Mental Health Disorder Trends in Denmark According to Age, Calendar Period, and Birth Cohort

Natalie C Momen; Christoffer Beck; Mette Lise Lousdal; Esben Agerbo; John J McGrath; Carsten B Pedersen; Merete Nordentoft; Oleguer Plana-Ripoll

doi:10.1001/jamapsychiatry.2024.3723

. 2024 Nov 27;82(2):161–170. doi: 10.1001/jamapsychiatry.2024.3723

Mental Health Disorder Trends in Denmark According to Age, Calendar Period, and Birth Cohort

Natalie C Momen ¹, Christoffer Beck ^2,³, Mette Lise Lousdal ¹, Esben Agerbo ^2,^4,⁵, John J McGrath ^2,^6,⁷, Carsten B Pedersen ^2,^3,⁸, Merete Nordentoft ^9,¹⁰, Oleguer Plana-Ripoll ^1,^2,^✉

¹Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark

²National Centre for Register-based Research, Aarhus University, Aarhus School of Business and Social Sciences, Aarhus, Denmark

³Big Data Centre for Environment and Health, Aarhus University, Aarhus, Denmark

⁴Centre for Integrated Register-based Research (CIRRAU), Aarhus University, Aarhus, Denmark

⁵The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark

⁶Queensland Brain Institute, University of Queensland, St Lucia, Brisbane, Queensland, Australia

⁷Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, Queensland, Australia

⁸Hammel Neurorehabilitation Centre and University Research Clinic, Aarhus University, Hammel, Denmark

⁹Copenhagen Research Centre for Mental Health, Mental Health Services in the Capital Region, Copenhagen, Denmark

¹⁰Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

Accepted for Publication: September 16, 2024.

Published Online: November 27, 2024. doi:10.1001/jamapsychiatry.2024.3723

^✉

Corresponding Author: Oleguer Plana-Ripoll, PhD, Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Olof Palmes Allé 43-45, DK-8200 Aarhus N, Denmark (opr@clin.au.dk).

Author Contributions: Mr Beck and Dr Plana-Ripoll had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Agerbo, McGrath, Plana-Ripoll.

Acquisition, analysis, or interpretation of data: Momen, Beck, Lousdal, Agerbo, Pedersen, Nordentoft, Plana-Ripoll.

Drafting of the manuscript: Momen, Beck, Agerbo, Plana-Ripoll.

Critical review of the manuscript for important intellectual content: Momen, Lousdal, Agerbo, McGrath, Pedersen, Nordentoft, Plana-Ripoll.

Statistical analysis: Beck, Agerbo, Plana-Ripoll.

Obtained funding: Plana-Ripoll.

Administrative, technical, or material support: Agerbo, Pedersen, Nordentoft, Plana-Ripoll.

Supervision: Agerbo, McGrath, Nordentoft, Plana-Ripoll.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by the Lundbeck Foundation (Dr Plana-Ripoll; fellowship R345-2020-1588), Independent Research Fund Denmark (Dr Plana-Ripoll; grants 1030-00085B and 2066-00009B), the Novo Nordisk Foundation Challenge Programme Big Data Centre for Environment and Health (Mr Beck and Dr Pedersen; grant NNF17OC0027864).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

^✉

Corresponding author.

PMCID: PMC11603380 PMID: 39602130

Key Points

Question

How do the incidence rates of mental disorders in Denmark vary according to age, calendar period, and birth cohort?

Findings

This cohort study found that more recent birth cohorts and calendar periods had higher sex-specific incidence rates of any mental disorder. While an increase was observed for most types of mental disorders for both female and male individuals, reductions and variations in sex-specific patterns were seen for some mental disorder types.

Meaning

The findings suggest that sex- and age-specific incidence of mental disorders have varied over time by birth cohorts and calendar periods, possibly owing to a range of factors, including diagnostic patterns, health care capacity, risk factors, and actual changes in incidence.

This cohort study evaluates mental health disorders in Denmark by age, calendar period, and birth cohort.

Abstract

Importance

Research suggests an increase in mental disorder incidence in recent years, but this trend remains unexplained, and there is a lack of large studies based on a representative sample that investigate mental disorders over the full spectrum.

Objective

To explore sex- and age-specific incidence of any mental disorder and 19 specific disorders according to birth cohort and calendar period.

Design, Setting, and Participants

This was a population-based cohort study among 5 936 202 individuals aged 1 to 80 years living in Denmark at some point between January 1, 2004, and December 31, 2021. Data were derived from the Danish Civil Registration System and analyzed from February to August 2024.

Exposures

Birth cohort (8 categories from 1924 to 2011) and calendar period (six 3-year categories from 2004 to 2021).

Main Outcomes and Measures

Incidence rates of mental disorders from 2004 to 2021 by sex and age, according to birth cohort and calendar period, including the first years of the COVID-19 pandemic, using Danish health register data.

