Adult Psychiatric Morbidity Survey: Survey of Mental Health and Wellbeing, England, 2023/4

Common mental health conditions (CMHCs) comprise different types of depression and anxiety disorder. They cause marked emotional distress and interfere with daily function, but do not usually affect insight or cognition. CMHCs are usually less disabling than major psychiatric disorders.

The Clinical Interview Schedule-Revised (CIS-R) has been used in each Adult Psychiatric Morbidity Survey (APMS) in the series to assess six types of CMHCs:

• Depression
• Generalised anxiety disorder (GAD)
• Panic disorder
• Phobias
• Obsessive compulsive disorder (OCD)
• CMHC not otherwise specified (CMHC-NOS).

Some people meet the criteria for more than one CMHC. The CIS-R is also used to produce a score that reflects overall severity of CMHC symptoms. A CIS-R score of 12 or more is used to indicate a clinically significant level of CMHC symptoms, and of 18 or more to indicate severe CMHC symptoms.

• One in five (20.2%) adults in England had a CMHC, with prevalence higher in women (24.2%) than men (15.4%). The most prevalent CMHCs were GAD (7.5%), depression (3.8%), and the general category of CMHC-NOS (8.6%).
• CMHCs have increased in prevalence among 16 to 64 year olds: from 15.5% in 1993, 17.5% in 2000, 17.6% in 2007, and 18.9% in 2014, to 22.6% in 2023/4. Increases since 2014 were evident in males and females, and most age groups.
• Young people were more likely to have a CMHC than older people. Among 16 to 24 year olds, CMHC prevalence rose from 17.5% in 2007 and 18.9% in 2014, to 25.8% in 2023/4. While among those aged 75 and over, prevalence was lower and stable (9.9% in 2007, 8.8% in 2014, 10.2% in 2023/4).
• Prevalence of severe CMHC symptoms has also increased: 11.6% of 16 to 64 year olds scored 18 or more on the CIS-R in 2023/4, compared with 9.3% in 2014.
• There is a socioeconomic gradient in CMHCs, with prevalence higher in the most deprived fifth of areas (26.2%) than in the least deprived fifth of areas (16.0%). People with problem debt were twice as likely to have a CMHC (39.0%) as those with no problem debt (18.4%). This pattern of association was similar for men and women. Among working age adults, unemployed (40.0%) and economically inactive (38.8%) people were more likely to have a CMHC than those in employment (18.3%). This association was stronger for men than women.
• Regional disparities in CMHCs were evident, with people in the North East (24.6%) and East Midlands (24.6%) more likely to have a CMHC than those in the South East (16.3%) and South West (18.7%).
• Physical and mental health are strongly linked. 32.9% of people with a physical health condition that limited their activities had a CMHC, compared with 12.6% of those without a limiting physical health condition. This association was stronger for men than women.
• Most people identified by the CIS-R with a CMHC also perceived themselves to have had a CMHC at some point (84.0%). Two-thirds (66.5%) reported that they had been diagnosed by a professional. Adults identified with anxiety disorders had lower levels of professional diagnosis for those conditions, such as OCD with only 9.6% being professionally diagnosed and 3.3% for those identified with a phobia. However, such individuals had often received a professional diagnosis of depression.

CMHCs include a range of anxiety and depressive disorders. They vary in severity from mild to severe and are associated with social and physical impairments and difficulties with occupational functioning (Goldberg and Huxley 1992). Although a significant source of distress to individuals and those around them, anxiety disorders and depression often remain undiagnosed (Kessler et al. 2002). Sometimes people do not seek or receive treatment (Lowther-Payne et al. 2023), sometimes they may get but do not adhere to treatment (Cooper et al. 2007). If left untreated, CMHCs can lead to long term physical, social and occupational disability (Collins et al. 2023) and premature mortality (Plana-Ripoll et al. 2019). Comorbidity between mental disorders is common (McGrath et al. 2020) and has implications for treatment pathways (Bhavsar et al. 2021). CMHCs can be relapsing conditions, especially where the stressors that caused them continue to exist (Solmi et al. 2023). For example, about half of people treated for depression experienced a recurrence within 12 months of initial improvement (Beshai et al. 2011).

There is a strong economic case for investing in the prevention of CMHCs. The societal costs of mental health conditions were estimated at £117.9 billion in the UK in 2019 (McDaid et al. 2022). Most of this was due to the lost productivity of people living with mental health conditions, as well as costs incurred by unpaid informal carers. Mental illness impacts on labour force engagement, accounting for 7.9% of UK sickness absence in 2022 (ONS 2023). In the same year, 69% of Work Capability Assessments had a ‘mental or behavioural disorder’ recorded as the primary condition (Department for Work and Pensions 2024). Analysis of APMS 2014 found that two thirds (65.2%) of Employment and Support Allowance (ESA) recipients (a benefit aimed at people with a health condition or disability that affects how much they can work) had a CMHC, four times that of employed people (14.6%) (Lapham et al. 2024). Between 2013 and 2019, one in four specialist mental health service users received Universal Credit, a welfare benefit rolled out in the UK from 2013 (Stevelink et al. 2024). Some studies have suggested the introduction of Universal Credit may have led to an increase in psychological distress among unemployed people affected by the policy (Wickham et al. 2020; Brewer et al. 2024).

The social determinants of mental disorder are well established (Kirkbride et al. 2024). Data from the APMS series have helped quantify the extent to which a range of characteristics and experiences have been associated with CMHC in England (McManus et al. 2020), including those related to:

• Demographics: gender (Weich et al. 1998), ethnicity (Ahmad et al. 2022), age (Bogdanova et al. 2022), sexual identity (Pitman et al. 2022)
• Early years: bullying (Meltzer et al. 2011), child sexual abuse (Bebbington et al. 2011), adversity (Meltzer et al. 2012b)
• Social relationships: loneliness (Meltzer et al. 2013b), family adversity (Cook et al. 2024), caring responsibilities (Stansfeld et al. 2014)
• Violence and abuse: physical (Fadeeva et al. 2024), sexual (McManus et al. 2022), threats (McManus et al. 2021), domestic abuse (Hashemi et al. 2025; Bhavsar et al. 2023)
• Health risk behaviours: gambling (Wardle et al. 2020), drug use (Bebbington et al. 2020), alcohol use (Puddephatt et al. 2021)
• Physical health and impairments: disability (Meltzer et al. 2012a), menopause (Adji et al. 2023), sensory impairments (Shoham et al. 2019), epilepsy (Nimmo‐Smith et al. 2016)
• Stressful life events: discrimination (Rhead et al. 2022), incarceration (Bebbington et al. 2021), homelessness (Chilman et al. 2024), flooding (Graham et al. 2019)
• Occupational environment: workplace bullying (Bunce et al. 2024), job quality (Butterworth et al. 2013), being a student (McManus and Gunnell 2020) or veteran (Woodhead et al. 2011)
• Financial strain: poor housing (Harris et al. 2010), debt (Meltzer et al. 2013a), unemployment (Lapham et al. 2024).

