key: cord-0984289-gau20zbn
authors: Nochaiwong, Surapon; Ruengorn, Chidchanok; Thavorn, Kednapa; Hutton, Brian; Awiphan, Ratanaporn; Phosuya, Chabaphai; Ruanta, Yongyuth; Wongpakaran, Nahathai; Wongpakaran, Tinakon
title: Global prevalence of mental health issues among the general population during the coronavirus disease-2019 pandemic: a systematic review and meta-analysis
date: 2021-05-13
journal: Sci Rep
DOI: 10.1038/s41598-021-89700-8
sha: e5a7a752d65a8fb0b068cc1f565a17b12e9442aa
doc_id: 984289
cord_uid: gau20zbn

To provide a contemporary global prevalence of mental health issues among the general population amid the coronavirus disease-2019 (COVID-19) pandemic. We searched electronic databases, preprint databases, grey literature, and unpublished studies from January 1, 2020, to June 16, 2020 (updated on July 11, 2020), with no language restrictions. Observational studies using validated measurement tools and reporting data on mental health issues among the general population were screened to identify all relevant studies. We have included information from 32 different countries and 398,771 participants. The pooled prevalence of mental health issues amid the COVID-19 pandemic varied widely across countries and regions and was higher than previous reports before the COVID-19 outbreak began. The global prevalence estimate was 28.0% for depression; 26.9% for anxiety; 24.1% for post-traumatic stress symptoms; 36.5% for stress; 50.0% for psychological distress; and 27.6% for sleep problems. Data are limited for other aspects of mental health issues. Our findings highlight the disparities between countries in terms of the poverty impacts of COVID-19, preparedness of countries to respond, and economic vulnerabilities that impact the prevalence of mental health problems. Research on the social and economic burden is needed to better manage mental health problems during and after epidemics or pandemics. Systematic review registration: PROSPERO CRD 42020177120.

Outcomes. The primary outcomes were key parameters that reflect the global mental health status during the COVID-19 pandemic, including depression, anxiety, PTSS, stress, psychological distress, and sleep problems (insomnia or poor sleep). To deliver more evidence regarding the psychological consequences, secondary outcomes of interest included psychological symptoms, suicidal ideation, suicide attempts, loneliness, somatic symptoms, wellbeing, alcohol drinking problems, obsessive-compulsive symptoms, panic disorder, phobia anxiety, and adjustment disorder.

Data extraction and risk of bias assessment. Two reviewers (SN and YR) independently extracted the pre-specified data using a standardised approach to gather information on the study characteristics (the first author's name, study design [cross-sectional survey, longitudinal survey, case-control, or cohort], study country, article type [published article, short report/letters/correspondence, or preprint reporting data], the data collection period), participant characteristics (mean or median age of the study population, the proportion of females, proportion of unemployment, history of mental illness, financial problems, and quarantine status [never, past, www.nature.com/scientificreports/ or current]), and predefined outcomes of interest (including assessment outcome definitions, measurement tool, and diagnostic cut-off criteria). For international studies, data were extracted based on the estimates within each country. For studies that had incomplete data or unclear information, the corresponding author was contacted by email for further clarification. The final set of data was cross-checked by the two reviewers (RA and CP), and discrepancies were addressed through a discussion. Two reviewers (SN and CR) independently assessed and appraised the methodological quality of the included studies using the Hoy and colleagues Risk of Bias Tool-10 items 21 . A score of 1 (no) or 0 (yes) was assigned to each item. The higher the score, the greater the overall risk of bias of the study, with scores ranging from 0 to 10. The included studies were then categorised as having a low (0-3 points), moderate (4-6 points), or high (7 or 10 points) risk of bias. A pair of reviewers (RA and CP) assessed the risk of bias of each study. Any disagreements were resolved by discussion.

Data synthesis and statistical methods. A two-tailed P value of less than 0.05 was considered statistically significant. We used Stata software version 16 .0 (StataCorp, College Station, TX, USA) for all analyses and generated forest plots of the summary pooled prevalence. Inter-rater agreements between reviewers for the study selection and risk of bias assessment were tested using the kappa (κ) coefficient of agreement 22 . Based on the crude information data, we recalculated and estimated the unadjusted prevalence of mental health and psychological problems using the crude numerators and denominators reported by each of the included studies. Unadjusted pooled prevalence with corresponding 95% confidence intervals (CIs) was reported for each WHO regions (Africa, America, South-East Asia, Europe, Eastern Mediterranean, and Western Pacific) and World Bank income group (low-, lower-middle-, upper-middle-, and high-income).

We employed the variance of the study-specific prevalence using the Freeman-Tukey double arcsine methods for transforming the crude data before pooling the effect estimates with a random-effect model to account for the effects of studies with extreme (small or large) prevalence estimates 23 . Heterogeneity was evaluated using the Cochran's Q test, with a p value of less than 0.10 24 . The degree of inconsistency was quantified using I 2 values, in which a value greater than 60-70% indicated the presence of substantial heterogeneity 25 .

