{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T17:56:03Z","timestamp":1785520563280,"version":"3.56.0"},"reference-count":51,"publisher":"The Endocrine Society","issue":"11","funder":[{"name":"Intramural Research Program of the National Institutes of Health"},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["ZIAES09013"],"award-info":[{"award-number":["ZIAES09013"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"name":"American Recovery and Reinvestment Act"},{"name":"National Institutes of Health research"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Fibroids are hormonally dependent uterine tumors. The literature on adiposity and fibroid prevalence is inconsistent. Previous work usually combined all those with a body mass index (BMI) \u226530\u2005kg\/m2 into a single category and relied on clinically diagnosed fibroids, which misclassifies the many women with undiagnosed fibroids. We used a prospective cohort design with periodic ultrasound screening to investigate associations between repeated measures of BMI and fibroid incidence and growth assessed at each follow-up ultrasound.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>The Study of Environment, Lifestyle &amp; Fibroids followed 1693 Black\/African American women, ages 23 to 35 years from Detroit, Michigan, with ultrasound every 20 months for 5 years. Measured height and repeated weight measures were used to calculate BMI. Fibroid incidence was modeled using Cox models among those who were fibroid free at the enrollment ultrasound. Fibroid growth was estimated for individual fibroids matched across visits as the difference in log-volume between visits and was modeled using linear mixed models. All models used time-varying BMI and adjusted for time-varying covariates.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Compared with BMI &amp;lt;25\u2005kg\/m2, those with BMI 30 to &amp;lt;35\u2005kg\/m2 had increased fibroid incidence (adjusted hazard ratio, 1.37; 95% CI, 0.96-1.94), those with BMI \u226540\u2005kg\/m2 had reduced incidence (adjusted hazard ratio, 0.61; 95% CI, 0.41-0.90). Fibroid growth had mostly small magnitude associations with BMI.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>BMI has a nonlinear association with fibroid incidence, which could be driven by effects of BMI on inflammation and reproductive hormones. More detailed measures of visceral and subcutaneous adiposity and their effects on hormones, DNA damage, and cell death are needed.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1210\/clinem\/dgae036","type":"journal-article","created":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T08:19:58Z","timestamp":1706775598000},"page":"e2016-e2023","source":"Crossref","is-referenced-by-count":13,"title":["Body Mass Index and Uterine Fibroid Development: A Prospective Study"],"prefix":"10.1210","volume":"109","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5866-848X","authenticated-orcid":false,"given":"Quaker E","family":"Harmon","sequence":"first","affiliation":[{"name":"Epidemiology Branch, National Institute of Environmental Health Sciences , Durham, NC 27709 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stacy","family":"Patchel","sequence":"additional","affiliation":[{"name":"Westat, Public Health Practice , Durham, NC 27713 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