Prevalence of depression,anxiety and stress in china during COVID-19 pandemic: A systematic review with meta-analysis

Abstract

Background

The novel coronavirus disease which is believed to have initially originated in Wuhan city of China at the end of 2019 was declared as pandemic by March 2020 by WHO. This pandemic significantly impacted the mental health of communities around the globe. This project draws data from available research to quantify COVID-19 mental health issues and its prevalence in China during the early period of the COVID-19 crisis. It is believed that this pooling of data will give fair estimate of the effects of the COVID-19 pandemic on mental health.

Methods

We conducted this study in accordance with PRISMA guidelines 2009. The protocol for this review is registered and published in PROSPERO (CRD42020182893). The databases used were Pubmed, Medline, Google scholar and Scopus. The studies were extracted according to pre-defined eligibility criteria and risk of bias assessment was conducted. The Meta-analysis was done using OpenMeta [analyst].

Results

Total of 62382 participants in nineteen studies fulfilled the eligibility criteria. Stress was the most prevalent (48.1%) mental health consequence of Covid-19 pandemic, followed by depression (26.9%) and anxiety (21.8%). After performing subgroup analysis, prevalence of depression and anxiety in both females and frontline health care workers were high as compared to the prevalence in general Chinese population.

Conclusion

The prevalence of depression and anxiety is moderately high whereas pooled prevalence of stress was found to be very high in Chinese people during this Covid-19 crisis.

Keywords

stress anxiety depression pandemic Covid-19 China mental health health care worker psychological impact

Introduction

The novel coronavirus disease which is believed to have initially originated in Wuhan city of China at the end of 2019, was declared to be a Public Health Emergency of International Concern in January 2020 by the World Health Organization (WHO), and unanticipatedly became a pandemic for the world by March 2020.¹Around that time, The Lancet issued a statement to show appreciation and solidarity towards public health workers and scientists who were risking their lives fighting against the odds.²

While symptoms of the disease vary from an asymptomatic presentation to severe findings including high grade fever, chills, breathing difficulty, cough, sore throat, coryza, myalgia, nausea, vomiting, and diarrhea, the actual mode of transmission of the virus is not completely understood. Patients with medical comorbidities are associated with worse outcomes such as cardiac injury, respiratory failure, acute respiratory distress syndrome, and death. To combat the rapid progression of the disease the Chinese government imposed lockdown initially in the city of Wuhan and then gradually, to other cities.³ During this period, the significance of the desperate measures such as quarantine and self-isolation that were imposed to halt the spread of the disease gained popularity, but subsequently the Chinese government started noticing evolving panic, anxiety, and mood symptoms among their population. These psychological effects are believed to be linked with quarantine duration, fear of infection, frustration due to boredom, inadequate supplies due to panic buying, lack of proper and accurate information due to increased media reporting, financial loss due to shutdown of the industrial and business sectors and the labeling of people with the disease as “COVID-19 cases” thus creating stigma.⁴ The negative psychosocial effects of COVID-19 are under-addressed and little data is currently available on the mental health impact this disease, and the measures taken to limit its spread, has on the general population or those who suffer from it.

For many, quarantine can be an unpleasant experience. Separation from loved ones, the loss of freedom, uncertainty, and boredom can lead to anxiety, stress, depression, and even suicide.⁴ Researchers have suggested the psychological stress from situations of this magnitude may have a long-lasting effect on one’s overall psychosocial wellbeing. Even after a decade post its outbreak in 2003, it was reported that depression, chronic fatigue and post-traumatic stress disorders still exist in survivors of severe acute respiratory syndrome.⁵ Another study, which utilizes snowball sampling strategy, focused on the general public living in mainland China during the epidemic of COVID-19. The study suggests females suffered a greater psychological impact of the outbreak, including higher levels of anxiety, stress and depression.³ Another domain of the study suggests students experience an increased psychological impact from the outbreak with higher levels of stress, anxiety, sleeplessness, frustration and depression.⁶

This project draws data from available research to quantify COVID-19 mental health effects and prevalence in China during the early period of the COVID-19 crisis. It is believed this pooling of data will help build a greater consensus about the effects of the COVID-19 pandemic on mental health, which may be generalizable, and provide benefit and guidance to those in other parts of the world.

