This chapter investigates trends in mental ill health across OECD and EU countries from 1990 to 2021, focussing on four prevalent conditions: depressive disorders, anxiety disorders, alcohol use disorders and substance use disorders. The analysis considers factors often linked to the recent decline in mental well-being, such as the COVID‑19 pandemic, the climate crisis and problematic use of social media. The chapter also examines the distribution of mental ill health across the population, looking at inequities by age, gender and socio-demographic group, and discusses the extent of unmet mental healthcare needs across these countries.
The Economic Case for Preventing Mental Ill Health
Abstract
Mental ill health is a significant public health challenge. Modelled data suggest that in 2023 slightly over one in five individuals in OECD and EU countries experienced a mental disorder. The majority of these conditions were depressive and anxiety disorders.
In OECD and EU countries, prevalence of mental disorders reached its highest point during the COVID‑19 pandemic, and some long-term upward trends are also emerging. These trends may be linked to increasing rates of depressive and anxiety disorders. Prevalence of alcohol use and substance use disorders has remained relatively stable.
A range of factors are hypothesised to be contributing to these trends, including the influence of the COVID‑19 pandemic, the climate crisis, war and conflict, the cost-of-living crisis and growing economic inequality, and the rising use of social media among children and adolescents.
In 2023, prevalence of mental disorders was highest among individuals aged 15‑19. In most age groups (except children under 10 and adults aged 60‑74), women experienced higher levels of mental ill health than men. Further, people on low incomes and those with lower levels of educational attainment experienced disproportionate levels of mental ill health.
With rising levels of mental ill health, a range of barriers contribute to a lack of access to mental healthcare. It is estimated that only one in three people with mental health needs received access to treatment for their condition in the last 12 months across EU countries.
Mental health is a pivotal component of individuals’ overall health and well-being. A state of good mental health enhances the capacity for interpersonal engagement, cognitive performance, adaptive coping mechanisms and holistic flourishing (WHO, 2022[1]). Conversely, mental ill health refers to a spectrum of conditions, ranging from mild forms of depression, anxiety, and alcohol and drug use disorders to severe disorders such as schizophrenia, bipolar disorders, and severe forms of depression and anxiety (Charlson et al., 2019[2]; Fagiolini and Goracci, 2009[3]). Mental ill health has negative effects on an individual’s quality of life, as well as being associated with heightened risks of comorbidities such as diabetes and obesity; hypertension; respiratory, vascular, kidney and gastrointestinal diseases; and cancer (Pizzol et al., 2023[4]).
In addition to direct suffering and health impacts, mental ill health leads to significant economic costs. Costs arise both through health system expenditure associated with preventing and treating mental ill health and through costs associated with reduced workforce productivity. Chapter 3 delves deeper into these costs, providing detailed quantifications and projections of the health and economic impacts of mental ill health using the OECD SPHeP-NCDs model. It reveals that anxiety, depression and alcohol use disorders are expected to constitute about 6% of annual healthcare expenditure in the 27 EU Member States, Iceland, Norway and Switzerland from 2025 to 2050. Additionally, these conditions are estimated to reduce GDP by an average of 1.7% across these 30 countries, owing to their detrimental effects on productivity and human capital. Notably, the extent of the economic costs is related to the severity of mental ill health, with higher costs strongly associated with higher levels of severity (König et al., 2023[5]).
Slightly over one in five people in EU countries experienced a mental disorder in 2023
A mental disorder is characterised by a clinically significant disturbance in an individual’s cognition, emotional regulation or behaviour, and is typically associated with impairment in important areas of functioning (WHO, 2022[6]). Nearly 21% of people across EU countries and 21% across OECD countries experienced a mental disorder in 2023 (Figure 2.1) (IHME, 2026[7]).
Note: Prevalence data are presented cumulatively, which may overestimate total mental disorder prevalence because individuals with multiple conditions can be counted more than once. Conversely, underreporting – for example, driven by stigma and health system limitations – may lead to underestimation of single‑condition prevalence. Depressive disorders include major depressive disorders, along with other depressive disorders; anxiety disorders include generalised anxiety disorders, among other anxiety disorders. The data presented are modelled using a range of country‑specific sources, which may limit the degree of cross‑country comparability.
Source: IHME (2026[7]), GBD Compare Data Visualization, https://vizhub.healthdata.org/gbd-compare.
These figures include the following five categories of mental disorders:
Depressive disorders are characterised by a depressed mood, such as a feeling of sadness, irritability or emptiness, or by a loss of pleasure in activities (WHO, 2026[8]; APA, 2013[9]). Major depressive disorders are the most common subtype of depressive disorders (Li et al., 2023[10]). They are characterised as episodic mood disorders, involving the experience of one of more major depressive episodes, which is either a depressed mood or loss of interest/pleasure, for most of every day, for at least two weeks. Like other depressive disorders, major depressive disorders vary across levels of severity, ranging from mild through moderate to severe.
Anxiety disorders are characterised by excessive fear, anxiety and associated behaviours. This disorder spectrum covers separation anxiety disorders, selective mutism, specific phobias, social anxiety disorders, panic disorders, agoraphobia and generalised anxiety disorders (APA, 2013[9]). Generalised anxiety disorders are among the most common. These are characterised by persistent and excessive worry about a number of domains in a person’s life, which is present for at least six months and causes significant distress and/or impairment in an individual’s functioning (Spitzer et al., 2006[11]; Mortazavi et al., 2014[12]).
Psychotic disorders are a heterogenous group of conditions – including bipolar disorders – that is characterised by episodic mood changes, where periods of mania, hypomania or mixed symptoms often alternate with episodes of depression or periods marked by depressive symptoms throughout the disorder (WHO, 2026[8]). Related conditions such as schizophrenia also include disturbance in a variety of mental functions, such as flow of thoughts, perception, self-experience, cognition, mood and behaviour.
Substance use disorders are characterised by a cluster of cognitive, behavioural and physiological symptoms. These symptoms include the individual persisting in using the substance despite adverse consequences (APA, 2013[9]). Alcohol use disorders are a type of substance use disorder defined by an inability to control alcohol consumption, compulsive drinking behaviour and a negative emotional state during periods of abstinence. Drug use disorders are also a type of substance use disorder. Ten separate classes of drugs come under this umbrella – including, for example, cannabis, hallucinogens and opioids.
