Happiness and cardiovascular mortality: the HAPIEE study
| Author | Affiliation | |
|---|---|---|
Pikhart, H | ||
| Date | Volume | Issue | Start Page | End Page |
|---|---|---|---|---|
2024-06-13 | 31 | Suppl. 1 | 191 | 191 |
e-Cardiology / Digital Health, Public Health, Health Economics, Research Methodology – Research Methodology, Cardiovascular Epidemiology
Background There is mixed evidence on the relationship between happiness and cardiovascular mortality (CVD), and how it is affected by health and other variables, with almost no evidence in the region of Central and Eastern Europe (CEE) with high CVD mortality. This analysis aims to evaluate such association in longitudinal data from three countries of CEE, and investigate the role of other variables in this association.
Methods This analysis is based on data from 18,362 men and women from the prospective longitudinal Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study conducted in the Czech Republic, Lithuania and Poland who were 45-70 years old at the baseline. Happiness was based on 4-points Likert scale answers to the question "Taking all things together, would you say you are …", with the answers "Very happy", "Quite happy", "Not very happy", and "Not at all happy". Cardiovascular mortality was obtained from local or national mortality registers. Cox proportional hazards regression was used to estimate the hazard ratios (HRs).
Results 1,051 cardiovascular deaths have been recorded over the 11 years of follow-up (among 2,718 all-cause deaths). After adjustment for country and age the HR comparing very happy and unhappy was 0.39 (95%CI: 0.26-0.58) in men and 0.70 (0.43-1.13) in women. This association was reduced after adjusting for socioeconomic characteristics, health behaviours and conventional risk factors (HR 0.65 in men and 0.95 in women); and disappeared in both sexes after controlling for self-rated health. No evidence for country interaction was identified.
Conclusions Happiness has been shown to predict CVD mortality in this population sample from CEE although it may be explained by established risk factors and self-rated health.