Material and methods

We’ve conducted the systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines 2009.⁷The protocol for this review is registered and published in PROSPERO (CRD42020182893). It is available on: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020182893

Literature search strategy

An extensive data search was performed on PubMed, Ovid Medline, Google Scholar and Scopus databases using MeSH and non-MeSH search terms which includes (“Depression” OR “Anxiety” OR “Stress” OR “Major depressive disorder” OR “Generalized anxiety disorder” OR “Acute stress disorder” OR “Post-traumatic stress disorder” OR “Mental Health” OR “Psychological impact” OR “Anxi*” OR “Depressi*”) AND (“SARS-CoV-2” OR “COVID-19” OR “Pandemic” OR “Corona virus” OR “Coronaphobia” OR “Novel coronavirus” OR “2019-nCoV) AND (“China” OR “Chinese” OR “Wuhan” OR ‘’Hubei”). Two independent authors (SBB & SSS) performed this task. No specific timeline was defined however, all research published prior to April 2020 were considered for inclusion. To expedite the identification of eligible research, we screened the reference list of cited studies within the extracted articles. Additionally, sources, including MedRxiv.org & SSRN were explored to look for preprints. The screening method was as follows: initially, titles were screened for potential relevant articles followed by detailed screening of abstracts to confine the search. Full-texts of the articles were screened and shortlisted on the basis of eligibility and relevance to the topic.

Eligibility criteria

Studies that met the following criteria were included in the review: (a) Studies in which Depression or Anxiety or Stress or any combination of the above was assessed as a primary outcome; (b) No restrictions were applied on the basis of age, gender, study setting or type of participant; (c) Must be a cross-sectional study/survey; (d) Only populations belonging to the region of China were included.

Studies were excluded from this review if they met the following criteria: (a) If depression or anxiety or stress was not assessed as a major outcome; (b) If a study included hypothetical or unquantified results (no supportive statistical evidence of analyzed outcome); (c) Data was presented in any language other than English; (d) If abstracts and/or full-texts were unavailable; (e) If primary results were presented in mean & standard deviations (SD) instead of frequencies and percentages.

Data extraction

Two review authors independently (SIA & SZ) extracted data using a predefined extraction form. Any discrepancies in extracted data, including duplicate reporting of studies or inclusion of irrelevant articles was resolved by collaborative discussion with the third independent investigator (GMM). All the relevant data about each study was entered on predefined MS-Word sheet. We extracted information about: Study details (First author, year of publication); Population characteristics (total number of respondents, response rate, age, gender, country or region, types of population included in each survey); scales (that were utilized to assess primary outcome) and addressed mental health condition. For all quantitative variables, data was extracted in frequencies and percentages except for age of respondents, which was presented in mean & standard deviation.

Statistical analysis

OpenMeta[Analyst] software was utilized to run meta-analysis. We’ve considered pooled prevalence with their 95% confidence intervals (95% CI) as the measures of effect. In order to assess the heterogeneity among the studies for primary outcome groups and subgroups, we’ve applied I² statistic as a proportionate measure of the total variance in pooled estimates. The heterogeneity was considered low, moderate and high if the cut-off points for I² values of 25%, 50% and 75% or more were found respectively.⁸ For the stability of variance, we’ve used Freeman-Tukey Double Arcsine Transformation⁹ before calculating the pooled estimates. Random-effect model was applied considering that prevalence of depression, anxiety and stress in different population groups would be variable.

Subgroup analysis was conducted on gender (female), and type of population (Front-line health care workers). Sensitivity analysis was done to evaluate the alteration in pooled effect size. It was performed by removal of individual studies one by one and running the meta-analysis after the removal of each study. In this way, a cumulative analysis was carried out to test the impact of the largest studies on the pooled effect size. To figure out the variance due to utilization of different scales within studies, a separate scale-specific analysis on frequently used scales (e.g. PHQ-9, SDS, GAD-7, SAS and IES-R) was performed.

Risk of bias assessment

Two independent reviewers (SSS & SIA) conducted the process of assessing risk of bias. Initially, relevant data and studies were extracted by two independent investigators in accordance with The Meta-analysis Of Observational Studies in Epidemiology standard (MOOSE)¹⁰ and Strengthening the reporting of observational studies in epidemiology (STROBE)¹¹ 22-item checklists, modified according to Sanderson et al.¹² and Fowkes and Fulton,¹³ to assess the methodological quality of each study. Two independent authors (SBB & WY) then evaluated risk of bias using the Modified Newcastle-Ottawa scale¹⁴ which was cross-checked by a third independent reviewer (RVG) to resolve any discrepancy between findings. Assessment was based upon following essential components: (a) Representativeness; (b) Size of the sample; (c) Comparability; (d) Outcome and (e) Statistical methods. Studies scoring ≥3 were considered to be low risk whereas studies with scores of <3 were high risk studies. Strict criterion were set for all the essential components to ensure appropriate quality assessment. The details of criterion is given in supplementary document (eMethod 1).

