{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T00:13:57Z","timestamp":1706228037044},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684567","type":"print"},{"value":"9781643684574","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,25]]},"abstract":"<jats:p>Gestational diabetes and preterm birth are perinatal morbidities that significantly impact women and infants\u2019 health. While clinical factors like cesarean delivery, multiple gestation, preeclampsia, and hypertensive disorder are associated with these conditions, it is increasingly recognized that social determinants of health play a crucial role. This study aims to measure the associations between the social vulnerability index (SVI) and these perinatal morbidities using multivariate logistic regression models. The results indicate that factors across all four themes in SVI are significantly associated with these conditions. These findings suggest that interventions targeting these areas are needed to achieve better reproductive health.<\/jats:p>","DOI":"10.3233\/shti231177","type":"book-chapter","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:28:05Z","timestamp":1706178485000},"source":"Crossref","is-referenced-by-count":0,"title":["Discovering Social Determinant of Health Risk Factors for Perinatal Morbidity Through Real World Data"],"prefix":"10.3233","author":[{"given":"Cheng","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"You","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA"},{"name":"Department of Computer Science, Vanderbilt University, Nashville, TN, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2023 \u2014 The Future Is Accessible"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI231177","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:28:06Z","timestamp":1706178486000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI231177"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,25]]},"ISBN":["9781643684567","9781643684574"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti231177","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,25]]}}}