Stressful life events and heart disease and stroke: A study among Portuguese older adults.
Ana QuaresmaElisabete AlvesSilvia FragaAna HenriquesPublished in: Stress and health : journal of the International Society for the Investigation of Stress (2023)
The link between stressful life events (SLE) and cardiovascular diseases (CVD) remains underexplored. This study aimed to examine the association between SLE and the diagnosis of heart disease or stroke, among older adults. Data from 678 participants from the population-based cohort EPIPorto, with ≥60 years and complete information regarding SLE and heart disease or stroke, were analysed. Stressful life events were measured through the 'Stressful Life Events Screening Questionnaire'. A previous diagnosis of heart disease or stroke was self-reported. Adjusted odds ratios (OR) with the respective 95% confidence intervals were computed through logistic regression. Almost a fourth of the participants never experienced any SLE throughout life, 30.0% experienced at least one event, 17.5% experienced two and 27.7% had experienced three or more SLE. A dose-effect association between SLE and the diagnosis of heart disease or stroke was observed, statistically significant for those who had at least 3 types of SLE, independently of confounders (≥3SLE vs. 0SLE: OR = 2.00; 95% CI: 1.12-3.57). This cross-sectional study suggests that cumulative exposure to different types of SLE during the life course was associated with a higher likelihood of having a diagnosis of heart disease or a stroke at a later age. Future longitudinal studies should better deepen this association, particularly by evaluating which type of SLE is more related to a higher prevalence of heart disease and stroke, and how the timing of the SLE influence this relation.
Keyphrases
- systemic lupus erythematosus
- disease activity
- atrial fibrillation
- pulmonary hypertension
- rheumatoid arthritis
- type diabetes
- physical activity
- computed tomography
- risk factors
- cross sectional
- magnetic resonance imaging
- machine learning
- subarachnoid hemorrhage
- cardiovascular events
- big data
- contrast enhanced
- diffusion weighted imaging