Results

The initial search revealed a total of 1170 articles. Additional database and preprints publishing sites were included in our search strategy to ensure the most recent available data on the required topic was extracted. After extensive scrutiny of titles, abstracts, and full texts, 19 studies were included for final quantitative analysis. A PRISMA flow diagram detailing the study extraction process is presented in Figure 1.

Figure 1.

Data extraction strategy in accordance to PRISMA flow diagram for the study.

Baseline characteristics of included studies

Nineteen^15–33 studies with 62382 participants were included in the analysis. As per inclusion criteria, all studies were cross-sectional surveys reporting prevalence of depression or anxiety or stress or any of the preceding in combination among Chinese population during COVID-19 pandemic. A majority of the 62382 participants were females (69.7%) with the remainder being males (30.3%). The median response rate for the studies was 84.7% ranging from 43.2% to 100%. Out of the 19 studies, 6 did not report the response rate. The mean age of total participants was 36.44 (±6.27) years. The most frequently utilized scale for depression was Patient Health Questionnaire-9 item scale (in 5 studies). The Generalized Anxiety Disorder 7-item scale was used in 8 studies to measure anxiety and the Impact of Event Scale-Revised was utilized in 3 studies for the assessment of stress. Of the 19 studies, 15 included medical staff within their study population.

Details about the baseline features of all studies including Author & year of publication, total number of respondents, participation rate, distribution of age (in mean & SD) and gender (in number & percentage), clinical scales and investigated mental health, region and the type of study population is summarized in Table 1. After applying the Modified Newcastle-Ottawa scale (NOS) for calculating risk of bias, 5 studies were found to be high risk studies (scoring < 3 on NOS) whereas 14 (scoring ≥3 on NOS) were low risk studies. Details of NOS scoring is presented in Table 2.

Table 1.

Baseline characteristics of included studies.