Results

The population comprised 2 933 857 female individuals and 3 002 345 male individuals, who were followed up for 83.8 million person-years, with median ages at start and end of follow-up of 30.2 and 46.2 years, respectively. There was an overall mental disorder incidence rate of 55.27 every 10 000 person-years. For diagnoses of any mental disorder, higher incidence rates were observed for more recent birth cohorts and calendar periods in the younger ages. Over older ages, incidence rates did not vary so greatly. An increase was observed in rates of most types of mental disorders, especially among young people, and decreases for other types (eg, substance use disorders). Prominent sex differences were also observed. For example, for schizophrenia, a large increase was seen in incidence rates for female individuals in more recent birth cohorts at younger ages, but no change for male individuals, leading to a higher peak incidence for female individuals than for male individuals in the most recent periods. For personality disorders, a large increase was observed in incidence for female individuals over time and a slight decrease for male individuals.

Conclusions and Relevance

This comprehensive investigation of mental disorders incidence in Denmark indicates sex- and age-specific patterns according to birth cohorts and calendar periods. While trends may partly be explained by increases in incidence, several other factors may contribute, such as diagnostic practices, health sector capacity, and risk factors for mental disorders.

Introduction

Evidence suggests that there has been an increase in incidence of mental disorders in recent years.^1,2,3,4,5 Estimates of prevalence also support that mental illness has become increasingly common: the global number of people with a mental disorder rose from 655 million in 1990 to 970 million in 2019.⁶ There is ongoing speculation about the potential reasons. For example, changes leading to broader diagnostic and reporting practices¹ can affect incidence rates. Additionally, increased awareness and recognition of mental disorders can result in increases in diagnoses of childhood disorders, like autism and attention-deficit/hyperactivity disorder,^1,7,8 and changes in health care policies and capacity have been linked to apparent increased schizophrenia incidence.⁹ It is also feasible that the underlying incidence of certain mental disorders has changed due to socially mediated factors, including economic recession,¹⁰ war and conflict,^11,12 pandemics such as COVID-19,^11,13 and natural disasters.¹⁴ However, large parts of trends in mental disorder incidence remain unexplained.

Several studies have assessed the impact of age, calendar period, and birth cohort on mental disorder incidence.^{15,16,17,18,19,20,21,22,23,24,25,26} However, disentangling these 3 intertwined factors is complicated. On one hand, it is clear that mental disorder incidence varies with age, and different mental disorders have different age-specific patterns,^27,28,29,30 which for some may be shifting.¹ On the other hand, period and cohort effects on changes in mental disorder incidence are difficult to confidently elucidate. Several studies report cohort effects for mental disorders,^{17,19,31,32,33} while others find period effects¹⁵ or a combination of both.^{20,21,22,23,26} However, understanding whether time trends are due to cohort or period effects requires strong assumptions.³⁴

In this study, we aim to assess the changes in sex- and age-specific incidence of different types of mental disorders across the entire spectrum diagnosed in Denmark from 2004 to 2021 according to calendar time and birth cohort. Follow-up includes the first years of the COVID-19 pandemic, which is generally accepted to have affected mental well-being, although a recent systematic review was unable to conclude that this had impacted associated diagnoses.³⁵ The Danish registers allow us to investigate time trends comprehensively with longitudinal nationwide data, which are available in a few countries. With this, we can indicate the differences in incidence over time and between birth cohorts in Denmark, potentially providing a better understanding of trends and what is driving them, which may also be applicable to other countries.

Methods

The study was registered with the Danish Data Protection Agency at Aarhus University and approved by Statistics Denmark and the Danish Health Data Authority. According to Danish law, informed consent or ethical approval is not required for register-based studies in Denmark. All data were pseudonymized and not recognizable at an individual level, and analyzed on the secured platform of Statistics Denmark.

We designed a population-based cohort study including all people aged 1 to 80 years living in Denmark at some point between January 1, 2004, and December 31, 2021 (ie, born between 1924 and 2020). The study population was identified through the Danish Civil Registration System.³⁶ The results were reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Data were analyzed from February to August 2024.

Information on mental disorders was obtained from the Danish Psychiatric Central Research Register,³⁷ which contains admissions to psychiatric inpatient facilities since 1969 and visits to outpatient and emergency psychiatric departments since 1995. We considered chapter V of the International Classification of Diseases, Tenth Revision (ICD-10; F10-F98), excluding organic disorders (F00-F09). Specific disorders (including a category for any mental disorder) were defined using the Danish modification of the ICD-10 from 1994 and corresponding ICD-8 codes from 1969 to 1993 (eTable 1 in Supplement 1).^28,30 Date of onset for each disorder was defined as the date of first contact with the psychiatric care system leading to the diagnosis of the disorder.

For each mental disorder, individuals were followed up from January 1, 2004, or the minimum diagnosis age for that disorder (eTable 1 in Supplement 1), whichever came last; until mental disorder onset, 80th birthday, death, emigration from Denmark, or December 31, 2021, whichever came first. Analyses were based on incident mental disorder diagnoses during follow-up (2004 to 2021). Thus, we excluded individuals diagnosed before follow-up. Starting follow-up in 2004 provided at least 9 years of diagnostic data during which ICD-10 codes were used and outpatient appointments were included in the register. Since follow-up was possible for an 18-year period, most individuals were followed up for only part of their life span. For example, those born January 1, 2003, contributed information from their first birthday to the day before their 19th birthday, while those born January 1, 1980, contributed information from their 24th birthday to the day before their 42nd birthday. All individuals were classified into birth cohorts (1924-1939, 1940-1949, 1950-1959, 1960-1969, 1970-1979, 1980-1989, 1990-1999, 2000-2009, and 2010-2020), and follow-up time was divided into 3-year periods (2004-2006, 2007-2009, 2010-2012, 2013-2015, 2016-2018, and 2019-2021). eFigure 1 in Supplement 1 shows the ages of people born in the first year of each birth cohort as follow-up progressed.

