{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T14:33:50Z","timestamp":1784039630565,"version":"3.55.0"},"reference-count":33,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"vor","delay-in-days":23,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["ift.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Food Science"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:label\/>\n                    <jats:p>The role of gut microbiota\u2010modulating diets in cardiovascular\u2010kidney\u2010metabolic (CKM) syndrome progression is poorly understood. This study investigated associations between the dietary index for gut microbiota (DI\u2010GM) and advanced CKM risk, with a focus on inflammatory mediation.<\/jats:p>\n                    <jats:p>Cross\u2010sectional data from 12,068 NHANES participants (2007\u20132020) were analyzed. Advanced CKM stages (3\u20134) were classified using American Heart Association (AHA) criteria. DI\u2010GM scores were derived from 14 dietary components, and inflammatory biomarkers (e.g., dietary inflammatory index [DII], neutrophil to lymphocyte ratio [NLR], systemic inflammation response index [SIRI]) were assessed. Multivariable logistic regression, mediation analysis, and machine learning (XGBoost, SHAP) evaluated associations and predictive performance.<\/jats:p>\n                    <jats:p>High DI\u2010GM adherence (\u22656) was associated with a 25% reduction in advanced CKM risk, while each unit increase was associated with a 7% lower risk. Inflammatory biomarkers mediated 42.88% (DII) to 5.59% (neutrophils) of this association. XGBoost identified coffee, refined grains, and fat as top risk predictors.<\/jats:p>\n                    <jats:p>This cross\u2010sectional study underscores the protective role of DI\u2010GM against CKM progression, mediated substantially by inflammation suppression. While these results highlight promising associations, the cross\u2010sectional design necessitates caution in inferring causality. Machine learning underscores the importance of dietary synergy over isolated components, advocating for integrated dietary\u2010microbiota interventions in precision CKM management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Practical Applications<\/jats:title>\n                    <jats:p>What is currently known about this topic? Cardiovascular\u2010kidney\u2010metabolic (CKM) syndrome, formally defined in 2023, affects over 25% of US adults, yet evidence linking gut microbiota\u2010targeted dietary patterns to advanced CKM risk remains limited.<\/jats:p>\n                    <jats:p>What is the key research question? Higher dietary index for gut microbiota (DI\u2010GM) scores\u2014characterized by fiber\u2010rich, fermented, and plant\u2010based components\u2014are inversely associated with advanced CKM risk, particularly in males sedentary and hypertension subgroups.<\/jats:p>\n                    <jats:p>How might this study influence clinical practice? Inflammatory biomarkers mediate 42.88% of the association between DI\u2010GM and CKM progression, with machine learning identifying coffee, refined grains, and dietary fat as key contributors to risk stratification, supporting microbiota\u2010driven precision nutrition strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/1750-3841.70634","type":"journal-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T05:26:27Z","timestamp":1761369987000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Gut Microbiota\u2010Modulating Diets Attenuate Cardiovascular\u2010Kidney\u2010Metabolic Syndrome via Inflammatory Mediation: Insights From NHANES and Machine Learning Model"],"prefix":"10.1111","volume":"90","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2988-9021","authenticated-orcid":false,"given":"Zhaoqi","family":"Yan","sequence":"first","affiliation":[{"name":"Guang'anmen Hospital, China Academy of Chinese Medical Sciences Beijing China"},{"name":"Department of Rehabilitation Medicine The Third Hospital of Nanchang, Nanchang People's Hospital Nanchang Jiangxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifeng","family":"Xu","sequence":"additional","affiliation":[{"name":"Guang'anmen Hospital, China Academy of Chinese Medical Sciences Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiufan","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Medicine The Third Hospital of Nanchang, Nanchang People's Hospital Nanchang Jiangxi 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