A total of 645 medical staff (280 physicians and 365 nurses) were invited to participate in this study, among whom 22 refused to complete the survey for some reason. Another 75 participants answered the questionnaire incompletely or did not meet the response requirements, with a correct response rate of 85%. A total of 548 respondents completed the survey (240 physicians and 308 nurses). There were 144 males and 404 females, aged between 20 and 60 years, with a median of 28 years (doctors = 31 years, nurses = 27 years).
3.1 Prevalence of depression, anxiety, headache and sleep disorders
Among 548 medical staff, the 1-year prevalence of depression was 42.7% (mild 26.8%, moderate and severe 15.9%), the prevalence of headache disorders was 53.3% (migraine 25.9%, TTH 24.1%, other types 3.3%), and the prevalence of anxiety and sleep disorders was 26.6%, and 69.0%, respectively. Among them, depression combined with anxiety, headache, and sleep disorders was 23%, 27% (migraine 14.4%, TTH 10.4%), and 34.5%, but only 11 respondents (4.7%) have received psychiatric medication for depression.
We found that the prevalence of depression in females was significantly higher than that in males (48.3% vs 27.1%, OR = 2.512), and females were about five times as likely to have depression as males were (35.6% vs 7.1%). The median age of the depressed group (28 years) was lower than that of the non-depressed group (30 years). And the prevalence of depression in unmarried or divorced people was significantly higher than that in the married group (50.5% vs 35.8%, OR = 1.900). The prevalence of depression among nurses was nearly twice as high as among doctors (55.2% vs. 26.7%, OR = 3.388), and among rotating-shift workers was significantly higher than that among day-shift workers (35.2% vs. 7.5%, OR = 1.719). The total prevalence of overweight and obesity in the medical population was about 33.1%, among which 10.6% were depressed, while 32.1% were depressed in the population with a BMI < 23kg/m2. In addition, with the improvement of educational background and professional titles, the prevalence of depression has gradually decreased.
The prevalence of mild, moderate, and severe anxiety was all higher in patients with depression than in those without depression. The prevalence of migraine was higher in the depressive group (55.6% vs 44.4%, OR = 2.031), while the prevalence of TTH was higher in the non-depressive group (43.2% vs 56.8%). In comparison with the sleep disorder group, we found that the prevalence of mild sleep disorders was similar in the two groups, while the prevalence of moderate and severe sleep disorders was higher in the depressive group. We showed these results in Table 1.
Table 1 Comparison of the medical staff characteristics with and without depression
|
|
With depression(n=234)
|
Without depression(n=314)
|
P-value
|
OR(95%Cl)
|
Sex(n %)
|
Male
|
39(27.1%)
|
105(72.9%)
|
<0.001
|
0.398(0.263-0.604)
|
|
Female
|
195(48.3%)
|
209(51.7%)
|
|
|
Age
|
Median
(P25,P75)
|
28.0
(25,30)
|
30.0
(26,35)
|
<0.001
|
1.833(1.302-2.582)
|
Marital status
|
Single or divorced
Married
|
129(51.2%)
105(35.6%)
|
126(48.8%)
188(64.4%)
|
<0.001
|
1.900(1.348-2.678)
|
BMI
(kg /m2)
Occupation
Educational background
Work Seniority(year)
Work arrangements
Night shifts
Professional titles
Anxiety
Headache
Sleep disorders
|
Underweight <18.5
Normal Weight 18.5-22.9
Overweight 23-25
Obese≥25
Doctor
Nurse
College or lower Bachelor
Master or above
Median
(P25,P75)
Day-shift
Rotating-shift
Median
(P25,P75)
Junior
Senior
Advanced
Total
Mild
Moderate
Severe
Total
Migraine
Tension-type headache
Total
Mild
Moderate
Severe
|
51(56.0%)
125(45.5%)
26(31.3%)
32(32.3%)
64(26.7%)
170(55.2%)
101(54.6%)
124(41.2%)
9(14.5%)
5
(3,8)
41(32.8%)
193(45.6%)
5
(4,8)
199(48.8%)
24(26.1%)
11(8.8%)
126(86.3%)
69(79.3%)
42(95.5%)
15(100%)
148(50.7%)
79(55.6%)
57(43.2%)
189(50.0%)
104(39.5%)
77(72.0%)
8(100%)
|
40(44.0%)
150(54.5%)
57(68.7%)
67(67.7%)
176(73.3%)
138(44.8%)
84(45.4%)
177(58.8%)
53(85.5%)
6
(3,12)
84(67.2%)
230(54.4%)
5
(0,7)
209(51.2%)
68(73.9%)
37(77.1%)
20(13.7%)
18(20.7%)
2(4.5%)
0
144(49.3%)
63(44.4%)
75(56.8%)
189(50.0%)
159(60.5%)
30(28.0%)
0
|
0.001
<0.001
<0.001
0.021
0.011
0.003
<0.001
<0.001
<0.001
<0.001
|
0.295(0.205-0.425)
1.716(1.186-2.483)
4.126(1.963-8.673)
0.582(0.382-0.885)
2.698(1.629-4.467)
1.187(0.524-2.691)
17.150(10.188-28.869)
2.032(1.437-2.872)
2.778(1.870-4.127)
|
3.2 Correlation analysis and multivariate logistic regression on the occurrence of depression
We first used nonparametric spearman correlation analysis of binary classification variables of depression and anxiety, headache, and sleep disorders, and then we examined the correlation with demographic characteristics factors. The results showed that the occurrence of depression and anxiety, sleep disorders, total headache and migraine have correlation, with the correlation coefficient of anxiety the biggest (Spearman's rho = 0.531). However, there was no significant correlation between TTH and depression. Other related factors included age, gender, BMI, professional title, educational background, marital status, occupation, work arrangements, night shifts, etc(see Fig. 1).
