In line with previous research [2, 18, 19], we found large variation in involuntary hospitalisation under the MHA across areas in England. There was a four-fold difference between the CCGs with the highest and lowest rates. In an adjusted analysis, CCGs with a higher percentage of severe mental illness, higher male population, and more community and outpatient mental health visits showed higher MHA use. Urbanicity, ethnicity, age, and deprivation were not strongly associated with MHA use when analyses were adjusted.

Higher severe mental illness in the population was the factor most strongly associated with higher MHA use in the current study. The level of depression, however, was not associated with MHA use in unadjusted or adjusted analyses. This finding builds on previous ecological studies conducted in England, which have so far been unable to control for differences in levels of severe mental illness between areas [18, 19]. Studies of individuals have consistently linked severe mental illness to involuntary hospitalisation [9, 11, 33, 34], suggesting that involuntary mental health treatment is most used for those with bipolar or psychotic disorders. This is likely due to reduced capacity to consent and perceived higher risk [35], meaning people with these conditions more often meet the criteria for involuntary detention. However, it is unclear whether levels of severe mental illness are rising substantially [12, 36], and so this is unlikely to fully explain rising involuntary hospitalisations.

Areas with a higher proportion of males also showed higher involuntary hospitalisations in our study. Males may exhibit higher perceived or actual dangerousness, meaning they are seen as a higher risk to themselves or others, a key factor for MHA detention [37]. Higher detention of males may also relate to differences in help-seeking behaviour [38]. Males are less likely to be in contact with mental health services [39, 40], which may lead to more involuntary hospitalisations when experiencing a mental health crisis [11, 41]. While male gender and reduced contact with mental health services are seen to separately predict involuntary hospitalisation [11], these factors have not yet been linked empirically.

We found higher community and outpatient mental health use to be associated with higher involuntary hospitalisations across CCGs. This association remained after controlling for other area-level factors, including the percentage of severe mental illness. Previously, higher community healthcare spending and better community services have been linked to higher involuntary hospitalisations [2, 19, 42]. This is concerning as greater access to community treatment should reduce the need for involuntary inpatient care [8, 9, 43]. It could be the case that greater access to community treatment means those in need of involuntary hospitalisation are better identified [19]. However, as involuntary treatment often results in poor outcomes [5, 6], these findings suggest that community services need to be improved to provide earlier interventions for mental health and reduce unnecessary involuntary hospitalisation.

We did not find higher urbanicity, deprivation, or the percentage of population aged 18 to 35 to be associated with higher involuntary hospitalisation in the adjusted analysis. This is mostly in contradiction with previous work [15, 16, 18, 19], and could suggest that these factors do not affect involuntary hospitalisations when other variables are accounted for. Furthermore, an area having a higher percentage of non-White population was not strongly associated with higher MHA detentions in the adjusted analysis. Similar work has found that increased detention of BAME populations is mostly attributable to these populations showing higher severe mental illness, younger age, and living in urban areas [15, 16, 18]. However, higher urbanicity, non-White population, deprivation, and percentage of people aged 18 to 35 were all associated with higher MHA use in the unadjusted analyses. Complex relationships between these variables and mental illness may complicate our results [47, 48], masking each variable’s individual contribution at the area-level. For example, an area having higher deprivation, urbanicity, young population, and non-White population could contribute to higher SMI and, in turn, higher MHA use. Future research should aim to disentangle these relationships, ideally using longitudinal methods, to better understand how these variables interact to increase use of the MHA. As the population in England is rising, particularly in urban areas which show higher rates of ethnic diversity, deprivation, younger population, and mental illness [18], this could explain some of the rise in involuntary hospitalisation.

To explore these relationships further, we looked at urban and rural areas separately. However, we found no clear evidence that risk factors differ based on urbanicity. These findings differ from Keown et al. [18], who suggested that younger age and higher ethnic density were associated with involuntary hospitalisation in urban areas only. Our results suggest that when all factors are considered, higher area-level ethnic density and younger age profile are not risk factors for involuntary hospitalisation in either rural or urban areas. Our results may differ due to the addition of area-level severe mental illness in our study.

