Small area-level variation in the incidence of psychotic disorders in an urban area in France: an ecological study

Small area variations in non-affective first-episode psychosis: the role of socioeconomic and environmental factors

BACKGROUND

There is strong evidence supporting the association between environmental factors and increased risk of non-affective psychotic disorders. However, the use of sound statistical methods to account for spatial variations associated with environmental risk factors, such as urbanicity, migration, or deprivation, is scarce in the literature.

METHODS

We studied the geographical distribution of non-affective first-episode psychosis (NA-FEP) in a northern region of Spain (Navarra) during a 54-month period considering area-level socioeconomic indicators as putative explanatory variables. We used several Bayesian hierarchical Poisson models to smooth the standardized incidence ratios (SIR). We included neighborhood-level variables in the spatial models as covariates.

RESULTS

We identified 430 NA-FEP cases over a 54-month period for a population at risk of 365,213 inhabitants per year. NA-FEP incidence risks showed spatial patterning and a significant ecological association with the migrant population, unemployment, and consumption of anxiolytics and antidepressants. The high-risk areas corresponded mostly to peripheral urban regions; very few basic health sectors of rural areas emerged as high-risk areas in the spatial models with covariates.

DISCUSSION

Increased rates of unemployment, the migrant population, and consumption of anxiolytics and antidepressants showed significant associations linked to the spatial-geographic incidence of NA-FEP. These results may allow targeting geographical areas to provide preventive interventions that potentially address modifiable environmental risk factors for NA-FEP. Further investigation is needed to understand the mechanisms underlying the associations between environmental risk factors and the incidence of NA-FEP.

Urbanicity and psychotic disorders: Facts and hypotheses

In the present qualitative literature review, we summarise data on psychotic disorders and urbanicity, focusing particularly on recent findings. Longitudinal studies of the impact of urbanicity on the risk for psychotic disorders have consistently shown a significant association, with a relative risk between 2 and 2.5. However, most of the original studies were conducted in Western Europe, and no incidence studies were conducted in low- and middle-income countries. European studies suggest that neighbourhood-level social fragmentation and social capital may partly explain this association. Exposure to air pollution (positive association) and green space (negative association) may also be part of the explanation, but to date, available data do not make it possible to conclude if they act independently from urbanicity, or as part of the effect of urbanicity on psychotic disorders. Finally, several studies have consistently shown significant associations between the polygenic risk score for schizophrenia and urbanicity, with several possible explanations (pleiotropic effects, results of prodromic symptoms, or selection/intergenerational hypothesis). Thus, more studies are needed to understand the factors that explain the association between urbanicity and the risk of psychotic disorders. Further studies should account for the interdependence and/or interactions of different psychosocial and physical exposures (as well as gene-environment interactions), and explore this association in low- and middle-income countries.

The impact of study design on schizophrenia incidence estimates: A systematic review of Northern European studies 2008-2019

The best estimates of the incidence of schizophrenia range more than 25-fold from 3 to 80 per 100,000 person-years. To what extent do differences in study design explain this wide variation? We selected all studies published between 2008-2019 reporting the incidence of schizophrenia in general populations of Northern Europe. We identified 17 estimates covering 85 million person-years and more than 15,000 individual cases. The estimates ranged from 4-72 per 100,000 person-years (median 30; interquartile range 13-41). We classified the estimates in terms of three study design factors (coverage of services, time frame, and diagnostic quality) and two population factors (urbanicity and age). A meta-regression model of the three design factors, using the two population factors as covariates, explained 91% of between-study variation. Studies performed in general psychiatric services reported similar estimates [incidence rate ratio 1.12 (95% confidence interval 0.88 to 1.43)] to those performed in specialized services. But studies applying a cumulative time frame to diagnosis reported fourfold higher estimates [4.04 (3.14 to 5.2)] than those applying a first-contact time frame. And studies based on clinical diagnoses reported lower estimates [0.55 (0.43 to 0.72)] than those based on standardized research diagnoses. The three study design factors by themselves explained 67% of between-study variation. When comparing incidence rates from different populations, distorsions arising from differences in study design can eclipse differences caused by schizophrenia risk factors, such as gender, age or migrant status.

Temporal variation in the incidence of treated psychotic disorders in young people

INTRODUCTION

The incidence of psychotic disorders varies between geographical areas, however less is known about whether it varies over time in the same region. Analyzing this temporal variation of incidence could improve the allocation of healthcare resources and our understanding of the aetiology of psychotic disorders. This study aimed to determine whether there was a change in the incidence of psychotic disorders over a six-year period.

METHODS

Young people aged 15 to 24 presenting with a first episode of psychosis (FEP) attending an early intervention service in Melbourne between 2011 and 2016 were included. The population at-risk was determined from the two corresponding census periods and analyses were adjusted for age, sex and migrant status.

RESULTS

A total of 1217 young people presented with a FEP over the six-year period and the crude incidence rate in 2011 was 102.4 per 100,000 population at-risk, compared to 125.4 in 2016. There was an increase in the incidence by 33% in 2015 (aIRR = 1.33, 95% CI 1.09-1.63) and 28% in 2016 (aIRR = 1.28, 95% CI 1.05-1.56). When examined according to diagnostic groups, there was an increase in the incidence of substance-induced psychotic disorders among females in 2015 (aIRR = 4.62, 95% CI 1.02-20.8).

DISCUSSION

This study shows significant temporal variations in the incidence of treated psychotic disorders. These findings demonstrate that early intervention services should continually monitor incidence case numbers and funding should be provided accordingly, to ensure the required intensive and comprehensive treatments can be sustained.

Relationship between incidence and prevalence in psychotic disorders: An incidence-prevalence-mortality model

OBJECTIVES

Incidence-prevalence-mortality (IPM) models have been developped to estimate incidence or prevalence when one of these two measures is unavailable. We aimed to test the consistency of an IPM model of psychotic disorders on a recent incidence-prevalence couple dataset and to identify potential causes of inconsistency by applying the model to (a) the whole population, (b) female and male subgroups, (c) migrant subgroups, and (d) psychotic disorders with age at onset (AAO) between 18 and 24 (18-24 AAO).

METHODS

We modelled prevalence (MP) using incidence data and the expected mortality and remission values. We then compared the MP to the observed prevalence (OP).

RESULTS

In the whole population, the model significantly underestimated the prevalence (MP = 3.30, 95% CI [2.97, 3.66]; OP = 4.98, 95% CI [4.58, 5.41]). The results were similar for the two genders. In the migrants group, results were in the opposite direction, the model significantly overestimating the prevalence. Finally, in the 18-24 AAO subgroup, the model performed well, with OP and MP not significantly different.

CONCLUSION

These results suggest that standard IPM models do not perform well for psychotic disorders and more complex models taking into account the heterogeneity of the sample (in terms of remission, mortality, population movements, etc.) need to be developed.

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.