Temporal trends and social inequities in adolescent and young adult mental health disorders in Catalonia, Spain: a 2008-2022 primary care cohort study

Temporal trends and social inequities in adolescent and young adult mental health disorders in Catalonia, Spain: a 2008-2022 primary care cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Temporal trends and social inequities in adolescent and young adult mental health disorders in Catalonia, Spain: a 2008-2022 primary care cohort study Ana Lozano-Sánchez, Enric Aragonès, Tomàs López-Jiménez, Matthew Bennett, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5038084/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Dec, 2024 Read the published version in Child and Adolescent Psychiatry and Mental Health → Version 1 posted 9 You are reading this latest preprint version Abstract Background: The prevalence of mental health disorders in children, teens, and young adults is rising at an alarming rate. This study aims to explore time trends in the incidence of mental disorders among young people in Catalonia, Spain from 2008 to 2022, focusing on the effects of the COVID-19 pandemic and from the perspective of social inequities. Methods: A cohort study using primary care records from the SIDIAP database was conducted. It included 2,088,641 individuals aged 10 to 24 years. We examined the incidence of depressive, anxiety, eating, and attention deficit/hyperactivity disorders, stratified by sex, age, deprivation, and nationality. Results: Anxiety disorders were most prevalent in 2022, with an incidence rate (IR) of 2,537 per 100,000 persons-year (95% CI: 2,503-2,571). Depressive disorders followed with an IR of 471 (95% CI: 458-486), ADHD with an IR of 306 (95% CI: 295-317) and eating disorders with an IR of 249 (95% CI: 239-259). All disorders reflected an increasing trend: depressive disorders (IRR: 2.44, 95% CI: 2.31-2.59), anxiety disorders (IRR: 2.33, 95% CI: 2.27-2.39), ADHD (IRR: 2.33, 95%CI: 2.17-2.50), and eating disorders (IRR: 3.29, 95% CI: 3.01-3.59). A significant increase in incidence was observed after the outbreak of the COVID-19 pandemic. Significant associations were reported mainly in girls, in 15-18 years and 19-24 years groups, with high and middle socioeconomic deprivation, and Spanish nationality. Conclusion: The incidence of all studied disorders has steadily increased, reaching unprecedented levels during the pandemic. This increase is not observed uniformly across all axes of social inequity. Understanding these trends is essential for an appropriate healthcare response, while addressing the non-medical determinants, requires action across all sectors of society. Adolescents and young People Mental Health Disorders Incidence Social Inequities Gender Inequities Cohort Study Figures Figure 1 Figure 2 Figure 3 Figure 4 BACKGROUND The growing prevalence and incidence of mental health disorders in adolescents and young people is an important societal concern given its implications for the diagnosed individual, the family and society [ 1 ]. Recent Global Burden of Disease studies have revealed that mental health disorders rank among the most debilitating conditions for young people, leading to the highest number of years lived with disability with anxiety and depression topping this list [ 2 ]. In Europe, approximately 15.5% of young people are estimated to suffer from a mental disorder [ 3 ]. In high-income countries, significant socioeconomic inequalities are strongly linked to adverse mental health outcomes in children and adolescents [ 4 , 5 , 6 ]. From social inequities perspective, structural factors as socioeconomic disadvantage, early life adversity, migratory processes, racism, lesbian, gay, bisexual, transgender, questioning, intersex, asexual, and other (LGTBIAQ+) discrimination and gender inequity contribute to worsened mental health outcomes [ 7 ]. In addition, environmental factors such as neighborhood socioeconomic status, lack of social capital, and the built environment, influence the state of mental health, especially in adolescence and young people [7]. Furthermore, increased awareness and positively evolving attitudes toward mental health, in addition to reconsidering the medicalization of feelings and behaviors once considered normal may encourage parents and adolescents to seek healthcare more readily [ 8 ]. Data from various sources indicate that the burden of mental health problems among young people in high-income countries has been increasing over recent decades [2, 8, 9 , 10 ], likely exacerbated by diverse societal changes and growing inequities [8, 11 ]. Previous studies analyzing the incidence of mental disorders in childhood and adolescence in Catalonia and the United Kingdom (UK) have reported this secular trend [ 12 , 13 ]. However, these studies do not cover the timeframe that includes the impact of the COVID-19 pandemic on mental health, which is anticipated to have intensified the negative effects of socioeconomic determinants on mental health, leading to increased emotional distress and a rise in psychiatric symptoms [ 14 , 15 ]. Youth and adolescence are critical periods in the development of the individuals that could be particularly vulnerable to the negative impact of social stressors [ 16 ]. These disorders can significantly affect key areas such as individual wellbeing and health, family dynamics, social interactions, and academic performance, with lasting repercussions [ 17 ]. Moreover, experiencing mental disorders during these formative years is associated with a disrupted transition to adulthood and an increased risk of mental health issues in later life [ 18 , 19 ]. The World Health Organization’s (WHO) Action Plan for Mental Health 2013-2030 emphasizes the need for data on child mental health to be disaggregated by sex and age, while also considering the vulnerability of specific groups [20]. It is well established that girls are at greater risk than boys for depression and anxiety, with recent reports indicating worsening internalizing symptoms among adolescent girls. However, the specific reasons for this trend remain unclear, and the impact on boys is not well understood [10]. Therefore, it is essential to analyze the specific effects of sex on the incidence of mental disorders in adolescents and young people [10]. Early prevention and non-medicalizing interventions are crucial for improving long-term outcomes, and this study is valuable designing adequate public policies and resources to effectively address the mental health needs of adolescents and young people [ 20 ]. The objective of this study was to explore temporal trends in the incidence of several mental disorders in adolescents and young adults in Catalonia, Spain, according to demographic characteristics and social inequities (sex, age, deprivation and nationality) during the period 2008-2022, with a particular focus on the impact of the COVID-19 pandemic on these outcomes. METHODS Study design, setting and data source We carried out a cohort study using primary care records spanning from January 1, 2008 to December 31, 2022 in Catalonia, Spain. We utilized individual-level data extracted from electronic health records from 328 primary care centers managed by the Catalan Institute of Health. Data from these records are systematically compiled to make up the Information System for Research in Primary Care (SIDIAP) database. Since its establishment in 2006, SIDIAP has gathered records for over 8 million individuals. In June 2021, with 5.8 million people represented in the database, corresponding to approximately 75% of the total resident. SIDIAP is representative of the general population of Catalonia in terms of age, sex, and geographic distribution [ 21 ]. Study participants An open cohort was established, allowing for the inclusion or exclusion of participants over time. All individuals registered in the SIDIAP aged 10 to 24 years old at any point during the study period were considered for inclusion. Individuals were enrolled in the cohort either on the study's start date (1 January 2008) or when they reached the minimum age for inclusion (10 years old) after the start of the study. Individuals were followed until diagnosis of a mental health disorder within one of the defined categories, reaching the maximum age (25 years old), transferring out of SIDIAP, death, or the end of the study period. Variables Outcomes: The study focused on the incidence of specific mental health disorders included in the following categories: (1) depressive disorders (F30-F39), (2) anxiety disorders (F40-F44), (3) eating disorders (F50), and (4) ADHD disorders (F90). Conditions were identified based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes [ 22 ]. The first recorded code for each outcome category was considered an incident episode. Covariates: We used sociodemographic data recorded in SIDIAP, including sex (male or female), age groups (10 to 14 years, 15 to 19 years, and 20 to 24 years), and nationality (Spain, other European countries, Northern America, Central and South America, Africa, and Asia/Oceania). To gauge socioeconomic status, we utilized the Mortality in Small Spanish Areas and Socioeconomic and Environmental Inequalities (MEDEA) Deprivation Index, which is associated with each residential census area. This index is applicable to urban areas, defined as municipalities with over 10,000 inhabitants and a population density exceeding 150 inhabitants/km². The deprivation index is divided into quintiles, with the first and fifth quintiles denoting the least and most deprived areas, respectively [ 23 ]. Statistical methods We conducted a descriptive analysis to describe the sociodemographic characteristics of the population. Continuous variables were summarized using the median and Interquartile Range (IQR), while categorical variables were presented as absolute sums and percentages. The annual incidence of depressive disorders, anxiety disorders, eating disorders, and ADHD was calculated separately. To do so, the number of individuals aged 10–24 years diagnosed with each mental disorder (on or before January 1 of each year) was divided by the total number of individuals aged 10–24 years on January 1 of each calendar year of study. For incidence calculations, individuals without a prior history of the specific mental health disorder before January 1, 2008, contributed person-time starting from the date they became eligible for the study (aged 10 years at any time during follow-up) until the first occurrence of, their 25th birthday, death, transfer out of SIDIAP, or the study's conclusion on December 31, 2022. Annual Incidence Rates (IRs) of mental disorder diagnoses were calculated from 2008 to 2022 by dividing the number of new cases by 100,000 person-years at risk. We only took into account first-ever diagnoses. All analyses were stratified IRs by sex, age groups (calculated annually), nationality, and deprivation index quintiles. Following a thorough visual examination of incidence curves over the study period, several significant trends emerged spanning from 2008 to 2022, including growth, decline, and stabilization patterns. To further explore these trends, we defined and analyzed them using Incidence Rate Ratios (IRRs) between the end and start of each defined period. Poisson's 95% confidence intervals (95% CIs) were utilized to assess differences in incidence across different periods and sociodemographic groups. The analyses were conducted using SPSS 25.0 (SPSS Inc., Armonk, NY: IBM Corp) and R version 4.3.2. RESULTS We utilized data from a total of 2,088,641 eligible individuals, accumulating 13,136,826 person-years of observation [Fig. S1, see Additional file 1]. Among the participants enrolled, 1,022,600 (49.0%) were female. Upon cohort entry, the median age of the cohort was 12.0 years, with an interquartile range spanning from 10.0 to 19.2 years. Additional