Open access Original research Impact of the COVID-­19 pandemic on diagnoses of common mental health disorders in adults in Catalonia, Spain: a population-­based cohort study Berta Raventós ‍ ‍,1,2 Andrea Pistillo,1 Carlen Reyes ‍ ‍,1 Sergio Fernández-­Bertolín,1 Maria Aragón,1 Anna Berenguera ‍ ‍,1,2 Constanza Jacques-­Aviñó,1,2 Laura Medina-­Perucha ‍ ‍,1,2 Edward Burn ‍ ‍,1,3 Talita Duarte-­Salles ‍ ‍1 To cite: Raventós B, Pistillo A, ABSTRACT Reyes C, et al. Impact of Strengths and limitations of this study Objective To investigate how trends in incidence of the COVID-­19 pandemic on anxiety and depressive disorders have been affected by ► This study was based on primary care data of 3.6 diagnoses of common mental the COVID-­19 pandemic. million people in Catalonia, Spain. health disorders in adults in Catalonia, Spain: a population-­ Design Population-­based cohort study. ► This study has quantified the impact of the COVID-­19 based cohort study. BMJ Open Setting Retrospective cohort study from 2018 to 2021 pandemic on trends in incidence of anxiety and de- 2022;12:e057866. doi:10.1136/ using the Information System for Research in Primary Care pressive disorders among adults living in Catalonia, bmjopen-2021-057866 (SIDIAP) database in Catalonia, Spain. Spain and how it differs by sex, age and socioeco- ► Prepublication history and Participants 3 640 204 individuals aged 18 or older in nomic status. additional supplemental material SIDIAP on 1 March 2018 with no history of anxiety and ► Forecasted rates were estimated based on data from for this paper are available depressive disorders. 2 years and we validated our modelling approach in online. To view these files, Primary and secondary outcomes measures The the year prior to the COVID-­19 pandemic. please visit the journal online incidence of anxiety and depressive disorders during ► Our analysis investigates the COVID-­ 19-­ related (http://dx.doi.org/10.1136/​ the prelockdown period (March 2018–February 2020), effects up to March 2021, providing data up to a bmjopen-2021-057866). lockdown period (March–June 2020) and postlockdown year after the onset of the lockdown measures in EB and TD-­S are joint senior period (July 2020–March 2021) was calculated. Catalonia. authors. Forecasted rates over the COVID-­19 periods were estimated using negative binomial regression models Received 29 September 2021 based on prelockdown data. The percentage of reduction Accepted 10 March 2022 INTRODUCTION was estimated by comparing forecasted versus observed The outbreak of the COVID-­19 pandemic and events, overall and by sex, age and socioeconomic the associated control measures have impacted status. many aspects of people’s lives. In Spain, a Results The incidence rates per 100 000 person-­months of anxiety and depressive disorders were 151.1 (95% national lockdown was implemented on 14 CI 150.3 to 152.0) and 32.3 (31.9 to 32.6), respectively, March 2020, limiting mobility with few excep- during the prelockdown period. We observed an increase tions such as grocery shopping, health emer- of 37.1% (95% prediction interval 25.5 to 50.2) in incident gencies or essential work.1 The restrictions were anxiety diagnoses compared with the expected in March gradually lifted following different de-­escalation 2020, followed by a reduction of 15.8% (7.3 to 23.5) phases, which ended on 21 June 2020, when the during the postlockdown period. A reduction in incident so-­ called ‘new normality’ was re-­ established.2 depressive disorders occurred during the lockdown and Due to a resurgence of COVID-­19 infections, postlockdown periods (45.6% (39.2 to 51.0) and 22.0% new nationwide measures were implemented © Author(s) (or their (12.6 to 30.1), respectively). Reductions were higher on 25 October 2020, including mobility restric- employer(s)) 2022. Re-­use among women during the lockdown period, adults aged tions and curfew hours, which were extended permitted under CC BY-­NC. No 18–34 years and individuals living in the most deprived up to 9 May 2021.3 commercial re-­use. See rights and permissions. Published by areas. Studies based on self-­reported surveys have BMJ. Conclusions The COVID-­19 pandemic in Catalonia was provided evidence of elevated rates of anxiety, For numbered affiliations see associated with an initial increase in anxiety disorders depression and stress in the initial stages of the diagnosed in primary care but a reduction in cases end of article. pandemic.4–7 In Catalonia (a northern region as the pandemic continued. Diagnoses of depressive Correspondence to in Spain), self-­ reported surveys performed disorders were lower than expected throughout the Dr Talita Duarte-­Salles; in April–May 2020 found increased levels of pandemic. ​tduarte@​idiapjgol.​org anxiety and depression during the COVID-­19 Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 1 Open access lockdown, especially among women and young adults.8 9 geography, age and sex distributions.15 The database has Conversely, healthcare contacts related to mental condi- been mapped to the Observational Medical Outcomes tions substantially reduced in primary care, emergency Partnership Common Data Model.16 departments and hospital settings after the lockdown All individuals aged 18 or older registered in the SIDIAP announcement in March 2020.10 A discrepancy between on 1 March 2018 were identified. Individuals with less increasing levels of mental health disorders and reduc- than 1 year of history available were excluded so that the tions in primary care diagnoses during the COVID-­19 study participants had sufficient prior observation time to pandemic may well result in a substantial burden of ill detect incident cases of anxiety and depressive disorders. health, as long delays in diagnosis are associated with Individuals with episodes of anxiety or depressive disor- negative health outcomes among adults with mood and/ ders prior to index date (ie, date of start of the cohort) or anxiety disorders.11 12 were excluded. Individuals were observed until the event To date, most evidence regarding the mental health of interest, until they were transferred or died, or until impact of COVID-­ 19 is from self-­ reported surveys the end of the study period. performed during the initial stages of the pandemic. We do not know yet whether the survey results are mirrored Variables in the rates of recorded incident diagnoses of common Individuals’ age and sex were extracted. Information