Bridging between Two Standards for Collecting Information on Race and Ethnicity: An Application to Census 2000 and Vital Rates
Objectives: The 2000 Census, which provides denominators used in calculating vital statistics and other rates, allowed multiple-race responses. Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denom...
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description | Objectives: The 2000 Census, which provides denominators used in calculating vital statistics and other rates, allowed multiple-race responses. Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denominators comparable. This report describes and evaluates the method used by the National Center for Health Statistics to bridge multiple-race responses obtained from Census 2000 to single-race categories, creating single-race population estimates that are available to the public. Methods: The authors fitted logistic regression models to multiple-race data from the National Health Interview Survey (NHIS) for 1997-2000. These fitted models, and two bridging methods previously suggested by the Office of Management and Budget, were applied to the public-use Census Modified Race Data Summary file to create single-race population estimates for the U.S. The authors also compared death rates for single-race groups calculated using these three approaches. Results: Parameter estimates differed between the NHIS models for the multiple-race groups. For example, as the percentage of multiple-race respondents in a county increased, the likelihood of stating black as a primary race increased among black/white respondents but decreased among American Indian or Alaska Native/black respondents. The inclusion of county-level contextual variables in the regression models as well as the underlying demographic differences across states led to variation in allocation percentages; for example, the allocation of black/white respondents to single-race white ranged from nearly zero to more than 50% across states. Death rates calculated using bridging via the NHIS models were similar to those calculated using other methods, except for the American Indian/Alaska Native group, which included a large proportion of multiple-race reporters. Conclusion: Many data systems do not currently allow multiple-race reporting. When such data systems are used with Census counts to produce race-specific rates, bridging methods that incorporate geographic and demographic factors may lead to better rates than methods that do not consider such factors. |
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Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denominators comparable. This report describes and evaluates the method used by the National Center for Health Statistics to bridge multiple-race responses obtained from Census 2000 to single-race categories, creating single-race population estimates that are available to the public. Methods: The authors fitted logistic regression models to multiple-race data from the National Health Interview Survey (NHIS) for 1997-2000. These fitted models, and two bridging methods previously suggested by the Office of Management and Budget, were applied to the public-use Census Modified Race Data Summary file to create single-race population estimates for the U.S. The authors also compared death rates for single-race groups calculated using these three approaches. Results: Parameter estimates differed between the NHIS models for the multiple-race groups. For example, as the percentage of multiple-race respondents in a county increased, the likelihood of stating black as a primary race increased among black/white respondents but decreased among American Indian or Alaska Native/black respondents. The inclusion of county-level contextual variables in the regression models as well as the underlying demographic differences across states led to variation in allocation percentages; for example, the allocation of black/white respondents to single-race white ranged from nearly zero to more than 50% across states. Death rates calculated using bridging via the NHIS models were similar to those calculated using other methods, except for the American Indian/Alaska Native group, which included a large proportion of multiple-race reporters. Conclusion: Many data systems do not currently allow multiple-race reporting. When such data systems are used with Census counts to produce race-specific rates, bridging methods that incorporate geographic and demographic factors may lead to better rates than methods that do not consider such factors.</description><identifier>ISSN: 0033-3549</identifier><identifier>EISSN: 1468-2877</identifier><identifier>DOI: 10.1177/003335490411900213</identifier><identifier>PMID: 15192907</identifier><identifier>CODEN: PHRPA6</identifier><language>eng</language><publisher>Los Angeles, CA: Elsevier</publisher><subject>Adolescent ; Adult ; Aged ; Aged, 80 and over ; Application programming interfaces ; Biological and medical sciences ; Census of Population ; Censuses ; Child ; Child, Preschool ; Continental Population Groups ; Data Collection ; Ethnic Groups ; Ethnicity ; Female ; General aspects ; Health surveys ; Humans ; Infant ; Infant, Newborn ; Information standards ; Interviews as Topic ; Logistic Models ; Male ; Medical sciences ; Middle Aged ; Miscellaneous ; Modeling ; Mortality ; Mortality - trends ; National Center for Health Statistics (U.S.) ; National health insurance ; Population estimates ; Public health ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; Race ; Rates ; Sample Size ; United States ; Vital Statistics</subject><ispartof>Public health reports (1974), 2004-03, Vol.119 (2), p.192-205</ispartof><rights>Copyright 2004 Association of Schools of Public Health</rights><rights>2004 US Surgeon General's Office</rights><rights>2004 INIST-CNRS</rights><rights>Copyright Oxford Publishing Limited(England) Mar/Apr 2004</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c517t-66a8f6a03b49a25e16cec89de5715bb103abc8fbc83f14301f673ed206e387f83</citedby><cites>FETCH-LOGICAL-c517t-66a8f6a03b49a25e16cec89de5715bb103abc8fbc83f14301f673ed206e387f83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/20056663$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/20056663$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,727,780,784,803,885,21819,27866,27924,27925,43621,43622,53791,53793,58017,58250</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15665467$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15192907$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Parker, Jennifer D.