sociodemographic data are available in Table S1 [see Additional file 1]. Anxiety disorders were the most commonly diagnosed mental illnesses, with a 2022 IR (incidence rate) of 2,537 per 100,000 persons-year (95%CI: 2,503-2,571). The other disorders studied presented lower incidence: depressive disorders IR: 471 (95%CI: 458-486), ADHD IR: 306 (95%CI: 295-317) and eating disorders IR: 249 (95% CI: 239-259). Annual incidence rates over the entire study period for all the mental health disorders of study stratified by sociodemographic characteristics can be found in Tables S2, S3, S4, and S5 [see Additional file 1]. Time trends in the incidence of mental disorders We have observed a fluctuating yet overall increasing trend in the IR of depressive disorders (IRR: 2.44, 95% CI: 2.31-2.59) and anxiety disorders (IRR: 2.33; 95% CI: 2.27-2.39), from 2008-2022. Notably, both disorders experienced a decline in incidence in 2020 compared to 2019, followed by a significant upsurge in incidence rates during the period from 2020 to 2022. In this period (2020-2022), for depressive disorders we found IRR: 1.64 (95% CI: 1.56-1.72); and for anxiety disorders IRR: 1.46 (95% CI: 1.43-1.49) (Figure 1, Table 1). Table 1. IRR for mental health disorders in people 10-24 years old by sex, age, deprivation and nationality. Regarding eating disorders, the IRR between 2022 and 2008 was 3.29 (95% CI: 3.01-3.59), increasing especially after 2020. In 2021, there was a notable increase in its incidence (IRR between 2021 and 2020: 2.75, 95% CI: 2.57-2.95), which then stabilized in 2022. This phenomenon was particularly evident in girls (Figure 1, Table 1). ADHD presented irregular trends from 2008 to 2022, with peak incidence observed in 2013 (IRR between 2013 and 2008: 2.21, 95% CI: 2.06-2.38). In 2020, there was a notable decrease compared to 2019 (IRR: 0.69, 95% CI: 0.64-0.74), followed by a sharp increase in the period from 2020 to 2022 (IRR: 2.22, 95% CI: 2.07-2.37) (Figure 1, Table 1). Sex In terms of sex-specific trends, the incidence rates of depressive and anxiety disorders exhibited parallel trends over the entire study duration. However, the incidence in girls is consistently double that of boys. For example, in 2022 the IRR between girls and boys for depressive disorders was 2.08 (95% CI: 1.96-2.22), and for anxiety disorders was 2.07 (95% CI: 2.01-2.13) (Figure 1, Table 1). In the case of eating disorders, incidence rates were manifestly higher in girls compared to boys (in 2022 the IRR: 8.96, 95% IC: 7.87-10.21). Finally, for ADHD, we observed parallel trends between both sexes, with the highest incidence consistently observed in boys. For example, in 2022, the IRR between girls and boys was 0.54 (95% CI: 0.50-0.58) (Figure 1, Table 1). Age In the growing secular trend in the incidence rates of depressive and anxiety disorders, the trajectories in the three age groups were generally the same. Notably, the incidence among the youngest age group remains consistently lower than that of the other age groups. For example, in 2022, the IRR for depressive disorders between the 19–24 year-old age group and 10-14 year-old age group was 1.52 (95% IC: 1.41-1.63) and for anxiety disorders the IRR was 2.25 (95% CI: 2.18-2.33) (Figure 2, Table 1). In the case of eating disorders, the highest incidence rates were observed among the 15-18 year-old age group, followed by the 10-14 year-old age group. While these two groups present similar time trend evolutions, the 19-24 year-old age group presents lower and relatively stable incidence levels throughout the entire study period. However, IRs double across all age groups experience after 2020 (Figure 2, Table 1). Regarding ADHD, the highest incidence was noted in the 10-14 year-old age group, with a notable increase from 2008 to 2013 (IRR: 1.92, 95% IC: 1.77-2.08), followed by a subsequent decrease. After a sharp decline in 2020, incidence rebounded until 2022 (between 2022 and 2020, in the 10-14 year-old age group IRR: 2.09, 95% CI: 1.93-2.27). The 15-18 year-old age group demonstrates similar trends, albeit at a lower level, while the 19-24 year-old age group maintains consistently low levels of incidence during the study period, with an upswing from 2020 onwards (Figure 2, Table 1). Deprivation In both depressive and anxiety disorders, incidence curves by deprivation levels exhibit similar trends throughout the study period and present some intersections and overlaps. The least deprived group generally presents lower IRs compared to the other groups, particularly evident in anxiety disorders. For example, in 2022, the IRR between the least and the most deprived groups was 0.87 (95% CI: 0.79-0.97) for depressive disorders, and 0.70 (95% CI: 0.67-0.73) for anxiety disorders (Figure 3, Table 1). Similarly, in eating disorders, the incidence curves overlapped between different deprivation levels. However, in 2022, the incidence among the most deprived group was lower than that of the other groups (Figure 3, Table 1). In ADHD, the curves of the deprivation index quintiles remain parallel throughout the study period, showing an inverse correlation between degree of deprivation and incidence: the lower the deprivation level, the higher the incidence of ADHD. In 2022, the IRR between the most and the least deprivation level was 1.38 (95% CI: 1.20-1.60) (Figure 3, Table 1). Nationality For all the disorders, the incidence curves for non-Spanish nationals generally remain at lower levels compared to those for individuals with Spanish nationality. Notably, incidence rates among individuals with North and South America nationality increase from 2015 onwards, exceeding the incidence rates of those with Spanish nationality. In 2022, the IRR between North and South American vs. Spanish nationality groups was 1.50 (95% CI: 1.35-1.68) for depressive disorders, and 1.59 (95% CI: 1.52-1.67) for anxiety disorders (Figure 4, Table 1). DISCUSSION This study highlights a significant overall increase in the incidence of all mental health diagnoses during the COVID-19 pandemic, with anxiety disorders being the most common. Notably, the incidence of all studied mental health disorders was higher in girls compared to boys, with the exception of ADHD. Additionally, there was an elevated incidence of depression and anxiety diagnoses among individuals aged 19-24 years, while ADHD was more prevalent in the younger cohort aged 10-14 years. Depressive and anxiety disorders were more common among individuals from the most deprived areas, whereas eating disorders and ADHD were more frequent among those from less deprived areas. Furthermore, the incidence of mental health disorders was generally lower among individuals of non-Spanish nationality compared to Spanish nationals. We noticed a consistent increase in incident depressive and anxiety disorders from 2008 to 2022, which is consistent with the results from longitudinal studies conducted in the UK [13] as well as a previous study carried out in Catalonia that used a different database [12]. Recent reviews corroborate the ongoing secular increase in the incidence of mental health disorders in adolescents, particularly in high-income countries, which is plateauing globally [ 24 ]. We observed increases in the incidence of all disorders in the years 2011-2013. This phenomenon, which has already been documented both in Catalonia [12] and in the UK [13], may be related to the impact of the economic crisis that began in 2008 [ 25 ]. The crisis reached its peak social impact in Spain in 2011 and continued in the following years due to austerity policies affecting social welfare, health, and education. [ 26 ]. Nevertheless, in this study a sharp increase in incidence of studied mental health disorders was noted following the onset of the COVID-19 pandemic. In 2020, a temporary dip in the incidence curves of anxiety, depression, and ADHD is observed. This finding aligns with other epidemiological studies on mental health disorders [ 27 , 28 ] and can be attributed to the lockdown and restrictions on access to healthcare services during the early months of the COVID-19 pandemic [ 29 , 30 ]. Longitudinal studies that calculated the incidence rates of mental health disorders over shorter periods (monthly or bimonthly) show a notable decrease in new recorded diagnoses in the initial months after the outbreak, with a gradual return thereafter to expected values [27, 28]. Following this decline, there has been a dramatic increase in all studied disorders until 2022. This surge reflects the adverse effects on adolescent and youth mental health resulting from the pandemic, as well as that of the lockdown and social distancing measures that were implemented. These impacts have been observed using different methodologies in many countries around the world [14]. Anxiety was the most frequent diagnosis during our study period, with incidences 5-times that of depression or about 10-times that of ADHD or eating disorders. While the higher prevalence of anxiety disorders compared to other disorders is expected, it appears excessively disproportionate considering epidemiological data [ 31 ]. Anxiety symptoms can be part of the clinical expression of other mental disorders or can precede the manifestation of other symptoms or mental health disorders [ 32 ]. Therefore, a significant percentage of the diagnoses of anxiety registered in primary care records may be an indicator of nonspecific emotional distress or preliminary states of other disorders. The results of this study reveal a worsened state of mental health among girls, with a higher incidence in all disorders except ADHD. This disparity may be partly attributed to a sexist social system, where sexism and other forms of violence against women negatively impact mental health [7, 33 ]. Additionally, the greater prevalence of diagnoses in girls could be linked to the gender socialization process, which may enhance girls' ability to express psychological discomfort [33]. The results suggest that psychological distress manifests differently by gender, with girls more likely to express it emotionally, while boys tend to express it behaviorally [33]. This would correspond to the higher incidence in girls of depressive, anxiety, and eating disorders, and in boys of ADHD. ADHD incidence is consistently higher in boys than in girls throughout the study period, which could be attributed to sex bias in its clinical diagnosis process: girls with ADHD may be more easily overlooked due to a higher symptom threshold requirement for seeking help and diagnosis [ 34 ]. For eating disorders, the results reveal higher incidence in girls than in boys, in line with many other studies which indicate a greater presence of these disorders in girls [ 35 ]. This may be due to gender norms related to body image and weight [ 36 ] though other research suggests these disorders express different cultural norms, values, and conflicts influenced by gender and the sociocultural context [ 37 ]. According to age, our findings are consistent with the idea that internalized symptoms are more prevalent in older adolescents and young adults, whereas externalized symptoms are more prevalent in children and adolescents [ 38 ]. Thus, the 15-18 and 19-24 age groups would score higher for depressive and anxiety disorders, while the 10 -14 age group would score higher for ADHD. Age is a determining factor in the incidence of ADHD, displaying a gradient: the incidence is higher in the younger age group (10-14 years) while new ADHD diagnoses are infrequent in the age group over 18 years old. A limitation of our data is that we did not examine individuals under the age of 10, when, according to epidemiological data, the peak incidence by age is precisely around 7-9 years old [ 39 ]. Our study also observed a noteworthy relationship between socioeconomic deprivation and the incidence of ADHD and eating disorders, which diverges