Mental illness and COVID-19 vaccination: a multinational investigation of observational & register-based data

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However, previous studies on the uptake of COVID-19 vaccination in this population have reported conflicting results. Therefore, we aimed to investigate the association between mental illness and COVID-19 vaccination uptake, using data from five countries. Methods: Data from seven cohort studies (N=325,298), and the Swedish registers (8,080,234), were used to identify mental illness and COVID-19 vaccination uptake. Multivariable modified Poisson regression models were conducted to calculate the prevalence ratio (PR) and 95% CIs of vaccination uptake among individuals with v.s. without mental illness. Results from the cohort studies were pooled using random effects meta-analyses. Findings: Most of the meta-analyses performed using the COVIDMENT study population showed no significant association between mental illness and vaccination uptake. In the Swedish register study population, we observed a very small reduction in the uptake of both the first (prevalence ratio [PR]: 0.98, 95% CI: 0.98-0.99, p<0.001) and second dose among individuals with mental illness; the reduction was however greater among those not using pyschiatric medication (PR: 0.91, 95% CI: 0.91-0.91, p<0.001). Conclusions: The high uptake of COVID-19 vaccination observed among individuals with most types of mental illness highlights the comprehensiveness of the vaccination campaign , however lower levels of vaccination uptake among subgroups of individuals with unmedicated mental illness warrants attention in future vaccination campaigns. Health sciences/Diseases/Psychiatric disorders Health sciences/Health care/Disease prevention/Preventive medicine Health sciences/Health care/Public health/Epidemiology Figures Figure 1 Figure 2 Figure 3 INTRODUCTION The coronavirus disease 2019 (COVID-19) pandemic was an unprecedented global health crisis, which, as of August 2023, had caused 6.9 million deaths globally.( 1 ) Although multiple effective vaccines against COVID-19 were developed and distributed globally, vaccine hesitancy and refusal were observed worldwide.( 2 – 5 ) Crucially, the success of vaccination programmes in controlling the COVID-19 pandemic relies on high vaccination coverage,( 6 ) which is especially important among people at increased risk of severe COVID-19 infection and COVID-19-related mortality, including individuals with mental illness.( 7 ) Previous systematic reviews exploring the association between mental illness and uptake of various vaccinations have reported heterogenous results.( 8 , 9 ) Similarly, results from previous country-specific studies of COVID-19 vaccination uptake in people with mental illness have been inconsistent. While some studies have observed significantly lower uptake of COVID-19 vaccination among individuals with mental illness,( 10 , 11 ) others have either reported higher uptake ( 12 ), no significant difference,( 13 ) or differences in uptake according to the type of mental illness.( 14 – 16 ) Additionally, little is currently known regarding the effect of psychiatric treatment on COVID-19 vaccination uptake. As a result, the relationship between mental illness and COVID-19 vaccination uptake may be more complex, and could differ depending on the type, severity, and treatment status of mental illness. A comprehensive understanding of the impact of mental illness on COVID-19 vaccination uptake is crucial to inform the design of future vaccination campaigns, and, ultimately, to protect at-risk populations from infectious diseases and future pandemics. This study aimed to investigate the association between mental illness and COVID-19 vaccination uptake using data from seven cohort studies included in the multinational COVIDMENT consortium,( 17 ) in addition to data from Swedish national registers, focusing on studying mental illness of different types, severity, and treatment status (i.e., use of prescribed psychiatric medications). METHODS COVIDMENT Study Analysis Study Population The COVIDMENT study population included data from seven cohorts within the COVIDMENT consortium, namely the Estonian Biobank (EstBB) cohorts: EstBB full cohort with electronic health record linkages (EstBB-EHR) and the EstBB COVID-19 subcohort (EstBB-C19); the Icelandic COVID-19 National Resilience Cohort (C-19 Resilience); the Norwegian COVID-19 Mental Health and Adherence study (MAP-19); the Norwegian Mother, Father, and Child Cohort study (MoBa);( 18 ) the Scottish CovidLife study; and the Swedish Omtanke2020 study.( 17 ) Ethical approvals for all included cohorts were obtained from regional or national ethics committees, and all participants provided informed consent (Supplementary Table 1). The cohorts used different recruitment strategies, with most recruiting from established cohorts whilst others also allowed self-recruitment via social media. The number of data collection waves varied between the cohorts, with the first data collected in March 2020. Exposure Variables All exposure variables referred to mental illness experienced before the initiation of COVID-19 vaccination in each study country (Supplementary Table 2). The primary exposure variable was the lifetime diagnosis of any mental illness, which, for all cohorts except EstBB-C19 and EstBB-EHR, was defined using self-report data from questionnaire items asking participants if they had ever been diagnosed with any mental illness. In EstBB-C19 and EstBB-EHR, ICD-10 codes were used to define mental illness diagnoses through linked EHRs (containing diagnoses from Estonian Health Insurance Fund (HIF) treatment bills since 2004), including primary/secondary care and inpatient/outpatient diagnoses (Supplementary Table 3). Anxiety and depressive symptoms were included as secondary exposure variables. In the majority of cohorts, moderate-to-severe anxiety and depressive symptoms, during the past two weeks, were defined as total scores of ≥ 10 from the Generalised Anxiety Disorder Assessment (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) scales, respectively.( 19 , 20 ) In EstBB-C19, anxiety and depressive symptoms, during the past four weeks, were measured using the Emotional State Questionnaire (EST-Q2), utilising cut-off values of > 11 to define moderate-to-severe anxiety or depressive symptoms.( 21 ) Outcome Variables The primary outcome variable was (i) first dose of a COVID-19 vaccine by 30th September 2021. This end date represents the time at which all included countries had offered COVID-19 vaccination to all adult residents and cohort participants had adequate opportunity to book and attend vaccination appointments (Supplementary Table 2). Two additional outcome variables were used: (ii) first dose of a COVID-19 vaccine by 18th February 2022, and (iii) second dose of a COVID-19 vaccine by 18th February 2022. This second date represents the time point at which the majority of cohorts had conducted a new wave of data collection, and therefore it was the first date post-September 2021 that vaccination uptake could be re-assessed. As C-19 Resilience did not conduct further data collection between September 2021 and February 2022, it was only included in the analysis of outcome (i). Participants were eligible for the present study if they had available data for outcomes (i) and/or (ii). Participants were included in the analysis of outcome (iii) if they had received the first dose of any COVID-19 vaccine, except the JCOVDEN vaccine (for which a one-dose schedule was used( 22 )), before 18th February 2022. In C-19 Resilience, MAP-19, MoBa, and Omtanke2020, vaccination uptake was defined using self-report data collected in various cohort-specific follow-up questionnaires. The remaining cohorts used linked EHR data to define vaccination uptake. Covariates All covariates (age, sex, smoking status, previous COVID-19 infection, and physical comorbidity status) were defined using data collected before COVID-19 vaccination was initiated in each study country. Smoking was used as a binary variable, defined as current or non-current smoker or user of any tobacco products at the time of data collection. COVID-19 infection was defined as a positive COVID-19 test before the initiation of COVID-19 vaccination. Self-report data was used to define COVID-19 infection in the majority of cohorts. However, the Electronic Communication of Surveillance in Scotland (ECOSS) COVID-19 testing data was used in the CovidLife cohort, and the E-Health Record registry data was used in EstBB-EHR. Physical comorbidity status was defined as the presence of at least two physical health conditions (hypertension, heart disease, lung disease, chronic renal failure, cancer, diabetes, or immunological conditions), using either self-report data from the cohort-specific questionnaires or EHR data (Supplementary Table 3). Neither data on smoking nor physical comorbditiy status was available in the MAP-19 cohort. Further details regarding the time at which variables were defined in each cohort are displayed in Supplementary Table 4. Statistical Analysis Covariates were summarised, stratified by the diagnosis of any mental illness, using mean (standard deviation [SD]) or frequency (percentage), as appropriate. Multivariable modified Poisson regression models were conducted for each exposure-outcome combination, to assess the prevalence ratio (PR) with 95% confidence intervals (CI), adjusted for age, sex, previous COVID-19 infection, smoking, and physical comorbidity status. Due to data inavailability in MAP-19, models from this cohort were only adjusted for age, sex, and previous COVID-19 infection. As EstBB-EHR had a high proportion of missing COVID-19 testing data, this cohort used an additional “missing” indicator for the COVID-19 infection covariate in addition to “negative” and “positive” groups, to avoid dropping large numbers of participants. Random effects meta-analyses were performed to pool the results from each participating cohort. Heterogeneity was assessed using the I 2 statistic. Two sensitivity analyses were conducted: ( 1 ) to explore potential differences related to self-report vs. EHR-based variable definitions, meta-analyses for the primary exposure variable (‘diagnosis of any mental illness’) were run excluding cohorts that used EHR to define exposure and/or outcome variables (i.e., CovidLife, EstBB-C19, and EstBB-EHR), ( 2 ) to further explore the potential impact of physical health status, meta-analyses for the primary exposure variable were conducted excluding participants with any chronic physical conditions (using all cohorts except MAP-19). Statistical analyses were conducted using STATA (version 17.0) and the metafor package in R (version 4.3.0).( 23 ) Swedish Register Study Analysis Study Population To assess the internal and external validity of the COVIDMENT results, and to gain understanding of the role of disease type, severity and treatment status on the association between mental illness and COVID-19 vaccination uptake, further analyses were conducted using Swedish register data within the SCIFI-PEARL (Swedish COVID-19 Investigation for Future Insights – a Population Epidemiology Approach using Register Linkage) project.( 24 ) Ethical approval was obtained from the Swedish Ethical Review Authority (2020 − 01800 with subsequent amendments). SCIFI-PEARL is a regularly updated, nationwide register-based study, with individual linkages to multiple registers performed using the unique Swedish Personal Identity Number (PIN). The present study included all individuals aged ≥ 18 years who were living in Sweden on 27th December 2020 (date of first COVID-19 vaccination in Sweden( 25 )) and did not die or emigrate on or before the final study end point (30th November 2021). Exposure Variables Mental illness was first defined using secondary care-based specialist diagnoses (as denoted by ≥ 1 ICD-10 code listed in Supplementary Table 5) from all inpatient and outpatient hospital encounters reported in the National Patient Register (NPR) between 1st January 2018 and 26th December 2020. In addition to any mental illness, we also studied specific types of mental illness (substance use disorder [excluding aclohool and tobacco use disorders], alcohol use disorder, tobacco use disorder, psychotic disorders, depression, anxiety, and stress-related disorders), defined by ≥ 1 relevant ICD-10 code. The NPR includes data on specialist care only, whereas patients with milder mental illness are often treated in primary care. Therefore, we also identified information on prescribed use of psychiatric medication (as denoted by ≥ 1 Anatomical Therapeutic Chemical (ATC) code displayed in Supplementary Table 6), between 1st January 2018 and 26th December 2020, according to the National Prescribed Drug Register (NPDR). Prescribed use of psychiatric medication was used both to ascertain mental illnesses not attended to by specialist care and as a proxy for treatment of mental illness. We studied prescribed use of any psychiatric medication as well as prescribed use of antidepressants, anxiolytics, hypnotics/sedatives, and antipsychotics, respectively. To investigate the effect of disease severity and treatment with psychiatric medication, an alternative (multi-level) categorisation of exposure variables was used for any mental illness, depression, anxiety, and psychotic disorder, with the following categories: ( 1 ) no specialist diagnosis of mental illness and no prescribed use of psychiatric medication (i.e., reference category), ( 2 ) prescribed use of psychiatric medication without specialist diagnosis (i.e., proxy of milder illness with medical treatment), ( 3 ) specialist diagnosis with prescribed use of psychiatric medication (i.e., proxy of more severe illness with medical treatment), and ( 4 ) specialist diagnosis without prescribed use of psychiatric medication (i.e., proxy of more severe illness without medical treatment). Outcome Variables For the definition of outcome variables, the National Vaccination Register (NVR) was used, which includes information on all COVID-19 vaccinations conducted in Sweden from December 2020.