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Depression, worry, and loneliness are associated with subsequent risk of hospitalization for COVID-19: a prospective study

Published online by Cambridge University Press:  19 May 2022

Siwen Wang*
Affiliation:
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
Luwei Quan
Affiliation:
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Ming Ding
Affiliation:
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Jae H. Kang
Affiliation:
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
Karestan C. Koenen
Affiliation:
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA Psychiatric Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
Laura D. Kubzansky
Affiliation:
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Westyn Branch-Elliman
Affiliation:
Department of Medicine, VA Boston Healthcare System, Boston, MA, USA Harvard Medical School, Boston, MA, USA
Jorge E. Chavarro
Affiliation:
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
Andrea L. Roberts
Affiliation:
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
*
Author for correspondence: Siwen Wang, E-mail: siwenwang@hsph.harvard.edu
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Abstract

Background

Pre-pandemic psychological distress is associated with increased susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but associations with the coronavirus disease 2019 (COVID-19) severity are not established. The authors examined the associations between distress prior to SARS-CoV-2 infection and subsequent risk of hospitalization.

Methods

Between April 2020 (baseline) and April 2021, we followed 54 781 participants from three ongoing cohorts: Nurses' Health Study II (NHSII), Nurses' Health Study 3 (NHS3), and the Growing Up Today Study (GUTS) who reported no current or prior SARS-CoV-2 infection at baseline. Chronic depression was assessed during 2010–2019. Depression, anxiety, worry about COVID-19, perceived stress, and loneliness were measured at baseline. SARS-CoV-2 infection and hospitalization due to COVID-19 was self-reported. Relative risks (RRs) were calculated by Poisson regression.

Results

3663 participants reported a positive SARS-CoV-2 test (mean age = 55.0 years, standard deviation = 13.8) during follow-up. Among these participants, chronic depression prior to the pandemic [RR = 1.72; 95% confidence interval (CI) 1.20–2.46], and probable depression (RR = 1.81, 95% CI 1.08–3.03), being very worried about COVID-19 (RR = 1.79; 95% CI 1.12–2.86), and loneliness (RR = 1.81, 95% CI 1.02–3.20) reported at baseline were each associated with subsequent COVID-19 hospitalization, adjusting for demographic factors and healthcare worker status. Anxiety and perceived stress were not associated with hospitalization. Depression, worry about COVID-19, and loneliness were as strongly associated with hospitalization as were high cholesterol and hypertension, established risk factors for COVID-19 severity.

Conclusions

Psychological distress may be a risk factor for hospitalization in patients with SARS-CoV-2 infection. Assessment of psychological distress may identify patients at greater risk of hospitalization. Future work should examine whether addressing distress improves physical health outcomes.

Type
Original Article
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has led to over 4.4 million hospital admissions in the United States (CDC, 2022), severely straining healthcare systems (Grimm, Reference Grimm2021). Identified risk factors for hospitalization due to severe coronavirus disease 2019 (COVID-19) include age, obesity, asthma, hypertension, and diabetes (Garg et al., Reference Garg, Kim, Whitaker, O'Halloran, Cummings, Holstein and Fry2020), in addition to behaviors such as smoking (Hamer, Kivimäki, Gale, & Batty, Reference Hamer, Kivimäki, Gale and Batty2020). Various forms of distress, including depression, anxiety, and perceived stress, have also been implicated in elevated susceptibility to infections, including SARS-CoV-2 (Batty et al., Reference Batty, Deary, Luciano, Altschul, Kivimäki and Gale2020; Orlando et al., Reference Orlando, Rea, Savaré, Guarino, Mucherino, Perrella and Corrao2021; Taquet, Luciano, Geddes, & Harrison, Reference Taquet, Luciano, Geddes and Harrison2021; Yang et al., Reference Yang, Chen, Hu, Chen, Zeng, Sun and Song2020a), as well as increased severity of infectious disease (Aiello, Simanek, Stebbins, & Dowd, Reference Aiello, Simanek, Stebbins, Dowd, Kivimäki, Batty, Steptoe and Kawachi2018; Cohen et al., Reference Cohen, Doyle, Skoner, Fireman, Gwaltney and Newsom1995; Falagas, Karamanidou, Kastoris, Karlis, & Rafailidis, Reference Falagas, Karamanidou, Kastoris, Karlis and Rafailidis2010; Janicki Deverts, Cohen, & Doyle, Reference Janicki Deverts, Cohen and Doyle2017). Numerous prospective studies have additionally identified loneliness (LeRoy, Murdock, Jaremka, Loya, & Fagundes, Reference LeRoy, Murdock, Jaremka, Loya and Fagundes2017) and other factors associated with distress (e.g. small social network, low emotional support) (Cohen, Doyle, Skoner, Rabin, & Gwaltney, Reference Cohen, Doyle, Skoner, Rabin and Gwaltney1997; Cohen, Doyle, Turner, Alper, & Skoner, Reference Cohen, Doyle, Turner, Alper and Skoner2003) as potential contributors to a worse course of respiratory infections, although not consistently (Bu, Philip, & Fancourt, Reference Bu, Philip and Fancourt2020; Hamrick, Cohen, & Rodriguez, Reference Hamrick, Cohen and Rodriguez2002).

Better understanding of the links between psychological distress and risk of COVID-19-hospitalization may help prevent severe outcomes and strain on healthcare systems by identifying those at greatest risk. Although the Centers for Disease Control and Prevention have identified mental health conditions as risk factors for COVID-19 severity (People with Certain Medical Conditions, 2021), our understanding of the association of distress with COVID-19 severity remains incomplete. Prior studies have primarily investigated mortality as the outcome (Lee et al., Reference Lee, Yang, Moon, Yoo, Ha, Kim and Yon2020; Li, Li, Fortunati, & Krystal, Reference Li, Li, Fortunati and Krystal2020; Nemani et al., Reference Nemani, Li, Olfson, Blessing, Razavian, Chen and Goff2021; Wang, Xu, & Volkow, Reference Wang, Xu and Volkow2021), leaving the association with hospitalization comparatively unexplored. Most studies used medical records of mental illness diagnoses to measure psychological distress (Lee et al., Reference Lee, Yang, Moon, Yoo, Ha, Kim and Yon2020; Li et al., Reference Li, Li, Fortunati and Krystal2020; Nemani et al., Reference Nemani, Li, Olfson, Blessing, Razavian, Chen and Goff2021; Orlando et al., Reference Orlando, Rea, Savaré, Guarino, Mucherino, Perrella and Corrao2021; Taquet et al., Reference Taquet, Luciano, Geddes and Harrison2021; Wang et al., Reference Wang, Xu and Volkow2021; Yang et al., Reference Yang, Chen, Hu, Chen, Zeng, Sun and Song2020a). However, medical records have only moderate sensitivity to detect common mental disorders such as depression and anxiety (Beesley et al., Reference Beesley, Salvatore, Fritsche, Pandit, Rao, Brummett and Mukherjee2020; Spiranovic, Matthews, Scanlan, & Kirkby, Reference Spiranovic, Matthews, Scanlan and Kirkby2016; Townsend, Walkup, Crystal, & Olfson, Reference Townsend, Walkup, Crystal and Olfson2012), which are frequently undiagnosed (Gwynn et al., Reference Gwynn, McQuistion, McVeigh, Garg, Frieden and Thorpe2008; Ko, Farr, Dietz, & Robbins, Reference Ko, Farr, Dietz and Robbins2012; Perruche et al., Reference Perruche, Elie, Ussel, Ray, Thys, Bleichner and Claessens2011). Additionally, some medical record studies examined the diagnosis of any psychiatric disorder as a single exposure, reducing the utility for intervention and prediction (Li et al., Reference Li, Li, Fortunati and Krystal2020; Wang et al., Reference Wang, Xu and Volkow2021). No studies have examined other common manifestations of distress, such as perceived stress and loneliness in relation to hospitalization from COVID-19.