The category of other disorders includes all other mental health conditions not captured in the categories above, such as eating disorders, autism spectrum disorders, attention deficit/hyperactivity disorders and conduct disorders, among others.
As shown in Figure 2.1, depressive and anxiety disorders account for more than half of mental disorders, with 8% of the population of the EU experiencing anxiety disorders and 4.2% experiencing depressive disorders. These are followed by substance use disorders at 3.5% and bipolar disorders and schizophrenia, which affect 1.0% of the population. Across EU countries, there is variability in the prevalence of these mental disorders: the lowest proportions were reported in Bulgaria (16.4%) and Romania (16.6%), while the Netherlands experienced the highest level (27.1%).
When interpreting epidemiological estimates for mental disorders, it is crucial to exercise caution due to various factors that limit the reliability of these estimates. In particular, the following factors should be considered when analysing the results presented in Figure 2.1:
Prevalence rates may underestimate prevalence of mild to moderate conditions that may not be detected, for example, when they do not meet the clinical criteria for a diagnosis or due to underreporting caused by stigma (see Box 2.1).
The cumulative figures are likely to overestimate the overall prevalence of mental disorders across the population, as individuals may experience multiple disorders simultaneously, leading to double counting.
Cross‑country differences may also reflect other factors, such as variations in disclosure and reporting – for example, driven by differing levels of stigma and self‑reporting, as well as methodological differences – rather than true differences in underlying prevalence.
Mental ill health is a continuum rather than a static state. Symptoms of mental disorders can emerge and fluctuate over time. A broad range of tools and symptom scales exist to assess the presence and severity of a mental disorder at a given time. Symptom scales have been increasingly incorporated into national health surveys to assess measure population mental health. For instance, PHQ‑8 is used in the 2019 European Health Interview Survey, the Korea Community Health Survey 2019, and the United States National Health Interview Survey 2019. These tools provide an important way to measure current states of mental health and to identify trends and patterns in population mental health over time (OECD, forthcoming[13]). Examples of three frequently used screening tools for major depressive and anxiety disorders are summarised below.
Screening tools for symptom severity
Screening tools help to assess the severity of mental disorders such as major depressive and anxiety disorders, and to evaluate the impact of mental health interventions. For instance, the 9‑item Patient Health Questionnaire (PHQ‑9) and the shorter PHQ‑8 are validated scales to assess the severity of depressive symptoms. Depressive symptom scales can be a good indicator to measure population-level mental health. An analysis of national survey data from 22 OECD countries shows a strong positive correlation between the share of people who reported having moderate and severe depressive symptoms and those who were diagnosed with depression by a doctor in the last 12 months (Wei et al., 2016[14]). Similarly, GAD‑7 has been shown to be a valid tool for anxiety symptom severity (Kroenke et al., 2009[15]; Spitzer et al., 2006[11]). The Alcohol Use Disorders Identification Test (AUDIT), which is composed of 10 questions, and AUDIT-C – a shorter version, composed of 3 questions – are screening tools developed by the WHO, commonly used in the identification of alcohol use disorders in a primary healthcare setting (Babor et al., 2011[16]). Of course, in the absence of a full clinical diagnostic process, these tools can be subject to measurement error or risk of under- or over-diagnosis.
Table 2.1 provides a summary of the scales used by these three screening tools to identify the presence and/or severity of a mental disorder.
Sources: Kroenke et al. (2009[15]), “The PHQ-8 as a measure of current depression in the general population”, https://doi.org/10.1016/j.jad.2008.06.026; Spitzer et al. (2006[11]), “A brief measure for assessing generalized anxiety disorder: The GAD-7”, https://doi.org/10.1001/archinte.166.10.1092; Babor and Robaina (2016[17]), “The Alcohol Use Disorders Identification Test (AUDIT): A review of graded severity algorithms and national adaptations”, https://doi.org/10.7895/ijadr.v5i2.222.
Prevalence of mental disorders peaked during the COVID‑19 pandemic
OECD analysis of modelled data from IHME suggests that there was an upward trend in prevalence of mental disorders from 1990 to 2023, as shown in Figure 2.2 (IHME, 2026[7]). On average, prevalence of mental disorders in EU countries increased by 21.1% – from 17.0% in 1990 to 20.6% in 2023. The highest increase (37.9%) was found in Malta, where prevalence rose from 17.3% to 23.9%, followed by Ireland (34.8% increase). These findings align with previous research suggesting that mental ill health has been increasing over recent decades (Fu et al., 2013[18]; ten Have et al., 2023[19]; Compton et al., 2006[20]; Richter et al., 2019[21]). Most countries experienced the majority of the increase in prevalence of mental disorders between 2006 and 2023. This trend supports the hypothesis that various shocks and factors – such as the impact of COVID‑19, climate change, war, conflict, political unrest and economic stressors – have adversely affected mental health in recent years, as discussed in the following section. Other research argues, however, that mental ill health may have remained constant over this period, but the rise in prevalence is a result of demographic changes and increased reporting of mental ill health due to increased mental health literacy, reduced stigma and other factors that have led to more accurate diagnosis and reporting – particularly of mild and moderate cases (Richter et al., 2019[21]; Baxter et al., 2014[22]).
Note: Anxiety disorders, bipolar disorders, depressive disorders, schizophrenia, substance use disorders and others (attention deficit and hyperactivity disorders, autism spectrum disorders, conduct disorders, eating disorders and other mental disorders) were included. It is likely that cumulative numbers are an overestimate, as individuals experiencing multiple disorders at once would be double counted in cumulative tallies.
Source: IHME (2026[7]), GBD Compare Data Visualization, https://vizhub.healthdata.org/gbd-compare.
Major depressive and anxiety disorders are the leading contributors to the burden of mental ill health
Understanding whether patterns are consistent across mental disorders is essential for identifying what drives them, and for targeting interventions toward the conditions with the highest prevalence and fastest acceleration. As the number of mental conditions is extensive, this chapter limits the scope of analysis to four of the leading conditions: major depressive disorders, anxiety disorders, and alcohol use and drug use disorders. Examining the trends for these four conditions reveals that prevalence of major depressive and anxiety disorders has increased throughout the study period, especially since 2006.
