Trends in Daily Heart Rate Variability Fluctuations Are Associated with Longitudinal Changes in Stress and Somatisation in Police Officers

The emergence of wearable sensors that allow for unobtrusive monitoring of physiological and behavioural patterns introduces new opportunities to study the impact of stress in a real-world context. This study explores to what extent within-subject trends in daily Heart Rate Variability (HRV) and daily HRV fluctuations are associated with longitudinal changes in stress, depression, anxiety, and somatisation. Nine Dutch police officers collected daily nocturnal HRV data using an Oura ring during 15–55 weeks. Participants filled in the Four-Dimensional Symptoms Questionnaire every 5 weeks. A sample of 47 five-week observations was collected and analysed using multiple regression. After controlling for trends in total sleep time, moderate-to-vigorous physical activity and alcohol use, an increasing trend in the seven-day rolling standard deviation of the HRV (HRVsd) was associated with increases in stress and somatisation over 5 weeks. Furthermore, an increasing HRV trend buffered against the association between HRVsd trend and somatisation change, undoing this association when it was combined with increasing HRV. Depression and anxiety could not be related to trends in HRV or HRVsd, which was related to observed floor effects. These results show that monitoring trends in daily HRV via wearables holds promise for automated stress monitoring and providing personalised feedback.

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Heart Rate Variability And Anxiety In Police Officers

PsycEXTRA Dataset ◽

10.1037/e507312017-001 ◽

2017 ◽

Author(s):

Michael E. Andrew ◽

Anna Mnatsakanova ◽

Luenda E. Charles ◽

Ja K. Gu ◽

Diane B. Miller ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Police Officers

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Mindfulness meditation, well-being, and heart rate variability: A preliminary investigation into the impact of intensive Vipassana meditation

International Journal of Psychophysiology ◽

10.1016/j.ijpsycho.2013.06.017 ◽

2013 ◽

Vol 89 (3) ◽

pp. 305-313 ◽

Cited By ~ 122

Author(s):

Jonathan R. Krygier ◽

James A.J. Heathers ◽

Sara Shahrestani ◽

Maree Abbott ◽

James J. Gross ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Mindfulness Meditation ◽

Preliminary Investigation ◽

Well Being ◽

Vipassana Meditation ◽

The Impact

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THE IMPACT OF STRESS ON HEART RATE VARIABILITY OF ON-CALL PHYSICIANS

CHEST Journal ◽

10.1378/chest.128.4_meetingabstracts.277s-a ◽

2005 ◽

Vol 128 (4) ◽

pp. 277S

Author(s):

Stavros E. Mountantonakis ◽

Dimitrios A. Moutzouris ◽

Craig McPherson

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

The Impact

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Abstract P315: Increase in Stress May Contribute to Lower Heart Rate Variability in Healthy Young Subjects

Circulation ◽

10.1161/circ.125.suppl_10.ap315 ◽

2012 ◽

Vol 125 (suppl_10) ◽

Author(s):

Amanda C Costa ◽

Ana Gabriela C Silva ◽

Cibele T Ribeiro ◽

Guilherme A Fregonezi ◽

Fernando A Dias

Keyword(s):

Cardiovascular Disease ◽

Heart Rate ◽

Heart Rate Variability ◽

Healthy Volunteers ◽

Perceived Stress ◽

Low Frequency ◽

Statistical Correlation ◽

Total Power ◽

The Impact ◽

Nonparametric Correlation

Background: Stress is one of the risk factors for cardiovascular disease and decreased heart rate variability is associated to increased mortality in some cardiac diseases. The aim of the study was to assess the impact of perceived stress on cardiac autonomic regulation in young healthy volunteers. Methods: 35 young healthy volunteers (19 to 29 years old, 6 men) from a Brazilian population were assessed for perceived stress by the translated and validated Perceived Stress Scale (PSS, 14 questions) and had the R-R intervals recorded at rest on supine position (POLAR RS800CX) and analyzed (5 minutes, Kubius HRV software) by Fast-Fourier Transform for quantification of Heart Rate Variability (HRV). Results: Average data (±SD) for age, heart rate, BMI, waist circumference and percentage of body fat (%BF) were: 21.3±2.7 years; 65.5±7.9 bpm; 22.3±1.9 Kg/m 2 ; 76.0±6.1 cm and 32.1±6.6%; respectively. The mean score for the PSS-14 was 23.5±7.2 and for the HRV parameter as follow: SSDN=54.8±21.2ms; rMSSD=55.9±32.2ms; low-frequency (LF)= 794.8±579.7ms 2 ; High-frequency (HF)= 1508.0±1783.0 ms 2 ; LF(n.u.)= 41.1±16.2; HF(n.u.)= 58.9±16.2; LF/HF=0.89±0.80 and Total power (TP)= 3151±2570ms 2 . Spearman nonparametric correlation was calculated and there was a significant correlation of PSS-14 scores and LF (ms 2 ) (r=−0.343; p= 0.044). Other HRV variables did not shown significant correlation but also had negative values for Spearman r (TP r=−0.265, p=0.124; HF r=−0.158; SSDN r=−0.207; rMSSD r=−0.243, p=0.160). LF/HF and LF(n.u.) did not correlate to PSS-14 having Spearman r very close to zero (LF/HF r=−0.007, p=0.969; LF(n.u.) r=−0.005, p=0.976). No correlation was found for HRV parameters and BMI and there was a trend for statistical correlation of %BF and LF (ms 2 ) (r=−0.309, p=0.071). Conclusions: These data demonstrate a possible association of perceived stress level and HRV at rest. Changes in LF can be a consequence of both sympathetic and parasympathetic activity, however, analyzing the other variables HF, TP, SSDN and rMSSD (all negative Spearman r) and due to the lack of changes in LF/HF ratio and LF(n.u.) we interpret that increased stress may be associated to decrease in overall heart rate variability. These changes were seen in healthy individuals and may point out an important mechanism in cardiovascular disease development.

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