PMC:1247194 / 20900-21970 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/1247194","sourcedb":"PMC","sourceid":"1247194","source_url":"https://www.ncbi.nlm.nih.gov/pmc/1247194","text":"A common metric used in studies employing GIS is the proximity between a pollutant source and a residence. Simple proximity metrics are likely to overestimate the population truly exposed (high sensitivity but low specificity). If those truly exposed represent only a small percent of the study population, there will be substantial attenuation of the risk estimate if a true risk exists. Rull and Ritz (2003) compared several methods of classifying a study population in California on the basis of agricultural pesticide use reported by the California Pesticide Use Reporting (CPUR) database (http://www.cdpr.ca.gov/). The prevalence of exposure differed substantially depending on the metric used. They assumed that a metric that accounted for the location of crop fields more accurately represented true exposures and this metric resulted in lower exposure prevalence compared with a metric based on the CPUR database alone. In a simulation study they demonstrated that the reduced specificity of the CPUR metric resulted in substantial attenuation of risk estimates.","tracks":[{"project":"2_test","denotations":[{"id":"15198921-14527836-28170888","span":{"begin":404,"end":408},"obj":"14527836"}],"attributes":[{"subj":"15198921-14527836-28170888","pred":"source","obj":"2_test"}]},{"project":"MyTest","denotations":[{"id":"15198921-14527836-28170888","span":{"begin":404,"end":408},"obj":"14527836"}],"namespaces":[{"prefix":"_base","uri":"https://www.uniprot.org/uniprot/testbase"},{"prefix":"UniProtKB","uri":"https://www.uniprot.org/uniprot/"},{"prefix":"uniprot","uri":"https://www.uniprot.org/uniprotkb/"}],"attributes":[{"subj":"15198921-14527836-28170888","pred":"source","obj":"MyTest"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"2_test","color":"#93ecc3","default":true},{"id":"MyTest","color":"#eca993"}]}]}}