Figure 2.3 shows that prevalence of major depressive disorders in EU countries rose from 2.2% in 1990 to 3.1% in 2023, representing a 39.4% increase. These trends were consistent across most European regions1 and OECD Member countries. Over the same period, prevalence of anxiety disorders increased from 4.8% to 8% in EU countries; a trend also mirrored across all European regions and OECD countries. However, these same trends were not observed in prevalence of alcohol use and drug use disorders. The rate of alcohol use disorders remained 2.8% between 1990 and 2006, then decreased to 2.7% in 2023. The highest decline was observed in the Northern Europe region, where the rate of alcohol use disorders decreased from 3.2% in 1990 to 2.7% in 2023; a reduction of almost 15.0%. Similarly, the average rate of drug use disorders remained 0.9% between 1990 and 2006, then declined to 0.8% in 2023. The highest decrease was observed in the Western Europe region, where the rate of drug use disorders declined from 1.2% in 1990 to 1.0% in 2023. Only the Northern Europe region experienced an important rise, from 0.9% in 1990 to 1.1% in 2023. Depressive and anxiety disorders together accounted for the majority of mental disorders; as such, the increases in these disorders seem to be driving the overall trend for rising levels of mental ill health.
Note: Error bars represent the standard deviation of prevalence, indicating cross-country variability of prevalence within each European region.
Source: IHME (2026[7]), GBD Compare Data Visualization, https://vizhub.healthdata.org/gbd-compare.
As highlighted, overall rates of mental ill health are high and have increased over recent decades, with most of the rise occurring in recent years. A rapid literature review highlighted several social, economic and lifestyle factors thought to have contributed to the observed trends. In some instances, such as in the case of recent wars and conflicts, the impact of these events is not yet reflected in the available statistics, suggesting that the situation may have worsened further. Some of these factors are discussed below.
The COVID‑19 pandemic had a significant influence on mental well-being
The COVID‑19 pandemic not only caused anxiety and stress as a major public health crisis; global measures imposed to control the spread of the virus also affected mental health (OECD, 2023[23]; Holmes et al., 2020[24]). Lockdowns, border closures, business and work closures, work-from-home mandates, and a broad range of other measures had significant impacts on social lives, economic and housing stability, significantly affecting quality of life and mental health (OECD, 2021[25]; OECD, 2021[26]). As shown in Figure 2.4, these substantial impacts appear to have had a significant impact on prevalence of depression and anxiety, which rose following the onset of the COVID‑19 pandemic. In 2019, the rate of major depressive disorders in EU countries was 2.4%, and by 2023, this had increased to 3.1%. The highest increase was observed in Southern Europe, where prevalence of major depressive disorders increased from 2.5% (2019) to 3.2% (2023). At the same time, prevalence of anxiety disorders across EU countries also increased, from 5.7% in 2019 to 8.0% in 2023. The highest prevalences were observed in Southern Europe, where the rates reached to 11.0% in 2023. These detrimental mental health impacts are hypothesised to be associated with the international public health measures put in place to slow the spread of the virus, which resulted in social isolation, economic insecurity job precarity and other factors that were likely to contribute to declining mental health (Leung et al., 2022[27]). Recent evidence from various sources suggests that in Europe mental ill health may mostly have recovered to pre‑pandemic levels, while other studies suggest there may be legacy effects – particularly among children and adolescents (Ahmed et al., 2023[28]; Kiviruusu et al., 2024[29]; Ma, Yao and Hao, 2022[30]). As subsequent waves of data become available, it is expected to become clearer whether, and to what extent, the COVID‑19 pandemic has resulted in a “scarring” effect, increasing and keeping rates of mental ill health high over the longer term (Mitrea et al., 2024[31]; Zhu et al., 2024[32]).
Unlike major depressive and anxiety disorders, prevalence of alcohol use disorders stayed constant, and prevalence of drug use disorders declined slightly over the period 2019-2023. Prevalence of alcohol use disorders in the EU stayed at 2.7%, as shown in Figure 2.4. Moreover, prevalence of drug use disorders declined slightly between 2019 and 2023 across most EU countries. Indeed, an average 1.1% decrease in drug use disorders was observed between 2019 and 2021, and then a further 0.7% decrease to 2023.These trends appear to follow previous trends in drug use disorders in Europe (Rehm et al., 2019[33]). These changes have been argued to be a result of reduced availability of illicit drugs – a result of border closures, which reduced accessibility and demand for drugs typically used in recreational settings (Zaami, Marinelli and Vari, 2020[34]). While this would appear to be a positive outcome overall, it is potentially obscuring a change in types of drug use disorders, which could be damaging overall. For example, it may conceal substitution with other drugs, such as prescription drugs or narcotics, which are available online and which may have serious impacts on health and economic costs of drug use disorders.
Note: Error bars represent the standard deviation of prevalence, indicating cross-country variability of prevalence within each European region.
Source: IHME (2026[7]), GBD Compare Data Visualization, https://vizhub.healthdata.org/gbd-compare.
The climate crisis has contributed to worsening mental health
Over the last decade, the impact of climate change is increasingly evident and salient, with extreme events such as wildfires, flooding and heat events becoming more frequent and severe. These events, and the understanding of the future risks associated with projected climate change, have been associated with increased levels of mental ill health – from elevated stress through to severe mental conditions (Ebi et al., 2021[35]; Makwana, 2019[36]; OECD, 2023[37]; Crimmins et al., 2016[38]). So-called “climate anxiety”, characterised by pervasive fear and worry about the future of the planet, has emerged as a significant concern and contributor to mental ill health (Sampaio and Sequeira, 2022[39]). Young people have been shown to be particularly affected by the psychological impacts of the climate crisis due to their unique and acute awareness of how climate change will affect their quality of life and the world around them (Whitlock, 2023[40]). Indeed, in an international survey of more than 10 000 children and young people, 84% were either moderately or extremely worried about climate change, and more than 45% stated that climate change negatively affected their daily lives and functioning (Hickman et al., 2021[41]). Further, climate migration driven by the loss of habitable land and resources compounds these challenges by disrupting lives and communities, leading to grief, anxiety and loss of identity for those forced to relocate (Kanthee et al., 2024[42]). Similarly, the trauma of living through extreme weather events, combined with the chronic stress of climate uncertainty, has been linked to worsening mental health – particularly among vulnerable populations (Filho et al., 2022[43]; Zhang et al., 2022[44]; Zhang, Zhang and Dai, 2022[45]). These combined effects of the climate crisis are already having a marked effect on population mental health, which is only expected to increase in severity as the impacts of climate change become more severe over coming decades.