from patterns seen in other disorders. While depressive and anxiety disorders show higher incidence among individuals in the most deprived groups, ADHD presents higher incidence among individuals in the least deprived groups. This contradicts findings where ADHD symptoms, diagnoses, and treatments were more among individuals in most deprived groups [39, 40 , 41 ]. Other studies reveal the mechanisms of more frequent ADHD diagnoses among individuals in diagnoses in individuals of high socioeconomic status, including heightened awareness among parents and teachers, greater academic performance expectations, higher health literacy, and improved access to healthcare [ 42 , 43 ]. Moreover, the DSM-5 expanded the criteria for ADHD diagnosis, which may partially explain the peak in diagnoses around 2013. Similarly, eating disorders predominantly occur in least deprived group. The reasons remain unclear, though some studies suggest that in statistical terms, a high family level of education is a risk factor. The relation between socioeconomic-status and higher incidence of eating disorders should continue to be studied [ 44 ]. Our study surprisingly revealed lower incidence of the studied mental health disorders among non-Spanish nationals compared to those with Spanish nationality. Despite universal coverage offered by the Spanish public healthcare system, barriers related to language and culture, lack of familiarity with rights, gaps in health literacy, limited knowledge of the health system, discrimination, and socioeconomic inequity lead to differential treatment within the healthcare system [ 45 ]. However, those of American nationality have shown a strong and sustained increase in the incidence of depression and anxiety since 2015, accelerating from the outbreak of the COVID-19 pandemic, resulting in their rates surpassing those of individuals with Spanish nationality. The specific factors behind these differential incidence trends merit further research. There is a significant issue of psychological distress and adverse mental health among adolescents and young people, which have been exacerbated by the COVID-19 pandemic, though they preceded it [24]. Structural factors, discrimination and violence are risk factors, as they are different expressions of psychological distress between genders, age groups and socioeconomic status [7, 33, 37, 38]. Parental psychopathology, living in an urban context, excessive use of the internet and social networks, among others, have been identified as risk factors in previous research [ 46 , 47 ], mediated by additional factors that facilitate or promote seeking help in the healthcare system [ 48 ]. Understanding this phenomenon is necessary for an appropriate response from the healthcare system and, since many relevant determinants are not healthcare-related, the response must also be rooted in societal change [ 49 ]. This study has limitations that must be considered when interpreting the results. Firstly, the data pertain to diagnoses recorded in primary care medical records, not the actual incidence of mental disorders in the population. Underdiagnosis or overdiagnosis can contribute to discrepancies between recorded diagnoses and the actual presence of disorders in the population [43, 50 ]. Additionally, increased knowledge and awareness among physicians and pediatricians about mental disorders, decreased stigma, and social trends regarding mental health, can facilitate increased help-seeking behavior and mental health diagnoses [ 51 ]. Secondly, diagnoses given in specialized psychiatry settings may not be adequately recorded in primary care medical records. However, within the Catalan public health system, primary and specialty care are integrated, reducing underreporting [ 52 ]. The management of chronic diagnoses initiated in other levels of care, –including private healthcare–, usually occur in primary care [ 53 ], reducing the probability of undocumented diagnostic information. Thirdly, for the gender-based analysis, we used the variable "sex" as a proxy. However, we acknowledge that gender is a far more complex construct that cannot be limited to a simple binary biological category [ 54 ]. And finally, the variable "nationality" must be interpreted with caution since we lack other data regarding origin, years of residence in the country, level of integration, or other relevant factors [ 55 ]. The strengths of the study lie in the sample size and the use of real-world origin of the data. Our study reports broadly representative data, including about two million adolescents and young adults seen in primary care in Catalonia. The SIDIAP database has been proven to be a valid and useful tool for research purposes [21]. Moreover, the extended study period allows us to analyze and interpret the situation within the context of the COVID-19 pandemic from a temporal perspective, including the secular evolution of the outcomes of interest since 2008. Additionally, our study encompasses the entire period of the COVID-19 pandemic, from its onset in early 2020 to the end of 2022, shortly before the formal declaration of the end of the pandemic by the WHO in March 2023 [ 56 ]. CONCLUSION In this study, we have observed a secular increase in the incidence of the studied disorders, a trend that has accelerated with the onset of the COVID-19 pandemic, pushing incidence rates to unprecedented levels. It remains uncertain whether these incidence rates will continue to rise, stabilize, or return to pre-pandemic levels. Future longitudinal studies will be necessary to monitor this phenomenon. Our findings indicate that mental health disorders were reported predominantly in girls, 15-18 and 19-24 year olds, those of most deprived areas, and Spanish nationality. This study leaves questions unanswered, such as the relationship between migratory status and incidence, the response of the healthcare system, gender biases in the actual incidence and clinical management of disorders, and the role of socioeconomic inequities, which have been studied here in a generic way using an ecological indicator but deserve deeper investigation. In addition to longitudinal studies, it is crucial to explore these phenomena further through qualitative studies involving the active participation of those affected. This approach will help provide a comprehensive understanding of the data presented in this article. ABBREVIATIONS IR: Incidence Rate; ADHD: Attention deficit/hyperactivity disorder; LGBTQIA+: Lesbian, gay, bisexual, transgender, questioning, intersex, asexual, and other; UK: United Kingdom; WHO: World Health Organization; SIDIAP: Information System for Research in Primary Care; ICD-10: International Statistical Classification of Diseases and Related Health Problems, 10th Revision; MEDEA: Mortality in Small Spanish Areas and Socioeconomic and Environmental Inequalities Deprivation Index; IQR: Interquartile Range; IRs: Annual Incidence Rates Declarations SUPPLEMENTARY INFORMATION The online version contains supplementary material available at […] Ethics approval and consent to participate The study was designed in accordance with the Guide to Good Practice in Health Science Research and the principles of the Declaration of Helsinki of the World Medical Association, modified in 2013, and the applicable regulations. The study protocol was approved by the Ethics Committee of IDIAP Jordi Gol (Barcelona, January 17, 2023; code 22/206-P). Consent for publication Not applicable Availability of data and materials Data cannot be shared publicly because of ethical restrictions. The Ethical Committee does not allow us to share the data publicly as our data contain sensitive personal information and cannot be fully anonymized. Data are available from the Research Ethics Committee of the Institut de Recerca en Atenció Primària Jordi Gol i Gurina (IDIAPJGol) (contact via [email protected] ) for researchers who meet the criteria for access to confidential data. Competing interests Enric Aragonès has received fees as a speaker or consultant from Lündbeck, Esteve and Boehringer Ingelheim. All authors declare that they have no other relationships, interests, or activities that could appear to have influenced the submitted work. Funding This research has received funding from the Instituto de Salud Carlos III (ISCIII) and has been co-funded by the European Union (PI22/01278). A. L. is the recipient of an award for her doctoral thesis, which provides the funding for the publication of this article (IDIAPJGol, 2024). E. A. acknowledges support from a grant for intensification of research activity provided by IDIAP Jordi Gol (SENIOR-20/2). The funders played no part in the study's design, data collection, analysis, interpretation, manuscript preparation or review, nor in the decision to submit the article for publication. Authors' contributions C.J lead the research project. C.J, A.L, T.L and E.A conceptualized and designed this study. T.L, serving as the data manager, conducted data cleaning and led the design and execution of statistical analyses. E.A, A.L, C.J and T.L drafted the initial version of the manuscript. All authors engaged in reviewing the initial draft, offering substantial insights into data interpretation, and granting approval for the final manuscript. The corresponding author confirms that all named authors meet the criteria for authorship and that no eligible contributors have been omitted. Acknowledgements Not applicable Authors' information C.J is member of the Network for Research on Chronicity, Primary Care and Health Promotion (RICAPPS), in Barcelona, Spain. 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IRR 2022 vs. 2008 (the entire study period) IRR 2013 vs 2011 (peak period of economic crisis) IRR 2020 vs 2019 (lockdown/restriction of access to health services) IRR 2022 vs 2020 (pandemic period) Depressive disorders 2.44 (2.31-2.59) 1.41 (1.32-1.50) 0.88 (0.83-0.92) 1.64 (1.56-1.72) Anxiety disorders 2.33 (2.27-2.39) 1.28 (1.25-1.32) 0.85 (0.83-0.87) 1.46 (1.43-1.49) Eating disorders 3.29 (3.01-3.59) 1.68 (1.54-1.84) 1.16 (1.06-1.26) 1.90 (1.77-2.04) ADHD 2.33 (2.17-2.50) 1.18 (1.11-1.25) 0.69 (0.64-0.74) 2.22 (2.07-2.37) IRR (95% CI) by sex, year 2022 IRR (95% CI) by age group, year 2022 IRR (95% CI) by deprivation quintiles, year 2022 IRR (95% CI) by nationality, year 2022 Depressive disorders Boys 1,00 10-14 y/o 1,00 Q5 (most deprived) 1,00 Spain 1,00 Girls 2.08 (1.96-2.22) 15-18 y/o 1.25 (1.15-1.36) Q4 0.93 (0.84-1.04) Americas 1.50 (1.35-1.68) 19-24 y/o 1.52 (1.41-1.63) Q3 0.98 (0.88-1.09) Africa 0.56 (0.46-0.67) Q2 0.98 (0.88-1.09) Asia and Oceania 0.45 (0.35-0.58) Q1 (least deprived) 0.87 (0.79-0.97) Other European 0.90 (0.76-1.07) Anxiety disorders Boys 1,00 10-14 y/o 1,00 Q5 (most deprived) 1,00 Spain 1,00 Girls 2.07 (2.01-2.13) 15-18 y/o 1.59 (1.53-1.66) Q4 1.00 (0.96-1.05) Americas 1.59 (1.52-1.67) 19-24 y/o 2.25 (2.18-2.33) Q3 0.96 (0.92-1.01) Africa 0.74 (0.69-0.80) Q2 0.87 (0.83-0.91) Asia and Oceania 0.43 (0.38-0.48) Q1 (least deprived) 0.70 (0.67-0.73) Other European 1.05 (0.97-1.12) Eating disorders Boys 1,00 10-14 y/o 1,00 Q5 (most deprived) 1,00 Spain 1,00 Girls 8.96 (7.87-10.21) 15-18 y/o 1.16 (1.06-1.28) Q4 1.15 (0.99-1.33) Americas 0.84 (0.69-1.01) 19-24 y/o 0.41 (0.37-0.46) Q3 1.16 (1.00-1.35) Africa 0.26 (0.18-0.37) Q2 1.23 (1.06-1.43) Asia and Oceania 0.25 (0.16-0.39) Q1 (least deprived) 1.09 (0.94-1.27) Other European 0.80 (0.63-1.01) Attention deficit and hyperactivity disorder Boys 1,00 10-14 y/o 1,00 Q5 (most deprived) 1,00 Spain 1,00 Girls 0.54 (0.50-0.58) 15-18 y/o 0.39 (0.36-0.43) Q4 1.07 (0.92-1.23) Americas 0.80 (0.67-0.95) 19-24 y/o 0.16 (0.14-0.18) Q3 1.01 (0.87-1.17) Africa 0.37 (0.29-0.49) Q2 1.08 (0.94-1.25) Asia and Oceania 0.16 (0.10-0.27) Q1 (least deprived) 1.38 (1.20-1.60) Other European 0.68 (0.54-0.86) Notes: The analyzed periods were chosen following a visual examination of the graphs to capture significant variations in incidence rates over the follow-up Additional Declarations Competing interest reported. Enric Aragonès has received fees as a speaker or consultant from Lündbeck, Esteve and Boehringer Ingelheim. All authors declare that they have no other relationships, interests, or activities that could appear to have influenced the submitted work. 