Principal findings

This first Headway-based study aimed to carry out a comparison of the population MH status and its determinants across European countries. Two main findings emerged from the analyses. First, as expected, there were relevant differences in the population MH status and its determinants across European countries. Second, somehow surprising, for up to 11 countries MH status differed from what a determinants-based risk assessment appeared to suggest, including both “low risk, poor MH status”, and “high risk, good MH status” countries. Thus, Slovakia and Cyprus emerged as the “healthiest” countries, whereas Finland, Sweden, and Estonia were the lowest-risk countries according to the MH determinants KPIs. In brief, between-country differences in their responsiveness to the population MH needs may, in large part, explain this discrepancy, which forms the basis for the second Headway article in this issue.

Mental health status of the European population

A deeper theoretical debate about the conceptualization of MH, although still warranted [Reference Galderisi22, Reference Galderisi, Heinz, Kastrup, Beezhold and Sartorius23], falls outside the scope of this article. This noted, Slovakia, Cyprus, and Greece emerged as the countries with the best population MH status, whereas Sweden, the UK, and The Netherlands had the poorest MH status. However, much caution is needed when interpreting these results, which take into account multiple variables and may have been affected by misreporting issues. Specifically, it is worth noting that those countries with worse MH status could just reflect better quality of data/reporting, which appears to apply to those countries with greater MH expenditure, such as Scandinavian countries.

Of concern, the COVID-19 pandemic triggered a 25% increase in the prevalence of anxiety and depressive disorders [4], with a prevalence of anxiety ranging from 4.3% (Estonia) to 11.3% (Portugal) and a prevalence of depression ranging from 4.2% (Slovakia) to 7.5% (Spain). The prevalence of schizophrenia, however, was shown to have a much smaller variation (0.5% in The Netherlands vs. 0.3% in Denmark) compared with between-country differences in the incidence of first-episode psychosis [Reference Jongsma, Gayer-Anderson, Lasalvia, Quattrone, Mulè and Szöke24].

Over the past three decades, data from the Global Burden of Disease project have replicated mental disorders to be a major contributor to disability [6]. In line with this, our results showed a widely used measure of disability, namely the number of years lived with disability (YLD), to range from 1617.8 (Hungary) to 2603.9 (Portugal), hence unacceptably high across Europe, which will require coordinated delivery of effective prevention and treatment programmes by governments and the global health community.

More importantly, mortality, particularly suicide, can be considered as the most tragic outcome in MH. In this respect, mortality rates per 100,000 inhabitants in 2021 ranged from 8.9 (Slovakia) to 84.0 (UK), i.e., an almost 10-fold variation, which may have been due to reporting differences, especially for deaths by natural causes, which cannot be easily linked with MH issues by the relevant authority across countries. This is less likely to apply to suicide rates (per 100,000 inhabitants) which in 2020 ranged from 3.45 (Cyprus) to 21.25 (Lithuania), hence a 6-fold variation. Both mortality and suicide rates have remained unchanged in Europe for the past few years, as supported by the Global Burden of Disease 2019 study [Reference Santos, Padron-Monedero, Bikbov, Grad, Plass and Mechili25]. Addressing the mortality gap in MH, particularly in schizophrenia [Reference Correll, Solmi, Croatto, Schneider, Rohani-Montez and Fairley9], through psychosocial interventions targeting modifiable risk factors, such as unhealthy lifestyles [Reference Luciano, Sampogna, Amore, Andriola, Calcagno and Carmassi26], urges multi-agency action worldwide [Reference Fiorillo, de Girolamo, Simunovic, Gureje, Isaac and Lloyd27, Reference Fiorillo and Sartorius28].

Determinants of mental health of the European population

The well-established individual, environmental, and social determinants of MH have been demonstrated to be unequally distributed within- and between populations [4, Reference Kirkbride, Anglin, Colman, Dykxhoorn, Jones and Patalay29], which is in full agreement with our data showing high variation across the board. This raises a fundamental question: to what extent is one’s MH (pre)determined by external socioeconomic and environmental factors? Truly, up to 62% of Europeans, especially women (67%), were affected by the aforementioned post-pandemic polycrisis [13]. In keeping with this, the 2023 Headway Mental Health Index 3.0 incorporated some relatively novel polycrisis-related KPIs, such as the impact of natural disasters, eco-anxiety, and crime level on MH [16].

The effects of natural disasters on MH are well-established [Reference Leppold, Gibbs, Block, Reifels and Quinn30]. In Europe the number of natural disasters has grown from 91 in 1979 to 1,452 in 2019, accounting for over 145,000 deaths over the past 40 years [16]. Although exposure to these events has been linked with negative MH outcomes [Reference Leppold, Gibbs, Block, Reifels and Quinn30], adequate MH support, community resilience initiatives, and disaster preparedness measures [Reference Roudini, Khankeh and Witruk31], including the use of mobile apps [Reference Ezeonu, Hertelendy, Adu, Kung and Itanyi32], may mitigate this.

