An ideal lifestyle was associated with a 2.50-year younger deep learning-predicted electrocardiographic age compared to an unfavorable lifestyle.
Cohort (n=44,094)
Yes
Does an ideal healthy lifestyle reduce the difference between deep learning predicted electrocardiographic age and chronological age in a general adult population?
Adherence to healthy lifestyle factors is significantly associated with decelerated biological aging as measured by a deep learning-derived electrocardiographic age.
Effect estimate: β -2.50 years
p-value: p=<0.001
Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear. Methods: This study included participants from the UK Biobank who had undergone 12-lead resting electrocardiography (ECG). Biological age was estimated by a deep learning model (defined as ECG-age), and the difference between ECG-age and chronological age was defined as Δage. Participants were further categorized into an ideal (score 4), intermediate (scores 2 and 3) or unfavorable lifestyle (score 0 or 1). Four lifestyle factors were investigated, including diet, alcohol consumption, physical activity, and smoking. Linear regression models were used to examine the association between lifestyle factors and Δage, and the models were adjusted for sex and chronological age. Results: < 0.001) and the mean Δage (absolute error of biological age and chronological age) was 9.8 ± 7.4 years. Δage was significantly associated with all of the four lifestyle factors, with the effect size ranging from 0.41 ± 0.11 for the healthy diet to 2.37 ± 0.30 for non-smoking. Compared with an ideal lifestyle, an unfavorable lifestyle was associated with an average of 2.50 ± 0.29 years of older predicted ECG-age. Conclusion: In this large contemporary population, a strong association was observed between all four studied healthy lifestyle factors and deaccelerated aging. Our study underscores the importance of a healthy lifestyle to reduce the burden of aging-related diseases.
Zhang et al. (Mon,) conducted a cohort in Biological aging (n=44,094). Ideal lifestyle vs. Unfavorable lifestyle was evaluated on Difference between ECG-age and chronological age (Δage) (β -2.50 years, p=<0.001). An ideal lifestyle was associated with a 2.50-year younger deep learning-predicted electrocardiographic age compared to an unfavorable lifestyle.