Sleep quality and anxiety among nurses in tertiary hospitals in China and the influencing factors: A cross-sectional study

DOI: https://doi.org/10.21203/rs.3.rs-17774/v2

Abstract

Background: The purpose of the study was to investigate to understand the situation of sleep quality and anxiety among nurses in tertiary hospitals in China, and analyze their influencing factors.

Methods: A cross-sectional survey was performed for nurses in Beijing tertiary hospitals including Beijing Tongren hospital, Anzhen Hospital and Beijing Children Hospital. The Pittsburgh Sleep Quality Indes (PSQI) and Zung Self-Rating Anxiety Scale (SAS) were used to measured the sleep quality and anxiety symptoms, respectively. Survey of quality of life in nurses was measured by 36-item Short Form Health Survey (SF-36). Spearman’s correlations analysis and logistic regression analysis was used to understand the influencing factors with sleep disorder, anxiety symptoms and quality of sleep. Quality of life (both PCS and MCS) were affected by influencing factors including marital status, working years, education background, income monthly, working hours, regular diet, physical exercise, sleep disorder, anxiety symptoms, felling of stress, and stress from economic, social, occupational.

Results: 643 registered nurses in three tertiary hospitals were surveyed, 517 (80.4%) returned questionnaires were valid for analysis. The average PSQI score was 7.71±3.62, including 372 participants that scores were above 5 (72.0%). The average SAS score was 45.18±9.90,including 157 participants with a SAS score > 50 (30.4%) that had different anxiety symptoms. The nurses’ sleep quality were affected by some factors including income monthly, working hours, regular diet, physical exercise, stress from economic, social, occupational. Education background, income monthly, working hours, regular diet and economic stress, social stress, occupational stress have significantly related to anxiety symptoms. Correlation between sleep disorder and anxiety severity was positive for nurses.

Conclusions: The situation of sleep disorder and anxiety symptoms among nurses in tertiary hospitals in China were very serious. The problem has negative effect on physical and mental health in nurses which reminded hospital administrators should take preventive actions. In addition, the results of the study hinted that promotion of health lifestyle, effort-reward balance and providing social support may be significant to decrease the poor sleep quality and anxiety symptoms and increase quality of life in nurses.

Background

The status of physical and mental health have important effect for quality of life and work for medical staffs[1]. Clinical nurses, as an important medical group, maintain faster work pace and heavier workload for a long time that increase the risk of physical and mental health problem, including feeling stress, fatigue, burnout, anxiety, and decreasing the quality of life. However, as a negative result, poor sleep quality has becoming an obvious and complaint problem for nursing staff all over the world[2-5]. Shift work disorder, stressful workload and complex work environment had been studied that may be the main reasons of sleep problems for nurses[2,3,4,6].Poor sleep quality has negative effects for physical health such as metabolic disturbance, cardiometabolic disorders and chronic diseases[6-10].

Moreover, sleep problems for a long time also could result in serious effects for psychology and mental health including thought retardation, low spirit, irritability, depression and so on[11,12]. In fact, apart from impacting health of nurses, the previous studies have been improved that poor sleep quality could decrease the work performance and increase the risk of medical errors, impaired psychomotor performance over the past 40 years[13-18].

As we know, anxiety is an unpleasant emotion characterized by fear, worry, rumination[19].However, anxiety disorder is medical disease if it was persistent and intense[19]. Anxiety disorder has become a worldwide problem that we need focus on. Previous researches reported that one-eighth population of world may suffer from inappropriate anxiety[20].Some influencing factors were supposed like women,older age, urban,obese,and so on[21-22]. Previous studies also have indicated that nurses was a higher risk professional group that with anxiety disorder that others, 21% of Singapore general hospital nurses,20% of ICU and general care nurses in the US, 43.2% of shift-work nurses in Iranian have suffered from anxiety disorder, respectively[23-25].

