Spatio-temporal clustering of the incidence of schizophrenia in Quebec, Canada from 2004 to 2007

Psychosis prevalence in London neighbourhoods; A case study in spatial confounding

Analysis of impacts of neighbourhood risk factors on mental health outcomes frequently adopts a disease mapping approach, with unknown neighbourhood influences summarised by random effects. However, such effects may show confounding with observed predictors, especially when such predictors have a clear spatial pattern. Here, the standard disease mapping model is compared to methods which account and adjust for spatial confounding in an analysis of psychosis prevalence in London neighbourhoods. Established area risk factors such as area deprivation, non-white ethnicity, greenspace access and social fragmentation are considered as influences on psychosis. The results show evidence of spatial confounding in the standard disease mapping model. Impacts expected on substantive grounds and available evidence are either nullified or reversed in direction. It is argued that the potential for spatial confounding to affect inferences about geographic disease patterns and risk factors should be routinely considered in ecological studies of health based on disease mapping.

Spatial variations of COVID-19 risk by age in Toronto, Canada

The risk of coronavirus disease 2019 (COVID-19) may vary by age, biological, socioeconomic, behavioural and logistical reasons may be attributed to these variations. In Toronto, Canada, the aging population has been severely impacted, accounting for 92% of all COVID-19 deaths. Four age groups: 60-69 years, 70-79 years, 80-89 years and ≥90 years in Toronto neighbourhoods were investigated for clustering tendencies using space-time statistics. Cohen's Kappa coefficient was computed to assess variations in risk by neighbourhood between different age groups. The findings suggest that knowledge of health risks and health behaviour varied by age across neighbourhoods in Toronto. Therefore, understanding the socioecological context of the communities and targeting age-appropriate intervention strategies is important for planning an effective mechanism for controlling the disease.

Predictors of Emergency Department Use for Suicidal Behaviors among Patients with Substance-Related Disorders

OBJECTIVE

This study aimed to identify predictors of emergency department (ED) use for suicide ideation or suicide attempt compared with other reasons among 14,158 patients with substance-related disorders (SRD) in Quebec (Canada).

METHODS

Longitudinal data on clinical, sociodemographic, and service use variables for patients who used addiction treatment centers in 2012-13 were extracted from Quebec administrative databases. A multinomial logistic regression was produced, comparing predictors of suicide ideation or attempts to other reasons for ED use in 2015-16.

RESULTS

Patients using ED for both suicide ideation and attempt were more likely to have bipolar or personality disorders, problems related to the social environment, 4+ previous yearly outpatient consultations with their usual psychiatrist, high prior ED use, and dropout from SRD programs in addiction treatment centers in the previous 7 years, compared with those using ED for other reasons. Patients with alcohol- or drug-related disorders other than cannabis and living in the least materially deprived areas, urban territories, and university healthcare regions made more suicide attempts than those using ED for other reasons. Patients with common mental disorders, 1-3 previous yearly outpatient consultations with their usual psychiatrist, one previous treatment episode in addiction treatment centers, and those using at least one SRD program experienced more suicide ideation than patients using ED for other reasons.

CONCLUSION

Clinical variables most strongly predicted suicidal behaviors, whereas completion of SRD programs may help to reduce them. SRD services and outreach strategies should be reinforced, particularly for patients with complex issues living in more advantaged urban areas. HIGHLIGHTSOver 10% of ED visits were for suicidal behaviors among patients with SRD.ED use for suicidal behaviors was mainly associated with clinical variables.Addiction treatment centers may help reduce ED use for suicidal behaviors.

The Incidence of Psychotic Disorders and Area-level Marginalization in Ontario, Canada: A Population-based Retrospective Cohort Study

BACKGROUND

There is limited Canadian evidence on the impact of socio-environmental factors on psychosis risk. We sought to examine the relationship between area-level indicators of marginalization and the incidence of psychotic disorders in Ontario.

METHODS

We conducted a retrospective cohort study of all people aged 14 to 40 years living in Ontario in 1999 using health administrative data and identified incident cases of psychotic disorders over a 10-year follow-up period. Age-standardized incidence rates were estimated for census metropolitan areas (CMAs). Poisson regression models adjusting for age and sex were used to calculate incidence rate ratios (IRRs) based on CMA and area-level marginalization indices.

RESULTS

There is variation in the incidence of psychotic disorders across the CMAs. Our findings suggest a higher rate of psychotic disorders in areas with the highest levels of residential instability (IRR = 1.26, 95% confidence interval [CI], 1.18 to 1.35), material deprivation (IRR = 1.30, 95% CI, 1.16 to 1.45), ethnic concentration (IRR = 1.61, 95% CI, 1.38 to 1.89), and dependency (IRR = 1.35, 95% CI, 1.18 to 1.54) when compared to areas with the lowest levels of marginalization. Marginalization attenuates the risk in some CMAs.

