{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T17:53:13Z","timestamp":1782323593719,"version":"3.54.5"},"reference-count":32,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["No. RS-2024-00440787"],"award-info":[{"award-number":["No. RS-2024-00440787"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["No. RS-2024-00354881"],"award-info":[{"award-number":["No. RS-2024-00354881"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Family history of diabetes mellitus (FH_ DM) is a well-established risk factor for diabetes, but most studies have focused on disease incidence rather than glycemic changes over time. Understanding how FH_ DM affects the magnitude of change in blood glucose biomarkers before clinical diagnosis can inform earlier intervention strategies and optimize screening intervals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed standardized health checkup data from Korean adults aged 20 years or older with repeated measurements over approximately 2-year (n\u2009=\u200925,647) and 4-year (n\u2009=\u200912,831) intervals. Using propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and doubly robust (DR) estimation, we estimated the average treatment effect of FH_ DM on changes in fasting blood glucose (FBG) and hemoglobin A1c (HbA1c). The analytic cohort included individuals with normoglycemia, prediabetes, and diabetes. Sensitivity analyses using robustness values assessed potential unmeasured confounding.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>After adjusting for 49 measured confounders, individuals with FH_ DM showed consistently greater glycemic progression than those without FH_ DM across all methods. Over 2 years, HbA1c showed a 0.02% greater increase (95% CI: 0.01\u20130.03) and FBG showed a 0.3 mg\/dL greater increase (95% CI: 0.1\u20130.6) in the FH_ DM group. Over 4 years, the difference in FBG change was 1.3\u20131.9 mg\/dL. Results remained robust when excluding individuals on diabetes medication and across sensitivity analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Family history of diabetes is independently associated with greater glycemic progression across the normoglycemia-to-diabetes spectrum, even after rigorous adjustment for confounding. These findings support the use of FH_ DM as a practical marker for risk-stratified screening strategies. Individuals with FH_ DM may benefit from more frequent glucose monitoring and earlier preventive interventions to delay or prevent diabetes onset.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0352348","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T17:42:25Z","timestamp":1782322945000},"page":"e0352348","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Family history of diabetes and glycemic progression: A propensity score-based analysis using health checkup data"],"prefix":"10.1371","volume":"21","author":[{"given":"Sangtaek","family":"Oh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seongtae","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaesuk","family":"Yun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jung Kee","family":"Min","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0811-3053","authenticated-orcid":true,"given":"Hee-Jung","family":"Jee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae-Young","family":"Heo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"issue":"7","key":"pone.0352348.ref001","doi-asserted-by":"crossref","first-page":"404","DOI":"10.5124\/jkma.2023.66.7.404","article-title":"Prevalence and treatment status of diabetes mellitus in Korea","volume":"66","author":"H-S Kwon","year":"2023","journal-title":"J Korean Med Assoc"},{"issue":"3","key":"pone.0352348.ref002","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/s11892-008-0033-y","article-title":"Genes and type 2 diabetes mellitus","volume":"8","author":"L Groop","year":"2008","journal-title":"Curr Diab Rep"},{"issue":"2","key":"pone.0352348.ref003","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/S0749-3797(02)00585-8","article-title":"Research priorities for evaluating family history in the prevention of common chronic diseases","volume":"24","author":"PW Yoon","year":"2003","journal-title":"Am J Prev Med"},{"key":"pone.0352348.ref004","article-title":"Family history, diabetes, and other demographic and risk factors among participants of the National Health and Nutrition Examination Survey 1999-2002","volume":"2","author":"AM Annis","year":"2002","journal-title":"Prev Chronic Dis"},{"key":"pone.0352348.ref005","doi-asserted-by":"crossref","first-page":"15","DOI":"10.3389\/fcell.2014.00015","article-title":"Epigenetics and type II diabetes mellitus: underlying mechanisms of prenatal predisposition","volume":"2","author":"JD Sterns","year":"2014","journal-title":"Front Cell Dev Biol"},{"issue":"1","key":"pone.0352348.ref006","doi-asserted-by":"crossref","first-page":"1220","DOI":"10.1186\/s12889-025-21404-4","article-title":"Risk factors for progression to type 2 diabetes in prediabetes: a systematic review and meta-analysis","volume":"25","author":"S Hu","year":"2025","journal-title":"BMC Public Health"},{"issue":"9833","key":"pone.0352348.ref007","doi-asserted-by":"crossref","first-page":"2279","DOI":"10.1016\/S0140-6736(12)60283-9","article-title":"Prediabetes: a high-risk state for diabetes development","volume":"379","author":"AG Tab\u00e1k","year":"2012","journal-title":"Lancet"},{"issue":"1","key":"pone.0352348.ref008","doi-asserted-by":"crossref","first-page":"63","DOI":"10.21032\/jhis.2017.42.1.63","article-title":"Impaired Fasting Glucose Rate by Diabetes Family History","volume":"42","author":"E-H Kim","year":"2017","journal-title":"J Health Info Stat"},{"issue":"2","key":"pone.0352348.ref009","article-title":"Association between family history risk categories and prevalence of diabetes in Chinese population","volume":"10","author":"J Zhang","year":"2015","journal-title":"PLoS One"},{"issue":"6","key":"pone.0352348.ref010","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0324696","article-title":"Effects of family history and sex on diabetes-related outcome in type 2 diabetes - Analysis from the tyrolean diabetes registry","volume":"20","author":"C Plattner","year":"2025","journal-title":"PLoS One"},{"issue":"1","key":"pone.0352348.ref011","doi-asserted-by":"crossref","first-page":"2145644","DOI":"10.1080\/08839514.2022.2145644","article-title":"Artificial