Abstract
BACKGROUND: Tools like Life's Simple 7 (LS7) can help estimate the risk of cardiovascular events in healthy subjects. Recently, the Life's Essential 8 (LE8) was developed, including sleep as an additional variable for a more precise cardiovascular risk estimation. However, it is unclear whether such an increase in complexity is associated with an improvement in the score's performance. We aimed to test the LS7 and LE8 in a European cohort in order to understand whether adding subjective sleep information could allow a better cardiovascular risk stratification. METHODS: UK Biobank data were used for computing the cardiovascular scores. Sleep duration was evaluated through questionnaires. The cardiovascular outcomes were fatal and non-fatal CVD events. Multivariable-adjusted logistic and Cox proportional hazards models were used to evaluate associations of the different metrics with CVD prevalence and incidence. The c-statistic was used to quantify differences in incident CVD discrimination. RESULTS: A cohort of 106,724 participants (mean age: 55.9 years, 55% males) included 6,130 prevalent and 11,575 incident CVD events (mean follow-up: 12.9 ± 2.7 years). CVH metrics were categorised into tertiles. LS7- and LE8-based metrics effectively characterised prevalent and incident CVD events. LS7 models had similar C-statistics with (0.705, 95% CI: 0.701-0.709) and without (0.706, 95% CI: 0.702-0.710) sleep data. LE8 without sleep (0.708, 95% CI: 0.704-0.712) outperformed LS7 without sleep by 0.002 (95% CI: 0.001-0.003, p < 0.05). However, standard LE8 with sleep (0.706, 95% CI: 0.702-0.710) showed no significant difference from LS7. CONCLUSIONS: In a European cohort, LS7 and LE8 are useful tools for risk stratification. However, despite the LE8 offering marginally better risk stratification than LS7, the inclusion of subjective sleep did not provide a tangible advantage.