CONCLUSIONS

There is geographic variation in the incidence of psychotic disorders across the province of Ontario. Areas with greater levels of marginalization have a higher incidence of psychotic disorders, and marginalization attenuates the differences in risk across geographic location. With further study, replication, and the use of the most up-to-date data, a case may be made to consider social policy interventions as preventative measures and to direct services to areas with the highest risk. Future research should examine how marginalization may interact with other social factors including ethnicity and immigration.

Fine-Scale Space-Time Cluster Detection of COVID-19 in Mainland China Using Retrospective Analysis

Exploring spatio-temporal patterns of disease incidence can help to identify areas of significantly elevated or decreased risk, providing potential etiologic clues. The study uses the retrospective analysis of space-time scan statistic to detect the clusters of COVID-19 in mainland China with a different maximum clustering radius at the family-level based on case dates of onset. The results show that the detected clusters vary with the clustering radius. Forty-three space-time clusters were detected with a maximum clustering radius of 100 km and 88 clusters with a maximum clustering radius of 10 km from 2 December 2019 to 20 June 2020. Using a smaller clustering radius may identify finer clusters. Hubei has the most clusters regardless of scale. In addition, most of the clusters were generated in February. That indicates China's COVID-19 epidemic prevention and control strategy is effective, and they have successfully prevented the virus from spreading from Hubei to other provinces over time. Well-developed provinces or cities, which have larger populations and developed transportation networks, are more likely to generate space-time clusters. The analysis based on the data of cases from onset may detect the start times of clusters seven days earlier than similar research based on diagnosis dates. Our analysis of space-time clustering based on the data of cases on the family-level can be reproduced in other countries that are still seriously affected by the epidemic such as the USA, India, and Brazil, thus providing them with more precise signals of clustering.

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.

Retraction: Caractérisation des premiers épisodes de schizophrénie à partir de bases de données administratives de santé jumelées. [Characterization of First Episodes of Schizophrenia from Combined Administrative Databases]. Beaudoin, M., Potvin, S., Dellazizzo, L., Surprenant, M., Lesage, A., Vanasse, A., Ngamini-Ngui, A.† et Dumais, A. Santé mentale au Québec. 2018 Fall ; 43(2) : 83-105.PMID : 32338687

This corrects the article DOI: https://doi.org/10.7202/1058611ar.

Factors associated with emergency department use for mental health reasons among low, moderate and high users

OBJECTIVES

This study identified factors associated with frequency of emergency department (ED) use for mental health (MH) reasons in Quebec during 2015-2016.

METHODS

Participants (n = 115,066) were categorized as: 1) low (1 visit/year; 76%); 2) moderate (2 visits/year; 14%); and 3) high (3+ visits/year; 10%) ED users. Independent variables included predisposing, enabling and needs factors based on the Andersen Behavioral Model. Variables significantly associated with frequency of ED use were entered into a multinomial logistic regression.

RESULTS

Patients with mental illness (MI), especially substance-related disorders (SRD) and schizophrenia spectrum disorders; bipolar, depressive, anxiety or personality disorders; and those with severe chronic physical illness (needs factors) were more likely to use ED for MH reasons, as were male participants 18-64 years old, and those living in metropolitan areas with high social or material deprivation (predisposing factors). Regarding enabling factors, consultations with outpatient psychiatrists and not seeing a general practitioner (GP) in the year prior to ED visit were associated with high ED use.

CONCLUSION

The severity of MI/SRD contributed most to frequent ED use, while social and material deprivation in metropolitan areas, and intensity of medical care also influenced ED use for MH reasons.

Inclusion of edaphic predictors for enhancement of models to determine distribution of soil-transmitted helminths: the case of Zimbabwe

Background

Reliable mapping of soil-transmitted helminth (STH) parasites requires rigorous statistical and machine learning algorithms capable of integrating the combined influence of several determinants to predict distributions. This study tested whether combining edaphic predictors with relevant environmental predictors improves model performance when predicting the distribution of STH, Ascaris lumbricoides and hookworms at a national scale in Zimbabwe.

Methods

Geo-referenced parasitological data obtained from a 2010/2011 national survey indicating a confirmed presence or absence of STH among school children aged 10–15 years was used to calibrate ten species distribution models (SDMs). The performance of SDMs calibrated with a set of environmental and edaphic variables was compared to that of SDMs calibrated with environmental variables only. Model performance was evaluated using the true skill statistic and receiver operating characteristic curve.

Results

Results show a significant improvement in model performance for both A. lumbricoides and hookworms for all ten SDMs after edaphic variables were combined with environmental variables in the modelling of the geographical distribution of the two STHs at national scale. Using the top three performing models, a consensus prediction was developed to generate the first continuous maps of the potential distribution of the two STHs in Zimbabwe.

