{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T11:34:12Z","timestamp":1793100852480,"version":"4.5.0"},"reference-count":18,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"5","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:sec>\n                    <jats:title\/>\n                    <jats:p>Many research findings are based on a nested subset of an original cohort followed over time, but results are rarely generalized back to the original population. Here, we conduct a \u201cproof of concept\u201d analysis demonstrating the application of simple methods to generalize the association between prepregnancy obesity and preeclampsia in women from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers to Be (nuMoM2b, target sample), using a subset of women whose follow-up was extended to 3 years postpartum in the Heart Health Study (nuMoM2b-HHS, source sample). We constructed inverse probability of selection weights and estimated three risk ratios for the association between obesity and preeclampsia: in the target nuMoM2b sample (N = 9,920), in the source nuMoM2b-HHS sample (N = 4,486), and in the weighted source nuMoM2b-HHS sample generalized back to the target sample using inverse probability of selection weights (pseudo N = 4,468). In the target, source, and weighted samples, the estimated risk ratios (95% confidence intervals) were 2.0 (1.7, 2.3), 2.2 (1.8, 2.6), and 2.0 (1.6, 2.4), respectively. We discuss the assumptions involved in generalizing study findings and methods available for doing so. When relevant, researchers should deploy methods for generalizing study nested cohort findings back to a target sample.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1097\/ede.0000000000002012","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T09:00:08Z","timestamp":1779699608000},"page":"578-581","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Generalizing Findings in Nested Cohorts"],"prefix":"10.1097","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1510-8175","authenticated-orcid":false,"given":"Ashley I.","family":"Naimi","sequence":"first","affiliation":[{"name":"Department of Epidemiology, Emory University, Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya-Hui","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Emory University, Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara M.","family":"Parisi","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisa M.","family":"Bodnar","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,5,25]]},"reference":[{"key":"R1-20261027","doi-asserted-by":"crossref","first-page":"539.e1","DOI":"10.1016\/j.ajog.2015.01.019","article-title":"A description of the methods of the nulliparous pregnancy outcomes study: monitoring mothers-to-be (nuMoM2b).","volume":"212","author":"Haas","year":"2015","journal-title":"Am J Obstet Gynecol"},{"key":"R2-20261027","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1093\/aje\/kwv309","article-title":"Pregnancy as a window to future cardiovascular health: design and implementation of the nuMoM2b heart health study.","volume":"183","author":"Haas","year":"2016","journal-title":"Am J Epidemiol"},{"key":"R3-20261027","first-page":"1122","article-title":"Hypertension in pregnancy. Report of the American college of obstetricians and gynecologists\u2019 task force on hypertension in pregnancy.","volume":"122","year":"2013","journal-title":"Obstet Gynecol"},{"key":"R4-20261027","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1097\/AOG.0000000000001805","article-title":"Association between sleep-disordered breathing and hypertensive disorders of pregnancy and gestational diabetes mellitus.","volume":"129","author":"Facco","year":"2017","journal-title":"Obstet Gynecol"},{"key":"R5-20261027","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1093\/aje\/kwaa044","article-title":"Estimating risk ratios and risk differences using regression.","volume":"189","author":"Naimi","year":"2020","journal-title":"Am J Epidemiol"},{"key":"R6-20261027","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1093\/aje\/kwq084","article-title":"Generalizing evidence from randomized clinical trials to target populations: the ACTG 320 trial.","volume":"172","author":"Cole","year":"2010","journal-title":"Am J Epidemiol"},{"key":"R7-20261027","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1214\/14-STS486","article-title":"External validity: from do-calculus to transportability across populations.","volume":"29","author":"Pearl","year":"2014","journal-title":"Statist Sci"},{"key":"R8-20261027","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1093\/aje\/kwad041","article-title":"How choice of effect measure influences minimally sufficient adjustment sets for external validity.","volume":"192","author":"Webster-Clark","year":"2023","journal-title":"Am J Epidemiol"},{"key":"R9-20261027","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1093\/aje\/kwaa185","article-title":"Directed acyclic graphs, effect measure modification, and generalizability.","volume":"190","author":"Webster-Clark","year":"2021","journal-title":"Am J Epidemiol"},{"key":"R10-20261027","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1093\/aje\/kwae048","article-title":"Variable selection when estimating effects in external target populations.","volume":"193","author":"Webster-Clark","year":"2024","journal-title":"Am J Epidemiol"},{"key":"R11-20261027","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1002\/(SICI)1097-0258(20000515)19:9<1141::AID-SIM479>3.0.CO;2-F","article-title":"Bootstrap confidence intervals: when, which, what? 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