Chinese hospitals are divided into three degrees(tertiary hospital;sencod-class hospital; class-I hospital) according to hospital scale, clinical staffs, work quality, technical facilities, etc. As of 2016, there were 2232 tertiary hospital(7.6% all kinds of hospitals in China). In 2016, there were 2213718 hospital beds(the proportion of all is 43.97% , this number was 40.71% in 2012) in Chinese tertiary hospitals and there were 1246308 registered nurses; and have provided high-quality medical care for 1627848 thousands of patients (the proportion of all is 49.78% , this number was 42.75% in 2012)[26]. As we know, tertiary hospital represents the highest medical care level in China, Chinese patients would like obtaining their clinical care no matter haw far and how long time spent in waiting. Therefore, nurses in Chinese tertiary hospitals were faced with heavy workload, stressful work environment and complex interpersonal relationship. Chinese studies indicated that the quality of life of nurses in Chinese tertiary hospital was facing great challenge[6,27-28].

Previous researches have shown that we should pay more attention to physical and mental health of clinical nurses.Nurses are encountering more stressful job and workload in tertiary hospital than that in secondary and first-level hospitals. Not only that, they were more possibility and risk for physical and mental health and medical errors. However, we do not know that clearly. Then, the purpose of our study was understanding the status and influencing factors of sleep quality, source of stress, mental health, quality of life and their correlation among nurses in tertiary hospitals in China. We also hope to offer some suggestion for improving their quality of life and work.

Methods

Participants

We selected three famous tertiary hospitals in China locating in Beijing into our cross-sectional survey that a lot of patients all over China were coming because of their high quality of medical care, including Beijing Children hospital,Beijing Tongren Hospital, and Anzhen hospital. We have surveyed 643 nurses by self-administered questionnaire from April to June in 2018, and 517 questionnaires were returned valid(80.4%). These 517 nurses were becoming our participants in our study.

Survey questionnaire

Our self-administered questionnaire consisted of five parts, including survey of basic information, source of stress, quality of sleep, anxiety and quality of life.

Basic information and source of stress

  The basic information of study contained sex; age; marital status; seniority; education level (junior college degree or below, bachelor degree or above); professional status ( primary, intermediate or above); monthly income; working hours per week, smoking , drinking, regular diet and physical exercise. We understood the subjective feeling of source of stress by the question “what do you think the main source of your stress? Economic stress, occupational stress, social stress, or other reason”.

Quality of sleep

  The Pittsburgh Sleep Quality Index(PSQI) is a valid and widely instrument to measure and assess the quality of sleep for the general and clinical populations over a 1-month period[29,30]. The Chinese version of Pittsburgh Sleep Quality Index(C-PSQI) had an good reliability and sensitivity using cutoff value of 5 that discriminate poor from good quality of sleep[30]. C-PSQI contain 19 items that are combined into 7 component scores including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, used sleep medication, daytime dysfunction[30]. The range of global score is from 0 to 21 summing 7 component scores, and higher scores represent the subjective quality of sleep is poorer[6,29,30].

Anxiety

  We measured the anxiety symptoms of our participants by the Zung Self-Rating Anxiety Scale(SAS) that has an good internal consistency and test-retest reliability[31-33]. There are 20 items gathered the scale, and every item has 4 options that scored different scores. The range of total raw score is from 20 to 80,or index score is from 25 to 100.The upper limit for the normal was a raw score 40 or index score 50, respectively. A higher score indicate higher level of anxiety symptoms. The study used the index score to measure the anxiety symptom. When the total index score ≥50 was defined as “mild anxiety symptom”, ≥60 that was moderate anxiety, ≥70 was severe anxiety according to Chinese version[34].