( 24 ) Two outcome variables were used: (i) first dose of a COVID-19 vaccine by 30th September 2021, and (ii) second dose of a COVID-19 vaccine by 30th November 2021. By using this end date for outcome (ii) we ensured that all individuals vaccinated with a first dose up until 30th September would have had the recommended time period between their first and second vaccine dose.( 26 ) Individuals were included in the analysis of outcome (ii) if they had received the first dose of any COVID-19 vaccine, except the JCOVDEN vaccine, by 30th September 2021. Covariates Covariates included age and sex (identified through the Total Population Register (TPR)), region of residence, highest educational attainment, cohabitation status, and income (identified from the Swedish Longitudinal Integrated Database for Health Insurance and Labour Market Studies (LISA) in 2020), severe COVID-19 infection and the Charlson Comorbidity Index (CCI). Severe COVID-19 infection was defined as an inpatient or ICU visit due to COVID-19 before the study start date (27th December 2020), whilst CCI was calculated at the study start date, using diagnostic data identified from 1st January 2015 onwards in the NPR.( 27 ) Statistical Analysis All covariates were summarized, stratified by the diagnosis of any mental illness, using mean (standard deviation [SD]) or frequency (percentage), as appropriate. Multivariable modified Poisson regression models were run for all exposures and outcomes to assesss PR and 95% CIs of COVID-19 vaccination uptake in relation to mental illness, adjusted for the covariates listed above. Stratified analyses were conducted by sex and the presence of chronic physical condition(s) (defined as a CCI score of ≥ 1). Complete case analysis was used throughout. Statistical analyses were conducted using STATA (version 17.0). RESULTS COVIDMENT Study Analysis Of the 403,794 individuals included in the participating COVIDMENT cohort studies, 325,298 individuals met the eligibility criteria for the present study (Supplementary Fig. 1). Over half of the overall study population (65.1%), and of each participating cohort, were female (Supplementary Table 7). The mean age in the participating cohorts ranged from 36.9 years (MAP-19) to 59.4 years (CovidLife), with a mean of 48 years in the overall study population. Individuals with a diagnosis of any mental illness were more likely to be female, compared to those without a mental illness (Table 1 ). The proportion of individuals with chronic physical conditions was higher among those with any mental illness diagnosis. Low levels of missing data were observed for the majority of covariates. Table 1 Distribution of sociodemographic variables in the included COVIDMENT study population, overall and by diagnosis of any mental illness diagnosis, presented as N (%) or mean [SD]. Diagnosis of any mental illness Yes (n = 122,976) No (n = 201,273) Missing (n = 1,049) Total (N = 325,298) Cohort EstBB-C19 (Estonia) 3,107 (2.5%) 2,526 (1.3%) 0 (0.0%) 5,633 (1.7%) EstBB-EHR (Estonia) 95,208 (77.4%) 88,124 (43.8%) 0 (0.0%) 183,332 (56.4%) C-19 Resilience (Iceland) 2,895 (2.4%) 7,283 (3.6%) 239 (22.8%) 10,417 (3.2%) MAP-19 (Norway) 698 (0.6%) 2,722 (1.3%) 474 (45.2%) 3,894 (1.2%) MoBa (Norway) 15,496 (12.6%) 87,315 (43.4%) 0 (0.0%) 102,811 (31.6%) CovidLife (Scotland) 1,230 (1.0%) 3,499 (1.7%) 31 (2.9%) 4,760 (1.5%) Omtanke2020 (Sweden) 4,342 (3.5%) 9,804 (4.9%) 305 (29.1%) 14,451 (4.4%) Sex Female 88,515 (72.0%) 122,544 (60.9%) 753 (71.8%) 211,812 (65.1%) Male 34,446 (28.0%) 78,713 (39.1%) 205 (19.5%) 113,364 (34.9%) Other 8 (0.0%) 6 (0.0%) 1 (0.1%) 15 (0.0%) Missing 7 (0.0%) 10 (0.0%) 90 (8.6%) 107 (0.0%) Age group, years 18–29 12,826 (10.5%) 14,670 (7.3%) 265 (25.3%) 27,761 (8.5%) 30–39 24,119 (19.6%) 30,486 (15.1%) 197 (18.8%) 54,802 (16.9%) 40–49 31,864 (25.9%) 78,311 (38.9%) 177 (16.9%) 110,352 (33.9%) 50–59 24,359 (19.8%) 44,785 (22.2%) 184 (17.5%) 69,328 (21.3%) 60–69 17,228 (14.0%) 19,053 (9.5%) 147 (14.0%) 36,428 (11.2%) 70+ 12,558 (10.2%) 13,845 (6.9%) 76 (7.2%) 26,479 (8.1%) Missing 22 (0.0%) 123 (0.1%) 3 (0.3%) 148 (0.1%) Mean [SD] age, years 48.5 [1.8] 47.8 [3.6] 44.1 [9.4] 48.0 [2.9] COVID-19 infection Yes 3,094 (2.5%) 4,629 (2.3%) 17 (1.6%) 7,740 (2.4%) No 64,035 (52.1%) 140,877 (70.0%) 1032 (98.4%) 205,944 (63.3%) Missing* 55,847 (45.4%) 55,767 (27.7%) 0 (0.0%) 111,614 (34.3%) Smoking status Yes 26,465 (21.5%) 34,253 (17.0%) 62 (5.9%) 60,780 (18.7%) No 86,737 (70.5%) 155,181 (77.1%) 493 (47.0%) 242,411 (74.5%) Missing 9,774 (8.0%) 11,839 (5.9%) 494 (47.1%) 22,107 (6.8%) Chronic physical conditions 0 47,606 (38.7%) 123,948 (61.6%) 160 (15.2%) 171,714 (52.8%) 1 34,723 (28.2%) 46,836 (23.3%) 68 (6.5%) 81,627 (25.1%) 2+ 39,497 (32.1%) 27,288 (13.5%) 46 (4.4%) 66,831 (20.5%) Missing 1,150 (0.9%) 3,201 (1.6%) 775 (73.9%) 5,126 (1.6%) *Mainly due to COVID-19 testing data only being available for some EstBB-EHR individuals First dose of a COVID-19 vaccine by 30th September 2021 314,827 individuals were included in the analysis of uptake of the first dose of a COVID-19 vaccine by 30th September 2021 (Table 2 ). Overall vaccination uptake was high (85.1%; n = 267,981/314,827). However, a small difference in uptake was observed between individuals with (82.4%; n = 99,041/120,212) v.s. without (86.8%; n = 168,174/193,706) any mental illness. Vaccination uptake in each included cohort is displayed in Supplementary Table 8. Table 2 Uptake of COVID-19 vaccination overall and by diagnosis of any mental illness diagnosis, in the included COVIDMENT study population, presented as N (%). Uptake of first dose of a COVID-19 vaccine by 30th September 2021 Uptake of first dose of a COVID-19 vaccine by 18th February 2022 Uptake of second dose of a COVID-19 vaccine by 18th February 2022 Yes No Total Yes No Total Yes No Total Total study population 267,981 (85.1%) 46,846 (14.9%) 314,827 (100.0) 278,887 (88.9%) 34,697 (11.1%) 313,584 (100.0%) 252,439 (95.5%) 11,965 (4.5%) 264,404 (100.0%) Mental illness 99,041 (82.4%) 21,171 (17.6%) 120,212 (100.0%) 103,955 (86.7%) 15,953 (13.3%) 119,908 (100.0%) 93,420 (94.7%) 5,251 (5.3%) 98,671 (100.0%) No mental illness 168,174 (86.8%) 25,532 (13.2%) 193,706 (100.0%) 174,612 (90.3%) 18,728 (9.7%) 193,340 (100.0%) 158,830 (95.9%) 6,712 (4.1%) 165,542 (100.0%) Missing 766 (84.3%) 143 (15.7%) 909 (100.0%) 320 (95.2%) 16 (4.8%) 336 (100.0%) 189 (99.0%) 2 (1.0%) 191 (100.0%) Results from the meta-analysis showed no significant association, after adjustment for covariates, between the diagnosis of any mental illness and vaccination uptake (pooled PR: 0.99, 95% CI: 0.97- 1.00]; I 2 : 91.7%, p < 0.001) (Fig. 1 A, Supplementary Table 9). Although the level of heterogeneity was high, a statistically significant association between the diagnosis of any mental illness and lower vaccination uptake was only found in the EstBB-EHR and MAP-19 cohorts. No associations were observed between anxiety or depressive symptoms and vaccination uptake. First dose of a COVID-19 vaccine by 18th February 2022 Uptake of the first dose of a COVID-19 vaccine by 18th February 2022 was analysed in 313,584 individuals. Vaccination uptake was high (88.9%; n = 278,887/313,584); however, a small difference in uptake remained between individuals with (86.7%; n = 103,955/119,908) v.s. without (90.3%; n = 174,612/193,340) mental illness (Table 2 ). Results from the meta-analysis revealed a small association, after adjustment for covariates, between the diagnosis of any mental illness and vaccination uptake (PR: 0.99, 95% CI: 0.98–0.99; I 2 : 79.98, p < 0.001) (Fig. 1 B, Supplementary Table 9). No associations were observed between anxiety or depressive symptoms and vaccination uptake. Second dose of a COVID-19 vaccine by 18th February 2022 264,404 individuals were eligible for the analysis of uptake of the second dose of a COVID-19 vaccine by 18th February 2022 (Table 2 ). Among these individuals, vaccination uptake wasvery high (95.5%; n = 252,439/264,404) and the difference in uptake between those with (94.7%; n = 93,420/98,671) v.s. without (95.9%; n = 158,830/165,542) mental illness was very small. Due to low numbers of participants, models could not be run in the MAP-19 and CovidLife cohorts. The meta-analysis of the remaining eligible cohorts showed no significant differences in vaccination uptake by the diagnosis of any mental illness or the presence of anxiety or depressive symptoms, after adjustment for covariates (Fig. 1 C, Supplementary Table 9). For all outcomes, no substantial differences were observed in any of the sensitivity analyses (Supplementary Table 10). Swedish Register Study Analysis Among the 8,080,234 individuals included in the Swedish register study population, individuals with a specialist diagnosis of mental illness were more likely to be female (55.5% vs. 49.7%) and were, on average, younger (45.0 years vs. 50.2 years), compared to those without a mental illness (Table 3 ). Among those with a mental illness diagnosis, the proportions of individuals who had completed university education, were cohabiting, and were in the highest quartile of income were all lower, whilst the presence of chronic physical conditions was more common, compared to those without a mental illness diagnosis. The proportion of missing data for all covariates was low (≤ 2.5%). Table 3 Distribution of sociodemographic variables in the included Swedish register study population, overall and by specialist diagnosis of a mental illness, presented as N (%) or mean [SD]. Mental illness (n = 473,386) No mental illness (n = 7,606,848) Total (N = 8,080,234) Sex Male 210,601 (44.5%) 3,829,720 (50.3%) 4,040,321 (50.0%) Female 262,785 (55.5%) 3,777,128 (49.7%) 4,039,913 (50.0%) Age group, years 18–29 123,576 (26.1%) 1,389,202 (18.3%) 1,512,778 (18.7%) 30–39 93,549 (19.8%) 1,295,735 (17.0%) 1,389,284 (17.2%) 40–49 75,419 (15.9%) 1,220,404 (16.0%) 1,295,823 (16.0%) 50–59 74,689 (15.8%) 1,229,745 (16.2%) 1,304,434 (16.2%) 60–69 53,272 (11.3%) 1,042,587 (13.7%) 1,095,859 (13.6%) 70–79 36,203 (7.6%) 949,670 (12.5%) 985,873 (12.2%) 80+ 16,678 (3.5%) 479,505 (6.3%) 496,183 (6.1%) Mean [SD] age, years 45.0 [18.1] 50.2 [19.0] 49.9 [19.0] Region of residence East 217,982 (46.0%) 2,977,470 (39.1%) 3,195,452 (39.5%) South 180,150 (38.1%) 3,308,918 (43.5%) 3,489,068 (43.2%) North 75,246 (15.9%) 1,312,775 (17.3%) 1,388,021 (17.2%) Missing 8 (0.0%) 7,685 (0.1%) 7,693 (0.1%) Highest educational attainment University (> 12 years) 132,793 (28.0%) 2,928,124 (38.5%) 3,060,917 (37.9%) Secondary school (9–12 years) 218,796 (46.2%) 3,263,952 (42.9%) 3,482,748 (43.1%) Primary school (< 9 years) 114,887 (24.3%) 1,224,746 (16.1%) 1,339,633 (16.6%) Missing 6,910 (1.5%) 190,026 (2.5%) 196,936 (2.4%) Cohabitation status Cohabiting 103,576 (21.9%) 3,227,296 (42.4%) 3,330,872 (41.2%) Non-cohabiting 369,802 (78.1%) 4,371,867 (57.5%) 4,741,669 (58.7%) Missing 8 (0.0%) 7,685 (0.1%) 7,693 (0.1%) Income Q1 (lowest) 212,484 (44.9%) 1,805,939 (23.8%) 2,018,423 (25.0%) Q2 116,302 (24.6%) 1,903,106 (25.0%) 2,019,408 (25.0%) Q3 83,798 (17.7%) 1,933,705 (25.4%) 2,017,503 (25.0%) Q4 (highest) 60,794 (12.8%) 1,956,408 (25.7%) 2,017,202 (24.9%) Missing 8 (0.0%) 7,690 (0.1%) 7,698 (0.1%) Severe COVID-19 infection Yes 3,769 (0.8%) 24,773 (0.3%) 28,542 (0.4%) No 469,617 (99.2%) 7,582,075 (99.7%) 8,051,692 (99.6%) Charlson Comorbidity Index (CCI) 0 382,408 (80.8%) 6,770,464 (89.0%) 7,152,872 (88.5%) 1 32,744 (6.9%) 299,760 (3.9%) 332,504 (4.1%) 2+ 58,234 (12.3%) 536,624 (7.1%) 594,858 (7.4%) First dose of a COVID-19 vaccine by 30th September 2021 In this study population, uptake of the first dose of a COVID-19 vaccine by 30th September 2021 was high (84.6%; n = 6,834,074/8,080,234) (Table 4 ). However vaccination uptake was slightly lower in individuals with (78.1%; n = 369,549/473,386) v.s. without (85.0%; 6,464,525/7,606,848) a specialist diagnosis of a mental illness. Vaccination uptake in relation to each type of mental illness diagnosis and type of psychiatric medication used is shown in Supplementary Table 11. Table 4 Uptake of COVID-19 vaccination overall, and by specialist diagnosis of any mental illness and prescribed use of any psychiatric medication, in the included Swedish register population, presented as N (%). First dose of a COVID-19 vaccine by 30th September 2021 Second dose of a COVID-19 vaccine by 30th November 2021 Yes No Total Yes No Total Total study population 6,834,074 (84.6%) 1,246,160 (15.4%) 8,080,234 (100.0%) 6,704,293 (98.1%) 129,761 (1.9%) 6,834,054 (100.0%) Any mental illness Yes 369,549 (78.1%) 103,837 (21.9%) 473,386 (100.0%) 355,040 (96.1%) 14,508 (3.9%) 369,548 (100.0%) No 6,464,525 (85.0%) 1,142,323 (15.0%) 7,606,848 (100.0%) 6,349,253 (98.2%) 115,253 (1.8%) 6,464,506 (100.0%) Any psychiatric medication Yes 1,801,401 (87.7%) 253,406 (12.3%) 2,054,807 (100.0%) 1,766,489 (98.1%) 34,909 (1.9%) 1,801,398 (100.0%) No 5,032,673 (83.5%) 992,754 (16.5%) 6,025,427 (100.0%) 4,937,804 (98.1%) 94,852 (1.9%) 5,032,656 (100.0%) Taking