on mental disorders in primary care and how they have socioeconomic status (SES) was available through the evolved during the pandemic in Catalonia. The effects Mortalidad en áreas pequeñas Españolas y Desigualdades of the pandemic on mental health and well-­being may Socioeconómicas y Ambientales (MEDEA) Deprivation well persist beyond lockdown measures, causing a long-­ Index, linked to each residential census area of the popu- term upsurge in number and severity of mental health lation.17 The deprivation index was only available for problems as the pandemic continues.13 14 In this study, we urban areas, defined as municipalities with more than aim to investigate how trends in incidence of anxiety and 10 000 inhabitants and a population density greater than depressive disorders have been affected by the various 150 habitants/km2; the remaining areas were considered stages of the COVID-­19 pandemic 1 year after the onset rural areas. The deprivation index is categorised in quin- of lockdown measures through analysis of a large primary tiles, in which the first and fifth quintiles are the least and care longitudinal dataset representative of the population most deprived, respectively. living in Catalonia, Spain. The outcome of the study was the incidence of anxiety or depressive disorders. Conditions were identified on the basis of the International Statistical Classification of Diseases and METHODS Related Health Problems, Tenth Revision, Clinical Modifica- Study design tion (ICD-­10-­CM) codes of interest. The ICD-­10-­CM codes We conducted a cohort study based on primary care records included for depressive disorders were F32 (major depres- from 1 March 2018 to 31 March 2021 in Catalonia, Spain. sive disorder, single episode) and F33 (major depressive Time trends were assessed in three different periods: (1) disorder, recurrent). All descendants were included except the prelockdown period, from 1 March 2018 to 29 February for the ones referring to episodes in partial or complete 2020; (2) the lockdown period, from 1 March 2020 to 30 June remission (F32.4, F32.5 and F33.4). For anxiety disorder, 2020; and (3) the postlockdown period, from 1 July 2020 the F41 (other anxiety disorders) code and all its descen- to 31 March 2021. The postlockdown period was divided dants were included. Detailed data of the ICD-­10-­CM codes into three trimesters, which were broadly aligned with the included for each outcome are described in online supple- different stages of the pandemic in Catalonia: (1) easing mental table 1. of restrictions from 1 July 2020 to 30 September 2020; (2) implementation of new control measures from 1 October Statistical methods 2020 to 31 December 2020; and (3) extension of control We summarised the sociodemographic characteristics measures and start of the vaccination campaign from 1 of the individuals included in the study, with counts and January 2021 to 31 March 2021. Of note, we only considered percentages for categorical variables and median and the first wave of the pandemic as the lockdown period, as it interquartile range (IQR) for continuous variables. We was the only wave in which a stay-­at-­home order was issued. structured the data in a monthly time-­series format with Various restrictions continued to be imposed following this incident and person-­months at risk aggregated with strat- initial, strict lockdown. ification by sex (men and women), age group (18–34, 35–64, >65 years) and SES (quintiles of MEDEA Depri- Study participants, setting and data source vation Index). Incidence rates with 95% CI were calcu- We used individual-­ level data from the Information lated for each month and study period by dividing the System for Research in Primary Care (SIDIAP; www.sidiap.​ number of first recorded cases of anxiety and depression org) database, which is comprised of pseudo-­anonymised by 100 000 person-­months at risk, overall and stratified by electronic health records from approximately 80% of the sex, age group and SES. Incidence rate ratios (IRR) with population living in Catalonia. SIDIAP has been shown to 95% CI were calculated to compare the differences in be representative of the Catalan population in terms of the incidence of each strata of the population during the 2 Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 Open access lockdown and postlockdown periods compared with the corresponding periods from March 2018 to March 2019. We used negative binomial regression models to esti- mate the expected monthly incident cases from March 2020 to March 2021 using data collected in the prelock- down period. To account for possible seasonality and linear trends, we fitted calendar month as a categorical variable and time as a continuous variable. The number of months since the start of the study was considered as the unit of measurement for time. The estimated number of underdiagnoses was calcu- lated by subtracting the number of observed from the expected diagnoses. Reduction in diagnoses was calcu- lated by dividing the number of underdiagnoses by the expected diagnoses and was estimated monthly and by study period (lockdown and postlockdown, overall and divided by trimesters). Reduction in diagnoses is Figure 1 Expected and observed incidence rates of (A) anxiety and (B) depressive disorders in primary care in expressed as percentage with 95% prediction interval Catalonia (March 2018–March 2021). Points indicate monthly (PI),18 as previously reported in a similar study.19 incidence rates of anxiety and depressive disorders. The For each month during the COVID-­19 study period, number of expected cases (95% PI) was estimated with observed and expected incident counts were converted to negative binomial models using data from 1 March 2018 to rates using the observed person-­month denominator. We 29 February 2020. Shaded areas in blue represent 95% PI. plotted monthly expected rates and the corresponding The vertical lines show 1 March 2020. PI, prediction interval. 