Conclusions

The findings from this study demonstrate significant model improvement if relevant edaphic variables are included in model calibration resulting in more accurate mapping of STH. The results also provide spatially-explicit information to aid targeted control of STHs in Zimbabwe and other countries with STH burden.

Ethnic Minority Status, Age-at-Immigration and Psychosis Risk in Rural Environments: Evidence From the SEPEA Study

OBJECTIVE

Several ethnic minority groups experience elevated rates of first-episode psychosis (FEP), but most studies have been conducted in urban settings. We investigated whether incidence varied by ethnicity, generation status, and age-at-immigration in a diverse, mixed rural, and urban setting.

METHOD

We identified 687 people, 16-35 years, with an ICD-10 diagnosis of FEP, presenting to Early Intervention Psychosis services in the East of England over 2 million person-years. We used multilevel Poisson regression to examine incidence variation by ethnicity, rural-urban setting, generation status, and age-at-immigration, adjusting for several confounders including age, sex, socioeconomic status, population density, and deprivation.

RESULTS

People of black African (incidence rate ratio: 4.06; 95% confidence interval [CI]: 2.63-6.25), black Caribbean (4.63; 95% CI: 2.38-8.98) and Pakistani (2.31; 95% CI: 1.35-3.94) origins were at greatest FEP risk relative to the white British population, after multivariable adjustment. Non-British white migrants were not at increased FEP risk (1.00; 95% CI: 0.77-1.32). These patterns were independently present in rural and urban settings. For first-generation migrants, migration during childhood conferred greatest risk of psychotic disorders (2.20; 95% CI: 1.33-3.62).

CONCLUSIONS

Elevated psychosis risk in several visible minority groups could not be explained by differences in postmigratory socioeconomic disadvantage. These patterns were observed across rural and urban areas of our catchment, suggesting that elevated psychosis risk for some ethnic minority groups is not a result of selection processes influencing rural-urban living. Timing of exposure to migration during childhood, an important social and neurodevelopmental window, may also elevate risk.

Social and spatial heterogeneity in psychosis proneness in a multilevel case-prodrome-control study

OBJECTIVE

To test whether spatial and social neighbourhood patterning of people at ultra-high risk (UHR) of psychosis differs from first-episode psychosis (FEP) participants or controls and to determine whether exposure to different social environments is evident before disorder onset.

METHOD

We tested differences in the spatial distributions of representative samples of FEP, UHR and control participants and fitted two-level multinomial logistic regression models, adjusted for individual-level covariates, to examine group differences in neighbourhood-level characteristics.

RESULTS

The spatial distribution of controls (n = 41) differed from UHR (n = 48; P = 0.04) and FEP participants (n = 159; P = 0.01), whose distribution was similar (P = 0.17). Risk in FEP and UHR groups was associated with the same neighbourhood-level exposures: proportion of single-parent households [FEP adjusted odds ratio (aOR): 1.56 95% CI: 1.00-2.45; UHR aOR: 1.59; 95% CI: 0.99-2.57], ethnic diversity (FEP aOR: 1.27; 95% CI: 1.02-1.58; UHR aOR: 1.28; 95% CI: 1.00-1.63) and multiple deprivation (FEP aOR: 0.88; 95% CI: 0.78-1.00; UHR aOR: 0.86; 95% CI: 0.76-0.99).

CONCLUSION

Similar neighbourhood-level exposures predicted UHR and FEP risk, whose residential patterning was closer to each other's than controls. Adverse social environments are associated with psychosis before FEP onset.

A Bayesian Approach to Latent Class Modeling for Estimating the Prevalence of Schizophrenia Using Administrative Databases

Estimating the incidence and the prevalence of psychotic disorders in the province of Quebec has been the object of some interest in recent years as a contribution to the epidemiological study of the causes of psychotic disorders being carried out primarily in UK and Scandinavia. A number of studies have used administrative data from the Régie de l'assurance maladie du Québec (RAMQ) that includes nearly all Quebec citizens to obtain geographical and temporal prevalence estimates for the illness. However, there has been no investigation of the validity of RAMQ diagnoses for psychotic disorders, and without a measure of the sensitivity and the specificity of these diagnoses, it is impossible to be confident in the accuracy of the estimates obtained. This paper proposes the use of latent class analysis to ascertain the validity of a diagnosis of schizophrenia using RAMQ data.

Hitting the floor: understanding migration patterns following the first episode of psychosis

Recent research published in Health and Place (Ngamini Ngui et al., 2013b) found that one third of people with first episode psychosis [FEP] will have made a large-scale migration six years after initial diagnosis. Here, I extend this discussion around three important observations. Namely, at first presentation the most disadvantaged communities already shoulder the burden of psychotic morbidity; people with FEP in more rural communities migrate less often, and; people with FEP exhibit both upwards and downwards social mobility after onset. Understanding the reasons for (non-)migration before and after psychosis onset is now required for effective public mental health and service provision.