into account all covariates, we found that the uptake of vaccination in individuals with any mental illness was 2% lower than that of individuals without a mental illness (PR: 0.98, 95% CI: 0.98–0.99, p < 0.001) (Fig. 2 A). Similarly small differences in vaccination uptake were shown for most types of mental illness, except for substance use disorder which had the strongest association with lower vaccination uptake (PR: 0.95, 95% CI: 0.94–0.95, p < 0.001). A 3% higher uptake was observed among individuals using prescribed psychiatric medication, compared to individuals not using such medication (PR: 1.03, 95% CI: 1.03–1.03, p < 0.001). Similar associations were found for different types of psychiatric medication. Stratified analyses revealed no substantial differences in the associations by sex or the presence of chronic physical conditions (Supplementary Table 12). Results from the multi-level exposure analysis showed that, compared to individuals with neither a specialist mental illness diagnosis nor prescribed use of psychiatric medication, vaccination uptake was 3% higher among those with prescribed use of psychiatric medication but no specialist diagnosis (PR: 1.03, 95% CI: 1.03–1.03, p < 0.001), and 1% higher among those with both a specialist diagnosis and prescribed use of any psychiatric (PR: 1.01, 95% CI: 1.01–1.01, p < 0.001) (Fig. 3 A). However, those with a specialist diagnosis of any mental illness but no prescribed use of any psychiatric medication had a 9% reduction in vaccination uptake (PR: 0.91, 95% CI: 0.91–0.91, p < 0.001). This pattern was also observed for the multi-level exposure analysis carried out for anxiety, depression, and psychotic disorder. Second dose of a COVID-19 vaccine by 30th November 2021 6,834,054 individuals were eligible for the analysis of the uptake of the second dose of a COVID-19 vaccine by 30th November 2021 (Table 4 ). Vaccination uptake had a very high coverage overall (98.1%; n = 6,704,293/6,834,054), and the difference between those with (96.1%; n = 355,040/369,548) v.s. without (98.2%; n = 6,349,253/6,464,506) a mental illness was very small. A very small difference in vaccination uptake was noted among those with v.s. without a specialist diagnosis of a mental illness (PR: 0.99, 95% CI: 0.99–0.99, p < 0.001) or prescribed use of psychiatric medication (Fig. 2 B). This was also observed for different types of mental illness diagnosis and all types of psychiatric medication. Results from the stratified analyses showed no differences in the associations by sex or the presence of chronic physical conditions (Supplementary Table 12). Simiarly, the multi-level exposure analysis showed statistically significant, but very small, differences in vaccination uptake according to specialist diagnosis and/or prescribed medication use (Fig. 3 B). DISCUSSION This multinational study of 325,298 individuals from the participating COVIDMENT cohort studies, and 8,080,234 individuals from the Swedish national registers, showed that uptake of COVID-19 vaccination was high, and differences in uptake by mental illness were, in general, small. The majority of the analyses conducted in the COVIDMENT study population showed no significant difference in vaccination uptake according to the presence of diagnosed mental illness or anxiety or depressive symptoms. In the Swedish register analysis, although slightly lower vaccination uptake was observed among individuals with a specialist diagnosis of a mental illness, the absolute difference in vaccination uptake was very small. We did, however, observe that individuals with a specialist diagnosis of mental illness without ongoing psychiatric treatment had approximately 9% lower uptake of COVID-19 vaccination. Our findings of substantially lower vaccination uptake among individuals with unmedicated diagnosed mental illness in the Swedish register study analysis have important implications. Although we were unable to investigate the underlying reasons in the present study, lower vaccination uptake could have been due to particularly low levels of engagement with preventative healthcare in these groups.( 28 ) Individuals with mental illness have been shown to have poor access to nonpsychiatric healthcare, including preventative services such as vaccination programmes, primarily due to barriers such as low levels of knowledge and awareness of such services, and accessibility issues.( 29 ) However, pilot interventions aimed at increasing vaccination uptake among individuals with mental illness by addressing these barriers, for example through targeted education campaigns and the integration of psychiatric providers in vaccination programmes, have been shown to be effective.( 29 , 30 ) Therefore, strategies such as these could be incorporated into future vaccination campaings in order to reduce barriers to vaccination among individuals with relatively severe mental illness (e.g., attended by specialist care). We found no significant association between mental illness and COVID-19 vaccinion uptake in most of the COVIDMENT cohorts, and the absolute rate of vaccination in the included cohorts was generally high, both among individuals with and without mental illness. The slight differences across cohorts could have been, at least partially, due to the varying prioritisation schedules for COVID-19 vaccination used in the different countries. Although the European Union (EU) recommended that member states prioritise indivdiuals at the highest risk for severe COVID-19, countries could decide which population groups to include in their prioritisation schedules, meaning that not all countries prioritised vaccination for individuals with mental illness.( 31 ) There are many strengths of our study, which represents the first multinational study of the association between mental illness and COVID-19 vaccination uptake. The complementary use of the two different types of prospectively collected data sources combined the benefits of the rich self-reported COVIDMENT data with the Swedish national registers, which has minimal concerns of selection bias, thereby increasing the robustness of the study’s conclusions. By including a very large sample size from several different countries we were also able to investigate whether the results found in previous country-specific studies translated to an multinational context. However, limitations of the study must also be noted. Although the multinational nature of the study increases the representativeness of the findings, all participating countries have established welfare systems and generally accessible healthcare, meaning caution should be taken when generalising the results to other global regions. There were also specific limitations relating to the two study populations, such as potential selection bias in the COVIDMENT cohorts, meaning individuals with severe mental illness were less likely to take part in the study. In conclusion, in this large, multinational study we showed that uptake of the COVID-19 vaccine was high, even among most individuals with a mental illness, highlighting the comprehensiveness and success of the COVID-19 vaccination campaign in reaching most population groups. However, specific groups of people with a recent specialist diagnosis of mental illness yet not on psychiatric medication, were still at risk for low vaccination uptake. These findings have important implications for the design of current and future vaccination campaigns against infectious diseases and future pandemics. Declarations Data Sharing Statement The raw data underlying this article were subject to ethical approval and cannot be shared publicly due to data protection laws in each participating country. Acknowledgements We would like to thank all of the participants who contributed data to the COVIDMENT project. The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this ongoing cohort study. We would also like to acknowledge the work of the Estonian Biobank Research Team. Author Contributions The participating COVIDMENT cohorts and/or their data collections were designed by IM, AL, AKK, EEJ, AHo, SUJ, HA, DLM, OVE, KL, UAV, FF and their respective teams. HL and FN provided the registry-based data, server and software to conduct the analysis. MMB, FF and UAV directed the combined effort of this study implementation. MMB, EH, HL, UAV, FN and FF designed the analytical strategy in close collaboration with all team members and all authors helped to interpret the findings. MMB and GM conducted the literature review and MMB, KK, IM, HM, BW, and XD drafted the manuscript under supervision of UAV, FN, and FF. All authors revised the manuscript for critical content and approved the final version of the manuscript. MMB, GM and HL had access to and verified the data. Competing Interests EMF received speaker’s honoraria from Astra Zeneca. OAA is a consultant for Cortechs.ai, and received speaker’s honoraria from Janssen, Lundbeck, Sunovion, Otsuka. PFS is a shareholder and on the advisory committee of Neumora Therapeutics. FN owns some AstraZeneca shares. Funding This work was supported by grants from NordForsk (https://www.nordforsk.org) [COVIDMENT, grant numbers 105668 and 138929] and Horizon 2020 (https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-2020_en) [CoMorMent, 847776]. Estonian Biobank is supported by the European Union through the European Regional Development Fund (https://ec.europa.eu/regional_policy/funding/erdf_en) [Project No. 2014-2020.4.01.15-0012]. KL and KK were supported by the Estonian Research Council (https://etag.ee/en/) [grant PSG615] and Estonian sub-project of NordForsk project no. 105668. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (https://www.cso.scot.nhs.uk) [CZD/16/6] and the Scottish Funding Council (https://www.sfc.ac.uk) [HR03006] and is currently supported by the Wellcome Trust (https://wellcome.org) [216767/Z/19/Z]. Recruitment to the CovidLife study was facilitated by SHARE- the Scottish Health Research Register and Biobank (https://www.registerforshare.org). SHARE is supported by NHS Research Scotland, the Universities of Scotland and the Chief Scientist Office of the Scottish Government. Omtanke2020 was supported by funding from the Swedish Research Council (https://www.vr.se/english.html) [D0886501]. SCIFI-PEARL has funding to support this study from the SciLifeLab National COVID-19 Research Program, financed by the Knut and Alice Wallenberg Foundation (https://kaw.wallenberg.org/en) [grants KAW 2021-0010/VC2021.0018 and KAW 2020.0299/VC 2022.0008], and the Swedish Research Council (https://www.vr.se/english.html) [grants 2021-05045 and 2021-05450]. SCIFI-PEARL also has basic funding based on grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF agreement (https://www.vr.se/english/mandates/clinical-research/clinical-research-in-the-alf-regions.html) [grants ALFGBG-938453, ALFGBG-971130, ALFGBG-978954] and from FORMAS (Research Council for Environment, Agricultural Sciences and Spatial Planning), a Swedish Research Council for Sustainable Development (https://formas.se/en/start-page.html) [grant 2020-02828]. OAA and BW were also supported by the Research Council of Norway (https://www.forskningsradet.no/en/) [#223273 and #324620, resepctively]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. References World Health Organisation. WHO Coronavirus (COVID-19) Dashboard 2023 [Available from: https://covid19.who.int. Tregoning JS, Flight KE, Higham SL, Wang Z, Pierce BF. 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Moghadas SM, Vilches TN, Zhang K, Nourbakhsh S, Sah P, Fitzpatrick MC, et al. Evaluation of COVID-19 vaccination strategies with a delayed second dose. PLoS biology. 2021;19(4):e3001211. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. American journal of epidemiology. 2011;173(6):676-82. Lawrence D, Kisely S. Inequalities in healthcare provision for people with severe mental illness. Journal of psychopharmacology. 2010;24(4_suppl):61-8. Miles LW, Williams N, Luthy KE, Eden L. Adult vaccination rates in the mentally ill population: an outpatient improvement project. Journal of the American Psychiatric Nurses Association. 2020;26(2):172-80. Lim C, Van Alphen MU, Maclaurin S, Mulligan C, Macri B, Cather C, et al. Increasing COVID-19 vaccination rates among patients with serious mental illness: a pilot intervention study. Psychiatric Services. 2022;73(11):1274-7. De Picker LJ, Dias MC, Benros ME, Vai B, Branchi I, Benedetti F, et al. Severe mental illness and European COVID-19 vaccination strategies. The Lancet Psychiatry. 