</creatorcontrib><creatorcontrib>Schenker, Nathaniel</creatorcontrib><creatorcontrib>Ingram, Deborah D.</creatorcontrib><creatorcontrib>Weed, James A.</creatorcontrib><creatorcontrib>Heck, Katherine E.</creatorcontrib><creatorcontrib>Madans, Jennifer H.</creatorcontrib><title>Bridging between Two Standards for Collecting Information on Race and Ethnicity: An Application to Census 2000 and Vital Rates</title><title>Public health reports (1974)</title><addtitle>Public Health Rep</addtitle><description>Objectives: The 2000 Census, which provides denominators used in calculating vital statistics and other rates, allowed multiple-race responses. Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denominators comparable. This report describes and evaluates the method used by the National Center for Health Statistics to bridge multiple-race responses obtained from Census 2000 to single-race categories, creating single-race population estimates that are available to the public. Methods: The authors fitted logistic regression models to multiple-race data from the National Health Interview Survey (NHIS) for 1997-2000. These fitted models, and two bridging methods previously suggested by the Office of Management and Budget, were applied to the public-use Census Modified Race Data Summary file to create single-race population estimates for the U.S. The authors also compared death rates for single-race groups calculated using these three approaches. Results: Parameter estimates differed between the NHIS models for the multiple-race groups. For example, as the percentage of multiple-race respondents in a county increased, the likelihood of stating black as a primary race increased among black/white respondents but decreased among American Indian or Alaska Native/black respondents. The inclusion of county-level contextual variables in the regression models as well as the underlying demographic differences across states led to variation in allocation percentages; for example, the allocation of black/white respondents to single-race white ranged from nearly zero to more than 50% across states. Death rates calculated using bridging via the NHIS models were similar to those calculated using other methods, except for the American Indian/Alaska Native group, which included a large proportion of multiple-race reporters. Conclusion: Many data systems do not currently allow multiple-race reporting. When such data systems are used with Census counts to produce race-specific rates, bridging methods that incorporate geographic and demographic factors may lead to better rates than methods that do not consider such factors.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Application programming interfaces</subject><subject>Biological and medical sciences</subject><subject>Census of Population</subject><subject>Censuses</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Continental Population Groups</subject><subject>Data Collection</subject><subject>Ethnic Groups</subject><subject>Ethnicity</subject><subject>Female</subject><subject>General aspects</subject><subject>Health surveys</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Information standards</subject><subject>Interviews as Topic</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Miscellaneous</subject><subject>Modeling</subject><subject>Mortality</subject><subject>Mortality - trends</subject><subject>National Center for Health Statistics (U.S.)</subject><subject>National health insurance</subject><subject>Population estimates</subject><subject>Public health</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Race</subject><subject>Rates</subject><subject>Sample Size</subject><subject>United States</subject><subject>Vital Statistics</subject><issn>0033-3549</issn><issn>1468-2877</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7TQ</sourceid><recordid>eNp90WFr1DAYB_AgijunX0BQgjDf1eVpmqT1hXA7pg4Ggk7fhjRNbzl6yS1JHXvjZzddj20qCAmB5Pf8k_Ag9BLIOwAhjgmhlLKqIRVAQ0gJ9BFaQMXroqyFeIwWEygmcYCexbgh5BY9RQfAoCkbIhbo10mw3dq6NW5NujbG4Ytrj78l5ToVuoh7H_DKD4PRaUJnLm9sVbLe4Ty-Km1wpvg0XTqrbbp5j5cOL3e7wepZJY9XxsUx4jJff4t_2KSGXJtMfI6e9GqI5sV-PUTfP55erD4X518-na2W54VmIFLBuap7rghtq0aVzADXRtdNZ5gA1rZAqGp13edJe6gogZ4LarqScENr0df0EH2Yc3djuzWdNi4FNchdsFsVbqRXVv554uylXPufEqpGcJgC3u4Dgr8aTUxya6M2w6Cc8WOUoiTQAOcZvvkLbvwYXP6czIRxVguWUTkjHXyMwfR3LwEip97Kf3ubi14__MN9yb6ZGRztgYpaDX1QTtv4wHHOKj6549lFtTb3z_vv1a_mik1MPtwl5o7mTE7pb2_swtc</recordid><startdate>20040301</startdate><enddate>20040301</enddate><creator>Parker, Jennifer D.</creator><creator>Schenker, Nathaniel</creator><creator>Ingram, Deborah D.</creator><creator>Weed, James A.</creator><creator>Heck, Katherine E.</creator><creator>Madans, Jennifer H.