In the present study, we prospectively examined whether various manifestations of psychological distress prior to infection with SARS-CoV-2 predicted hospitalization among individuals after SARS-CoV-2 infection, using data from three large longitudinal cohorts: the Nurses' Health Study II (NHSII), the Nurses' Health Study III (NHS3), and the Growing Up Today Study (GUTS) (Bao et al., Reference Bao, Bertoia, Lenart, Stampfer, Willett, Speizer and Chavarro2016). We additionally examined the extent to which established risk factors for COVID-19 hospitalization (e.g. age, diabetes, asthma, hypertension, smoking, obesity) accounted for possible associations.

Methods

Study design and population

Study participants were drawn from the Nurses Health cohorts, a set of cohorts initiated in the early 1970s to study the long-term health effects of exogenous hormone use in the early 1970s in a medically sophisticated group. The NHSII is a cohort of 116 429 female registered nurses living in the US, enrolled in 1989 at ages of 25–42 years and followed biennially. The NHSII was established to study the health effects of oral contraceptive use and other health risk factors among women of reproductive age. The NHS3, currently recruiting, was established in 2010 and includes more than 40 000 female nurses aged 18 years and older, living in the US or Canada and followed biannually using web-based questionnaires. NHS3 recruited more participants of different race/ethnicity groups. Recruitment was extended to male nurses in 2015 (N = 856). GUTS began in 1996 when NHSII participants enrolled their offspring (N = 27 793) aged 9–17 years to study the potential impacts of factors (e.g. diet and exercise) that influence weight change trajectory throughout the life course.

From April 2020 to May 2020, we invited participants who returned the most recent main cohort questionnaire to complete a supplementary online COVID-19 survey. Of 105 662 invited participants, 58 612 (55%) responded to the first COVID-19 questionnaire from April 2020 to August 2020 (termed ‘baseline’ henceforth). Respondents were then administered monthly surveys. Additional weekly surveys were administered to those who self-identified as frontline healthcare workers (n = 23 053). In August 2020, the surveys changed to quarterly administration (online Supplementary Figs S1 and S2). The end of follow-up for the current analysis was 27 April 2021. Among 58 612 people who responded to the COVID-19 baseline survey, we further restricted the analysis to 54 781 participants with no documented history of SARS-CoV-2 infection and not hospitalized at baseline who returned at least one follow-up questionnaire.

The study was approved by the Partners Healthcare System Institutional Review Board. Return of questionnaires constituted implied consent.

Measures

Forms of distress

Chronic depression in the 10 years prior to the COVID-19 pandemic was derived from multiple indicators queried at varying intervals on main cohort questionnaires, 2010–2019. These included self-reported physician-diagnosed depression, use of antidepressants, and depressive symptoms as reported on the Center for Epidemiologic Studies Depression Scale-10 (CESD-10) and the Patient Health Questionnaire-9 (PHQ-9) (online Supplementary Table S1). Participants were considered to have a history of chronic depression if they reported any indicator of depression at two or more time points.

All other forms of distress were assessed at the COVID-19 study baseline. Current depression and anxiety symptoms were assessed with the PHQ-4, which combines a 2-item measure of depression (PHQ-2) and a 2-item measure of anxiety [Generalized Anxiety Disorder-2 (GAD-2)] (Kroenke, Spitzer, Williams, & Lowe, Reference Kroenke, Spitzer, Williams and Lowe2009). The PHQ-4 queries frequency of symptoms, with response options 0 (‘not at all’) to 3 (‘nearly every day’). A summed score of 3 or greater on each subscale indicates probable major depressive disorder or anxiety disorder (Kroenke, Spitzer, & Williams, Reference Kroenke, Spitzer and Williams2003; Kroenke, Spitzer, Williams, Monahan, & Lowe, Reference Kroenke, Spitzer, Williams, Monahan and Lowe2007). To create reference groups with no symptoms, and to examine possible dose-dependent relations, we divided these scores into three levels for analysis: 0 points (reference), 1–2 points (subclinical symptoms), ⩾3 points (probable depression or anxiety). The PHQ-2 and GAD-2 have been validated against clinical diagnosis (Kroenke et al., Reference Kroenke, Spitzer and Williams2003, Reference Kroenke, Spitzer, Williams, Monahan and Lowe2007, Reference Kroenke, Spitzer, Williams and Lowe2009; Lowe et al., Reference Lowe, Wahl, Rose, Spitzer, Glaesmer, Wingenfeld and Brahler2010). Worry about COVID-19 was assessed with a single question, ‘How worried are you about COVID-19?’ with response options: ‘not at all’, ‘not very’, ‘somewhat’, and ‘very worried’ (YouGov, 2020). ‘Not at all’ and ‘not very worried’ were combined to serve as the reference group, as only 5.9% participants responded ‘not at all worried’.

Due to concerns about participant burden, two additional forms of distress were assessed only among non-healthcare workers. The 4-item Perceived Stress Scale (PSS-4) (Cohen, Reference Cohen, Spacapan and Oskamp1988), a shortened version of the well-validated 14-item PSS (Cohen, Kamarck, & Mermelstein, Reference Cohen, Kamarck and Mermelstein1983), assesses the ability to cope with existing stressors. Total scores range from 0 to 16, with higher scores indicating higher levels of perceived stress, with satisfactory psychometrics (Cohen, Reference Cohen, Spacapan and Oskamp1988; Mitchell, Crane, & Kim, Reference Mitchell, Crane and Kim2008; Vallejo, Vallejo-Slocker, Fernandez-Abascal, & Mananes, Reference Vallejo, Vallejo-Slocker, Fernandez-Abascal and Mananes2018; Warttig, Forshaw, South, & White, Reference Warttig, Forshaw, South and White2013). Loneliness was assessed with the 3-item UCLA Loneliness Scale (Hughes, Waite, Hawkley, & Cacioppo, Reference Hughes, Waite, Hawkley and Cacioppo2004) which has demonstrated good internal consistency reliability and validity (Hughes et al., Reference Hughes, Waite, Hawkley and Cacioppo2004; Steptoe, Shankar, Demakakos, & Wardle, Reference Steptoe, Shankar, Demakakos and Wardle2013). Participants reported how often they felt: (i) lack of companionship; (ii) left out; and (iii) isolated from others. Responses were coded as 1 (‘hardly ever’), 2 (‘some of the time’), and 3 (‘often’), with higher scores indicating greater loneliness. We divided the score into three levels for analysis, 3 points (loneliness hardly ever, reference), 3–5 points (less than some of the time), and ⩾6 points (some of the time or often) (Steptoe et al., Reference Steptoe, Shankar, Demakakos and Wardle2013). For all continuous scores, effects associated with an increase of one interquartile range (IQR) were estimated. Because the distribution of the scores were skewed, IQRs were approximate.

COVID-19 infection and hospitalization

Past 7-, 30-, and 90-day positive SARS-CoV-2 diagnostic test (antibody, antigen, or PCR), COVID-19 symptoms, and hospitalization due to COVID-19 occurring since 1 March 2020, were self-reported on all questionnaires. Participants were asked specifically, ‘Have you been hospitalized because of COVID-19?’ and the treatments they received, including intravenous fluid, oxygen through nasal prong or facial mask, ICU admission, and invasive ventilation.

