{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:51:30Z","timestamp":1786978290588,"version":"build-2736575974"},"reference-count":17,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2013,2,4]],"date-time":"2013-02-04T00:00:00Z","timestamp":1359936000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmacoepidemiology and Drug"],"published-print":{"date-parts":[[2013,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Evaluating disparities in health care is an important aspect of understanding differences in disease risk. The purpose of this study is to describe the methodology for estimating such disparities, with application to a large multi\u2010ethnic cohort study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The Multi\u2010Ethnic Study of Atherosclerosis includes 6814 participants aged 45\u201384\u2009years free of cardiovascular disease. Prevalence ratio (PR) regression was used to model baseline lipid lowering medication (LLM) or anti\u2010hypertensive medication use at baseline as a function of gender, race, risk factors, and estimated pre\u2010treatment biomarker values.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Hispanics and African Americans had lower prevalence of medication use than did non\u2010Hispanic whites, even at the same risk factor profile. This became non\u2010significant after adjusting for socioeconomic status. Although gender did not influence the prevalence of LLM use (\n                      <jats:italic>PR<\/jats:italic>\n                      \u2009=\u20091.09, 95%CI 0.95\u20131.25), there were differences in the association of diabetes and HDL with LLM use by gender. Men were significantly less likely to be on anti\u2010hypertensive medications than women (\n                      <jats:italic>PR<\/jats:italic>\n                      \u2009=\u20090.86, 95%CI 0.80\u20130.92,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), and this was not explained by risk factors or socioeconomic status. Lack of health insurance strongly influenced medication use, controlling for risk factors and other markers of socioeconomic status.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Disparities exist in the treatment of cholesterol and hypertension. Hispanics and African Americans had less use of LLM; men had less use of anti\u2010hypertensives. Risk factors have differential associations with medication use depending on gender. Methods described in this paper can provide improved disparity estimation in observational cohort studies. Copyright \u00a9 2013 John Wiley &amp; Sons, Ltd.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/pds.3406","type":"journal-article","created":{"date-parts":[[2013,2,4]],"date-time":"2013-02-04T11:20:27Z","timestamp":1359976827000},"page":"533-541","source":"Crossref","is-referenced-by-count":10,"title":["Methods for estimation of disparities in medication use in an observational cohort study: results from the Multi\u2010Ethnic Study of Atherosclerosis"],"prefix":"10.1002","volume":"22","author":[{"given":"Robyn L.","family":"McClelland","sequence":"first","affiliation":[{"name":"Department of Biostatistics University of Washington  Seattle WA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neal W.","family":"Jorgensen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics University of Washington  Seattle WA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wendy S.","family":"Post","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Medicine Johns Hopkins University School of Medicine  Baltimore MD USA"},{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University  Baltimore MD USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moyses","family":"Szklo","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University  Baltimore MD USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard A.","family":"Kronmal","sequence":"additional","affiliation":[{"name":"Department of Biostatistics University of Washington  Seattle WA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2013,2,4]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11883-006-0062-4"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.1974"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.105.552737"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijcard.2008.11.033"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1001\/archinte.162.8.929"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1345\/aph.1L181"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1001\/archinte.164.12.1313"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3341"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwf113"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1093\/clinchem\/18.6.499"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19990330)18:6<681::AID-SIM71>3.0.CO;2-R"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1177\/1536867X0400400301"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1177\/1536867X0500500404"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/9780470316696"},{"key":"e_1_2_8_16_1","first-page":"459","article-title":"Managing cardiovascular risk in minority patients","volume":"97","author":"Ferdinand KC","year":"2005","journal-title":"Journal of the National Medication Association."},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1161\/01.CIR.0000085994.38132.E5"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1161\/HYPERTENSIONAHA.108.113357"}],"container-title":["Pharmacoepidemiology and Drug Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fpds.3406","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/pds.3406","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T19:24:38Z","timestamp":1696879478000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/pds.3406"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,2,4]]},"references-count":17,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2013,5]]}},"alternative-id":["10.1002\/pds.3406"],"URL":"https:\/\/doi.org\/10.1002\/pds.3406","archive":["Portico"],"relation":{},"ISSN":["1053-8569","1099-1557"],"issn-type":[{"value":"1053-8569","type":"print"},{"value":"1099-1557","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,2,4]]}}}