95% PI against the observed rates. To validate our modelling approach, we developed a nega- disorders was 151.1 (95% CI 150.3 to 152.0) and 32.3 (31.9 tive binomial model based on 2 years of history (from March to 32.6), respectively. During the lockdown period, the 2017 to February 2019). We forecasted our expected values incidence rate of anxiety disorders increased up to 183.3 from March 2019 to February 2020, and checked if the per 100 000 person-­months (181.0 to 185.6), whereas the values predicted from the model fell within the calculated rate of depressive disorders sharply decreased to 21.1 per 95% PI. We validated our approach for overall diagnoses and 100 000 person-­months (20.4 to 21.9). The incidence rate stratified by sex, age group and SES. of anxiety disorders substantially reduced from July to The SIDIAP version used for this analysis was from 15 September 2020 (127.6 per 100 000 person-­months (125.4 June 2021. All analyses were performed in R V.4.0.4. to 129.9)), but subsequently increased and exceeded the figures observed before the pandemic during the Patient and public involvement first trimester of 2021 (162.3 per 100 000 person-­months This research was done without patient involvement. (159.7 to 164.9)). Quarterly incidence rates (consisting Patients were not invited to comment on the study of intervals of 3 months) of depressive disorders progres- design and were not consulted to develop patient rele- sively recovered after the lockdown period and achieved vant outcomes or interpret the results. Patients were not the observed figures prior to the pandemic during the invited to contribute to the writing or editing of this docu- first trimester of 2021 (33.2 per 100 000 person-­months ment for readability or accuracy. (32.1 to 34.4)) (figure 1). To note, some data on quarterly incidence rates have been omitted in order to ensure the RESULTS readability of the manuscript. Detailed data of incidence There were 5 811 652 adults registered in our data set on rates overall and stratified by sex, age group, and SES over 1 March 2018 who were eligible to enter the study. We the study periods are included in online supplemental excluded 1 044 705 due to not being 18 years old; 87 740 tables 3–8. due to having less than a year of clinical history; and The IRRs comparing the differences in incidence of 1 039 003 due to history of anxiety or depression disorders each strata of the population during the lockdown and (online supplemental figure 1). We included 3 640 204 postlockdown periods compared with the corresponding individuals, of whom 1 709 659 (47.0%) were women. periods in 2018 and 2019 are shown in table 1. The IRRs The median age of the individuals on the index date was of anxiety disorders were significantly higher during the 47 years (IQR 35–63). A total of 310 546 (8.5%) individ- lockdown period for all age groups and deprivation quin- uals were lost to follow-­up at the end of the study period. tiles (ie, IRR range from 1.06 (1.01 to 1.11) to 1.38 (1.27 Detailed demographic data of the study population are to 1.49) across sex and age groups) but reduced during included in online supplemental table 2. the following trimester (ie, IRR range from 0.87 (0.78 to Incidence trends 0.97) to 0.97 (0.91 to 1.04) across sex and age groups). During the prelockdown period, the overall incidence The incidence rates during the three trimesters of the rate per 100 000 person-­months of anxiety or depressive postlockdown period were similar to those observed in Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 3 4 Table 1 Incidence rate ratios of the first recorded cases of anxiety and depressive disorders stratified by sex, age group, and MEDEA Deprivation Index according to the study period Open access Incidence rate ratio (95% CI) for each time period Anxiety disorders (n=196 933)* Depressive disorders (n=40 020)* Postlockdown period Postlockdown period Postlockdown period Postlockdown period Postlockdown period Postlockdown period Lockdown period 1 (July–September 2 (October–December 3 (January–March Lockdown period 1 (July–September 2 (October–December 3 (January–March (March–June 2020) 2020) 2020) 2021) (March–June 2020) 2020) 2020) 2021) Overall 1.19 (1.17 to 1.22) 0.94 (0.92 to 0.96) 1.00 (0.98 to 1.03) 1.00 (0.98 to 1.03) 0.64 (0.61 to 0.67) 0.94 (0.89 to 0.99) 0.95 (0.90 to 1.00) 0.97 (0.93 to 1.02) Sex  Women 1.17 (1.14 to 1.20) 0.95 (0.92 to 0.97) 1.05 (1.02 to 1.08) 1.01 (0.98 to 1.04) 0.64 (0.61 to 0.68) 0.91 (0.85 to 0.97) 0.97 (0.91 to 1.04) 0.95 (0.89 to 1.01)  Men 1.24 (1.20 to 1.27) 0.94 (0.90 to 0.97) 0.94 (0.91 to 0.98) 1.00 (0.96 to 1.03) 0.64 (0.59 to 0.69) 1.00 (0.92 to 1.08) 0.92 (0.84 to 1.00) 1.01 (0.93 to 1.09) Sex: women Age group (years)  18–34 1.06 (1.01 to 1.11) 0.94 (0.89 to 1.00) 1.14 (1.08 to 1.20) 1.14 (1.08 to 1.19) 0.60 (0.51 to 0.71) 1.01 (0.84 to 1.21) 1.17 (0.99 to 1.38) 1.12 (0.96 to 1.31)  35–64 1.25 (1.21 to 1.29) 0.95 (0.91 to 0.99) 1.02 (0.98 to 1.07) 0.97 (0.93 to 1.00) 0.70 (0.64 to 0.76) 0.93 (0.84 to 1.02) 0.99 (0.90 to 1.09) 0.92 (0.85 to 1.01)  >65 1.10 (1.04 to 1.17) 0.94 (0.87 to 1.01) 0.97 (0.91 to 1.04) 0.94 (0.88 to 1.01) 0.61 (0.56 to 0.67) 0.88 (0.79 to 0.97) 0.90 (0.81 to 0.99) 0.94 (0.85 to 1.03) Sex: men Age group (years)  18–34 1.12 (1.06 to 1.18) 0.97 (0.91 to 1.04) 0.99 (0.92 to 1.06) 1.07 (1.00 to 1.14) 0.58 (0.47 to 0.71) 1.00 (0.81 to 1.23) 0.99 (0.81 to 1.22) 1.09 (0.90 to 1.30)  35–64 1.27 (1.22 to 1.32) 0.93 (0.88 to 0.97) 0.92 (0.88 to 0.97) 0.98 (0.94 to 1.03) 0.64 (0.57 to 0.71) 0.94 (0.83 to 1.06) 0.89 (0.80 to 1.01) 1.03 (0.93 to 1.15)  >65 1.38 (1.27 to 1.49) 0.87 (0.78 to 0.97) 0.90 (0.81 to 1.00) 0.85 (0.76 to 0.94) 0.69 (0.61 to 0.78) 1.11 (0.96 to 1.27) 0.95 (0.82 to 1.09) 0.95 (0.83 to 1.10) MEDEA Deprivation Index  First, least 1.11 (1.05 to 1.16) 0.94 (0.88 to 1.01) 1.04 (0.98 to 1.11) 0.94 (0.89 to 1.00) 0.70 (0.62 to 0.79) 0.94 (0.81 to 1.08) 0.88 (0.76 to 1.00) 1.07 (0.94 to 1.22) deprived  Second 1.22 (1.17 to 1.28) 0.90 (0.84 to 0.95) 0.96 (0.90 to 1.02) 1.00 (0.95 to 1.06) 0.65 (0.57 to 0.73) 0.94 (0.81 to 1.08) 0.99 (0.86 to 1.13) 0.92 (0.81 to 1.04)  Third 1.19 (1.14 to 1.25) 0.94 (0.88 to 1.00) 1.00 (0.94 to 1.06) 0.96 (0.91 to 1.02) 0.67 (0.59 to 0.75) 0.89 (0.77 to 1.02) 1.05 (0.92 to 1.21) 0.97 (0.85 to 1.10)  Fourth 1.21 (1.15 to 1.27) 0.93 (0.87 to 0.99) 0.96 (0.91 to 1.02) 0.98 (0.92 to 1.04) 0.64 (0.56 to 0.72) 1.04 (0.91 to 1.20) 1.10 (0.96 to 1.26) 1.05 (0.92 to 1.19)  Fifth, most 1.19 (1.14 to 1.25) 0.90 (0.85 to 0.96) 0.95 (0.90 to 1.02) 1.01 (0.96 to 1.07) 0.55 (0.48 to 0.62) 1.01 (0.88 to 1.17) 0.90 (0.79 to 1.03) 0.97 (0.85 to 1.10) deprived  Rural 1.18 (1.13 to 1.24) 0.96 (0.90 to 1.02) 1.03 (0.97 to 1.09) 1.03 (0.98 to 1.09) 0.73 (0.65 to 0.81) 1.02 (0.91 to 1.16) 0.98 (0.86 to 1.11) 1.06 (0.94 to 1.19) Incidence rate ratios were calculated by dividing the incidence rate obtained for each strata during the COVID-­19 periods (lockdown and postlockdown periods) by the incidence rate obtained for the same time period in 2018 and 2019. The MEDEA Deprivation Index is calculated at the census tract level in the urban areas of Catalonia and categorised in quintiles of deprivation. *Total number of diagnoses from March 2018 to March 2021. MEDEA, Mortalidad en áreas pequeñas Españolas y Desigualdades Socioeconómicas y Ambientales. Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 Open access the corresponding periods in 2018 and 2019 for all strata, years had greater reductions in incident diagnoses of with a few exceptions. Women aged 18–34 years obtained both outcomes during the lockdown and postlockdown a significantly higher IRR during the last trimester of periods, except for reductions during the first trimester 2020 (1.14 (1.08 to 1.20)), whereas both women and men of 2021, which were higher among men aged 65 years of the same age group obtained significantly higher IRRs or above. In terms of sex, women accounted for higher from January to March 2021 compared with the corre- reductions in diagnoses of anxiety (during the lockdown sponding period in 2019 (1.14 (1.08 to 1.19) and 1.07 period) and depressive disorders (during the lockdown (1.00 to 1.14), respectively). Significant reductions in the and postlockdown periods). For SES, we found a gradient diagnosis of depressive disorders were found for all strata in the incidence of anxiety disorders in March 2020, from during the lockdown period (ie, IRR range from 0.58 low to high between the less and fourth most deprived (0.47 to 0.71) to 0.70 (0.64 to 0.76) across sex and age urban areas (figure 3A). Conversely, most deprived urban groups). These reductions were particularly pronounced areas accounted for higher reductions in anxiety disor- among individuals aged 65 years or above (0.61 (0.56 ders compared with the least deprived during the post- to 0.67) in women and 0.69 (0.61 to 0.78) in men) and lockdown period. Reductions in depressive disorders were those living in the most deprived urban areas (0.55 (0.48 higher among the most deprived urban areas compared to 0.62)). The IRRs of depressive disorders increased with the least deprived ones in April 2020 (figure 3B) and during the following trimester and suggested no differ- during the lockdown period, but obtained similar values ence in risk from October 2020 to March 2021 compared during the postlockdown period. Rural areas mostly with the corresponding period in 2018 and 2019. accounted for lower reductions in diagnoses compared with urban areas. Reductions in diagnoses of anxiety and Estimates of new diagnoses (March 2020–March 2021) depressive disorders decreased during the first quarter of Incident diagnoses of anxiety disorders showed a sudden 2021 compared with the first trimester after the lockdown peak at the onset of the lockdown measures in Catalonia overall and stratified by sex, age group and SES, except and accounted for an increase of 37.1% (95% PI 25.5 for men aged 65 or above (table 2). to 50.2) new diagnoses compared with the expected in Our validation approach obtained consistent perfor- March 2020 (figure 1A). However, the gap between the mances overall and stratified by sex, age group and SES. observed and the expected anxiety diagnoses during the Figures of monthly observed expected incidence rates and lockdown period was not statistically significant (−2.5 the corresponding 95% PI from March 2017 to February (95% PI −12.5 to 6.9)). Conversely, a decrease of 19.3% 2020 are included in online supplemental figures 2–4. (11.4 to 26.3) compared with the expected was found from July to September 2020. The reduction in incident cases was progressively recovered during the following DISCUSSION two trimesters and accounted for a reduction of 15.8% In this large population-­based cohort study, we observed (7.3 to 23.5) during the postlockdown period (table 2). large variations in the incidence of anxiety and depres- New cases of depressive disorders substantially reduced sive disorders diagnosed in primary care in Catalonia by compared with the expected at the onset of the lockdown the different periods of the COVID-­19 pandemic. The measures, accounting for a reduction of 65.8% (95% PI incidence of anxiety disorders showed a sudden peak 61.7 to 69.3) compared with the expected in April 2020 compared with the expected rates in March 2020 and (figure 2B). Overall monthly incidence rates remained was followed by a reduction in diagnoses during the next under the 95% PI from March 2020 to February 2021 months. Conversely, the incidence of depressive disorders (figure 1B). We estimated that the difference between sharply decreased, reaching its minimum value in April the expected and the observed diagnoses accounted for 2020. Based on the observed data, the incidence of both a reduction of 45.6% (39.2 to 51.0) during the lockdown disorders seemed to reach prelockdown levels in the first period compared with the expected. This reduction quarter of 2021. According to our model, which captures substantially decreased to 23.8% (14.5 to 31.5) from July the underlying upward trend of diagnoses over time, the 2020 to September 2020 and progressively diminished incidence of anxiety and depressive disorders did not during the following two trimesters (table 2). Consid- fully reach what would have been expected. Although the ering the three trimesters combined, the overall reduc- negative impact on the incidence of anxiety and depres- tion of incident cases of the postlockdown period was sive disorders appeared to occur across all sex, age groups 22.0% (12.6 to 30.1). and SES, this was mostly pronounced among women, Patterns in anxiety and depressive disorders during young adults and individuals living in the most deprived the pandemic differ between demographic groups urban areas. (table 2). The peak of diagnoses of anxiety disorders in Similar studies performed in the UK have used the March 2020 was particularly pronounced among indi- same modelling approach to forecast the incidence of viduals aged 35–64 years and men aged 18–34 years anxiety and depressive disorders during lockdown and (figure 2A). Conversely, adults aged 65 or above had the the first months of its aftermath.19 Carr et al20 found largest absolute decrease in diagnoses of depressive disor- that, compared with the expected rates, the incidence of ders in April 2020 (figure 2B). Individuals aged 18–34 primary