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BMC Nursing
Erschienen in:

Open Access 01.12.2024 | Research

The impact of working night shifts on cardiac autonomic nervous regulation during the six-minute walk test in nurses

verfasst von: Taihe Zhan, Xiumei Wei, Ziying Zhang, Zhimin Shi, Hongyan Xie, Xiaotao Ma, Suyue Pan, Daogang Zha

Erschienen in: BMC Nursing | Ausgabe 1/2024

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Abstract

Background

Clinical nurses frequently face the necessity of working night shifts, often with insufficient opportunities for timely sleep recovery, which may negatively impact autonomic nervous system regulation. The aim of this study was to evaluate changes in heart rate variability (HRV) after the six-minute walk test (6MWT) in nurses post-night shift and to explore the impact of night shift work on cardiac autonomic regulation.

Methods

Thirty-five female nurses, with a mean age of 28.7 years (range 21.0–37.0 years), participated in this study. On the first and second mornings after a night shift, the nurses performed the 6MWT. During the test, electrocardiogram (ECG) signals, blood pressure, and walking distance were recorded simultaneously.

Results

Compared with the second postshift morning, on the first postshift morning, nurses presented higher ratings of perceived exertion (RPE), higher Borg scale scores, and a slower pulse rate before and after the 6MWT but covered a shorter walking distance. Additionally, HRV indicators such as the SDNN, RMSSD, pNN50, TP, VLF, LF, and HF were all higher on the first postshift morning. Regarding the amplitude of cardiac autonomic nervous regulation, variations in the RMSSD and pNN50 were both greater during the 6MWT on the first postshift morning, although there was no significant difference in post-6MWT recovery.

Conclusions

Night shifts appear to increase the activity of the autonomic nervous system in nurses on the first postshift morning and exert a greater inhibitory effect on parasympathetic activity during the 6MWT. Therefore, it is important to ensure timely recovery sleep and improve autonomic regulation after working night shifts.

Keywords

Heart rate variability; Night shift; Autonomic nervous system; Six-minute walk test; Nurses.

Trial registration

This study was retrospectively registered in the Clinicaltrials.gov. Registration Date: August 1, 2024. Clinicaltrials.gov ID: NCT06542510.
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Hinweise

Supplementary Information

The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s12912-024-02563-y.
Taihe Zhan and Xiumei Wei contributed equally to this work.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

