Traffic density in California: Socioeconomic and ethnic differences among potentially exposed children
Motor vehicles are the main source of many hazardous air pollutants in California. Previous studies have shown that low-income and minority populations are more likely to live near industrial sources of pollution and in areas that do not meet national air quality standards. We estimated neighborhood...
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Veröffentlicht in: | Journal of exposure analysis and environmental epidemiology 2003-05, Vol.13 (3), p.240-246 |
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description | Motor vehicles are the main source of many hazardous air pollutants in California. Previous studies have shown that low-income and minority populations are more likely to live near industrial sources of pollution and in areas that do not meet national air quality standards. We estimated neighborhood exposures to motor vehicle emissions from a road network with daily traffic counts using a geographic information system. To calculate traffic density, we summed the average daily vehicle miles of travel per square mile of land area for each census block group in the state. We used 1990 census data to characterize the population by age, race and socioeconomic status in block groups with high traffic density. Block groups with more than 500,000 vehicle miles of travel per square mile were defined to be high traffic density. Statewide, about 5% of all block groups met this criterion and more than 215,000 children under 15 years of age lived in these high traffic density areas. Block groups in the lowest quartile of median family income were three times more likely to have high traffic density than block groups in the highest income quartile. The percentage of children living in high traffic density block groups increased with decreasing median family income for all race and ethnicities except White. Overall, children of color were about three times more likely to live in high-traffic areas than were white children. Based on this analysis, low-income and children of color have higher potential exposure to vehicle emissions. Future exposure assessment studies should target the highest traffic density areas, and health studies should consider the differences by income and race or ethnicity during design. |
doi_str_mv | 10.1038/sj.jea.7500276 |
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Previous studies have shown that low-income and minority populations are more likely to live near industrial sources of pollution and in areas that do not meet national air quality standards. We estimated neighborhood exposures to motor vehicle emissions from a road network with daily traffic counts using a geographic information system. To calculate traffic density, we summed the average daily vehicle miles of travel per square mile of land area for each census block group in the state. We used 1990 census data to characterize the population by age, race and socioeconomic status in block groups with high traffic density. Block groups with more than 500,000 vehicle miles of travel per square mile were defined to be high traffic density. Statewide, about 5% of all block groups met this criterion and more than 215,000 children under 15 years of age lived in these high traffic density areas. Block groups in the lowest quartile of median family income were three times more likely to have high traffic density than block groups in the highest income quartile. The percentage of children living in high traffic density block groups increased with decreasing median family income for all race and ethnicities except White. Overall, children of color were about three times more likely to live in high-traffic areas than were white children. Based on this analysis, low-income and children of color have higher potential exposure to vehicle emissions. Future exposure assessment studies should target the highest traffic density areas, and health studies should consider the differences by income and race or ethnicity during design.