We then performed a multifactor binary logistic regression analysis on the occurrence of depression. The TTH, headache frequency and VAS scores of headache intensity were found to be P > 0.1 in the univariate logistic regression, so they were not included in the multifactor regression model. The results showed that anxiety and nursing occupation were risk factors, while BMI was the protective factor for depression (see Table 2 and Fig. 2). The prediction accuracy of our multi-factor binary logistic regression model is 78.5%.
Table 2
Multivariate logistic regression of depression occurrence
| B | Standard error | P-value | Exp(B) | Exp(B)95%CI |
Constant | 0.191 | 1.276 | 0.881 | 1.210 | |
Anxiety | 2.791 | 0.291 | < 0.001** | 16.298 | 9.208 ~ 28.847 |
Sleep disorders | 0.228 | 0.248 | < 0.360 | 1.256 | 0.772 ~ 2.043 |
Headache | 0.286 | 0.229 | 0.212 | 1.331 | 0.850 ~ 2.085 |
BMI | -0.078 | 0.036 | 0.032* | 0.925 | 0.861 ~ 0.993 |
Education background | -0.226 | 0.197 | 0.250 | 0.797 | 0.543 ~ 1.172 |
Age | -0.001 | 0.030 | 0.962 | 0.999 | 0.942 ~ 1.058 |
Nurse occupation | 0.965 | 0.328 | 0.003** | 2.626 | 1.381 ~ 4.993 |
Gender | -0.507 | 0.354 | 0.153 | 0.603 | 0.301 ~ 1.206 |
Marital status | 0.487 | 0.274 | 0.076 | 1.627 | 0.950 ~ 2.785 |
Work arrangements | -0.026 | 0.477 | 0.956 | 0.974 | 0.383 ~ 2.479 |
Night shifts | 0.405 | 0.062 | 0.467 | 1.046 | 0.927 ~ 1.180 |
Professional title | 0.029 | 0.311 | 0.926 | 1.029 | 0.560 ~ 1.893 |
3.3 Correlation analysis and multivariate logistic regression on SDS
We further analyzed the correlation between SDS scores of depression severity and quantitative variables of SAS, PSQI, headache frequency, and headache intensity VAS scores as well as demographic data. The results showed that the severity of depression was significantly correlated with the grades of anxiety and sleep disorders (Spearman's rho = 0.801, 0.503), and the presence or absence of headache and migraine was also related. However, there was no significant correlation between SDS scores with headache frequency, headache intensity and TTH, but headache frequency and headache intensity could affect the PSQI score of sleep disorders (Spearman's rho = 0.205, 0.166, P < 0.001). In addition, the results showed that the severity of depression was positively correlated with nurse occupation, night shifts, and working arrangements and negatively correlated with age, gender, marital status, BMI, educational background, professional titles, and so on (see Fig. 3).
Then we performed multiple linear regression analysis on the SDS scores to predict depression severity. The VAS scores of headache intensity were found to be P > 0.1 in the early screening process, so it was not included in the regression model. Considering the multicollinearity between age, working years and professional title, medical profession and gender, working arrangement, and night shift frequency, we included only variables such as age, nurse occupation, and night shift frequency. According to the results of multiple linear regression, grades of anxiety, sleep disorders and nurse occupation were the risk factors, while educational background was the protective factors for depression severity (see Table 3).
Table 3
Multiple linear regression of the SDS score
| Coefficient | Standard error | P-value | 95%CI of B | VIF |
Constant | 52.152 | 3.897 | < 0.001 | 44.496 to 59.807 | |
SAS grade | 7.932 | 0.584 | < 0.001** | 6.786 ~ 9.078 | 1.378 |
PSQI grade | 3.310 | 0.607 | < 0.001** | 2.118 ~ 4.502 | 1.468 |
Headache | 1.165 | 0.801 | 0.146 | -0.409 ~ 2.739 | 1.144 |
BMI | -0.284 | 0.108 | 0.088 | -0.497~-0.072 | 1.207 |
Education background | -1.614 | 0.622 | 0.010** | -2.837~-0.392 | 1.575 |
Age | -0.101 | 0.072 | 0.159 | -0.242 ~ 0.040 | 1.920 |
Nurse occupation | 1.998 | 0.976 | 0.041* | -0.081 ~ 3.915 | 1.679 |
Marital status | -0.497 | 0.906 | 0.584 | -2.277 ~ 1.284 | 1.562 |
Night shifts | 0.052 | 0.129 | 0.684 | -0.201 ~ 0.306 | 1.140 |