Heart rate variability (HRV) is an important marker of cardiac autonomic regulation and health. We examined the influence of sleep duration and sex on HRV in younger and middle-aged adults. Cross-sectional data (888 participants, 44% women) were analyzed from Program 4 of the Healthy Aging in Industrial Environment study (HAIE). Sleep duration was measured across 14 days using Fitbit Charge monitors. Short-term EKG recordings were used to evaluate HRV in the time (RMSSD) and frequency domains (low frequency (LF) and high frequency (HF) power). Regression analysis showed age was associated with lower HRV across all HRV variables (all P < 0.001). Sex was a significant predictor for LF (β = 0.52) and HF (β = 0.54; both P < 0.001) in normalized units. Similarly, sleep duration was only associated with HF in normalized units (β = 0.06, P = 0.04). To explore this finding further, participants within each sex were separated into groups based on age (<40 and ≥ 40y) and adequate sleep duration (<7 and ≥7 h). Middle-aged women with sleep durations <7 h, but not ≥7 h, had lower HRV than younger women after adjusting for medications, respiratory frequency, and cardiorespiratory fitness (peak VO2). Middle-aged women with sleep durations <7 h also had lower RMSSD (33 ± 2 vs. 41±4 ms, P = 0.04), HF power (5.6 ± 0.1 vs. 6.0 ± 0.1 log ms2, P = 0.04), and HF in normalized units (39 ± 1 vs. 48 ± 2, P = 0.01) than middle-aged women with sleep durations ≥7 h. In contrast, middle-aged men irrespective of sleep duration had lower HRV than younger men. These results suggest that adequate sleep duration may positively influence HRV in middle-aged women but not men.

Department of Human Movement Studies University of Ostrava Ostrava Czech Republic

Department of Human Movement Studies University of Ostrava Ostrava Czech Republic; Department of Epidemiology and Public Health Faculty of Medicine University of Ostrava Ostrava Czech Republic

Department of Human Movement Studies University of Ostrava Ostrava Czech Republic; Department of Machine Learning and Data Processing Masaryk University Brno Czech Republic

Department of Kinesiology and Sport Management Texas Tech University Lubbock TX USA

Institute for Research and Applications of Fuzzy Modeling University of Ostrava Czech Republic

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