</description><identifier>ISSN: 1053-4245</identifier><identifier>ISSN: 1559-0631</identifier><identifier>EISSN: 1476-5519</identifier><identifier>EISSN: 1559-064X</identifier><identifier>DOI: 10.1038/sj.jea.7500276</identifier><identifier>PMID: 12743618</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject><![CDATA[Adolescent ; Air pollution ; Air quality ; Air quality standards ; California ; Census ; Child ; Child, Preschool ; Children ; Color ; Emissions ; Environmental Exposure - analysis ; Environmental Exposure - statistics & numerical data ; Environmental Monitoring - methods ; Environmental Monitoring - statistics & numerical data ; Epidemiology ; Ethnic Groups - statistics & numerical data ; Exposure ; Family income ; Geographic information systems ; Humans ; Income ; Industrial pollution ; Land area ; Low income groups ; Medicine ; Medicine & Public Health ; Minority & ethnic groups ; Motor vehicles ; Motor Vehicles - statistics & numerical data ; original-research ; Pollutants ; Pollution sources ; Race ; Remote sensing ; Roads ; Socioeconomic Factors ; Socioeconomics ; Traffic ; Traffic information ; Traffic volume ; Travel ; Vehicle emissions ; Vehicle Emissions - analysis]]></subject><ispartof>Journal of exposure analysis and environmental epidemiology, 2003-05, Vol.13 (3), p.240-246</ispartof><rights>Springer Nature America, Inc. 2003</rights><rights>COPYRIGHT 2003 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group May 2003</rights><rights>Nature Publishing Group 2003.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c506t-2adfaf39360dd0f1e4c49880a9c44794996d335f23f36b76840ee73ddc4f92403</citedby><cites>FETCH-LOGICAL-c506t-2adfaf39360dd0f1e4c49880a9c44794996d335f23f36b76840ee73ddc4f92403</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12743618$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gunier, Robert B</creatorcontrib><creatorcontrib>Hertz, Andrew</creatorcontrib><creatorcontrib>von Behren, Julie</creatorcontrib><creatorcontrib>Reynolds, Peggy</creatorcontrib><title>Traffic density in California: Socioeconomic and ethnic differences among potentially exposed children</title><title>Journal of exposure analysis and environmental epidemiology</title><addtitle>J Expo Sci Environ Epidemiol</addtitle><addtitle>J Expo Anal Environ Epidemiol</addtitle><description>Motor vehicles are the main source of many hazardous air pollutants in California. Previous studies have shown that low-income and minority populations are more likely to live near industrial sources of pollution and in areas that do not meet national air quality standards. We estimated neighborhood exposures to motor vehicle emissions from a road network with daily traffic counts using a geographic information system. To calculate traffic density, we summed the average daily vehicle miles of travel per square mile of land area for each census block group in the state. We used 1990 census data to characterize the population by age, race and socioeconomic status in block groups with high traffic density. Block groups with more than 500,000 vehicle miles of travel per square mile were defined to be high traffic density. Statewide, about 5% of all block groups met this criterion and more than 215,000 children under 15 years of age lived in these high traffic density areas. Block groups in the lowest quartile of median family income were three times more likely to have high traffic density than block groups in the highest income quartile. The percentage of children living in high traffic density block groups increased with decreasing median family income for all race and ethnicities except White. Overall, children of color were about three times more likely to live in high-traffic areas than were white children. Based on this analysis, low-income and children of color have higher potential exposure to vehicle emissions. Future exposure assessment studies should target the highest traffic density areas, and health studies should consider the differences by income and race or ethnicity during design.</description><subject>Adolescent</subject><subject>Air pollution</subject><subject>Air quality</subject><subject>Air quality standards</subject><subject>California</subject><subject>Census</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Color</subject><subject>Emissions</subject><subject>Environmental Exposure - analysis</subject><subject>Environmental Exposure - statistics & numerical data</subject><subject>Environmental Monitoring - methods</subject><subject>Environmental Monitoring - statistics & numerical data</subject><subject>Epidemiology</subject><subject>Ethnic Groups - statistics & numerical data</subject><subject>Exposure</subject><subject>Family income</subject><subject>Geographic information systems</subject><subject>Humans</subject><subject>Income</subject><subject>Industrial pollution</subject><subject>Land area</subject><subject>Low income groups</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Minority & ethnic groups</subject><subject>Motor vehicles</subject><subject>Motor Vehicles - statistics & numerical data</subject><subject>original-research</subject><subject>Pollutants</subject><subject>Pollution sources</subject><subject>Race</subject><subject>Remote sensing</subject><subject>Roads</subject><subject>Socioeconomic Factors</subject><subject>Socioeconomics</subject><subject>Traffic</subject><subject>Traffic information</subject><subject>Traffic volume</subject><subject>Travel</subject><subject>Vehicle