care-­recorded depression and anxiety disorders Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 5 6 Table 2 Estimated number of underdiagnosed anxiety and depressive disorders based on prelockdown data and percentage of reduction compared with expected, by lockdown and postlockdown period Lockdown period Postlockdown period (by trimesters) Postlockdown period (overall) March–June 2020 July–September 2020 October–December 2020 January–March 2021 July 2020–March 2021 Estimated Estimated Open access number of Reduction in number of Reduction in Estimated number of Reduction in Estimated number of Reduction in Estimated number of Reduction in underdiagnoses, cases*, % underdiagnoses, cases, % underdiagnoses, n cases, % underdiagnoses, n cases, % underdiagnoses, n cases, % n (95% PI) (95% PI) n (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) Anxiety disorders Overall −586 (−2690 to −2.5 (−12.5 to 6.9) 2987 (1604 to 19.3 (11.4 to 2552 (1141 to 4102) 16.2 (8.0 to 2148 (485 to 3976) 12.4 (3.1 to 7688 (3230 to 12547) 15.8 (7.3 to 23.5) 1783) 4469) 26.3) 23.7) 20.8) Sex  Women 212 (−1413 to 1.4 (−10.8 to 12.0) 1890 (816 to 3058) 19.9 (9.7 to 1414 (312 to 2637) 14.4 (3.6 to 1380 (110 to 2762) 12.8 (1.2 to 4684 (1238 to 8457) 15.5 (4.6 to 24.9) 1983) 28.6) 23.9) 22.7)  Men −771 (−1727 to −8.7 (−21.7 to 2.4) 1146 (487 to 1858) 19.0 (9.1 to 1156 (500 to 1853) 19.4 (9.4 to 807 (69 to 1599) 12.3 (1.2 to 3108 (1056 to 5310) 16.8 (6.4 to 25.6) 233) 27.5) 27.9) 21.8) Sex: women Age group (years)  18–34 895 (405 to 1420) 19.7 (10.0 to 28.0) 855 (510 to 1231) 26.5 (17.7 to 479 (148 to 839) 15.6 (5.4 to 390 (2 to 804) 11.5 (0.1 to 1723 (660 to 2874) 17.8 (7.7 to 26.5) 34.2) 24.5) 21.1)  35–64 −497 (−1354 to −6.3 (−19.2 to 5.1) 874 (336 to 1463) 18.2 (7.9 to 816 (240 to 1466) 15.6 (5.2 to 872 (203 to 1612) 15.0 (3.9 to 2563 (779 to 4541) 16.2 (5.5 to 25.4) 451) 27.1) 25.0) 24.5)  >65 −186 (−464 to 112) −8.2 (−23.5 to 4.4) 161 (−30 to 364) 10.9 (−2.3 to 119 (−76 to 332) 7.7 (−5.7 to 118 (−95 to 346) 7.5 (−7.0 to 398 (−201 to 1042) 8.7 (−5.0 to 19.9) 21.7) 18.9) 19.3) Sex: men Age group (years)  18–34 337 (−10 to 698) 11.3 (−0.4 to 20.9) 552 (304 to 823) 25.2 (15.7 to 506 (266 to 758) 25.1 (15.0 to 350 (77 to 641) 15.9 (4.0 to 1408 (647 to 2222) 22.0 (11.5 to 30.8) 33.4) 33.5) 25.7)  35–64 −783 (−1229 to −15.8 (−27.3 to 476 (183 to 791) 15.1 (6.4 to 535 (232 to 855) 16.5 (7.9 to 322 (−17 to 689) 8.9 (−0.5 to 1332 (398 to 2335) 13.3 (4.4 to 21.2) −310) −5.7) 22.8) 23.9) 17.2)  >65 −325 (−488 to −33.1 (−59.6 to 118 (0 to 244) 17.1 (0.0 to 115 (2 to 240) 16.9 (0.4 to 135 (9 to 269) 18.6 (1.5 to 368 (11 to 753) 17.5 (0.6 to 30.3) −155) −13.5) 29.9) 29.7) 31.3) MEDEA Deprivation Index  First, least −53 (−405 to 345) −1.7 (−14.5 to 9.7) 272 (43 to 533) 13.9 (2.5 to 217 (−25 to 492) 10.3 (−1.3 to 287 (5 to 611) 12.2 (0.2 to 776 (23 to 1636) 12.1 (0.4 to 22.5) deprived 24.0) 20.6) 22.9)  Second −107 (−501 to 324) −3.1 (−16.1 to 8.2) 454 (194 to 738) 20.9 (10.1 to 433 (153 to 727) 17.9 (7.2 to 277 (−38 to 614) 10.6 (−1.7 to 1165 (309 to 2079) 16.2 (4.9 to 25.6) 30.0) 26.8) 20.9)  Third −191 (−619 to 260) −5.4 (−19.8 to 6.5) 484 (198 to 785) 20.4 (9.5 to 347 (67 to 646) 15.2 (3.3 to 417 (84 to 780) 15.7 (3.6 to 1248 (349 to 2211) 17.0 (5.4 to 26.7) 29.4) 25.0) 25.8)  Fourth −144 (−478 to 193) −3.9 (−14.4 to 4.8) 506 (282 to 741) 20.9 (12.8 to 452 (211 to 692) 18.1 (9.3 to 371 (113 to 644) 14.0 (4.7 to 1330 (606 to 2077) 17.5 (8.8 to 24.9) 27.9) 25.2) 22.0)  Fifth, most −81 (−444 to 287) −2.3 (−14.1 to 7.4) 533 (287 to 790) 22.5 (13.5 to 511 (269 to 760) 21.3 (12.5 to 361 (81 to 653) 13.7 (3.4 to 1405 (637 to 2203) 19.0 (9.6 to 26.9) deprived 30.1) 28.8) 22.3) Continued Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 Table 2 Continued Lockdown period Postlockdown period (by trimesters) Postlockdown period (overall) March–June 2020 July–September 2020 October–December 2020 January–March 2021 July 2020–March 2021 Estimated Estimated number of Reduction in number of Reduction in Estimated number of Reduction in Estimated number of Reduction in Estimated number of Reduction in underdiagnoses, cases*, % underdiagnoses, cases, % underdiagnoses, n cases, % underdiagnoses, n cases, % underdiagnoses, n cases, % n (95% PI) (95% PI) n (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI)  Rural −88 (−405 to 256) −2.5 (−12.5 to 6.6) 426 (197 to 676) 17.2 (8.8 to 351 (126 to 590) 14.6 (5.8 to 234 (−18 to 500) 8.9 (−0.8 to 1011 (305 to 1766) 13.5 (4.5 to 21.4) 24.8) 22.3) 17.3) Depressive disorders Overall 2419 (1856 to 45.6 (39.2 to 51.0) 821 (446 to 1209) 23.8 (14.5 to 832 (445 to 1247) 22.8 (13.6 to 804 (361 to 1281) 19.8 (10.0 to 2458 (1252 to 3737) 22.0 (12.6 to 30.1) 3002) 31.5) 30.7) 28.3) Sex  Women 1596 (1078 to 47.1 (37.6 to 54.7) 596 (239 to 986) 27.7 (13.3 to 559 (182 to 968) 23.8 (9.2 to 632 (206 to 1102) 24.1 (9.4 to 1788 (627 to 3056) 25.1 (10.5 to 36.4) 2165) 38.7) 35.0) 35.6)  Men 830 (442 to 1261) 43.2 (28.9 to 53.6) 227 (−41 to 526) 17.6 (−4.0 to 293 (18 to 600) 22.2 (1.7 to 205 (−99 to 554) 14.0 (−8.6 to 723 (−122 to 1680) 17.8 (−3.8 to 33.4) 33.0) 36.9) 30.6) Sex: women Age group (years)  18–34 332 (211 to 475) 61.5 (50.4 to 69.5) 115 (29 to 208) 34.1 (11.6 to 93 (0 to 199) 23.2 (0.0 to 121 (14 to 249) 26.9 (4.1 to 329 (43 to 656) 27.7 (4.8 to 43.3) 48.4) 39.3) 43.1) Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866  35–64 715 (499 to 942) 45.1 (36.4 to 52.0) 280 (136 to 437) 28.2 (16.0 to 271 (119 to 436) 24.4 (12.4 to 325 (148 to 516) 25.4 (13.4 to 877 (403 to 1389) 25.9 (13.9 to 35.7) 38.0) 34.2) 35.1)  >65 549 (368 to 748) 43.5 (34.1 to 51.2) 201 (74 to 341) 24.4 (10.6 to 195 (63 to 333) 23.2 (8.9 to 186 (44 to 337) 20.7 (5.8 to 582 (181 to 1011) 22.7 (8.4 to 33.8) 35.3) 34.0) 32.2) Sex: men Age group (years)  18–34 176 (85 to 286) 55.2 (37.3 to 66.7) 58 (−7 to 136) 25.1 (−4.2 to 60 (−7 to 140) 25.5 (−4.2 to 44 (−34 to 138) 15.7 (−17.0 to 161 (−48 to 414) 21.7 (−9.0 to 41.6) 44.2) 44.6) 37.1)  35–64 409 (244 to 583) 43.1 (31.1 to 51.9) 122 (12 to 243) 19.8 (2.4 to 164 (42 to 292) 24.0 (7.5 to 72 (−58 to 212) 9.9 (−9.8 to 357 (−4 to 747) 17.7 (−0.2 to 31.0) 33.0) 36.0) 24.6)  >65 245 (113 to 392) 37.6 (21.7 to 49.1) 47 (−46 to 147) 10.6 (−13.0 to 69 (−17 to 168) 17.1 (−5.4 to 89 (−7 to 204) 19.4 (−1.9 to 205 (−70 to 519) 15.7 (−6.8 to 32.0) 26.9) 33.5) 35.5) MEDEA Deprivation Index  First, least 315 (174 to 481) 42.0 (28.6 to 52.5) 134 (39 to 246) 27.8 (10.1 to 148 (43 