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12:14:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5038084/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5038084/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13034-024-00849-2","type":"published","date":"2024-12-18T15:58:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":67195292,"identity":"ecd02354-16ac-43c1-9c04-efcbed7cf08a","added_by":"auto","created_at":"2024-10-22 09:06:10","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1071926,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5038084/v1/3d3c72a158a1284d4dd4e164.jpg"},{"id":67195295,"identity":"062a56c2-d126-4cb2-9f82-adfe24aea228","added_by":"auto","created_at":"2024-10-22 09:06:10","extension":"jpg","order_by":2,"title":"Figure 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4","display":"","copyAsset":false,"role":"figure","size":535445,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5038084/v1/687f2588e894e23c91038fc7.jpg"},{"id":72202627,"identity":"f95399d4-6e12-4098-b5bd-ebad1daeaa90","added_by":"auto","created_at":"2024-12-23 16:15:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4659922,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5038084/v1/c73ba30c-e103-44db-85ac-ced2bd22975d.pdf"},{"id":67195293,"identity":"6ba56854-ccbd-4f5a-b1d6-e305dda1f0b7","added_by":"auto","created_at":"2024-10-22 09:06:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":69167,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-5038084/v1/479cd9a8e031ad596b75c3a1.docx"}],"financialInterests":"Competing interest reported. Enric Aragonès has received fees as a speaker or consultant from Lündbeck, Esteve and Boehringer Ingelheim. All authors declare that they have no other relationships, interests, or activities that could appear to have influenced the submitted work.","formattedTitle":"Temporal trends and social inequities in adolescent and young adult mental health disorders in Catalonia, Spain: a 2008-2022 primary care cohort study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe growing prevalence and incidence of mental health disorders in adolescents and young people is an important societal concern given its implications for the diagnosed individual, the family and society [\u003csup\u003e1\u003c/sup\u003e].\u0026nbsp;Recent Global Burden of Disease studies have revealed that mental health disorders rank among the most debilitating conditions for young people, leading to the highest number of years lived with disability with anxiety and depression topping this list [\u003csup\u003e2\u003c/sup\u003e].\u0026nbsp;In Europe, approximately 15.5% of young people are estimated to suffer from a mental disorder [\u003csup\u003e3\u003c/sup\u003e].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn high-income countries, significant socioeconomic inequalities are strongly linked to adverse mental health outcomes in children and adolescents [\u003csup\u003e4\u003c/sup\u003e, \u003csup\u003e5\u003c/sup\u003e, \u003csup\u003e6\u003c/sup\u003e].\u0026nbsp;From social inequities perspective, structural factors as socioeconomic disadvantage, early life adversity, migratory processes, racism, lesbian, gay, bisexual, transgender, questioning, intersex, asexual, and other (LGTBIAQ+) discrimination and gender inequity contribute to worsened mental health outcomes [\u003csup\u003e7\u003c/sup\u003e]. In addition, environmental factors such as neighborhood socioeconomic status, lack of social capital, and the built environment, influence the state of mental health, especially in adolescence and young people [7]. \u0026nbsp;Furthermore, increased awareness and positively evolving attitudes toward mental health, in addition to reconsidering the medicalization of feelings and behaviors once considered normal may encourage parents and adolescents to seek healthcare more readily [\u003csup\u003e8\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eData from various sources indicate that the burden of mental health problems among young people in high-income countries has been increasing over recent decades [2,\u0026nbsp;8, \u003csup\u003e9\u003c/sup\u003e, \u003csup\u003e10\u003c/sup\u003e],\u0026nbsp;likely exacerbated by diverse societal changes and growing inequities\u0026nbsp;[8, \u003csup\u003e11\u003c/sup\u003e]. Previous studies analyzing the incidence of mental disorders in childhood and adolescence in Catalonia and the United Kingdom (UK) have reported this secular trend [\u003csup\u003e12\u003c/sup\u003e, \u003csup\u003e13\u003c/sup\u003e]. However, these studies do not cover the timeframe that includes the impact of the COVID-19 pandemic on mental health,\u0026nbsp;which is anticipated to have intensified the negative effects of socioeconomic determinants on mental health, leading to increased emotional distress and a rise in psychiatric symptoms [\u003csup\u003e14\u003c/sup\u003e, \u003csup\u003e15\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eYouth and adolescence are critical periods in the development of the individuals that could be particularly vulnerable to the negative impact\u0026nbsp;of social stressors [\u003csup\u003e16\u003c/sup\u003e].\u0026nbsp;These disorders can significantly affect key areas such as individual wellbeing and health, family dynamics, social interactions, and academic performance, with lasting repercussions [\u003csup\u003e17\u003c/sup\u003e]. Moreover, experiencing mental disorders during these formative years is associated with a disrupted transition to adulthood and an increased risk of mental health issues in later life [\u003csup\u003e18\u003c/sup\u003e, \u003csup\u003e19\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eThe World Health Organization\u0026rsquo;s (WHO) Action Plan for Mental Health 2013-2030 emphasizes the need for data on child mental health to be disaggregated by sex and age, while also considering the vulnerability of specific groups [20].\u0026nbsp;It is well established that girls are at greater risk than boys for depression and anxiety, with recent reports indicating worsening internalizing symptoms among adolescent girls. However, the specific reasons for this trend remain unclear, and the impact on boys is not well understood [10]. Therefore, it is essential to analyze the specific effects of sex on the incidence of mental disorders in adolescents and young people [10]. Early prevention and non-medicalizing interventions are crucial for improving long-term outcomes, and this study is valuable designing adequate public policies and resources to effectively address the mental health needs of adolescents and young people [\u003csup\u003e20\u003c/sup\u003e].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe objective of this study was to explore temporal trends in the incidence of several mental disorders in adolescents and young adults in Catalonia, Spain, according to demographic characteristics and social inequities (sex, age, deprivation and nationality) during the period 2008-2022, with a particular focus on the impact of the COVID-19 pandemic on these outcomes.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design, setting and data source\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe carried out a cohort study using primary care records spanning from January 1, 2008 to December 31, 2022 in Catalonia, Spain. We utilized individual-level data extracted from electronic health records from 328 primary care centers managed by the Catalan Institute of Health. Data from these records are systematically compiled to make up the Information System for Research in Primary Care (SIDIAP) database. Since its establishment in 2006, SIDIAP has gathered records for over 8 million individuals. In June 2021, with 5.8 million people represented in the database, corresponding to approximately 75% of the total resident. \u0026nbsp;SIDIAP is representative of the general population of Catalonia in terms of age, sex, and geographic distribution [\u003csup\u003e21\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy participants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn open cohort was established, allowing for the inclusion or exclusion of participants over time. All individuals registered in the SIDIAP aged 10 to 24 years old at any point during the study period were considered for inclusion. Individuals were enrolled in the cohort either on the study\u0026apos;s start date (1 January 2008) or when they reached the minimum age for inclusion (10 years old) after the start of the study. Individuals were followed until diagnosis of a mental health disorder within one of the defined categories, reaching the maximum age (25 years old), transferring out of SIDIAP, death, or the end of the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcomes:\u003c/em\u003e\u003c/strong\u003e The study focused on the incidence of specific mental health disorders included in the following categories: (1) depressive disorders (F30-F39), (2) anxiety disorders (F40-F44), (3) eating disorders (F50), and (4) ADHD disorders (F90). Conditions were identified based on the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes [\u003csup\u003e22\u003c/sup\u003e]. The first recorded code for each outcome category was considered an incident episode.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCovariates:\u003c/em\u003e\u003c/strong\u003e We used sociodemographic data recorded in SIDIAP, including sex (male or female), age groups (10 to 14 years, 15 to 19 years, and 20 to 24 years), and nationality (Spain, other European countries, Northern America, Central and South America, Africa, and Asia/Oceania). To gauge socioeconomic status, we utilized the Mortality in Small Spanish Areas and Socioeconomic and Environmental Inequalities (MEDEA) Deprivation Index, which is associated with each residential census area. This index is applicable to urban areas, defined as municipalities with over 10,000 inhabitants and a population density exceeding 150 inhabitants/km\u0026sup2;. The deprivation index is divided into quintiles, with the first and fifth quintiles denoting the least and most deprived areas, respectively [\u003csup\u003e23\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical methods\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a descriptive analysis to describe the sociodemographic characteristics of the population. Continuous variables were summarized using the median and Interquartile Range (IQR), while categorical variables were presented as absolute sums and percentages.\u003c/p\u003e\n\u003cp\u003eThe annual incidence of depressive disorders, anxiety disorders, eating disorders, and ADHD was calculated separately. To do so, the number of individuals aged 10\u0026ndash;24 years diagnosed with each mental disorder (on or before January 1 of each year) was divided by the total number of individuals aged 10\u0026ndash;24 years on January 1 of each calendar year of study.\u003c/p\u003e\n\u003cp\u003eFor incidence calculations, individuals without a prior history of the specific mental health disorder before January 1, 2008, contributed person-time starting from the date they became eligible for the study (aged 10 years at any time during follow-up) until the first occurrence of, their 25th birthday, death, transfer out of SIDIAP, or the study\u0026apos;s conclusion on December 31, 2022.