emissions</subject><subject>Vehicle Emissions - analysis</subject><issn>1053-4245</issn><issn>1559-0631</issn><issn>1476-5519</issn><issn>1559-064X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kUtv1DAUhSMEog_YsgNFVGKXqd-Ju6tGQJEqddGytlz7euoosQc7kZh_j6cTqIRaeWHL57vnXvtU1QeMVhjR7jz3qx70quUIkVa8qo4xa0XDOZavyxlx2jDC-FF1knOP0F6Ub6sjTFpGBe6OK3eXtHPe1BZC9tOu9qFe68G7mILXF_VtND6CiSGOBdLB1jA9hD3vnYMEwUCu9RjDpt7GCcLk9TDsavi9jRlsbR78YAv1rnrj9JDh_bKfVj-_fb1bXzXXN99_rC-vG8ORmBqirdOOSiqQtchhYIbJrkNaGsZayaQUllLuCHVU3LeiYwigpdYa5iRhiJ5WXw6-2xR_zZAnNfpsYBh0gDhnhQVuieh4Ac_-A_s4p1BmU0QwxFvKKSnU5xcpLDmR6LHnYrXRAygfXJySNvu-6hJLhLjECBdq9QxVloXyszGA8-X-uQKTYs4JnNomP-q0UxipffYq96pkr5bsS8GnZdj5fgT7hC9hF-D8AOQihQ2kp9e8aPnxUBH0NCf4Z_lX_wPXZMI8</recordid><startdate>200305</startdate><enddate>200305</enddate><creator>Gunier, Robert B</creator><creator>Hertz, Andrew</creator><creator>von Behren, Julie</creator><creator>Reynolds, Peggy</creator><general>Nature Publishing Group US</general><general>Nature Publishing Group</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7ST</scope><scope>7T2</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>M7S</scope><scope>P64</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7TV</scope><scope>7U2</scope></search><sort><creationdate>200305</creationdate><title>Traffic density in California: Socioeconomic and ethnic differences among potentially exposed children</title><author>Gunier, Robert B ; Hertz, Andrew ; von Behren, Julie ; Reynolds, Peggy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c506t-2adfaf39360dd0f1e4c49880a9c44794996d335f23f36b76840ee73ddc4f92403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Adolescent</topic><topic>Air pollution</topic><topic>Air quality</topic><topic>Air quality standards</topic><topic>California</topic><topic>Census</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Children</topic><topic>Color</topic><topic>Emissions</topic><topic>Environmental Exposure - 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Previous studies have shown that low-income and minority populations are more likely to live near industrial sources of pollution and in areas that do not meet national air quality standards. We estimated neighborhood exposures to motor vehicle emissions from a road network with daily traffic counts using a geographic information system. To calculate traffic density, we summed the average daily vehicle miles of travel per square mile of land area for each census block group in the state. We used 1990 census data to characterize the population by age, race and socioeconomic status in block groups with high traffic density. Block groups with more than 500,000 vehicle miles of travel per square mile were defined to be high traffic density. Statewide, about 5% of all block groups met this criterion and more than 215,000 children under 15 years of age lived in these high traffic density areas. Block groups in the lowest quartile of median family income were three times more likely to have high traffic density than block groups in the highest income quartile. The percentage of children living in high traffic density block groups increased with decreasing median family income for all race and ethnicities except White. Overall, children of color were about three times more likely to live in high-traffic areas than were white children. Based on this analysis, low-income and children of color have higher potential exposure to vehicle emissions. Future exposure assessment studies should target the highest traffic density areas, and health studies should consider the differences by income and race or ethnicity during design.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>12743618</pmid><doi>10.1038/sj.jea.7500276</doi><tpages>7</tpages></addata></record> |
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subjects | Adolescent Air pollution Air quality Air quality standards California Census Child Child, Preschool Children Color Emissions Environmental Exposure - analysis Environmental Exposure - statistics & numerical data Environmental Monitoring - methods Environmental Monitoring - statistics & numerical data Epidemiology Ethnic Groups - statistics & numerical data Exposure Family income Geographic information systems Humans Income Industrial pollution Land area Low income groups Medicine Medicine & Public Health Minority & ethnic groups Motor vehicles Motor Vehicles - statistics & numerical data original-research Pollutants Pollution sources Race Remote sensing Roads Socioeconomic Factors Socioeconomics Traffic Traffic information Traffic volume Travel Vehicle emissions Vehicle Emissions - analysis |
title | Traffic density in California: Socioeconomic and ethnic differences among potentially exposed children |
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