Quality of life

  In the study, we selected the 36-item Short Form Health Survey (SF-36) to evaluate the quality of life (QOL) for our participants. The SF-36 is also a reliable and effective measuring tool to assess QOL of patients and occupational populations [35-36]. The measurement contents of 8 dimensions constitute the scale, including physical function (PF), role physical (RP), bodily pain (BP), global health (GH), vitality (VT), social function(SF), role emotional (RE), mental health(MH). The range of scores of every dimension is from 0 to 100. The higher score represents the better possible health status. The scores of eight dimensions are summarized in physical component summary (PCS) and mental component summary (MCS) scores.

Statistical Analyses

  Firstly, we understood the status of quality of sleep, source of stress, anxiety and quality of life among our participants by descriptive statistical analysis. Secondly, Spearman’s correlations analysis was used to compare the scores of PSQI and SAS and the t-test and the analysis of variance (ANOVA) were used to compare the scores of SF-36 (the scores of PCS and MCS) among the factors about demographic characteristics, lifestyle, and felling of stress. The t-test was used to compare the scores of SF-36(PCS and MCS) between whether there is sleep disorder, and the analysis of variance (ANOVA) was used to compare that among different anxiety severity groups. Thirdly, Spearman’s correlations analysis was used to understand the relationship between sleep disorder and anxiety severity. Finally, logistic regression analysis was using to explore factors associated with sleep disorder and anxiety symptoms. SPSS version 20.0 was used to analysis the date in the study. All tests accepted the 5% significance level.

  

Results

Characteristics of participants

  All the participants of our study were female, and their average age was 30.49±7.53 years. The average PSQI score was 7.71±3.62, including 372 participants that scores were above 5 (72.0%). The average SAS score was 45.18±9.90,including 157 participants with a SAS score > 50 (30.4%) that had different anxiety symptoms. According our results, there were 334 nurses (64.6%) felling heavy or very heavy stress, and 355 nurses(68.7%) felling economic stress, 407 nurses (78.7%) felling occupational stress and 249 nurses(48.2%) felling social stress.

Influencing factors analysis related to quality of sleep

  Table 1 showed the results that different factors affected the quality of sleep. The nurses’ sleep quality were affected by some factors including income monthly, working hours, regular diet, physical exercise, stress from economic, social, occupational. However, we did not find the marital status, working years, education background, professional title, leader, smoking and alcohol consumption were significantly related to quality of sleep.

Influencing factors analysis related to anxiety symptoms 

  Results of influencing factors analysis showed education background, income monthly, working hours, regular diet and economic stress, social stress, occupational stress have significantly related to anxiety symptoms. Whereas marital status, working years, professional title, leader, smoking, alcohol consumption and physical exercise were not. The results were showed in Table 2.

Influencing factors analysis related to quality of life

  Table 3 indicated quality of life (both PCS and MCS) were affected by influencing factors including marital status, working years, education background, income monthly, working hours, regular diet, physical exercise, sleep disorder, anxiety symptoms, felling of stress, and stress from economic, social, occupational. However, smoking, alcohol consumption and leader were not. Professional title was significant related to MCS, but not to PSC.

The relationship between sleep disorder and anxiety severity

  Correlation between sleep disorder and anxiety severity was positive for nurses. The result was showed in Table 4.

Logistic regression analysis of multiple factors influencing sleep disorder

  Table 5 showed that physical exercise, regular diet and income monthly have independent influence with sleep disorder for nurses. In other words, physical exercise frequency, keeping regular diet and salary suitably were positive factors for preventing sleep disorder for nurses.

Logistic regression analysis of multiple factors influencing anxiety symptoms

  Table 6 showed that anxiety symptoms revealed an independent relevance with education background, working hours, regular diet, economic stress. In other words, the risk factors for anxiety in nurses were higher education background, longer working hours, irregular diet and economic stress.