Eco-anxiety, which can be defined as a” pre-traumatic stress disorder in response to climate change and ecological crises,” has become a focus of major concern in global public MH [Reference Sisodiya, Gulcebi, Fortunato, Mills, Haynes and Bramon33], including Europe [Reference Brandt, Adorjan, Catthoor, Chkonia, Falkai and Fiorillo34]. Eco-anxiety appears to particularly affect children and adolescents’ MH [Reference Hickman, Marks, Pihkala, Clayton, Lewandowski and Mayall35] irrespective of neuroticism and/or personal beliefs [Reference Ogunbode, Salmela-Aro, Maran, van den Broek, Doran and Lins36]. Combating climate change may therefore contribute to preventing mental disorders via reduced risk of eco-anxiety, especially for youth, a universal prevention measure to which the European Psychiatric Association (EPA) is particularly committed [Reference Brandt, Adorjan, Catthoor, Chkonia, Falkai and Fiorillo34].

Crime level has been long associated with poorer MH and identified as a barrier to engagement in health-promoting activities [Reference Stafford, Chandola and Marmot37]. Truly, community violence was linked with poorer MH outcomes [Reference Baranyi, Di Marco, Russ, Dibben and Pearce38]. While victims of crime may benefit from targeted prevention interventions, future studies should clarify the extent to which crime level affects MH, while controlling for social disadvantage and related factors.

Relationship between mental health status and its determinants across Europe

As noted above (Table 4), the extent to which determinants of MH predicted the population MH status across countries was found to be somehow weak. In particular, there were both “high risk, good MH” countries, such as Bulgaria, Croatia, Romania, Greece, Italy, and Latvia; and “low risk, poor MH” countries, namely Ireland, Lithuania, The Netherlands, Sweden, and Hungary. Although further non-tested risk/protective factors may contribute to MH and quality of data and reporting issues should be considered, this is likely to be explained, in large part, by countries’ responsiveness to their citizens’ MH needs (see Arango et al., this issue).

Based on the bivariate associations between KPI scores (Table 5), alcohol use, smoking, hours of daylight, commuting time, ecoanxiety, air pollution, and Fragile State Index emerged as the common determinants of MH across Europe. Smoking and alcohol use have been consistently linked to poorer (mental) health outcomes worldwide [39] in spite of significant progress in fighting both addictions [40]. Daylight exposure was linked with better MH [Reference Bonatto, Pilz, Borges, Xavier, Tonon and do Amaral41], consistent with our data showing a positive relationship between more hours of daylight and lower suicide rates [Reference Plöderl, Pichler, Westerlund, Niederseer and Fartacek42]. Interestingly, ecoanxiety can be both cause and consequence of mental disorders [Reference Sisodiya, Gulcebi, Fortunato, Mills, Haynes and Bramon33]. Commuting time, which can be defined as the proportion of people who take over 30 minutes to go to work, showed a positive correlation with MH status – the lower the proportion of people with long commuting times, the better the MH. Reducing commuting time may therefore prevent mental disorders, such as depression in adults [Reference Marques, Peralta, Henriques-Neto, Frasquilho, Rubio Gouveira and Gomez-Baya43] and in adolescents [Reference Nakajima, Otsuka, Itani, Kaneko, Suzuki and Kaneita44], which warrants future intervention studies. The Fragile State Index can be considered as a proxy measure of social cohesion, economic status and political stability of countries, which is inextrincably linked to most determinants of MH [Reference Kirkbride, Anglin, Colman, Dykxhoorn, Jones and Patalay29], thus behaving as a major MH risk factor, especially for child maltreatment [Reference Skinner, Bywaters and Kennedy45]. Poverty alleviation programmes, which have been recommended by the Lancet-Commission [Reference Patel, Saxena, Lund, Thornicroft, Baingana and Bolton46], may reduce this risk [Reference Zaneva, Guzman-Holst, Reeves and Bowes47].

Also, sexual abuse, noise pollution, and the proportion of green areas correlated with most status KPIs except mortality and suicide (Table 5). Between 11% (men) and 13% (women) of MH service users were meta-analytically found to have suffered from sexual abuse, a well-established predictor of poor MH outcomes [Reference Dragioti, Radua, Solmi, Arango, Oliver and Cortese48–Reference Kaul, Connell-Jones, Paphitis and Oram50]. Although noise pollution was thought to worsen MH, high-quality longitudinal studies showing the benefits of noise-reducing policies are lacking [Reference Moore, Kesten, López-López, Ijaz, McAleenan and Richards51]. Finally, our findings revealed that countries with a higher proportion of green area space achieved better MH status, except for suicide outcomes, which was probably due to the link between rurality and increased suicide risk, hence, a complex issue worthy of further investigation [Reference Geneshka, Coventry, Cruz and Gilbody52].