\u003c/p\u003e\n\u003cp\u003eAnnual Incidence Rates (IRs) of mental disorder diagnoses were calculated from 2008 to 2022 by dividing the number of new cases by 100,000 person-years at risk. We only took into account first-ever diagnoses. All analyses were stratified IRs by sex, age groups (calculated annually), nationality, and deprivation index quintiles. Following a thorough visual examination of incidence curves over the study period, several significant trends emerged spanning from 2008 to 2022, including growth, decline, and stabilization patterns. To further explore these trends, we defined and analyzed them using Incidence Rate Ratios (IRRs) between the end and start of each defined period. Poisson\u0026apos;s 95% confidence intervals (95% CIs) were utilized to assess differences in incidence across different periods and sociodemographic groups. The analyses were conducted using SPSS 25.0 (SPSS Inc., Armonk, NY: IBM Corp) and R version 4.3.2.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eWe utilized data from a total of 2,088,641 eligible individuals, accumulating 13,136,826 person-years of observation [Fig. S1, see Additional file 1].\u003c/p\u003e\n\u003cp\u003eAmong the participants enrolled, 1,022,600 (49.0%) were female. Upon cohort entry, the median age of the cohort was 12.0 years, with an interquartile range spanning from 10.0 to 19.2 years. Additional sociodemographic data are available in Table S1 [see Additional file 1].\u003c/p\u003e\n\u003cp\u003eAnxiety disorders were the most commonly diagnosed mental illnesses, with a 2022 IR (incidence rate) of 2,537 per 100,000 persons-year (95%CI: 2,503-2,571). The other disorders studied presented lower incidence: depressive disorders IR: 471 (95%CI: 458-486), ADHD IR: 306 (95%CI: 295-317) and eating disorders IR: 249 (95% CI: 239-259). \u0026nbsp;Annual incidence rates over the entire study period for all the mental health disorders of study stratified by sociodemographic characteristics can be found in\u0026nbsp;Tables S2, S3, S4, and S5 [see Additional file 1].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTime trends in the incidence of mental disorders\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have observed a fluctuating yet overall increasing trend in the IR of depressive disorders (IRR: 2.44, 95% CI: 2.31-2.59) and anxiety disorders (IRR: 2.33; 95% CI: 2.27-2.39), from 2008-2022. Notably, both disorders experienced a decline in incidence in 2020 compared to 2019, followed by a significant upsurge in incidence rates during the period from 2020 to 2022. In this period (2020-2022), for depressive disorders we found IRR: 1.64 (95% CI: 1.56-1.72); and for anxiety disorders IRR: 1.46 (95% CI: 1.43-1.49) (Figure 1, Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. IRR for mental health disorders in people 10-24 years old by sex, age, deprivation and nationality.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding eating disorders, the IRR between 2022 and 2008 was 3.29 (95% CI: 3.01-3.59), increasing especially after 2020. In 2021, there was a notable increase in its incidence (IRR between 2021 and 2020: 2.75, 95% CI: 2.57-2.95), which then stabilized in 2022. This phenomenon was particularly evident in girls (Figure 1, Table 1).\u003c/p\u003e\n\u003cp\u003eADHD presented irregular trends from 2008 to 2022, with peak incidence observed in 2013 (IRR between 2013 and 2008: 2.21, 95% CI: 2.06-2.38). In 2020, there was a notable decrease compared to 2019 (IRR: 0.69, 95% CI: 0.64-0.74), followed by a sharp increase in the period from 2020 to 2022 (IRR: 2.22, 95% CI: 2.07-2.37) (Figure 1, Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn terms of sex-specific trends, the incidence rates of depressive and anxiety disorders exhibited parallel trends over the entire study duration. However, the incidence in girls is consistently double that of boys. For example, in 2022 the IRR between girls and boys for depressive disorders was 2.08 (95% CI: 1.96-2.22), and for anxiety disorders was 2.07 (95% CI: 2.01-2.13) (Figure 1, Table 1).\u003c/p\u003e\n\u003cp\u003eIn the case of eating disorders, incidence rates were manifestly higher in girls compared to boys (in 2022 the IRR: 8.96, 95% IC: 7.87-10.21).\u003c/p\u003e\n\u003cp\u003eFinally, for ADHD, we observed parallel trends between both sexes, with the highest incidence consistently observed in boys. For example, in 2022, the IRR between girls and boys was 0.54 (95% CI: 0.50-0.58) (Figure 1, Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the growing secular trend in the incidence rates of depressive and anxiety disorders, the trajectories in the three age groups were generally the same. Notably, the incidence among the youngest age group remains consistently lower than that of the other age groups. For example, in 2022, the IRR for depressive disorders between the 19\u0026ndash;24 year-old age group and 10-14 year-old age group was 1.52 (95% IC: 1.41-1.63) and for anxiety disorders the IRR was 2.25 (95% CI: 2.18-2.33) (Figure 2, Table 1).\u003c/p\u003e\n\u003cp\u003eIn the case of eating disorders, the highest incidence rates were observed among the 15-18 year-old age group, followed by the 10-14 year-old age group. While these two groups present similar time trend evolutions, the 19-24 year-old age group presents lower and relatively stable incidence levels throughout the entire study period. However, IRs double across all age groups experience after 2020 (Figure 2, Table 1).\u003c/p\u003e\n\u003cp\u003eRegarding ADHD, the highest incidence was noted in the 10-14 year-old age group, with a notable increase from 2008 to 2013 (IRR: 1.92, 95% IC: 1.77-2.08), followed by a subsequent decrease. After a sharp decline in 2020, incidence rebounded until 2022 (between 2022 and 2020, in the 10-14 year-old age group IRR: 2.09, 95% CI: 1.93-2.27). The 15-18 year-old age group demonstrates similar trends, albeit at a lower level, while the 19-24 year-old age group maintains consistently low levels of incidence during the study period, with an upswing from 2020 onwards (Figure 2, Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeprivation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn both depressive and anxiety disorders, incidence curves by deprivation levels exhibit similar trends throughout the study period and present some intersections and overlaps. The least deprived group generally presents lower IRs compared to the other groups, particularly evident in anxiety disorders. For example, in 2022, the IRR between the least and the most deprived groups was 0.87 (95% CI: 0.79-0.97) for depressive disorders, and 0.70 (95% CI: 0.67-0.73) for anxiety disorders (Figure 3, Table 1).\u003c/p\u003e\n\u003cp\u003eSimilarly, in eating disorders, the incidence curves overlapped between different deprivation levels. However, in 2022, the incidence among the most deprived group was lower than that of the other groups (Figure 3, Table 1).\u003c/p\u003e\n\u003cp\u003eIn ADHD, the curves of the deprivation index quintiles remain parallel throughout the study period, showing an inverse correlation between degree of deprivation and incidence: the lower the deprivation level, the higher the incidence of ADHD. In 2022, the IRR between the most and the least deprivation level was 1.38 (95% CI: 1.20-1.60) (Figure 3, Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNationality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor all the disorders, the incidence curves for non-Spanish nationals generally remain at lower levels compared to those for individuals with Spanish nationality. Notably, incidence rates among individuals with North and South America nationality increase from 2015 onwards, exceeding the incidence rates of those with Spanish nationality. In 2022, the IRR between North and South American vs. Spanish nationality groups was 1.50 (95% CI: 1.35-1.68) for depressive disorders, and 1.59 (95% CI: 1.52-1.67) for anxiety disorders (Figure 4, Table 1).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study highlights a significant overall increase in the incidence of all mental health diagnoses during the COVID-19 pandemic, with anxiety disorders being the most common. Notably, the incidence of all studied mental health disorders was higher in girls compared to boys, with the exception of ADHD. Additionally, there was an elevated incidence of depression and anxiety diagnoses among individuals aged 19-24 years, while ADHD was more prevalent in the younger cohort aged 10-14 years. Depressive and anxiety disorders were more common among individuals from the most deprived areas, whereas eating disorders and ADHD were more frequent among those from less deprived areas. Furthermore, the incidence of mental health disorders was generally lower among individuals of non-Spanish nationality compared to Spanish nationals.\u003c/p\u003e\n\u003cp\u003eWe noticed a consistent increase in incident depressive and anxiety disorders from 2008 to 2022, which is consistent with the results from longitudinal studies conducted in the UK [13] as well as a previous study carried out in Catalonia that used a different database [12]. Recent reviews corroborate the ongoing secular increase in the incidence of mental health disorders in adolescents, particularly in high-income countries, which is plateauing globally [\u003csup\u003e24\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eWe observed increases in the incidence of all disorders in the years 2011-2013. This phenomenon, which has already been documented both in Catalonia [12] and in the UK [13], may be related to the impact of the economic crisis that began in 2008 [\u003csup\u003e25\u003c/sup\u003e]. The crisis reached its peak social impact in Spain in 2011 and continued in the following years due to austerity policies affecting social welfare, health, and education. [\u003csup\u003e26\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eNevertheless, in this study a sharp increase in incidence of studied mental health disorders was noted following the onset of the COVID-19 pandemic. In 2020, a temporary dip in the incidence curves of anxiety, depression, and ADHD is observed. This finding aligns with other epidemiological studies on mental health disorders [\u003csup\u003e27\u003c/sup\u003e, \u003csup\u003e28\u003c/sup\u003e] and can be attributed to the lockdown and restrictions on access to healthcare services during the early months of the COVID-19 pandemic [\u003csup\u003e29\u003c/sup\u003e, \u003csup\u003e30\u003c/sup\u003e]. Longitudinal studies that calculated the incidence rates of mental health disorders over shorter periods (monthly or bimonthly) show a notable decrease in new recorded diagnoses in the initial months after the outbreak, with a gradual return thereafter to expected values [27, 28]. Following this decline, there has been a dramatic increase in all studied disorders until 2022. This surge reflects the adverse effects on adolescent and youth mental health resulting from the pandemic, as well as that of the lockdown and social distancing measures that were implemented. These impacts have been observed using different methodologies in many countries around the world [14].\u003c/p\u003e\n\u003cp\u003eAnxiety was the most frequent diagnosis during our study period, with incidences 5-times that of depression or about 10-times that of ADHD or eating disorders. While the higher prevalence of anxiety disorders compared to other disorders is expected, it appears excessively disproportionate considering epidemiological data [\u003csup\u003e31\u003c/sup\u003e]. Anxiety symptoms can be part of the clinical expression of other mental disorders or can precede the manifestation of other symptoms or mental health disorders [\u003csup\u003e32\u003c/sup\u003e]. Therefore, a significant percentage of the diagnoses of anxiety registered in primary care records may be an indicator of nonspecific emotional distress or preliminary states of other disorders.