Table 1 Influencing factors analysis related to quality of sleep (N=517)

Demographic characteristics

Number of participants without Sleep disorder

Number of participants with sleep disorder 

P value

Marital status

Married/cohabitation

75

223

0.089

 

Unmarried/divorced

/widowed

70

149

Working years 

5 years

64

130

0.288

 

6-10 years

20

75

 

11-15 years

24

70

 

15-20 years

14

35

 

20 years

23

62

Education background

Junior college

 or below

64

145

0.283

 

Bachelor degree or above

81

227

Professional title

Junior 

105

244

0.137

 

Medium-grade or above

40

128

leader

Yes

9

14

0.226

 

No 

136

358

Income monthly(RMB)

5000

37

31

0.000

 

5000-10000

99

325

 

10000 

9

16

Working hours a week

40H

88

172

0.000

 

41-56H

55

190

 

56H

2

9

Smoking 

Yes

2

12

0.244

 

No 

143

359

Alcohol consumption

Yes

8

24

0.701

 

No 

134

342

Regular diet

Yes 

85

142

0.000

 

General 

52

168

 

no

8

62

Physical exercise

3 or more times a week

21

14

0.000

 

1-2 times a week

41

98

 

No 

83

260

Economic stress

No 

55

107

0.044

 

Yes

90

265

Occupational stress

No 

41

69

0.000

 

Yes

104

303

Social stress

No 

86

182

0.034

 

Yes

59

190

 

 

Table 2 Influencing factors analysis related to anxiety symptoms (N=517)

Demographic characteristics

Number of participants without anxiety symptom

Number of participants with anxiety symptom

P value

Marital status

Married/cohabitation

198

100

0.066

 

Unmarried/divorced

/widowed

162

57

Working years 

5 years

149

45

0.089

 

6-10 years

61

34

 

11-15 years

64

30

 

15-20 years

32

17

 

20 years

54

31

Education background

Junior college or below

158

51

0.015

 

Bachelor degree or above

202

106

Professional title

Junior 

247

102

0.416

 

Medium-grade or above

113

55

leader

yes

16

7

0.994

 

no

344

150

Income monthly(RMB)

5000

56

12

0.019

 

5000-10000

284

140

 

10000 

20

5

Working hours a week

40H

199

61

0.000

 

41-56H

157

88

 

56H

4

7

Smoking 

Yes

7

7

0.107

 

No 

352

150

Alcohol consumption

Yes

24

8

0.514

 

No 

331

145

Regular diet

Yes 

175

52

0.003

 

General 

144

76

 

No

41

29

Physical exercise

3 or more times a week

28

7

0.250

 

1-2 times a week

100

39

 

No 

232

111

Economic stress

No 

126

36

0.007

 

Yes

234

121

Occupational stress

No 

85

25

0.050

 

Yes

275

132

Social stress

No 

198

70

0.029

 

Yes

162

87

 

 

Table 3 Influencing factors analysis related to quality of life (N=517)

Demographic  characteristics

N

PCS

P value

MCS

P value

Marital status

 

 

 

 

 

Married/cohabitation

298

68.13±17.99

0.000

63.15±18.94

0.000

Unmarried/divorced/widowed

219

76.41±16.48

70.33±16.97

Working years

 

 

 

 

 

5 years

194

76.83±16.00

0.000

70.99±17.06

0.000

6-10 years

95

65.66±16.83

59.94±17.80

11-15 years

94

70.56±18.80

65.97±17.42

15-20 years

49

69.49±17.33

61.23±21.45

20 years

85

68.89±19.19

65.30±18.94

Education background

 

 

 

 

 

Junior college or below

209

75.11±16.83

0.000

70.71±16.83

0.000

Bachelor degree or above

308

69.28±18.04

63.18±18.72

Professional title

 

 

 

 

 

Junior 

349

72.06±18.08

0.439

67.33±18.39

0.042

Medium-grade or above

168

70.76±17.29

63.81±18.43

leader

 

 

 

 

 

Yes

23

74.70±14.23

0.399

68.93±13.03

0.467

No 

494

71.49±17.97

66.06±18.67

Income monthly(RMB)

 

 

 

 

 

