Vital exhaustion as a risk factor for adverse cardiac events (from the Atherosclerosis Risk In Communities [ARIC] study)

Abstract

Vital exhaustion, defined as excessive fatigue, feelings of demoralization, and increased irritability, has been identified as a risk factor for incident and recurrent cardiac events, but there are no population-based prospective studies of this association in US samples. We examined the predictive value of vital exhaustion for incident myocardial infarction or fatal coronary heart disease in middle-aged men and women in 4 US communities. Participants were 12,895 black or white men and women enrolled in the Atherosclerosis Risk In Communities (ARIC) study cohort and followed for the occurrence of cardiac morbidity and mortality from 1990 through 2002 (maximum follow-up 13.0 years). Vital exhaustion was assessed using the 21-item Maastricht Questionnaire and scores were partitioned into approximate quartiles for statistical analyses. High vital exhaustion (fourth quartile) predicted adverse cardiac events in age-, gender-, and race-center-adjusted analyses (1.69, 95% confidence interval 1.40 to 2.05) and in analyses further adjusted for educational level, body mass index, plasma low-density lipoprotein and high-density lipoprotein cholesterol levels, systolic and diastolic blood pressure levels, diabetes mellitus, cigarette smoking status, and pack-years of cigarette smoking (1.46, 95% confidence interval 1.20 to 1.79). Risk for adverse cardiac events increased monotonically from the first through the fourth quartile of vital exhaustion. Probabilities of adverse cardiac events over time were significantly higher in people with high vital exhaustion compared to those with low exhaustion (p = 0.002). In conclusion, vital exhaustion predicts long-term risk for adverse cardiac events in men and women, independent of established biomedical risk factors.

Figure 1

The Kaplan-Meier product limit estimate of the cumulative probability of adverse cardiac events by level of vital exhaustion (P = 0.01, 0.0005, 0.002 for differences between Q4 and Q3, Q2, and Q1, respectively).