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We included all incident cases among residents of either Massachusetts (MA; 1990 population = 6,016,425) or Rhode Island (RI; 1990 population = 1,003,464) for: STIs (MA: 1994\u20131998,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 26,535 chlamydia, 7,464 gonorrhea, 2,619 syphilis; RI: 1994\u20131996,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 4,473 chlamydia, 1,256 gonorrhea, 305 syphilis); TB (MA: 1993\u20131998,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 1,793; RI: 1985\u20131994,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 576), and non-fatal weapons related injuries (MA: 1995\u20131997,\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 6,628).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results.<\/jats:title>\n                    <jats:p>\n                      Analyses indicated that: (\n                      <jats:italic toggle=\"yes\">a<\/jats:italic>\n                      ) block group and tract socioeconomic measures performed similarly within and across both states, with results more variable for the ZIP Code level measures; (\n                      <jats:italic toggle=\"yes\">b<\/jats:italic>\n                      ) measures of economic deprivation consistently detected the steepest socioeconomic gradients, considered across all outcomes (incidence rate ratios on the order of 10 or higher for syphilis, gonorrhea, and non-fatal intentional weapons-related injuries, and 7 or higher for chlamydia and TB); and (\n                      <jats:italic toggle=\"yes\">c<\/jats:italic>\n                      ) results were similar for categories generated by quintiles and by a priori categorical cut-points.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions.<\/jats:title>\n                    <jats:p>Supplementing U.S. public health surveillance systems with census tract or block group area-based socioeconomic measures of economic deprivation could greatly enhance monitoring and analysis of social inequalities in health in the United States.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/phr\/118.3.240","type":"journal-article","created":{"date-parts":[[2003,5,23]],"date-time":"2003-05-23T15:38:47Z","timestamp":1053704327000},"page":"240-260","source":"Crossref","is-referenced-by-count":143,"title":["Monitoring Socioeconomic Inequalities in Sexually Transmitted Infections, Tuberculosis, and Violence: Geocoding and Choice of Area-Based Socioeconomic Measures\u2014The Public Health Disparities Geocoding Project (US)"],"prefix":"10.1177","volume":"118","author":[{"given":"Nancy","family":"Krieger","sequence":"first","affiliation":[{"name":"Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pamela D.","family":"Waterman","sequence":"additional","affiliation":[{"name":"Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jarvis T.","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mah-Jabeen","family":"Soobader","sequence":"additional","affiliation":[{"name":"Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"SV","family":"Subramanian","sequence":"additional","affiliation":[{"name":"Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2003,5]]},"reference":[{"key":"e_1_2_1_2_2","first-page":"481","article-title":"Can we monitor socioeconomic inequalities in health? 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