Next steps

This first Headway data-based study provided an overview of the population MH status and its determinants across Europe, which may pave the way towards more targeted prevention interventions. In short, this study may provide new insights into the extent to which one’s MH status is determined by such a complex interplay of individual, environmental, and social factors, which is not to underestimate the role of genetics and other neurobiological variables in the aetiology and outcomes of mental disorders [Reference Arango, Dragioti, Solmi, Cortese, Domschke and Murray21].

Interestingly, a well-studied indicated prevention intervention in psychiatry, such as the “At clinical high-risk for psychosis” (CHR-P) model [Reference McGorry, Mei, Chanen, Hodges, Alvarez-Jimenez and Killackey53], has largely failed to predict [Reference de Pablo, Besana, Arienti, Catalan, Vaquerizo-Serrano and Cabras54] and prevent [Reference Catalan, de Pablo, Vaquerizo Serrano, Mosillo, Baldwin and Fernández‐Rivas55] transition to psychosis. Even in a catchment area with well-resourced CHR-P clinics, such as South-East London (UK), only 4.1% of first-episode psychosis incident cases had presented to these CHR-P clinics and met CHR-P criteria [Reference Ajnakina, Morgan, Gayer-Anderson, Oduola, Bourque and Bramley56]; hence, of little value from a public health and/or economic perspective [Reference van Os and Guloksuz57]. Alternatively, from a universal prevention approach, decreasing population exposure to well-known risk factors for psychosis, such as cannabis use [Reference Murray, Quigley, Quattrone, Englund and Di Forti58], may be more effective [Reference Ajnakina, David and Murray59]. Consistent with this public health model, some evidence-based prevention measures in MH can be recommended [Reference Arango, Díaz-Caneja, McGorry, Rapoport, Sommer and Vorstman17], which were also demonstrated to be cost-effective, especially in children and adolescents [Reference McDaid, Park and Wahlbeck60, Reference Le LK-D, Mihalopoulos, Chiotelis, Bucholc and Chatterton61]. Of note, most major mental disorders onset occurs before age 25 [Reference Solmi, Radua, Olivola, Croce, Soardo and de Pablo62], thus making childhood and adolescence the optimal period to deliver any preventive intervention [Reference Fusar-Poli, Correll, Arango, Berk, Patel and Ioannidis19]. In line with this notion, Table 6 provides some examples of primary prevention strategies targeting the common determinants of MH across Europe.

Table 6. Proposed prevention strategies targeting the determinants of mental health in Europe

Abbreviations: SEL: social and emotional learning. MA: meta-analysis.

Prevention in MH has attempted to reduce exposure to well-established risk factors thus far. However, in the years to come the focus should be switched towards promoting protective factors [Reference Fusar-Poli, Correll, Arango, Berk, Patel and Ioannidis19], such as resilience [Reference Fusar-Poli, de Pablo, De Micheli, Nieman, Correll and Kessing63], physical activity [Reference Rahmati, Lee, Yon, Lee, Udeh and McEvoy64], school-based social, and emotional learning [Reference Taylor, Oberle, Durlak and Weissberg65]. Of note, this MH promotion model has proved useful in asylum seekers children and adolescents [Reference Della Rocca, Bello, Carbone, Pezzella, Toni and Sampogna66], which is in line with global strategies promoting physical health in psychiatry [Reference Wasserman, Arango, Fiorillo, Levin, Peters and Rao20] and the 2023 European Commission (EC) Mental Health Strategy [67]. More controversially, the long-term benefits of new technologies, such as smartphone-based apps, remain less clear and their recommendation, particularly to the youth, raises ethical issues [Reference Wies, Landers and Ienca68].

Advancing in preventive psychiatry, however, seems to be hampered by stigma [Reference Thornicroft69], which underestimates the general public perception of the need for MH prevention, and financial issues. In particular, its long-term high return appears to discourage health authorities and policymakers from investing in MH prevention as a priority [Reference Arango, Díaz-Caneja, McGorry, Rapoport, Sommer and Vorstman17].

Strengths and limitations

Data supporting this study’s findings came from the updated 2023 Headway Mental Health Index 3.0, which measured 54 MH-related KPIs across EU-27 countries and the UK, thus allowing direct country-to-country comparisons. All data sources were official authoritative open-access datasets. Results may therefore inform some evidence-based public MH strategies and universal primary prevention interventions.

However, this study has three limitations. First, the Headway methodology relied partly on national datasets which differed in quality of data, which also were collected during different years. Specifically, mis- and under-reporting issues should be considered. Second, non-tested KPIs, such as mass media use or fear of war, may influence the European population MH. Third, both analytical and qualitative approaches were adopted, which may have incorporated some biases, although this seems unlikely.

Final remarks

The post-pandemic polycrisis [16] has put MH at the top of the political agenda of numerous institutions and governments, including the European Commission [67]. This is therefore a unique opportunity to implement a new roadmap for MH in Europe [16] under the scientific leadership of the EPA, although the challenges ahead will require increased efforts. In particular, while precision psychiatry cannot yet inform clinical decision-making at an individual level [Reference Krishnadas, Leighton and Jones70], universal preventive psychiatry seems to be much more within our grasp [71].