Housing, environment and social contexts are important determinants of mental health
Housing quality, affordability and stability are increasingly recognised as important determinants of mental health. Inadequate or insecure housing is associated with elevated levels of stress, anxiety and depressive symptoms – particularly among low‑income and vulnerable populations (The Lancet Public Health, 2025[46]), including children and young people (Schwartz et al., 2025[47]). Beyond the home itself, broader features of the built environment – including, for example, access to green spaces, pedestrian infrastructure and well‑designed public areas – have also been linked to lower stress, improved well-being and increased opportunities for restorative experiences (Xian et al., 2024[48]). Growing evidence also indicates that safer neighbourhoods and reduced exposure to crime contribute to better mental health by supporting a greater sense of security, and facilitating community participation (Bogar, 2016[49]). Together, these environmental factors shape everyday experiences in ways that influence psychological resilience and mental well-being.
Social conditions beyond the built environment also play a central role. Higher levels of social cohesion and opportunities for social participation help to protect against loneliness and social isolation, which are factors increasingly associated with poor mental health. Evidence from recent longitudinal research shows that strong social connectedness – including social support, larger social networks and lower levels of loneliness – is consistently associated with reduced risks of depression, anxiety and other adverse mental health outcomes (Wickramaratne et al., 2024[50]). Findings from the analyses reviewed by that study suggest that higher social connectedness protected against later depressive symptoms and disorders, while loneliness at baseline was repeatedly linked to worse outcomes at follow‑up, including increased risk of major depressive disorders and greater severity of depressive and anxiety symptoms.
War and conflict have a profound influence on mental health
War, conflict and geopolitical unrest have long been understood to be associated with increased rates of mental ill health: conditions like generalised anxiety, depressive and post-traumatic stress disorders occur at higher rates in regions and at times of war and conflict (Suhaiban, Grasser and Javanbakht, 2019[51]; Charlson, van Ommeren and Flaxman, 2019[52]; Abudayya et al., 2023[53]). In recent years, the effects of war and conflict in Ukraine (see Box 2.2), the Middle East and beyond have been associated with increases in mental ill health – both within and outside the regions directly affected (Charlson, van Ommeren and Flaxman, 2019[52]; Carpiniello, 2023[54]). Studies of previous and ongoing war and conflict have confirmed that exposure to these events has a scarring effect, negatively affecting individuals’ mental health over the life course (McFarlane, 2015[55]). This is true both for professional combatants exposed directly to frontline contexts and for civilians and broader populations, including civilians living in countries that are not directly engaged in war or conflict (Kalaitzaki et al., 2024[56]). The mental health effects of exposure to war and conflict are particularly pronounced for children and adolescents, for whom such exposure significantly raises their lifetime risk of developing a mental disorder (Akbulut-Yuksel, Zimmer and Pandey, 2024[57]). For example, Viet Nam War survivors who were aged 6‑9 at the time of exposure to war were more than three times more likely to experience post-traumatic stress disorder than those who had no, or less, exposure to war. Furthermore, evidence suggests that exposure to wartime events leads to long-term effects and intergenerational trauma, meaning that the effects of current conflicts could adversely affect mental health for decades to come (Ventriglio et al., 2024[58]). As such, the impacts of any given war or conflict can be expected to have vast and far-reaching consequences for mental ill health – not only during wartime but over subsequent decades and generations.
The Russian Federation’s full-scale invasion of Ukraine, launched on 24 February 2022, has been associated with significant impacts to population mental health for Ukrainians living both within and outside Ukraine (Kurapov et al., 2023[59]). Indeed, one year after the invasion, a study of 2 364 adults aged 18‑79 living in Ukraine found that 44.2% had depressive symptoms, 23.1% had anxiety symptoms and 14.4% had probable post-traumatic stress disorder (Wang et al., 2024[60]). Another study looked at the mental health of 8 096 Ukrainian adolescents living both in Ukraine and abroad since 2022. It found that almost half (49.6%) of adolescents living in Ukraine were directly exposed to war; 32.0% screened positive for moderate or severe depression, 17.9% for moderate or severe anxiety, 35.0% for clinically relevant psychological trauma, 29.5% for eating disorders and 20.5% for medium or higher risk of substance use disorders (Goto et al., 2024[61]). The psychological symptoms were of a similar magnitude for Ukrainian adolescents living abroad. Unfortunately, the ongoing war and associated high levels of need for mental healthcare has exposed weaknesses in the Ukrainian mental healthcare system, which is struggling to meet the needs of its population due to a lack of financial and human resources, as well as destruction of critical infrastructure (Seleznova et al., 2023[62]; Martsenkovskyi et al., 2024[63]). Another study found that the detrimental effects of the war are not limited to Ukrainians (Kalaitzaki et al., 2024[56]). Although Ukrainians’ mental health was the most severely affected by the Russian Federation’s full-scale invasion, among 11 countries with differing levels of proximity to Ukraine, non-Ukrainian citizens were also affected. The most significant impacts were found among those countries bordering Ukraine (such as Romania and Poland), with less significant mental health impacts among more distant countries (including Ecuador and Peru).