Statistical Analysis

First, we estimated the incidence rate of each mental disorder for each age interval (1, 2, 5, or 10 years; shorter intervals were preferred but this varied to ensure at least 5 cases during each interval) as the number of cases divided by the follow-up time in that age group by sex. We carried out these analyses separately for the 9 birth cohorts and 6 calendar periods. Second, we modeled the incidence rate as a function of age and either birth cohort or calendar period through Poisson generalized additive models,³⁸ including age and either birth cohort or calendar period using penalized splines.³⁸ The incidence rate for a specific birth cohort represents the rate of new diagnoses of a mental disorder within that birth cohort, whereas the incidence rate for a given calendar period indicates the rate of new mental disorder diagnoses in that time period across the entire population (ie, all birth cohorts). If there were too few cases to allow for reporting, the earliest birth cohorts were removed, and the end age was limited to 50 years. Since individuals in the later calendar periods would have a longer washout period to exclude prevalent cases than those in the earlier periods, we performed sensitivity analyses using a fixed 9-year washout period for all individuals. Incidence rates across ages were presented graphically for each birth cohort and calendar period by sex. Comparisons between periods were made qualitatively. All analyses were performed with R version 4.2.1.

Results

A total of 6 222 682 individuals aged 1 to 80 years resided in Denmark during the follow-up period, 286 480 of whom had a previously diagnosed mental disorder. The remaining 5 936 202 individuals (2 933 857 female and 3 002 345 male) were followed up for 83.8 million person-years, and 463 057 were diagnosed with an incident mental disorder (241 522 female and 221 535 male), representing an incidence rate of 55.27 every 10 000 person-years (58.31 for female individuals and 52.29 for male individuals). The median age at the start of follow-up was 30.21 years; at the end of follow-up, it was 46.21 years. eTable 2 in Supplement 1 displays baseline characteristics of the study population, and eTable 3 in Supplement 1 shows the numbers of individuals and incidence rates for all mental disorder types. Figures 1, 2, 3, 4, and 5 and eFigures 2-16 in Supplement 1 display incidence rates according to age, birth cohort, and calendar period.

Age-Specific Incidence Rates of Any Mental Disorder

For female individuals, the highest incidence rate for any mental disorder was observed in the 2000 to 2009 birth cohort with 254.4 (95% CI, 247.2-261.8.1) new cases per 10 000 person-years at age 15 years, followed by the 1990 to 1999 and 1980 to 1989 birth cohorts (Figure 1). For these cohorts, incidence peaked in the late teenage years. After peaking, there was a relatively steep decline in incidence with increasing age. In the youngest birth cohort (2010-2020), incidence of any mental disorder sharply increased with age, with the oldest of this cohort reaching 12 years old by the end of follow-up. In the older birth cohorts (born 1970-1979 and earlier), incidence of any mental disorder declined with age. At each age, the incidence in each of these birth cohorts was similar. There was a slight increase in incidence rate once the age of 65 to 70 years was reached.

For male individuals, the highest incidence rate for any mental disorder was observed in the 2010 to 2020 birth cohort, peaking at age 8 years (161.8; [95% CI, 154.0-169.9] per 10 000 person-years). A similar increase was seen in slightly older cohorts that included this age; however, this then plateaued or decreased slightly, followed by an increase to a peak in the late teenage years. Among the birth cohorts that were followed up over younger ages, incidence was higher in more recent birth cohorts. Among older birth cohorts, differences in incidence rates were similar, decreasing until around age 70 years. The peak absolute incidence rate was lower among male individuals than female individuals for each birth cohort. In the oldest birth cohorts for both sexes, incidence rates were more convergent.

Incidence rate patterns for any mental disorder among both female and male individuals were similar for all calendar periods. A sharp increase occurred in the younger ages (<10 years for male individuals and during the teenage years for female individuals). After peaking and declining, incidence began increasing again at age 65 to 70 years. For female individuals, in the 2019 to 2021 calendar year, peak incidence was reached at age 15 years (272.5 [95% CI, 261.8-283.5] per 10 000 person-years), whereas for male individuals it was reached at age 8 years (158.0 [95% CI, 149.9.6-166.5] per 10 000 person-years). Incidence rates for diagnosis with any mental disorder were stacked by calendar period for both sexes, with the highest peak incidence rate observed during the most recent period and slightly lower rates observed in each preceding period. However, after age 35 years, the incidence rates were similar at each calendar period, until around age 65 years, where the trends reversed and the highest rates were seen in 2004 to 2006.

