{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T16:56:21Z","timestamp":1790614581586,"version":"4.1.0"},"reference-count":36,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"2","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["JAHA"],"published-print":{"date-parts":[[2025,1,21]]},"abstract":"<jats:sec xml:lang=\"en\">\n            <jats:title>Background<\/jats:title>\n            <jats:p xml:lang=\"en\">Hypertension control and related cardiovascular outcomes among Americans remain suboptimal, and differ by race, ethnicity, and geography. Healthcare access is one of multiple critical factors in hypertension control. Understanding the degree to which healthcare access, versus other factors, produce these outcomes can inform policies and interventions to improve cardiovascular outcomes and reduce disparities. Department of Veterans Affairs Healthcare System data provide a unique opportunity to understand residual racial and ethnic differences in hypertension control after accounting for healthcare access. Our objective was to describe pre\u2010pandemic post\u2010Affordable Care Act implementation hypertension control by geographic sector and race and ethnicity, and assess spatial clustering of hypertension control.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results<\/jats:title>\n            <jats:p xml:lang=\"en\">A secondary data analysis of hypertension control among US veterans (n=1\u2009619\u2009414) nationwide and in 4 US territories was conducted using electronic health record data. Age\u2010 and sex\u2010adjusted regression models estimated overall and race\u2010 and ethnicity\u2010specific rates by geographic sector. We created choropleth maps of hypertension control rates and assessed spatial autocorrelation. Hypertension control rates varied across sectors by race and ethnicity (range, 44.1%\u201397.5%); Black veterans, followed by American Indian or Alaska Native veterans, had the lowest mean control rates (72.5% and 75.4%, respectively). There was clustering of low hypertension control rates for Black veterans in the Pacific Northwest, Southwest, Missouri, Kansas, and Arkansas, and for American Indian or Alaska Native veterans in the West and Southwest.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p xml:lang=\"en\">Hypertension control rates varied geographically for veteran groups experiencing racial and ethnic disparities. Geographic areas with concentrations of low rates of hypertension control should be a focus for interventions to address racial and ethnic disparities.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/jaha.123.035682","type":"journal-article","created":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T11:19:37Z","timestamp":1736507977000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":9,"title":["Variation in Hypertension Control by Race and Ethnicity, and Geography in US Veterans"],"prefix":"10.1161","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8850-1576","authenticated-orcid":false,"given":"Kimberly E.","family":"Lind","sequence":"first","affiliation":[{"name":"VA HSR Center for the Study of Healthcare Innovation, Implementation &amp; Policy (CSHIIP) VA Greater Los Angeles Healthcare System Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7917-9696","authenticated-orcid":false,"given":"Michelle S.","family":"Wong","sequence":"additional","affiliation":[{"name":"VA HSR Center for the Study of Healthcare Innovation, Implementation &amp; Policy (CSHIIP) VA Greater Los Angeles Healthcare System Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6613-2506","authenticated-orcid":false,"given":"Stephen E.","family":"Frochen","sequence":"additional","affiliation":[{"name":"VA HSR Center for the Study of Healthcare Innovation, Implementation &amp; Policy (CSHIIP) VA Greater Los Angeles Healthcare System Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anita H.","family":"Yuan","sequence":"additional","affiliation":[{"name":"VA HSR Center for the Study of Healthcare Innovation, Implementation &amp; Policy (CSHIIP) VA Greater Los Angeles Healthcare System Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donna L.","family":"Washington","sequence":"additional","affiliation":[{"name":"VA HSR Center for the Study of Healthcare Innovation, Implementation &amp; Policy (CSHIIP) VA Greater Los Angeles Healthcare System Los Angeles CA USA"},{"name":"Division of General Internal Medicine and Health Services Research, Department of Medicine UCLA David Geffen School of Medicine Los Angeles CA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2020.113439"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamahealthforum.2021.2375"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.14545"},{"key":"e_1_3_1_5_2","first-page":"2083","article-title":"Writing group of the PREMIER collaborative research group. 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