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Background <p>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.</p> Methods <p>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.</p> Results <p>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 (<i>P</i> <sub>for interaction</sub> = 0.002). Restricted cubic spline analysis revealed a significant nonlinear association for all-cause mortality (<i>P</i> <sub>for nonlinear</sub> &lt; 0.001), but not for CVD mortality (<i>P</i> <sub>for nonlinear</sub> = 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.</p> Conclusions <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月21日

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

摘要

Background

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.

Methods

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.

Results

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.

Conclusions

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.