Age-Specific Incidence Rates of Specific Mental Disorders

Incidence rates of mood disorders in both sexes in younger ages (before age 30 years) were markedly higher in more recent birth cohorts (ie, 1980-1989, 1990-1999, and 2000-2011) and calendar periods (Figure 2). However, at around 30 to 65 years of age, incidence rates were similar between birth cohorts, after which they were slightly higher in older birth cohorts. Similarly, we observed that mood disorder incidence declined in both male and female individuals after age 35 years in the most recent calendar periods. The same trends were observed for bipolar and depressive disorders (eFigures 5 and 6 in Supplement 1). For anxiety-related and obsessive compulsive disorders (eFigures 7 and 8 in Supplement 1), we also observed an increase after age 35 years in the recent birth cohorts and calendar periods, but not the reverse effect after this age, as was observed for mood disorders.

For schizophrenia spectrum disorders, similar patterns were seen as for mood disorders, but differences in rates for female individuals and male individuals were less marked. Incidence rates increased for male individuals but especially for female individuals up until age 30 years by both birth cohort and calendar period (with higher incidences in the most recent birth cohorts and latest periods) (Figure 3). However, at around age 35 years , differences between birth cohorts or calendar periods were no longer apparent. When looking at schizophrenia only (eFigure 4 in Supplement 1), we observed similar patterns for female individuals, but for male individuals, there were no differences according to birth cohort and minor differences for calendar period.

There were no substantial differences for either sex in incidence rates of mental and behavioral disorders due to psychoactive substance use between birth cohorts of 1980 to 1989 up to 2000 to 2011 (followed up until age 30-40 years) or according to calendar period until age 35 years (Figure 4). However, for those born from 1924 to 1969 (followed up from around age 35 years) and for calendar periods after that age, incidence rates decreased slightly for each successive birth cohort and calendar period. This pattern was similar when looking specifically at alcohol use disorder (eFigure 2 in Supplement 1).

Incidence rates for behavioral and emotional disorders with onset usually occurring in childhood and adolescence increased in both sexes by both birth cohort and calendar time, with higher incidences observed for later birth cohorts and more recent calendar years (Figure 5). Patterns for other disorders with typical onset in childhood were similar (eFigures 14-16 in Supplement 1).

Estimates by mental disorder type (eFigures 2-16 in Supplement 1) showed various trends. For example, for eating disorders (eFigures 9 and 10 in Supplement 1), we observed incidence rates increasing over time for female individuals; however, for personality disorders (eFigures 11 and 12 in Supplement 1), we observed an increase for female individuals and a decrease for male individuals born in the later cohorts. Sensitivity analyses with the fixed washout period length provided comparable estimates (examples in eFigures 17 and 18 in Supplement 1).

Discussion

The results of this cohort study suggest that sex- and age-specific incidence rates of mental disorder diagnoses in Denmark varied between birth cohorts and calendar periods. More recent birth cohorts had higher incidence rates of any mental disorder. For the older birth cohorts, who were followed up over older ages, there were not large differences in incidence rates. They were highest in the most recent calendar period and decreased slightly in each preceding period.

The findings for any mental disorder were mainly driven by mood and anxiety disorders, for which similar patterns were observed. However, incidence patterns differed by mental disorder type. For most types, higher rates were observed in more recent birth cohorts and calendar periods for younger ages. In older ages, incidence rates were more convergent, with some exceptions (eg, substance use disorders in both sexes demonstrated higher incidence rates in earlier calendar periods in middle to older age [≥35 years]). We also observed prominent sex differences for both overall incidence rates and trends over time. For example, for schizophrenia, we observed a large increase for female individuals in more recent birth cohorts at younger ages, but no change for male individuals, leading to a higher peak incidence for female than for male individuals in the most recent periods. For personality disorders, we observed a large increase in incidence for female individuals over time and a slight decrease for male individuals.

Similar to previous studies,^{9,15,17,19,20,21,22,26,31,32,39} our findings suggest that mental disorder incidence varies with age, birth cohort, and calendar period. However, general comparisons are challenging, as within-country factors vary (eg, administrative and diagnostic changes occurring at different time points). Our findings indicate that schizophrenia spectrum disorders increased with successive birth cohorts and over successive periods at younger ages, particularly in female individuals. This contrasts a 1999 Finnish study,²³ which described significant decreases in schizophrenia incidence rates across both successive cohorts (attributed to reduced intensity or frequency of an early life risk factor) and periods (attributed to confounding or changes in diagnostic criteria). However, our findings reflect those of other Danish studies, indicating increases in incident schizophrenia spectrum disorders in 2000 to 2012 or 2013 in younger age groups (until approximately 25-35 years)^1,9,39 and female individuals.^1,9 These changes could be explained by implementation of different diagnostic criteria and increased treatment capacity, as well as the increase in use and potency of cannabis in Denmark.⁹ Studies on mood disorders reported increased incidence due to period effects in the US,^17,25 particularly in younger age groups (ie, those aged 12-25 years),¹⁷ and in more recent birth cohorts (ie, post-1950s) in Germany.²⁰ Our findings also suggested higher incidence in these birth cohorts and calendar periods in younger ages; however, the opposite was seen in older age groups. This finding may reflect greater awareness in the general community about depression, increased treatment capacity, and changes in referral practices from general practice (which are not included in Danish registers) to hospital settings (which are included).

