Lopez-Jimenez, F

Abstract Background The implications of poor sleep for cardiovascular disease risk are increasingly recognised. Although previous research has focused on clinical sleep disorders, emerging evidence highlights the relevance of subclinical sleep aspects for cardiovascular health. Sleep midpoint, an index of sleep timing and a proxy of circadian phase, has been shown to be associated with markers of cardiometabolic risk, including obesity, in the general population. Purpose We aimed to assess whether sleep midpoint was related to body composition measures in patients with coronary heart disease enrolled in cardiac rehabilitation (CR). Methods Study participants were recruited from the patient population referred to our CR center for acute coronary syndrome or coronary revascularisation. Shift work was exclusionary. Participants underwent sleep testing prior to entering the CR program, including completion of one week of wrist actigraphy and sleep log. Using actigraphy-derived sleep metrics, sleep midpoint was calculated as the middle time (hh:mm) between bedtime and wake up time for each individual night, and averaged across the monitoring week. Based on the median sleep midpoint of the sample, participants were categorised as having early (before 2:42) or late (after 2:42) sleep midpoint. Body composition and regional fat distribution were determined by whole-body dual-energy absorptiometry (DEXA). Between-group characteristics were compared using independent t-test, Mann-Whitney U test and Chi-square statistics as appropriate. Linear regression was used to test the association between sleep midpoint and body fat measures. Results Thirty-one participants (26 males, 64.7±12.5 years) completed both actigraphy and DEXA assessments. Demographics, lifestyle, and clinical characteristics were similar between patients with early sleep midpoint (n=15; sleep midpoint, hh:mm: 2:00, range 0:57 to 2:41) and patients with late sleep midpoint (n=16; sleep midpoint 3:18, range 2:42 to 4:17). Despite comparable body mass index between groups (p=0.21), patients with late sleep midpoint had significantly higher total body fat percentage (p=0.017), android fat percentage (p=0.015), and gynoid fat percentage (p=0.045). Late sleep midpoint remained significantly associated with adiposity measures in age- and sex-adjusted analysis (total body fat percentage, beta = 0.371, 95% CI 0.063 to 0.68; android fat percentage, beta = 0.394, 95% CI 0.078 to 0.71; gynoid fat percentage, beta = 0.301, 95% CI 0.007 to 0.596). Conclusions Late sleep midpoint was associated with excess adiposity in patients with coronary heart disease enrolled in CR. These findings support the predictive value of sleep timing for cardiometabolic risk and emphasise the importance of objective sleep assessment for secondary prevention.

Abstract Aims Social isolation (SI) is associated with a higher risk of cardiovascular disease (CVD). One mechanism linking SI and CVD is accelerated biological ageing, which can be assessed using artificial intelligence-enabled electrocardiography (AI-ECG). We investigated whether longitudinal changes in SI status are associated with changes in biological ageing patterns. Methods and results A retrospective longitudinal cohort study including 17 663 individuals without significant CVD who completed ≥2 Berkman and Syme Social Network Index and had paired ECGs within 1 year of each questionnaire. Longitudinal SI status was defined by comparing baseline and follow-up SI status. Ageing trends were assessed using Δage-gap, defined as the change in the gap between AI-ECG-predicted age and chronological age from baseline to follow-up. Linear regression models predicting Δage-gap and survival analyses with Kaplan–Meier and multivariable Cox regression for all-cause mortality were performed. Persistently connected individuals were older [63.1 (52.1, 70.6) years] and had a higher prevalence of hyperlipidaemia and hypertension, yet demonstrated more favourable ageing trajectories. Similarly, those who became connected showed a non-significant attenuation of accelerated ageing. In multivariable linear regression, being persistently isolated [β = +0.412 years, P < 0.001] or becoming isolated [β = +0.438 years, P = 0.012] was associated with accelerated ageing compared to being persistently connected. In survival analyses, becoming isolated (aHR = 1.94, 95% CI = 1.53–2.46, P < 0.001) and being persistently isolated (aHR = 1.66, 95% CI = 1.40–1.96, P < 0.001) were associated with significantly higher all-cause mortality, independent of chronological age and comorbidities. Conclusion Persistent social connection is associated with slower biological ageing and lower mortality. The effects of SI on ageing and survival appear to be potentially reversible, calling for a prospective study to evaluate interventions aimed at improving both the social and biological burden of SI.