Concern about population mental health came to the fore during the COVID-19 pandemic. Studies found an initial increase in psychological distress in the UK (Pierce et al. 2020), particularly for those who already had a CMHC (Pierce et al. 2021). There was evidence of a widening in mental health inequalities (Taxiarchi et al. 2023), alongside disruptions to mental health treatment access and modes of delivery (Abel et al. 2021). The pandemic may have a lasting impact on mental health risks, for example through persisting increases in remote working and consequent concerns about social isolation (Parry et al. 2022). However, signals of rising rates of CMHC predate the pandemic (Dykxhoorn et al. 2024), with a variety of potential drivers noted such as recession and subsequent austerity (Curtis et al. 2021), precarity and the cost-of-living crisis (ONS 2022) and digital technology use (Orben et al. 2024). Lord Darzi noted in his investigation of the NHS in England that ‘many of the social determinants of health – such as poor quality housing, low income, insecure employment – have moved in the wrong direction over the past 15 years with the result that the NHS has faced rising demand for healthcare from a society in distress’ (Darzi 2024).  

Reducing CMHCs is a major public health challenge (Public Health England 2018). England’s Prevention Concordat for Better Mental Health was developed to support cross-sector adoption of public mental health approaches (Office for Health Improvement and Disparities 2024). Its consensus statement highlights that improving population mental health requires preventive action by local authorities; integrated care systems (ICSs); public, private, and voluntary, community and social enterprise (VCSE) sector organisations; educational settings; employers; emergency services; justice systems; and social care, as well as the NHS. As well as addressing risk and protective factors, the Prevention Concordat also supports the aims of the NHS Long Term Plan to increase and widen access to care for those needing mental health support (NHS 2019). For information on use of treatment and services among people with CMHCs, see Chapter 2 Mental health treatment and service use.

Common mental health conditions (CMHCs, also known as common mental disorders (CMD) and neurotic disorders), cause marked emotional distress and interfere with daily function. CMHCs comprise different types of depression and anxiety disorder:

• Symptoms of depressive episodes include low mood and a loss of interest and enjoyment in ordinary things and experiences. They impair emotional and physical wellbeing and behaviour (NICE 2022).
• Anxiety disorders include generalised anxiety disorder (GAD), panic disorder, phobias, and obsessive compulsive disorder (OCD) (NICE 2020).

Symptoms of depression and anxiety frequently co-exist, with the result that many people meet criteria for more than one CMHC.

The Clinical Interview Schedule – Revised (CIS-R)

Different types of CMHCs and symptoms of CMHC were assessed in the first phase interview using the CIS-R. The CIS-R is an interviewer administered structured interview schedule covering the presence of non-psychotic symptoms in the week prior to interview. It can be used to provide prevalence estimates for 14 types of CMHC symptoms and six types of CMHCs, together with a continuous scale that reflects the overall severity of CMHC psychopathology (Lewis et al. 1992).

Each section of the CIS-R assesses one type of CMHC symptom. These are: 

• Somatic symptoms
• Fatigue
• Concentration and forgetfulness
• Sleep problems
• Irritability
• Worry about physical health
• Depression
• Depressive ideas
• Worry
• Anxiety
• Phobias
• Panic
• Compulsions
• Obsessions.

Although minor changes were made to the questions to improve comparability with the International Classification of Diseases 11th Revision (ICD-11) diagnostic classification, results in this chapter use diagnoses generated by the 10th International Classification of Disease (ICD-10) to allow comparability across the APMS survey series (World Health Organization (WHO) 1993; 2022). Each section starts with two filter questions to establish the presence of the particular symptom in the past month. A positive response leads to further questions enabling a more detailed assessment of the symptom in the past week including frequency, duration, severity, and time since onset. Answers to these questions determine the scores for each symptom. Symptom scores range from zero to four, except for depressive ideas, which has a maximum score of five. Descriptions of the items that make up the scores for each of the symptoms measured by the CIS-R can be found in Appendix A of the APMS 2023/4 Methods documentation. Data on the symptom scores are not presented in this chapter but are available in the archived dataset.

The scores for each symptom are summed to produce a total CIS-R score, which is an indication of overall severity.

• CIS-R score of 12 or more is the threshold applied to indicate that a level of CMHC symptoms is present such that primary care recognition is likely to be warranted. In this chapter, ‘presence of CMHC symptoms’ includes all participants with a CIS-R score of 12 or more (including those with a score of 18 or more).
• CIS-R score of 18 or more denotes more severe or pervasive symptoms of a level very likely to warrant intervention such as medication or psychological therapy. In this chapter ‘severe CMHC symptoms’ is used to indicate those with a CIS-R score of 18 or more.

The participants’ answers to the CIS-R were used to generate ICD-10 diagnoses of CMHC using the computer algorithms described in Appendix A of the APMS 2023/4 Methods documentation (WHO 1993). ICD-10 diagnoses were used throughout the chapter to enable comparison across the APMS survey series. These ICD-10 diagnoses were then amalgamated to produce the six categories of disorder used in this report:

• Generalised anxiety disorder (GAD)
• Depression (including mild, moderate and severe)
• Phobias
• Obsessive compulsive disorder (OCD)
• Panic disorder
• CMHC not otherwise specified (CMHC-NOS).

CIS-R scores of 12 or more are conventionally taken to indicate a CMHC. Participants with such a score who did not meet the criteria for any of the specific disorders assessed were categorised with CMHC not otherwise specified (CMHC-NOS). ‘CMHC-NOS’ is also known as mixed anxiety and depression or cothymia (Das-Munshi et al. 2008). By definition, participants with this diagnosis could not be classed as having any other CMHC measured by the CIS-R. For the other five ICD-10 disorders, participants could be classed in more than one category. Some adults identified with a CMHC did not score 12 or more on the CIS-R. Participants with a CIS-R score of 11 or less could still meet the criteria for some specific CMHC. All of those with a CIS-R score of 12 or above were classed as having a CMHC, compared with 0.3% of those with a score of 5 or below (few or no CMHC symptoms), and 9.6% of those with a score of between 6 and 11 (some evidence of CMHC symptoms). Most of those with a CMHC with a CIS-R score below 12 were classed as having GAD.

