| Titre : | Association between behavioural circadian rhythm profiles and incident cardiovascular disease in older adults: results from the UK Biobank accelerometer sub-study |
| Auteurs : | Nathalia Garcia Ocampo ; Ecole des hautes études en santé publique (EHESP) (Rennes, FRA) |
| Type de document : | Mémoire |
| Année de publication : | 2025 |
| Description : | 41p. |
| Langues: | Anglais |
| Classement : | MPH/ (Mémoires MPH à partir de 2024) |
| Mots-clés : | Biorythme ; Appareil circulatoire [pathologie] ; Personne âgée ; Promotion santé ; Prévention santé |
| Résumé : |
Background : Evidence suggests that physical activity (PA), sleep, chronotype, and rest-activity rhythm (RAR) play a role in cardiovascular disease (CVD) incidence. These behaviours, regulated over a 24-hour clock, are part of the bio-behavioural expression of circadian rhythm (CR). These four dimensions can be objectively measured using accelerometers. Most studies examining the association between CR and CVD have not considered all CR dimensions simultaneously or accounted for their interdependence. This study aims to examine the association between accelerometer-derived CR profiles accounting for all four dimensions and incident CVD in older adults, and whether these associations vary by sex, age, or BMI.
Methods : Participants included 48,946 adults older than 60years from the UK Biobank accelerometer sub-study. Nine CR profiles were previously identified using a 2-step approach, comprising principal component analysis following by a clustering method on 36 accelerometer-derived metrics covering all CR dimensions. Cox proportional hazards models estimated the hazard ratios for incident CVD across CR profiles, adjusted for sociodemographic, behavioural, health-related, and cardiometabolic factors. Interaction terms for sex, age, and BMI were added to the models. Results: Over a median follow-up of 7.7 years, 4,220 incident CVD cases occurred. Compared to Profile 3 (RAR+/LIPA+/Sleep+), Profile 4 (MVPA++) showed 14% lower CVD risk. In contrast, Profiles 7 (RAR-/PA-/Sleep--), 8 (RAR-/PA+/Restless-Sleep), and 9 (RAR--/PA--/Chronotype-) presented 19%, 20%, and 27% increased CVD risk, respectively. The protective association of Profile 1 (RAR++/PA++) was attenuated after adjusting for cardiometabolic factors. Only Profile 9 (RAR--/PA--/Chronotype-) showed a significant interaction with sex, with a stronger effect in women than in men, although the direction of the association was the same for both sexes. Conclusion: These findings highlight the importance of assessing CR holistically to understand CVD risk in ageing populations. An active daytime pattern, particularly involving MVPA, was found to be protective. Differences in RAR, daytime activity and sleep patterns across CR profiles contributed to varying CVD risks. Our results support targeted interventions covering all CR dimensions to promote cardiovascular health in older adults. |
| Diplôme : | Master MPH of public health |
| Plan de classement simplifié : | Master of Public Health - master international de Santé Publique (MPH) |
| En ligne : | https://documentation.ehesp.fr/memoires/2025/mph/nathalia-garcia-ocampo.pdf |
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