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Findings From the Heart and Soul Study

Anil Gehi, MD; Dennis Mangano, PhD, MD; Sharon Pipkin, MPH; Warren S. Browner, MD, MPH; Mary A. Whooley, MD

Arch Gen Psychiatry. 2005;62:661-666.

Context  Depression is associated with low heart rate variability (HRV) in patients following myocardial infarction, suggesting that alterations in the autonomic nervous system may contribute to the adverse cardiac outcomes associated with depression. Whether depression is associated with low HRV in patients with stable coronary heart disease (CHD) is not known.

Objective  To examine the association between major depression and 24-hour HRV in patients with stable CHD.

Design, Setting, and Participants  Cross-sectional study of 873 outpatients with stable CHD recruited from outpatient clinics in the San Francisco Bay Area, California.

Main Outcome Measures  Major depression was assessed using the Computerized National Institute of Mental Health Diagnostic Interview Schedule. Heart rate variability was measured by 24-hour ambulatory electrocardiography.

Results  A total of 195 participants (22%) had major depression. Overall, we observed no association between depression and HRV as measured by time domain or frequency domain variables. Mean HRV was similar in participants with and without depression (all P values >.10), and participants with depression were no more likely than those without depression to have low HRV (all P values >.10).

Conclusions  We found no evidence of an association between depression and HRV in 873 outpatients with stable CHD. These findings raise questions about the potential role of HRV in the association between depression and cardiovascular disease.

Author Affiliations: The Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai School of Medicine, New York, NY (Dr Gehi); Ischemia Research and Education Foundation (Dr Mangano), Veterans Affairs Medical Center (Ms Pipkin and Dr Whooley), Research Institute, California Pacific Medical Center (Dr Browner), Departments of Medicine and Epidemiology and Biostatistics, University of California San Francisco (Drs Browner and Whooley).

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