Assessing exposure metrics for PM and birth weight models
The link between air pollution exposure and adverse birth outcomes is of public health concern due to the relationship between poor pregnancy outcomes and the onset of childhood and adult diseases. As personal exposure measurements are difficult and expensive to obtain, proximate measures of air pol...
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| Veröffentlicht in: | Journal of exposure science & environmental epidemiology 2010-07, Vol.20 (5), p.469-477 |
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| creator | Gray, Simone C Edwards, Sharon E Miranda, Marie Lynn |
| description | The link between air pollution exposure and adverse birth outcomes is of public health concern due to the relationship between poor pregnancy outcomes and the onset of childhood and adult diseases. As personal exposure measurements are difficult and expensive to obtain, proximate measures of air pollution exposure are traditionally used. We explored how different air pollution exposure metrics affect birth weight regression models. We examined the effect of maternal exposure to ambient levels of particulate matter |
| doi_str_mv | 10.1038/jes.2009.52 |
| format | Article |
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10
, PM
2.5
) on birth weight among infants in North Carolina. We linked maternal residence to the closest monitor during pregnancy for 2000–2002 (
n
=350,754). County-level averages of air pollution concentrations were estimated for the entire pregnancy and each trimester. For a finer spatially resolved metric, we calculated exposure averages for women living within 20, 10, and 5 km of a monitor. Multiple linear regression was used to determine the association between exposure and birth weight, adjusting for standard covariates. In the county-level model, an interquartile increase in PM
10
and PM
2.5
during the entire gestational period reduced the birth weight by 5.3 g (95% CI: 3.3–7.4) and 4.6 g (95% CI: 2.3–6.8), respectively. This model also showed a reduction in birth weight for PM
10
(7.1 g, 95% CI: 1.0–13.2) and PM
2.5
(10.4 g, 95% CI: 6.4–14.4) during the third trimester. Proximity models for 20, 10, and 5 km distances showed results similar to the county-level models. County-level models assume that exposure is spatially homogeneous over a larger surface area than proximity models. Sensitivity analysis showed that at varying spatial resolutions, there is still a stable and negative association between air pollution and birth weight, despite North Carolina's consistent attainment of federal air quality standards.</description><identifier>ISSN: 1559-0631</identifier><identifier>EISSN: 1559-064X</identifier><identifier>DOI: 10.1038/jes.2009.52</identifier><identifier>PMID: 19773814</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>Air pollution ; Air Pollution - adverse effects ; Air Pollution - analysis ; Air pollution measurements ; Air quality ; Air quality standards ; Birth Weight ; Birth weight, Low ; Children ; Diameters ; Environmental Monitoring ; Epidemiology ; Exposure ; Female ; Health aspects ; Humans ; Infant, Newborn ; Infants ; Linear Models ; Maternal Exposure - adverse effects ; Medicine ; Medicine & Public Health ; North Carolina ; Outdoor air quality ; Particles ; Particulate emissions ; Particulate matter ; Particulate Matter - adverse effects ; Particulate Matter - analysis ; Pregnancy ; Pregnancy Trimesters ; Public health ; Regression analysis ; Regression models ; Residence Characteristics ; Risk Assessment ; Risk factors ; Sensitivity analysis ; Surface area</subject><ispartof>Journal of exposure science & environmental epidemiology, 2010-07, Vol.20 (5), p.469-477</ispartof><rights>Nature America, Inc. 2010</rights><rights>COPYRIGHT 2010 Nature Publishing Group</rights><rights>Nature America, Inc. 2010.</rights><rights>Copyright Nature Publishing Group Jul 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c547t-b654a43c6b7c6f48e93bf74899705c0864e03f355c64eac81db3e9595ade032a3</citedby><cites>FETCH-LOGICAL-c547t-b654a43c6b7c6f48e93bf74899705c0864e03f355c64eac81db3e9595ade032a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/jes.2009.52$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/jes.2009.52$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51298</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19773814$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gray, Simone C</creatorcontrib><creatorcontrib>Edwards, Sharon E</creatorcontrib><creatorcontrib>Miranda, Marie Lynn</creatorcontrib><title>Assessing exposure metrics for PM and birth weight models</title><title>Journal of exposure science & environmental epidemiology</title><addtitle>J Expo Sci Environ Epidemiol</addtitle><addtitle>J Expo Sci Environ Epidemiol</addtitle><description>The link between air pollution exposure and adverse birth outcomes is of public health concern due to the relationship between poor pregnancy outcomes and the onset of childhood and adult diseases. As personal exposure measurements are difficult and expensive to obtain, proximate measures of air pollution exposure are traditionally used. We explored how different air pollution exposure metrics affect birth weight regression models. We examined the effect of maternal exposure to ambient levels of particulate matter <10, <2.5 μm in aerodynamic diameter (PM
10
, PM
2.5
) on birth weight among infants in North Carolina. We linked maternal residence to the closest monitor during pregnancy for 2000–2002 (
n
=350,754). County-level averages of air pollution concentrations were estimated for the entire pregnancy and each trimester. For a finer spatially resolved metric, we calculated exposure averages for women living within 20, 10, and 5 km of a monitor. Multiple linear regression was used to determine the association between exposure and birth weight, adjusting for standard covariates. In the county-level model, an interquartile increase in PM