The cost-of-living crisis and growing economic inequality are increasing rates of mental ill health
Economic crises have long been known to be associated with increases in mental ill health: the effects of job precarity, job loss and prolonged unemployment all have a detrimental influence on mental well-being (WHO Regional Office for Europe, 2011[64]; The Lancet Regional Health – Europe, 2023[65]). Recent macroeconomic shocks and trends have been found to be associated with increased rates of mental ill health, including the economic effects of the COVID‑19 pandemic, rising rates of income inequality, and increasing levels of job precarity and automatability (Lordan and Stringer, 2022[66]; Simonse et al., 2022[67]). In 2022, inflation in OECD countries reached the highest levels seen in four decades, resulting in a rapid increase in the cost of living as essentials such as energy, housing and food prices rose faster than real wages (Causa et al., 2022[68]). These effects disproportionately affect individuals on low incomes, who are particularly vulnerable to the effects of inflation on increasing costs of living (Bhat and Rather, 2012[69]; Barr, Kinderman and Whitehead, 2015[70]; Causa et al., 2022[68]).
Even in the absence of economic shocks and crises, however, recent research suggests that that increasing levels of income inequality are associated with increased mental ill health – not only among those who experience hardship and deprivation as a result of lower incomes but across the entire population (Tibber et al., 2022[71]; Ribeiro, Bauer and Andrade, 2017[72]). Indeed, a systematic review and meta‑analysis of 26 studies from high-income countries revealed that the risk of depression was 1.19 times (risk ratio) higher among populations with higher levels of income inequality (Patel et al., 2018[73]). These effects were more pronounced for certain subgroups, including women and low-income populations. As income and wealth inequality in OECD countries has been rising since the1980s, it is likely that that these trends are also detrimentally affecting mental well-being, thereby also contributing to the trends in mental ill health (Guschanski and Onaran, 2021[74]; Bourquin, Brewer and Wernham, 2024[75]).
The influence of social media on children and adolescents’ mental health is of concern
In recent years, concern has been growing about the impact rising use of social media is having on mental health – particularly for children and adolescents (Barry et al., 2017[76]; ANSES, 2025[77]). Some evidence suggests that problematic use of social media is associated with increased rates of anxiety, depression and other mental disorders, with increasing evidence that girls and young women are more vulnerable to these effects (Kelly et al., 2018[78]; Valkenburg, Meier and Beyens, 2022[79]). Indeed, a recent meta‑analysis of 143 studies covering more than 1 million adolescents and nearly 900 effect sizes found a small but significant positive association between increased social media use and higher levels of anxiety and/or depression (Fassi et al., 2024[80]). Some research has found that there are windows of development in which the effects of social media may have a particularly detrimental effect on well-being, such as during early- to mid-adolescence (Orben et al., 2022[81]). Recent OECD interviews with policymakers and clinicians similarly highlighted concerns about mechanisms that may intensify emotional vulnerabilities among young people (Box 2.3). A recent legal development may further reinforce these concerns and accelerate policy responses: in March 2026, a California jury ruled that two major social media platforms were liable for designing addictive platforms that harmed a young woman’s mental health, setting a major legal precedent likely to prompt further claims, and potentially speeding efforts toward stronger regulation of social media (Taylor, 2026[82]).
Nevertheless, the evidence on the detrimental relationship between social media use and mental health is not yet considered to be conclusive (Orben and Blakemore, 2023[83]). Indeed, some longitudinal studies have not found a significant association between social media use and mental disorders among adolescents (Coyne et al., 2020[84]). Other research has suggested that the negative effects of social media may not be a direct result of the time spent on social media, but instead are mediated by mechanisms such as poor sleep, lack of physical activity, online harassment, low self-esteem and poor body image, which can result from higher social media use (Viner et al., 2019[85]; Kelly et al., 2018[78]). Some evidence, in fact, suggests that social media use can be associated with an increased sense of community for users (Ulvi et al., 2022[86]). Overall, while there does appear to be a negative relationship between social media use and mental health, the causal nature of these effects remains unclear: it has yet to be demonstrated that those who use social media at higher rates are not those who already experience or have a predisposition to mental ill health.
A recent OECD analysis based on interviews with policymakers and clinical experts confirms that views about the mental health impact of social media remain mixed. Of the 26 stakeholders interviewed, 12 reported a negative effect, while 9 (around one‑third) felt they lacked sufficient evidence to judge, and an additional 5 expressed a neutral position.
Interviewed experts mentioned that social media can disrupt protective routines such as sleep, schoolwork and in‑person social interaction, and that algorithm‑driven feeds may increase exposure to harmful or distressing material. Clinicians noted that adolescents already experiencing anxiety, depression or low self‑esteem can be particularly vulnerable, with body‑image‑related content highlighted as especially concerning for girls. A recurring theme was an “amplification effect”, whereby constant, real‑time access to negative news and crisis‑focussed content heightens fear, worry and hopelessness among children and adolescents. Interviewees also warned that continuous exposure to global conflicts, violence or distressing imagery may intensify negative emotions and deepen existing vulnerabilities. Experts further expressed concern about misleading or inaccurate mental health information circulating on social media, noting that repetitive exposure can encourage self‑diagnosis, over‑pathologisation of normal emotions and, in some cases, increased emotional distress among young users.
Source: OECD (2026[87]), Child, Adolescent and Youth Mental Health in the 21st Century, https://doi.org/10.1787/1092c3cb-en.
A range of socio-demographic factors are associated with elevated risk of mental ill health (Kirkbride et al., 2024[88]). While there is evidence of a broad range of factors, many of which can be cultural or regionally specific (such as culturally and linguistically diverse communities and native populations), a selection of commonly researched socio-demographic risk factors with a robust evidence base are discussed below. Understanding the factors that heighten risk of mental ill health throughout an individual’s life course is essential to implementing efficient and effective interventions for the right people at the right time. In particular, gender, age and socio‑economic status have been shown to be strongly associated with mental health outcomes, as discussed below.
Mental ill health is unequally distributed by gender
It is well established that gender is a strong predictor of mental health, predicting not only prevalence but also the type and severity of the mental disorder suffered. As shown in Figure 2.5, women and girls experience higher rates of mental disorders than males across most age groups in EU countries, except children under 10 and adults aged 60‑74. When looking at specific conditions, girls and women show higher rates of depression and anxiety than men and boys, while men experience higher rates of less prevalent disorders such alcohol use and substance use disorders (Kuehner, 2017[89]; Foster et al., 2016[90]). The factors that drive these differences by gender are difficult to disentangle, although evidence overall suggests that both biological and social factors contribute to these disparities (Farhane-Medina et al., 2022[91]). Biological factors include genetics and hormones, encompassing hormonal changes with reproductive events such as menstruation, pregnancy and menopause, which increase the likelihood of depression and anxiety over a woman’s life course (Halbreich and Kahn, 2001[92]; Soares and Zitek, 2008[93]; Bains and Abdijadid, 2024[94]).
