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Alcohol use has complex effects on cardiovascular (CV) health. The associations between drinking and CV diseases such as hypertension, coronary heart disease, stroke, peripheral arterial disease, and cardiomyopathy have been studied extensively and are outlined in this review. Although many behavioral, genetic, and biologic variants influence the interconnection between alcohol use and CV disease, dose and pattern of alcohol consumption seem to modulate this most. Low-to-moderate alcohol use may mitigate certain mechanisms such as risk and hemostatic factors affecting atherosclerosis and inflammation, pathophysiologic processes integral to most CV disease. But any positive aspects of drinking must be weighed against serious physiological effects, including mitochondrial dysfunction and changes in circulation, inflammatory response, oxidative stress, and programmed cell death, as well as anatomical damage to the CV system, especially the heart itself. Both the negative and positive effects of alcohol use on particular CV conditions are presented here. The review concludes by suggesting several promising avenues for future research related to alcohol use and CV disease. These include using direct biomarkers of alcohol to confirm self-report of alcohol consumption levels; studying potential mediation of various genetic, socioeconomic, and racial and ethnic factors that may affect alcohol use and CV disease; reviewing alcohol–medication interactions in cardiac patients; and examining CV effects of alcohol use in young adults and in older adults.

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Aging is associated with decreased aerobic fitness and cardiac remodeling leading to increased risk for cardiovascular disease. High-intensity interval training (HIIT) on the treadmill has been reported to be more effective in ameliorating these risk factors compared with moderate-intensity continuous training (MICT) in patients with cardiometabolic disease. In older adults, however, weight-bearing activities are frequently limited due to musculoskeletal and balance problems. The purpose of this study was to examine the feasibility and safety of non-weight-bearing all-extremity HIIT in older adults. In addition, we tested the hypothesis that all-extremity HIIT will be more effective in improving aerobic fitness, cardiac function, and metabolic risk factors compared with all-extremity MICT. Fifty-one healthy sedentary older adults (age: 65±1 years) were randomized to HIIT (n=17), MICT (n=18) or non-exercise control (CONT; n=16). HIIT (4×4 minutes 90% of peak heart rate; HRpeak) and isocaloric MICT (70% of HRpeak) were performed on a non-weight-bearing all-extremity ergometer, 4x/week for 8 weeks under supervision. All-extremity HIIT was feasible in older adults and resulted in no adverse events. Aerobic fitness (peak oxygen consumption; VO2peak) and ejection fraction (echocardiography) improved by 11% (P<0.0001) and 4% (P=0.001) respectively in HIIT, while no changes were observed in MICT and CONT (P≥0.1). Greater improvements in ejection fraction were associated with greater improvements in VO2peak (r=0.57; P<0.0001). Insulin resistance (homeostatic model assessment) decreased only in HIIT by 26% (P=0.016). Diastolic function, body composition, glucose and lipids were unaffected (P≥0.1). In conclusion, all-extremity HIIT is feasible and safe in older adults. HIIT, but not MICT, improved aerobic fitness, ejection fraction, and insulin resistance.

Aortic pulse wave velocity (AoPWV) and augmentation index (AIx) are commonly used measures of large elastic artery stiffness and wave reflection, respectively. Recently, a new cuff-based SphygmoCor device (Xcel) has been developed to measure both AoPWV and AIx. We sought to examine the following: (1) the validity of Xcel compared with the well-validated tonometry-based SphygmoCor device (MM3); (2) the intratest and day-to-day reliability of Xcel; (3) the influence of body side (right or left) on Xcel measurements; and (4) the relation of Xcel measurements to carotid artery compliance, distensibility and β-stiffness index. We found that measurements of AoPWV and AIx between Xcel and MM3 were not different (P=0.26 and P=0.43, N=22 and 26, respectively) and were strongly related (r=0.85 and 0.75, P<0.0001), and based on Bland-Altman plots there was good agreement between them. Intra-test (intraclass correlation=0.996 and 0.983, P<0.0001; AoPWV and AIx, N=24 and 26, respectively) and day-to-day reliability (intraclass correlation=0.979 and 0.939, P<0.0001) were high. Xcel AoPWV and AIx on the left versus right body side were not different (P=0.19 and P=0.58, N=14 and 15, respectively) and were highly correlated (r=0.99 and 0.94, P<0.0001). AoPWV and AIx measured with Xcel were positively related with β-stiffness index (r=0.62 and 0.51, P< or = 0.005, N=23 and 24, respectively) and negatively related with distensibility (r = -0.58 and -0.44, P < or = 0.02, N=23 and 24, respectively). In conclusion, Xcel measures of AIx and AoPWV are valid, highly reliable and not affected by body side. Xcel is a useful tool for use in research and the clinic.