5000

68

81.48±17.83

0.000

74.26±18.38

0.000

5000-10000

424

69.53±17.35

64.61±18.25

10000 

25

80.59±14.02

70.96±16.14

Working hours a week

 

 

 

 

 

40H

260

75.04±17.06

0.000

69.60±16.93

0.000

41-56H

245

68.89±17.81

63.43±18.88

56H

11

52.83±15.17

44.97±20.90

Smoking

 

 

 

 

 

Yes

14

66.84±15.83

0.306

57.89±16.36

0.086

No 

502

71.80±17.88

66.47±18.46

Alcohol consumption

 

 

 

 

 

Yes

32

72.75±14.17

0.764

60.90±17.38

0.103

No 

476

71.78±17.91

66.42±18.58

Regular diet

 

 

 

 

 

Yes 

227

74.92±17.73

0.000

69.19±18.58

0.000

General 

220

70.09±17.78

65.66±17.44

no

70

65.84±16.28

58.14±18.90

Physical exercise

 

 

 

 

 

3 or more times a week

35

78.34±19.50

0.019

73.06±20.19

0.034

1-2 times a week

139

73.22±20.19

67.34±16.95

No 

343

70.31±17.70

65.02±18.74

Anxiety symptoms

 

 

 

 

 

No 

360

77.37±15.29

0.000

72.25±15.54

0.000

Mild

116

62.12±15.21

55.59±15.58

Moderate 

34

48.79±15.31

44.31±18.14

severe

7

45.52±11.02

36.51±16.71

Sleep disorder

 

 

 

 

 

Yes

372

68.20±17.46

0.000

62.23±18.20

0.000

No 

145

80.44±15.64

76.33±14.98

Felling stress

 

 

 

 

 

Very heavy

124

63.43±17.15

0.000

57.78±19.42

0.000

Heavy

210

69.90±18.28

64.10±17.66

General 

175

78.91±14.56

73.84±15.38

Little

4

78.53±11.99

84.24±9.27

Very little

4

91.96±12.00

83.89±11.47

Economic stress

 

 

 

 

 

Yes

355

70.04±17.60

0.002

64.41±18.61

0.001

No 

162

75.13±17.86

70.08±17.58

Occupational stress

 

 

 

 

 

Yes

407

70.08±18.06

0.000

64.74±18.84

0.001

No 

110

77.40±15.68

71.56±15.95

Social stress

 

 

 

 

 

Yes

249

69.12±17.29

0.002

63.24±18.79

0.000

No 

268

73.97±18.02

68.93±17.75

 

Table 4 Correlation between sleep disorder and anxiety severity for nurses

Anxiety severity

NO. of subjects with Sleep disorder

X2

P value

NO

YES

No 

134

226

50.81

0.000

Mild

11

105

Moderate 

0

34

severe

0

7

 

Table 5 logistic regression analysis of multiple factor influencing quality of sleep 

Demographic characteristics

B

S.E.

P

OR

95%CI for OR

lower

upper

Physical exercise

 

 

 

 

 

 

3 or more times a week

 

 

 

1.000

 

 

1-2 times a week

-1.267

0.386

0.001

0.282

0.132

0.600

No 

-0.008

0.239

0.972

0.992

0.620

1.585

Regular diet

 

 

 

 

 

 

Yes 

 

 

 

1.000

 

 

General 

-1.484

0.417

0.000

0.227

0.100

0.513

no

-0.938

0.422

0.026

0.392

0.171

0.896

Income monthly(RMB)

 

 

 

 

 

 

5000

 

 

 

1.000

 

 

5000-10000

-1.021

0.504

0.043

0.360

0.134

0.966

10000 

0.281

0.451

0.533

1.325

0.548

3.204

 

 

Table 6 Logistic regression analysis of multiple factor influencing anxiety symptom

Demographic characteristics

B

S.E.