Note: Anxiety disorders, bipolar disorders, depressive disorders, schizophrenia, substance use disorders and others (attention deficit and hyperactivity disorders, autism spectrum disorders, conduct disorders, eating disorders and other mental disorders) were included. It is likely that cumulative numbers are a slight overestimate, as individuals experiencing multiple disorders at once would be double counted in cumulative tallies.
Source: IHME (2026[7]), GBD Compare Data Visualization, https://vizhub.healthdata.org/gbd-compare.
Social factors also probably play an important role in explaining the gender disparities in prevalence of mental disorders. Women experience disproportionate rates of sexual and domestic violence, which has been closely tied to adverse mental health outcomes (Oram, Khalifeh and Howard, 2017[95]). Moreover, socially constructed gender norms, roles and responsibilities create circumstances for women – far more frequently than men – in which they have little control over important decisions concerning their lives (WHO, 2002[96]). It is also suggested that interview techniques and self-reported instruments may not detect a large proportion of men who experience depressive symptoms (Addis, 2008[97]). Artefactual factors – such as women seeking help and reporting more detail about their depressive symptoms more often – may also contribute to the observed differences in mental ill health prevalence by gender (Kuehner, 2003[98]).
Rates of mental ill health vary by age
As shown in Figure 2.5, mental ill health is not distributed homogenously across age groups. Prevalence of mental ill‑health becomes measurable from around age 5, and rises steadily through childhood, reaching its highest levels in adolescence and early adulthood, when more than 26% of those aged 15‑19 and 20‑24 are living with a mental disorder. Prevalence then declines relatively consistently, up to age 95 and above, at which point prevalence of mental ill health appears to increase slightly – particularly for men. The fact that mental ill health is highest among adolescents and young adults is concerning, particularly considering the importance of this age group as a future predictor of mental health. Indeed, the life‑course approach to mental health has been developing in recent years, and has demonstrated the unique importance of childhood and adolescence to mental health (Stelmach et al., 2022[99]; McDaid and Park, 2022[100]). This area of research emphasises that an individual’s mental health is shaped by experiences, exposures and influences across their entire lifespan, from before birth to old age, and across generations (Zhang et al., 2024[101]; Koenen et al., 2013[102]). Key life stages – such as childhood, adolescence, adulthood and later life – are considered critical windows during which positive or negative influences can have long-lasting effects. Indeed, 75% of adult mental disorders start before the age of 24 (Fusar-Poli, 2019[103]). When left untreated, early-onset mental disorders tend to persist into adulthood, contributing to the burden of many chronic mental disorders (Jones, 2013[104]; Kim-Cohen et al., 2003[105]). Promisingly however, early-onset cases of mental ill health can be very responsive to treatment, although they can often be more serious (Jones, 2013[104]). As such, adolescence and young adulthood is also a period when prevention or effective mental health interventions may yield substantial long-term benefits by reducing the risk of mental ill health that will endure (Fusar-Poli, 2019[103]).
In addition to the high prevalence of mental ill health among adolescents and young adults, the life‑course approach to mental health highlights that accumulated adversities across the life course escalate risk of mental ill health. For example, transformative stages and/or events in life are associated with an elevated risk of new and reoccurring mental disorders – such as pregnancy and postpartum, job loss, extended period(s) of unemployment, divorce and family dissolution, death of a partner or other family member, economic hardship, migration, child or sexual abuse, and experiencing or observing domestic violence (Mindlis and Boffetta, 2017[106]; Lippard and Nemeroff, 2020[107]; Bhuller et al., 2024[108]; Grummitt et al., 2024[109]; Hald et al., 2020[110]; Munk-Olsen et al., 2006[111]; Virgolino et al., 2022[112]). A range of socio‑economic risk factors – such as earning a low income or racial discrimination – further compound the risk of developing mental ill health (Kessler et al., 2005[113]; Houtepen et al., 2020[114]; McLaughlin et al., 2012[115]; Turner et al., 2019[116]; Merikukka et al., 2020[117]). Significantly, accumulation of multiple adverse events has not only an additive effect for risk of mental disorder onset but an interactive accumulation during the life course, in that each adverse event has a more significant negative effect when it occurs simultaneously with another (Mandemakers and Kalmijn, 2018[118]). As such, targeting at-risk age groups and people experiencing life transitions that put them at higher risk of mental ill health is increasingly understood to be to a more efficient and effective way to prevent and treat mental ill health (Khanh-Dao Le et al., 2021[119]).
Mental ill health is inequitably distributed across socio-demographic groups
As discussed, mental ill health is disproportionately experienced by gender and across the life course (Kirkbride et al., 2024[88]). While a broad range of factors elevate risk, two primary factors have been shown to be consistent predictors of mental ill health across countries and cultures: income and level of education. To estimate the extent to which inequalities exist across these socio‑economic groups in the 27 EU countries, Iceland and Norway, an analysis was conducted using the Relative Index of Inequality (RII). This is a measure frequently used in epidemiological studies to assess socio‑economic inequalities in health (Moreno-Betancur et al., 2015[120]), as described in Box 2.4. Owing to availability of data on income and level of education, this analysis was only able to be conducted for depressive symptoms, which is a broader classification than major depressive disorders or depressive disorders. It refers to self-reported measures of depressive symptoms experienced in the prior two weeks, rather than reaching a clinical cutoff for depressive disorders (used for data analysed earlier in the chapter) (Eurostat, 2019[121]).