Author and year	Total number of respondent	Response rate	Age in yearsMean (SD)	Gender distribution N (%)		Scales	Addressed mental health conditions	Region or country	Study population
				M	FM
Jianming Guo et al. 2020	11118	NR	NR	2802 (25.2)	8316 (74.8)	SASSDS	-Anxiety-Depression	China mainland	-Medical staff
Zhou Zhu et al. 2020	5062	77.1%	NR	759 (15)	4303 (85)	PHQ-9GAD-7IES-R	-Depression-Anxiety-Stress	Wuhan	-Medical staff
Wenjun Cao et al. 2020	7143	100%	NR	2168 (30.35)	4975 (69.65)	GAD-7	-Anxiety	Changzhi	-Medical students
Junling Gao et al. 2020	4827	83.2%	32.3 (±10.0)	1560 (32.3)	3267 (67.7)	WHO-5GAD-7	-Depression-Anxiety	China	-Students-Medical staff-General population
Yeen Huang at al. 2020	7236	NR	35.3 (±5.6)	3284 (45.4)	3952 (54.6)	CES-DGAD-7	-Depression-Anxiety	China	-Medical Staff-Enterprise or institution worker-Teachers or students-General population
Juhong Zhu et al. 2020	165	100%	34.16 (±8.06)	28 (17)	137 (83.0)	SDSSAS	-Depression-Anxiety	Gansu	-Medical staff
Wen Lu et al. 2020	2299	94.88%	NR	514 (22.3)	1785 (77.6)	HAMAHAMD	-Anxiety-Depression	Fuzhou	-Medical staff-Administrative staff
Jianbo Lai et al. 2020	1257	68.7%	NR	293 (23.3)	964 (76.7)	PHQ-9GAD-7IES-R	-Depression-Anxiety-Stress	-Wuhan-Hubei-Other provinces	-Medical staff
Jie Zhang et al. 2020	205	NR	46.9 (±15.37)	90 (44)	115 (56)	PHQ-9GAD-7GHQ-9	-Depression-Anxiety	Zhongshan	-General population-COVID 19 patients-Quarantined
Yun Chen et al. 2020	105	84.7%	32.6 (±6.5)	10 (9.5)	95 (90.5)	SDSSAS	-Depression-Anxiety	Guiyang	-Medical staff
Xiaoxv Yin et al. 2020	8151	NR	31.7 (±13.69)	3514 (43.1)	4637 (56.9)	PHQ-9GAD-7	-Depression-Anxiety	China mainland	-General population
Hai-Xin Bo et al. 2020	714	97.8%	50.2 (±12.9)	351 (49.1)	363 (50.9)	PCL-C	-Stress	Wuhan	- COVID 19 patients
Wen-rui Zhang et al. 2020	2182	NR	NR	781 (35.8)	1401 (64.2)	PHQ-2PHQ-4GAD-2	-Depression-Anxiety	China	-Medical staff
Zhaorui Liu et al. 2020	4679	NR	35.9 (±9.0)	830 (17.7)	3849 (82.3)	SDSSASSRQ-20	-Depression-Anxiety-Stress	China mainland	-Medical staff
Yuhong Dai et al. 2020	4357	94.7%	35 (±8.6)	1,026 (23.5)	3331 (76.5)	GHQ-12	-Stress	-Wuhan-Hubei-Other provinces	-Medical staff
Wanqiu Tan et al. 2020	673	50.87%	30.8 (±7.4)	501 (74.4)	172 (25.6)	DASS-21	-Depression-Anxiety-Stress	Chongqing	-Medical staff
Jiang Du et al. 2020	134	43.22%	36 (±8.05)	53 (39.5)	81 (60.5)	BDI-IIBAIPSS	-Depression-Anxiety-Stress	-Wuhan -Wuhan outreach	-Medical staff
Chen-Yun Liu et al. 2020	512	85.3%	NR	79 (15.43)	433 (84.57)	SAS	-Anxiety	-China	-Medical staff
Chenxi Zhang et al. 2020	1563	80.31%	NR	270 (17.3)	1293 (82.6)	PHQ-9GAD-7IES-R	-Depression-Anxiety-Stress	-China	-Medical staff

NR=Not reported; SAS=self-rating anxiety scale; SDS=Self-Rating Depression Scale; HCW= Health care worker; IES-R= Impact of Event Scale-Revised; PHQ-9 = Patient Health Questionnaire-9 item scale; PHQ-2 = Patient Health Questionnaire-2 item scale; PHQ-4 = Patient Health Questionnaire-4 item scale; GAD-7 = Generalized Anxiety Disorder 7-item scale; GAD-2 = Generalized Anxiety Disorder 2-item scale; WHO-5 = WHO-Five Well-Being Index; CES-D= The Center for Epidemiology Scale for Depression; HAMA= Hamilton Anxiety Scale; HAMD= Hamilton Depression Scale; GHQ-9 = 9- item General Health Questionnaire; PCL-C= Posttraumatic Stress Disorder Checklist– Civilian Version; SRQ-20= WHO 20-item Self-Reporting Questionnaire; DASS-21= Depression, Anxiety & Stress 21-item scale; PSS= Perceived Stress Scale; BAI= Beck Anxiety Inventory; BDI-II= Beck Depression Inventory-II.

Table 2.

Modified Newcastle-Ottawa scale scores of each included study.

	Modified Newcastle-Ottawa scale for risk of bias assessment
Studies	Representativeness(1)	Size(2)	Comparability(3)	Outcome(4)	Statistics(5)	Total score
Jianming Guo et al. 2020	1	1	0	0	0	2
Zhou Zhu et al. 2020	1	1	0	1	1	5
Wenjun Cao et al. 2020	1	1	1	1	0	4
Junling Gao et al. 2020	1	1	0	1	0	4
Yeen Huang at al. 2020	1	1	0	1	1	4
Juhong Zhu et al. 2020	1	0	1	0	0	2
Wen Lu et al. 2020	1	1	1	0	1	4
Jianbo Lai et al. 2020	1	1	0	1	1	5
Jie Zhang et al. 2020	1	0	0	1	1	3
Yun Chen et al. 2020	1	0	1	0	0	2
Xiaoxv Yin et al. 2020	1	1	0	1	1	4
Hai-Xin Bo et al. 2020	1	1	1	0	0	3
Wen-rui Zhang et al. 2020	1	1	0	0	1	3
Zhaorui Liu et al. 2020	1	1	0	0	0	2
Yuhong Dai et al. 2020	1	1	1	0	1	4
Wanqiu Tan et al. 2020	1	1	0	1	0	3
Jiang Du et al. 2020	1	0	0	0	1	2
Chen-Yun Liu et al. 2020	1	1	1	1	1	5
Chenxi Zhang et al. 2020	1	1	0	1	0	3

