D. Ritzwoller, Nikki M. Carroll, B. Gaglio, Anna Sukhanova, Fabio A. Almeida, Melanie A. Stopponi, Diego Osuna
{"title":"Variation in Hispanic Self-Identification, Spanish Surname, and Geocoding: Implications for Ethnicity Data Collection","authors":"D. Ritzwoller, Nikki M. Carroll, B. Gaglio, Anna Sukhanova, Fabio A. Almeida, Melanie A. Stopponi, Diego Osuna","doi":"10.2174/1874924000801010012","DOIUrl":null,"url":null,"abstract":"This study examines the variation in surname analysis and geocoding, and their association with self-identified Hispanics in an HMO. We collected ethnicity data from three studies, and employed Spanish surname software and cen- sus tract level geocoding to create proxies for Hispanic ethnicity. We computed sensitivity, specificity, and estimated mul- tivariate logistic regression models to examine the variation in the likelihood of a match between self-identified Hispanics and surname. Sensitivity and specificity with respect to surname varied across the three studies, ranging from 57%-91% and 89%-96%, respectively. Relative to self-report, the sensitivity of the census tract measure of density of Hispanics, var- ied from 5%-15%. Multivariate models suggest that the likelihood of a match between self-identified Hispanics and sur- name was not associated with age or gender. Self-identified Hispanics living in neighborhoods with the highest density of Hispanics were less likely than those in more mixed neighborhoods to have a Spanish surname. Employing the Spanish surname software on only densely populated Hispanic census tracts may not always improve the likelihood of correctly identifying Hispanic subjects.","PeriodicalId":88329,"journal":{"name":"The open health services and policy journal","volume":"1 1","pages":"12-18"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The open health services and policy journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874924000801010012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This study examines the variation in surname analysis and geocoding, and their association with self-identified Hispanics in an HMO. We collected ethnicity data from three studies, and employed Spanish surname software and cen- sus tract level geocoding to create proxies for Hispanic ethnicity. We computed sensitivity, specificity, and estimated mul- tivariate logistic regression models to examine the variation in the likelihood of a match between self-identified Hispanics and surname. Sensitivity and specificity with respect to surname varied across the three studies, ranging from 57%-91% and 89%-96%, respectively. Relative to self-report, the sensitivity of the census tract measure of density of Hispanics, var- ied from 5%-15%. Multivariate models suggest that the likelihood of a match between self-identified Hispanics and sur- name was not associated with age or gender. Self-identified Hispanics living in neighborhoods with the highest density of Hispanics were less likely than those in more mixed neighborhoods to have a Spanish surname. Employing the Spanish surname software on only densely populated Hispanic census tracts may not always improve the likelihood of correctly identifying Hispanic subjects.