Covariates

All covariates were assessed prior to the pandemic in main cohort questionnaires, using the most recent data available (online Supplementary Table S2). Demographic factors included age, race/ethnic identity, sex, and educational attainment of the participant (GUTS) or their spouse/partner (NHSII and NHS3). Risk factors for COVID-19 severity included body mass index (BMI), smoking, and history of clinician-diagnosed: diabetes, hypertension, high cholesterol, asthma, and cancer (yes/no for each of the diseases).

Statistical analysis

To examine the association of distress and risk of SARS-CoV-2 infection, we compared level of distress among participants with and without a positive SARS-CoV-2 diagnostic test during follow-up. Among participants who reported a positive SARS-CoV-2 test, we compared the prevalence of established risk factors for severe COVID-19 and demographic factors by forms of distress at baseline. To examine the association of distress with risk of subsequent hospitalization for COVID-19, we fit Poisson regression models with hospitalization as the dependent variable with each form of distress as the independent variable in separate models adjusted for demographic factors, educational attainment, and healthcare worker status. To examine whether health risk factors that commonly co-occur with distress might account for possible associations, we further adjusted for: (1) health behavioral factors including BMI and smoking; and (2) health behavioral factors and history of hypertension, diabetes, high cholesterol, asthma, and cancer.

We conducted several sensitivity analyses. First, as frontline healthcare workers have higher risk of infection and increased psychological distress than non-healthcare workers (Chou et al., Reference Chou, Dana, Buckley, Selph, Fu and Totten2020; Preti et al., Reference Preti, Di Mattei, Perego, Ferrari, Mazzetti, Taranto and Calati2020; Sasaki, Kuroda, Tsuno, & Kawakami, Reference Sasaki, Kuroda, Tsuno and Kawakami2020; Zheng et al., Reference Zheng, Wang, Zhou, Liu, Li, Sun and Wang2020), we investigated the association of forms of distress with COVID-19 hospitalization stratified by healthcare worker status and tested a distress-by-healthcare-worker-status interaction term. Second, we further adjusted for month using indicator variables, to account for the different phases of the pandemic. Third, although we excluded participants who reported a positive SARS-CoV-2 test at baseline, some participants reported COVID-19-related symptoms at baseline. Therefore, to ensure that distress preceded SARS-COV-2 infection, we further excluded 175 respondents who were identified as possible cases using a symptom-based predictor of SARS-CoV-2 infection (Rich-Edwards et al., Reference Rich-Edwards, Ding, Rocheleau, Boiano, Kang, Becene and Lawson2021). Fourth, we excluded 104 participants who reported a positive SARS-COV-2 test within 30 days of return of the baseline questionnaire, to minimize the possibility that prodromal symptoms were causing psychological distress. Fifth, to remove possible effects of vaccination on SARS-CoV-2 susceptibility and severity, we excluded people who reported SARS-COV-2 infections after participants could have been fully vaccinated (1 February 2021 for active healthcare workers, N excluded = 225, and 1 April 2021 for non-healthcare workers, N excluded = 21). Sixth, we further adjusted for cohort and number of questionnaires. Seventh, to examine the possible difference in sex, we stratified the analysis by sex. As only 1 male participant was hospitalized, models restricted to males did not convergence. We presented analyses to female participants (n = 3535). Eighth, we fit models using the most recent measures of pre-infection psychological distress as independent variables. Ninth, to evaluate whether loneliness might be a proxy for low availability of getting care when sick, we adjusted for the living situation reported at baseline (living alone or not).

For all models, relative risks (RRs) were estimated using generalized linear models (Zou, Reference Zou2004) in SAS 9.4 (SAS Institute). A 2-sided p < 0.05 was considered statistically significant.

Results

The 54 781 participants who returned at least one follow-up questionnaire were primarily female (96.6%) and White (96.5%), with mean age = 57.5 years (s.d. = 13.8). More than one third of participants (38.0%) were frontline healthcare workers. We documented 3663 incident cases of SARS-CoV-2 (6.7% of participants) from 1 May 2020, to 1 April 2021. At baseline, the mean age of participants who had a positive SARS-CoV-2 test during follow-up was 55.0 years (s.d. = 13.8); 96.5% were female, 128 (3.5%) were male, 96.7% were White, and 52.1% were frontline healthcare workers. The mean (s.d.) age of male participants was 33.4 (4.9). 34 (26.6%) of male participants were active healthcare workers. The median time from return of baseline questionnaire to positive SARS-CoV-2 test was 30 weeks (range, 1–47 weeks). Active healthcare workers had elevated level of depression and anxiety at baseline compared to non-active healthcare workers (depressive symptoms: 1.18 v. 1.06; anxiety symptoms: 1.60 v. 1.35). The prevalence of all forms of distress at baseline was similar among respondents who reported a positive SARS-CoV-2 test during follow up and those who did not (online Supplementary Table S3).

Respondents with probable depression or anxiety at baseline were younger, had higher BMI, had a higher prevalence of asthma, and were more likely to be frontline healthcare workers than those who had no symptoms of these disorders (Table 1). Compared with participants who reported not being worried or not very worried about COVID-19, those reporting being very worried were more likely to be female, to be racial or ethnic minorities, to be frontline healthcare workers, to have a higher BMI, and to have a comorbidity. Lonely participants were younger than participants who were hardly ever lonely. Chronic depression and all forms of distress at baseline were correlated (Table 2, all p < 0.001), with depression and anxiety most strongly correlated (Spearman correlation = 0.63). Despite appearing to be similar constructs, each of the 2 items that comprised the GAD-2 anxiety measure was only modestly correlated with worry about COVID-19 (rho = 0.29, 0.26, p < 0.001).

Table 1. Health and demographic characteristics by forms of distress at baseline (April–August 2020), among participants who ever tested positive for SARS-CoV-2 between April 2020 – April 2021, N = 3663

aNumbers do not add to 100% because mid-levels of variables, i.e., subclinical depressive and anxious symptoms, somewhat worried, and somewhat lonely, are not shown due to space constraints; UCLA loneliness information was collected only in non-active health care workers.

bParticipants' own education attainment in GUTS (unmarried category did not apply).

Table 2. Spearman correlations between forms of distress among persons with a positive SARS-CoV-2 test from April 2020 to April 2021, NHS II, NHS3, and GUTS, N = 3663

Note. NHS, Nurses' Health Study; GUTS, Growing Up Today Study. Perceived stress and loneliness were queried in non-active health care workers only.

*p < 0.001.

All subsequent analyses were conducted among the 3663 respondents with a positive SARS-CoV-2 test during follow-up. Of these, 132 (4%) were hospitalized due to COVID-19, of whom 75% received oxygen and 20% reported ICU admission. Chronic depression prior to the pandemic was significantly associated with COVID-19 hospitalization (risk ratio (RR) = 1.72; 95% confidence interval (CI) 1.20–2.46, Fig. 1) adjusted for demographic factors. Probable depression at baseline was also associated with COVID-19 hospitalization (RR = 1.81; 95% CI 1.08–3.03, p = 0.02, Table 3). In analyses examining depressive symptoms as a continuous measure, an IQR increase in depressive symptoms was associated with 45% increased risk of COVID-19 hospitalization (95% CI 17–81%, p < 0.001).