With the globalization of the economy, there is an increasing demand for 24-hour continuous service, leading to more people engaging in shift work [1, 2]. Studies from 2014 showed that approximately 15–30% of Europeans and Americans are involved in shift work, with this trend on the rise, raising concerns about health issues related to shift work [1, 3]. Notably, in 2017, literature reported that more than 35% of individuals in healthcare occupations in the United States (US) work shifts at times other than during the day [4]. Research indicates that working night shifts is associated with an increased risk of developing coronary heart disease (CHD) and a modest reduction in the likelihood of healthy aging in nurses [5‐7]. Additionally, studies have shown that nurses experience neuroautonomic dysregulation during sleep following night shifts, which is measurable by heart rate variability (HRV) [8]. Owing to the lack of long-term outcome data, it remains unclear whether changes in HRV are associated with the prevalence and mortality of cardiovascular diseases among night shift nurses [9].
HRV is used to assess cardiac autonomic nervous system activity by measuring heart rate over time, which indirectly reflects cardiac sympathetic activity, parasympathetic activity, and the balance between them [10, 11]. A 2022 study applied HRV to assess workplace stress in nurses [12]. Furthermore, as early as 2011, researchers applied HRV to evaluate the sympathomodulatory effects of Saam acupuncture on night shift nurses [13]. HRV includes both time- and frequency-domain analyses [14]. The standard deviation of normal to normal R-R intervals (SDNNs) reflects the activities of both the sympathetic nervous system (SNS) and parasympathetic nervous system (PNS), whereas the root mean square of the successive differences (RMSSD) and the percentage of intervals > 50 ms different from the preceding interval (pNN50) are used to evaluate vagal activity [10]. Low frequency (LF) represents both sympathetic and parasympathetic activity, high frequency (HF) represents parasympathetic activity, the LF/HF ratio is the most sensitive indicator of sympathovagal balance, and total power (TP) reflects general autonomic, sympathetic activity and parasympathetic activity [10].
There are few studies on shift-work-related HRV. Research has indicated that shift work can lead to an imbalance in the autonomic nervous system of male blue-collar workers, reducing their HRV during sleep [15]. Aprajita Panwar et al. reported that night shift nurses exhibited increased markers of sympathetic activity during sleep and decreased markers of vagal activity compared to morning shift nurses, indicating autonomic dysregulation [16]. Additionally, Tobaldini et al. reported that when HRV was used as a research method, sympathetic activity was predominant, parasympathetic activity was weakened after working night shifts, and the neural response amplitude of a 10-minute tilt table test following a night shift was lower than that of rest days [17]. In 2018, Rossana Borchini et al. linked work stress to the occurrence of cardiovascular disease by using HRV to assess autonomic nervous system disorders in nurses working shifts [18]. However, other studies suggest that HRV is not significantly impacted by shift work [19]. The discrepancies in previous clinical studies on the relationship between shift work status and HRV may be due to various factors, such as physiology, pathology, lifestyle, environmental factors, and research conditions [20, 21].
In reality, some medical staff do not catch up on sleep immediately after working night shifts for various reasons; instead, they engage in other activities. The potential impact of this behavior on the regulation of the autonomic nervous system has rarely been studied. Tobaldini et al. assessed autonomic regulation of stress by measuring changes in HRV through a head-up tilt test conducted after working night shifts [17]. However, in real-world scenarios, there are few activities similar to the orthostatic tilt test performed by medical staff after working night shifts, making it essential to find alternative activities that closely mimic reality to assess autonomic stress regulation. The six-minute walk test (6MWT) is a widely used and easily administered test that effectively reflects cardiopulmonary function and closely mimics everyday activities [22, 23]. Physiological stress responses occur during the 6MWT, and HRV can reflect the activity of both the sympathetic and vagal nerves in response to this stress. A previous study used HRV to assess changes in autonomic regulation during the 6MWT [24]. Therefore, we measured HRV before, during, and after the 6MWT to assess the ability of autonomic nerves to regulate stress. We hypothesize that differences in autonomic regulation will be observed among shift work nurses during the 6MWT between the first and second post-shift mornings, and that these differences could be quantified using HRV. The aim of this study was to provide a scientific basis for instructing night shift staff on their schedules and developing corresponding interventions.

Methods

Participants and procedures

This was a prepost self-controlled clinical study. The participants were nurses from Nanfang Hospital of Southern Medical University who worked ward shifts. The nurses in this study had one night shift every 5–10 days, from 00:00 a.m. to 8:00 a.m., followed by 2–3 days off. This study focused on the effects of night shifts on autonomic neuromodulation, as measured by HRV changes.
The process of subject selection is shown in section A of Fig. 1. Female nurses aged ≥ 18 years who had undergone annual physical examinations, did not have serious cardiopulmonary diseases, and were able to walk normally were considered for inclusion in the study. The exclusion criteria were as follows:
Note: CRF, case report form; 6MWT, six-minute walk test; HRV, heart rate variability.
(i)
Having children at home who require night care;
 
(ii)
Current pregnancy;
 
(iii)
Engaging in activities that significantly impact heart rate, such as sexual activity, 24 h before and 24 h after working night shifts;
 
(iv)
History of thyroid dysfunction, hypertension, diabetes, CHD, etc.;
 
(v)
Experiencing upper respiratory tract infection, fever, cough, diarrhea, or other illnesses within 1 week before the planned enrollment;
 
(vi)
Consuming coffee or strong tea, smoking, drinking alcohol, or using other substances that affect heart rate 3 days before the planned enrollment;
 
(vii)
Taking β-receptor blockers, sleeping pills, psychotropic drugs, or other medications that affect heart rate; and.
 
(viii)
Judged by the investigator to be unsuitable for participation in this study.
 