\u003c/p\u003e\n\u003cp\u003eThe results of this study reveal a worsened state of mental health among girls, with a higher incidence in all disorders except ADHD. This disparity may be partly attributed to a sexist social system, where sexism and other forms of violence against women negatively impact mental health [7,\u0026nbsp;\u003csup\u003e33\u003c/sup\u003e]. Additionally, the greater prevalence of diagnoses in girls could be linked to the gender socialization process, which may enhance girls\u0026apos; ability to express psychological discomfort [33]. The results suggest that psychological distress manifests differently by gender, with girls more likely to express it emotionally, while boys tend to express it behaviorally [33]. This would correspond to the higher incidence in girls of depressive, anxiety, and eating disorders, and in boys of ADHD. ADHD incidence is consistently higher in boys than in girls throughout the study period, which could be attributed to sex bias in its clinical diagnosis process: girls with ADHD may be more easily overlooked due to a higher symptom threshold requirement for seeking help and diagnosis [\u003csup\u003e34\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eFor eating disorders, the results reveal higher incidence in girls than in boys, in line with many other studies which indicate a greater presence of these disorders in girls [\u003csup\u003e35\u003c/sup\u003e]. This may be due to gender norms related to body image and weight [\u003csup\u003e36\u003c/sup\u003e] though other research suggests these disorders express different cultural norms, values, and conflicts influenced by gender and the sociocultural context [\u003csup\u003e37\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eAccording to age, our findings are consistent with the idea that internalized symptoms are more prevalent in older adolescents and young adults, whereas externalized symptoms are more prevalent in children and adolescents [\u003csup\u003e38\u003c/sup\u003e]. Thus, the 15-18 and 19-24 age groups would score higher for depressive and anxiety disorders, while the 10 -14 age group would score higher for ADHD. \u0026nbsp;Age is a determining factor in the incidence of ADHD, displaying a gradient: the incidence is higher in the younger age group (10-14 years) while new ADHD diagnoses are infrequent in the age group over 18 years old. A limitation of our data is that we did not examine individuals under the age of 10, when, according to epidemiological data, the peak incidence by age is precisely around 7-9 years old [\u003csup\u003e39\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eOur study also observed a noteworthy relationship between socioeconomic deprivation and the incidence of ADHD and eating disorders, which diverges from patterns seen in other disorders. While depressive and anxiety disorders show higher incidence among individuals in the most deprived groups, ADHD presents higher incidence among individuals in the least deprived groups. This contradicts findings where ADHD symptoms, diagnoses, and treatments were more among individuals in most deprived groups [39, \u003csup\u003e40\u003c/sup\u003e, \u003csup\u003e41\u003c/sup\u003e]. Other studies reveal the mechanisms of more frequent ADHD diagnoses among individuals in diagnoses in individuals of high socioeconomic status, including heightened awareness among parents and teachers, greater academic performance expectations, higher health literacy, and improved access to healthcare [\u003csup\u003e42\u003c/sup\u003e, \u003csup\u003e43\u003c/sup\u003e]. Moreover, the DSM-5 expanded the criteria for ADHD diagnosis, which may partially explain the peak in diagnoses around 2013.\u003c/p\u003e\n\u003cp\u003eSimilarly, eating disorders predominantly occur in least deprived group. The reasons remain unclear, though some studies suggest that in statistical terms, a high family level of education is a risk factor. The relation between socioeconomic-status and higher incidence of eating disorders should continue to be studied [\u003csup\u003e44\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eOur study surprisingly revealed lower incidence of the studied mental health disorders among non-Spanish nationals compared to those with Spanish nationality.\u0026nbsp;Despite universal coverage offered by the Spanish public healthcare system, barriers related to language and culture, lack of familiarity with rights, gaps in health literacy, limited knowledge of the health system, discrimination, and socioeconomic inequity lead to differential treatment within the healthcare system [\u003csup\u003e45\u003c/sup\u003e]. However, those of American nationality have shown a strong and sustained increase in the incidence of depression and anxiety since 2015, accelerating from the outbreak of the COVID-19 pandemic, resulting in their rates surpassing those of individuals with Spanish nationality. The specific factors behind these differential incidence trends merit further research.\u003c/p\u003e\n\u003cp\u003eThere is a significant issue of psychological distress and adverse mental health among adolescents and young people, which have been exacerbated by the COVID-19 pandemic, though they preceded it [24]. Structural factors, discrimination and violence are risk factors, as they are different expressions of psychological distress between genders, age groups and socioeconomic status [7, 33, 37, 38]. \u0026nbsp;Parental psychopathology, living in an urban context, excessive use of the internet and social networks, among others, have been identified as risk factors in previous research [\u003csup\u003e46\u003c/sup\u003e, \u003csup\u003e47\u003c/sup\u003e], mediated by additional factors that facilitate or promote seeking help in the healthcare system [\u003csup\u003e48\u003c/sup\u003e]. Understanding this phenomenon is necessary for an appropriate response from the healthcare system and, since many relevant determinants are not healthcare-related, the response must also be rooted in societal change [\u003csup\u003e49\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eThis study has limitations that must be considered when interpreting the results. Firstly, the data pertain to diagnoses recorded in primary care medical records, not the actual incidence of mental disorders in the population. Underdiagnosis or overdiagnosis can contribute to discrepancies between recorded diagnoses and the actual presence of disorders in the population [43, \u003csup\u003e50\u003c/sup\u003e]. Additionally, increased knowledge and awareness among physicians and pediatricians about mental disorders, decreased stigma, and social trends regarding mental health, can facilitate increased help-seeking behavior and mental health diagnoses [\u003csup\u003e51\u003c/sup\u003e]. Secondly, diagnoses given in specialized psychiatry settings may not be adequately recorded in primary care medical records. However, within the Catalan public health system, primary and specialty care are integrated, reducing underreporting [\u003csup\u003e52\u003c/sup\u003e]. The management of chronic diagnoses initiated in other levels of care, \u0026ndash;including private healthcare\u0026ndash;, usually occur in primary care [\u003csup\u003e53\u003c/sup\u003e], reducing the probability of undocumented diagnostic information. Thirdly, for the gender-based analysis, we used the variable \u0026quot;sex\u0026quot; as a proxy. However, we acknowledge that gender is a far more complex construct that cannot be limited to a simple binary biological category [\u003csup\u003e54\u003c/sup\u003e]. And finally, the variable \u0026quot;nationality\u0026quot; must be interpreted with caution since we lack other data regarding origin, years of residence in the country, level of integration, or other relevant factors [\u003csup\u003e55\u003c/sup\u003e].\u003c/p\u003e\n\u003cp\u003eThe strengths of the study lie in the sample size and the use of real-world origin of the data. Our study reports broadly representative data, including about two million adolescents and young adults seen in primary care in Catalonia. The SIDIAP database has been proven to be a valid and useful tool for research purposes [21]. Moreover, the extended study period allows us to analyze and interpret the situation within the context of the COVID-19 pandemic from a temporal perspective, including the secular evolution of the outcomes of interest since 2008. Additionally, our study encompasses the entire period of the COVID-19 pandemic, from its onset in early 2020 to the end of 2022, shortly before the formal declaration of the end of the pandemic by the WHO in March 2023 [\u003csup\u003e56\u003c/sup\u003e].\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn this study, we have observed a secular increase in the incidence of the studied disorders, a trend that has accelerated with the onset of the COVID-19 pandemic, pushing incidence rates to unprecedented levels. It remains uncertain whether these incidence rates will continue to rise, stabilize, or return to pre-pandemic levels. Future longitudinal studies will be necessary to monitor this phenomenon. Our findings indicate that mental health disorders were reported predominantly in girls, 15-18 and 19-24 year olds, those of most deprived areas, and Spanish nationality. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study leaves questions unanswered, such as the relationship between migratory status and incidence, the response of the healthcare system, gender biases in the actual incidence and clinical management of disorders, and the role of socioeconomic inequities, which have been studied here in a generic way using an ecological indicator but deserve deeper investigation. In addition to longitudinal studies, it is crucial to explore these phenomena further through qualitative studies involving the active participation of those affected. This approach will help provide a comprehensive understanding of the data presented in this article.\u003c/p\u003e"},{"header":"ABBREVIATIONS","content":"\u003cp\u003eIR: Incidence Rate; ADHD: Attention deficit/hyperactivity disorder; LGBTQIA+: Lesbian, gay, bisexual, transgender, questioning, intersex, asexual, and other; UK: United Kingdom; WHO: World Health Organization; SIDIAP: Information System for Research in Primary Care; ICD-10: International Statistical Classification of Diseases and Related Health Problems, 10th Revision; MEDEA: Mortality in Small Spanish Areas and Socioeconomic and Environmental Inequalities Deprivation Index; IQR: Interquartile Range; IRs: Annual Incidence Rates\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSUPPLEMENTARY INFORMATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe online version contains supplementary material available at [\u0026hellip;]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was designed in accordance with the Guide to Good Practice in Health Science Research and the principles of the Declaration of Helsinki of the World Medical Association, modified in 2013, and the applicable regulations. The study protocol was approved by the Ethics Committee of IDIAP Jordi Gol (Barcelona, January 17, 2023; code 22/206-P).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData cannot be shared publicly because of ethical restrictions. The Ethical Committee does not allow us to share the data publicly as our data contain sensitive personal information and cannot be fully anonymized. Data are available from the Research Ethics Committee of the Institut de Recerca en Atenci\u0026oacute; Prim\u0026agrave;ria Jordi Gol i Gurina (IDIAPJGol) (contact via [email protected]) for researchers who meet the criteria for access to confidential data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnric Aragon\u0026egrave;s has received fees as a speaker or consultant from L\u0026uuml;ndbeck, Esteve and Boehringer Ingelheim. All authors declare that they have no other relationships, interests, or activities that could appear to have influenced the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research has received funding from the Instituto de Salud Carlos III (ISCIII) and has been co-funded by the European Union (PI22/01278). A. L. is the recipient of an award for her doctoral thesis, which provides the funding for the publication of this article (IDIAPJGol, 2024).