P

OR

95%CI for OR

lower

upper

Education background

 

 

 

 

 

 

Junior college or below

 

 

 

1.000

 

 

Bachelor degree or above

0.462

0.209

0.027

0.630

0.419

0.949

Working hours a week

 

 

 

 

 

 

40H

 

 

 

1.000

 

 

41-56H

-1.550

0.651

0.017

0.212

0.059

0.760

56H

-1.079

0.647

0.095

0.340

0.096

1.207

Regular diet

 

 

 

 

 

 

Yes 

 

 

 

1.000

 

 

General 

-0.719

0.304

0.018

0.487

0.269

0.884

no

-0.221

0.292

0.449

0.802

0.453

1.420

Economic stress

 

 

 

 

 

 

NO

 

 

 

1.000

 

 

YES

0.503

0.227

0.027

0.605

0.388

0.944

Discussion

Prevalence and influencing factors of sleep disorder among nurses in tertiary hospitals

  Under the environment of long-term heavy workload, shift work system and high requirement of work quality, health care workers were lower status of physical and mental health than other groups. As a typical physical problem, Sleep disorder has become the focus of attention. According to our results and previous studies, the overall prevalence of sleep disorder in hospital staffs was higher than the general population [6,37-40]. However, the status in nurses was even more serious. A pilot study in Urumqi(Xinjiang,China) using PSQI to evaluate the quality of sleep in physicians, indicated 59.92% participants had sleep disorders[41], that was lower than our results. The Other researcher in Tehran(Iran) and Taiwan(China) also revealed that nurses had higher incidence rate than other health care workers[42-43]. However, as a high-risk group, compare to other health care workers, nurses were most likely to suffer from sleep disorder that be focused first.

  The previous study found highly stress correlated positively with sleep disorder[6,44].In our study, nurses had sleep disorder with felling economic, occupational and social stress. Nurses in tertiary hospitals need deal with different kinds of medical condition, keep learning new medical knowledge and solving different social relationship problem. In fact, nurses always be exposed to high level stress for a long time[45-46].The percentage of nurses (working hours>40H per week) was 49.6% in our study. The previous studies indicated that heavy workload and longer working hours squeeze time for rest and exercise, and made nurses felling highly stress which influence quality of sleep[6]. However, along with the rapid rhythm of work and work time uncertainty, nurses develop a habit of irregular diet and exercise that affect the circadian rhythms which decrease the quality of life[2].

Prevalence and influencing factors of anxiety symptoms among nurses in tertiary hospitals

  The prevalence of anxiety symptoms in nurses was 30.4% in our study that converged towards the results of similar studies[27,47-49]. However, the prevalence in medical students and doctors were 12.5% and 21.1%, respectively[50-51]. The previous studies indicated, nurses were risk group of anxiety symptom in health care workers. Comparing with other populations in China, the prevalence was obvious higher[52-53]. According to the fact, it was warranted to in-depth studies and active interventions about anxiety symptoms in Chinese nurses.

  Our study found higher education backgrounds was risk factor about anxiety symptom in nurses. The results of Liaoning general hospital also indicate nurses with higher education backgrounds may more likely be anxiety symptoms[27]. The results may reflect nurses with higher education backgrounds have higher learning and working target and demand. The previous study indicated nurses with regular meals have lower anxiety symptom(OR 0.719)that was similar with our study[27]. Keeping healthy lifestyle may be helpful for reducing anxiety symptoms in nurses. Longer working hours, heavier workload and lower salary make effort-reward imbalance in nurses that have negative effect for mental health and their job satisfaction[27,54-55] however, a lot of researches have shown that the status of stress was significantly related to physical and mental health, including anxiety symptom[56-57].