</creator><general>Elsevier</general><general>SAGE Publications</general><general>Association of Schools of Public Health</general><general>SAGE PUBLICATIONS, INC</general><scope>IQODW</scope><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>7TQ</scope><scope>ASE</scope><scope>DHY</scope><scope>DON</scope><scope>FPQ</scope><scope>K6X</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20040301</creationdate><title>Bridging between Two Standards for Collecting Information on Race and Ethnicity: An Application to Census 2000 and Vital Rates</title><author>Parker, Jennifer D. ; Schenker, Nathaniel ; Ingram, Deborah D. ; Weed, James A. ; Heck, Katherine E. ; Madans, Jennifer H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c517t-66a8f6a03b49a25e16cec89de5715bb103abc8fbc83f14301f673ed206e387f83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Application programming interfaces</topic><topic>Biological and medical sciences</topic><topic>Census of Population</topic><topic>Censuses</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Continental Population Groups</topic><topic>Data Collection</topic><topic>Ethnic Groups</topic><topic>Ethnicity</topic><topic>Female</topic><topic>General aspects</topic><topic>Health surveys</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Information standards</topic><topic>Interviews as Topic</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Miscellaneous</topic><topic>Modeling</topic><topic>Mortality</topic><topic>Mortality - trends</topic><topic>National Center for Health Statistics (U.S.)</topic><topic>National health insurance</topic><topic>Population estimates</topic><topic>Public health</topic><topic>Public health. 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Hygiene-occupational medicine</topic><topic>Race</topic><topic>Rates</topic><topic>Sample Size</topic><topic>United States</topic><topic>Vital Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Parker, Jennifer D.</creatorcontrib><creatorcontrib>Schenker, Nathaniel</creatorcontrib><creatorcontrib>Ingram, Deborah D.</creatorcontrib><creatorcontrib>Weed, James A.</creatorcontrib><creatorcontrib>Heck, Katherine E.</creatorcontrib><creatorcontrib>Madans, Jennifer H.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PAIS Index</collection><collection>British Nursing Index</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>British Nursing Index</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Public health reports (1974)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Parker, Jennifer D.</au><au>Schenker, Nathaniel</au><au>Ingram, Deborah D.</au><au>Weed, James A.</au><au>Heck, Katherine E.</au><au>Madans, Jennifer H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bridging between Two Standards for Collecting Information on Race and Ethnicity: An Application to Census 2000 and Vital Rates</atitle><jtitle>Public health reports (1974)</jtitle><addtitle>Public Health Rep</addtitle><date>2004-03-01</date><risdate>2004</risdate><volume>119</volume><issue>2</issue><spage>192</spage><epage>205</epage><pages>192-205</pages><issn>0033-3549</issn><eissn>1468-2877</eissn><coden>PHRPA6</coden><abstract>Objectives: The 2000 Census, which provides denominators used in calculating vital statistics and other rates, allowed multiple-race responses. Many other data systems that provide numerators used in calculating rates collect only single-race data. Bridging is needed to make the numerators and denominators comparable. This report describes and evaluates the method used by the National Center for Health Statistics to bridge multiple-race responses obtained from Census 2000 to single-race categories, creating single-race population estimates that are available to the public. Methods: The authors fitted logistic regression models to multiple-race data from the National Health Interview Survey (NHIS) for 1997-2000. These fitted models, and two bridging methods previously suggested by the Office of Management and Budget, were applied to the public-use Census Modified Race Data Summary file to create single-race population estimates for the U.S. The authors also compared death rates for single-race groups calculated using these three approaches. Results: Parameter estimates differed between the NHIS models for the multiple-race groups. For example, as the percentage of multiple-race respondents in a county increased, the likelihood of stating black as a primary race increased among black/white respondents but decreased among American Indian or Alaska Native/black respondents. The inclusion of county-level contextual variables in the regression models as well as the underlying demographic differences across states led to variation in allocation percentages; for example, the allocation of black/white respondents to single-race white ranged from nearly zero to more than 50% across states. Death rates calculated using bridging via the NHIS models were similar to those calculated using other methods, except for the American Indian/Alaska Native group, which included a large proportion of multiple-race reporters. Conclusion: Many data systems do not currently allow multiple-race reporting. When such data systems are used with Census counts to produce race-specific rates, bridging methods that incorporate geographic and demographic factors may lead to better rates than methods that do not consider such factors.</abstract><cop>Los Angeles, CA</cop><pub>Elsevier</pub><pmid>15192907</pmid><doi>10.1177/003335490411900213</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Aged Aged, 80 and over Application programming interfaces Biological and medical sciences Census of Population Censuses Child Child, Preschool Continental Population Groups Data Collection Ethnic Groups Ethnicity Female General aspects Health surveys Humans Infant Infant, Newborn Information standards Interviews as Topic Logistic Models Male Medical sciences Middle Aged Miscellaneous Modeling Mortality Mortality - trends National Center for Health Statistics (U.S.) National health insurance Population estimates Public health Public health. Hygiene Public health. Hygiene-occupational medicine Race Rates Sample Size United States Vital Statistics |
title | Bridging between Two Standards for Collecting Information on Race and Ethnicity: An Application to Census 2000 and Vital Rates |
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