to 266) 27.8 (10.0 to 103 (−15 to 242) 17.9 (−3.3 to 385 (67 to 754) 24.2 (5.3 to 38.4) deprived 41.4) 40.9) 33.8)  Second 391 (241 to 556) 49.2 (37.4 to 57.9) 157 (55 to 273) 30.3 (13.2 to 153 (46 to 275) 26.7 (9.9 to 175 (49 to 321) 27.2 (9.4 to 486 (150 to 869) 27.9 (10.7 to 41.0) 43.0) 39.5) 40.6)  Third 309 (166 to 465) 42.9 (28.8 to 53.1) 101 (7 to 206) 21.8 (1.9 to 60 (−34 to 166) 13.0 (−9.3 to 77 (−38 to 202) 14.1 (−8.8 to 237 (−65 to 574) 16.2 (−5.6 to 31.8) 36.3) 29.3) 30.1)  Fourth 376 (231 to 539) 49.9 (38.0 to 58.8) 107 (8 to 220) 22.2 (2.1 to 37) 113 (9 to 231) 21.3 (2.1 to 118 (4 to 255) 20.1 (0.8 to 338 (21 to 706) 21.1 (1.6 to 35.9) 35.6) 35.3)  Fifth, most 375 (204 to 575) 52.9 (37.9 to 63.3) 113 (0 to 247) 24.5 (0.0 to 137 (9 to 286) 26.0 (2.3 to 118 (−21 to 284) 21 (−5.0 to 367 (−12 to 817) 23.8 (−1.0 to 41.0) deprived 41.5) 42.4) 39.1) Open access Continued 7 8 Table 2 Continued Open access Lockdown period Postlockdown period (by trimesters) Postlockdown period (overall) March–June 2020 July–September 2020 October–December 2020 January–March 2021 July 2020–March 2021 Estimated Estimated number of Reduction in number of Reduction in Estimated number of Reduction in Estimated number of Reduction in Estimated number of Reduction in underdiagnoses, cases*, % underdiagnoses, cases, % underdiagnoses, n cases, % underdiagnoses, n cases, % underdiagnoses, n cases, % n (95% PI) (95% PI) n (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI) (95% PI)  Rural 347 (197 to 515) 39.7 (27.2 to 49.4) 94 (−14 to 212) 15.4 (−2.8 to 125 (17 to 244) 20.6 (3.4 to 76 (−44 to 215) 11.7 (−8.3 to 296 (−41 to 671) 15.8 (−2.7 to 29.9) 29.2) 33.6) 27.2) The estimated number of underdiagnoses was calculated by subtracting the observed diagnoses from the expected number of diagnoses (95% PI) estimated by negative binomial models. Reduction in diagnoses (95% PI) was calculated by dividing the number of underdiagnoses by the expected diagnoses and was estimated by study period (lockdown and postlockdown, overall and divided by trimesters). *Negative values indicate an increase in diagnoses. The MEDEA Deprivation Index is calculated at the census tract level in the urban areas of Catalonia and categorised in quintiles of deprivation. MEDEA, Mortalidad en áreas pequeñas Españolas y Desigualdades Socioeconómicas y Ambientales; PI, prediction interval. Rural; U, Urban. PI, prediction interval; Y, years. categorised in quintiles of deprivation. It also includes a March 2021). Points indicate monthly incidence rates of Figure 3 Expected and observed incidence rates of (A) Figure 2 Expected and observed incidence rates of (A) areas in blue represent 95% PI. The vertical lines show 1 the census tract level in the urban areas of Catalonia and anxiety and (B) depressive disorders stratified by MEDEA anxiety and (B) depressive disorders stratified by sex and rural category for individuals living in rural areas. MEDEA, from 1 March 2018 to 29 February 2020. Shaded areas in Socioeconómicas y Ambientales; PI, prediction interval; R, Mortalidad en áreas pequeñas Españolas y Desigualdades age group in primary care in Catalonia (March 2019–March anxiety and depressive disorders. The number of expected depressive disorders. The number of expected cases (95% March 2020. The MEDEA Deprivation Index is calculated at Deprivation Index in primary care in Catalonia (March 2019– PI) was estimated with negative binomial models using data using data from 1 March 2018 to 29 February 2020. Shaded 2021). Points indicate monthly incidence rates of anxiety and cases (95% PI) was estimated with negative binomial models blue represent 95% PI. The vertical lines show 1 March 2020. Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 Open access reduced by 43.0% (95% CI 38.3 to 47.4) and 47.8% COVID-­19 services, and health authorities advised against (44.3 to 51.2) in April 2020, respectively. In line with going to health centres except in the event of serious our findings, they found larger reductions among adults illness or urgent situations. Mental health services were aged 18–64 years old and among patients registered in also affected by the pandemic due to the relocation of more deprived areas. Indeed, a similar study performed healthcare professionals and temporary suspensions.23 in a UK deprived population found a 50.0% reduction Psychiatric inpatient units were largely reconverted to (95% CI 41.1 to 56.9) in the first diagnoses of common provide care to patients with COVID-­ 19, and outpa- mental health problems between March and May 2020.20 tient mental health visits were replaced by telephone Although reductions in diagnoses of depressive disorders consultations. Continuous dissemination of mass media reported in these studies are similar to those obtained messages reporting the strain on healthcare systems in our study, the initial decline in diagnoses seemed to might have influenced healthcare-­ seeking behaviours, be larger in our setting (45.6% (95% PI 39.2 to 51.0) as people might have delayed seeking care in order to during the lockdown period; 65.8% (61.7 to 69.1) in avoid overburdening the health systems or out of fear of April 2020). In contrast, none of these studies has found contracting the disease.24 In such an extraordinary situ- an increase in new cases of anxiety disorders at the ation, low perceived legitimacy of mental issues might onset of the pandemic. While the peak of anxiety disor- have also prevented those psychologically suffering to ders observed in our study overlaps with the reduction discern their emotional distress as an appropriate reason of healthcare contacts for the same disorders in March to seek care. In this line, we believe that a large number 2020,10 we cannot exclude the possibility that retrospec- of people experiencing psychological distress might have tive recording of diagnoses could have occurred once developed coping strategies without seeking help in the routine clinical practice was re-­established. In addition, public healthcare system. Prior evidence suggests that while Carr et al20 suggested that the incidence of mental clinicians perceive the emotional distress of their patients health illness had returned to expected rates in England but have difficulties in specifying standardised psychiatric by September 2020, the monthly incidence rates obtained diagnoses.25 26 Consultations with a recorded diagnosis of in our study remained under the 95% PI until