The CIS-R was used to assess CMHCs in the 1993, 2000, 2007 and 2014 APMS. The schedule was administered using computer assisted interviewing in the 2000, 2007, 2014 and 2023/4 surveys, and by paper in 1993. The approach has otherwise remained consistent, and the data are comparable across survey years. Trends over time presented in this chapter focus on 16 to 64 year olds, because the 1993 survey did not sample adults aged 65 and over. In APMS 2007, 2014 and 2023/4, there was no an upper age limit to participation and the sample covered England only (the first two surveys also covered Scotland and Wales).

Calculation of CIS-R scores are described in detail in Appendix A of the APMS 2023/4 Methods documentation.

Prevalence of CMHC symptoms, by age and gender

Nearly one in five adults (18.3%) were identified with CMHC symptoms of a level likely to benefit from acknowledgement and possible intervention (as indicated by a CIS-R score of 12 or more). Prevalence in the wider population is likely to be between 17.0% and 19.6%, referred to as the 95% confidence interval (95% CI). This equates to about 8.5 million adults in England. One in ten (10.0%, CI 9.1, 11.0) adults had severe CMHC symptoms (CIS-R 18+), approximately 4.7 million adults in England.

Women (21.8%, CI 20.1, 23.5) were more likely than men (14.0%, CI 12.4, 15.8) to score 12 or more on the CIS-R. Women (11.9%, CI 10.6, 13.4) were also more likely than men (7.5%, CI 6.4, 8.9) to have severe CMHC symptoms (CISR 18+).

The proportion scoring 12 or more on the CIS-R declined with age, from 22.8% (CI 18.0, 28.6) of those aged 16 to 24 to 9.4% (CI 7.5, 11.7) of those aged 75 and over. A similar pattern was observed for severe CMHC symptoms: 14.2% (CI 10.4, 19.0) of those aged 16 to 24 scored 18 or more on the CIS-R, compared with 3.8% (CI 2.5, 5.6) of those aged 75 and over).

The overall pattern of association between age and CMHC symptoms was not significantly different for men and women, with prevalence generally higher in women than men in each age group.

For more information: Table 1.1 and Table A1 for confidence intervals

Trends in CMHC symptoms, 1993, 2000, 2007, 2014 and 2023/4

Note that the trends in this chapter are based on 16 to 64 year olds, to allow for comparison with 1993, and analysed by sex (male and female) rather than gender (men and women). See How to interpret the findings for information on how changes over time were assessed.

Among 16 to 64 year olds, the proportion with CMHC symptoms (CIS-R 12+) has increased over time. It was 14.1% (95% CI 13.4, 14.9) in 1993, 16.3% (CI 15.3, 17.3) in 2000, 16.4% (CI 15.3, 17.5) in 2007 and 17.5% (CI 16.4, 18.7) in 2014, increasing to 20.4% (CI 18.9, 22.0) in 2023/4.

Severe CMHC symptoms (CIS-R 18+) also rose in prevalence, from 6.9% (CI 6.4, 7.5) in 1993 and 8.5% (CI 7.8, 9.3) in 2007, up to 11.6% (CI 10.5, 12.8) in 2023/4.

The upward trend in CMHC symptoms was evident in both males and females, with scores consistently higher in females.

The upward trend in CMHC symptoms was evident across the 16 to 64 age range. In each age group, the proportion scoring 12 or more was higher in 2023/4 than it was in 1993. This was also true for the proportion scoring 18 or more.

There is evidence of different patterns of change over time among males and females in different age groups. These trends need to be treated with some caution as the base sizes for some age by sex combinations are small. However, it seems that in women, increases in rates over time have been steady and evident across different age groups, while the trends for men are less clear.

For more information: Table 1.2 and Table B1 for confidence intervals

Prevalence of CMHCs, by age and gender

One in five (20.2%) adults were identified with a CMHC in the past week, based on the CIS-R. If all adults in the population had been assessed, it is likely that the proportion would be between 18.9% and 21.6% (95% CI). This equates to an estimated 9.4 million adults living in England having a CMHC.

The most common CMHC, as in previous years of the survey, was CMHC-NOS (CMHC not otherwise specified) (8.6%, 95% CI 7.8, 9.5). Prevalence of other conditions was:

• 7.5% for generalised anxiety disorder (GAD) (CI 6.7, 8.4)
• 3.8% for depressive episode (CI 3.3, 4.5)
• 2.6% for phobias (CI 2.2, 3.2)
• 2.2% for OCD (CI 1.7, 2.8)
• 1.0% for panic disorder (CI 0.7, 1.5).

Women (24.2%) were more likely than men (15.4%) to have a CMHC. Specific CMHCs that were more prevalent in women than men were GAD (8.9%, CI 7.8, 10.2, compared with 5.7%, CI 4.7, 6.8), depression (4.5%, CI 3.7, 5.5, compared with 3.1%, CI 2.4, 3.9) and CMHC-NOS (10.5%, CI 9.3, 11.8, compared with 6.4%, CI 5.3, 7.7). The prevalence of phobias, OCD and panic disorder was similar among men and women.

People of working age (16 to 64) were more likely to have a CMHC than those aged 65 and over. This was also true for each type of CMHC (except for panic disorder). CMHC prevalence among those aged 75 and over was 10.2% (CI 8.3, 12.5), less than half that for those aged 16 to 64 (22.6%, CI 21.0, 24.3).

The pattern of association between age and depression was different for women and men. For women, prevalence of depression decreased with age, from 7.4% (CI 3.8, 14.1) of 16 to 24 year olds to 2.5% (CI 1.0, 5.8) of women aged 75 and over. For men, there was no clear association between depression and age. For other CMHCs, the pattern of association with age was similar for men and women.

For more information: Table 1.3, Table 1.4 and Table A2 for confidence intervals

Trends in CMHCs, 1993, 2000, 2007, 2014 and 2023/4

Note that the trends in this chapter are based on 16 to 64 year olds, to allow for comparison with 1993, and analysed by sex (male and female) rather than gender (men and women). See How to interpret the findings for information on how changes over time were assessed.

Among 16 to 64 year olds, CMHC prevalence increased over time, from 15.5% (95% CI 14.7, 16.3) in 1993, 17.5% in 2000 (CI 16.5, 18.5), 17.6% in 2007 (CI 16.5, 18.8) and 18.9% in 2014 (CI 17.7, 20.1), up to 22.6% (CI 21.0, 24.3) in 2023/4.