2021;8(5):356-9. Additional Declarations Yes there is potential Competing Interest. EMF received speaker’s honoraria from Astra Zeneca. OAA is a consultant for Cortechs.ai, and received speaker’s honoraria from Janssen, Lundbeck, Sunovion, Otsuka. PFS is a shareholder and on the advisory committee of Neumora Therapeutics. FN owns some AstraZeneca shares. Supplementary Files supplementarymaterialBarkeretal.pdf Cite Share Download PDF Status: Published Journal Publication published 26 Sep, 2024 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Iceland","correspondingAuthor":false,"prefix":"","firstName":"Thor","middleName":"","lastName":"Aspelund","suffix":""},{"id":279262855,"identity":"bf4cc588-63b0-4a28-ac11-cad8b4acd716","order_by":27,"name":"Ragnhild Brandlistuen","email":"","orcid":"","institution":"Department of Child Health and Development, Norwegian Institute of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Ragnhild","middleName":"","lastName":"Brandlistuen","suffix":""},{"id":279262856,"identity":"9410c951-0142-4c6f-a181-9dc6f8f17c46","order_by":28,"name":"Helga Ask","email":"","orcid":"https://orcid.org/0000-0003-0149-5319","institution":"Norwegian Institute of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Helga","middleName":"","lastName":"Ask","suffix":""},{"id":279262857,"identity":"47ab5df0-a644-42f3-acf6-cbe32a47dbc5","order_by":29,"name":"Daniel McCartney","email":"","orcid":"https://orcid.org/0000-0003-3242-0360","institution":"Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"McCartney","suffix":""},{"id":279262858,"identity":"7ef3f515-fd63-4bd9-98de-ad58941f5d67","order_by":30,"name":"Omid Ebrahimi","email":"","orcid":"","institution":"University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Omid","middleName":"","lastName":"Ebrahimi","suffix":""},{"id":279262859,"identity":"73ee89fc-fd88-4cb6-aeef-ea8f07f6ccea","order_by":31,"name":"Kelli Lehto","email":"","orcid":"","institution":"Tartu University","correspondingAuthor":false,"prefix":"","firstName":"Kelli","middleName":"","lastName":"Lehto","suffix":""},{"id":279262860,"identity":"19da2a8e-c2b5-41d9-bc2d-35fce897bb6c","order_by":32,"name":"Unnur Valdimarsdóttir","email":"","orcid":"https://orcid.org/0000-0001-5382-946X","institution":"University of Iceland","correspondingAuthor":false,"prefix":"","firstName":"Unnur","middleName":"","lastName":"Valdimarsdóttir","suffix":""},{"id":279262861,"identity":"93f9ed30-024c-4542-aee0-e0addd6cf951","order_by":33,"name":"Fredrik Nyberg","email":"","orcid":"https://orcid.org/0000-0003-0892-5668","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Fredrik","middleName":"","lastName":"Nyberg","suffix":""},{"id":279262862,"identity":"5f2d099b-db9e-4ee6-bd3d-4a19d20eedcd","order_by":34,"name":"Fang Fang","email":"","orcid":"https://orcid.org/0000-0002-3310-6456","institution":"Karolinska Institutet","correspondingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Fang","suffix":""}],"badges":[],"createdAt":"2024-03-11 14:25:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4075473/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4075473/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-024-52342-1","type":"published","date":"2024-09-26T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52704518,"identity":"efcbf208-a8eb-4143-8e96-8479145143ad","added_by":"auto","created_at":"2024-03-14 18:32:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":568920,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence ratio (PR) and 95% CI of (A) first dose of a COVID-19 vaccine by 30\u003csup\u003eth\u003c/sup\u003e September 2021, (B) first dose of a COVID-19 vaccine by 18\u003csup\u003eth\u003c/sup\u003e February 2022, (C) second dose of a COVID-19 vaccine by 18\u003csup\u003eth\u003c/sup\u003e February 2022, according to the presence of any mental illness diagnosis, anxiety symptoms or depressive symptoms, in the included COVIDMENT study population. N.B. PR and 95% CI reported rounded to 2 decimal places.\u003c/p\u003e","description":"","filename":"Figure1Barkeretal.png","url":"https://assets-eu.researchsquare.com/files/rs-4075473/v1/4147350d4abb05044eab7c65.png"},{"id":52705090,"identity":"39ce2643-098b-41a7-95ab-715cf4638311","added_by":"auto","created_at":"2024-03-14 18:40:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":540085,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence ratio (PR) and 95% CI of (A) first dose of a COVID-19 vaccine by 30\u003csup\u003eth\u003c/sup\u003e September 2021 and (B) second dose of a COVID-19 vaccine by 30\u003csup\u003eth\u003c/sup\u003e November 2021, according to specialist diagnosis of a mental illness and prescribed use of psychiatric medication, in the Swedish register study population. N.B. PR and 95% CI reported rounded to 2 decimal places. ‘Substance use disorder’ excludes alcohol and tobacco use disorders.\u003c/p\u003e","description":"","filename":"Figure2Barkeretal.png","url":"https://assets-eu.researchsquare.com/files/rs-4075473/v1/553f0db87f134cc0646d50d2.png"},{"id":52704519,"identity":"c7050e8f-1aac-4460-a731-9bfe8521064e","added_by":"auto","created_at":"2024-03-14 18:32:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":450086,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence ratio (PR) and 95% CI of (A) first dose of a COVID-19 vaccine by 30\u003csup\u003eth \u003c/sup\u003eSeptember 2021 and (B) second dose of a COVID-19 vaccine by 30\u003csup\u003eth\u003c/sup\u003e November 2021, according to specialist diagnosis of a mental illness/prescribed medication use status, in the Swedish register study population. N.B. PR and 95% CI reported rounded to 2 decimal places.\u003c/p\u003e","description":"","filename":"Figure3Barkeretal.png","url":"https://assets-eu.researchsquare.com/files/rs-4075473/v1/00136ea58ed79713d2b46931.png"},{"id":65415514,"identity":"353572fd-0ec4-4696-b730-803a6a42cbc3","added_by":"auto","created_at":"2024-09-27 07:06:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2339882,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4075473/v1/bc3b4876-6f1a-4365-9fc5-44afe2c7e0fc.pdf"},{"id":52704521,"identity":"7e7ed070-45d5-4968-ae5f-eb09ac61104f","added_by":"auto","created_at":"2024-03-14 18:32:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":429505,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"supplementarymaterialBarkeretal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4075473/v1/cf52e966e92910f6ba0526c1.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nEMF received speaker’s honoraria from Astra Zeneca. OAA is a consultant for Cortechs.ai, and received speaker’s honoraria from Janssen, Lundbeck, Sunovion, Otsuka. PFS is a shareholder and on the advisory committee of Neumora Therapeutics. FN owns some AstraZeneca shares.","formattedTitle":"Mental illness and COVID-19 vaccination: a multinational investigation of observational \u0026 register-based data","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe coronavirus disease 2019 (COVID-19) pandemic was an unprecedented global health crisis, which, as of August 2023, had caused 6.9\u0026nbsp;million deaths globally.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Although multiple effective vaccines against COVID-19 were developed and distributed globally, vaccine hesitancy and refusal were observed worldwide.(\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Crucially, the success of vaccination programmes in controlling the COVID-19 pandemic relies on high vaccination coverage,(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) which is especially important among people at increased risk of severe COVID-19 infection and COVID-19-related mortality, including individuals with mental illness.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePrevious systematic reviews exploring the association between mental illness and uptake of various vaccinations have reported heterogenous results.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) Similarly, results from previous country-specific studies of COVID-19 vaccination uptake in people with mental illness have been inconsistent. While some studies have observed significantly lower uptake of COVID-19 vaccination among individuals with mental illness,(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) others have either reported higher uptake (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), no significant difference,(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) or differences in uptake according to the type of mental illness.(\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) Additionally, little is currently known regarding the effect of psychiatric treatment on COVID-19 vaccination uptake. As a result, the relationship between mental illness and COVID-19 vaccination uptake may be more complex, and could differ depending on the type, severity, and treatment status of mental illness.\u003c/p\u003e \u003cp\u003eA comprehensive understanding of the impact of mental illness on COVID-19 vaccination uptake is crucial to inform the design of future vaccination campaigns, and, ultimately, to protect at-risk populations from infectious diseases and future pandemics. This study aimed to investigate the association between mental illness and COVID-19 vaccination uptake using data from seven cohort studies included in the multinational COVIDMENT consortium,(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) in addition to data from Swedish national registers, focusing on studying mental illness of different types, severity, and treatment status (i.e., use of prescribed psychiatric medications).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCOVIDMENT Study Analysis\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eThe COVIDMENT study population included data from seven cohorts within the COVIDMENT consortium, namely the Estonian Biobank (EstBB) cohorts: EstBB full cohort with electronic health record linkages (EstBB-EHR) and the EstBB COVID-19 subcohort (EstBB-C19); the Icelandic COVID-19 National Resilience Cohort (C-19 Resilience); the Norwegian COVID-19 Mental Health and Adherence study (MAP-19); the Norwegian Mother, Father, and Child Cohort study (MoBa);(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) the Scottish CovidLife study; and the Swedish Omtanke2020 study.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) Ethical approvals for all included cohorts were obtained from regional or national ethics committees, and all participants provided informed consent (Supplementary Table\u0026nbsp;1). The cohorts used different recruitment strategies, with most recruiting from established cohorts whilst others also allowed self-recruitment via social media. The number of data collection waves varied between the cohorts, with the first data collected in March 2020.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eExposure Variables\u003c/h2\u003e \u003cp\u003eAll exposure variables referred to mental illness experienced before the initiation of COVID-19 vaccination in each study country (Supplementary Table\u0026nbsp;2). The primary exposure variable was the lifetime diagnosis of any mental illness, which, for all cohorts except EstBB-C19 and EstBB-EHR, was defined using self-report data from questionnaire items asking participants if they had ever been diagnosed with any mental illness. In EstBB-C19 and EstBB-EHR, ICD-10 codes were used to define mental illness diagnoses through linked EHRs (containing diagnoses from Estonian Health Insurance Fund (HIF) treatment bills since 2004), including primary/secondary care and inpatient/outpatient diagnoses (Supplementary Table\u0026nbsp;3). Anxiety and depressive symptoms were included as secondary exposure variables. In the majority of cohorts, moderate-to-severe anxiety and depressive symptoms, during the past two weeks, were defined as total scores of \u0026ge;\u0026thinsp;10 from the Generalised Anxiety Disorder Assessment (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) scales, respectively.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) In EstBB-C19, anxiety and depressive symptoms, during the past four weeks, were measured using the Emotional State Questionnaire (EST-Q2), utilising cut-off values of \u0026gt;\u0026thinsp;11 to define moderate-to-severe anxiety or depressive symptoms.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Variables\u003c/h2\u003e \u003cp\u003eThe primary outcome variable was (i) first dose of a COVID-19 vaccine by 30th September 2021. This end date represents the time at which all included countries had offered COVID-19 vaccination to all adult residents and cohort participants had adequate opportunity to book and attend vaccination appointments (Supplementary Table\u0026nbsp;2). Two additional outcome variables were used: (ii) first dose of a COVID-19 vaccine by 18th February 2022, and (iii) second dose of a COVID-19 vaccine by 18th February 2022. This second date represents the time point at which the majority of cohorts had conducted a new wave of data collection, and therefore it was the first date post-September 2021 that vaccination uptake could be re-assessed. As C-19 Resilience did not conduct further data collection between September 2021 and February 2022, it was only included in the analysis of outcome (i). Participants were eligible for the present study if they had available data for outcomes (i) and/or (ii). Participants were included in the analysis of outcome (iii) if they had received the first dose of any COVID-19 vaccine, except the JCOVDEN vaccine (for which a one-dose schedule was used(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)), before 18th February 2022. In C-19 Resilience, MAP-19, MoBa, and Omtanke2020, vaccination uptake was defined using self-report data collected in various cohort-specific follow-up questionnaires. The remaining cohorts used linked EHR data to define vaccination uptake.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eAll covariates (age, sex, smoking status, previous COVID-19 infection, and physical comorbidity status) were defined using data collected before COVID-19 vaccination was initiated in each study country. Smoking was used as a binary variable, defined as current or non-current smoker or user of any tobacco products at the time of data collection. COVID-19 infection was defined as a positive COVID-19 test before the initiation of COVID-19 vaccination. Self-report data was used to define COVID-19 infection in the majority of cohorts. However, the Electronic Communication of Surveillance in Scotland (ECOSS) COVID-19 testing data was used in the CovidLife cohort, and the E-Health Record registry data was used in EstBB-EHR. Physical comorbidity status was defined as the presence of at least two physical health conditions (hypertension, heart disease, lung disease, chronic renal failure, cancer, diabetes, or immunological conditions), using either self-report data from the cohort-specific questionnaires or EHR data (Supplementary Table\u0026nbsp;3). Neither data on smoking nor physical comorbditiy status was available in the MAP-19 cohort. Further details regarding the time at which variables were defined in each cohort are displayed in Supplementary Table\u0026nbsp;4.