\u0026nbsp;E. A. acknowledges support from a grant for intensification of research activity provided by IDIAP Jordi Gol (SENIOR-20/2). The funders played no part in the study\u0026apos;s design, data collection, analysis, interpretation, manuscript preparation or review, nor in the decision to submit the article for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC.J lead the research project. C.J, A.L, T.L and E.A conceptualized and designed this study. T.L, serving as the data manager, conducted data cleaning and led the design and execution of statistical analyses. E.A, A.L, C.J and T.L drafted the initial version of the manuscript. All authors engaged in reviewing the initial draft, offering substantial insights into data interpretation, and granting approval for the final manuscript. The corresponding author confirms that all named authors meet the criteria for authorship and that no eligible contributors have been omitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC.J is member of the Network for Research on Chronicity, Primary Care and Health Promotion (RICAPPS), in Barcelona, Spain.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePiao J, Huang Y, Han C, Li Y, Xu Y, Liu Y, He X (2022)Alarming changes in the global burden of mental disorders in children and adolescents from 1990 to 2019: a systematic analysis for the Global Burden of Disease studyEur Child Adolesc Psychiatry 31(11):1827-1845https://10.1007/s00787-022-02040-4\u003c/li\u003e\n\u003cli\u003eKieling C, Buchweitz C, Caye A, Silvani J, Ameis SH, Brunoni AR, Cost KT, Courtney DB, Georgiades K, Merikangas KR, Henderson JL, Polanczyk GV, Rohde LA, Salum GA, Szatmari P (2024)Worldwide Prevalence and Disability from Mental Disorders across Childhood and Adolescence: Evidence from the Global Burden of Disease StudyJAMA Psychiatry 81(4):347-356https://doi.org/10.1001/jamapsychiatry.2023.5051.\u003c/li\u003e\n\u003cli\u003eSacco R, Camilleri N, Eberhardt J, Umla-Runge K, Newbury-Birch D (2022)A systematic review and meta-analysis on the prevalence of mental disorders among children and adolescents in EuropeEur Child Adolesc Psychiatry Dec 30:1\u0026ndash;18https://doi.org/10.1007/s00787-022-02131-2\u003c/li\u003e\n\u003cli\u003eMackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinsalu M, Kunst AE; European Union Working Group on Socioeconomic Inequalities in Health (2008)Socioeconomic inequalities in health in 22 European countriesN Engl J Med 358:2468-2481https://doi.org/10.1056/NEJMsa0707519\u003c/li\u003e\n\u003cli\u003eRajmil L, Herdman M, Ravens-Sieberer U, Erhart M, Alonso J; European KIDSCREEN group (2014)Socioeconomic inequalities in mental health and health-related quality of life (HRQOL) in children and adolescents from 11 European countriesInt J Public Health 59:95-105https://doi.org/10.1007/s00038-013-0479-9\u003c/li\u003e\n\u003cli\u003eReiss F (2013)Socioeconomic inequalities and mental health problems in children and adolescents: a systematic reviewSoc Sci Med 90:24-31https://doi.org/10.1016/j.socscimed.2013.04.026\u003c/li\u003e\n\u003cli\u003eKirkbride JB, Anglin DM, Colman I, Dykxhoorn J, Jones PB, Patalay P, Pitman A, Soneson E, Steare T, Wright T, Griffiths SL (2024)The social determinants of mental health and disorder: evidence, prevention and recommendationsWorld Psychiatry, 23(1), 58\u0026ndash;90https://doi.org/10.1002/wps.21160.\u003c/li\u003e\n\u003cli\u003eDowrick C, Frances A(2013)Medicalising unhappiness: New classification of depression risks more patients being put on a drug treatment from which they will not benefitBMJ 347:f7140https://doi.org/10.1136/bmj.f7140\u003c/li\u003e\n\u003cli\u003ePotrebny T, Wiium N, Lundeg\u0026aring;rd MM-I (2017) Temporal trends in adolescents\u0026rsquo; self-reported psychosomatic health complaints from 1980\u0026ndash;2016: a systematic review and meta-analysisPLoS One 12(11):e0188374https://doi.org/10.1371/journal.pone.0188374\u003c/li\u003e\n\u003cli\u003eBor W, Dean AJ, Najman J, Hayatbakhsh R (2014) Are child and adolescent mental health problems increasing in the 21st century? 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Nagata JM, Cuccolo K, Ganson KT (2024)Associations between dieting practices and eating disorder attitudes and behaviors: Results from the Canadian study of adolescent health behaviorsEat Behav 54:101886https://doi.org/10.1016/j.eatbeh.2024.101886\u003c/li\u003e\n\u003cli\u003eLaMarre A, Levine MP, Holmes S, Malson H (2022)An open invitation to productive conversations about feminism and the spectrum of eating disorders (part 2): Potential contributions to the science of diagnosis, treatment, and preventionJ Eat Disord 10(1):55https://doi.org/10.1186/s40337-022-00572-3.\u003c/li\u003e\n\u003cli\u003eOrban E, Li LY, Gilbert M, Napp AK, Kaman A, Topf S, Boecker M, Devine J, Rei\u0026szlig; F, Wendel F, Jung-Sievers C, Ernst VS, Franze M, M\u0026ouml;hler E, Breitinger E, Bender S, Ravens-Sieberer U (2024)Mental health and quality of life in children and adolescents during the COVID-19 pandemic: a systematic review of longitudinal studiesFront Public Health 11:1275917https://doi.org/10.3389/fpubh.2023.1275917.\u003c/li\u003e\n\u003cli\u003eMar J, Larra\u0026ntilde;aga I, Ibarrondo O, Gonz\u0026aacute;lez-Pinto A, Las Hayas C, Fullaondo A, Izco-Basurko I, Alonso J, Zorrilla I, Vilagut G, Mateo-Abad M, de Manuel E; UPRIGHT Consortium (2023)Incidence of mental disorders in the general population aged 1-30 years disaggregated by gender and socioeconomic statusSoc Psychiatry Psychiatr Epidemiol 58(6):961-971https://doi.org/10.1007/s00127-023-02425-z.\u003c/li\u003e\n\u003cli\u003ePrasad V, West J, Kendrick D, Sayal K (2019)Attention-deficit/hyperactivity disorder: variation by socioeconomic deprivationArch Dis Child 104(8):802-805https://doi.org/10.1136/archdischild-2017-314470.\u003c/li\u003e\n\u003cli\u003eNunn SPT, Kritsotakis EI, Harpin V, Parker J (2020)Social gradients in the receipt of medication for attention-deficit hyperactivity disorder in children and young people in SheffieldBJPsych Open 6(2):e14https://doi.org/10.1192/bjo.2019.87.\u003c/li\u003e\n\u003cli\u003eGetahun D, Jacobsen SJ, Fassett MJ, Chen W, Demissie K, Rhoads GG (2013)Recent trends in childhood attention-deficit/hyperactivity disorderJAMA Pediatr 167(3):282-8https://doi.org/10.1001/2013.jamapediatrics.401.\u003c/li\u003e\n\u003cli\u003eMerten EC, Cwik JC, Margraf J, Schneider S (2017)Overdiagnosis of mental disorders in children and adolescents (in developed countries)Child Adolesc Psychiatry Ment Health 11:5https://doi.org/10.1186/s13034-016-0140-5\u003c/li\u003e\n\u003cli\u003eBarakat S, McLean SA, Bryant E, Le A, Marks P; National Eating Disorder Research Consortium; Touyz S, Maguire S(2023)Risk factors for eating disorders: findings from a rapid reviewJ Eat Disord 11(1):8https://doi.org/10.1186/s40337-022-00717-4\u003c/li\u003e\n\u003cli\u003eGimeno-Feliu LA, Calder\u0026oacute;n-Larra\u0026ntilde;aga A, Diaz E, Poblador-Plou B, Macipe-Costa R, Prados-Torres A (2016)Global healthcare use by immigrants in Spain according to morbidity burden, area of origin, and length of stayBMC Public Health 16:450https://doi.org/10.1186/s12889-016-3127-5.\u003c/li\u003e\n\u003cli\u003eFranzoi D, Bockting CL, Bennett KF, Odom A, Lucassen PJ, Pathania A, Lee A, Brouwer ME, van de Schoot R, Wiers RW, Breedvelt JJF (2023)Which individual, social, and urban factors in early childhood predict psychopathology in later childhood, adolescence and young adulthood? A systematic reviewSSM Popul Health 25:101575https://doi.org/10.1016/j.ssmph.2023.101575\u003c/li\u003e\n\u003cli\u003eGupta C, Jogdand DS, Kumar M(2022)Reviewing the Impact of Social Media on the Mental Health of Adolescents and Young AdultsCureus, 14(10), e30143https://doi.org/10.7759/cureus.30143.\u003c/li\u003e\n\u003cli\u003eTam MT, Wu JM, Zhang CC, Pawliuk C, Robillard JM(2024)A Systematic Review of the Impacts of Media Mental Health Awareness Campaigns on Young PeopleHealth promotion practice, 15248399241232646https://doi.org/10.1177/15248399241232646.\u003c/li\u003e\n\u003cli\u003eJeindl R, Hofer V, Bachmann C, Zechmeister-Koss I(2023)Optimising child and adolescent mental health care - a scoping review of international best-practice strategies and service modelsChild Adolesc Psychiatry Ment Health 17(1):135https://doi.org/10.1186/s13034-023-00683-y\u003c/li\u003e\n\u003cli\u003eGubi E, Sj\u0026ouml;qvist H, Dalman C, B\u0026auml;\u0026auml;rnhielm S, Hollander AC (2022)Are all children treated equally? Psychiatric care and treatment receipt among migrant, descendant and majority Swedish children: a register-based studyEpidemiol Psychiatr Sci 31:e20https://doi.org/10.1017/S2045796022000142.\u003c/li\u003e\n\u003cli\u003eFoulkes L, Andrews JL (2023)Are mental health awareness efforts contributing to the rise in reported mental health problems? A call to test the prevalence inflation hypothesisNew Ideas in Psychology 69: 101010https://doi.org/10.1016/j.newideapsych.2023.101010.\u003c/li\u003e\n\u003cli\u003eEnfedaque-Montes B, Garcia O, Gil-S\u0026aacute;nchez E, Lobo E, Vegu\u0026eacute; J, Cid J, Ruiz R (2023)Collaboration program between attention to mental health and addictions, and primary and community careDeptde SalutGeneralitat de Catalunya, BarcelonaAvailable at: https://hdl.handle.net/11351/9424\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez Gil S, Millas Ros J, L\u0026oacute;pez Z\u0026uacute;\u0026ntilde;iga MC, Arzuaga Arambarri MJ, Aldanondo Gabilondo A, San Vicente Blanco R (2010)Analysis of the induced prescription in a primary care regionRev Calid Asist 25(6):321-326doi:10.1016/j.cali.2010.03.008.\u003c/li\u003e\n\u003cli\u003eSolans-Dom\u0026egrave;nech M Saborit S, coordinators and Hypatia of Alexandria Charter Group (2022)Incorporating the sex and gender perspective in research content: a toolkitAgency for Health Quality and Assessment of Catalonia (AQuAS), Barcelona (Spain.\u003c/li\u003e\n\u003cli\u003eJacobs D, Swyngedouw M, Hanquinet L, Vandezande V, Andersson R, Horta APB, Berger M, Diani M, Gonzalez Ferrer A, Giugni M, Morariu M, Pilati K, Statham, P (2009)The challenge of measuring immigrant origin and immigration-related ethnicity in EuropeJ Int Migr Integr 10:67-88https://doi.org/10.1007/s12134-009-0091-2.\u003c/li\u003e\n\u003cli\u003eWise J (2023)Covid-19: WHO declares end of global health emergencyBMJ 381:1041https://doi.org/10.1136/bmj.p1041.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Incidence rate ratios (IRR) for mental health disorders in people from 10 to 24 years old in Catalonia along the follow-up period, and by sex, age, deprivation and nationality.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"936\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR 2022 vs. 2008\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(the entire study period)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR 2013 vs 2011\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(peak period of economic crisis)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR 2020 vs 2019\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(lockdown/restriction of access to health services)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR 2022 vs 2020\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(pandemic period)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eDepressive disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e2.44 (2.31-2.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e1.41 (1.32-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.88 (0.83-0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e1.64 (1.56-1.