CMHC prevalence increased in both males and females aged 16 to 64. The proportion of males with a CMHC rose from 11.9% (10.9,12.9) in 1993 to 17.3% (15.2,19.5) in 2023/4. Among females, prevalence rose from 19.1% (18.0, 20.4) in 1993 to 27.8% (25.7, 30.1) in 2023/4. CMHC prevalence was consistently higher among females than males.

Patterns of change over time varied by type of CMHC. A particularly pronounced change was evident for GAD. Among 16 to 64 year olds, GAD prevalence was stable between 1993 (4.4%, CI 3.9, 4.8), 2000 (4.7%, CI 4.2, 5.3) and 2007 (4.7%, CI 4.2, 5.3), before increasing to 6.6% (CI 5.9, 7.4) in 2014 and 8.5% (7.5, 9.5) in 2023/4. The increase was in both males and females.

Depression, phobias, and OCD also increased significantly in prevalence since 2007.

• Depression rose from 2.6% (2.2, 3.1) in 2007 to 4.4% (3.8, 5.2) in 2023/4
• Phobias rose from 2.1% (1.8, 2.6) in 2007 to 3.3% (2.7, 4.0) in 2023/4
• OCD rose from 1.3% (1.0, 1.7) in 2007 to 2.6% (2.0, 3.4) in 2023/4.

The rise in depression was steeper for females than males, while for phobias the rise was steeper for males than females.

Prevalence of CMHC-NOS has remained broadly stable since 2000.

The upward trend in CMHCs was evident across the 16 to 64 age range. For every age group in this range, the proportion with a CMHC was higher in 2023/4 than it was in 1993.

There is evidence of different patterns of change since 2000 in different age groups and in males and females. These trends need to be treated with some caution as the base sizes for some age by sex combinations are small.

Increase in prevalence of any CMHC since 2000 was particularly prominent in those aged 16 to 24, from 14.6% (CI 12.0, 17.7) in 2000 to 25.8% (CI 20.8, 31.9) in 2023/4.

The increased prevalence of specific CMHCs since 2000 was also particularly steep for younger age groups.

The proportion of 16 to 24 year olds with GAD rose from 1.1% (CI 0.6, 2.1) in 2000 to 7.6% (CI 5.0, 11.6) in 2023/4. In 25 to 34 year olds, GAD rose in prevalence from 4.5% (CI 3.5, 5.8) in 2000, to 10.1% (CI 7.8, 12.6) in 2023/4.

The proportion of 16 to 24 year olds with OCD increased from 1.5% (CI 0.8, 2.9) in 2000 to 5.7% (CI 3.3, 9.6) in 2023/4.

For more information: Table 1.4 and Table B2 for confidence intervals

CMHCs, by CIS-R score

Among people with a CIS-R score of 18 or more, most met the criteria for a specific CMHC, and a quarter (27.9%) were classed as having CMHC-NOS. About half (48.4%) of those with severe CMHC symptoms (CIS-R 18+) were identified with GAD, a third (32.5%) with depression, and about a quarter (22.0%) with phobias.

Among those with a CIS-R score of 12 to 17, 70.5% were identified with CMHC-NOS.

For more information: Table 1.5

Variation in CMHCs by other characteristics

Ethnic group

Using age-standardised figures, overall variation in CMHC prevalence by ethnic group was not statistically significant. However, the number of participants in some ethnic groups was small and the confidence intervals around estimates were wide.

For more information: Table 1.6 and Table A3 for confidence intervals

Employment status

Age-standardised analyses of having a CMHC varied by employment status for those of working age (16 to 64 years). Prevalence of a CMHC in unemployed (40.0%) and economically inactive (38.8%) adults was twice that of employed adults (18.3%).

The strength of association between employment status and presence of a CMHC was stronger for men than women. Among employed adults, women (23.7%) were twice as likely as men (12.3%) to have a CMHC, while CMHC prevalence was similar in unemployed men (40.1%) and women (39.8%), and economically inactive men (38.4%) and women (38.3%).

For more information: Table 1.7

Problem debt

In age-standardised analyses, being seriously behind on at least one debt repayment or having utilities cut off was associated with greater likelihood of having a CMHC, as well as each type of CMHC. Adults with problem debt were more than twice as likely to have a CMHC (39.0%) as those without problem debt (18.4%). See the APMS 2023/4 Methods documentation for more information on how problem debt was derived.

The pattern of association between having a CMHC and having problem debt was similar in men and women.

For more information: Table 1.8

Likelihood of having a CMHC was associated with area-level deprivation. Prevalence of a CMHC was highest among those living in areas in the most deprived quintile (age-standardised 26.2%) and lowest among those living in areas in the least deprived quintile (16.0%).

The pattern of association between having a CMHC and area-level deprivation was similar in men and women.

For more information: Table 1.9

Region

The age-standardised prevalence of having a CMHC varied across regions in England. The proportion of adults with a CMHC was greatest in the East Midlands (24.6%) and the North East (24.6%) of England and lowest in the South East (16.3%) and South West (18.7%) of England.

For more information: Table 1.10

Comorbidity

Physical health conditions

Age-standardised prevalence of having a CMHC varied by the presence of a limiting physical health condition. Those with a limiting physical health condition (32.9%) were more likely than those without (12.6%) to have a CMHC. This association was stronger for men than women.

For more information: Table 1.11

Self-diagnosis and professional diagnosis of CMHCs

Participants were asked whether they thought they had ever had specific CMHCs (phobias, panic attacks, post-traumatic stress disorder, depression, postnatal depression, a ‘nervous breakdown’, obsessive compulsive disorder, seasonal affective disorder, or ‘any other anxiety disorder’). For each reported condition, they were asked if the condition had ever been diagnosed by a professional and whether the condition had been present in the past 12 months.

Overall, 45.4% of adults reported that they believed they have had a CMHC at some point in their life (36.1% of men, and 53.7% of women). 31.1% of all adults reported that they had received a diagnosis from a professional (22.1% of men and 39.3% of women), and 18.9% reported the presence of a professionally diagnosed CMHC in the past 12 months (13.3% of men and 24.0% of women). Women were more likely than men to believe they had ever had a CMHC, to report a professional diagnosis, and to report having symptoms of a diagnosed CMHC in the past 12 months.

Most (84.0%) participants identified by the CIS-R as having a CMHC believed that they have had a CMHC at some point and 66.5% reported that they had received a professional diagnosis. Over half (55.6%) of those with a current CMHC reported having a diagnosed CMHC with symptoms in the past year.

