Key result
Combined smoking, inactivity, and inadequate sleep linked to ~15-fold higher odds of sudden cardiac arrest.
Why the study?
Sudden cardiac arrest often occurs in individuals without diagnosed cardiovascular disease, suggesting conventional risk assessment may overlook behavioural contexts.
Are distinct lifestyle phenotypes associated with sudden cardiac arrest in the community?
Case-Control (n=4,085)
Yes
Are distinct lifestyle phenotypes associated with sudden cardiac arrest in the community?
Specific multidomain lifestyle phenotypes, particularly those combining smoking, inactivity, and poor sleep or high intake of red meat and fish, are strongly associated with increased odds of sudden cardiac arrest.
High-risk lifestyle clusters associate with SCA; hypothesis-generating and requires prospective trials before any practice change.
Aims Sudden cardiac arrest (SCA) often occurs in individuals without diagnosed cardiovascular disease, suggesting conventional risk assessment may overlook behavioural contexts. We examined whether co-occurring lifestyle behaviours formed distinct phenotypes associated with SCA. Methods We analysed data from a prospective multicentre case-control study conducted in South Korea (2017–2023) including out-of-hospital cardiac arrest of presumed cardiac aetiology and community controls frequency-matched by age, sex, and residential area. Seven lifestyle indicators were assessed: smoking, physical activity, sleep duration, and intake of red meat, fish, fruit, and vegetables. Latent class analysis identified lifestyle phenotypes, and odds ratios (ORs) were estimated using a single fully adjusted logistic regression model informed by a directed acyclic graph. Results The primary analysis included 1,466 cases and 2,619 controls, identifying five phenotypes. The reference class (C2) showed the lowest observed proportion of SCA and a predominantly middle-frequency dietary pattern. Compared with C2, fully adjusted odds of SCA were higher for C1 (OR, 1.48; 95% confidence interval: 1.13–1.94) and C3 (1.95; 1.60–2.39), and markedly higher for C4 (8.93; 6.75–11.81) and C5 (15.20; 11.19–20.64). C5 was characterised by high reported intake frequency across food groups, particularly red meat and fish; C4 combined current smoking, physical inactivity, and inadequate sleep with low reported intake frequency across food groups. Conclusion Cluster-derived lifestyle phenotypes were associated with differing odds of SCA. Although causal effects and absolute risk cannot be inferred from this case-control design, these multidomain patterns may help characterise behavioural profiles associated with SCA and inform future prevention research.
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Ahn et al. (2026) conducted a case-control in Sudden cardiac arrest (n=4,085). Cluster-derived lifestyle phenotypes vs. Reference class (C2) with middle-frequency dietary pattern was evaluated on Sudden cardiac arrest (OR 15.20, 95% CI 11.19-20.64). Cluster-derived lifestyle phenotypes, particularly those combining smoking, inactivity, and inadequate sleep, were associated with markedly higher odds of sudden cardiac arrest (up to OR 15.20; 95% CI 11.19-20.64).
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