Fig. 1. Relative Risks (RRs) and 95% Confidence Intervals (CIs) of the associations between forms of distress at baseline and established risk factors for severe COVID-19 in relation to COVID-19 hospitalization, April 2020 – April 2021, N = 3663. Multivariable model adjusted for age, sex, racial identity, healthcare worker status and partner's education (participants' own education attainment in GUTS). Perceived stress and loneliness were queried in non-active health care workers only.

Note. PHQ-2, 2-item Patient Health Questionnaire; GAD-2, 2-item Generalized Anxiety Disorder.

Table 3. Association of forms of distress prior to infection and risk of COVID-19 hospitalization among persons testing positive for SARS-CoV-2, April 2020 – April 2021, N = 3663

Note. PHQ-2, 2-item Patient Health Questionnaire-2; GAD-2, 2-item Generalized Anxiety Disorder; perceived stress and loneliness were queried in non-active health care workers only. IQR, interquartile range.

a p trend analysis used indicator levels as a continuous variable.

*p < 0.05, **p < 0.01, ***p < 0.001.

Worry about COVID-19 was significantly associated with COVID-19 hospitalization (very worried, RR = 1.79; 95% CI 1.12–2.86; p trend = 0.02), as was loneliness (RR = 1.81, 95% CI 1.02–3.20, p = 0.04). An IQR increase in the continuous loneliness score was associated with 29% increased risk of COVID-19 hospitalization (95% CI 1–65%, p = 0.04). Anxiety and perceived stress were not associated with hospitalization, although perceived stress could only be assessed in non-healthcare workers. Figure 1 shows risk ratios for hospitalization associated with forms of distress and, for comparison, several established risk factors for severe COVID-19. The magnitude of the associations with COVID-19 hospitalization was as strong for chronic depression prior to the pandemic and worry about COVID-19 at baseline as for hypertension and high cholesterol.

In models further adjusted for smoking and BMI (Table 3, model 2), associations between chronic depression, depression at baseline, worry, and loneliness and COVID-19 hospitalization were attenuated (attenuation range, 13–29%). Higher BMI among persons with distress accounted for most of the attenuation. Associations were further attenuated after adjustment for comorbidities (additional attenuation, 6–25%; total attenuation due to all covariates, 23–46%), primarily due to the higher prevalence of asthma among persons with distress. Depressive symptoms coded continuously remained significantly associated with increased risk for COVID-19 hospitalization in the model fully adjusted for health behaviors and comorbidities (RR per IQR = 1.32, 95% CI 1.06–1.65, p = 0.01).

Associations of distress with COVID-19 hospitalization were generally somewhat stronger in non-healthcare workers than healthcare workers, though these differences were not statistically significant (data not shown). Results were comparable in models further adjusted for month, excluding probable baseline SARS-CoV-2 cases, excluding cases diagnosed within 30 days after return of baseline questionnaire, further adjusting for cohort number, restricting the analysis to female, and using the most recent distress measures prior to infection. In analyses of loneliness, results were similar in models further adjusted for living alone (online Supplementary Table S4).

Discussion

In this prospective study of 54 809 people who reported no history of SARS-CoV-2 infection, in demographically adjusted models, chronic depression prior to the pandemic, and probable depression, worry about COVID-19, and loneliness early in the pandemic were associated with increased risk for hospitalization due to COVID-19, among the 3663 individuals who subsequently became infected with SARS-CoV-2. There was no association of anxiety or perceived stress with risk of hospitalization, although we were not able to assess perceived stress among healthcare workers. Depression, worry about COVID-19, and loneliness were as strongly associated with hospitalization as were established risk factors for COVID-19 severity, such as high cholesterol and hypertension.

Higher prevalence of risk factors for COVID-19 severity, in particular, higher BMI and asthma accounted for 23–46% of these associations. In fully adjusted models accounting for all comorbidities, only depressive symptoms at baseline remained significantly associated with risk of COVID-19 hospitalization. We did not have information about whether distress preceded weight gain and asthma or the reverse. Evidence from longitudinal studies suggests a bi-directional association of depression and high BMI, with depression increasing risk of subsequent obesity and obesity increasing the risk of subsequent depression. Longitudinal and Mendelian randomization studies also indicate bi-directional effects between depression and adult-onset asthma, although evidence that asthma predicts incident depression is not consistent (Gao et al., Reference Gao, Zhao, Zhang, Gao, Shen, Chen and Zhang2015; Kim, Min, Oh, Lim, & Choi, Reference Kim, Min, Oh, Lim and Choi2019; Lehto, Pedersen, Almqvist, Lu, & Brew, Reference Lehto, Pedersen, Almqvist, Lu and Brew2019; Lu et al., Reference Lu, Chen, Xu, Bao, Ma, Guo and Ruan2018; Zhu et al., Reference Zhu, Zhu, Liu, Shi, Shen, Yang and Liang2019). Mendelian randomization studies show causal effects of both BMI and body fat on loneliness, but not loneliness on BMI (Abdellaoui et al., Reference Abdellaoui, Sanchez-Roige, Sealock, Treur, Dennis, Fontanillas and Boomsma2019; Day, Ong, & Perry, Reference Day, Ong and Perry2018); however, the direction of causality with asthma has not been well studied. Therefore, depression and loneliness may have increased risk of obesity and asthma, and obesity and asthma may also have increased risk of depression and loneliness.

A single prior study using data from the UK Biobank assessed depressive and anxious symptoms with the PHQ-4 in 2006–2010 and found an association between these symptoms and susceptibility to SARS-CoV-2 infection and COVID-19 hospitalization over an 1-year period in age- and sex-adjusted models, but not after further adjustment for ethnicity, comorbidity, and lifestyle factors (Batty et al., Reference Batty, Deary, Luciano, Altschul, Kivimäki and Gale2020). However, the study conflated risk of infection and risk of hospitalization, as the reference group included people uninfected with SARS-CoV-2 and people infected with SARS-CoV-2 who were not hospitalized. As risk factors for SARS-CoV-2 infection and COVID-19 severity may differ (Yang, Gui, & Xiong, Reference Yang, Gui and Xiong2020b), the implications of these findings are unclear.

Chronic depression is pro-inflammatory and immunosuppressive (Leonard, Reference Leonard2010). Psychological distress, more generally, may increase risk of severe clinical outcomes in respiratory infections (Aiello, Simanek, Stebbins, & Dowd, Reference Aiello, Simanek, Stebbins, Dowd, Kivimäki, Batty, Steptoe and Kawachi2018; Bu et al., Reference Bu, Philip and Fancourt2020; Falagas et al., Reference Falagas, Karamanidou, Kastoris, Karlis and Rafailidis2010; LeRoy et al., Reference LeRoy, Murdock, Jaremka, Loya and Fagundes2017), possibly through dysregulation of stress signaling pathways. Sustained stress leads to protracted HPA-axis stimulation and subsequent chronic immune suppression (Guilliams & Edwards, Reference Guilliams and Edwards2010) as well as elevated levels of circulating cortisol (Hannibal & Bishop, Reference Hannibal and Bishop2014), which leads to susceptibility to infection and more severe clinical outcomes among those infected (Tian, Hou, Li, & Yuan, Reference Tian, Hou, Li and Yuan2014). Chronic exposure to elevated cortisol may additionally result in an inability to attenuate levels of pro-inflammatory cytokines post-infection (Chi et al., Reference Chi, Zhu, Wen, Cui, Ge, Jiao and Zhou2013; Cohen et al., Reference Cohen, Doyle, Skoner, Rabin and Gwaltney1997; Tian et al., Reference Tian, Hou, Li and Yuan2014), which further compounds disease severity (Del Valle et al., Reference Del Valle, Kim-Schulze, Huang, Beckmann, Nirenberg, Wang and Gnjatic2020; Short, Kroeze, Fouchier, & Kuiken, Reference Short, Kroeze, Fouchier and Kuiken2014; Zhao et al., Reference Zhao, Huang, Zhang, Zhang, Li and Zhou2018) and increases risk of hospitalization (Yende et al., Reference Yende, Tuomanen, Wunderink, Kanaya, Newman, Harris and Kritchevsky2005). Despite common pathways linking depression, anxiety, stress, and loneliness to immune dysregulation, we did not find associations of anxiety and perceived stress with hospitalization risk. Of note, perceived stress has not been consistently associated with physical health outcomes (Macleod et al., Reference Macleod, Davey Smith, Heslop, Metcalfe, Carroll and Hart2002; Väänänen et al., Reference Väänänen, Murray, Koskinen, Vahtera, Kouvonen and Kivimäki2009).