Among those identified by the CIS-R as having a CMHC, most (66.6%) felt that they have had depression, 45.8% felt that they have had ‘panic attacks’, and 29.4% felt that they have had ‘any other anxiety disorder’. Similarly, these were also the most common professional diagnoses that those identified by the CIS-R reported having been given: 55.1% reported having been diagnosed with depression, 29.4% reported having been diagnosed with panic attacks, and 21.0% reported having been diagnosed with ‘any other anxiety disorder’.

Of those identified by the CIS-R as having a depressive episode in the past week, 81.9% reported ever having depression. 72.2% had ever received a professional diagnosis of depression, and 67.7% reported the presence of diagnosed depression in the past 12 months.

Of adults identified by the CIS-R with panic disorder, 63.4% reported ever having ‘panic attacks’, 42.3% had ever received a professional diagnosis, and 35.2% reported the presence of diagnosed panic attacks within the past year.

Of adults identified by the CIS-R with GAD, 40.2% reported ever having ‘any other anxiety disorder’. Of those, 30.4% had received a professional diagnosis and 29.6% reported having symptoms of this other diagnosed anxiety disorder in the past year.

Among adults with less prevalent conditions, reports of having ever received a professional diagnosis were low. 29.7% of participants identified by the CIS-R with OCD reported ever having OCD, and 9.6% had ever received a professional diagnosis. Similarly, 12.5% of adults identified with a phobia reported ever having a phobia, and 3.3% had ever received a professional diagnosis for one.

Professional diagnosed CMHC (self-reported), by CMHC in past week (as identified by CIS-R)

For more information: Table 1.12

CMHCs are among the most prevalent health conditions in England. The results in this chapter show that at any recent point in time, about one in five adults in England had a CMHC in the past week; one in four women and almost one in six men. Around half of these people had symptoms severe enough to warrant active intervention (CIS-R 18+), and the rest would likely have benefited from at least clinical recognition (CIS-R 12-17). After the general category of CMHC-NOS (8.6%), generalised anxiety disorder (GAD) (7.5%) stands out as the most prevalent type of CMHC in England, followed by depression (3.8%), phobias (2.6%), obsessive compulsive disorder (OCD) (2.2%) and panic disorder (1.0%).

CMHCs have increased in prevalence over time, up from 15.5% of working age adults in 1993 to 22.6% in 2023/4. The small increase in CMHCs observed between 1993 and 2007 and the greater increase since then are likely to indicate a real shift in population prevalence of symptoms of anxiety and depression. This has occurred alongside various societal shifts and stresses, including global recession and subsequent policies of austerity (Curtis et al. 2021). For example, a cost of living crisis has led to increased rates of unmanageable personal debt (Financial Conduct Authority 2023), a known powerful risk factor for mental disorders (Jenkins et al. 2008, Meltzer et al. 2013a, ONS 2022). Increases in psychological distress were observed during the COVID-19 pandemic, however, evidence for the UK suggests that among adults this has largely returned to pre-pandemic levels (Pierce et al. 2021). It is also possible that overall increased public awareness and reduced stigma (Foulkes and Andrews 2023) may have also influenced response to CIS-R questions in survey participants, although generally the CIS-R is thought to perform well in multiple environments (Das-Munshi et al. 2014).

High levels of CMHC recognition and awareness. Four fifths of those identified by the CIS-R as having a CMHC also felt that they have had a CMHC, and two thirds reported that they had been diagnosed with a CMHC by a professional. However, results also indicate that anxiety disorders may be less well recognised, both by the public and by professionals, than depression. The symptoms identified by the survey instrument did not always match the diagnoses that participants reported being given by professionals. Most of those reporting a professional CMHC diagnosis said that they had been diagnosed with depression or panic attacks. This may reflect the language used by people when discussing their mental health with professionals, and may reflect people’s understanding of their own experiences of mental illness. When doctors and patients talk about mental health, it is likely that they use widely understood terms and symptoms such as ‘depression’ and ‘panic attacks’. Differences between disorders identified by the CIS-R and disorders that people report having had or having been diagnosed with may - but do not necessarily mean - that people have been misdiagnosed.

Increases across age groups, but particularly the young. Evidence from the Mental Health of Children and Young People surveys suggests that for young people, the COVID-19 pandemic had both a significant and a sustained effect on mental health (Newlove-Delgado et al. 2021; 2023). The results in this chapter show that a quarter of 16 to 24 year olds had a CMHC, the highest level observed in the APMS series. The upward trend in CMHCs among young people however was evident even before the COVID-19 pandemic, alongside indications that the profile of CMHCs among young people has been changing, with increases notable at the higher severity threshold (CIS-R 18+). Anxiety disorders, including generalized anxiety disorder, OCD and phobias, characterise CMHC presentation in 16 to 24 year olds. This chapter shows a notable proportion of young women identified with depression, although it must be noted that the sample size was small for comparing men and women in this age group. These trends also need to be understood in the context of results from other APMS chapters, especially in relation to increased levels of self-harming. While concerns about young people’s mental health have often been linked to digital technology and social media use, evidence for this as a key causal factor are weak (Orben et al. 2024). Issues spanning environmental, social, economic and political - as well as technological - change are likely to be factors (McGorry et al. 2024). Changes in parenting styles, especially increased risk aversion, have also been cited. One study found reductions between generations in young people’s home range, variety of outdoor spaces visited, range of activities undertaken, and in number of companions (Woolley and Griffin 2015).

Public health approaches and a cross-sectoral prevention role. The results presented in this chapter are consistent with the emphasis placed by England’s Prevention Concordat for Better Mental Health on addressing the social determinants of health. CMHCs were more prevalent in people struggling financially and in those with a limiting physical health condition. About 40% of people who were unemployed or economically inactive had a CMHC, with associated reliance on changing welfare support systems (Wickham et al. 2020). The results in this chapter show that area-level disparities persist, with CMHCs being more prevalent among people living in the most deprived neighbourhoods. Pronounced regional disparities in CMHCs are also evident: people in the North East (24.6%) and East Midlands (24.6%) were more likely to have a CMHC than those in the South East (16.3%) and South West (18.7%), highlighting the need for locally informed responses. The Prevention Concordat for Better Mental Health highlights the need for local areas to put in place effective prevention planning arrangements, aimed at health and wellbeing boards, local authorities, integrated care systems and other health partnerships (OHID 2024).

Abel, K. M., Carr, M. J., Ashcroft, D. M., Chalder, T., Chew-Graham, C. A., Hope, H., ... & Pierce, M. (2021). Association of SARS-CoV-2 infection with psychological distress, psychotropic prescribing, fatigue, and sleep problems among UK primary care patients. JAMA Network Open, 4(11), e2134803-e2134803.