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eCovariates were summarised, stratified by the diagnosis of any mental illness, using mean (standard deviation [SD]) or frequency (percentage), as appropriate. Multivariable modified Poisson regression models were conducted for each exposure-outcome combination, to assess the prevalence ratio (PR) with 95% confidence intervals (CI), adjusted for age, sex, previous COVID-19 infection, smoking, and physical comorbidity status. Due to data inavailability in MAP-19, models from this cohort were only adjusted for age, sex, and previous COVID-19 infection. As EstBB-EHR had a high proportion of missing COVID-19 testing data, this cohort used an additional \u0026ldquo;missing\u0026rdquo; indicator for the COVID-19 infection covariate in addition to \u0026ldquo;negative\u0026rdquo; and \u0026ldquo;positive\u0026rdquo; groups, to avoid dropping large numbers of participants. Random effects meta-analyses were performed to pool the results from each participating cohort. Heterogeneity was assessed using the I\u003csup\u003e2\u003c/sup\u003e statistic.\u003c/p\u003e \u003cp\u003eTwo sensitivity analyses were conducted: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) to explore potential differences related to self-report vs. EHR-based variable definitions, meta-analyses for the primary exposure variable (\u0026lsquo;diagnosis of any mental illness\u0026rsquo;) were run excluding cohorts that used EHR to define exposure and/or outcome variables (i.e., CovidLife, EstBB-C19, and EstBB-EHR), (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) to further explore the potential impact of physical health status, meta-analyses for the primary exposure variable were conducted excluding participants with any chronic physical conditions (using all cohorts except MAP-19). Statistical analyses were conducted using STATA (version 17.0) and the metafor package in R (version 4.3.0).(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSwedish Register Study Analysis\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eTo assess the internal and external validity of the COVIDMENT results, and to gain understanding of the role of disease type, severity and treatment status on the association between mental illness and COVID-19 vaccination uptake, further analyses were conducted using Swedish register data within the SCIFI-PEARL (Swedish COVID-19 Investigation for Future Insights \u0026ndash; a Population Epidemiology Approach using Register Linkage) project.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) Ethical approval was obtained from the Swedish Ethical Review Authority (2020\u0026thinsp;\u0026minus;\u0026thinsp;01800 with subsequent amendments). SCIFI-PEARL is a regularly updated, nationwide register-based study, with individual linkages to multiple registers performed using the unique Swedish Personal Identity Number (PIN). The present study included all individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years who were living in Sweden on 27th December 2020 (date of first COVID-19 vaccination in Sweden(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)) and did not die or emigrate on or before the final study end point (30th November 2021).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eExposure Variables\u003c/h2\u003e \u003cp\u003eMental illness was first defined using secondary care-based specialist diagnoses (as denoted by \u0026ge;\u0026thinsp;1 ICD-10 code listed in Supplementary Table\u0026nbsp;5) from all inpatient and outpatient hospital encounters reported in the National Patient Register (NPR) between 1st January 2018 and 26th December 2020. In addition to any mental illness, we also studied specific types of mental illness (substance use disorder [excluding aclohool and tobacco use disorders], alcohol use disorder, tobacco use disorder, psychotic disorders, depression, anxiety, and stress-related disorders), defined by \u0026ge;\u0026thinsp;1 relevant ICD-10 code. The NPR includes data on specialist care only, whereas patients with milder mental illness are often treated in primary care. Therefore, we also identified information on prescribed use of psychiatric medication (as denoted by \u0026ge;\u0026thinsp;1 Anatomical Therapeutic Chemical (ATC) code displayed in Supplementary Table\u0026nbsp;6), between 1st January 2018 and 26th December 2020, according to the National Prescribed Drug Register (NPDR). Prescribed use of psychiatric medication was used both to ascertain mental illnesses not attended to by specialist care and as a proxy for treatment of mental illness. We studied prescribed use of any psychiatric medication as well as prescribed use of antidepressants, anxiolytics, hypnotics/sedatives, and antipsychotics, respectively.\u003c/p\u003e \u003cp\u003eTo investigate the effect of disease severity and treatment with psychiatric medication, an alternative (multi-level) categorisation of exposure variables was used for any mental illness, depression, anxiety, and psychotic disorder, with the following categories: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) no specialist diagnosis of mental illness and no prescribed use of psychiatric medication (i.e., reference category), (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) prescribed use of psychiatric medication without specialist diagnosis (i.e., proxy of milder illness with medical treatment), (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) specialist diagnosis with prescribed use of psychiatric medication (i.e., proxy of more severe illness with medical treatment), and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) specialist diagnosis without prescribed use of psychiatric medication (i.e., proxy of more severe illness without medical treatment).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Variables\u003c/h2\u003e \u003cp\u003eFor the definition of outcome variables, the National Vaccination Register (NVR) was used, which includes information on all COVID-19 vaccinations conducted in Sweden from December 2020.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) Two outcome variables were used: (i) first dose of a COVID-19 vaccine by 30th September 2021, and (ii) second dose of a COVID-19 vaccine by 30th November 2021. By using this end date for outcome (ii) we ensured that all individuals vaccinated with a first dose up until 30th September would have had the recommended time period between their first and second vaccine dose.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) Individuals were included in the analysis of outcome (ii) if they had received the first dose of any COVID-19 vaccine, except the JCOVDEN vaccine, by 30th September 2021.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eCovariates included age and sex (identified through the Total Population Register (TPR)), region of residence, highest educational attainment, cohabitation status, and income (identified from the Swedish Longitudinal Integrated Database for Health Insurance and Labour Market Studies (LISA) in 2020), severe COVID-19 infection and the Charlson Comorbidity Index (CCI). Severe COVID-19 infection was defined as an inpatient or ICU visit due to COVID-19 before the study start date (27th December 2020), whilst CCI was calculated at the study start date, using diagnostic data identified from 1st January 2015 onwards in the NPR.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll covariates were summarized, stratified by the diagnosis of any mental illness, using mean (standard deviation [SD]) or frequency (percentage), as appropriate. Multivariable modified Poisson regression models were run for all exposures and outcomes to assesss PR and 95% CIs of COVID-19 vaccination uptake in relation to mental illness, adjusted for the covariates listed above. Stratified analyses were conducted by sex and the presence of chronic physical condition(s) (defined as a CCI score of \u0026ge;\u0026thinsp;1). Complete case analysis was used throughout. Statistical analyses were conducted using STATA (version 17.0).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCOVIDMENT Study Analysis\u003c/h2\u003e \u003cp\u003eOf the 403,794 individuals included in the participating COVIDMENT cohort studies, 325,298 individuals met the eligibility criteria for the present study (Supplementary Fig.\u0026nbsp;1). Over half of the overall study population (65.1%), and of each participating cohort, were female (Supplementary Table\u0026nbsp;7). The mean age in the participating cohorts ranged from 36.9 years (MAP-19) to 59.4 years (CovidLife), with a mean of 48 years in the overall study population.\u003c/p\u003e \u003cp\u003eIndividuals with a diagnosis of any mental illness were more likely to be female, compared to those without a mental illness (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The proportion of individuals with chronic physical conditions was higher among those with any mental illness diagnosis. Low levels of missing data were observed for the majority of covariates.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of sociodemographic variables in the included COVIDMENT study population, overall and by diagnosis of any mental illness diagnosis, presented as N (%) or mean [SD].\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDiagnosis of any mental illness\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;122,976)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;201,273)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMissing (n\u0026thinsp;=\u0026thinsp;1,049)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;325,298)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstBB-C19 (Estonia)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,107 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,526 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,633 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstBB-EHR (Estonia)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95,208 (77.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88,124 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e183,332 (56.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-19 Resilience (Iceland)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,895 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,283 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e239 (22.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,417 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAP-19 (Norway)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e698 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,722 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e474 (45.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3,894 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoBa (Norway)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15,496 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87,315 (43.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102,811 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCovidLife (Scotland)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,230 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,499 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4,760 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmtanke2020 (Sweden)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,342 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9,804 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e305 (29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14,451 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88,515 (72.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e122,544 (60.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e753 (71.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e211,812 (65.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34,446 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78,713 (39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e205 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e113,364 (34.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,826 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14,670 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e265 (25.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27,761 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24,119 (19.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30,486 (15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e197 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54,802 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,864 (25.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78,311 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e177 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e110,352 (33.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24,359 (19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44,785 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e184 (17.