Correlation between heart rate variability and pulmonary function adjusted by confounding factors in healthy adults

The autonomic nervous system maintains homeostasis, which is the state of balance in the body. That balance can be determined simply and noninvasively by evaluating heart rate variability (HRV). However, independently of autonomic control of the heart, HRV can be influenced by other factors, such as respiratory parameters. Little is known about the relationship between HRV and spirometric indices. In this study, our objective was to determine whether HRV correlates with spirometric indices in adults without cardiopulmonary disease, considering the main confounders (e.g., smoking and physical inactivity). In a sample of 119 asymptomatic adults (age 20-80 years), we evaluated forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). We evaluated resting HRV indices within a 5-min window in the middle of a 10-min recording period, thereafter analyzing time and frequency domains. To evaluate daily physical activity, we instructed participants to use a triaxial accelerometer for 7 days. Physical inactivity was defined as <150 min/week of moderate to intense physical activity. We found that FVC and FEV1, respectively, correlated significantly with the following aspects of the RR interval: standard deviation of the RR intervals (r =0.31 and 0.35), low-frequency component (r =0.38 and 0.40), and Poincaré plot SD2 (r =0.34 and 0.36). Multivariate regression analysis, adjusted for age, sex, smoking, physical inactivity, and cardiovascular risk, identified the SD2 and dyslipidemia as independent predictors of FVC and FEV1 (R2=0.125 and 0.180, respectively, for both). We conclude that pulmonary function is influenced by autonomic control of cardiovascular function, independently of the main confounders.

Correlation between heart rate variability and pulmonary function adjusted by confounding factors in healthy adults.

The autonomic nervous system maintains homeostasis, which is the state of balance in the body. That balance can be determined simply and noninvasively by evaluating heart rate variability (HRV). However, independently of autonomic control of the heart, HRV can be influenced by other factors, such as respiratory parameters. Little is known about the relationship between HRV and spirometric indices. In this study, our objective was to determine whether HRV correlates with spirometric indices in adults without cardiopulmonary disease, considering the main confounders (e.g., smoking and physical inactivity). In a sample of 119 asymptomatic adults (age 20-80 years), we evaluated forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). We evaluated resting HRV indices within a 5-min window in the middle of a 10-min recording period, thereafter analyzing time and frequency domains. To evaluate daily physical activity, we instructed participants to use a triaxial accelerometer for 7 days. Physical inactivity was defined as <150 min/week of moderate to intense physical activity. We found that FVC and FEV1, respectively, correlated significantly with the following aspects of the RR interval: standard deviation of the RR intervals (r =0.31 and 0.35), low-frequency component (r =0.38 and 0.40), and Poincaré plot SD2 (r =0.34 and 0.36). Multivariate regression analysis, adjusted for age, sex, smoking, physical inactivity, and cardiovascular risk, identified the SD2 and dyslipidemia as independent predictors of FVC and FEV1 (R2=0.125 and 0.180, respectively, for both). We conclude that pulmonary function is influenced by autonomic control of cardiovascular function, independently of the main confounders.

Heart rate variability during 6-min walk test in adults aged 40 years and older.

We evaluated age- and sex-dependent differences in heart rate variability (HRV) during the 6-min walk test (6MWT) in healthy adults. We also evaluated the intensity of the 6MWT based on HRV. 78 participants aged 40-49, 50-59, 60-69, and ≥ 70 years (42 females; 36 men) performed the 6MWT. Heart rate and HRV were monitored 1 min at rest and during the last 2-min of the test. The root mean square (RMSSD), instantaneous beat-to-beat variability (SD1), and long-term standard deviation (SD2) of RR intervals were calculated. The SD1 <3 ms at the end of the 6MWT was defined as high-intensity exercise. Despite the significantly higher peak values of heart rate observed for women, we did not find sex- and age-related differences in HRV during the 6MWT. The ROC curve identified percentage of maximum heart rate >67% as the best cut-point for prediction of high-intensity exercise with 94% of sensitivity and 65% of specificity (area under the curve=0.804). We may conclude that autonomic modulation of heart rate during exercise was not dependent of age and sex. The HRV assessment during walking enables a valid estimation of exercise intensity in adults. We may therefore suggest the use of 6MWT for assessing exercise capacity and for prescribing exercises in adults aged 40 yrs and older.