{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,18]],"date-time":"2025-10-18T11:00:11Z","timestamp":1760785211961,"version":"3.33.0"},"reference-count":33,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T00:00:00Z","timestamp":1736726400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tianjin Key Medical Discipline(Specialty) Construction Project","award":["TJYXZDXK-032A"],"award-info":[{"award-number":["TJYXZDXK-032A"]}]}],"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>Diagnosis and intervention of prediabetes is an emerging approach to preventing the progression and complications of diabetes. Inflammatory factors and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis have been suggested as potential mechanisms underlying the pathogenesis of both diabetes and depression. However, the relationship between depression levels and the prevalence of prediabetes and its prognosis remains elusive. This study aimed to explore the relationship between depression and the prevalence of prediabetes and to further explore the all-cause mortality of different levels of depression in patients with prediabetes.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>Our study used a data set from the National Health and Nutrition Examination Survey (NHANES). Participants were initially divided into two groups (depression vs. non-depression) and further stratified by different depression severity levels. We used a weighted multiple logistic regression model to analyze the association between depression and prediabetes prevalence and a Cox regression model to assess all-cause mortality in prediabetic patients.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>A total of 4384 participants were included, divided into depression group (n = 1379) and non-depression group (n = 3005). Results showed that people with depression were at higher risk of developing prediabetes. After adjusting for covariates, moderate to severe depression was positively associated with prediabetes (moderate to severe depression vs no depression: OR = 1.834, 95%CI: 0.713\u20134.721; severe depression vs no depression: OR = 1.004, 95% CI 0.429\u20132.351). In addition, we explored the relationship between all-cause mortality and depressive status in patients diagnosed with prediabetes (n = 2240) and found that moderate to severe depression (HR = 2.109, 95%CI 0.952\u20134.670) was associated with higher mortality in patients with prediabetes.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>Overall, the findings consistently suggest that depression is positively associated with both the prevalence and mortality risk among individuals with prediabetes. This suggests that depression may be a new and valuable indicator of prediabetes risk. Early treatment of depression improves outcomes in prediabetes.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0304303","type":"journal-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T18:47:52Z","timestamp":1736794072000},"page":"e0304303","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Association between depression and the prevalence and prognosis of prediabetes: Data from National Health and Nutrition Examination Survey (NHANES) 2013\u20132018"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7755-4501","authenticated-orcid":true,"given":"Jin","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojiao","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,1,13]]},"reference":[{"issue":"6","key":"pone.0304303.ref001","doi-asserted-by":"crossref","first-page":"e3642","DOI":"10.1002\/dmrr.3642","article-title":"Association of sleep patterns and cardiovascular disease risk is modified by glucose tolerance status","volume":"39","author":"B Wang","year":"2023","journal-title":"Diabetes Metab Res Rev"},{"issue":"4","key":"pone.0304303.ref002","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1097\/PSY.0000000000001298","article-title":"The Association of Multidimensional Sleep Health With HbA1c and Depressive Symptoms in African American Adults With Type 2 Diabetes","volume":"86","author":"J Woo","year":"2024","journal-title":"Psychosom Med"},{"issue":"1","key":"pone.0304303.ref003","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1186\/s12889-024-17996-y","article-title":"Prevalence of prediabetes and risk of CVD mortality in individuals with prediabetes alone or plus hypertension in Northeast China: insight from a population based cohort study","volume":"24","author":"L Yue","year":"2024","journal-title":"BMC Public Health"},{"issue":"1","key":"pone.0304303.ref004","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.pcd.2018.11.011","article-title":"Prediabetes Risk Evaluation Scoring System [PRESS]: A simplified scoring system for detecting undiagnosed Prediabetes","volume":"13","author":"R Rajput","year":"2019","journal-title":"Prim Care Diabetes"},{"key":"pone.0304303.ref005","doi-asserted-by":"crossref","first-page":"111022","DOI":"10.1016\/j.diabres.2023.111022","article-title":"Trends and risk factors of diabetes and prediabetes in US adolescents, 1999\u20132020","volume":"207","author":"A Ouyang","year":"2024","journal-title":"Diabetes Res Clin Pract"},{"issue":"Supple1","key":"pone.0304303.ref006","volume":"71","author":"E. 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