The present study was conducted in a primarily female sample. Prior studies have suggested men with COVID-19 may face higher rates of hospitalization than women. A systematic review of COVID-19 outcomes in Europe found that men with COVID-19 experienced higher rates of hospitalization than women (Gebhard, Regitz-Zagrosek, Neuhauser, Morgan, & Klein, Reference Gebhard, Regitz-Zagrosek, Neuhauser, Morgan and Klein2020). Multicenter cohort studies have similarly found higher rates of COVID-19 hospitalization in men vs. women, although these studies were not adjusted for factors which may affect hospitalization, such as age and health comorbidities (Garg et al., Reference Garg, Kim, Whitaker, O'Halloran, Cummings, Holstein and Fry2020; Gomez et al., Reference Gomez, Du-Fay-de-Lavallaz, Fugar, Sarau, Simmons, Clark and Volgman2021). Past studies of SARS-CoV and MERS-CoV outbreaks have also found men to have higher case fatality rates than women (Ebrahim et al., Reference Ebrahim, Maher, Kanagasabai, Alfaraj, Alzahrani, Alqahtani and Memish2021; Karlberg, Chong, & Lai, Reference Karlberg, Chong and Lai2004). Additional research is therefore needed to investigate the association of distress with risk of COVID-19 hospitalization in men.

Our study has several strengths. Periodic surveys were sent to three large cohorts prospectively measuring distress, incident infection, and hospitalization over a 1-year period during an active stage of the COVID-19 pandemic. Distress was measured early in the pandemic, which may have more accurately captured recent distress compared with studies examining pre-pandemic medical records of mental illness. Findings were also robust to exclusion of persons with COVID-19 diagnosis within 30 days of the baseline questionnaire. We examined some largely unexplored forms of distress, such as loneliness, perceived stress, and worry about COVID-19.

Our study has several limitations. Baseline anxiety and depression were measured with brief screeners rather than clinician diagnoses and may have been misclassified. Worry about COVID-19 was measured with a single question, which may have lower reliability than a multi-item measure (Diamantopoulos, Sarstedt, Fuchs, Wilczynski, & Kaiser, Reference Diamantopoulos, Sarstedt, Fuchs, Wilczynski and Kaiser2012). SARS-CoV-2 infection and hospitalization due to COVID-19 were self-reported, although self-reported health outcomes have had good validity in these cohorts (Forman, Curhan, & Taylor, Reference Forman, Curhan and Taylor2008; Troy et al., Reference Troy, Hunter, Manson, Colditz, Stampfer and Willett1995). We were not able to capture COVID-19-related mortality. Finally, our sample of individuals infected with COVID-19 was relatively small, limiting statistical power, and was comprised primarily of white female nurses, limiting generalizability.

Conclusions

In this prospective study of adults, we found chronic depression prior to the pandemic and probable depression, worry about COVID-19, and loneliness predicted hospitalization due to COVID-19, which was in part accounted for by poorer physical health in persons with these forms of distress. Depressive symptoms early in the pandemic remained associated with COVID-19 hospitalization even after adjusting for health-related behaviors and comorbidities. Our findings suggest the need to consider psychological health in addition to physical health as risk factors of severe COVID-19. Future research should examine whether reducing distress, in addition to other medical interventions, improves outcomes in patients with SARS-CoV-2 and other infectious diseases.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291722000691

Financial support

This research was supported by NIH NICHD grant 3R01HD094725-02S1 (to ALR). Other support includes grants U01HL145386, R24ES028521, U01 CA176726, R01 CA67262, and R01 HD057368 from the National Institutes of Health; the Dean's Fund for Scientific Advancement Acceleration Award from the Harvard T. H. Chan School of Public Health; and the Massachusetts Consortium on Pathogen Readiness Evergrande COVID-19 Response Fund Award.

Conflict of interest

WBE is the site PI for a COVID-19 therapeutics study funded by Gilead pharmaceuticals (funds to institution). Views expressed are those of the authors and do not necessarily represent those of the US Federal Government.