Adji, A., Rhead, R., McManus, S., & Shoham, N. (2023). Associations between common mental disorders and menopause: cross-sectional analysis of the 2014 Adult Psychiatric Morbidity Survey. BJPsych Open, 9(4), e103.

Ahmad, G., McManus, S., Cooper, C., Hatch, S. L., & Das-Munshi, J. (2022). Prevalence of common mental disorders and treatment receipt for people from ethnic minority backgrounds in England: repeated cross-sectional surveys of the general population in 2007 and 2014. The British Journal of Psychiatry, 221(3), 520-527.

Bebbington, P. E., Jonas, S., Brugha, T., Meltzer, H., Jenkins, R., Cooper, C., ... & McManus, S. (2011). Child sexual abuse reported by an English national sample: characteristics and demography. Social Psychiatry and Psychiatric Epidemiology, 46, 255-262.

Bebbington, P. E., McManus, S., Coid, J. W., Garside, R., & Brugha, T. (2021). The mental health of ex-prisoners: analysis of the 2014 English National Survey of Psychiatric Morbidity. Social Psychiatry and Psychiatric Epidemiology, 1-11.

Bebbington, P. E., & McManus, S. (2020). Revisiting the one in four: the prevalence of psychiatric disorder in the population of England 2000–2014. The British Journal of Psychiatry, 216(1), 55-57.

Beshai, S., Dobson, K. S., Bockting, C. L., & Quigley, L. (2011). Relapse and recurrence prevention in depression: current research and future prospects. Clinical Psychology Review, 31(8), 1349-1360.

Bhavsar, V., Dorrington, S., Morgan, C., Hatch, S. L., McGuire, P., Fusar-Poli, P., ... & Hotopf, M. (2021). Psychotic experiences, psychiatric comorbidity and mental health need in the general population: a cross-sectional and cohort study in Southeast London. Psychological Medicine, 51(1), 147-157.

Bhavsar, V., McManus, S., Saunders, K., & Howard, L. M. (2023). Intimate partner violence perpetration and mental health service use in England: analysis of nationally representative survey data. BJPsych Open, 9(3), e64.

Bogdanova, N., Cooper, C., Ahmad, G., McManus, S., & Shoham, N. (2022). Associations between sociodemographic characteristics and receipt of professional diagnosis in Common Mental Disorder: Results from the Adult Psychiatric Morbidity Survey 2014. Journal of Affective Disorders, 319, 112-118.

Brewer, M., Dang, T., & Tominey, E. (2024). Universal Credit: Welfare reform and mental health. Journal of Health Economics, 98, 102940.

Bunce, A., Hashemi, L., Clark, C., Stansfeld, S., Myers, C. A., & McManus, S. (2024). Prevalence and nature of workplace bullying and harassment and associations with mental health conditions in England: a cross-sectional probability sample survey. BMC Public Health, 24(1), 1147.

Butterworth, P., Leach, L. S., McManus, S., & Stansfeld, S. A. (2013). Common mental disorders, unemployment and psychosocial job quality: is a poor job better than no job at all?. Psychological Medicine, 43(8), 1763-1772.

Chilman, N., Schofield, P., McManus, S., Ronaldson, A., Stagg, A., & Das-Munshi, J. (2024). The public health significance of prior homelessness: findings on multimorbidity and mental health from a nationally representative survey. Epidemiology and Psychiatric Sciences, 33, e63.

Collins, B., Downing, J., Head, A., Comerford, T., Nathan, R., & Barr, B. (2023). Investigating the impact of undiagnosed anxiety and depression on health and social care costs and quality of life: cross-sectional study using household health survey data. BJPsych Open, 9(6), e201.

Cook, E. A., & McManus, S. (2024). Indirect victims of violence: Mental health and the close relatives of serious assault victims in England. Social Science & Medicine, 359, 117278.

Cooper, C., Bebbington, P., King, M., Brugha, T., Meltzer, H., Bhugra, D., & Jenkins, R. (2007). Why people do not take their psychotropic drugs as prescribed: results of the 2000 National Psychiatric Morbidity Survey. Acta Psychiatrica Scandinavica, 116(1), 47-53.

Curtis, S., Cunningham, N., Pearce, J., Congdon, P., Cherrie, M., & Atkinson, S. (2021). Trajectories in mental health and socio-spatial conditions in a time of economic recovery and austerity: A longitudinal study in England 2011–17. Social Science & Medicine, 270, 113654.

Darzi, L. (2024) Independent Investigation of the National Health Service in England. http:// https://www.gov.uk/government/publications/independent-investigation-of-the-nhs-in-england

Das‐Munshi, J., Castro‐Costa, E., Dewey, M. E., Nazroo, J., & Prince, M. (2014). Cross‐cultural factorial validation of the Clinical Interview Schedule–Revised (CIS‐R); findings from a nationally representative survey (EMPIRIC). International Journal of Methods in Psychiatric Research, 23(2), 229-244.

Das-Munshi, J., Goldberg, D., Bebbington, P. E., Bhugra, D. K., Brugha, T. S., Dewey, M. E., ... & Prince, M. (2008). Public health significance of mixed anxiety and depression: beyond current classification. The British Journal of Psychiatry, 192(3), 171-177.

Department for Work and Pensions (2024) Universal Credit Work Capability Assessment, April 2019 to December 2023. https://www.gov.uk/government/statistics/universal-credit-work-capability-assessment-statistics-april-2019-to-december-2023/universal-credit-work-capability-assessment-april-2019-to-december-2023

Dykxhoorn, J., Osborn, D., Walters, K., Kirkbride, J. B., Gnani, S., & Lazzarino, A. I. (2024). Temporal patterns in the recorded annual incidence of common mental disorders over two decades in the United Kingdom: a primary care cohort study. Psychological Medicine, 54(4), 663-674.

Fadeeva, A., Hashemi, L., Cooper, C., Stewart, R., & McManus, S. (2024). Violence against older people and associations with mental health: A national probability sample survey of the general population in England. Journal of Affective Disorders, 363, 1-7.

Financial Conduct Authority. (2023). Financial Lives 2022: Key findings from the FCA’s Financial Lives May 2022 survey. https://www.fca.org.uk/publication/financial-lives/financial-lives-survey-2022-key-findings.pdf

Foulkes, L. and Andrews, J.L. (2023). Are mental health awareness efforts contributing to the rise in reported mental health problems? A call to test the prevalence inflation hypothesis. New Ideas in Psychology, 69, p.101010.