10
and PM
2.5
during the entire gestational period reduced the birth weight by 5.3 g (95% CI: 3.3–7.4) and 4.6 g (95% CI: 2.3–6.8), respectively. This model also showed a reduction in birth weight for PM
10
(7.1 g, 95% CI: 1.0–13.2) and PM
2.5
(10.4 g, 95% CI: 6.4–14.4) during the third trimester. Proximity models for 20, 10, and 5 km distances showed results similar to the county-level models. County-level models assume that exposure is spatially homogeneous over a larger surface area than proximity models. Sensitivity analysis showed that at varying spatial resolutions, there is still a stable and negative association between air pollution and birth weight, despite North Carolina's consistent attainment of federal air quality standards.</description><subject>Air pollution</subject><subject>Air Pollution - adverse effects</subject><subject>Air Pollution - analysis</subject><subject>Air pollution measurements</subject><subject>Air quality</subject><subject>Air quality standards</subject><subject>Birth Weight</subject><subject>Birth weight, Low</subject><subject>Children</subject><subject>Diameters</subject><subject>Environmental Monitoring</subject><subject>Epidemiology</subject><subject>Exposure</subject><subject>Female</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Infant, Newborn</subject><subject>Infants</subject><subject>Linear Models</subject><subject>Maternal Exposure - adverse effects</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>North Carolina</subject><subject>Outdoor air quality</subject><subject>Particles</subject><subject>Particulate emissions</subject><subject>Particulate matter</subject><subject>Particulate Matter - adverse effects</subject><subject>Particulate Matter - analysis</subject><subject>Pregnancy</subject><subject>Pregnancy Trimesters</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Residence Characteristics</subject><subject>Risk Assessment</subject><subject>Risk factors</subject><subject>Sensitivity analysis</subject><subject>Surface 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Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><collection>Pollution Abstracts</collection><collection>Safety Science and Risk</collection><jtitle>Journal of exposure science & environmental epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gray, Simone C</au><au>Edwards, Sharon E</au><au>Miranda, Marie Lynn</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing exposure metrics for PM and birth weight models</atitle><jtitle>Journal of exposure science & environmental epidemiology</jtitle><stitle>J Expo Sci Environ Epidemiol</stitle><addtitle>J Expo Sci Environ Epidemiol</addtitle><date>2010-07-01</date><risdate>2010</risdate><volume>20</volume><issue>5</issue><spage>469</spage><epage>477</epage><pages>469-477</pages><issn>1559-0631</issn><eissn>1559-064X</eissn><abstract>The link between air pollution exposure and adverse birth outcomes is of public health concern due to the relationship between poor pregnancy outcomes and the onset of childhood and adult diseases. As personal exposure measurements are difficult and expensive to obtain, proximate measures of air pollution exposure are traditionally used. We explored how different air pollution exposure metrics affect birth weight regression models. We examined the effect of maternal exposure to ambient levels of particulate matter <10, <2.5 μm in aerodynamic diameter (PM
10
, PM
2.5
) on birth weight among infants in North Carolina. We linked maternal residence to the closest monitor during pregnancy for 2000–2002 (
n
=350,754). County-level averages of air pollution concentrations were estimated for the entire pregnancy and each trimester. For a finer spatially resolved metric, we calculated exposure averages for women living within 20, 10, and 5 km of a monitor. Multiple linear regression was used to determine the association between exposure and birth weight, adjusting for standard covariates. In the county-level model, an interquartile increase in PM
10
and PM
2.5
during the entire gestational period reduced the birth weight by 5.3 g (95% CI: 3.3–7.4) and 4.6 g (95% CI: 2.3–6.8), respectively. This model also showed a reduction in birth weight for PM
10
(7.1 g, 95% CI: 1.0–13.2) and PM
2.5
(10.4 g, 95% CI: 6.4–14.4) during the third trimester. Proximity models for 20, 10, and 5 km distances showed results similar to the county-level models. County-level models assume that exposure is spatially homogeneous over a larger surface area than proximity models. Sensitivity analysis showed that at varying spatial resolutions, there is still a stable and negative association between air pollution and birth weight, despite North Carolina's consistent attainment of federal air quality standards.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>19773814</pmid><doi>10.1038/jes.2009.52</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of exposure science & environmental epidemiology, 2010-07, Vol.20 (5), p.469-477 |
| issn | 1559-0631 1559-064X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_744625400 |
| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Air pollution Air Pollution - adverse effects Air Pollution - analysis Air pollution measurements Air quality Air quality standards Birth Weight Birth weight, Low Children Diameters Environmental Monitoring Epidemiology Exposure Female Health aspects Humans Infant, Newborn Infants Linear Models Maternal Exposure - adverse effects Medicine Medicine & Public Health North Carolina Outdoor air quality Particles Particulate emissions Particulate matter Particulate Matter - adverse effects Particulate Matter - analysis Pregnancy Pregnancy Trimesters Public health Regression analysis Regression models Residence Characteristics Risk Assessment Risk factors Sensitivity analysis Surface area |
| title | Assessing exposure metrics for PM and birth weight models |
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