{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T09:47:55Z","timestamp":1774000075374,"version":"3.50.1"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T00:00:00Z","timestamp":1773964800000},"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. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Cardiovascular-kidney-metabolic (CKM) syndrome, a novel multisystem disorder, integrates interconnected risks across cardiovascular, renal, and metabolic systems. While lifestyle factors are known to influence each CKM component disease, their impact on the dynamic progression of CKM syndrome as a unified entity remains unclear, particularly across its longitudinal stages and clinical subtypes (4a\/4b).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The study included 308,657 United Kingdom Biobank participants in CKM stages 0\u20133 at baseline. Multi-state models were used to investigate the effects of composite and individual lifestyle scores (smoking, alcohol consumption, physical activity, diet, sleep duration, and sedentary time) on transitions to clinical stage and subsequent death. The relative contribution of each factor was quantified using quantile G-computation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>During a median follow-up of 13.71\u202fyears, 30,516 participants progressed to stage 4 and 22,280 deaths occurred. Each 1-point improvement in lifestyle score was associated with approximately a 15% lower risk of CKM progression. After refining stage 4 into subtypes, the strongest protective effect was observed in transition from baseline to stage 4b, with hazard ratios (HRs) of 0.57 [95% confidence interval (CI): 0.52\u20130.63] for the score 2\u20134 group and 0.35 (95% CI: 0.30\u20130.41) for the score 5\u20136 group, compared to score 0\u20131. Never smoking showed the greatest contribution overall (23.1\u201365.1%) across stage transitions, with the strongest risk reduction observed in the transition from stage 4a to death (HR\u202f=\u202f0.65, 95% CI: 0.60\u20130.70).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>A healthy lifestyle was associated with slower longitudinal CKM syndrome progression. These findings support stage-specific lifestyle strategies and early intervention, emphasizing smoking cessation as a key target to delay CKM progression and reduce premature death.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1782700","type":"journal-article","created":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T06:37:15Z","timestamp":1773988635000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Relative contributions of lifestyle factors to stage-specific progression and mortality in cardiovascular-kidney-metabolic syndrome: a prospective cohort study with multi-state models"],"prefix":"10.3389","volume":"14","author":[{"given":"Qi","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nian","family":"Duan","sequence":"additional","affiliation":[{"name":"Department of Day Surgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenrui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fenghuixue","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,3,20]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1093\/ndt\/gfy407","article-title":"SGLT-2 inhibitors and GLP-1 receptor agonists for nephroprotection and cardioprotection in patients with diabetes mellitus and chronic kidney disease. 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