Goldberg, D. P., & Huxley, P. (1992). Common mental disorders: a bio-social model. Tavistock/Routledge.

Graham, H., White, P., Cotton, J., & McManus, S. (2019). Flood-and weather-damaged homes and mental health: An analysis using England’s Mental Health Survey. International Journal of Environmental Research and Public Health, 16(18), 3256.

Harris, J., Hall, J., Meltzer, H., Jenkins, R., Oreszczyn, T. & McManus, S. (2010) Health, mental health and housing conditions in England. Eaga Charitable Trust and NatCen: London. https://www.fuelpovertylibrary.info/sites/default/files/EAGA14%20%282010%29%20%20 REPORT%20Health%20mental%20health%20and%20housing%20conditions%20in%20England.pdf

Hashemi, L., Fadeeva, A., Khan, N., & McManus, S. (2025). Intimate partner violence and physical health in England: Gender stratified analyses of a probability sample survey. Women's Health, 21, 17455057251326419.

Kessler, D., Bennewith, O., Lewis, G., & Sharp, D. (2002). Detection of depression and anxiety in primary care: follow up study. BMJ, 325(7371), 1016-1017.

Kirkbride, J. B., Anglin, D. M., Colman, I., Dykxhoorn, J., Jones, P. B., Patalay, P., ... & Griffiths, S. L. (2024). The social determinants of mental health and disorder: evidence, prevention and recommendations. World Psychiatry, 23(1), 58-90.

Jenkins, R., Bhugra, D., Bebbington, P., Brugha, T., Farrell, M., Coid, J., ... & Meltzer, H. (2008). Debt, income and mental disorder in the general population. Psychological Medicine, 38(10), 1485-1493.

Lapham, C., Conolly, A., & McManus, S. (2024). A health, social and economic profile of Employment and Support Allowance (ESA) recipients in the 2014 Adult Psychiatric Morbidity Survey. Department for Work and Pensions.

Lewis, G., Pelosi, A. J., Araya, R., & Dunn, G. (1992). Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychological Medicine, 22(2), 465-486.

Lowther-Payne, H. J., Ushakova, A., Beckwith, A., Liberty, C., Edge, R., & Lobban, F. (2023). Understanding inequalities in access to adult mental health services in the UK: a systematic mapping review. BMC Health Services Research, 23(1), 1042.

McGorry, P. D., Mei, C., Dalal, N., Alvarez-Jimenez, M., Blakemore, S. J., Browne, V., ... & Killackey, E. (2024). The Lancet Psychiatry Commission on youth mental health. The Lancet Psychiatry, 11(9), 731-774.

McDaid, D., Park, AL., & Mental Health Foundation (2022). The economic case for investing in the prevention of mental health conditions in the UK. https://www.mentalhealth.org.uk/sites/default/files/2022-06/MHF-Investing-in-Prevention-Full-Report.pdf

McGrath, J. J., Lim, C. C. W., Plana-Ripoll, O., Holtz, Y., Agerbo, E., Momen, N. C., ... & De Jonge, P. (2020). Comorbidity within mental disorders: a comprehensive analysis based on 145 990 survey respondents from 27 countries. Epidemiology and Psychiatric Sciences, 29, e153.

McManus, S., Bebbington, P. E., Tanczer, L., Scott, S., & Howard, L. M. (2021). Receiving threatening or obscene messages from a partner and mental health, self-harm and suicidality: results from the Adult Psychiatric Morbidity Survey. Social Psychiatry and Psychiatric Epidemiology, 1-11.

McManus, S., Walby, S., Barbosa, E. C., Appleby, L., Brugha, T., Bebbington, P. E., ... & Knipe, D. (2022). Intimate partner violence, suicidality, and self-harm: a probability sample survey of the general population in England. The Lancet Psychiatry, 9(7), 574-583.

McManus, S., Bebbington, P. E., Jenkins, R., Morgan, Z., Brown, L., Collinson, D., & Brugha, T. (2020). Data resource profile: adult psychiatric morbidity survey (APMS). International Journal of Epidemiology, 49(2), 361-362e.

McManus, S., & Gunnell, D. (2020). Trends in mental health, non‐suicidal self‐harm and suicide attempts in 16–24-year old students and non-students in England, 2000–2014. Social Psychiatry and Psychiatric Epidemiology, 55(1), 125-128.

Meltzer, H., Vostanis, P., Ford, T., Bebbington, P., & Dennis, M. S. (2011). Victims of bullying in childhood and suicide attempts in adulthood. European Psychiatry, 26(8), 498-503.

Meltzer, H., Bebbington, P., Brugha, T., Farrell, M., & Jenkins, R. (2013a). The relationship between personal debt and specific common mental disorders. The European Journal of Public Health, 23(1), 108-113.

Meltzer, H., Bebbington, P., Dennis, M. S., Jenkins, R., McManus, S., & Brugha, T. S. (2013b). Feelings of loneliness among adults with mental disorder. Social Psychiatry and Psychiatric Epidemiology, 48, 5-13.

Meltzer, H., Brugha, T., Dennis, M. S., Hassiotis, A., Jenkins, R., McManus, S., ... & Bebbington, P. (2012a). The influence of disability on suicidal behaviour. Alter, 6(1), 1-12.

Meltzer, H., Ford, T., Bebbington, P., & Vostanis, P. (2012b). Children who run away from home: Risks for suicidal behavior and substance misuse. Journal of Adolescent Health, 51(5), 415-421.

National Institute for Health and Care Excellence. (2020). Generalised anxiety disorder and panic disorder in adults: management - Clinical guideline [CG113]. https://www.nice.org.uk/guidance/cg113/

National Institute for Health and Care Excellence. (2022). Depression in adults: treatment and management – NICE guideline [NG222]. https://www.nice.org.uk/guidance/ng222

Newlove-Delgado, T., McManus, S., Sadler, K., Thandi, S., Vizard, T., Cartwright, C., ... & of Children, M. H. (2021). Child mental health in England before and during the COVID-19 lockdown. The Lancet Psychiatry, 8(5), 353.

Newlove-Delgado, T., Marcheselli, F., Williams, T., Mandalia, D., Davis, J., McManus, S., ... & Ford, T. (2023). Mental Health of Children and Young People in England, 2023-wave 4 follow up to the 2017 survey. NHS England.

NHS. (2019). The NHS Long Term Plan. https://www.longtermplan.nhs.uk/ 

Nimmo‐Smith, V., Brugha, T. S., Kerr, M. P., McManus, S., & Rai, D. (2016). Discrimination, domestic violence, abuse, and other adverse life events in people with epilepsy: population‐based study to assess the burden of these events and their contribution to psychopathology. Epilepsia, 57(11), 1870-1878.