Written informed consent was obtained from all participants, and the subjects received a subsidy of RMB 50 for each completed follow-up visit. This study protocol was approved by the Ethics Committee of Nanfang Hospital of Southern Medical University in China (NFEC-2024-064).

Sample size calculation

In accordance with the results of a previous study [17], specifically HF, the sample size was estimated via PASS 2021 software. Tests for paired means (stimulation) were used with α = 0.05, a test power of 0.9, δ0 = 0, δ1 = 24, and a standard deviation of 37. The necessary sample size was determined to be 28 participants; therefore, to account for a 20% attrition rate, the overall sample size was set to 35.

Data collection

After enrollment, the participants provided information such as age, marital status, height, weight, body mass index (BMI), history of alcohol consumption, tea and coffee consumption history, smoking history, and sleep duration and quality before and after working night shifts.
On the first and second mornings after the night shift, the participants fasted and arrived at the research office of the Department of General Medicine, Nanfang Hospital, Southern Medical University, before 10:00 a.m. They filled out personal information forms, and the investigators introduced the trial process, measured, and recorded the participants’ body temperature, blood pressure, and pulse rate while standing at rest. At each follow-up visit, the participants followed the trial process shown in section B of Fig. 1.

Data recording

This step involved recording the participants’ blood pressure, pulse rate, electrocardiogram (ECG) information, and 6MWT distance.
(i)
Following the product instructions for the Diagnostic Monitoring Software (DMS) CardioScan Holter System 300–4 A recorders, the investigator cleaned the skin where the electrodes were attached, placed 10 electrode stickers, and connected the leads.
 
(ii)
Participants stood at rest for 3 min to measure their blood pressure and pulse rate via a Microlife automatic arm-type electronic sphygmomanometer (BP3MV1-1E). ECGs were then collected while the participants stood for an additional 6 min (stage 1).
 
(iii)
Participants performed the 6MWT in a 30-meter-long corridor while ECGs were collected for 6 min (stage 2).
 
(iv)
At the end of the 6MWT, the participants stood at rest for 6 min, and ECGs were collected simultaneously (stage 3).
 
(v)
Blood pressure and pulse rate were measured again via the BP3MV1-1E while the participants were in an upright position.
 
(vi)
The total 6MWT distance was measured with a flexible measuring tape.
 
(vii)
Participants completed the Borg scale and rating of perceived exertion (RPE) scale [25, 26]. Both the Borg scale and the RPE scale were assessed before and after the 6MWT. The Borg scale evaluates the degree of dyspnea, with scores ranging from 0 to 10, where higher scores indicate more severe dyspnea. In contrast, the RPE scale ranges from 6 to 20, with higher scores reflecting greater levels of fatigue.
 

Digital analysis

The ECGs from each stage were automatically analyzed via commercially available Holter software (DMS CardioScan 12.0; DM Software, Stateline, NV, USA). The software detected R waves, and manual rechecks were performed to correct any leakage analysis or misidentified waveforms. The software was then used to analyze HRV-related indicators and provide the data. HRV indicators from stages 1 to 3 were entered into the case report form (CRF) by one investigator and rechecked by another investigator. The difference in HRV between stage 2 and stage 1 was calculated as the delta-1 HRV, and the difference between stage 3 and stage 2 was calculated as the delta-2 HRV.

Statistical analysis

All the statistical analyses were conducted via SPSS version 26.0 software (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize the basic characteristics of the study subjects. Continuous data are presented as the means ± standard deviations. Paired t-tests were used for normally distributed data, whereas Mann‒Whitney U tests were applied for nonnormally distributed data. For all analyses, a p value < 0.05 was considered to indicate statistical significance.