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69,328 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17,228 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19,053 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e147 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36,428 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,558 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13,845 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26,479 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e148 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean [SD] age, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.5 [1.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.8 [3.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.1 [9.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.0 [2.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,094 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,629 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7,740 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64,035 (52.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140,877 (70.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1032 (98.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e205,944 (63.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55,847 (45.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55,767 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e111,614 (34.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26,465 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34,253 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60,780 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86,737 (70.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e155,181 (77.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e493 (47.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e242,411 (74.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,774 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11,839 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e494 (47.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22,107 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic physical conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47,606 (38.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123,948 (61.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171,714 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34,723 (28.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46,836 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81,627 (25.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39,497 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27,288 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66,831 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,150 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,201 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e775 (73.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,126 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Mainly due to COVID-19 testing data only being available for some EstBB-EHR individuals\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFirst dose of a COVID-19 vaccine by 30th September 2021\u003c/h2\u003e \u003cp\u003e314,827 individuals were included in the analysis of uptake of the first dose of a COVID-19 vaccine by 30th September 2021 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall vaccination uptake was high (85.1%; n\u0026thinsp;=\u0026thinsp;267,981/314,827). However, a small difference in uptake was observed between individuals with (82.4%; n\u0026thinsp;=\u0026thinsp;99,041/120,212) v.s. without (86.8%; n\u0026thinsp;=\u0026thinsp;168,174/193,706) any mental illness. Vaccination uptake in each included cohort is displayed in Supplementary Table\u0026nbsp;8.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUptake of COVID-19 vaccination overall and by diagnosis of any mental illness diagnosis, in the included COVIDMENT study population, presented as N (%).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUptake of first dose of a COVID-19 vaccine by 30th September 2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eUptake of first dose of a COVID-19 vaccine by 18th February 2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eUptake of second dose of a COVID-19 vaccine by 18th February 2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal study population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e267,981 (85.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46,846 (14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e314,827 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e278,887 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34,697 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e313,584 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e252,439 (95.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11,965 (4.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e264,404 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99,041 (82.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21,171 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e120,212 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103,955 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15,953 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e119,908 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e93,420 (94.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5,251 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e98,671 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo mental illness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168,174 (86.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25,532 (13.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e193,706 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e174,612 (90.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18,728 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e193,340 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e158,830 (95.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6,712 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e165,542 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e766 (84.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143 (15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e909 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e320 (95.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e336 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e189 (99.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e191 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eResults from the meta-analysis showed no significant association, after adjustment for covariates, between the diagnosis of any mental illness and vaccination uptake (pooled PR: 0.99, 95% CI: 0.97- 1.00]; I\u003csup\u003e2\u003c/sup\u003e: 91.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, Supplementary Table\u0026nbsp;9). Although the level of heterogeneity was high, a statistically significant association between the diagnosis of any mental illness and lower vaccination uptake was only found in the EstBB-EHR and MAP-19 cohorts. No associations were observed between anxiety or depressive symptoms and vaccination uptake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eFirst dose of a COVID-19 vaccine by 18th February 2022\u003c/h2\u003e \u003cp\u003eUptake of the first dose of a COVID-19 vaccine by 18th February 2022 was analysed in 313,584 individuals. Vaccination uptake was high (88.9%; n\u0026thinsp;=\u0026thinsp;278,887/313,584); however, a small difference in uptake remained between individuals with (86.7%; n\u0026thinsp;=\u0026thinsp;103,955/119,908) v.s. without (90.3%; n\u0026thinsp;=\u0026thinsp;174,612/193,340) mental illness (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResults from the meta-analysis revealed a small association, after adjustment for covariates, between the diagnosis of any mental illness and vaccination uptake (PR: 0.99, 95% CI: 0.98\u0026ndash;0.99; I\u003csup\u003e2\u003c/sup\u003e: 79.98, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, Supplementary Table\u0026nbsp;9). No associations were observed between anxiety or depressive symptoms and vaccination uptake.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSecond dose of a COVID-19 vaccine by 18th February 2022\u003c/h2\u003e \u003cp\u003e264,404 individuals were eligible for the analysis of uptake of the second dose of a COVID-19 vaccine by 18th February 2022 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among these individuals, vaccination uptake wasvery high (95.5%; n\u0026thinsp;=\u0026thinsp;252,439/264,404) and the difference in uptake between those with (94.7%; n\u0026thinsp;=\u0026thinsp;93,420/98,671) v.s. without (95.9%; n\u0026thinsp;=\u0026thinsp;158,830/165,542) mental illness was very small. Due to low numbers of participants, models could not be run in the MAP-19 and CovidLife cohorts.\u003c/p\u003e \u003cp\u003eThe meta-analysis of the remaining eligible cohorts showed no significant differences in vaccination uptake by the diagnosis of any mental illness or the presence of anxiety or depressive symptoms, after adjustment for covariates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, Supplementary Table\u0026nbsp;9).\u003c/p\u003e \u003cp\u003eFor all outcomes, no substantial differences were observed in any of the sensitivity analyses (Supplementary Table\u0026nbsp;10).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eSwedish Register Study Analysis\u003c/h2\u003e \u003cp\u003eAmong the 8,080,234 individuals included in the Swedish register study population, individuals with a specialist diagnosis of mental illness were more likely to be female (55.5% vs. 49.7%) and were, on average, younger (45.0 years vs. 50.2 years), compared to those without a mental illness (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among those with a mental illness diagnosis, the proportions of individuals who had completed university education, were cohabiting, and were in the highest quartile of income were all lower, whilst the presence of chronic physical conditions was more common, compared to those without a mental illness diagnosis. The proportion of missing data for all covariates was low (\u0026le;\u0026thinsp;2.5%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of sociodemographic variables in the included Swedish register study population, overall and by specialist diagnosis of a mental illness, presented as N (%) or mean [SD].\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMental illness (n\u0026thinsp;=\u0026thinsp;473,386)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo mental illness (n\u0026thinsp;=\u0026thinsp;7,606,848)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;8,080,234)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e210,601 (44.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,829,720 (50.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,040,321 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e262,785 (55.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,777,128 (49.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,039,913 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123,576 (26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,389,202 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,512,778 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93,549 (19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,295,735 (17.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,389,284 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75,419 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,220,404 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,295,823 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74,689 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,229,745 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,304,434 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53,272 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,042,587 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,095,859 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36,203 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e949,670 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e985,873 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16,678 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e479,505 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e496,183 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean [SD] age, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.0 [18.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.2 [19.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.9 [19.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217,982 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,977,470 (39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,195,452 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180,150 (38.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,308,918 (43.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,489,068 (43.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75,246 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,312,775 (17.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,388,021 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,685 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,693 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest educational attainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity (\u0026gt;\u0026thinsp;12 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132,793 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,928,124 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,060,917 (37.