Parity of esteem begins at home: translating empirical psychiatric research into effective public mental health

Area deprivation, urbanicity, severe mental illness and social drift - A population-based linkage study using routinely collected primary and secondary care data

We investigated whether associations between area deprivation, urbanicity and elevated risk of severe mental illnesses (SMIs, including schizophrenia and bipolar disorder) is accounted for by social drift or social causation. We extracted primary and secondary care electronic health records from 2004 to 2015 from a population of 3.9 million. We identified prevalent and incident individuals with SMIs and their level of deprivation and urbanicity using the Welsh Index of Multiple Deprivation (WIMD) and urban/rural indicator. The presence of social drift was determined by whether odds ratios (ORs) from logistic regression is greater than the incidence rate ratios (IRRs) from Poisson regression. Additionally, we performed longitudinal analysis to measure the proportion of change in deprivation level and rural/urban residence 10 years after an incident diagnosis of SMI and compared it to the general population using standardised rate ratios (SRRs). Prevalence and incidence of SMIs were significantly associated with deprivation and urbanicity (all ORs and IRRs significantly >1). ORs and IRRs were similar across all conditions and cohorts (ranging from 1.1 to 1.4). Results from the longitudinal analysis showed individuals with SMIs are more likely to move compared to the general population. However, they did not preferentially move to more deprived or urban areas. There was little evidence of downward social drift over a 10-year period. These findings have implications for the allocation of resources, service configuration and access to services in deprived communities, as well as, for broader public health interventions addressing poverty, and social and environmental contexts.

Waiting time variation in Early Intervention Psychosis services: longitudinal evidence from the SEPEA naturalistic cohort study

PURPOSE

Early Intervention Psychosis [EIP] services have gained traction internationally, but are currently undergoing various forms of reconfiguration. In England, such services are now mandated to ensure 50% of accepted referrals commence care within 14 days, but no empirical evidence exists. We sought to estimate waiting times to EIP services in a large, representative epidemiological cohort in England, and investigate possible reasons for any variation.

METHODS

We estimated median waiting time from referral to acceptance by EIP services and investigated whether this varied by clinical, demographic or neighbourhood-level factors, amongst 798 participants, 16-35 years old, presenting to six EIP services over 3.5 years in a defined catchment area serving 2.5 million people. We used parametric survival analysis to inspect variation in waiting times (in days).

RESULTS

Median waiting time was 15 days (interquartile range 7-30), although this varied across services (p < 0.01). Waiting times increased over the case ascertainment period by an average of 4.3 days (95% CI 1.3, 6.2; p < 0.01). Longer waiting times were associated with greater diagnostic uncertainty, indexed by an organic presentation (+ 9.1 days; 95% CI 1.9, 16.6; p < 0.01), polysubstance abuse (+ 2.6; 0.6, 3.9; p < 0.01), absence of psychotic disorder (+1.8; -0.1, 3.0; p = 0.05) and insidious onset (+1.8; -0.1, 3.0; p = 0.06). Waiting times did not vary by most demographic or neighbourhood-level characteristics.

CONCLUSIONS

EIP services operate close to new waiting time standards in England, with little systematic variation by sociodemographic position. However, waiting times increased over the study period, coinciding with substantial service reorganisation. Longer waiting times associated with greater diagnostic uncertainty highlight opportunities to reduce delays in certain clinical groups at initial referral.

Neighbourhood level social deprivation and the risk of psychotic disorders: a systematic review

PURPOSE

The incidence of psychotic disorders varies according to the geographical area, and it has been investigated whether neighbourhood level factors may be associated with this variation. The aim of this systematic review is to collate and appraise the literature on the association between social deprivation and the incidence or risk for psychotic disorders.

METHOD

A systematic review was conducted, and studies were included if they were in English, provided a measure of social deprivation for more than one geographically defined area and examined either the correlation, rate ratio or risk of psychotic disorder. A defined search strategy was undertaken with Medline, CINAHL Plus and PsychInfo databases.

RESULTS

A total of 409 studies were identified in the search, of which 28 fulfilled the inclusion criteria. Of these, four examined the association between social deprivation at the time of birth, three examined the putative prodrome of psychosis or those at ultra-high risk (UHR) for psychosis, and 23 examined the time at presentation with a first episode of psychosis (FEP) (one study examined two time points and one study included both UHR and FEP). Three of the studies that examined the level of social deprivation at birth found an association with a higher risk for psychotic disorders and increased social deprivation. Seventeen of the 23 studies found that there was a higher risk or rate of psychotic disorders in more deprived neighbourhoods at the time of presentation; however, adjusting for individual factors tended to weaken this association. Limited research has been conducted in the putative prodromal stage and has resulted in conflicting findings.

CONCLUSIONS

Research conducted to date has not definitively identified whether the association is a result of social causation or social drift; however, the findings do have significant implications for service provision, such as the location and access of services.

Neighbourhood characteristics and the incidence of first-episode psychosis and duration of untreated psychosis

BACKGROUND

The incidence of psychotic disorders varies between geographical areas and it has been hypothesized that neighbourhood-level factors may influence this variation. It is also plausible that the duration of untreated psychosis (DUP) is associated with neighbourhood characteristics. The aims of this study were to determine whether the incidence of first-episode psychosis (FEP) and the DUP are associated with the level of social deprivation, fragmentation, social capital and population density.

METHOD

All individuals with a FEP from a geographical defined catchment area over a 5-year period were included. Age-standardized incidence rates were calculated for each neighbourhood factor.

RESULTS

A total of 292 cases of FEP were included in the study and 45% had a diagnosis of a schizophrenia-spectrum disorder. The age standardized incidence rate of FEP in the most deprived area was 72.4 [95% confidence interval (CI) 26.4-162.7] per 100 000 person-years compared with 21.5 (95% CI 17.6-26.0) per 100 000 person-years in the most affluent areas. This represents a 3.4-fold increase in FEP incidence in the most deprived areas. The incidence of FEP was also increased in neighbourhoods that were more socially fragmented [incidence rate ratio (IRR) = 2.40, 95% CI 1.05-5.51, p = 0.04] and there was a trend for the incidence to be increased in neighbourhoods with lower social capital (IRR = 1.43, 95% CI 0.99-2.06, p = 0.05). The median DUP was 4 months and was higher in more socially fragmented neighbourhoods.

CONCLUSIONS

The incidence of psychotic disorders is related to neighbourhood factors and it may be useful to consider neighbourhood factors when allocating resources for early intervention services.

Epidemiology on demand: population-based approaches to mental health service commissioning

One in three people will experience a mental health problem in their lifetime, but the causes and consequences of psychiatric morbidity are socially patterned. Epidemiological studies can provide aetiological clues about the causes of disorder, and when they can provide robust estimates about risk in different strata of the population these can also be used translationally, to provide commissioners and service planners with detailed information about local service need. This approach is illustrated using a newly developed population-level prediction tool for first-episode psychosis, PsyMaptic. Such public mental health prediction tools could be used to improve allocation of finite resources, by integrating evidence-based healthcare, public health and epidemiology together.