Although there may be some true increase in incidence rates, as mentioned above, there are likely multiple other factors involved as well. For example, in Denmark, diagnostic criteria changed from ICD-8 to ICD-10 in 1994; one case register study suggested that the ICD-10 concept of affective disorder appeared to be broader than that in ICD-8.⁴⁰ Changes in the typical age mental health services identify and diagnose mental disorders could be a potential reason for different incidence rates. Increases across all ages in the more recent birth cohorts and calendar periods for all mental disorders during childhood and early adolescence could indicate more recognition or formal diagnoses of neurodevelopmental disorders. These changes are consistent with observed increases in treatment (eg, for attention-deficit/hyperactivity disorder)⁴¹ and recent increases in Danish mental health service capacity following changes in patient rights in 2013.⁴² Furthermore, mental health campaigns^43,44 may have contributed to awareness, encouraging individuals to seek help for mental disorders. Increases in incidence at younger ages and decreases at older ages (eg, for mood disorders) could suggest a shift to earlier diagnoses. While early treatment is ideal, it could create a considerable burden on child and adolescent psychiatry departments (who already have long waiting lists).⁴⁵ However, there have been increases in treatment capacity; a report from the Ministry of the Interior and Health⁴⁶ in Denmark showed that the number of adults, adolescents, and children having contact with mental health services has increased over the period from 2009 to 2022. Alternatively, changes in risk factors that affect different subgroups to varying extents could contribute. For example, cannabis use and potency has been increasing in Denmark,⁹ and a recent Danish study⁴⁷ indicated that associations between cannabis use disorder and schizophrenia varied by sex and age. It is notable that our follow-up period included the initial years of the COVID-19 pandemic, which led to lockdowns and social isolation. These have been suggested to have negatively affected mental health,^13,48,49 including in studies using survey data from Denmark.^50,51 Although sex- and age-specific incidence rates in the calendar period from 2019 to 2021 were higher than preceding calendar periods in younger age groups, this appeared to follow the established trend, and it is unclear whether the COVID-19 pandemic led to observable additional increases in mental disorder diagnoses by the end of 2021 above what may have been expected. However, not enough follow-up time is available yet to draw conclusions about the effect of the pandemic on mental disorder diagnoses and observe whether register data show the same trend as seen in survey data. We hope to revisit these estimates in the future to allow longer periods of follow-up.

Age-cohort-period models are sometimes used to consider the effect of these 3 time-related dimensions on health outcomes. However, these require strong assumptions—issues with which were clearly demonstrated by a reanalysis from Hansen and Parner³⁴ of data used by Keyes et al.¹⁹ Hansen and Parner³⁴ showed that small changes in the assumptions resulted in large changes in findings and, consequently, interpretations. Our results focus on general time trends without specifying if there is a cohort or period effect; thus, they are easily interpretable and do not rely on strong assumptions that may alter findings.

Strengths and Limitations

Our study has several strengths. The nationwide registers provide a large sample size, comprising the entire population of Denmark, minimizing selection bias. Free and equal access to health care⁵² ensures effects associated with the ability to afford private insurance or access to health care are likely negligible. Furthermore, register data are not subject to self-reporting or recall bias.

However, there are several limitations. First, most individuals are only followed up for part of their life span (eFigure 1 in Supplement 1). Information is not available about those in earlier birth cohorts at younger ages, or those in recent birth cohorts at older ages, limiting comparisons across birth cohorts. We cannot capture incident mental disorders after follow-up ends. Additionally, we may misclassify prevalent disorders for incident disorders, although the washout period minimizes this risk. Second, there may be misclassification of the incidence date (and, therefore, age), as the registers record diagnosis date, rather than onset date. Third, the Danish hospital registers were used to identify diagnoses of mental disorders. Data are not available on those treated solely in primary care, nor can we identify individuals who do not seek medical help. Fourth, while our findings can instigate future hypothesis-driven research, the registers do not contain sufficient information to draw inferences about causal pathways leading to observed changes.

Conclusions

In conclusion, our findings indicate particular patterns in sex- and age-specific incidence of mental disorders over time, according to birth cohorts and calendar periods. Some of these changes may indicate actual changes in incidence. Others may be due to variations in diagnostic patterns (eg, administrative changes), secondary health sector capacity or risk factors. Our findings can be used to help understand the changes in mental disorder incidence over time and may help stimulate future hypothesis-driven research on mental disorders and their risk factors.

Supplement 1.

eTable 1. Definition for each mental disorder

eTable 2. Baseline characteristics of the study population (n=5,936,202)

eTable 3. Numbers of individuals and cases, person-years of follow-up and incidence rates for each mental disorder

eFigure 1. Lexis diagram depicting age during follow-up depending on birth year and calendar year

eFigure 2. Age-specific incidence rate of alcohol use disorder by birth cohort and calendar period, for males and females

eFigure 3. Age-specific incidence rate of cannabis use disorder by birth cohort and calendar period, for males and females

eFigure 4. Age-specific incidence rate of schizophrenia by birth cohort and calendar period, for males and females

eFigure 5. Age-specific incidence rate of bipolar disorders by birth cohort and calendar period, for males and females

eFigure 6. Age-specific incidence rate of depressive disorders by birth cohort and calendar period, for males and females

eFigure 7. Age-specific incidence rate of anxiety-related disorders by birth cohort and calendar period, for males and females