Pre-planned subgroup analyses were performed based on the participant (i.e., age, the proportion of female sex, the proportion of unemployment, history of mental illness, financial problems, and quarantine status) and study characteristics (article type, study design, data collection, and sample size). To explore the inequality and poverty impacts across countries, subgroup analyses based on the global index and economic indices responses to the COVID-19 pandemic were performed, including (1) (4) the preparedness of countries in terms of hospital beds per 10,000 people, 2010-2018 (low, medium-low, medium, medium-high, and high) 15 ; (5) the preparedness of countries in terms of current health expenditure (% of gross domestic product [GDP] 2016; low, medium-low, medium, medium-high, and high) 15 ; (6) estimated percent change of real GDP growth based on the International Monetary Fund, April 2020 (below vs above world average [− 3.0]) 29 ; (7) the resilience of countries' business environment based on the 2020 global resilience index reports (first-, second-, third-, and fourth-quartile) 30 ; and (8) immediate economic vulnerability in terms of inbound tourism expenditure (% of GDP 2016-2018; low, medium-low, medium, medium-high, and high) 15 .

To address the robustness of our findings, we conducted a sensitivity analysis by restricting the analysis to studies with a low risk of bias (Hoy and Colleagues-Tool, 0-3 points). Furthermore, a random-effects univariate meta-regression analysis was used to explore the effect of participant and study characteristics, and the global index and economic indices responses to the COVID-19 pandemic as described above on the prevalence estimates.

The visual inspection of funnel plots was performed when there was sufficient data and tested for asymmetry using the Begg's and Egger's tests for each specific. A P value of less than 0.10 was considered to indicate statistical publication bias 31, 32 . If the publication bias was detected by the Begg's and Egger's regression test, the trim and fill method was then performed to calibrate for publication bias 33 .

Initially, the search strategy retrieved 4642 records. From these, 2682 duplicate records were removed, and 1960 records remained. Based on the title and abstract screening, we identified 498 articles that seemed to be relevant to the study question (the κ statistic for agreement between reviewers was 0.81). Of these, 107 studies fulfilled the study selection criteria and were included in the meta-analysis (Appendix, Figure S1 ). The inter-rater agreement between reviewers on the study selection and data extraction was 0.86 and 0.75, respectively. The reference list of all included studies in this review is provided in the Appendix, Table S3 .

Characteristics of included studies. In total, 398,771 participants from 32 different countries were included. The mean age was 33.5 ± 9.5 years, and the proportion of female sex was 60.9% (range, 16.0-51.6%). Table 1 summarises the characteristics of all the included studies according to World Bank income group, the global index of COVID-19 pandemic preparedness, and economic vulnerability indices. The included studies were conducted in the Africa (2 studies 34 Global prevalence of mental health issues among the general population amid the COVID-19 pandemic. 

In the subgroup analyses (Appendix , Table S8, Table S9, Table S10, Table S1, Table S12 ), the prevalence of mental health problems was higher in countries with a low to medium HDI (for depression, anxiety, PTSS, and psychological distress), high HDI (for sleep problems), high gender inequality index (for depression and PTSS), very stringent government response index (for PTSS and stress), less stringent government response index (for sleep problems), low to medium hospital beds per 10,000 people (for depression, anxiety, PTSS, stress, psychological distress, and sleep problems), low to medium current health expenditure (for depression, PTSS, and psychological distress), estimated percent change of real GDP growth 2020 below − 3.0 (for psychological distress), low resilience (fourth-quartile) of business environment (for depression, anxiety, and PTSS), medium www.nature.com/scientificreports/ resilience (second-quartile) of business environment (for psychological distress, and sleep problems), high economic vulnerability-inbound tourism expenditure (for psychological distress, sleep problems), article type-short communication/letter/correspondence (for stress), cross-sectional survey (for PTSS and psychological distress), longitudinal survey (for anxiety and stress), non-mainland China (for depression, anxiety, and psychological distress), sample size of less than 1000 (for psychological distress), sample size of more than 5000 (for PTSS), proportion of females more than 60% (for stress and sleep problems), and measurement tools (for depression, anxiety, stress, and sleep problems). However, several pre-planned subgroup analyses based on participant characteristics and secondary outcomes reported could not be performed due to limited data in the included studies. Findings from the sensitivity analysis were almost identical to the main analysis (Appendix, Table S14 ). The pooled prevalence by restricting the analysis to studies with a low risk of bias was 28 On the basis of univariate meta-regression, the analysis was suitable for the primary outcomes (Appendix, Table S15 ). The increased prevalence of mental health problems was associated with the WHO region (for depression, anxiety, and psychological distress), female gender inequality index (for depression and anxiety), the COVID-19-government response stringency index during the survey (for sleep problems), hospital beds per 10,000 people (for depression and anxiety), immediate economic vulnerability-inbound tourism expenditure (for sleep problems), study design (cross-sectional vs longitudinal survey; for stress), surveyed country (mainland China vs non-mainland China; for depression and psychological distress), and risk of bias (for PTSS).