Results

General characteristics of subjects

The general data of the participants are shown in Table 1. The average age of the nurses who participated in the study was 28.7 ± 4.3 years, with a BMI of 21.6 ± 2.3 kg/m², and 13 (37.1%) of them were married. None of the participants smoked or drank alcohol. Five participants had a history of tea consumption, and seven had a history of caffeine consumption. The duration of night shift work for the nurses was 6.0 ± 4.1 years, with a frequency of night shifts every 6.6 ± 1.5 days.
Table 1
Clinical features of the study population
 
N (%)
Mean
SD
Range
Marital status (married)
13 (37.1)
   
Smoking status
0 (0)
   
Alcohol consumption status
0 (0)
   
Caffeine consumption (years)
7 (20.0)
0.5
1.2
0.0–5.0
Tea consumption (years)
5 (14.3)
0.4
1.1
0.0–5.0
Age (years)
 
28.7
4.3
21.0–37.0
Weight (kg)
 
55.9
5.8
43.0–67.0
Height (cm)
 
161.1
4.6
152.0–170.0
BMI (kg/m2)
 
21.6
2.3
17.4–27.8
Duration of night shift work (years)
 
6.0
4.1
1.0–15.0
Frequency of night shifts (days)
 
6.6
1.5
5.0–10.0
Sleep duration before night shift (hours)
 
9.9
2.1
6.0–15.0
Number of arousals before night shift
 
1.8
1.3
0.0–6.0
Sleep quality before night shift (0–10)
 
6.6
1.7
3.0–10.0
Intensity of night shift work (0–10)
 
6.5
2.4
1.0–10.0
Sleep duration after night shift (hours)
 
11.4
2.3
6.5–16.0
Number of arousals after night shift
 
2.4
1.8
0.0–10.0
Sleep quality after night shift (0–10)
 
6.9
1.9
3.0–10.0
BMI body mass index, SD standard deviation

General 6MWT results

The changes in blood pressure, pulse rate, Borg scales, RPE scales, and 6MWT distance between the two 6MWTs are shown in Table 2. Compared with that in the first 6MWT, the distance covered in the second 6MWT was significantly greater (p = 0.009). Both before and after the 6MWT, the RPEs in the first 6MWT were greater than those in the second 6MWT (p = 0.032 and p = 0.003, respectively). For the Borg scale, the first 6MWT score was greater than the second 6MWT score both before and after the test (p = 0.005 and p = 0.004, respectively). Additionally, the pulse rate was lower in the first 6MWT than in the second 6MWT both before and after the test (p = 0.044 and p = 0.003, respectively). There was no statistically significant difference in systolic blood pressure, diastolic blood pressure, or their changes before and after the two 6MWTs.
Table 2
General information concerning the 6MWT
Variable
First 6MWT
Second 6MWT
P
 
Mean
SD
Mean
SD
 
Walking distance (meters)
560.1
56.1
576.4
54.8
0.009**
RPE before 6MWT
13.6
3.4
12.3
2.4
0.032*
RPE after 6MWT
15.2
2.8
13.8
2.7
0.003**
Delta RPE
1.6
2.4
1.5
2.0
0.947
Borg before 6MWTa
1.2
1.5
0.5
0.8
0.005**
Borg after 6MWTa
1.9
1.7
1.2
1.0
0.004**
Delta Borga
0.7
0.7
0.6
0.7
0.533
SBP before 6MWT (mmHg)
106.9
9.4
106.5
8.8
0.793
SBP after 6MWT (mmHg)
107.9
9.4
108.7
9.9
0.611
Delta SBP
1.0
6.8
2.2
8.9
0.531
DBP before 6MWT (mmHg)
75.1
6.9
73.9
7.6
0.245
DBP after 6MWT (mmHg)
77.1
7.9
76.8
7.0
0.808
Delta DBP
1.9
5.4
2.8
6.0
0.535
Pulse rate before 6MWT (bpm)
79.0
10.7
83.1
11.0
0.044*
Pulse rate after 6MWT (bpm)
86.5
10.9
91.2
10.9
0.003**
Delta pulse rate
7.5
7.0
8.1
7.6
0.655
aWilcoxon signed rank test, 6MWT six-minute walk test, SD standard deviation, RPE rating of perceived exertion, SBP systolic blood pressure, DBP diastolic blood pressure, bpm beat per minute, *p < 0.05, ** p < 0.01