eFigure 8. Age-specific incidence rate of obsessive-compulsive disorder by birth cohort and calendar period, for males and females

eFigure 9. Age-specific incidence rate of eating disorders by birth cohort and calendar period, for males and females

eFigure 10. Age-specific incidence rate of anorexia nervosa by birth cohort and calendar period, for males and females

eFigure 11. Age-specific incidence rate of specific personality disorders by birth cohort and calendar period, for males and females

eFigure 12. Age-specific incidence rate of borderline type personality disorder by birth cohort and calendar period, for males and females

eFigure 13. Age-specific incidence rate of intellectual disabilities by birth cohort and calendar period, for males and females

eFigure 14. Age-specific incidence rate of pervasive developmental disorders by birth cohort and calendar period, for males and females

eFigure 15. Age-specific incidence rate of childhood autism by birth cohort and calendar period, for males and females

eFigure 16. Age-specific incidence rate of attention-deficit/hyperactivity disorder by birth cohort and calendar period, for males and females

eFigure 17. Sensitivity analysis - Age-specific incidence rate of substance use disorders by birth cohort and calendar period, for males and females (fixed 9-year washout period for all individuals)

eFigure 18. Sensitivity analysis - Age-specific incidence rate of depressive disorders by birth cohort and calendar period, for males and females (fixed 9-year washout period for all individuals)

jamapsychiatry-e243723-s001.pdf^{(5.4MB, pdf)}

Supplement 2.