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAnxiety disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e2.33 (2.27-2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e1.28 (1.25-1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.85 (0.83-0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e1.46 (1.43-1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eEating disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e3.29 (3.01-3.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e1.68 (1.54-1.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e1.16 (1.06-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e1.90 (1.77-2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e2.33 (2.17-2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e1.18 (1.11-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.69 (0.64-0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e2.22 (2.07-2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR (95% CI) by sex, year 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR (95% CI) by age group, year 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR (95% CI) by deprivation quintiles, year 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR (95% CI) by nationality, year 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eDepressive disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;10-14 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ5 (most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.08 (1.96-2.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;15-18 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.25 (1.15-1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.93 (0.84-1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAmericas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.50 (1.35-1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;19-24 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.52 (1.41-1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.98 (0.88-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAfrica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.56 (0.46-0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.98 (0.88-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAsia and Oceania\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.45 (0.35-0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ1 (least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.87 (0.79-0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eOther European\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.90 (0.76-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAnxiety disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;10-14 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ5 (most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.07 (2.01-2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;15-18 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.59 (1.53-1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.00 (0.96-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAmericas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.59 (1.52-1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;19-24 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2.25 (2.18-2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.96 (0.92-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAfrica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.74 (0.69-0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.87 (0.83-0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAsia and Oceania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.43 (0.38-0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ1 (least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.70 (0.67-0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eOther European\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.05 (0.97-1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eEating disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;10-14 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ5 (most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e8.96 (7.87-10.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;15-18 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.16 (1.06-1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.15 (0.99-1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAmericas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.84 (0.69-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;19-24 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.41 (0.37-0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.16 (1.00-1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAfrica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.26 (0.18-0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.23 (1.06-1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAsia and Oceania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.25 (0.16-0.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ1 (least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.09 (0.94-1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eOther European\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.80 (0.63-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAttention deficit and hyperactivity disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;10-14 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ5 (most deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSpain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.54 (0.50-0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;15-18 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.39 (0.36-0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.07 (0.92-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAmericas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.80 (0.67-0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;19-24 y/o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.16 (0.14-0.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.01 (0.87-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAfrica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.37 (0.29-0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.08 (0.94-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eAsia and Oceania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.16 (0.10-0.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eQ1 (least deprived)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.38 (1.20-1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eOther European\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.68 (0.54-0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\" style=\"width: 936px;\"\u003e\n \u003cp\u003eNotes: The analyzed periods were chosen following a visual examination of the graphs to capture significant variations in incidence rates over the follow-up\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"child-and-adolescent-psychiatry-and-mental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caph","sideBox":"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)","snPcode":"13034","submissionUrl":"https://submission.nature.com/new-submission/13034/3","title":"Child and Adolescent Psychiatry and Mental Health","twitterHandle":"@IACAPAP","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adolescents and young People, Mental Health Disorders, Incidence, Social Inequities, Gender Inequities, Cohort Study ","lastPublishedDoi":"10.21203/rs.3.rs-5038084/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5038084/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe prevalence of mental health disorders in children, teens, and young adults is rising at an alarming rate. This study aims to explore time trends in the incidence of mental disorders among young people in Catalonia, Spain from 2008 to 2022, focusing on the effects of the COVID-19 pandemic and from the perspective of social inequities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cohort study using primary care records from the SIDIAP database was conducted. It included 2,088,641 individuals aged 10 to 24 years. We examined the incidence of depressive, anxiety, eating, and attention deficit/hyperactivity disorders, stratified by sex, age, deprivation, and nationality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Anxiety disorders were most prevalent in 2022, with an incidence rate (IR) of 2,537 per 100,000 persons-year (95% CI: 2,503-2,571). Depressive disorders followed with an IR of 471 (95% CI: 458-486), ADHD with an IR of 306 (95% CI: 295-317) and eating disorders with an IR of 249 (95% CI: 239-259). All disorders reflected an increasing trend: depressive disorders (IRR: 2.44, 95% CI: 2.31-2.59), anxiety disorders (IRR: 2.33, 95% CI: 2.27-2.39), ADHD (IRR: 2.33, 95%CI: 2.17-2.50), and eating disorders (IRR: 3.29, 95% CI: 3.01-3.59). A significant increase in incidence was observed after the outbreak of the COVID-19 pandemic. Significant associations were reported mainly in girls, in 15-18 years and 19-24 years groups, with high and middle socioeconomic deprivation, and Spanish nationality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The incidence of all studied disorders has steadily increased, reaching unprecedented levels during the pandemic. This increase is not observed uniformly across all axes of social inequity. Understanding these trends is essential for an appropriate healthcare response, while addressing the non-medical determinants, requires action across all sectors of society.\u003c/p\u003e","manuscriptTitle":"Temporal trends and social inequities in adolescent and young adult mental health disorders in Catalonia, Spain: a 2008-2022 primary care cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-22 09:06:05","doi":"10.21203/rs.3.rs-5038084/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-11T20:28:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-11T15:12:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82569609724194700296261974965964489368","date":"2024-10-29T12:51:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-08T09:26:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272528938831427509967527210727192218204","date":"2024-09-20T09:50:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-19T07:23:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-14T05:39:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-06T12:46:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Child and Adolescent Psychiatry and Mental Health","date":"2024-09-05T12:13:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"child-and-adolescent-psychiatry-and-mental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caph","sideBox":"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)","snPcode":"13034","submissionUrl":"https://submission.nature.com/new-submission/13034/3","title":"Child and Adolescent Psychiatry and Mental Health","twitterHandle":"@IACAPAP","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c6a41fe3-29a6-4cd7-a9ad-2c59a72b3e13","owner":[],"postedDate":"October 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:09:09+00:00","versionOfRecord":{"articleIdentity":"rs-5038084","link":"https://doi.org/10.1186/s13034-024-00849-2","journal":{"identity":"child-and-adolescent-psychiatry-and-mental-health","isVorOnly":false,"title":"Child and Adolescent Psychiatry and Mental Health"},"publishedOn":"2024-12-18 15:58:35","publishedOnDateReadable":"December 18th, 2024"},"versionCreatedAt":"2024-10-22 09:06:05","video":"","vorDoi":"10.1186/s13034-024-00849-2","vorDoiUrl":"https://doi.org/10.1186/s13034-024-00849-2","workflowStages":[]},"version":"v1","identity":"rs-5038084","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5038084","identity":"rs-5038084","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}