intelligence-based prediction of diabetes and prediabetes using health checkup data in Korea","volume":"36","author":"H Yuk","year":"2022","journal-title":"Appl Artif Intell"},{"issue":"7","key":"pone.0352348.ref012","article-title":"Estimating the cost of type 1 diabetes in the U.S.: a propensity score matching method","volume":"5","author":"B Tao","year":"2010","journal-title":"PLoS One"},{"issue":"396","key":"pone.0352348.ref013","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1080\/01621459.1986.10478354","article-title":"Statistics and causal inference","volume":"81","author":"PW Holland","year":"1986","journal-title":"J Am Stat Assoc"},{"issue":"3","key":"pone.0352348.ref014","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1111\/2041-210X.13111","article-title":"Using propensity scores for causal inference in ecology: Options, considerations, and a case study","volume":"10","author":"DSL Ramsey","year":"2019","journal-title":"Methods Ecol Evol"},{"key":"pone.0352348.ref015","volume-title":"Counterfactuals and Causal Inference","author":"S Morgan","year":"2015"},{"issue":"3","key":"pone.0352348.ref016","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1080\/00273171.2011.568786","article-title":"An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies","volume":"46","author":"PC Austin","year":"2011","journal-title":"Multivariate Behav Res"},{"issue":"1","key":"pone.0352348.ref017","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1093\/biomet\/70.1.41","article-title":"The central role of the propensity score in observational studies for causal effects","volume":"70","author":"PR ROSENBAUM","year":"1983","journal-title":"Biometrika"},{"issue":"3","key":"pone.0352348.ref018","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1177\/0962280210394483","article-title":"Propensity scores: from naive enthusiasm to intuitive understanding","volume":"21","author":"E Williamson","year":"2012","journal-title":"Stat Methods Med Res"},{"issue":"8","key":"pone.0352348.ref019","doi-asserted-by":"crossref","first-page":"457","DOI":"10.2188\/jea.JE20210145","article-title":"Using Propensity Scores for Causal Inference: Pitfalls and Tips","volume":"31","author":"K Shiba","year":"2021","journal-title":"J Epidemiol"},{"issue":"1","key":"pone.0352348.ref020","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1080\/00031305.1985.10479383","article-title":"Constructing a control group using multivariate matched sampling methods that incorporate the propensity score","volume":"39","author":"PR Rosenbaum","year":"1985","journal-title":"Am Stat"},{"issue":"6","key":"pone.0352348.ref021","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1002\/sim.6004","article-title":"A comparison of 12 algorithms for matching on the propensity score","volume":"33","author":"PC Austin","year":"2014","journal-title":"Stat Med"},{"key":"pone.0352348.ref022","doi-asserted-by":"crossref","first-page":"1393","DOI":"10.1016\/0270-0255(86)90088-6","article-title":"A new approach to causal inference in mortality studies with a sustained exposure period\u2014application to control of the healthy worker survivor effect","volume":"7","author":"J Robins","year":"1986","journal-title":"Math Model"},{"issue":"1","key":"pone.0352348.ref023","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1093\/ckj\/sfab158","article-title":"An introduction to inverse probability of treatment weighting in observational research","volume":"15","author":"NC Chesnaye","year":"2021","journal-title":"Clin Kidney J"},{"key":"pone.0352348.ref024","volume-title":"Causal Inference: What If","author":"MA Hern\u00e1n","year":"2020"},{"key":"pone.0352348.ref025","unstructured":"Facure M. Causal Inference for the Brave and True [Internet]. 2023 [cited 2025 January 15]. Available from: https:\/\/matheusfacure.github.io\/python-causality-handbook\/landing-page.html"},{"issue":"4","key":"pone.0352348.ref026","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1111\/j.1541-0420.2005.00377.x","article-title":"Doubly robust estimation in missing data and causal inference models","volume":"61","author":"H Bang","year":"2005","journal-title":"Biometrics"},{"issue":"25","key":"pone.0352348.ref027","doi-asserted-by":"crossref","first-page":"3083","DOI":"10.1002\/sim.3697","article-title":"Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples","volume":"28","author":"PC Austin","year":"2009","journal-title":"Stat Med"},{"issue":"5","key":"pone.0352348.ref028","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1111\/resp.12312","article-title":"Introduction to propensity scores","volume":"19","author":"EJ Williamson","year":"2014","journal-title":"Respirology"},{"issue":"1","key":"pone.0352348.ref029","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1111\/rssb.12348","article-title":"Making Sense of Sensitivity: Extending Omitted Variable Bias","volume":"82","author":"C Cinelli","year":"2020","journal-title":"J R Stat Soc Series B Stat Methodol"},{"issue":"10","key":"pone.0352348.ref030","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1001\/archinte.167.10.1068","article-title":"Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study","volume":"167","author":"PWF Wilson","year":"2007","journal-title":"Arch Intern Med"},{"issue":"11","key":"pone.0352348.ref031","doi-asserted-by":"crossref","first-page":"2732","DOI":"10.2337\/db10-0768","article-title":"Diabetes family history: a metabolic storm you should not sit out","volume":"59","author":"PW Franks","year":"2010","journal-title":"Diabetes"},{"issue":"1","key":"pone.0352348.ref032","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1007\/s12020-023-03642-x","article-title":"Mechanisms and risk factors of metabolic syndrome in children and adolescents","volume":"84","author":"V Codazzi","year":"2024","journal-title":"Endocrine"}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0352348","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T17:42:36Z","timestamp":1782322956000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0352348"}},"subtitle":[],"editor":[{"given":"Hidetaka","family":"Hamasaki","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,6,24]]},"references-count":32,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,6,24]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0352348","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,24]]}}}