Data sharing statement

jamapsychiatry-e243723-s002.pdf^{(15.7KB, pdf)}

References

1.Plana-Ripoll O, Momen NC, McGrath JJ, et al. Temporal changes in sex- and age-specific incidence profiles of mental disorders—a nationwide study from 1970 to 2016. Acta Psychiatr Scand. 2022;145(6):604-614. doi: 10.1111/acps.13410 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Cybulski L, Ashcroft DM, Carr MJ, et al. Temporal trends in annual incidence rates for psychiatric disorders and self-harm among children and adolescents in the UK, 2003-2018. BMC Psychiatry. 2021;21(1):229. doi: 10.1186/s12888-021-03235-w [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Skurtveit S, Bramness JG, Hjellvik V, et al. Increase in diagnosis of depressive disorders contributes to the increase in antidepressant use in adolescents. Acta Psychiatr Scand. 2018;137(5):413-421. doi: 10.1111/acps.12877 [DOI] [PubMed] [Google Scholar]
4.Agudelo-Botero M, Giraldo-Rodriguez L, Rojas-Russell M, et al. Prevalence, incidence and years of life adjusted for disability due to depressive disorders in Mexico: results of the Global Burden of Disease Study 2019. J Affect Disord Rep. 2021;6:100206. doi: 10.1016/j.jadr.2021.100206 [DOI] [Google Scholar]
5.Dykxhoorn J, Osborn D, Walters K, Kirkbride JB, Gnani S, Lazzarino AI. Temporal patterns in the recorded annual incidence of common mental disorders over two decades in the United Kingdom: a primary care cohort study. Psychol Med. 2024;54(4):663-674. doi: 10.1017/S0033291723002349 [DOI] [PubMed] [Google Scholar]
6.GBD 2019 Mental Disorders Collaborators . Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9(2):137-150. doi: 10.1016/S2215-0366(21)00395-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Russell G, Stapley S, Newlove-Delgado T, et al. Time trends in autism diagnosis over 20 years: a UK population-based cohort study. J Child Psychol Psychiatry. 2022;63(6):674-682. doi: 10.1111/jcpp.13505 [DOI] [PubMed] [Google Scholar]
8.Abdelnour E, Jansen MO, Gold JA. ADHD diagnostic trends: increased recognition or overdiagnosis? Mo Med. 2022;119(5):467-473. [PMC free article] [PubMed] [Google Scholar]
9.Kühl JOG, Laursen TM, Thorup A, Nordentoft M. The incidence of schizophrenia and schizophrenia spectrum disorders in Denmark in the period 2000-2012. a register-based study. Schizophr Res. 2016;176(2-3):533-539. doi: 10.1016/j.schres.2016.06.023 [DOI] [PubMed] [Google Scholar]
10.Frasquilho D, Matos MG, Salonna F, et al. Mental health outcomes in times of economic recession: a systematic literature review. BMC Public Health. 2016;16:115. doi: 10.1186/s12889-016-2720-y [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Hou WK, Li TW, Liang L, et al. Trends of depression and anxiety during massive civil unrest and COVID-19 in Hong Kong, 2019-2020. J Psychiatr Res. 2021;145:77-84. doi: 10.1016/j.jpsychires.2021.11.037 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Charlson F, van Ommeren M, Flaxman A, Cornett J, Whiteford H, Saxena S. New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis. Lancet. 2019;394(10194):240-248. doi: 10.1016/S0140-6736(19)30934-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.COVID-19 Mental Disorders Collaborators . Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. Lancet. 2021;398(10312):1700-1712. doi: 10.1016/S0140-6736(21)02143-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Keya TA, Leela A, Habib N, Rashid M, Bakthavatchalam P. Mental health disorders due to disaster exposure: a systematic review and meta-analysis. Cureus. 2023;15(4):e37031. doi: 10.7759/cureus.37031 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Keyes KM, Nicholson R, Kinley J, et al. Age, period, and cohort effects in psychological distress in the United States and Canada. Am J Epidemiol. 2014;179(10):1216-1227. doi: 10.1093/aje/kwu029 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Salway T, Gesink D, Ferlatte O, et al. Age, period, and cohort patterns in the epidemiology of suicide attempts among sexual minorities in the United States and Canada: detection of a second peak in middle adulthood. Soc Psychiatry Psychiatr Epidemiol. 2021;56(2):283-294. doi: 10.1007/s00127-020-01946-1 [DOI] [PubMed] [Google Scholar]
17.Twenge JM, Cooper AB, Joiner TE, Duffy ME, Binau SG. Age, period, and cohort trends in mood disorder indicators and suicide-related outcomes in a nationally representative dataset, 2005-2017. J Abnorm Psychol. 2019;128(3):185-199. doi: 10.1037/abn0000410 [DOI] [PubMed] [Google Scholar]
18.Askari MS, Mauro PM, Kaur N, Keyes KM. Age, period, and cohort trends in perceived mental health treatment need and differences by mental health severity in the United States, 2008-2019. Community Ment Health J. 2023;59(4):631-640. doi: 10.1007/s10597-022-01044-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Keyes KM, Susser E, Cheslack-Postava K, Fountain C, Liu K, Bearman PS. Cohort effects explain the increase in autism diagnosis among children born from 1992 to 2003 in California. Int J Epidemiol. 2012;41(2):495-503. doi: 10.1093/ije/dyr193 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Beller J. Age-period-cohort analysis of depression trends: are depressive symptoms increasing across generations in Germany? Eur J Ageing. 2022;19(4):1493-1505. doi: 10.1007/s10433-022-00732-z [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Dong W, Liu Y, Sun J, Liu Y, Sun Z, Bai R. Temporal trends in the incidence and disability adjusted life years of schizophrenia in China over 30 years. Front Psychiatry. 2022;13:831188. doi: 10.3389/fpsyt.2022.831188 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Okui T. An age-period-cohort analysis for prevalence of common psychiatric disorders in Japan, 1999-2017. Soc Psychiatry Psychiatr Epidemiol. 2021;56(4):639-648. doi: 10.1007/s00127-020-01988-5 [DOI] [PubMed] [Google Scholar]
23.Suvisaari JM, Haukka JK, Tanskanen AJ, Lönnqvist JK. Decline in the incidence of schizophrenia in Finnish cohorts born from 1954 to 1965. Arch Gen Psychiatry. 1999;56(8):733-740. doi: 10.1001/archpsyc.56.8.733 [DOI] [PubMed] [Google Scholar]
24.Thomson RM, Katikireddi SV. Mental health and the jilted generation: Using age-period-cohort analysis to assess differential trends in young people’s mental health following the Great Recession and austerity in England. Soc Sci Med. 2018;214:133-143. doi: 10.1016/j.socscimed.2018.08.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Wickramaratne PJ, Weissman MM, Leaf PJ, Holford TR. Age, period and cohort effects on the risk of major depression: results from five United States communities. J Clin Epidemiol. 1989;42(4):333-343. doi: 10.1016/0895-4356(89)90038-3 [DOI] [PubMed] [Google Scholar]