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary school (9\u0026ndash;12 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e218,796 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,263,952 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,482,748 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school (\u0026lt;\u0026thinsp;9 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114,887 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,224,746 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,339,633 (16.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,910 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190,026 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e196,936 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohabitation status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103,576 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,227,296 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,330,872 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-cohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e369,802 (78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,371,867 (57.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,741,669 (58.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,685 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,693 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212,484 (44.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,805,939 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,018,423 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116,302 (24.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,903,106 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,019,408 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83,798 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,933,705 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,017,503 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60,794 (12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,956,408 (25.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,017,202 (24.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,690 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,698 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere COVID-19 infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,769 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24,773 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28,542 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e469,617 (99.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,582,075 (99.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,051,692 (99.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson Comorbidity Index (CCI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e382,408 (80.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,770,464 (89.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7,152,872 (88.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32,744 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e299,760 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e332,504 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58,234 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e536,624 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e594,858 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eFirst dose of a COVID-19 vaccine by 30th September 2021\u003c/h2\u003e \u003cp\u003eIn this study population, uptake of the first dose of a COVID-19 vaccine by 30th September 2021 was high (84.6%; n\u0026thinsp;=\u0026thinsp;6,834,074/8,080,234) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However vaccination uptake was slightly lower in individuals with (78.1%; n\u0026thinsp;=\u0026thinsp;369,549/473,386) v.s. without (85.0%; 6,464,525/7,606,848) a specialist diagnosis of a mental illness. Vaccination uptake in relation to each type of mental illness diagnosis and type of psychiatric medication used is shown in Supplementary Table\u0026nbsp;11.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUptake of COVID-19 vaccination overall, and by specialist diagnosis of any mental illness and prescribed use of any psychiatric medication, in the included Swedish register population, presented as N (%).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFirst dose of a COVID-19 vaccine by 30th September 2021\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSecond dose of a COVID-19 vaccine by 30th November 2021\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal study population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,834,074 (84.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,246,160 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,080,234 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,704,293 (98.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e129,761 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,834,054 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAny mental illness\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e369,549 (78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103,837 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e473,386 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e355,040 (96.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14,508 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e369,548 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,464,525 (85.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,142,323 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,606,848 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,349,253 (98.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e115,253 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,464,506 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAny psychiatric medication\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,801,401 (87.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253,406 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,054,807 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,766,489 (98.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34,909 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,801,398 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,032,673 (83.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e992,754 (16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,025,427 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,937,804 (98.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94,852 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,032,656 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTaking into account all covariates, we found that the uptake of vaccination in individuals with any mental illness was 2% lower than that of individuals without a mental illness (PR: 0.98, 95% CI: 0.98\u0026ndash;0.99, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Similarly small differences in vaccination uptake were shown for most types of mental illness, except for substance use disorder which had the strongest association with lower vaccination uptake (PR: 0.95, 95% CI: 0.94\u0026ndash;0.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A 3% higher uptake was observed among individuals using prescribed psychiatric medication, compared to individuals not using such medication (PR: 1.03, 95% CI: 1.03\u0026ndash;1.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similar associations were found for different types of psychiatric medication. Stratified analyses revealed no substantial differences in the associations by sex or the presence of chronic physical conditions (Supplementary Table\u0026nbsp;12).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eResults from the multi-level exposure analysis showed that, compared to individuals with neither a specialist mental illness diagnosis nor prescribed use of psychiatric medication, vaccination uptake was 3% higher among those with prescribed use of psychiatric medication but no specialist diagnosis (PR: 1.03, 95% CI: 1.03\u0026ndash;1.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and 1% higher among those with both a specialist diagnosis and prescribed use of any psychiatric (PR: 1.01, 95% CI: 1.01\u0026ndash;1.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). However, those with a specialist diagnosis of any mental illness but no prescribed use of any psychiatric medication had a 9% reduction in vaccination uptake (PR: 0.91, 95% CI: 0.91\u0026ndash;0.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This pattern was also observed for the multi-level exposure analysis carried out for anxiety, depression, and psychotic disorder.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eSecond dose of a COVID-19 vaccine by 30th November 2021\u003c/h2\u003e \u003cp\u003e6,834,054 individuals were eligible for the analysis of the uptake of the second dose of a COVID-19 vaccine by 30th November 2021 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Vaccination uptake had a very high coverage overall (98.1%; n\u0026thinsp;=\u0026thinsp;6,704,293/6,834,054), and the difference between those with (96.1%; n\u0026thinsp;=\u0026thinsp;355,040/369,548) v.s. without (98.2%; n\u0026thinsp;=\u0026thinsp;6,349,253/6,464,506) a mental illness was very small.\u003c/p\u003e \u003cp\u003eA very small difference in vaccination uptake was noted among those with v.s. without a specialist diagnosis of a mental illness (PR: 0.99, 95% CI: 0.99\u0026ndash;0.99, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or prescribed use of psychiatric medication (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). This was also observed for different types of mental illness diagnosis and all types of psychiatric medication. Results from the stratified analyses showed no differences in the associations by sex or the presence of chronic physical conditions (Supplementary Table\u0026nbsp;12). Simiarly, the multi-level exposure analysis showed statistically significant, but very small, differences in vaccination uptake according to specialist diagnosis and/or prescribed medication use (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis multinational study of 325,298 individuals from the participating COVIDMENT cohort studies, and 8,080,234 individuals from the Swedish national registers, showed that uptake of COVID-19 vaccination was high, and differences in uptake by mental illness were, in general, small. The majority of the analyses conducted in the COVIDMENT study population showed no significant difference in vaccination uptake according to the presence of diagnosed mental illness or anxiety or depressive symptoms. In the Swedish register analysis, although slightly lower vaccination uptake was observed among individuals with a specialist diagnosis of a mental illness, the absolute difference in vaccination uptake was very small. We did, however, observe that individuals with a specialist diagnosis of mental illness without ongoing psychiatric treatment had approximately 9% lower uptake of COVID-19 vaccination.\u003c/p\u003e \u003cp\u003eOur findings of substantially lower vaccination uptake among individuals with unmedicated diagnosed mental illness in the Swedish register study analysis have important implications. Although we were unable to investigate the underlying reasons in the present study, lower vaccination uptake could have been due to particularly low levels of engagement with preventative healthcare in these groups.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) Individuals with mental illness have been shown to have poor access to nonpsychiatric healthcare, including preventative services such as vaccination programmes, primarily due to barriers such as low levels of knowledge and awareness of such services, and accessibility issues.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) However, pilot interventions aimed at increasing vaccination uptake among individuals with mental illness by addressing these barriers, for example through targeted education campaigns and the integration of psychiatric providers in vaccination programmes, have been shown to be effective.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) Therefore, strategies such as these could be incorporated into future vaccination campaings in order to reduce barriers to vaccination among individuals with relatively severe mental illness (e.g., attended by specialist care).\u003c/p\u003e \u003cp\u003eWe found no significant association between mental illness and COVID-19 vaccinion uptake in most of the COVIDMENT cohorts, and the absolute rate of vaccination in the included cohorts was generally high, both among individuals with and without mental illness. The slight differences across cohorts could have been, at least partially, due to the varying prioritisation schedules for COVID-19 vaccination used in the different countries. Although the European Union (EU) recommended that member states prioritise indivdiuals at the highest risk for severe COVID-19, countries could decide which population groups to include in their prioritisation schedules, meaning that not all countries prioritised vaccination for individuals with mental illness.