{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T01:37:55Z","timestamp":1750815475971,"version":"3.37.3"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2024,7,14]],"date-time":"2024-07-14T00:00:00Z","timestamp":1720915200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1 OT2 OD026549","1 OT2 OD026554","1 OT2 OD026557","1 OT2 OD026556","1 OT2 OD026550","1 OT2 OD 026552","1 OT2 OD026553","1 OT2 OD026548","1 OT2 OD026551","1 OT2 OD026555"],"award-info":[{"award-number":["1 OT2 OD026549","1 OT2 OD026554","1 OT2 OD026557","1 OT2 OD026556","1 OT2 OD026550","1 OT2 OD 026552","1 OT2 OD026553","1 OT2 OD026548","1 OT2 OD026551","1 OT2 OD026555"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Federally Qualified Health Centers","award":["HHSN 263201600085U"],"award-info":[{"award-number":["HHSN 263201600085U"]}]},{"name":"Data and Research Center","award":["5 U2C OD023196","1 U24 OD023121"],"award-info":[{"award-number":["5 U2C OD023196","1 U24 OD023121"]}]},{"name":"The Participant Center","award":["U24 OD023176"],"award-info":[{"award-number":["U24 OD023176"]}]},{"name":"Participant Technology Systems Center","award":["1 U24 OD023163"],"award-info":[{"award-number":["1 U24 OD023163"]}]},{"name":"Communications and Engagement","award":["3 OT2 OD023205","3 OT2 OD023206"],"award-info":[{"award-number":["3 OT2 OD023205","3 OT2 OD023206"]}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01LM013344","R01AG065330","UL1TR001445"],"award-info":[{"award-number":["R01LM013344","R01AG065330","UL1TR001445"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>We introduce a widely applicable model-based approach for estimating individual-level Social Determinants of Health (SDoH) and evaluate its effectiveness using the All of Us Research Program.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>Our approach utilizes aggregated SDoH datasets to estimate individual-level SDoH, demonstrated with examples of no high school diploma (NOHSDP) and no health insurance (UNINSUR) variables. Models are estimated using American Community Survey data and applied to derive individual-level estimates for All of Us participants. We assess concordance between model-based SDoH estimates and self-reported SDoHs in All of Us\u00a0and examine associations with undiagnosed hypertension and diabetes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Compared to self-reported SDoHs, the area under the curve for NOHSDP is 0.727 (95% CI, 0.724-0.730) and for UNINSUR is 0.730 (95% CI, 0.727-0.733) among the 329\u00a0074 All of Us participants, both significantly higher than aggregated SDoHs. The association between model-based NOHSDP and undiagnosed hypertension is concordant with those estimated using self-reported NOHSDP, with a correlation coefficient of 0.649. Similarly, the association between model-based NOHSDP and undiagnosed diabetes is concordant with those estimated using self-reported NOHSDP, with a correlation coefficient of 0.900.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion and Conclusion<\/jats:title>\n                  <jats:p>The model-based SDoH estimation method offers a scalable and easily standardized approach for estimating individual-level SDoHs. Using the All of Us dataset, we demonstrate reasonable concordance between model-based SDoH estimates and self-reported SDoHs, along with consistent associations with health outcomes. Our findings also underscore the critical role of geographic contexts in SDoH estimation and in evaluating the association between SDoHs and health outcomes.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocae168","type":"journal-article","created":{"date-parts":[[2024,7,14]],"date-time":"2024-07-14T12:10:27Z","timestamp":1720959027000},"page":"2880-2889","source":"Crossref","is-referenced-by-count":2,"title":["Model-based estimation of individual-level social determinants of health and its applications in <i>All of Us<\/i>"],"prefix":"10.1093","volume":"31","author":[{"given":"Bo Young","family":"Kim","sequence":"first","affiliation":[{"name":"Division of Biostatistics, Department of Population Health, NYU Grossman School of Medicine , New York, NY 10016,","place":["United 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