Abstract
This cross-sectional study investigates the prevalence of depression and anxiety and their associations with lifestyle changes among adolescents in Wuhan, China, during the coronavirus disease 2019 pandemic.
Coronavirus disease 2019 (COVID-19) broke out in Wuhan, China, in late 2019, and has become a pandemic.1 Unprecedented quarantine was imposed in Wuhan from January 23, 2020, to April 8, 2020, and all schools were closed. Mental health associated with the quarantine is of great concern, especially for adolescents. This study aimed to investigate the prevalence of depression and anxiety and their associations with lifestyle changes among adolescents in Wuhan.
Methods
A cross-sectional study of a convenience sample was conducted from March 30, 2020, to April 7, 2020, and data were collected through an online questionnaire using WeChat and QQ apps, which are widely used in China. Eligibility criteria were (1) current residents in Wuhan, (2) age between 12 and 18 years, and (3) not receiving a diagnosis of severe acute respiratory syndrome coronavirus 2 infection. There were 282 junior high schools (219 682 students) and 92 senior high schools (108 679 students) in Wuhan at the time of the survey. We recruited 10 713 students (3.26%) from 27 junior high schools (162 classes) and 11 senior high schools (81 classes) (details of sampling and survey content available on request). All participants provided written informed consent for the survey. Ethics approval was received from the Ethics Committee of the School of Public Health at Fudan University.
The questionnaire collected information on sociodemographic factors and daily life factors during the lockdown period. The Chinese-translated version of the Hospital Anxiety and Depression Scale (HADS) was used to assess levels of anxiety and depression symptoms.2,3 Descriptive and logistic regression analyses were performed using SPSS statistical software, version 20.0 (SPSS Inc). A 2-sided P value less than .05 was considered significant.
Results
Of 7890 participants, 4107 (52.1%) were female. The prevalence was 21.7% (n = 1708) for anxiety and 24.6% (n = 1941) for depression (HADS subscale score >7). Distributions of anxiety and depression according to sociodemographic factors are shown in Table 1.
Table 1. Distributions of Anxiety and Depression According to Sociodemographic Factors.
| Variable | No. (%) | HADS, No. (%)a | |
|---|---|---|---|
| Anxiety | Depression | ||
| Total | 7890 (100.0) | 1708 (21.6) | 1941 (24.6) |
| Sex | |||
| Male | 3783 (47.9) | 816 (21.5) | 976 (25.8) |
| Female | 4107 (52.1) | 892 (21.7) | 965 (23.5) |
| Age, y | |||
| 12-14 | 2970 (37.6) | 502 (16.9) | 596 (20.1) |
| 15-16 | 2773 (35.1) | 641 (23.1) | 719 (25.9) |
| 17-18 | 2147 (27.2) | 565 (26.3) | 626 (29.2) |
| District of residence | |||
| City | 6190 (78.5) | 1319 (21.3) | 1498 (24.2) |
| Suburb | 1700 (21.5) | 389 (22.9) | 443 (26.1) |
| Living with both parents or not | |||
| Yes | 1553 (19.7) | 1357 (21.4) | 1539 (24.3) |
| No | 6337 (80.3) | 351 (22.6) | 402 (25.9) |
| Father’s educational levelb | |||
| Low | 5553 (70.4) | 1260 (22.7) | 1462 (26.3) |
| High | 2337 (29.6) | 448 (19.2) | 479 (20.5) |
| Mother’s educational levelb | |||
| Low | 5857 (74.2) | 1317 (22.5) | 1509 (25.8) |
| High | 2033 (25.8) | 391 (19.2) | 432 (21.2) |
Abbreviation: HADS, Hospital Anxiety and Depression Scale.
HADS is a 14-item scale that measures the presence of symptoms related to anxiety (7 items) and depression (7 items) during the past week. The maximum subscale score for both anxiety and depression is 21. The 2 subscales were both stratified as follows: (1) scores from 0 to 7 indicate normal case; (2) scores from 8 to 10 indicate borderline case; and (3) scores from 11 to 21 indicate abnormal case. HADS anxiety and HADS depression represent borderline case and abnormal case.4
Low indicates educational level below junior college; high indicates junior college or above.
Table 2 provides the results from logistic regression analysis. After adjustment for covariates, going outside of the home, food insufficiency, perceived discrimination, poor sleep quality, less face-to-face communication with family members, and less pleasure or peace from interests/hobbies/specialties were significantly associated with increased risks of anxiety and depression. More physical activity was significantly associated with a lower risk of depression. The effect of home restrictions on study, screen time, and browsing information about COVID-19 were significantly associated with an increased risk of anxiety.
Table 2. Association Between Daily Life Characteristics and Anxiety and Depression.