The RII is a commonly used measure of the extent to which an outcome, such as prevalence of a mental disorder, occurs as a function of socio‑economic status (Sergeant and Firth, 2006[122]). The advantage of using RII is that it considers both population size and the comparative socio‑economic status of various groups (Mackenbach and Kunst, 1997[123]). It aims to standardise the impact of the variation in socio‑economic group size on the magnitude of health inequalities (Mackenbach et al., 2008[124]). It indicates the ratio between the rates of the lowest and the highest socio‑economic groups (referring to education, occupation status or income). Typically it is conceptualised analogously to relative risk, represented as RII = h(1)/h(0), where h(x) signifies the occurrence of health events, such as hazard rates or incidence rates, as a function of the socio‑economic rank (Mackenbach et al., 2008[124]). The positions 0 and 1 represent the theoretical extremes of socio‑economic advantage and disadvantage, respectively (Moreno-Betancur et al., 2015[120]). A higher score on the RII implies large health differences between the highest and the lowest socio‑economic groups (Mackenbach and Kunst, 1997[123]). An RII value higher than 1 refers to higher prevalence of outcome of interest among those with a lower socio‑economic status, while an RII lower than 1 indicates higher prevalence among those with higher socio‑economic status (Hosseinpoor et al., 2012[125]). For example, an RII of 1.5 indicates that people in the lowest income quintile are 50% more likely to have the outcome of interest (e.g. depressive symptoms) than people in the highest income quintile.
Income is a strong predictor of mental health
Income is consistently shown to be a very strong predictor of mental health. Individuals on lower incomes experience higher rates of mental ill health, including but not limited to major depression, anxiety and substance use disorders (Sareen et al., 2011[126]; Spivak et al., 2019[127]).These outcomes for people on lower incomes are argued to be driven by increased exposure to a range of additional hardships, such as housing and food insecurity, over-indebtedness, and an erosion of protective psychological factors (personal agency, self-esteem and hope) (Frankham, Richardson and Maguire, 2020[128]; Kimenez-Solomon et al., 2022[129]). Furthermore, low income earners may lack access to coping resources like social support networks that can help to buffer the effects of these stressors (Fryers et al., 2005[130]). This disparity may contribute to higher levels of social exclusion and feelings of marginalisation among people on lower incomes (Pickett and Wilkinson, 2010[131]). Importantly, the relationship between income and mental health is bi-directional, meaning that while low incomes lead to higher levels of mental ill health, higher levels of mental ill health also lead to lower incomes (Rauf, 2023[132]).
Analysis using the RII methodology reinforces previous evidence of a negative relationship between income and mental health outcomes, as shown in Figure 2.6. The analysis defines the lowest income group as the bottom 20% (quintile) of income earners, and the highest income group as the top 20% (quintile) of income earners in the 27 EU countries, Iceland and Norway. The analysis, divided by gender groups, reveals that men tend to experience greater levels of income‑related disparities in depressive symptoms than women. Across these countries, the RII for males is around 5.3 and the RII for females is around 3.7, meaning that men in the lowest income quintile are more than five times more likely and women in the lowest quintile are nearly four times more likely to report depressive symptoms than those in the highest income quintile.
Note: * Prevalence of depressive symptoms for those with the highest income among those in the top quintile is assumed to be 1%.
Source: OECD analysis of Eurostat (2019[133]) data on current depressive symptoms by sex, age and income quintile (data refer to 2019).
Income‑related inequalities in depressive symptoms vary widely across countries. In ten countries, men in the lowest income quintile are more than ten times as likely to have chronic depression as those in the highest. The largest disparity is observed in Estonia, where the least wealthy men are almost 34 times more likely to experience depressive symptoms than their wealthiest counterparts. The smallest disparities are observed in Italy (RII = 1.6), where men with the lowest income levels are 60% more likely to have depressive symptoms than those with the highest (RII = 1.7). In five countries, women with the lowest incomes are ten times more likely to demonstrate depressive symptoms: Lithuania (RII = 13.5), Latvia (RII = 12.5), Norway (RII = 11.8), Ireland (RII = 10.4) and Finland (RII = 10.0). Among women residing in Italy (RII = 1.7), Spain (RII = 1.9) and Belgium (RII = 2.2), the levels of income‑related inequalities in depressive symptoms are lowest. These findings align with previous studies, which reported that men suffer from higher levels of mental health disparities associated with income (Wildman, 2003[134]; Jacquet et al., 2018[135]).
Level of educational attainment has an impact on mental health
Like income, level of educational attainment is a reliable predictor of mental ill health (OECD, 2021[136]). Epidemiological studies consistently demonstrate that people with lower education levels experience higher prevalence of mental disorders (Dudal and Bracke, 2016[137]; Degerlund Maldi et al., 2019[138]). However, the reasons for these differences remain disputed. Some argue that higher educational attainment results in fewer chronic stressors, healthier lifestyles, more social support and better economic resources, and therefore is causally linked to lower levels of mental ill health (Ross and Wu, 1996[139]; Niemeyer et al., 2019[140]). Others suggest that people with higher education levels have better access to information about treatment options, and experience more effective symptom relief than those with lower education levels (Costa-Font and Gil, 2008[141]). Nevertheless, some research casts doubt over the causal impact of education on mental ill health, suggesting instead that education is a proxy for unobserved factors such as early-onset mental health problems, family characteristics, biologically based health conditions and genetics (Halpern-Manners et al., 2016[142]).There is also strong evidence of at least a bi-directional relationship between mental health and education, as evidence of mental ill health in school is associated with lower levels of educational attainment (Esch et al., 2014[143]).
The analysis undertaken on the 27 EU countries, Iceland and Norway using the RII method supports the premise that there is a negative relationship between education level and depressive symptoms. An RII greater than 1 indicates that depressive symptoms are more prevalent among those with the lowest levels of educational attainment. As shown in Figure 2.7, men in the lowest education quintile are 2.5 times more likely to have depressive symptoms than those in the highest. The largest inequalities among men were observed in Greece, where men with the lowest education levels were more than 41 times more likely to experience depressive symptoms than their most educated counterparts (RII = 41.1). In line with previous findings, women tend to experience greater levels of education-related disparities in depressive symptoms than men. In six countries, women with the lowest levels of education are more than 14 times more likely to demonstrate depressive symptoms. The largest education-related disparities in depressive symptoms among women were found in Luxembourg (RII = 27.5), Norway (RII = 25.3) and Denmark (RII = 22.1), while the smallest were found in the Netherlands (RII = 1.8) and Poland (RII = 1.8). On average, the least educated women in the studied countries were 3.3 times more likely to experience depressive symptoms than those with the highest education levels.