Prevalence of depression

Fifteen of the 19 studies (49656 participants) assessed the prevalence of depression. Data extraction sheet of depression is given in supplementary file (eTable 1). The estimated pooled prevalence of depression in Chinese people during COVID-19 pandemic was 26.9% (95% CI= 20–34.3, I²=99.68%) as presented in Figure 2. After performing the sensitivity analysis, we’ve found that no study affected the pooled prevalence of depression by over 2%. The alterations in depression prevalence obtained from influence analysis of studies ranged from 0.2%²⁴ to 1.9%.³⁰ When performed, a scale-specific analysis on Patient Health Questionnaire-9 (PHQ-9) which was utilized in 5 studies, found the prevalence of depression to be 35.5% (95% CI= 22.9–48.2, I²= 99.71%). Scale-specific analysis on Self-rating Depression Scale (SAS) revealed that depression was prevalent in 34.1% (95% CI= 30.8–37.3, I²= 87.71%) population.

Figure 2.

Pooled prevalence of depression in China during COVID-19 pandemic.

Prevalence of anxiety

Total 17 out of 19 studies reported anxiety in Chinese people. With 57311 participants included in the analysis, the pooled prevalence of anxiety was 21.8% (95% CI= 16.9–27.1, I²= 99.52%). The detail of this analysis is shown in Figure 3. Similar to depression, no significant alteration (>2%) was found after performing sensitivity analysis. The changes in the estimated pooled prevalence of anxiety after performing influence analysis ranged from 0%³¹ to 1.3%.³⁰ Details about the studies included in anxiety analysis, scales, anxiety in frontline health care workers & females is given in supplementary data sheet (eTable 2). The scale-specific analysis of Generalized Anxiety Disorder 7-item scale (used in 8 studies) revealed the total prevalence of anxiety to be 29.2% (95% Ci= 20.1– 39.3, I²= 99.74%); However, the prevalence of anxiety using Self-rating Anxiety Scale (used in 5 studies) was 16.2% (95% CI= 14.5–17.9, I²= 73.73%).

Figure 3.

Pooled prevalence of anxiety in China during COVID-19 pandemic.

Prevalence of stress

Of the 19 studies, only 8 surveys studied the prevalence of stress during the pandemic. When considering all of the primary outcomes, stress was found to be the most prevalent mental health condition in the Chinese population. The total prevalence among the 18439 participants included in this analysis was 48.1% (95% CI= 28.7–67.7, I²= 99.86%). Sensitivity analysis of data for prevalence of stress revealed 6 [16, 22, 26, 28, 30, 33] studies altering the pooled prevalence by more than 2%. The alterations in the estimated pooled prevalence was ranging from 1.3%²⁹ to 8.7%.²⁶ The recalculated prevalence of stress after removing Hai-Xin Bo et al.²⁶ was 39.4% (95% CI= 22.8–57.4, I²=99.81%). The pooled stress prevalence by assessment method is given in Figure 4 whereas the data extraction sheet is presented as supplementary data (eTable 3). The results of sensitivity analysis for depression, anxiety and stress is shown in Appendix 1. After performing scale-specific analysis for Impact of Event Scale-Revised, the prevalence of stress was 58.2% (95% CI= 26.2–90.2, I²=99.87%).

Figure 4.

Pooled prevalence of stress in China during COVID-19 pandemic.

Subgroup analysis

Our initial criteria for performance of subgroup analysis (e.g. Subgroup analysis will be conducted only if two or more studies will be assessing a particular variable) was quite lenient as it was anticipated there would be a lack of sufficient data due to novelty of topic. However, literature extraction proved this to not be the case. This allowed the criteria for conducting subgroup analysis to be strengthened by raising the cutoff (subgroup analysis was conducted only if five or more studies were assessing a particular variable).