| Variable | HADS, Adjusted odds ratio (95% CI)a | |
|---|---|---|
| Anxietyb | Depressionb | |
| Having ever gone out | ||
| No | 1 [Reference] | 1 [Reference] |
| Yes | 1.19 (1.05-1.34)c | 1.13 (1.00-1.27)d |
| Sufficiency of food | ||
| Sufficient | 1 [Reference] | 1 [Reference] |
| Somewhate | 1.43 (1.26-1.63) | 1.38 (1.22-1.57) |
| Insufficiente | 1.86 (1.47-2.37) | 1.70 (1.33-2.17) |
| Perceived discrimination | ||
| Never | 1 [Reference] | 1 [Reference] |
| Occasionallye | 1.60 (1.39-1.85) | 1.32 (1.15-1.52) |
| Oftene | 2.11(1.82-2.44) | 1.58 (1.37-1.82) |
| Sleep quality | ||
| Poor | 1 [Reference] | 1 [Reference] |
| Generale | 0.44 (0.37-0.53) | 0.49 (0.41-0.58) |
| Goode | 0.22 (0.18-0.27) | 0.23(0.20-0.28) |
| Physical activity, d/wk | ||
| ≤1 | 1 [Reference] | 1 [Reference] |
| 2-3 | 1.00 (0.87-1.16) | 0.77 (0.67-0.89)e |
| ≥4 | 1.01 (0.88-1.17) | 0.73 (0.63-0.84)e |
| Effect on studyingf | ||
| Little | 1 [Reference] | 1 [Reference] |
| Somewhat | 1.37 (1.17-1.60)e | 1.11 (0.95-1.28) |
| Greate | 2.82 (2.39-3.34) | 1.91 (1.63-2.24) |
| Score of screen time, points | ||
| ≤4 | 1 [Reference] | 1 [Reference] |
| 5-12d | 1.27 (1.05-1.52) | 1.16 (0.97-1.39) |
| 13-24d | 1.29 (1.05-1.60) | 1.27 (1.04-1.56) |
| Browsing information about coronavirus disease 2019, h/d | ||
| <0.5 | 1 [Reference] | 1 [Reference] |
| 0.5-2 | 1.24 (1.09-1.40)c | 1.04 (0.92-1.18) |
| >2 | 1.82 (1.38-2.40)e | 1.67 (1.26-2.21)d |
| Face-to-face communication, h/d | ||
| <0.5 | 1 [Reference] | 1 [Reference] |
| 0.5-2 | 0.83 (0.73-0.95)c | 0.64 (0.56-0.73)e |
| >2 | 0.77 (0.64-0.93)c | 0.53 (0.44-0.63)e |
| Seeking pleasure from interests | ||
| Occasionally | 1 [Reference] | 1 [Reference] |
| Sometimese | 0.72 (0.61-0.85) | 0.52 (0.45-0.61) |
| Oftene | 0.65 (0.55-0.76) | 0.25 (0.22-0.30) |
Abbreviation: HADS, Hospital Anxiety and Depression Scale.
Models are mutually adjusted for all presented variables, including demographic factors and all daily activity.
HADS is a 14-item scale that measures the presence of symptoms related to anxiety (7 items) and depression (7 items) during the past week. The maximum subscale score for both anxiety and depression is 21. The 2 subscales were both stratified as follows: (1) scores from 0 to 7 indicate normal case; (2) scores from 8 to 10 indicate borderline case; and (3) scores from 11 to 21 indicate abnormal case. HADS anxiety and HADS depression represent borderline case and abnormal case.4
Statistically significant (P < .01).
Statistically significant (P < .05).
Statistically significant (P < .001).
Effect on studying means the influence of home restrictions on studying, such as being unable to communicate effectively with teachers and classmates and unable to concentrate and inefficient in learning.
Discussion
During the COVID-19 quarantine period, more than 20% of adolescents had anxiety and depression. Long-term home restrictions might have adverse effects on mental health of adolescents because of a sharp change of lifestyles and various stressors, such as fears of infection, frustration, and boredom.5,6
This study revealed that anxiety and depression were closely associated with daily life under home restrictions among adolescents during the COVID-19 pandemic period, especially some factors that could be easily ignored, such as perceived discrimination and ability to study. A multisectoral collaboration has been called on to pay attention to these associations and to take necessary countermeasures.6
The study has several limitations. First, a convenient sampling method could reduce a representativeness of the population. Second, we were not able to evaluate some important cofounding factors, such as levels of community support and parents’ marital status. Third, a cross-sectional design prevents us from assuming any causal relationships between home quarantine–associated factors and the presence of anxiety or depression.
The evidence may help guide the formulation of intervention measures and effective and rapid response to an epidemic of novel infectious disease concerning the mental health of adolescents.
References
- 1.Xiang YT, Jin Y, Cheung T. Joint international collaboration to combat mental health challenges during the coronavirus disease 2019 pandemic. JAMA Psychiatry. 2020;77(10):989-990. doi: 10.1001/jamapsychiatry.2020.1057 [DOI] [PubMed] [Google Scholar]
- 2.Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand. 1983;67(6):361-370. doi: 10.1111/j.1600-0447.1983.tb09716.x [DOI] [PubMed] [Google Scholar]
- 3.Chan YF, Leung DY, Fong DY, Leung CM, Lee AM. Psychometric evaluation of the Hospital Anxiety and Depression Scale in a large community sample of adolescents in Hong Kong. Qual Life Res. 2010;19(6):865-873. doi: 10.1007/s11136-010-9645-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Ciprandi G, Schiavetti I, Rindone E, Ricciardolo FL. The impact of anxiety and depression on outpatients with asthma. Ann Allergy Asthma Immunol. 2015;115(5):408-414. doi: 10.1016/j.anai.2015.08.007 [DOI] [PubMed] [Google Scholar]
- 5.Brooks SK, Webster RK, Smith LE, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020;395(10227):912-920. doi: 10.1016/S0140-6736(20)30460-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Wang G, Zhang Y, Zhao J, Zhang J, Jiang F. Mitigate the effects of home confinement on children during the COVID-19 outbreak. Lancet. 2020;395(10228):945-947. doi: 10.1016/S0140-6736(20)30547-X [DOI] [PMC free article] [PubMed] [Google Scholar]