February a psychological problem take longer27 and might require 2021. Although our study observed that the rates of reassessment of suspected cases to increase accuracy.28 It anxiety and depressive disorders were increasing during seems likely that the diagnoses detected in primary care the first trimester of 2021, it seems likely that the effects during the early months of the pandemic might account of the measures implemented to control the spread of the for more severe cases of mental health issues. In addition, pandemic in our setting are still negatively affecting the it is important to emphasise the increasing use of tele- diagnoses of these mental health conditions in primary medicine in Catalonia, where the share of telemedicine-­ care. based visits has increased to 56.2%, from 15.4% in the In Catalonia, two studies have found declines in new prepandemic year. While telemedicine has ensured the all-­cause diagnoses and primary care visits associated with continuity of care of many healthcare processes during diagnoses related to chronic conditions.21 22 Both studies the pandemic, it might face limitations generating diag- found moderate reductions in diagnoses of mental health noses that require more assessments.21 conditions, which were lower than the ones observed for Our findings suggest that women, young adults and other diagnosis groups. For instance, while the average individuals living in the most deprived urban areas were decline in new all-­cause diagnoses in 2020 compared with affected disproportionately. The reductions among these 2019 was 31.1%, the decline in mental health conditions subgroups are particularly concerning as they have been was 27.5%.21 Although reductions have been reported previously identified as experiencing worse mental health across diagnostic groups,21 22 reductions in mental health due to the pandemic.4 14 Moreover, the IRRs provided by diagnoses are particularly concerning as the effects of the our study suggest that individuals aged 18–34 years were pandemic have been estimated to account for an increase the only age group with significant increases in cases of 27.6% (95% CI 25.1 to 30.3) in cases of major depres- of anxiety disorders during the last trimester of 2020 sive disorders and 25.6% (23.2 to 28.0) in cases of anxiety (women) and first trimester of 2021 (both women and disorders globally in 2020.14 Indeed, the increased rates men) compared with the same periods in 2018 and 2019. of anxiety and depressive disorders observed in our study The worsening mental health among this subgroup can during the first trimester of 2021 might be explained by be likely attributed to the disruption of their daily life, the midterm effects of the pandemic on mental health, including their access to education and employment which could be gradually appearing, and the efforts of opportunities, and their limited in-­person interactions general practitioners (GPs) to adapt to the increasing with peers.29 demands for care. The reduced number of new diagnoses observed Reductions in common mental health diagnoses might compared with the expected number obtained in this be explained by the disruption in the normal functioning study is most likely to represent a large number of disor- of healthcare systems due to the COVID-­19 pandemic. ders that have gone undiagnosed and untreated. Possible In Catalonia, non-­essential health activities were inter- consequences of this unmet need may include increased rupted during the lockdown in order to prioritise demand for mental health services, increased use of Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 9 Open access emergency departments for mental issues and height- While the stay-­at-­home order was limited to the first wave ened risk of suicide. Moreover, the economic impact of the pandemic in Spain, strict control measures were of the pandemic will likely increase the risk of mental implemented afterwards.3 Lastly, some of the ICD-­10-­CM health problems and exacerbate healthcare disparities.30 codes used in our study require several months of symp- Monitoring patterns in real-­time primary care data of toms in order to be diagnosed. While we cannot account common mental disorders will provide crucial informa- for the GP’s decision-­making behaviour around coding, tion to ensure health services can meet future demand, our study reflects diagnoses in primary care practice, as primary healthcare centres carry the major burden of which may differ from ICD-­10-­CM coding guidelines. management and treatment of common mental health In conclusion, the sudden peak in primary care-­recorded disorders in Spain.25 Data on psychotropic drug prescrip- incident cases of anxiety disorders suggests increased tions and secondary care referrals can provide valuable mental distress at the onset of the lockdown measures in information on the management of anxiety and depres- Catalonia. The marked reduction in incident diagnoses sive disorders during the COVID-­19 pandemic. Indeed, of anxiety and depressive disorders during the COVID-­19 data on psychotropic drug prescriptions are scarce. In pandemic indicates untreated mental health problems Catalonia, trends in psychotropic drug prescriptions given the increase in anxiety and depression observed during the first months of the pandemic were similar in studies using self-­reported data. Women, adults aged to those observed for other medications and reported a 18–34 years and individuals living in the most deprived brief increase in the number of dispensed drugs followed areas might have greater levels of undetected need. Our by a reduction in the number of medications prescribed findings may help to design public health interventions and dispensed. However, reductions observed for psycho- to target those particularly affected by the pandemic, as tropic drugs were lower than those observed for other well as to prepare healthcare systems for greater demand medications.10 Further research should also investigate for mental health services in the following months. the evolution of conditions over time using linkages to data from hospital emergency departments and outpa- Author affiliations 1 tient mental health centres. Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi The main strengths of this study are the sample size Gol i Gurina (IDIAPJGol), Barcelona, Spain 2 Universitat Autònoma de Barcelona, Barcelona, Spain and the real-­world nature of the data. Our study provided 3 Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, data from a broadly representative setting and included Rheumatology, and Musculoskeletal Sciences (NDORMS), University of Oxford, more than 3.6 million people registered in primary care Oxford, UK in Catalonia. The data used were obtained from primary care electronic health records, which have been shown Twitter Berta Raventós @raventosb, Anna Berenguera @ABerenguera, Laura to be a useful tool for research in many areas, including Medina-­Perucha @Lauramedp and Talita Duarte-­Salles @TDuarte_Salles COVID-­19.31 32 In order to strengthen our results we vali- Acknowledgements This study was carried out as part of the Doctoral Programme in Biomedical Research Methodology and Public Health at the Autonomous University dated our modelling approach forecasting the expected of Barcelona. The authors would like to acknowledge the efforts of all public diagnoses from 1 year prior to the pandemic, obtaining healthcare workers in Catalonia during this global pandemic crisis. The authors would consistent predictions compared with observed figures. also like to thank Daniel López-­Codina and his team for assistance in fitting the Moreover, our study investigates the COVID-­19-­related model, and Miguel-Ángel Mayer for his contributions in the initial stages of the study. effects up to March 2021, providing data up to a year after Contributors BR, EB and TD-­S conceived and designed the study. SF-­B, MA, the onset of the lockdown measures in Catalonia. EB and TD-­S mapped the source data to the Observational Medical Outcomes Partnership Common Data Model. BR, EB and AP performed the statistical analysis. We acknowledge several limitations to our study. First, BR drafted the initial version of the manuscript. TD-­S acts as a guarantor of the our data are limited to recorded diagnoses in primary study. All authors interpreted the results, critically reviewed the manuscript and care, with the absence of such a record taken to indicate approved the final version for submission. the absence of disease. Our data do not capture cases Funding TD-­S acknowledges receiving financial support from Instituto de Salud among patients who directly accessed emergency care Carlos III (ISCIII; Miguel Servet 2021: CP21/00023). or those who were hospitalised, which might account for Competing interests None declared. even more severe cases. It is therefore likely that this is an Patient and public involvement Patients and/or the public were not involved in underestimate of episodes of anxiety and depressive disor- the design, or conduct, or reporting, or dissemination plans of this research. ders. Although our data do not include registers from Patient consent for publication Not required. mental health services, we believe diagnoses performed Ethics approval This project was approved by the Clinical Research Ethics in these settings would not significantly alter our results Committee of the IDIAPJGol (project code: 21/052-­PCV). as referrals for specialist care must be indicated by a GP in Provenance and peer review Not commissioned; externally peer reviewed. primary care and must be linked to a registered diagnosis. Data availability statement Data may be obtained from a third party and are Second, reductions in diagnoses of anxiety and depres- not publicly available. In accordance with the current European and national law, sive disorders may have been underestimated as they were the data used in this study are only available for the researchers participating in based on prepandemic data and did not take into consid- this study. Thus, we are not allowed to distribute or make publicly available the data to other parties. However, researchers from public institutions can request eration an increase of incident cases of psychological data from SIDIAP if they comply with certain requirements. Further information is distress due to the pandemic. Third, the postlockdown available online (https://www.sidiap.org/index.php/menu-solicitudesen/application-​ period does not represent the return to prepandemic life. proccedure) or by contacting SIDIAP (​sidiap@​idiapjgol.​org). 10 Raventós B, et al. BMJ Open 2022;12:e057866. doi:10.1136/bmjopen-2021-057866 Open access Supplemental material This content has been supplied by the author(s). It has 12 Cheung R, O'Donnell S, Madi N, et al. Factors associated with not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been delayed diagnosis of mood and/or anxiety disorders. Health Promot peer-­reviewed. Any opinions or recommendations discussed are solely those Chronic Dis Prev Can 2017;37:137–48. 13 United Nations. United nations policy brief: COVID-­19 and the need of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and for action on mental health. Available: https://unsdg.un.org/sites/​ responsibility arising from any reliance placed on the content. Where the content default/files/2020-05/UN-Policy-Brief-COVID-19-and-mental-health.​ includes any translated material, BMJ does not warrant the accuracy and reliability pdf [Accessed 14 Feb 2021]. of the translations (including but not limited to local regulations, clinical guidelines, 14 COVID-­19 Mental Disorders Collaborators. Global prevalence terminology, drug names and drug dosages), and is not responsible for any error and burden of depressive and anxiety disorders in 204 countries and/or omissions arising from translation and adaptation or otherwise. and territories in 2020 due to the COVID-­19 pandemic. Lancet 2021;398:1700–12. Open access This is an open access article distributed in accordance with the 15 García-­Gil MDM, Hermosilla E, Prieto-­Alhambra D, et al. Construction Creative Commons Attribution Non Commercial (CC BY-­NC 4.0) license, which and validation of a scoring system for the selection of high-­quality permits others to distribute, remix, adapt, build upon this work non-­commercially, data in a Spanish population primary care database (SIDIAP). Inform and license their derivative works on different terms, provided the original work is Prim Care 2011;19:135–45. properly cited, appropriate credit is given, any changes made indicated, and the use 16 Voss EA, Makadia R, Matcho A, et al. Feasibility and utility of is non-­commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. applications of the common data model to multiple, disparate observational health databases. 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