EDE.0000000000000422</electronic-resource-num><language>English</language></record></EndNote>
Older adults (>64 years)
LT
β = 0.13976 (0.01775)
Parkinson's Disease
Kioumourtzoglou et al., 2016 -- ICD 332 ADDIN EN.CITE <EndNote><Author>Kioumourtzoglou</Author><Year>2016</Year><RecNum>1104</RecNum><DisplayText>Kioumourtzoglou et al., 2016</DisplayText><record><rec-number>1104</rec-number><foreign-keys><key app="EN" db-id="0xd5s9009txfw1eafstv220i5ds2wvtpwf5d" timestamp="1603732551">1104</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kioumourtzoglou, M. A.</author><author>Schwartz, J.</author><author>James, P.</author><author>Dominici, F.</author><author>Zanobetti, A.</author></authors></contributors><titles><title></title><secondary-title>Epidemiology</secondary-title><alt-title>Epidemiology</alt-title></titles><periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</periodical><alt-periodical><full-title>Epidemiology</full-title>EpidemiologyEpidemiology</alt-periodical><pages>221-227</pages><volume>27</volume><number>2</number><dates><year>2016</year></dates><isbn>ISSN 1044-3983
EISSN 1531-5487</isbn><accession-num>26600257</accession-num>3079253<urls><related-urls><url>http://dx.doi.org/10.1097/EDE.0000000000000422</url></related-urls></urls><electronic-resource-num>10.1097/EDE.0000000000000422</electronic-resource-num><language>English</language></record></EndNote>
Older adults (>64 years)
LT
β = 0.07696 (0.01891)
Asthma Symptoms
Rabinovitch et al., 2006
Children (6-17 years)
ST
β = 0.00200 (0.00148)
Minor Restricted Activity Days