  The correlation between sleep disorder and anxiety symptoms that influence the quality of life

  Several previous studies indicated sleep disorder have position relation with anxiety symptoms[58-59]. We also find the strong correlation between sleep disorder and anxiety symptom. We think there maybe correlation between physical health and mental health that the  previous similar studies shown the same viewpoint[60].We also found nurses with sleep disorder or anxiety symptoms have lower quality of life, no matter PCS or MCS. The results may indicate that sleep disorder and anxiety symptom could respect poor quality of life. However, as the common influencing factors, stress, effort-reward imbalance and irregular lifestyle have significantly related to sleep disorder and anxiety symptom in our study. We should pay attention to these factors and talk steps to prevent these problems in nurses.

  The previous studies shown that nurses with higher social support have higher quality of life, higher quality of sleep and lower anxiety symptoms[27,61-62]. However, providing social support like peer support, may be helpful for quality of sleep, relieve anxiety and increase quality of life in tertiary hospitals’ nurses. The present results remanded hospital managers that need pay more attention on the effort-reward balance by effective system like building appropriate performance measures. Meanwhile, by building positive channel like group activity, nurses could relieve the stress form job, economy and social. In addition, by healthy education, let nurses in tertiary maintain good lifestyle like keep regular diet and exercises. In other words, improving the quality of life, decreasing sleep disorder and anxiety symptoms must be on the agenda.

Conclusion

Hospital administrators had met challenges that nurses had bad sleep quality and anxiety symptoms because of heavy workload in tertiary hospitals in China. However, hierarchical diagnosis system engineering was carried out by National Health Commission of the People’s Republic of China that relieve the pressure of tertiary hospitals’ medical treatment, including doctors and nurses. In addition, from the perspective of hospital management, promotion of health lifestyle, effort-reward balance and providing social support may be significant to decrease the poor sleep quality and anxiety symptoms and increase quality of life in nurses.

Limitation

The limitation of this study was participants were concentrated in Beijing’s tertiary hospitals. However, as the Chinese capital, high-quality medical resources are gathered in Beijing. By the rapid development of Chinese economy and traffic infrastructure construction, patients from all over China want to see a doctor in Beijing tertiary hospitals. It has imposed a heavy burden on medical resources in Beijing, including job burden in nurses. Ensuring physical and mental health of nurses in tertiary hospitals is more significant for Beijing medical system. However, we have plan to take a nationwide survey about quality of life in nurses.

Abbreviations

PSQI: Pittsburgh Sleep Quality Index; SAS: Zung Self-Rating Anxiety Scale; SF-36: 36-item Short Form Health Survey; PCS: physical component summary; MCS: mental component summary; OR:Odds ratio; ANOVA: analysis of variance

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Beijing Children hospital, Beijing Tongren Hospital, and Capital Medical University Affiliated Anzhen Hospital. All the participants were orally informed after our researchers had introduced the study. Written informed consent concerning conduct of the survey was obtained from each respondent before data collection. Confidentiality and privacy were maintained by using unique identification numbers instead of names.

Consent for publication

Not applicable

Availability of data and material

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

Financial support was provided by Key consulting projects of Chinese academy of engineering (No.2019-XZ-29) and Hospital management foundation of Beijing Tongren hospital (NO.2016-YJJ-GLL-011). The funders had no role in the design of the study and collection, analysis, and in writing of the manuscript.

Authors’ contributions

DW and DH designed the study and questionnaire. JL,MH and HY collected the data and control the quality of study. DW and YP analyze the date and wrote the manuscript. DH supervised the study and data analysis. All authors read and approved the manuscript.

Acknowledgements

We would like to acknowledge all the nurses for their kind cooperation from Beijing Children hospital, Beijing Tongren Hospital, and Capital Medical University Affiliated Anzhen Hospital. Special thanks to our researchers who took part in this study.

Author details

  1. Beijing Tongren Hospital, NO.1 Dongjiaomin lane, DongCheng District, Beijing, China.
  2. Capital Medical University Affiliated Anzhen Hospital, NO.2 Anzhen lane, ChaoYang District, Beijing, China
  3. Department of public health, Capital Medical University, No.10, West gate, FengTai, District, Beijing, China

*Corresponding author to De-min Han

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