HRV during stage 1 of the 6MWT

The HRV of the subjects before the 6MWT was greater on the first postshift morning than on the second postshift morning (Table 3). In stage 1 of the first 6MWT, the SDNN and TP were greater than those in stage 1 of the second 6MWT (p = 0.001 and p = 0.020, respectively). The RMSSD and pNN50 were significantly greater during stage 1 of the first 6MWT than during stage 1 of the second 6MWT (p = 0.001 and p = 0.006, respectively). VLF, LF, and HF were also greater in stage 1 of the first 6MWT than during that of the second 6MWT (p = 0.042, p = 0.023 and p = 0.011, respectively). There was no statistically significant difference in the LF/HF ratio between the two 6MWTs.
Table 3
HRV during the 6MWT
Variable
First 6MWT
Second 6MWT
P
 
Mean (SD)
Mean (SD)
 
Stage 1
 SDNN (ms)
50.3 (20.7)
39.7 (13.5)
0.001**
 RMSSD (ms)
28.9 (28.5)
20.1 (9.1)
0.001**
 pNN50 (%)
6.2 (10.2)
2.6 (4.6)
0.006**
 TP (ms2)
1727.5 (1268.4)
1184.8 (1083.4)
0.020*
 VLF (ms2)
1195.1 (982.3)
838.4 (847.8)
0.042*
 LF (ms2)
411.8 (325.2)
279.9 (247.1)
0.023*
 HF (ms2)
110.9 (117.9)
60.8 (57.6)
0.011*
 LF/HF
6.2 (7.2)
7.1 (6.6)
0.169
Stage 2- Stage 1
 Delta1-SDNN (ms)
9.3 (29.0)
17.7 (18.4)
0.130
 Delta1-TP (ms2)
241.7 (2451.5)
336.6 (2350.6)
0.706
 Delta1-RMSSD (ms)
−15.2 (26.5)
−7.0 (8.9)
0.014*
 Delta1-pNN50 (%)
−5.6 (9.4)
−1.7 (4.3)
0.004**
 Delta1-HF (ms2)
−92.9 (114.4)
−48.8 (56.6)
0.053
 Delta1-LF (ms2)
−315.8 (301.0)
−228.6 (240.8)
0.080
 Delta1-VLF (ms2)
655.8 (2267.1)
616.4 (2289.0)
0.909
 Delta1-LF/HF
−1.0 (8.0)
−2.2 (6.6)
0.061
Stage 3- Stage 2
 Delta2-SDNN (ms)
8.0 (17.2)
6.5 (16.6)
0.596
 Delta2-TP (ms2)
−584.6 (2768.1)
−228.0 (2734.0)
0.302
 Delta2-RMSSD (ms)
2.0 (5.0)
3.7 (11.1)
0.510
 Delta2-pNN50 (%)
0.5 (1.4)
1.1 (5.1)
0.857
 Delta2-HF (ms2)
19.8 (33.2)
21.5 (40.1)
0.762
 Delta2-LF (ms2)
136.0 (268.5)
144.2 (261.2)
0.731
 Delta2-VLF (ms2)
−741.8 (2579.0)
−395.4 (2572.5)
0.342
 Delta2-LF/HF
1.7 (5.9)
2.2 (4.7)
0.550
Results derived from Wilcoxon signed rank test, HRV heart rate variability, 6MWT six-minute walk test, SD standard deviation, SDNN standard deviation of normal to normal R-R intervals, RMSSD root mean square of the successive differences, pNN50 percentage of intervals > 50 ms different from the preceding interval, TP total power, VLF very low frequency, LF low frequency, HF high frequency, Stage 1, six minutes before the 6MWT, Stage 2, six minutes during the 6MWT, Stage 3, six minutes after the 6MWT, *p < 0.05, ** p < 0.01