• Frontline health care workers: We’ve considered the definition of frontline HCW presented by Zhou M. et al. to include studies in this subgroup analysis, which was “a worker directly involved in COVID-19 prevention and treatment and having direct contact with confirmed or suspected cases through patient intake, screening, inspection, testing, transport, treatment, nursing, specimen collection, pathogen detection, pathologic examination, or pathologic anatomy of medical and healthcare professional and technical personnel.”³⁴ Studies that did not provide enough information to fulfill the defined criteria concerning included medical staff were excluded from the analysis.

Eight studies totaling 10267 participants were included for analysis of depression in frontline HCW. The estimated prevalence of depression was 31.5% (95% CI= 20.7-43.5, I²= 99.30%). Similarly, 10267 total participants and the same 8 studies were also included for assessment of anxiety in frontline HCW. The pooled prevalence of anxiety in frontline HCW was 23.7% (95% CI= 16.8-31.3, I²= 98.53%). The detail about the subgroup analysis on depression and anxiety on this population is presented as a forest plot in supplementary files (eFigure 1 and eFigure 2 respectively).

• Females: The majority share (69.7%) of participants included in this analysis was female. Six studies including 16416 participants were assessed for depression, of which 28.5% (95% CI= 18.7–39.5, I²=99.52%) were found to be depressed. In contrast, 21391 females from 7 studies were included in the prevalence of anxiety determination for Chinese females. The pooled prevalence of anxiety in females was 25% (95% CI= 16.8–34.3, I²=99.53%). The pooled prevalence of depression and anxiety in Chinese females is presented as forest plots in eFigure 3 and eFigure 4 respectively.

Subgroup analysis on stress was not performed due to insufficient data.

Discussion

Our shrinking world, where international travel is prominent, has been more susceptible to quickly spreading viral epidemics, including the severe acute respiratory syndrome (SARS-CoV), Middle-East respiratory syndrome (MERS-CoV), Ebola³⁵ and now this newly identified coronavirus (COVID-19), which was declared a pandemic within the last few months. The rapid movement of a virus across a region, not to mention the planet, has the potential to negatively influence the economic, social, professional, and psychological well-being of people.³⁶ Both direct medical sequalae, and indirect effects, such as lockdowns, isolation, stigma, and financial hardships are theorized to increase the likely hood of developing mental health disorders and comorbidities. World-leading experts have expressed concerns regarding the lack of high-quality data on the psychological impact of the COVID-19 pandemic and demanded time-sensitive efforts to fulfill the need.³⁷ With this in mind, we have attempted to provide timely systematic evidence on the psychological repercussions of the COVID-19 pandemic in Chinese population.

In this meta-analysis of 19 cross-sectional studies, the prevalence of depression and anxiety is moderately high (26.9% and 21.8% respectively) however the prevalence of stress is very high (48.1%) within the population of China. Overviewing the studies from different countries, the prevalence of depression, anxiety and stress in India is 12.4%, 17.1% and 3.8% respectively. Whereas, according to Chew NW. et al, 9% of people in Singapore are depressed, 14.4% are anxious and 6.5% are stressed due to COVID-19 contagion.³⁸ Considering the mental health issues due to COVID-19, when compared to these other countries, the levels seen in China were significantly higher. We recognize, this inference may be premature as the number of studies conducted in other countries is few, and with China being the believed foci of the COVID-19 outbreak, it may take time to see its full impact on other parts of the globe.

Comparing the current pandemic situation with past epidemics (e.g. SARS, MARS or Ebola) may help in better understanding the nature of stressors, intensity of psychological burdens and coping strategies for prevailing mental health issues. A study of SARS outbreak among unit nurses in Taiwan revealed 38.5% nurses were depressed, which was significantly higher than nurses in non-SARS units (3.1%).³⁹ Similarly, in our analysis, the pooled prevalence of depression and anxiety in those personnel who were directly in contact with or managing COVID-19 patients, was relatively high (31.5% and 23.7% respectively) as compared to total estimated prevalence of depression and anxiety. In addition, depression subgroup analysis in our study revealed 28.5% females were depressed during the COVID-19 pandemic. In comparing our results with the SARS outbreak in Hong Kong, a study conducted on 126 middle-aged females during that period, consistencies are seen as they suggested 28.6% women felt depressed during SARS epidemic.⁴⁰ Another notable observation after performing sensitivity analysis was that removal of study by Hai-Xin Bo et al.²⁶ decreased the pooled prevalence of stress by 8.7%. This particular research studied the prevalence of stress among COVID-19 infected patients, and gives an impression that the type of population under investigation can influence the pooled outcome.