26.Wu J, Lin Z, Liu Z, He H, Bai L, Lyu J. Secular trends in the incidence of eating disorders in China from 1990 to 2017: a joinpoint and age-period-cohort analysis. Psychol Med. 2022;52(5):946-956. doi: 10.1017/S0033291720002706 [DOI] [PubMed] [Google Scholar]
27.Solmi M, Radua J, Olivola M, et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol Psychiatry. 2022;27(1):281-295. doi: 10.1038/s41380-021-01161-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Pedersen CB, Mors O, Bertelsen A, et al. A comprehensive nationwide study of the incidence rate and lifetime risk for treated mental disorders. JAMA Psychiatry. 2014;71(5):573-581. doi: 10.1001/jamapsychiatry.2014.16 [DOI] [PubMed] [Google Scholar]
29.McGrath JJ, Al-Hamzawi A, Alonso J, et al. ; WHO World Mental Health Survey Collaborators . Age of onset and cumulative risk of mental disorders: a cross-national analysis of population surveys from 29 countries. Lancet Psychiatry. 2023;10(9):668-681. doi: 10.1016/S2215-0366(23)00193-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Beck C, Pedersen CB, Plana-Ripoll O, et al. A comprehensive analysis of age of onset and cumulative incidence of mental disorders: a Danish register study. Acta Psychiatr Scand. 2024;149(6):467-478. doi: 10.1111/acps.13682 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Sunderland M, Carragher N, Buchan H, Batterham PJ, Slade T. Comparing profiles of mental disorder across birth cohorts: results from the 2007 Australian National Survey of Mental Health and Wellbeing. Aust N Z J Psychiatry. 2014;48(5):452-463. doi: 10.1177/0004867413512382 [DOI] [PubMed] [Google Scholar]
32.Yoo C. The birth cohorts difference in depression. Child Indic Res. 2023;16(3):997-1017. doi: 10.1007/s12187-022-09985-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Schendel DE, Thorsteinsson E. Cumulative incidence of autism into adulthood for birth cohorts in Denmark, 1980-2012. JAMA. 2018;320(17):1811-1813. doi: 10.1001/jama.2018.11328 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Hansen SN, Parner ET. Cohort effects explain the increase in autism diagnosis: an identifiability problem of the age-period-cohort model. Int J Epidemiol. 2014;43(6):1988-1989. doi: 10.1093/ije/dyu213 [DOI] [PubMed] [Google Scholar]
35.Sun Y, Wu Y, Fan S, et al. Comparison of mental health symptoms before and during the covid-19 pandemic: evidence from a systematic review and meta-analysis of 134 cohorts. BMJ. 2023;380:e074224. doi: 10.1136/bmj-2022-074224 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Pedersen CB. The Danish civil registration system. Scand J Public Health. 2011;39(7)(suppl):22-25. doi: 10.1177/1403494810387965 [DOI] [PubMed] [Google Scholar]
37.Mors O, Perto GP, Mortensen PB. The Danish Psychiatric Central Research Register. Scand J Public Health. 2011;39(7)(suppl):54-57. doi: 10.1177/1403494810395825 [DOI] [PubMed] [Google Scholar]
38.Carstensen B. Parametrization and prediction of rates. Epidemiology with R. Oxford University Press; 2020. doi: 10.1093/oso/9780198841326.001.0001 [DOI] [Google Scholar]
39.Christensen TN, Wallstrøm IG, Eplov LF, Laursen TM, Nordentoft M. Incidence rates and employment trends in schizophrenia spectrum disorders, bipolar affective disorders and recurrent depression in the years 2000-2013: a Danish nationwide register-based study. Nord J Psychiatry. 2022;76(3):225-232. doi: 10.1080/08039488.2021.1952304 [DOI] [PubMed] [Google Scholar]
40.Kessing L. A comparison of ICD-8 and ICD-10 diagnoses of affective disorder—a case register study from Denmark. Eur Psychiatry. 1998;13(7):342-345. doi: 10.1016/S0924-9338(99)80700-7 [DOI] [PubMed] [Google Scholar]
41.Dalsgaard S, Nielsen HS, Simonsen M. Five-fold increase in national prevalence rates of attention-deficit/hyperactivity disorder medications for children and adolescents with autism spectrum disorder, attention-deficit/hyperactivity disorder, and other psychiatric disorders: a Danish register-based study. J Child Adolesc Psychopharmacol. 2013;23(7):432-439. doi: 10.1089/cap.2012.0111 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Sundhedsstyrelsen. Udrednings og behandlingsretten (The right to evaluation and treatment). Accessed May 2, 2023. https://www.sst.dk/da/Borger/Patientrettigheder/Udredningsret-og-behandlingsret
43.headpsace. Accessed May 1, 2024. https://headspace.dk/
44.EN AF OS . Sundhedsstyrelsen. Accessed May 1, 2024. https://www.sst.dk/da/en-af-os
45.Hansen AS, Kjaersdam Telléus G, Færk E, Mohr-Jensen C, Lauritsen MB. Help-seeking pathways prior to referral to outpatient child and adolescent mental health services. Clin Child Psychol Psychiatry. 2021;26(2):569-585. doi: 10.1177/1359104521994192 [DOI] [PubMed] [Google Scholar]
46.Indenrigs- og Sundhedsministeriet . Sundhedsstrukturkommissionens baggrundsrapport. 2024. https://www.ism.dk/Media/638536236116325595/Baggrundsrapport%20-%20Sundhedsstrukturkommissionen.pdf
47.Hjorthøj C, Compton W, Starzer M, et al. Association between cannabis use disorder and schizophrenia stronger in young males than in females. Psychol Med. 2023;53(15):7322-7328. doi: 10.1017/S0033291723000880 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Jeffers A, Meehan AA, Barker J, et al. Impact of social isolation during the COVID-19 pandemic on mental health, substance use, and homelessness: qualitative interviews with behavioral health providers. Int J Environ Res Public Health. 2022;19(19):12120. doi: 10.3390/ijerph191912120 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Liozidou A, Varela V, Vlastos DD, et al. Forced social isolation and lockdown during the COVID-19 pandemic: depression, anxiety, trauma-distress and coping mechanisms of a Greek sample. Z Gesundh Wiss. Published online April 13, 2023. doi: 10.1007/s10389-023-01907-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Cardona M, Andersen LH, Fallesen P, Bruckner TA. Stress/depression across the COVID-19 pandemic in Denmark. BMC Public Health. 2023;23(1):169. doi: 10.1186/s12889-023-15129-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Andreasen SM, Nielsen S, Fjorback LO, Jensen TK, Juul L. The impact of the Covid-19 pandemic on mental health in Danish school children in 5th to 7th grade. Scand J Public Health. 2024;52(3):336-344. doi: 10.1177/14034948241228907 [DOI] [PubMed] [Google Scholar]
52.Schmidt M, Schmidt SAJ, Adelborg K, et al. The Danish health care system and epidemiological research: from health care contacts to database records. Clin Epidemiol. 2019;11:563-591. doi: 10.2147/CLEP.S179083 [DOI] [PMC free article] [PubMed] [Google Scholar]

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