The visual inspection of the funnel plots, and the p values tested for asymmetry using the Begg's and Egger's tests for each prevalence outcome, indicated no evidence of publication bias related to the sample size (Appendix, Table S16, and Figure S2 ). 

This study is, to the best of our knowledge, the first systematic review and meta-analysis on the overall global prevalence of mental health problems and psychosocial consequences among the general population amid the COVID-19 pandemic. Overall, our findings indicate wide variability in the prevalence of mental health problems and psychosocial consequences across countries, particularly in relation to different regions, the global index of COVID-19 pandemic preparedness, inequalities, and economic vulnerabilities indices. Two reports examined the global prevalence of common mental health disorders among adults prior to the COVID-19 outbreak. The first study was based on 174 surveys across 63 countries from 1980 to 2013. The estimated lifetime prevalence was 29.1% for all mental disorders, 9.6% for mood disorders, 12.9% for anxiety disorders, and 3.4% for substance use disorder 141 . Another report which was conducted as part of the Global Health Estimates by WHO in 2015, showed that the global estimates of depression and anxiety were 4.4% and 3.6% (more common among females than males), respectively 142 . Despite the different methodological methods used, our findings show that the pooled prevalence of mental health problems during the COVID-19 pandemic is higher than before the outbreak.

Previous studies on the prevalence of mental health problems during the COVID-19 pandemic have had substantial heterogeneity. Three systematic reviews reported the prevalence of depression, anxiety, and stress among the general population (mainly in mainland China). The first of these by Salari et al. 11 , was based on 17 included studies (from ten different countries in Asia, Europe, and the Middle East), the pooled prevalence of depression, anxiety, and stress were 33.7% (95% CI 27.5-40.6), 31.9% (95% CI 27.5-36.7), and 29.6% (95% CI 24.3-35.4), respectively. A review by Luo et al. 8 , which included 36 studies from seven different countries, reported a similar overall prevalence of 27% (95% CI 22-33) for depression and 32% (95% CI 25-39) for anxiety. However, a review by Ren et al. 17 , which focussed on only the Chinese population (8 included studies), found that the pooled prevalence was 29% (95% CI and 24% (95% CI 16-32), respectively. Nevertheless, previous systematic reviews have been mainly on investigating the prevalence of PTSS, psychological distress, and sleep problems among the patients or healthcare workers that are limited to the general population during the In this systematic review and meta-analysis, we updated and summarised the global prevalence of mental health problems and psychosocial consequences during the COVID-19 pandemic using information from 32 different countries, and 398,771 participants. A range of problems, including depression, anxiety, PTSS, stress, psychological distress, and sleep problems were reported. The global prevalence of our findings was in line with the previous reviews mentioned above in terms of depression (28.0%; 95% CI 25.0-31.2), anxiety (26.9%; 95% CI 24.0-30.0), and stress (36.5%; 95% CI 30.0-43.3). Interestingly, our findings highlight the poverty impacts of COVID-19 in terms of inequalities, the preparedness of countries to respond, and economic vulnerabilities on the prevalence of mental health problems across countries. For instance, our results suggest that countries with a low or medium HDI had a higher prevalence of depression and anxiety compared to countries with a high or very high HDI (Appendix, Table S8 ). Likewise, the prevalence of depression and anxiety was higher among countries with low hospital beds per 10,000 people (Appendix , Table S8, and Table S9 ). Our findings suggest that the poverty impacts of COVID-19 are likely to be quite significant and related to the subsequent risk of mental health problems and psychosocial consequences. Although we performed a comprehensive review by incorporating articles published together with preprint reports, there was only limited data available on Africa, low-income groups, and secondary outcomes of interest (psychological distress, suicide ideation, suicide attempts, loneliness, somatic symptoms, wellbeing, alcohol drinking problems, obsessive-compulsive symptoms, panic disorder, phobia anxiety, and adjustment disorder).

