Life’s Essential 8-Defined Cardiovascular Health and Mortality Risk in Cardiovascular-Kidney-Metabolic Health Stages 0–4: A Cohort Study

Cardiovascular-kidney-metabolic (CKM) syndrome represents a primary contributor to global morbidity and mortality. Despite the Life’s Essential 8 framework offering a comprehensive assessment of cardiovascular health (CVH), its prognostic utility in CKM syndrome remains unclear. This study aimed to investigate the association between Life’s Essential 8-defined CVH and mortality risk in CKM health stages 0–4. Data were analyzed from 302,171 UK Biobank participants in CKM health stages 0–4. CVH scores were calculated based on eight components: diet, physical activity, nicotine exposure, sleep health, body mass index, blood lipids, blood glucose, and blood pressure. All-cause and cardiovascular disease (CVD) mortality were ascertained through linked health records. Cox proportional hazards models were employed to examine associations between CVH scores and mortality risks. The predictive factors for mortality risk were explored using the gradient boosting machines method. Over a median follow-up of 12.7 years, 20,282 all-cause and 3,979 CVD deaths occurred. Compared with low CVH, high CVH was associated with 55% (95% confidence interval (CI): 0.42–0.49) and 67% (95% CI: 0.27–0.41) reductions in all-cause and CVD mortality. The inverse association of CVH scores with CVD mortality was stronger in non-advanced stages (P for interaction = 0.002). Restricted cubic spline analysis revealed a significant nonlinear association for all-cause mortality (P for nonlinear < 0.001), but not for CVD mortality (P for nonlinear = 0.936). Machine learning analysis indicated that among the eight components, nicotine exposure and blood glucose scores had the highest relative influence on mortality prediction. Higher CVH scores were associated with lower mortality risk in CKM health stages 0–4, with stronger associations observed in non-advanced stages. Among the eight components, nicotine exposure and blood glucose scores showed stable and strong associations with mortality. These findings support the potential value of CVH assessment for risk stratification across CKM health stages.

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Journal
Journal of Epidemiology and Global Health
Published
2026-05-21
DOI
https://doi.org/10.1007/s44197-026-00590-3
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
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article

Life’s Essential 8-Defined Cardiovascular Health and Mortality Risk in Cardiovascular-Kidney-Metabolic Health Stages 0–4: A Cohort Study

Qiqi You, Ruiyang Niu, Yanyan Jia, Shaoyong Xu et al.
Journal of Epidemiology and Global Health
Cardiovascular Health and Risk Factors
article

Life’s Essential 8-Defined Cardiovascular Health and Mortality Risk in Cardiovascular-Kidney-Metabolic Health Stages 0–4: A Cohort Study

Qiqi You, Ruiyang Niu, Yanyan Jia, Shaoyong Xu, Lingqi Wei, Xiaoying Li, Wan Fu, Xinyi Zhang, Jingjing Zeng
article en

Abstract

Cardiovascular-kidney-metabolic (CKM) syndrome represents a primary contributor to global morbidity and mortality. Despite the Life’s Essential 8 framework offering a comprehensive assessment of cardiovascular health (CVH), its prognostic utility in CKM syndrome remains unclear. This study aimed to investigate the association between Life’s Essential 8-defined CVH and mortality risk in CKM health stages 0–4. Data were analyzed from 302,171 UK Biobank participants in CKM health stages 0–4. CVH scores were calculated based on eight components: diet, physical activity, nicotine exposure, sleep health, body mass index, blood lipids, blood glucose, and blood pressure. All-cause and cardiovascular disease (CVD) mortality were ascertained through linked health records. Cox proportional hazards models were employed to examine associations between CVH scores and mortality risks. The predictive factors for mortality risk were explored using the gradient boosting machines method. Over a median follow-up of 12.7 years, 20,282 all-cause and 3,979 CVD deaths occurred. Compared with low CVH, high CVH was associated with 55% (95% confidence interval (CI): 0.42–0.49) and 67% (95% CI: 0.27–0.41) reductions in all-cause and CVD mortality. The inverse association of CVH scores with CVD mortality was stronger in non-advanced stages (P for interaction = 0.002). Restricted cubic spline analysis revealed a significant nonlinear association for all-cause mortality (P for nonlinear < 0.001), but not for CVD mortality (P for nonlinear = 0.936). Machine learning analysis indicated that among the eight components, nicotine exposure and blood glucose scores had the highest relative influence on mortality prediction. Higher CVH scores were associated with lower mortality risk in CKM health stages 0–4, with stronger associations observed in non-advanced stages. Among the eight components, nicotine exposure and blood glucose scores showed stable and strong associations with mortality. These findings support the potential value of CVH assessment for risk stratification across CKM health stages.

Journal of Epidemiology and Global Health
Hubei University of Arts and Science (CN), Xiangyang Central Hospital (CN), Wuhan University of Science and Technology (CN)
Good health and well-being
Openalex Percentile: Top 6%
Cardiovascular Health and Risk Factors
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