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Associations of educational level with ECG-derived cardiovascular ageing in a population-based cohort: a mediation
Arya Panthalanickal Vijayakumar1, Tom Wilsgaard2, Henrik Schirmer3,4
1Department of Community Medicine, UiT The Arctic University of Norway Faculty of Health Sciences, Tromsø, Norway arya.p.vijayakumar@uit.no.
Objective:
To assess the association between educational level and cardiovascular age acceleration metric derived from ECG, and to determine whether this association is mediated by established cardiovascular disease (CVD) risk factors.
Design:
Prospective population-based cohort study (the Tromsø Study).
Setting:
General population of the Tromsø municipality, Norway.
Participants:
The study sample consisted of 4367 participants of the Tromsø Study, who took part in both Tromsø6 (2007-2008) and Tromsø7 (2015-2016), had a 12-lead ECG obtained at Tromsø7 and did not report a history of heart attack, stroke or atrial fibrillation.
Primary Outcome Measures:
δ-age, a biomarker of cardiovascular ageing, is defined as the difference (in years) between an individual's ECG-predicted heart age and their chronological age. ECG-predicted heart age was estimated using a previously validated deep neural network.
Results:
Our findings indicate an inverse association between education and δ-age, with a regression coefficient per increment increase in education of -0.24 (95% CI -0.41 to -0.07) in the overall sample, -0.38 (95% CI -0.59 to -0.16) for women and -0.04 (95% CI -0.31 to 0.23) for men. Participants with the highest level of education (university/college for 4 or more years) had the lowest estimated δ-age with a regression coefficient of -0.69 years (95% CI -1.23 to -0.16) compared with the group with primary education for the overall sample, -1.05 years (95% CI -1.73 to -0.37) for women and -0.15 years (95% CI -1.03 to 0.73) for men. CVD risk factors mediated up to 75% of the association between overall education and δ-age, and 80% of the association among those with the highest education level (university/college for 4 or more years). Among women, 50% of the effect of overall education on δ-age was mediated by CVD risk factors, rising to 53% in the category with the highest level of education. However, in the subsample of men, there was no significant association between education and δ-age, and the mediation analysis produced natural direct and indirect effects pointing in opposite directions.
Conclusions:
Cardiovascular ageing is inversely associated with educational level, an effect that appears to be largely mediated through established risk factors.
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