Delta HRV during the 6MWT

The changes in the HRV values before and after the two 6MWTs are detailed in Table 3. The delta-1 RMSSD was greater in the first 6MWT than in the second 6MWT (p = 0.014). Delta-1 pNN50 was also greater in the first 6MWT (p = 0.004). Additionally, delta-1 HF showed a similar trend to the delta-1 RMSSD and delta-1 pNN50 (p = 0.053). When the delta-2 HRV was compared, no statistically significant difference was found between the two 6MWTs. Line charts were used to illustrate the trends in the HRV at different stages and to plot the differences between the first and second 6MWTs (Fig. 2).
Note: HRV, heart rate variability; 6MWT, six-minute walk test; TP, total power; HF, high frequency; LF, low frequency; VLF, very low frequency; SDNN, standard deviation of normal to normal R‒R intervals; RMSSD, root mean square of the successive differences; pNN50, percentage of intervals >50 ms different from the preceding interval; Stage 1, six minutes before the 6MWT; Stage 2, six minutes during the 6MWT; Stage 3, six minutes after the 6MWT; * p < 0.05, ** p < 0.01.

Discussion

In this study, the effect of working night shifts on HRV was evaluated in 35 female nurses, and the impact of night shift work on stress regulation was further explored via the 6MWT. The HRV indicators were generally greater on the first postshift morning than on the second morning. Specifically, on the first postshift morning, the vagal response was more inhibited during the stressful stimulation of the 6MWT than on the second morning.
While a previous study showed that HRV is more susceptible to the effects of night shifts in males than in females [27], our study revealed significant differences in female participants as well, suggesting that sex may not be the main influencing factor. Other underlying factors, such as lifestyle habits, including smoking status and sleep patterns, could also contribute [27, 28]. Individuals of different genders may exhibit varying lifestyles [29], and these lifestyle differences may influence HRV, resulting in distinct effects of night shifts across genders. Many current clinical studies on shift work and HRV often include males and females [19, 30]. In our study, all the participants were female and had no history of smoking or alcohol consumption, abstained from medications that could affect HRV for three days prior to the trial, and fasted on the day of the trial. These measures were taken to minimize potential confounding factors that could influence the study outcomes.
In line with the findings of Munakata, M et al., who reported that night shifts increase participants’ fatigue levels [31], we observed higher Borg and RPE values on the first morning after working a night shift than on the second morning, both before and after the 6MWT. Additionally, nurses walked a shorter distance on the first 6MWT than on the second 6MWT. Thomas Leti et al. found that senior runners who exhibited high fatigue scores after rest exhibited low sympathetic and high parasympathetic tone manifestation through HRV metrics, possibly due to psychological fatigue rather than solely physical fatigue [32]. Similarly, Ke Lu et al. found that LF/HF, reflecting the balance between parasympathetic and sympathetic activity, was an important indicator of fatigue through systematic review analysis [33]. They also found that SDNN, VLF, and LF were elevated in subjects with fatigue due to sleep deprivation [33]. Furthermore, it has been suggested that fatigue activates the parasympathetic nervous system, resulting in increased HF levels when subjects struggle to remain awake, which, in turn, leads to sympathetic activation and an increase in LF [34]. In our study, nurses exhibited increased sympathetic and parasympathetic tones after night shifts, possibly due to physical and psychological fatigue from working overnight, and they struggled to stay awake at work all night. Notably, we found that both before and after the 6MWT, the pulse rate was lower and the HRV was greater on the first postshift morning than on the second morning. This observation is consistent with the formula used to calculate HRV indices [35], suggesting the reliability of our overall data. Other studies have reported similar findings, with lower heart rates during night shifts than during day shifts and opposite trends in HRV [36, 37]. These differences may be attributed to reduced activity of the ascending arousal system, including the locus coeruleus, inhibition from the ventrolateral preoptic (VLPO) nucleus of the hypothalamus, and increased sleepiness among participants on the first postshift morning, resulting in relatively slower pulse rates and higher HRV [36].
