Abstract 12269: The Association Between Measurements of Obesity and Accelerated Aging Estimated by Artificial Intelligence ECG

Introduction: The effect of obesity on physiologic aging has not been completely established. We previously developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm that predicts age and determines that the difference between AI-ECG age and chronological age (Age-Gap) may re...

Full description

Saved in:
Bibliographic Details
Published inCirculation (New York, N.Y.) Vol. 148; no. Suppl_1; p. A12269
Main Authors Bianchettin, Rosana G, Medina-Inojosa, Jose R, Attia, Zachi, Medina-Inojosa, Betsy, De Leon, Andrea, Mangold, Kathryn, Sheffeh, Mohammad Ali, Johnson, Lynne, Friedman, Paul, Lopez-Jimenez, Francisco
Format Journal Article
LanguageEnglish
Published Hagerstown, MD Lippincott Williams & Wilkins 07.11.2023
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Introduction: The effect of obesity on physiologic aging has not been completely established. We previously developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm that predicts age and determines that the difference between AI-ECG age and chronological age (Age-Gap) may reflect accelerated aging, as it is associated with increased total and cardiovascular (CV) mortality. Hypothesis: Obesity is associated with an increased Age-Gap reflecting morbidity and accelerated aging. Methods: We included adults undergoing a wellness evaluation including, body fat percentage (BF%) determination by air displacement plethysmography (Bod-Pod®) and a 12-lead ECG within 2 years. We excluded those with coronary artery disease, congestive heart failure, stroke or being underweight defined as having a BMI<18.5 kg/m2. Logistic regression models tested the association between obesity by BMI (≥30 kg/m2) or BF% quartiles (≥35% for men and ≥25 in women) and being older by AI-ECG. Results: We included 1295 subjects (70% women), mean chronological age 46.7 ± 13.1 years. Mean Age-gap positive difference compared to those with BMI<25 was 1.39, 2.06 and 2.83 for those with BMI 25-29.9, 30-34.9, and >35 respectively (p<0.05). In the BF% group, Age-gap difference compared to those in the 1st quartile was 0.008, 0.37 and 1.52 for those in the 2nd, 3rd, and 4th quartile (p<0.05). Those>3 years older by ECG were more likely to have obesity by BMI and BF%, see figure. Conclusions: Obesity, either by BMI or BF%, is associated with increased physiologic age as measured by AI-ECG, highlighting the importance of obesity as a health threat.
Bibliography:Author Disclosures: For author disclosure information, please visit the AHA Scientific Sessions 2023 Online Program Planner and search for the abstract title.
ISSN:0009-7322
1524-4539
DOI:10.1161/circ.148.suppl_1.12269