References

Abdellaoui, A., Sanchez-Roige, S., Sealock, J., Treur, J. L., Dennis, J., Fontanillas, P., … Boomsma, D. I. (2019). Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness. Human Molecular genetics, 28(22), 38533865. https://doi.org/10.1093/hmg/ddz219.CrossRefGoogle ScholarPubMed
Aiello, A. E., Simanek, A. M., Stebbins, R. C., & Dowd, J. B. (2018). Psychosocial Influences on Infectious diseases. In Kivimäki, M., Batty, G.D., Steptoe, A., & Kawachi, I. (Eds.), The Routledge international handbook of psychosocial epidemiology (1st ed., Vol. 1, pp. 281300). New York: Routledge. https://doi.org/10.4324/9781315673097-13.Google Scholar
Bao, Y., Bertoia, M. L., Lenart, E. B., Stampfer, M. J., Willett, W. C., Speizer, F. E., … Chavarro, J. E. (2016). Origin, methods, and evolution of the three nurses’ health studies. American Journal of Public Health, 106(9), 15731581. https://doi.org/10.2105/AJPH.2016.303338.CrossRefGoogle ScholarPubMed
Batty, G. D., Deary, I. J., Luciano, M., Altschul, D., Kivimäki, M., & Gale, C. R. (2020). Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study based on a community sample. Brain, Behavior, and Immunity, 89, 569578. https://doi.org/10.1016/j.bbi.2020.06.021.CrossRefGoogle ScholarPubMed
Beesley, L. J., Salvatore, M., Fritsche, L. G., Pandit, A., Rao, A., Brummett, C., … Mukherjee, B. (2020). The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities. Statistics in Medicine, 39(6), 773800. https://doi.org/https://doi.org/10.1002/sim.8445.CrossRefGoogle ScholarPubMed
Bu, F., Philip, K., & Fancourt, D. (2020). Social isolation and loneliness as risk factors for hospital admissions for respiratory disease among older adults. Thorax, 75(7), 597. https://doi.org/10.1136/thoraxjnl-2019-214445.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention, White House COVID-19 Team, Data Strategy and Execution Workgroup. (2022). New Amissions of Patients with Confirmed COVID-19 per 100,000 Population by Age Group, United States: Aug 01, 2020 – Feb 11, 2022. Unified Hospital Dataset. https://covid.cdc.gov/covid-data-tracker/#new-hospital-admissions.Google Scholar
Chi, Y., Zhu, Y., Wen, T., Cui, L., Ge, Y., Jiao, Y., … Zhou, M. (2013). Cytokine and chemokine levels in patients infected with the novel avian influenza A (H7N9) virus in China. The Journal of Infectious Diseases, 208(12), 19621967. https://doi.org/10.1093/infdis/jit440.CrossRefGoogle ScholarPubMed
Chou, R., Dana, T., Buckley, D. I., Selph, S., Fu, R., & Totten, A. M. (2020). Epidemiology of and risk factors for coronavirus infection in health care workers: A living rapid review. Annals of internal medicine, 173(2), 120136. https://doi.org/10.7326/M20-1632.CrossRefGoogle ScholarPubMed
Cohen, S. (1988). Perceived stress in a probability sample of the United States. In Spacapan, S. & Oskamp, S. (Eds.), The Social Psychology of Health (pp. 3167). Newbury Park, CA: Sage Publications, Inc.Google Scholar
Cohen, S., Doyle, W. J., Skoner, D. P., Fireman, P., Gwaltney, J. M. Jr., & Newsom, J. T. (1995). State and trait negative affect as predictors of objective and subjective symptoms of respiratory viral infections. Journal of Personality and Social Psychology, 68(1), 159169. https://doi.org/10.1037/0022-3514.68.1.159.CrossRefGoogle ScholarPubMed
Cohen, S., Doyle, W. J., Skoner, D. P., Rabin, B. S., & Gwaltney, J. M. Jr (1997). Social ties and susceptibility to the common cold. JAMA, 277(24), 19401944. https://doi.org/10.1001/jama.1997.03540480040036.CrossRefGoogle ScholarPubMed
Cohen, S., Doyle, W. J., Turner, R., Alper, C. M., & Skoner, D. P. (2003). Sociability and susceptibility to the common cold. Psychological Science, 14(5), 389395. https://doi.org/10.1111/1467-9280.01452.CrossRefGoogle ScholarPubMed
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385396.CrossRefGoogle ScholarPubMed
Day, F. R., Ong, K. K., & Perry, J. R. B. (2018). Elucidating the genetic basis of social interaction and isolation. Nature Communications, 9(1), 2457. Retrieved 2018/07//, from https://doi.org/10.1038/s41467-018-04930-1.CrossRefGoogle ScholarPubMed
Del Valle, D. M., Kim-Schulze, S., Huang, H.-H., Beckmann, N. D., Nirenberg, S., Wang, B., … Gnjatic, S. (2020). An inflammatory cytokine signature predicts COVID-19 severity and survival. Nature Medicine, 26(10), 16361643. https://doi.org/10.1038/s41591-020-1051-9.CrossRefGoogle ScholarPubMed
Diamantopoulos, A., Sarstedt, M., Fuchs, C., Wilczynski, P., & Kaiser, S. (2012). Guidelines for choosing between multi-item and single-item scales for construct measurement: A predictive validity perspective. Journal of the Academy of Marketing Science, 40(3), 434449. https://doi.org/10.1007/s11747-011-0300-3.CrossRefGoogle Scholar
Ebrahim, S. H., Maher, A. D., Kanagasabai, U., Alfaraj, S. H., Alzahrani, N. A., Alqahtani, S. A., … Memish, Z. A. (2021). MERS-CoV Confirmation among 6873 suspected persons and relevant epidemiologic and clinical features, Saudi Arabia - 2014 to 2019. EClinicalMedicine, 41, 101191. https://doi.org/10.1016/j.eclinm.2021.101191.CrossRefGoogle Scholar
Falagas, M. E., Karamanidou, C., Kastoris, A., Karlis, G., & Rafailidis, P. (2010). Psychosocial factors and susceptibility to or outcome of acute respiratory tract infections [Review article]. The International Journal of Tuberculosis and Lung Disease, 14, 141148.Google ScholarPubMed
Forman, J. P., Curhan, G. C., & Taylor, E. N. (2008). Plasma 25-hydroxyvitamin D levels and risk of incident hypertension among young women. Hypertension (Dallas, Tex. : 1979), 52(5), 828832. https://doi.org/10.1161/hypertensionaha.108.117630.CrossRefGoogle ScholarPubMed
Gao, Y.-H., Zhao, H.-S., Zhang, F.-R., Gao, Y., Shen, P., Chen, R.-C., & Zhang, G.-J. (2015). The relationship between depression and asthma: A meta-analysis of prospective studies. PloS One, 10(7), e0132424e0132424. https://doi.org/10.1371/journal.pone.0132424.CrossRefGoogle ScholarPubMed
Garg, S., Kim, L., Whitaker, M., O'Halloran, A., Cummings, C., Holstein, R., … Fry, A. (2020). Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed coronavirus disease 2019 – COVID-NET, 14 states, march 1–30, 2020. MMWR. Morbidity and Mortality Weekly Report, 69(15), 458464. https://doi.org/10.15585/mmwr.mm6915e3.CrossRefGoogle ScholarPubMed
Gebhard, C., Regitz-Zagrosek, V., Neuhauser, H. K., Morgan, R., & Klein, S. L. (2020). Impact of sex and gender on COVID-19 outcomes in Europe. Biology of sex differences, 11(1), 29. https://doi.org/10.1186/s13293-020-00304-9.CrossRefGoogle ScholarPubMed
Gomez, J., Du-Fay-de-Lavallaz, J. M., Fugar, S., Sarau, A., Simmons, J. A., Clark, B., … Volgman, A. S. (2021). Sex differences in COVID-19 hospitalization and mortality. Journal of Women's health, 30(5), 646653. https://doi.org/10.1089/jwh.2020.8948.CrossRefGoogle ScholarPubMed
Grimm, C. (2021). Hospitals Reported That the COVID-19 Pandemic Has Significantly Strained Health Care Delivery: Results of a National Pulse Survey, Feb. 22–26, 2021; 2021 ASI 4006-11.45844;OEI-09-21-00140.Google Scholar
Guilliams, T. G., & Edwards, L. (2010). Chronic stress and the hpa axis: Clinical assessment and therapeutic considerations. A review of Natural and Nutraceutical Therapies for Clinical Practice, 9, 112.Google Scholar
