{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T15:52:24Z","timestamp":1753890744323,"version":"3.41.2"},"reference-count":80,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T00:00:00Z","timestamp":1740700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>This study investigates the subclasses of metabolic syndrome (Mets) and their relationship with non-alcoholic fatty liver (NAFLD) and the probable predictive role of serum vitamin D and CRP levels.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This community-based, cross-sectional study was performed on adults in the framework of the Amol cohort prospective study (AmolCPS). Mets was defined as Adult Treatment Panel III criteria (ATP III) and ultrasound was used to diagnose NAFLD. Anthropometric and blood pressure measurements were conducted, and biochemical measurements were assessed after fasting. Data analysis included Latent class analysis, two-tailed \u03c72 statistics, one-way analysis of variance, and logistic regression using Mplus (version 7.4) and spss (version 26) softwares.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The study involved 2308 participants, with a mean age of 43.17 \u00b1 12.30 years. Mets prevalence was 25.64%, with three identified classes: Mets with Hypertension (HTN), Mets without HTN (Non-HTN), and Low Risk. Mets with HTN had a high probability of at least four components, particularly high SBP. Non-HTN had at least three high probable components, especially high TG and low HDL but not high SBP and DBP. The low-risk class had a low probability of all components except low HDL in women. Serum vitamin D and CRP levels did not significantly predict Mets classes in men, while CRP level significantly predicted the HTN class in women (OR:1.03, CI:1.004-1.067). Both HTN, and Non-HTN Mets classes significantly increased the odds of NAFLD compared to the low risk class, especially in women (HTN class OR: 4.20 vs 2.94; non-HTN class OR: 5.60 vs 3.12 in women and men respectively).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The latent class analysis in northern Iran identified three Mets classes: HTN, Non-HTN, and low-risk, with hypertension playing a crucial role in determining these classes. These classes were stronger predictors of NAFLD in women. Serum CRP and vitamin D levels did not emerge as significant predictors of the classes, except for serum CRP in the HTN class among women.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fendo.2025.1405833","type":"journal-article","created":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T05:12:13Z","timestamp":1740719533000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The crucial role of hypertension in determining latent classes of metabolic syndrome in northern Iran and predictive power of these classes in non-alcoholic fatty liver: a gender-based insight"],"prefix":"10.3389","volume":"16","author":[{"given":"Bahareh","family":"Amirkalali","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parvin","family":"Hassanzadeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fatemeh","family":"Sheikholmolooki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Esmaeel","family":"Gholizadeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Azam","family":"Doustmohammadian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fahimeh","family":"Safarnezhad Tameshkel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nima","family":"Motamed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mansooreh","family":"Maadi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masoudreza","family":"Sohrabi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elham","family":"Sobhrakhshankhah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farhad","family":"Zamani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hossein","family":"Ajdarkosh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,2,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(09)61794-3","article-title":"The metabolic syndrome","volume":"375","author":"Eckel","year":"2010","journal-title":"Lancet"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diabres.2014.04.006","article-title":"Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes","volume":"105","author":"Esser","year":"2014","journal-title":"Diabetes Res Clin Pract"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1038\/oby.2010.291","article-title":"Associations of visceral and liver fat with the metabolic syndrome across the spectrum of obesity: the AGES-Reykjavik study","volume":"19","author":"Kim","year":"2011","journal-title":"Obesity"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1177\/2047487314525529","article-title":"Metabolic syndrome across Europe: different clusters of risk factors","volume":"22","author":"Scuteri","year":"2015","journal-title":"Eur J Prev Cardiol"},{"key":"B5","doi-asserted-by":"publisher","first-page":"e0192372","DOI":"10.1371\/journal.pone.0192372","article-title":"Prevalence of metabolic syndrome and its risk factors in Kerala, South India: Analysis of a community based cross-sectional study","volume":"13","author":"Harikrishnan","year":"2018","journal-title":"PloS One"},{"key":"B6","doi-asserted-by":"publisher","first-page":"170","DOI":"10.4103\/2230-8229.142971","article-title":"Metabolic syndrome: Risk factors among adults in Kingdom of Saudi Arabia","volume":"21","author":"Aljohani","year":"2014","journal-title":"J Family Community Med"},{"key":"B7","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1007\/s11906-018-0812-z","article-title":"The global epidemic of the metabolic syndrome","volume":"20","author":"Saklayen","year":"2018","journal-title":"Curr Hypertens Rep"},{"key":"B8","article-title":"The prevalence of metabolic syndrome in Iran: A systematic review and meta-analysis","volume":"47","author":"Mazloomzadeh","year":"2018","journal-title":"Iran J Public Health"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.4103\/ijpvm.IJPVM_489_18","article-title":"Prevalence and incidence of metabolic syndrome in Iran: a systematic review and meta-analysis","volume":"11","author":"Fatahi","year":"2020","journal-title":"Int J Prev Med"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-S","article-title":"Definition, diagnosis and classification of diabetes mellitus and its complications. 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