From a methodological point of view, we used a rigorous and comprehensive approach to establish an up-to-date overview of the evidence-based information on the global prevalence of mental health problems amid the COVID-19 pandemic, with no language restrictions. The systematic literature search was extensive, comprising published peer-reviewed articles and preprints reporting data to present all relevant literature, minimise bias, and up to date evidence. Our findings expanded and www.nature.com/scientificreports/ addressed the limitations of the previous systematic reviews, such as having a small sample size and number of included studies, considered more aspects of mental health circumstance, and the generalisability of evidence at a global level 5, 6, 11, 17, 18 . To address biases from different measurement tools of assessment and the cultural norms across countries, we summarised the prevalence of mental health problems and psychosocial consequences using a random-effects model to estimate the pooled data with a more conservative approach. Lastly, the sensitivity analyses were consistent with the main findings, suggesting the robustness of our findings. As such, our data can be generalised to individuals in the countries where the included studies were conducted. There were several limitations to this systematic review and meta-analysis. First, despite an advanced comprehensive search approach, data for some geographical regions according to the WHO regions and World Bank income groups, for instance, the Africa region, as well as the countries in the low-income group, were limited. Moreover, the reporting of key specific outcomes, such as suicide attempts and ideation, alcohol drinking or drug-dependence problems, and stigma towards COVID-19 infection were also limited. Second, a subgroup analysis based on participant characteristics (that is, age, sex, unemployment, history of mental illness, financial problems, and quarantine status), could not be performed as not all of the included studies reported this data. Therefore, the global prevalence of mental health problems and psychosocial consequences amid the COVID-19 pandemic cannot be established. Third, it should be noted that different methods, for example, face-to-face interviews or paper-based questionnaires, may lead to different prevalence estimates across the general population. Due to physical distancing, the included studies in this review mostly used online surveys, which can be prone to information bias and might affect the prevalence estimates of our findings. Fourth, a high degree of heterogeneity between the included studies was found in all outcomes of interest. Even though we performed a set of subgroup analyses concerning the participant characteristics, study characteristics, the global index, and economic indices responses to the COVID-19 pandemic, substantial heterogeneity persisted. However, the univariate meta-regression analysis suggested that the WHO region, gender inequality index, COVID-19-government response stringency index during the survey, hospital beds, immediate economic vulnerability (inbound tourism expenditure), study design, surveyed country (mainland China vs non-mainland China), and risk of bias were associated with an increased prevalence of mental health problems and psychosocial consequences amid the COVID-19 pandemic. Finally, we underline that the diagnostic cut-off criteria used were not uniform across the measurement tools in this review, and misclassification remains possible. The genuine variation in global mental health circumstances across countries cannot be explained by our analyses. Indeed, such variation might be predisposed by social and cultural norms, public resilience, education, ethnic differences, and environmental differences among individual study populations.

Despite the limitations of our findings, this review provides the best available evidence that can inform the epidemiology of public mental health, implement targeted initiatives, improving screening, and reduce the long-term consequences of the COVID-19 pandemic, particularly among low-income countries, or those with high inequalities, low preparedness, and high economic vulnerability. Our findings could be improved by further standardised methods and measurement tools of assessment. There is a need for individual country-level data on the mental health problems and psychosocial consequences after the COVID-19 pandemic to track and monitor public health responses. There are a number network longitudinal surveys being conducted in different countries that aim to improve our understanding of the long-term effects of the COVID-19 pandemic 144 . To promote mental wellbeing, such initiatives could also be advocated for by public health officials and governments to increase awareness and provide timely proactive interventions in routine practice.

In conclusion, this systematic review and meta-analysis provides a more comprehensive global overview and evidence of the prevalence of mental health problems among the general population amid the COVID-19 pandemic. The results of this study reveal that the mental health problems and psychosocial consequences amid the COVID-19 pandemic are a global burden, with differences between countries and regions observed. Moreover, equality and poverty impacts were found to be factors in the prevalence of mental health problems. Studies on the long-term effects of the COVID-19 pandemic on the mental health status among the general population at a global level is needed. Given the high burden of mental health problems during the COVID-19 pandemic, an improvement of screening systems and prevention, prompt multidisciplinary management, and research on the social and economic burden of the pandemic, are crucial.

The data that support the findings of this study are available from the corresponding author upon reasonable request. 

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COVID-MINDS network: global mental health in the COVID-19 pandemic

The authors thank the research assistances and all staff of Pharmacoepidemiology and Statistics Research Center (PESRC), Chiang Mai, Thailand. This work reported in this manuscript was partially supported by a grant by the Chiang Mai University, Thailand. The funder of the study had no role in the study design collection, analysis, or interpretation of the data, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit it for publication.

S.N. conceived the study and, together with C.R., K.T., R.A., C.P., and Y.R. developed the protocol. S.N. and C.R. did the literature search, selected the studies. S.N. and Y.R. extracted the relevant information. S.N. synthesised the data. S.N. wrote the first draft of the paper. K.T., B.H., N.W., and T.W. critically revised successive drafts of the paper. All authors approved the final draft of the manuscript. SN is the guarantor of the study.

The authors declare no competing interests.

The online version contains supplementary material available at https:// doi. org/ 10. 1038/ s41598-021-89700-8.Correspondence and requests for materials should be addressed to S.N.Reprints and permissions information is available at www.nature.com/reprints.Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.