Gwynn, R. C., McQuistion, H. L., McVeigh, K. H., Garg, R. K., Frieden, T. R., & Thorpe, L. E. (2008). Prevalence, diagnosis, and treatment of depression and generalized anxiety disorder in a diverse urban community. Psychiatric Services, 59(6), 641647. https://doi.org/10.1176/ps.2008.59.6.641.CrossRefGoogle Scholar
Hamer, M., Kivimäki, M., Gale, C. R., & Batty, G. D. (2020). Lifestyle risk factors, inflammatory mechanisms, and COVID-19 hospitalization: A community-based cohort study of 387109 adults in UK. Brain, Behavior, and Immunity, 87, 184187. https://doi.org/10.1016/j.bbi.2020.05.059.CrossRefGoogle Scholar
Hamrick, N., Cohen, S., & Rodriguez, M. S. (2002). Being popular can be healthy or unhealthy: Stress, social network diversity, and incidence of upper respiratory infection. Health Psychology, 21(3), 294298. https://doi.org/10.1037/0278-6133.21.3.294.CrossRefGoogle ScholarPubMed
Hannibal, K. E., & Bishop, M. D. (2014). Chronic stress, cortisol dysfunction, and pain: A psychoneuroendocrine rationale for stress management in pain rehabilitation. Physical Therapy, 94(12), 18161825. https://doi.org/10.2522/ptj.20130597.CrossRefGoogle Scholar
Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research. on Aging, 26(6), 655672. https://doi.org/10.1177/0164027504268574.CrossRefGoogle Scholar
Janicki Deverts, D., Cohen, S., & Doyle, W. J. (2017). Dispositional affect moderates the stress-buffering effect of social support on risk for developing the common cold. Journal of Personality, 85(5), 675686. https://doi.org/10.1111/jopy.12270.CrossRefGoogle ScholarPubMed
Karlberg, J., Chong, D. S., & Lai, W. Y. (2004). Do men have a higher case fatality rate of severe acute respiratory syndrome than women do? American Journal of Epidemiology, 159(3), 229231. https://doi.org/10.1093/aje/kwh056.CrossRefGoogle Scholar
Kim, S. Y., Min, C., Oh, D. J., Lim, J.-S., & Choi, H. G. (2019). Bidirectional association between asthma and migraines in adults: Two longitudinal follow-up studies. Scientific Reports, 9(1), 18343. Retrieved 2019/12//, from https://doi.org/10.1038/s41598-019-54972-8.CrossRefGoogle ScholarPubMed
Ko, J. Y., Farr, S. L., Dietz, P. M., & Robbins, C. L. (2012). Depression and treatment among U.S. pregnant and nonpregnant women of reproductive age, 2005–2009. Journal of Women's Health, 21(8), 830836. https://doi.org/10.1089/jwh.2011.3466.CrossRefGoogle ScholarPubMed
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2003). The Patient Health Questionnaire-2: Validity of a two-item depression screener. Medical Care, 41(11), 12841292. https://doi.org/10.1097/01.MLR.0000093487.78664.3C.CrossRefGoogle ScholarPubMed
Kroenke, K., Spitzer, R. L., Williams, J. B., & Lowe, B. (2009). An ultra-brief screening scale for anxiety and depression: The PHQ-4. Psychosomatics, 50(6), 613621. https://doi.org/10.1176/appi.psy.50.6.613.Google ScholarPubMed
Kroenke, K., Spitzer, R. L., Williams, J. B., Monahan, P. O., & Lowe, B. (2007). Anxiety disorders in primary care: Prevalence, impairment, comorbidity, and detection. Annals of Internal Medicine, 146(5), 317325. https://doi.org/10.7326/0003-4819-146-5-200703060-00004.CrossRefGoogle ScholarPubMed
Lee, S. W., Yang, J. M., Moon, S. Y., Yoo, I. K., Ha, E. K., Kim, S. Y., … Yon, D. K. (2020). Association between mental illness and COVID-19 susceptibility and clinical outcomes in South Korea: A nationwide cohort study. The Lancet Psychiatry, 7(12), 10251031. https://doi.org/10.1016/S2215-0366(20)30421-1.CrossRefGoogle ScholarPubMed
Lehto, K., Pedersen, N. L., Almqvist, C., Lu, Y., & Brew, B. K. (2019). Asthma and affective traits in adults: A genetically informative study. The European Respiratory Journal, 53(5), 1802142. https://doi.org/10.1183/13993003.02142-2018.CrossRefGoogle ScholarPubMed
Leonard, B. E. (2010). The concept of depression as a dysfunction of the immune system. Current Immunology Reviews, 6(3), 205212. https://doi.org/10.2174/157339510791823835.CrossRefGoogle ScholarPubMed
LeRoy, A. S., Murdock, K. W., Jaremka, L. M., Loya, A., & Fagundes, C. P. (2017). Loneliness predicts self-reported cold symptoms after a viral challenge. Health Psychology: Official Journal of the Division of Health Psychology, American Psychological Association, 36(5), 512520. https://doi.org/10.1037/hea0000467.CrossRefGoogle ScholarPubMed
Li, L., Li, F., Fortunati, F., & Krystal, J. H. (2020). Association of a prior psychiatric diagnosis with mortality among hospitalized patients with coronavirus disease 2019 (COVID-19) infection. JAMA Network Open, 3(9), e2023282e2023282. https://doi.org/10.1001/jamanetworkopen.2020.23282.CrossRefGoogle ScholarPubMed
Lowe, B., Wahl, I., Rose, M., Spitzer, C., Glaesmer, H., Wingenfeld, K., … Brahler, E. (2010). A 4-item measure of depression and anxiety: Validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. Journal of Affective Disorders, 122(1-2), 8695. https://doi.org/10.1016/j.jad.2009.06.019.CrossRefGoogle ScholarPubMed
Lu, Z., Chen, L., Xu, S., Bao, Q., Ma, Y., Guo, L., … Ruan, L. (2018). Allergic disorders and risk of depression: A systematic review and meta-analysis of 51 large-scale studies. Annals of Allergy, Asthma & Immunology, 120(3), 310317, e312. https://doi.org/https://doi.org/10.1016/j.anai.2017.12.011.CrossRefGoogle ScholarPubMed
Macleod, J., Davey Smith, G., Heslop, P., Metcalfe, C., Carroll, D., & Hart, C. (2002). Psychological stress and cardiovascular disease: Empirical demonstration of bias in a prospective observational study of Scottish men. BMJ (Clinical Research ed.), 324(7348), 12471251. https://doi.org/10.1136/bmj.324.7348.1247.CrossRefGoogle Scholar
Mitchell, A. M., Crane, P. A., & Kim, Y. (2008). Perceived stress in survivors of suicide: Psychometric properties of the Perceived Stress Scale. Research in Nursing & Health, 31(6), 576585. https://doi.org/10.1002/nur.20284.CrossRefGoogle ScholarPubMed
Nemani, K., Li, C., Olfson, M., Blessing, E. M., Razavian, N., Chen, J., … Goff, D. C. (2021). Association of psychiatric disorders with mortality among patients with COVID-19. JAMA Psychiatry, 78(4), 380386. https://doi.org/10.1001/jamapsychiatry.2020.4442.CrossRefGoogle ScholarPubMed
Orlando, V., Rea, F., Savaré, L., Guarino, I., Mucherino, S., Perrella, A., … Corrao, G. (2021). Development and validation of a clinical risk score to predict the risk of SARS-CoV-2 infection from administrative data: A population-based cohort study from Italy. PloS One, 16(1), e0237202e0237202. https://doi.org/10.1371/journal.pone.0237202.CrossRefGoogle Scholar
People with Certain Medical Conditions (2021). Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html.Google Scholar
Perruche, F., Elie, C., Ussel, M., Ray, P., Thys, F., Bleichner, G., … Claessens, Y.-E. (2011). Anxiety and depression are unrecognised in emergency patients admitted to the observation care unit. Emergency Medicine Journal, 28(8), 662. https://doi.org/10.1136/emj.2009.089961.CrossRefGoogle Scholar
Preti, E., Di Mattei, V., Perego, G., Ferrari, F., Mazzetti, M., Taranto, P., … Calati, R. (2020). The psychological impact of epidemic and pandemic outbreaks on healthcare workers: Rapid review of the evidence. Current Psychiatry Reports, 22(8), 4343. https://doi.org/10.1007/s11920-020-01166-z.CrossRefGoogle ScholarPubMed