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThere are many strengths of our study, which represents the first multinational study of the association between mental illness and COVID-19 vaccination uptake. The complementary use of the two different types of prospectively collected data sources combined the benefits of the rich self-reported COVIDMENT data with the Swedish national registers, which has minimal concerns of selection bias, thereby increasing the robustness of the study\u0026rsquo;s conclusions. By including a very large sample size from several different countries we were also able to investigate whether the results found in previous country-specific studies translated to an multinational context.\u003c/p\u003e \u003cp\u003eHowever, limitations of the study must also be noted. Although the multinational nature of the study increases the representativeness of the findings, all participating countries have established welfare systems and generally accessible healthcare, meaning caution should be taken when generalising the results to other global regions. There were also specific limitations relating to the two study populations, such as potential selection bias in the COVIDMENT cohorts, meaning individuals with severe mental illness were less likely to take part in the study.\u003c/p\u003e \u003cp\u003eIn conclusion, in this large, multinational study we showed that uptake of the COVID-19 vaccine was high, even among most individuals with a mental illness, highlighting the comprehensiveness and success of the COVID-19 vaccination campaign in reaching most population groups. However, specific groups of people with a recent specialist diagnosis of mental illness yet not on psychiatric medication, were still at risk for low vaccination uptake. These findings have important implications for the design of current and future vaccination campaigns against infectious diseases and future pandemics.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eData Sharing Statement\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;raw\u0026nbsp;data underlying this article were subject to ethical approval and cannot be shared publicly due to data protection laws in each participating country.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all of the participants who contributed data to the COVIDMENT project.\u0026nbsp;The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian\u0026nbsp;Ministry of Health and Care Services and the Ministry of Education and Research. We are\u0026nbsp;grateful to all the participating families in Norway who take part in this ongoing cohort\u0026nbsp;study.\u0026nbsp;We would also like to acknowledge the work of the\u0026nbsp;Estonian Biobank Research Team.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthor Contributions\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe participating COVIDMENT cohorts and/or their data collections were designed by IM, AL, AKK, EEJ, AHo, SUJ, HA, DLM, OVE, KL, UAV, FF and their respective teams. HL and FN provided the registry-based data, server and software to conduct the analysis. MMB, FF and UAV directed the combined effort of this study implementation. MMB, EH, HL, UAV, FN and FF designed the analytical strategy in close collaboration with all team members and all authors helped to interpret the findings. MMB and GM conducted the literature review and MMB, KK, IM, HM, BW, and XD drafted the manuscript under supervision of UAV, FN, and FF. All authors revised the manuscript for critical content and approved the final version of the manuscript. MMB, GM and HL had access to and verified the data.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting Interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eEMF\u0026nbsp;received speaker’s honoraria from Astra Zeneca. OAA is a consultant for\u0026nbsp;Cortechs.ai, and received speaker’s honoraria from Janssen, Lundbeck, Sunovion, Otsuka. PFS is a shareholder and on the advisory committee of Neumora Therapeutics. FN owns some AstraZeneca shares.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from NordForsk (https://www.nordforsk.org) [COVIDMENT, grant numbers 105668 and 138929] and Horizon 2020 (https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-2020_en) [CoMorMent, 847776]. Estonian Biobank is supported by the European Union through the European Regional Development Fund\u0026nbsp;(https://ec.europa.eu/regional_policy/funding/erdf_en) [Project No. 2014-2020.4.01.15-0012]. KL and KK were supported by the Estonian Research Council\u0026nbsp;(https://etag.ee/en/) [grant PSG615] and Estonian sub-project of NordForsk project no. 105668. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates\u0026nbsp;(https://www.cso.scot.nhs.uk) [CZD/16/6] and the Scottish Funding Council\u0026nbsp;(https://www.sfc.ac.uk) [HR03006] and is currently supported by the Wellcome Trust (https://wellcome.org)\u0026nbsp;[216767/Z/19/Z]. Recruitment to the CovidLife study was facilitated by SHARE- the Scottish Health Research Register and Biobank\u0026nbsp;(https://www.registerforshare.org). SHARE is supported by NHS Research Scotland, the Universities of Scotland and the Chief Scientist Office of the Scottish Government. Omtanke2020 was supported by funding from the Swedish Research Council (https://www.vr.se/english.html) [D0886501]. SCIFI-PEARL has funding to support this study from the SciLifeLab National COVID-19 Research Program, financed by the Knut and Alice Wallenberg Foundation\u0026nbsp;(https://kaw.wallenberg.org/en) [grants KAW 2021-0010/VC2021.0018 and KAW 2020.0299/VC 2022.0008], and the Swedish Research Council (https://www.vr.se/english.html) [grants 2021-05045 and 2021-05450]. SCIFI-PEARL also has basic funding based on grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF agreement\u0026nbsp;(https://www.vr.se/english/mandates/clinical-research/clinical-research-in-the-alf-regions.html) [grants ALFGBG-938453, ALFGBG-971130, ALFGBG-978954] and from FORMAS (Research Council for Environment, Agricultural Sciences and Spatial Planning), a Swedish Research Council for Sustainable Development (https://formas.se/en/start-page.html) [grant 2020-02828]. OAA and BW were also supported by the Research Council of Norway (https://www.forskningsradet.no/en/) [#223273 and #324620, resepctively]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organisation. 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Serious Mental Illness Diagnosis and COVID-19 Vaccine Uptake in the Veterans Health Administration. Psychiatric Services. 2022:appi. ps. 202100499.\u003c/li\u003e\n \u003cli\u003eMurphy S, O\u0026apos;Reilly D, Owen RK, Akbari A, Lowthian E, Bedston S, et al. Variations in COVID-19 vaccination uptake among people in receipt of psychotropic drugs: cross-sectional analysis of a national population-based prospective cohort. The British Journal of Psychiatry. 2022:1-8.\u003c/li\u003e\n \u003cli\u003ePisl V, Vevera J. COVID-19 vaccine uptake in mental healthcare users: Czech nationwide register study. Vaccine. 2023;41(37):5435-40.\u003c/li\u003e\n \u003cli\u003eLee D-W, Bae YS, Lee J-R, Sohn JH, Lee H, Lee JY. COVID-19 vaccination, incidence, and mortality rates among individuals with mental disorders in South Korea: A nationwide retrospective study. Asian journal of psychiatry. 2023;85:103600.\u003c/li\u003e\n \u003cli\u003eUnnarsd\u0026oacute;ttir AB, Lovik A, Fawns-Ritchie C, Ask H, K\u0026otilde;iv K, Hagen K, et al. Cohort Profile: COVIDMENT: COVID-19 cohorts on mental health across six nations. International journal of epidemiology. 2022;51(3):e108-e22.\u003c/li\u003e\n \u003cli\u003eMagnus P, Birke C, Vejrup K, Haugan A, Alsaker E, Daltveit AK, et al. Cohort profile update: the Norwegian mother and child cohort study (MoBa). International journal of epidemiology. 2016;45(2):382-8.\u003c/li\u003e\n \u003cli\u003eSpitzer RL, Kroenke K, Williams JB, L\u0026ouml;we B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine. 2006;166(10):1092-7.\u003c/li\u003e\n \u003cli\u003eKroenke K, Spitzer RL, Williams JB. The PHQ‐9: validity of a brief depression severity measure. Journal of general internal medicine. 2001;16(9):606-13.\u003c/li\u003e\n \u003cli\u003eAluoja A, Shlik J, Vasar V, Luuk K, Leinsalu M. Development and psychometric properties of the Emotional State Questionnaire, a self-report questionnaire for depression and anxiety. Nordic Journal of Psychiatry. 1999;53(6):443-9.\u003c/li\u003e\n \u003cli\u003eEuropean Medicines Agency. EMA recommends COVID-19 Vaccine Janssen for authorisation in the EU 2021 [Available from: https://www.ema.europa.eu/en/news/ema-recommends-covid-19-vaccine-janssen-authorisation-eu.\u003c/li\u003e\n \u003cli\u003eViechtbauer W. Conducting meta-analyses in R with the metafor package. Journal of statistical software. 2010;36:1-48.\u003c/li\u003e\n \u003cli\u003eNyberg F, Franz\u0026eacute;n S, Lindh M, Vanfleteren L, Hammar N, Wettermark B, et al. Swedish Covid-19 investigation for future insights\u0026ndash;a population epidemiology approach using register linkage (SCIFI-PEARL). Clinical Epidemiology. 2021:649-59.\u003c/li\u003e\n \u003cli\u003eKrisinformation.se. Covid-19 vaccination begins on 27 December 2020 [Available from: https://www.krisinformation.se/en/news/2020/december/vaccination-27-december.\u003c/li\u003e\n \u003cli\u003eMoghadas SM, Vilches TN, Zhang K, Nourbakhsh S, Sah P, Fitzpatrick MC, et al. Evaluation of COVID-19 vaccination strategies with a delayed second dose. PLoS biology. 2021;19(4):e3001211.\u003c/li\u003e\n \u003cli\u003eQuan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. American journal of epidemiology. 2011;173(6):676-82.\u003c/li\u003e\n \u003cli\u003eLawrence D, Kisely S. Inequalities in healthcare provision for people with severe mental illness. Journal of psychopharmacology. 2010;24(4_suppl):61-8.\u003c/li\u003e\n \u003cli\u003eMiles LW, Williams N, Luthy KE, Eden L. Adult vaccination rates in the mentally ill population: an outpatient improvement project. Journal of the American Psychiatric Nurses Association. 2020;26(2):172-80.\u003c/li\u003e\n \u003cli\u003eLim C, Van Alphen MU, Maclaurin S, Mulligan C, Macri B, Cather C, et al. Increasing COVID-19 vaccination rates among patients with serious mental illness: a pilot intervention study. Psychiatric Services. 2022;73(11):1274-7.\u003c/li\u003e\n \u003cli\u003eDe Picker LJ, Dias MC, Benros ME, Vai B, Branchi I, Benedetti F, et al. Severe mental illness and European COVID-19 vaccination strategies. The Lancet Psychiatry. 2021;8(5):356-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4075473/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4075473/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Individuals with mental illness are at higher risk of severe COVID-19 outcomes. However, previous studies on the uptake of COVID-19 vaccination in this population have reported conflicting results. Therefore, we aimed to investigate the association between mental illness and COVID-19 vaccination uptake, using data from five countries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data from seven cohort studies (N=325,298), and the Swedish registers (8,080,234), were used to identify mental illness and COVID-19 vaccination uptake. Multivariable modified Poisson regression models were conducted to calculate the prevalence ratio (PR) and 95% CIs of vaccination uptake among individuals with v.s. without mental illness. Results from the cohort studies were pooled using random effects meta-analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings:\u003c/strong\u003e Most of the meta-analyses performed using the COVIDMENT study population showed no significant association between mental illness and vaccination uptake. In the Swedish register study population, we observed a very small reduction in the uptake of both the first (prevalence ratio [PR]: 0.98, 95% CI: 0.98-0.99, p\u0026lt;0.001) and second dose among individuals with mental illness; the reduction was however greater among those not using pyschiatric medication (PR: 0.91, 95% CI: 0.91-0.91, p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e The high uptake of COVID-19 vaccination observed among individuals with most types of mental illness highlights the comprehensiveness of the vaccination campaign , however lower levels of vaccination uptake among subgroups of individuals with unmedicated mental illness warrants attention in future vaccination campaigns.\u003c/p\u003e","manuscriptTitle":"Mental illness and COVID-19 vaccination: a multinational investigation of observational \u0026amp; register-based data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-14 18:32:51","doi":"10.21203/rs.3.rs-4075473/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"65f4712d-eeb4-43b9-91b9-b460170f631e","owner":[],"postedDate":"March 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":29411154,"name":"Health sciences/Diseases/Psychiatric disorders"},{"id":29411155,"name":"Health sciences/Health care/Disease prevention/Preventive medicine"},{"id":29411156,"name":"Health sciences/Health care/Public health/Epidemiology"}],"tags":[],"updatedAt":"2024-09-27T07:06:06+00:00","versionOfRecord":{"articleIdentity":"rs-4075473","link":"https://doi.org/10.1038/s41467-024-52342-1","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2024-09-26 04:00:00","publishedOnDateReadable":"September 26th, 2024"},"versionCreatedAt":"2024-03-14 18:32:51","video":"","vorDoi":"10.1038/s41467-024-52342-1","vorDoiUrl":"https://doi.org/10.1038/s41467-024-52342-1","workflowStages":[]},"version":"v1","identity":"rs-4075473","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4075473","identity":"rs-4075473","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}