Note: Refers to individuals aged 15‑64. Population data from Eurostat disaggregated by educational attainment level, sex and age were used. * Prevalence of depressive symptoms for those with highest level of education among those in tertiary education is assumed to be 1%.
Source: OECD analysis of Eurostat (2019[133]) data on current depressive symptoms by sex, age and educational attainment level (data refer to 2019).
In recognition of the significant rates and inequalities in mental ill health, many countries have made attempts in recent years to increase access to mental health services, and to move the focus of services from hospitals into the community and other non-traditional mental healthcare settings. Despite this, a substantial proportion of individuals with mental ill health have unmet mental healthcare needs. This refers to the gap between the services required to address one’s mental health concerns and treatment coverage rates (the proportion of individuals who are able to access mental healthcare).
Several factors create barriers to mental healthcare access
A variety of barriers contribute to unmet mental health needs, including financial, geographical and organisational barriers to mental healthcare (OECD, 2021[144]).
In many regions, mental health services – particularly psychological therapies – may not be covered by health insurance or public health coverage, requiring individuals to pay out of pocket. This financial cost creates a significant barrier to accessibility, especially for those on low incomes (Mojtabai, Olfson and Mechanic, 2002[145]; Wang et al., 2007[146]).
Geographical barriers also prevent access to mental healthcare, as individuals living in rural areas are less likely to receive mental health treatment than those who reside in urban areas (Wang et al., 2005[147]).
Systemic issues like shortages of healthcare professionals also create organisational barriers to access and a scarcity of available services. A lack of trained mental health providers – including psychiatrists, psychologists, clinical psychologists and specialist nurses – can result in extensive waiting times for mental healthcare, which is associated with poorer mental health outcomes (Punton, Dodd and McNeill, 2022[148]; Boerema et al., 2017[149]; OECD, 2021[144]). Indeed, longer waits for psychiatric appointments can lead to increases in psychiatric hospitalisations, decompensation, impairment, disability and risk of suicide (Williams, Latta and Conversano, 2008[150]; Reichert and Jacobs, 2018[151]).
Administrative requirements such as referrals from a GP are often needed to receive specialised mental healthcare. Insufficient referral information and inadequate co‑ordination between GPs and mental health specialists also results in poor continuity of care and longer waiting times (Yang et al., 2022[152]; Hartveit et al., 2017[153]). In several OECD countries, a waiting-time target or guarantee has been set up in at least one area of mental healthcare, and most countries aim for patients to start treatment or make the first service contact within 1‑3 months (OECD, 2021[144]).
Only one‑third of people requiring mental healthcare in EU countries are estimated to have access to treatment for their condition
At present, understanding the extent of unmet needs for mental health is difficult because of a lack of data using consistent definitions. In the absence of an international standardised definition that provides a comparable measure of unmet mental healthcare needs across OECD countries and beyond, this publication estimates treatment coverage – referring to the proportion of people with mental disorders who are able to access mental health treatment. This estimation was based on existing research using OECD data reporting the share of people with unmet needs (OECD, 2021[144]) and treatment coverage estimates from the WHO World Mental Health survey. The survey asked respondents from several EU countries whether they had ever sought professional help for issues related to emotions, mental health, nerves or substance use, and, if they had, whether they had received such treatment within the 12 months preceding the interview (Evans-Lacko et al., 2018[154]). Based on that analysis, the calculation used in this publication as a proxy for treatment access is 100% minus the share of individuals identified as having unmet needs. For countries that were missing from this measure, a statistical regression analysis was conducted using both WHO measured data and OECD benchmarks to estimate the treatment access levels for the remaining EU countries.
Figure 2.8 represents the results of this analysis, showing that treatment access levels are estimated at 33% across EU countries. The highest rates are estimated to be in Norway and Switzerland (43% and 45%), while the lowest reported levels are in Bulgaria and Romania (26%). There are obviously limitations to this measure, such as the fact that people who had not sought treatment (for example, owing to barriers such as financial burden) would not be captured. While this, among a range of other limitations, may reduce the accuracy of this measure, the analysis provides an interesting estimate of treatment access rates in the absence of a more comprehensive international measure of unmet healthcare needs.
Note: Extrapolation for countries lacking data was performed using an ensemble model based on a lasso regressor, incorporating the following country-specific indicators: suicide rates, depression rates, world happiness index, number of mental health professionals, universal healthcare service coverage index and GDP. Extrapolated data should only be considered as a high-level indicator of the possible coverage of services for mental ill health.
Source: OECD Mental Health Systems Performance Benchmark survey (2021[144]), WHO World Mental Health survey (Evans-Lacko et al., 2018[154]).
It is also worth noting that, with 67.5% of people across EU and OECD countries lacking treatment coverage for mental health conditions (Figure 2.8), unmet needs for mental healthcare appear substantial. Although the measure may not be fully comparable with the share of unmet needs for medical examinations and treatments, given that the numerators do not necessarily cover the same population of individuals who sought care, the significant contrast suggests that access challenges may be more pronounced for mental healthcare. Self‑reported data from the 2024 EU‑SILC survey indicate that 3.8% of people aged 16 and over in the EU reported an unmet need for a medical examination or treatment. Waiting lists were the most frequently cited reason, accounting for more than one‑third of cases, followed by high costs, which represented around 26% (Eurostat, 2025[155]).
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← 1. The regional classification of European countries is based on the geographic classifications provided in EuroVoc, a multilingual thesaurus maintained by the Publications Office of the EU (2024[156]). The countries included in each European region are as follows: Central and Eastern Europe includes Bulgaria, Croatia, Czechia, Hungary, Poland, Romania, the Slovak Republic and Slovenia; Northern Europe includes Denmark, Estonia, Finland, Iceland, Latvia, Lithuania, Norway and Sweden; Southern Europe includes Cyprus, Greece, Italy, Malta, Portugal and Spain; and Western Europe includes Austria, Belgium, France, Germany, Ireland, Luxembourg, the Netherlands and Switzerland.