Explanatory variables used in the current study explained 10.68% of the variance in MHA detentions between CCGs. This is similar to Weich et al. [19] and suggests that, even with the addition of severe mental illness, there are further variables that produce variation in involuntary hospitalisation across England. We controlled for clustering within NHS England regions that oversaw CCGs, but the addition of these regions to the analysis did not improve the model fit. This suggests that little variance in MHA detention was explained by differences in service provision between NHS England regions. While NHS England regions oversaw CCGs, the roles of these groups were not always well defined, and mental health service provision may instead be more influenced by NHS Mental Health Trusts [49]. Differences in service provision and implementation of the MHA may explain some of the remaining variance between areas. Examining these differences further may highlight overuse or misuse of the MHA, which can be targeted to reduce involuntary hospitalisations. We were not able to include area-level indicators for migration, marital status, accommodation, employment, and substance misuse, which may also explain some of the remaining variance [9,10,11, 16].

The current study used national, open access data sets to better understand what causes variation in involuntary hospitalisation between areas in England. The completeness of the data and the addition of demographic, clinical, and socioeconomic variables is a strength. Unlike previous population studies conducted in England [18, 19], we included the percentage of mental illness in the population. Mental illness is an important factor identified in the literature [11], and its addition to the current study helps us understand what variables increase the rate of MHA detentions when controlling for area-level severe mental illness. Furthermore, by using recent data we have accounted for changes in demographics and government policy that have influenced involuntary hospitalisations in England over the past 10 years [3, 8].

One limitation of the current study is the quality of MHA data reported to the Mental Health Services Data Set [20]. The Mental Health Services Data Set quality report assesses the completeness and coverage of MHA data by comparing current data to older, but more complete, datasets [50]. They report that many eligible healthcare providers did not provide data on MHA use and others provided incomplete data. However, it is difficult to assess the extent of these issues across time and geographical regions due to changing CCG boundaries, organisations closing or merging, and differing methods across datasets. Dorset Healthcare University NHS Foundation Trust was the largest eligible organisation to fail to provide MHA data in 2021/22 [50, Appendix 2, Table 9]. For this reason, Dorset CCG was excluded from our analysis. Other eligible organisations reported fewer MHA detentions in previous years, and so this is not expected to affect our data substantially.

Furthermore, while most of the data used was collected between 2019 and 2022, the age and sex variables were extrapolated from the 2011 Census [51]. These variables may therefore not capture the true values in the population.

Only the percentage of “non-White” population was available at CCG-level. This is an issue as different ethnicities are at differing risk of involuntary hospitalisation [14], and combining these groups may have attenuated the effect of ethnicity. Furthermore, as CCGs covered large areas, the affect of neighbourhood-level ethnic density could not be assessed. Some evidence suggests that living in neighbourhoods of higher own-ethnic density could act as a protective factor against mental illness [52]. However, the effect of neighbourhood ethnic density on involuntary hospitalisation in England is not clear [53].

The current study adds to evidence of large variation in MHA use across England [18, 19], but suggests this variation is largely unexplained by demographic, clinical, and socioeconomic differences between areas. Future research should focus on whether differences in service provision and application of the MHA between areas of England is contributing to variation in involuntary hospitalisation rates. This would allow us to better understand and tackle rising rates of MHA use.

Our findings do point to some potential causes of rising involuntary hospitalisations for mental health care. The population of England is rising, particularly in urban areas which show higher rates of ethnic diversity, deprivation, younger population, and mental illness [18]. This, paired with inadequate provision of community and inpatient mental health services [19, 42], may be driving rising rates of involuntary hospitalisation. While many of these factors were not associated with MHA use in our adjusted analyses, their influence at the area level may be masked by complex relationships. As such, the current study suggests a need to disentangle relationships between ethnicity, urbanicity, deprivation, age, mental illness, and use of community mental health services if we are to understand and combat rising rates of involuntary detention.

Our findings suggest that areas with higher severe mental illness, higher community mental health service use, and higher male population may benefit the most from interventions to reduce involuntary hospitalisation. We found that areas with higher community mental health use showed higher MHA detentions, suggesting that current community service provision in England may not be effective in reducing involuntary hospitalisation. Therefore, more research needs to assess how services can be improved to reduce involuntary hospitalisation in England. The current literature on interventions to reduce involuntary hospitalisation has found weak to moderate success of staff training, joint decision making, and integrated care interventions [54, 55]. However, researchers may need to focus on targeting potential risk factors for detention which may, in turn, help us to understand why MHA use is rising in England. For example, if help-seeking in males with severe mental illness is targeted, and this reduces the number of males being involuntarily hospitalised, then male gender can be more confidently identified as a risk factor.