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. 2025 May 21:13:1508274.
doi: 10.3389/fpubh.2025.1508274. eCollection 2025.

Associations between Life's Essential Eight cardiovascular health metrics and cardiovascular mortality risk across frailty statuses: evidence from a UK Biobank cohort study

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Associations between Life's Essential Eight cardiovascular health metrics and cardiovascular mortality risk across frailty statuses: evidence from a UK Biobank cohort study

Lirong Chai et al. Front Public Health. .

Abstract

Background: Higher cardiovascular health (CVH) scores are related to lower risk of cardiovascular disease (CVD) mortality, and frailty status may moderate the association. Whether the associations of Life's Essential 8 (LE8) with mortality from CVD and its subtypes differ across frailty status remains unknown. Therefore, we aimed to assess the association between LE8 and CVD mortality among individuals with different frailty status.

Methods: Data were sourced from the UK Biobank of 439,462 participants aged 37-73 years. LE8, as a metric of CVH, was assessed using four health behaviors (diet, physical activity, nicotine exposure, and sleep health) and four health factors (body mass index, blood lipids, blood glucose, and blood pressure). Frailty status was measured with frailty index (FI) and Fried phenotype (FP). The outcomes included mortality of CVD, coronary heart disease, and cerebrovascular disease. Cox regression was used to calculate hazard ratios (HR) and 95% confidence intervals (CI) to assess the association, and additive and multiplicative interactive effects were also examined.

Results: Over a median follow-up period of 13.7 [interquartile range 13.0-14.4] years, 6,085 participants died from CVD. The moderate or high level of LE8 lowered the risk of CVD mortality with HRs (95% CIs) of (0.50, 0.47-0.53) and (0.25, 0.22-0.29), respectively. The effect did not differ in individuals with different frailty status (Pinteraction > 0.05), each group with an HR of about 0.3. Compared with those with low LE8 and frail, the HR for individuals who are not frail and with high LE8 level was about 0.15. Similar results were found for endpoints of CVD subtypes and for participants of all ages and sexes, and specifically, CVH appeared to be better protected for CVD mortality in those who were not treated for blood pressure, cholesterol, and diabetes.

Conclusion: Ideal CVH was associated with lower risk of CVD mortality regardless of frailty status. Specifically, for frail participants, optimizing CVH is a cost-effective strategy to mitigate CVD risk and promote healthy ageing.

Keywords: cardiovascular health; cardiovascular mortality risk; cohort study; frailty; survival analysis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Association of cardiovascular health metrics and CVD mortality. CVH, cardiovascular health metrics; HR, hazard ratios; CI, confidence intervals; PYs, person-years. Cox regression model was adjusted for age, sex, region, ethnicity, education level, Townsend deprivation index, household income, employ status, and alcohol consumption.
Figure 2
Figure 2
Association between cardiovascular health metrics and risk of CVD mortality by frailty status. HR, hazard ratios; CI, confidence intervals; PYs, person-years. Cox regression model was adjusted for age, sex, region, ethnicity, education level, Townsend deprivation index, household income, employ status, and alcohol consumption. The p-values for multiplicative interaction of frailty index and frailty phenotype were 0.863 and 0.401, the p-values for additive interaction were 0.011 (RERI = 0.397) and 0.203.
Figure 3
Figure 3
Joint association of frailty status and cardiovascular health metrics with risk of CVD mortality. HR, hazard ratios; CI, confidence intervals; PYs, person-years. Cox regression model was adjusted for age, sex, region, ethnicity, education level, Townsend deprivation index, household income, employ status, and alcohol consumption.
Figure 4
Figure 4
The hazard ratios (solid line) and 95% confidence intervals (band) were estimated by fitting restricted cubic spline Cox regression models with 5th, 35th, 65th and 95th knots, in which cardiovascular health metrics was modeled as a continuous variable. The minimum value (cardiovascular health metrics =0) was set as the reference. Cox regression model was adjusted for age, sex, region, ethnicity, education level, Townsend deprivation index, household income, employ status, and alcohol consumption. (A) cardiovascular health metrics (CVH) and CVD mortality. (a1) CVH and CVD mortality by frailty index (FI). (a2) CVH and CVD mortality by frailty phenotypes (FP). (B) CVH and coronary heart disease (CHD) mortality. (b1) CVH and CHD mortality by FI. (b2) CVH and CHD mortality by FP. (C) CVH and cerebrovascular disease (CED) mortality. (c1) CVH and CED mortality by FI. (c2) CVH and CED mortality by FP.

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