Office for Health Improvement & Disparities. (2024, updated). Prevention Concordat for Better Mental Health. https://www.gov.uk/government/publications/prevention-concordat-for-better-mental-health -consensus-statement/prevention-concordat-for-better-mental-health#about-the-prevention-concordat

Office for National Statistics. (2022). Cost of living and depression in adults, Great Britain: 29 September to 23 October 2022. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/mentalhealth/articles/costof livinganddepressioninadultsgreatbritain/29septemberto23october2022#cost-of-living-and-depressive-symptoms

Office for National Statistics. (2023). Sickness absence in the UK labour market: 2022. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/labourproductivity/articles/sickness absenceinthelabourmarket/2022

Orben, A., Meier, A., Dalgleish, T., & Blakemore, S. J. (2024). Mechanisms linking social media use to adolescent mental health vulnerability. Nature Reviews Psychology, 3(6), 407-423.

Parry, J., Young, Z., Bevan, S., Veliziotis, M., Baruch, Y., Beigi, M., Bajorek, Z., Richards, S. and Tochia, C. (2022). Work After Lockdown: No Going Back what we have learned from working from home through the COVID-19 pandemic. University of Southampton.

Pierce, M., Hope, H., Ford, T., Hatch, S., Hotopf, M., John, A., ... & Abel, K. M. (2020). Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. The Lancet Psychiatry, 7(10), 883-892.

Pierce, M., McManus, S., Hope, H., Hotopf, M., Ford, T., Hatch, S. L., ... & Abel, K. M. (2021). Mental health responses to the COVID-19 pandemic: a latent class trajectory analysis using longitudinal UK data. The Lancet Psychiatry, 8(7), 610-619.

Pitman, A., Marston, L., Lewis, G., Semlyen, J., McManus, S., & King, M. (2022). The mental health of lesbian, gay, and bisexual adults compared with heterosexual adults: results of two nationally representative English household probability samples. Psychological Medicine, 52(15), 3402-3411.

Plana-Ripoll, O., Pedersen, C. B., Agerbo, E., Holtz, Y., Erlangsen, A., Canudas-Romo, V., ... & Laursen, T. M. (2019). A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study. The Lancet, 394(10211), 1827-1835.

Public Health England. (2018). Health matters: reducing health inequalities in mental illness. https://www.gov.uk/government/publications/health-matters-reducing-health-inequalities-in-mental-illness/health-matters-reducing-health-inequalities-in-mental-illness

Puddephatt, J. A., Jones, A., Gage, S. H., Fear, N. T., Field, M., McManus, S., ... & Goodwin, L. (2021). Associations of alcohol use, mental health and socioeconomic status in England: findings from a representative population survey. Drug and Alcohol Dependence, 219, 108463.

Rhead, R. D., Woodhead, C., Ahmad, G., Das-Munshi, J., McManus, S., & Hatch, S. L. (2022). A comparison of single and intersectional social identities associated with discrimination and mental health service use: data from the 2014 Adult Psychiatric Morbidity Survey in England. Social Psychiatry and Psychiatric Epidemiology, 57(10), 2049-2063.

Shoham, N., Lewis, G., McManus, S., & Cooper, C. (2019). Common mental illness in people with sensory impairment: results from the 2014 adult psychiatric morbidity survey. BJPsych 0pen, 5(6), e94.

Solmi, M., Cortese, S., Vita, G., De Prisco, M., Radua, J., Dragioti, E., ... & Correll, C. U. (2023). An umbrella review of candidate predictors of response, remission, recovery, and relapse across mental disorders. Molecular Psychiatry, 28(9), 3671-3687.

Stansfeld, S., Smuk, M., Onwumere, J., Clark, C., Pike, C., McManus, S., ... & Bebbington, P. (2014). Stressors and common mental disorder in informal carers–An analysis of the English Adult Psychiatric Morbidity Survey 2007. Social Science & Medicine, 120, 190-198.

Stevelink, S. A., Bakolis, I., Dorrington, S., Downs, J., Leal, R., Madan, I., ... & Fear, N. T. (2024). Universal Credit receipt among working-age patients who are accessing specialist mental health services: results from a novel data linkage study. J Epidemiol Community Health, 78(9), 592-598.

Taxiarchi, V. P., Senior, M., Ashcroft, D. M., Carr, M. J., Hope, H., Hotopf, M., ... & Pierce, M. (2023). Changes to healthcare utilisation and symptoms for common mental health problems over the first 21 months of the COVID-19 pandemic: parallel analyses of electronic health records and survey data in England. The Lancet Regional Health–Europe, 32.

Wardle, H., John, A., Dymond, S., & McManus, S. (2020). Problem gambling and suicidality in England: secondary analysis of a representative cross-sectional survey. Public Health, 184, 11-16.

Weich, S., Sloggett, A., & Lewis, G. (1998). Social roles and gender difference in the prevalence of common mental disorders. The British Journal of Psychiatry, 173(6), 489-493.

Wickham, S., Bentley, L., Rose, T., Whitehead, M., Taylor-Robinson, D., & Barr, B. (2020). Effects on mental health of a UK welfare reform, Universal Credit: a longitudinal controlled study. The Lancet Public Health, 5(3), e157-e164.

Woodhead, C., Rona, R. J., Iversen, A., MacManus, D., Hotopf, M., Dean, K., ... & Fear, N. T. (2011). Mental health and health service use among post-national service veterans: results from the 2007 Adult Psychiatric Morbidity Survey of England. Psychological Medicine, 41(2), 363-372.

Woolley, H. E., & Griffin, E. (2015). Decreasing experiences of home range, outdoor spaces, activities and companions: changes across three generations in Sheffield in north England. Children's Geographies, 13(6), 677-691.

World Health Organization. (1993). The ICD-10 classification of mental and behavioural disorders. World Health Organization.

World Health Organization. (2022). ICD-11: International classification of diseases (11th revision). https://icd.who.int/

Please cite this chapter as:

Liubertiene, G., Sloman, A., Morris, S., Bhavsar, V., Clark, C., Das-Munshi, J., Jenkins, R., McManus, S., Oram, S., & Wessely, S. (2025). Common mental health conditions. In Morris, S., Hill, S., Brugha, T., McManus, S. (Eds.), Adult Psychiatric Morbidity Survey: Survey of Mental Health and Wellbeing, England, 2023/4. NHS England.