We, as a global community can face serious consequences if timely measures to manage mental health aren’t taken. Suicidality is one of the most fearsome sequelae of untreated psychological illness and even early in the pandemic, started to show itself. Thakur V and his associate have reported 7 cases of COVID-related suicide from all over the globe, which is alarming.⁴¹ Therefore, it essential to adapt coping strategies as defined by World Health Organization (WHO) to fight through this psychological burden.¹

Since the studies included in this meta-analysis calculated only prevalence (not incidence) of the psychological illnesses, it is important to overview the metrics related to disease progression. In 2017, a China Global Burden Disease (GBD) study estimated that 56.36 million people were depressed in China, which accounted for 21.3% of the estimated global burden of the disease.⁴² Another factor considered while evaluating mental health in China is the cultured behavior of Chinese individuals towards stressors. According to Parker G. et al, when Chinese people are under stress, depression tends to be denied, and is often shown somatically, which can lead to under-reporting.⁴³ When considering cultural factors and the early timeline of included studies, given COVID has yet to fully remit at the time of our research, it is likely the numbers reported here do not fully represent the true magnitude of COVID-19’s psychological impact on China. Our literature review clearly indicates mental health concerns related to this outbreak has had an impact on mental health illness in the Chinese population which should not be ignored, and is in need of further investigation.

A multidimensional approach is needed in future researches, which can study the anticipated repercussions of Covid-19 pandemic (like suicide, violence against health care workers, effect of isolation on elderly, damage to social, political, economic and cultural structures).^44–47 These are frustrating times and people are channeling their stress and frustration through violence. Recent medical literature suggests that health care workers in numerous countries (like Pakistan and Bangladesh) are facing physical and verbal assault by Covid-19 patients and their families. Scientist needs to address this factor as well since it can play a significant role disturbing baseline mental health of health care workers.^44,46

Our attempt to quantify the prevalence and extent of mental health concerns present in the wake of the COVID-19 pandemic provides a starting point for understanding the mental health impact of this disease and the governmental response it created. The problem has been identified, and as the pandemic unfolds further, ongoing investigation into this topic may assist in decreasing the mental health fallout of emergencies such as these. We recognize limitations in our analysis. Studies included in this meta-analysis are cross-sectional surveys, therefore randomization was not done which can lead to highly heterogeneous results (due to different characteristics of people, different cut-offs of measuring scales etc) when conducting pooled analysis. Secondly, it is not known if the studied population had pre-existing mental health illness which decompensated during the pandemic crisis.⁴⁸ Most of the studies included in our analysis did not measure baseline mental health status of surveyed participants. Lastly, generalizing a data in which 15 out of 19 studies have included medical staff within their studied population, can pose an error since the medical staff working during the COVID-19 crisis are a high risk population themselves.

Conclusion

In conclusion, the prevalence of depression and anxiety is moderately high whereas pooled prevalence of stress was found to be very high in Chinese people during this Covid-19 crisis. Chronic surveillance is essential to keep track of subtly rising mental health crises. Since the quality of related literature to date is variable, future systematic studies like ours will be necessary to further clarify the pandemic’s full impact, as well as provide a path to meaningful interventions.

Supplemental Material

sj-pdf-1-ijp-10.1177_0091217420978005 - Supplemental material for Prevalence of depression, anxiety and stress in china during COVID-19 pandemic: A systematic review with meta-analysis

Supplemental material, sj-pdf-1-ijp-10.1177_0091217420978005 for Prevalence of depression, anxiety and stress in china during COVID-19 pandemic: A systematic review with meta-analysis by Syeda Beenish Bareeqa, Syed Ijlal Ahmed, Syeda Sana Samar, Waqas Yasin, Sani Zehra, George M Monese and Robert V Gouthro in The International Journal of Psychiatry in Medicine

Footnotes

Author Contributions

SBB and SSS searched the data and screened the articles. SIA and SZ performed data extraction whereas SIA and SBB conducted analysis on extracted data. SBB, SIA, SSS and WY performed risk of bias assessment. SBB and SZ wrote the first draft with input from GMM and RVG. WY, SIA, SSS, GMM and RVG contributed to the design and final manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Syeda Beenish Bareeqa

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