Our study further revealed that LF and VLF on the first morning after working night shifts were greater than those on the second morning. Tobaldini, E et al. also noted a similar trend, although statistical significance was not reached, potentially due to differences in participant groups (10 males and 5 females) and their smaller sample size of 15 individuals [17]. Similarly, Wang, M et al. reported that the SDNN was greater after working night shifts than before, with increases in the RMSSD and HF (representing vagal activity) and a tendency for LF to increase, although statistical significance was not achieved [38]. These findings on LF/HF were also largely consistent with our results, which revealed no significant difference [38]. Lee, S et al. reported greater TP and pNN50 values in the nonsleeping state of night shift subjects than in those of day shift subjects [39], suggesting increased HRV-related indices after working night shifts, indicative of a relatively active autonomic nervous system [40].
Our study demonstrated that, on the first morning after working night shifts, the HRV indices were greater, indicating increased autonomic nervous system activity, than they were on the second morning after working night shifts. Moreover, the degree of downregulation of the RMSSD and pNN50 during the 6MWT stress was more pronounced on the first morning after working night shifts, suggesting greater vagus nerve inhibition. Bonete, G et al. previously reported that diabetic patients exhibited lower HRV before, during, and after the 6MWT than nondiabetic patients did, although changes before and after the 6MWT were not statistically analyzed [24]. Additionally, studies have shown that individuals with type 2 diabetes aged 60–70 years are at increased risk of experiencing cardiovascular mortality, with relatively lower HRV indices possibly linked to the development of cardiac autonomic neuropathy [41]. J M Dekker et al. found that low HRV was associated with an increased risk of CHD [42], and Yasuhiko Kubota et al. found that greater HRV was modestly associated with lower lifetime cardiovascular disease risk [43]. In addition, some studies have found that night shifts increased the risk of CHD [5, 44]. However, our study revealed that nurses exhibited relatively high HRV after night shifts, which may contrast with previous findings that lower HRV is associated with an increased risk of CHD and that CHD risk is associated with night shifts; this finding underscores the necessity to consider that HRV may vary across different populations and physiological conditions if it is to be explored as a potential predictor of CHD in the future.
Our findings highlight that performing a 6MWT on the first postshift morning resulted in greater vagus nerve inhibition than it did on the second morning. Enhanced vagus nerve inhibition and increased sympathetic nerve excitation may lead to elevated cardiovascular event risks, posing potential health hazards [45]. Therefore, timely recovery from sleep following night shifts and adjustment of the autonomic state are crucial. Unfortunately, few clinical studies have investigated the long-term effects of inadequate recovery sleep after working night shifts.
The limitations of this study include its relatively narrow age range and exclusively female participant cohort, which restricts the generalizability of our findings. The study was conducted solely in women, and the potential influence of hormonal changes during the menstrual cycle on HRV could not be fully accounted for. Despite these limitations, our results clearly indicate that the autonomic nervous system exhibits increased activity after working night shifts, with stronger parasympathetic inhibition during submaximal exercise, such as the 6MWT, potentially leading to increased cardiovascular event risks. Moreover, our findings have practical implications for nurse scheduling and the development of evidence-based fatigue management strategies, which could help reduce the health risks associated with night shift work. Future research should explore the long-term cardiovascular health consequences of night shift work, particularly in relation to the cumulative effects of inadequate recovery sleep. Investigating targeted interventions aimed at improving autonomic regulation in night shift nurses is also warranted to mitigate these adverse outcomes.

Acknowledgements

We would like to thank Miao Liu from the Department of Psychiatry and other nurses from the Department of General Practice for their assistance in spreading information about the study and recruiting interested subjects. Additionally, we express our gratitude to the subjects for their participation in and support of our research.

Declarations

The study proposal received approval from the Ethics Committee on Clinical Research at Nanfang Hospital (NFEC-2024-064). The study received informed consent from patients, and all data were fully de-identified.
Not applicable.

Competing interests

The authors declare no competing interests.
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Metadaten
Titel
The impact of working night shifts on cardiac autonomic nervous regulation during the six-minute walk test in nurses
verfasst von
Taihe Zhan
Xiumei Wei
Ziying Zhang
Zhimin Shi
Hongyan Xie
Xiaotao Ma
Suyue Pan
Daogang Zha
Publikationsdatum
01.12.2024
Verlag
BioMed Central
Erschienen in
BMC Nursing / Ausgabe 1/2024
Elektronische ISSN: 1472-6955
DOI
https://doi.org/10.1186/s12912-024-02563-y

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