{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T16:53:23Z","timestamp":1788454403754,"version":"build-2803163510"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T00:00:00Z","timestamp":1752105600000},"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. Nutr."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Cardiovascular disease is associated with inflammation and dysregulated lipid metabolism. This study aimed to investigate the predictive value of high-sensitive C-reactive protein to high-density lipoprotein cholesterol ratio (CHR) in assessing the risk of developing cardiometabolic multi-morbidity (CMM) within the Chinese population.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A cohort of 8,187 participants were selected from the China Health and Retirement Longitudinal Study (CHARLS) and divided into four groups based on the quartile of CHR. To evaluate the association between CHR and CMM, we employed multivariable Cox proportional hazards regression, logistic regression, and restricted cubic splines (RCS) analysis. Subgroup analyses and interaction tests were conducted to further explore these relationships.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The mean age of the included participants was 58.64\u202f\u00b1\u202f9.66\u202fyears, with 53.7% being female. Over a median follow-up period of 109\u202fmonths, 858 participants (10.5%) were diagnosed with new-onset CMM. The incidence of CMM across CHR quartiles Q1, Q2, Q3, and Q4 were 6.4, 9.4, 12.0, and 14.2%, respectively. Compared to the lowest quartile, the fully adjusted hazard ratio (with 95% confidence intervals) for CMM for quartiles Q2\u2013Q4 were 1.43 (1.14\u20131.79), 1.67 (1.35\u20132.07), and 1.91 (1.55\u20132.37), respectively. Per 0.01 unit increase in CHR correlates with a 38% increase in the risk of CMM (HR\u202f=\u202f1.38, 95% CI\u202f=\u202f1.08\u20131.77, <jats:italic>p<\/jats:italic>\u202f=\u202f0.01) after full adjustment. Additionally, the odds ratios (ORs) (95% CIs) using multivariate logistic regression analysis for participants in quartiles 2 to 4 were 1.47 (1.16\u20131.86), 1.73 (1.38\u20132.17), and 2.00 (1.59\u20132.51), respectively, when compared to participants in Q1 of CHR. Furthermore, a nonlinear relationship was observed between CHR and the risk of CMM (overall <jats:italic>p<\/jats:italic>\u202f&amp;lt;\u202f0.001, nonlinear <jats:italic>p<\/jats:italic>\u202f&amp;lt;\u202f0.001). Subgroup and sensitivity analyses corroborated the robustness of our findings.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>A higher CHR was positively associated with the risk of CMM. Our findings suggest that CHR, when considered alongside other risk factors, could serve as a valuable biomarker for identifying individuals at heightened risk of developing CMM.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnut.2025.1580904","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T04:12:03Z","timestamp":1752120723000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["The predictive value of hsCRP\/HDL-C ratio for cardiometabolic multimorbidity in middle-aged and elderly people: evidence from a large national cohort study"],"prefix":"10.3389","volume":"12","author":[{"given":"Shiyang","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuyong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangyan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deyun","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangming","family":"Mao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhao","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e277","DOI":"10.1016\/S0140-6736(17)30058-2","article-title":"Overweight, 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