Association of mental disorders with SARS-CoV-2 infection and severe health outcomes: nationwide cohort study

  1. Ha-Lim Jeon
  2. Jun Soo Kwon
  3. So-Hee Park
  4. Ju-Young Shin

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Abstract

Epidemiological data on the association between mental disorders and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity are limited.

Aims

To evaluate the association between mental disorders and the risk of SARS-CoV-2 infection and severe outcomes following COVID-19.

Method

We performed a cohort study using the Korean COVID-19 patient database based on national health insurance data. Each person with a mental or behavioural disorder (diagnosed during the 6 months prior to their first SARS-CoV-2 test) was matched by age, gender and Charlson Comorbidity Index with up to four people without mental disorders. SARS-CoV-2-positivity risk and the risk of death or severe events (intensive care unit admission, use of mechanical ventilation and acute respiratory distress syndrome) post-infection were calculated using conditional logistic regression analysis.

Results

Among 230 565 people tested for SARS-CoV-2, 33 653 (14.6%) had mental disorders; 928/33 653 (2.76%) tested SARS-CoV-2 positive and 56/928 (6.03%) died. In multivariable analysis using the matched cohort, there was no association between mental disorders and SARS-CoV-2-positivity risk (odds ratio OR = 0.95; 95% CI 0.87–1.04); however, a higher risk was associated with schizophrenia-related disorders (OR = 1.50; 95% CI 1.14–1.99). Among confirmed COVID-19 patients, the mortality risk was significantly higher in patients with than in those without mental disorders (OR = 1.99, 95% CI 1.15–3.43).

Conclusions

Mental disorders are likely contributing factors to mortality following COVID-19. Although the infection risk was not higher for people with mental disorders overall, those with schizophrenia-related disorders were more vulnerable to infection.

Article activity feed

  1. Version published to 10.1192/bjp.2020.251
  2. ScreenIT

    SciScore for 10.1101/2020.08.05.20169201: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: All procedures involving human subjects/patients were approved by the Institutional Review Board of the Sungkyunkwan University in Korea (IRB number: SKKU-2020-05-012).
    Consent: This observational study was approved with a waiver of informed consent of patients.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were conducted using the SAS statistical software provided by HIRA (SAS Institute Inc, Cary, NC, USA).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study has some limitations. First, covariates regarding lifestyle (smoking status and alcohol consumption) and socioeconomic status (education and income level) of patients were not included in the analytic model. The NHI database was constructed on the basis of claims data and thus these variables were not available. Although unmeasured confounders are known to be associated with worse outcomes after SARS-CoV-2 infection, the result from the sensitivity analysis suggests that an unmeasured confounder associated with both mental disorders and death by a risk ratio of 3.08-fold each is required to explain away the observed OR of 1.84. Hence, our findings would be robust unless there is an unmeasured confounder of such magnitude. Second, we identified severe events based on diagnostic and procedure codes, which were recorded for administrative purpose; thus, there was potential for misclassification of outcomes. However, a validation study comparing the claims database and inpatients’ medical records of hospitals reported that the overall agreement of diagnosis was 82.0%.(29) Procedure codes, which are directly related to payment from the NHI, are also likely to be highly valid. Third, although we utilized the database covering overall COVID-19 patients in Korea, the number of patients with mental disorders was not sufficient to evaluate the risk of death and severe events by subgroup analysis based on more subdivided disease type such as depression, anxiety, and dementia....

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.08.05.20169201v1 on medRxiv