Pre-pregnancy Body Mass Index and Adverse Pregnancy Outcomes: A Cross-Sectional Analysis Followed by Mendelian Randomization Study

Pre-pregnancy Body Mass Index and Adverse Pregnancy Outcomes: A Cross-Sectional Analysis Followed by Mendelian Randomization Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pre-pregnancy Body Mass Index and Adverse Pregnancy Outcomes: A Cross-Sectional Analysis Followed by Mendelian Randomization Study xindong Zhu, Chun-ming Jiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8723004/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Pre-pregnancy body mass index (BMI) is closely associated with a wide range of pregnancy outcomes, yet controversies persist, and large-scale causal evidence remains limited. Methods To address this, we conducted a retrospective cohort study using U.S. National Vital Statistics System (NVSS) birth data (2015–2024). Logistic regression was used for binary outcomes (gestational diabetes mellitus [GDM], hypertensive disorders of pregnancy [HDP], eclampsia, preterm birth), and linear regression for continuous outcomes (birth weight), calculating effect estimates with 95% confidence intervals (CIs). A multivariable-adjusted restricted cubic spline model explored nonlinearity, with threshold effects analyzed by two-piecewise linear regression. Finally, two-sample Mendelian randomization (MR) was performed to infer causality. Results This study included 31,209,649 participants. Compared to the underweight group, higher pre-pregnancy BMI was associated with increased risks of most adverse outcomes. A J-shaped association was observed between pre-pregnancy BMI and preterm birth risk: the risk decreased across the lower BMI range(OR = 0.965, 95% CI: 0.956–0.974, P < 0.001) but increased beyond an inflection point(OR = 1.027, 95% CI: 1.015–1.039, P < 0.01). For other outcomes, pre-pregnancy BMI showed positive linear correlations. MR analysis provided genetic evidence supporting a causal role.Sensitivity analyses supported the robustness of these findings. Conclusion Pre-pregnancy BMI exhibited a complex, non-linear relationship with preterm birth and significant positive correlations with GDM, HDP, and birth weight. The Mendelian randomization analysis strengthens the evidence for potential causal relationships, highlighting the importance of pre-pregnancy weight management. Full Text Additional Declarations No competing interests reported. Supplementary Files supplementaryFigure1A5D.docx SupplementaryTableS1S6.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 15 Feb, 2026 Reviewers agreed at journal 15 Feb, 2026 Reviewers invited by journal 05 Feb, 2026 Editor assigned by journal 31 Jan, 2026 Submission checks completed at journal 31 Jan, 2026 First submitted to journal 28 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8723004","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":586691553,"identity":"48f24606-8e40-4e0d-8af0-db1db214f0e6","order_by":0,"name":"xindong Zhu","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"xindong","middleName":"","lastName":"Zhu","suffix":""},{"id":586691554,"identity":"a2b9b737-2463-4d46-8c44-4072e57732b6","order_by":1,"name":"Chun-ming Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABZklEQVRIie2RP0vDQBiH3xCwy0E2Sei/r3ASqEvRr+IR0KVCJ+lQMEchWVq6Vir6FepSdTLhoC6BroF2SJZMHVpQSaGgubM1tUhnhzzD3Y+7e+7euwPIyPiHSC3ROTyaAI1NqH/POmIGzvYongjUBMxHZfhLWeOsN7BEkPYqsi1H4VtzSh4PmRW+301L5X7LDmIMpKuMHSf2qqDkahiWT2lhB8d6YRSR5z6x9eIw0vHUpbSdKDc9A9y2fw5ae4aljrd1l0peMxkZTIiV14ZJUAk1EYbLgZ8UhuYMsF/DsmSlSu5jS7ll5L5HKF0lysuYgbuaf8LproIq2mKtiGD6hLbEKWAAQ74DWN1VrvIwYro4hQd+l34Bq9c938Cs4BlI9aK62/lRjrqvQy1usuJgchHxkLyYHSxmjaqudN0wnI1OSoptPATLVEn+T0abFxdBhbTloK2P45R5cfGmyvj34oyMjIwMwRclTZ26o8YZZQAAAABJRU5ErkJggg==","orcid":"","institution":"Hangzhou First People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Chun-ming","middleName":"","lastName":"Jiang","suffix":""}],"badges":[],"createdAt":"2026-01-28 15:54:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8723004/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8723004/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102403615,"identity":"0975a7cc-fb19-41f7-9d05-58f33533bd93","added_by":"auto","created_at":"2026-02-11 10:47:11","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":725224,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptfile.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8723004/v1_covered_4d00f1a7-2750-4782-8d19-df2baa7f6882.pdf"},{"id":102401045,"identity":"e9962409-4185-4222-9644-9a29904ef057","added_by":"auto","created_at":"2026-02-11 10:41:40","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2327598,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryFigure1A5D.docx","url":"https://assets-eu.researchsquare.com/files/rs-8723004/v1/2810e8521aa89851bed4e9a5.docx"},{"id":102402317,"identity":"628533ab-4e1e-44fa-82c5-c6198e61c492","added_by":"auto","created_at":"2026-02-11 10:44:34","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35476,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1S6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8723004/v1/6796850163e8894aef936458.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pre-pregnancy Body Mass Index and Adverse Pregnancy Outcomes: A Cross-Sectional Analysis Followed by Mendelian Randomization Study","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8723004/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8723004/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePre-pregnancy body mass index (BMI) is closely associated with a wide range of pregnancy outcomes, yet controversies persist, and large-scale causal evidence remains limited.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eTo address this, we conducted a retrospective cohort study using U.S. National Vital Statistics System (NVSS) birth data (2015\u0026ndash;2024). Logistic regression was used for binary outcomes (gestational diabetes mellitus [GDM], hypertensive disorders of pregnancy [HDP], eclampsia, preterm birth), and linear regression for continuous outcomes (birth weight), calculating effect estimates with 95% confidence intervals (CIs). A multivariable-adjusted restricted cubic spline model explored nonlinearity, with threshold effects analyzed by two-piecewise linear regression. Finally, two-sample Mendelian randomization (MR) was performed to infer causality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThis study included 31,209,649 participants. Compared to the underweight group, higher pre-pregnancy BMI was associated with increased risks of most adverse outcomes. A J-shaped association was observed between pre-pregnancy BMI and preterm birth risk: the risk decreased across the lower BMI range(OR\u0026thinsp;=\u0026thinsp;0.965, 95% CI: 0.956\u0026ndash;0.974, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but increased beyond an inflection point(OR\u0026thinsp;=\u0026thinsp;1.027, 95% CI: 1.015\u0026ndash;1.039, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). For other outcomes, pre-pregnancy BMI showed positive linear correlations. MR analysis provided genetic evidence supporting a causal role.Sensitivity analyses supported the robustness of these findings.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePre-pregnancy BMI exhibited a complex, non-linear relationship with preterm birth and significant positive correlations with GDM, HDP, and birth weight. The Mendelian randomization analysis strengthens the evidence for potential causal relationships, highlighting the importance of pre-pregnancy weight management.\u003c/p\u003e","manuscriptTitle":"Pre-pregnancy Body Mass Index and Adverse Pregnancy Outcomes: A Cross-Sectional Analysis Followed by Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 10:27:39","doi":"10.21203/rs.3.rs-8723004/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-15T12:24:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"161663264540388402258726446645350469634","date":"2026-02-15T12:09:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-06T03:43:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-31T08:34:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-31T08:30:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2026-01-28T14:55:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"275863a0-101e-477d-8f74-9abf6802629e","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-11T10:27:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 10:27:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8723004","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8723004","identity":"rs-8723004","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}