Rich-Edwards, J. W., Ding, M., Rocheleau, C. M., Boiano, J. M., Kang, J. H., Becene, I., … Lawson, C. C. (2021). American Frontline healthcare personnel's access to and Use of personal protective equipment early in the COVID-19 pandemic. Journal of Occupational and Environmental Medicine.CrossRefGoogle ScholarPubMed
Sasaki, N., Kuroda, R., Tsuno, K., & Kawakami, N. (2020). The deterioration of mental health among healthcare workers during the COVID-19 outbreak: A population-based cohort study of workers in Japan. Scandinavian Journal of Work, Environment & Health, 46(6), 639644. https://doi.org/10.5271/sjweh.3922.CrossRefGoogle ScholarPubMed
Short, K. R., Kroeze, E. J. B. V., Fouchier, R. A. M., & Kuiken, T. (2014). Pathogenesis of influenza-induced acute respiratory distress syndrome. The Lancet Infectious Diseases, 14(1), 5769. https://doi.org/https://doi.org/10.1016/S1473-3099(13)70286-X.CrossRefGoogle ScholarPubMed
Spiranovic, C., Matthews, A., Scanlan, J., & Kirkby, K. C. (2016). Increasing knowledge of mental illness through secondary research of electronic health records: Opportunities and challenges. Advances in Mental Health, 14(1), 1425. https://doi.org/http://dx.doi.org/10.1080/18387357.2015.1063635.CrossRefGoogle Scholar
Steptoe, A., Shankar, A., Demakakos, P., & Wardle, J. (2013). Social isolation, loneliness, and all-cause mortality in older men and women [10.1073/pnas.1219686110]. Proceedings of the National Academy of Sciences of the USA, 110(15), 57975801. https://doi.org/10.1073/pnas.1219686110.CrossRefGoogle ScholarPubMed
Taquet, M., Luciano, S., Geddes, J. R., & Harrison, P. J. (2021). Bidirectional associations between COVID-19 and psychiatric disorder: Retrospective cohort studies of 62 354 COVID-19 cases in the USA. The Lancet Psychiatry, 8(2), 130140. https://doi.org/10.1016/S2215-0366(20)30462-4.CrossRefGoogle ScholarPubMed
Tian, R., Hou, G., Li, D., & Yuan, T.-F. (2014). A possible change process of inflammatory cytokines in the prolonged chronic stress and its ultimate implications for health. The Scientific World Journal, 2014, 780616780616. https://doi.org/10.1155/2014/780616.CrossRefGoogle ScholarPubMed
Townsend, L., Walkup, J. T., Crystal, S., & Olfson, M. (2012). A systematic review of validated methods for identifying depression using administrative data. Pharmacoepidemiology and Drug Safety, 21(S1), 163173. https://doi.org/https://doi.org/10.1002/pds.2310.CrossRefGoogle ScholarPubMed
Troy, L. M., Hunter, D. J., Manson, J. E., Colditz, G. A., Stampfer, M. J., & Willett, W. C. (1995). The validity of recalled weight among younger women. International Journal of Obesity and Related Metabolic Disorders: Journal of the International Association for the Study of Obesity, 19(8), 570572.Google ScholarPubMed
Väänänen, A., Murray, M., Koskinen, A., Vahtera, J., Kouvonen, A., & Kivimäki, M. (2009). Engagement in cultural activities and cause-specific mortality: Prospective cohort study. Preventive Medicine, 49(2-3), 142147. https://doi.org/10.1016/j.ypmed.2009.06.026.CrossRefGoogle ScholarPubMed
Vallejo, M. A., Vallejo-Slocker, L., Fernandez-Abascal, E. G., & Mananes, G. (2018). Determining factors for stress perception assessed with the Perceived Stress Scale (PSS-4) in Spanish and other European samples. Frontiers in Psychology, 9, 37. https://doi.org/10.3389/fpsyg.2018.00037.CrossRefGoogle ScholarPubMed
Wang, Q., Xu, R., & Volkow, N. D. (2021). Increased risk of COVID-19 infection and mortality in people with mental disorders: Analysis from electronic health records in the United States. World Psychiatry, 20(1), 124130. https://doi.org/10.1002/wps.20806.CrossRefGoogle ScholarPubMed
Warttig, S. L., Forshaw, M. J., South, J., & White, A. K. (2013). New, normative, English-sample data for the short form Perceived Stress Scale (PSS-4). Journal of Health Psychology, 18(12), 16171628. https://doi.org/10.1177/1359105313508346.CrossRefGoogle ScholarPubMed
Yang, H., Chen, W., Hu, Y., Chen, Y., Zeng, Y., Sun, Y., … Song, H. (2020a). Pre-pandemic psychiatric disorders and risk of COVID-19: A UK biobank cohort analysis. The Lancet Healthy Longevity, 1(2), e69e79. https://doi.org/10.1016/S2666-7568(20)30013-1.CrossRefGoogle ScholarPubMed
Yang, R., Gui, X., & Xiong, Y. (2020b). Comparison of clinical characteristics of patients with asymptomatic vs symptomatic coronavirus disease 2019 in Wuhan, China. JAMA Network Open, 3(5), e2010182e2010182. https://doi.org/10.1001/jamanetworkopen.2020.10182.CrossRefGoogle ScholarPubMed
Yende, S., Tuomanen, E. I., Wunderink, R., Kanaya, A., Newman, A. B., Harris, T., … Kritchevsky, S. B. (2005). Preinfection systemic inflammatory markers and risk of hospitalization due to pneumonia. American Journal of Respiratory and Critical Care Medicine, 172(11), 14401446. https://doi.org/10.1164/rccm.200506-888OC.CrossRefGoogle ScholarPubMed
YouGov. (2020). Yahoo! News Coronavirus - April 8, 2020. Y. News. https://docs.cdn.yougov.com/1ayt0i64g6/20200408_yahoo_coronavirus.pdf.Google Scholar
Zhao, C. L., Huang, J. W., Zhang, L., Zhang, Q. R., Li, Q. M., & Zhou, M. (2018). Respiratory virus infections and inflammatory cytokines in hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease. Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases, 41(12), 942948. https://doi.org/10.3760/cma.j.issn.1001-0939.2018.12.009.Google ScholarPubMed
Zheng, L., Wang, X., Zhou, C., Liu, Q., Li, S., Sun, Q., … Wang, W. (2020). Analysis of the infection Status of healthcare workers in Wuhan during the COVID-19 outbreak: A cross-sectional study. Clinical Infectious Diseases, 71(16), 21092113. https://doi.org/10.1093/cid/ciaa588.CrossRefGoogle ScholarPubMed
Zhu, Z., Zhu, X., Liu, C.-L., Shi, H., Shen, S., Yang, Y., … Liang, L. (2019). Shared genetics of asthma and mental health disorders: A large-scale genome-wide cross-trait analysis. The European Respiratory Journal, 54(6), 1901507. https://doi.org/10.1183/13993003.01507-2019.CrossRefGoogle ScholarPubMed
Zou, G. (2004). A modified Poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159(7), 702706. https://doi.org/10.1093/aje/kwh090.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Health and demographic characteristics by forms of distress at baseline (April–August 2020), among participants who ever tested positive for SARS-CoV-2 between April 2020 – April 2021, N = 3663

Figure 1

Table 2. Spearman correlations between forms of distress among persons with a positive SARS-CoV-2 test from April 2020 to April 2021, NHS II, NHS3, and GUTS, N = 3663

Figure 2

Fig. 1. Relative Risks (RRs) and 95% Confidence Intervals (CIs) of the associations between forms of distress at baseline and established risk factors for severe COVID-19 in relation to COVID-19 hospitalization, April 2020 – April 2021, N = 3663. Multivariable model adjusted for age, sex, racial identity, healthcare worker status and partner's education (participants' own education attainment in GUTS). Perceived stress and loneliness were queried in non-active health care workers only.Note. PHQ-2, 2-item Patient Health Questionnaire; GAD-2, 2-item Generalized Anxiety Disorder.

Figure 3

Table 3. Association of forms of distress prior to infection and risk of COVID-19 hospitalization among persons testing positive for SARS-CoV-2, April 2020 – April 2021, N = 3663

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