Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)

Urbanicity and depression: A global meta-analysis

BACKGROUND

Previous meta-analyses have revealed that in adult and older adult populations of developed countries, depression is more prevalent in urban than rural areas. No meta-analyses have identified the effects of urbanicity on the general age demographic for developing countries. We conducted a meta-analysis of urban-rural differences in depression across all age demographics for developed and developing countries.

METHODS

PubMed and PsycINFO databases were searched for studies published between 1980 and 2020. Studies were included if they reported prevalences of urban and rural depression, or odds ratios comparing urban-rural depression prevalence. Studies were excluded for: nonrepresentative samples, non-standard measures of depression, and reporting continuous outcomes only. Meta-analytic models of urban-rural differences in the odds of depression were conducted across country development levels and age demographics.

RESULTS

From 1597 records screened and 302 full texts assessed for eligibility, 80 studies (N = 539,557) were included for meta-analysis. Urban residence was significantly associated with a higher prevalence of depression in developed countries (OR = 1.30, 95 % CI [1.17, 1.46], z = 4.75, p < .001), which was primarily driven by urban-rural differences in the general population age demographic (OR = 1.37, 95 % CI [1.22, 1.54], z = 5.38, p < .001).

LIMITATIONS

Studies reporting urban-rural differences in depression in terms of continuous symptom severity scores were not included.

CONCLUSIONS

Urbanicity appears to uniquely be associated with a higher prevalence of depression in developed countries, but not in developing countries.

Association between mental health workforce supply and clusters of high and low rates of youth suicide: An Australian study using suicide mortality data from 2016 to 2020

OBJECTIVE

To examine the association between mental health workforce supply and spatial clusters of high versus low incidence of youth suicide.

METHODS

A cross-sectional analysis of spatial suicide clusters in young Australians (aged 10-25) from 2016 to 2020 was conducted using the scan statistic and suicide data from the National Coronial Information System. Mental health workforce was extracted from the 2020 National Health Workforce Dataset by local government areas. The Geographic Index of Relative Supply was used to estimate low and moderate-to-high mental health workforce supply for clusters characterised by a high and low incidence of suicide (termed suicide hotspots and coldspots, respectively). Univariate and multivariate logistic regression was used to determine the association between suicide clusters and a range of sociodemographic characteristics including mental health workforce supply.

RESULTS

Eight suicide hotspots and two suicide coldspots were identified. The multivariate analysis showed low mental health workforce supply was associated with increased odds of being involved in a suicide hotspot (adjusted odds ratio = 8.29; 95% confidence interval = 5.20-13.60), followed by residential remoteness (adjusted odds ratio = 2.85; 95% confidence interval = 1.68-4.89), and illicit drug consumption (adjusted odds ratio = 1.97; 1.24-3.11). Both coldspot clusters occurred in areas with moderate-to-high mental health workforce supply.

CONCLUSION

Findings highlight the potential risk and protective roles that mental health workforce supply may play in the spatial distributions of youth suicide clusters. These findings have important implications for the provision of postvention and the prevention of suicide clusters.

Using Geospatial Analysis to Inform Development of a Place-Based Integrated Care Initiative: The Healthy Homes and Neighbourhoods Experience

INTRODUCTION

Disadvantaged families experience many barriers to accessing health and social care. The Healthy Homes and Neighbourhoods (HHAN) Integrated Care Initiative was developed to address these barriers, and ensure families have their complex needs met and are kept safe and connected to society.

DESCRIPTION

A spatial epidemiology approach was taken, as part of the HHAN feasibility phase, to identify the geographical distribution of the "most vulnerable" families in Sydney Local Health District (SLHD). A literature review was conducted to identify indicators of family stress and disadvantage, and cluster and hotspot analyses were undertaken. Hotspots of family stress and disadvantage were mapped for SLHD and used to identify areas for HHAN place-based delivery, and for collaborative co-design.

DISCUSSION

The HHAN initiative called for consideration of context and the undertaking of collaborative design with communities. The spatial analysis provided a more accurate picture of family stress and disadvantage than previously available and provided a tool that could be used during consultation and planning activities.

CONCLUSION

When planning place-based integrated care initiatives, spatial analysis of small geographic scales can allow identification of areas of concentrated or complex disadvantage that may be masked when analysis is performed on larger areas, allowing for targeted, place-based delivery of programs to those most in need.

[Everything is on the map: Integrated Mental Health Atlases as support tools for service planning. SESPAS Report 2020]

OBJECTIVE

This article reviews the usability of the Integrated Atlases of Mental Health as a decision support tool for service planning following a health ecosystem research approach.

METHOD

This study describes the types of atlases and the procedure for their development. Atlases carried out in Spain are presented and their impact in mental health service planning is assessed. Atlases comprise information on the local characteristics of the health care system, geographical availability of resources collected with the DESDE-LTC instrument and their use. Atlases use geographic information systems and other visualisation tools. Atlases follow a bottom-up collaborative approach involving decision-makers from planning agencies for their development and external validation.

RESULTS

Since 2005, Integrated Atlases of Mental Health have been developed for nine regions in Spain comprising over 65% of the Spanish inhabitants. The impact on service planning has been unequal for the different regions. Catalonia, Biscay and Gipuzkoa, and Andalusia reach the highest impact. In these areas, health advisors have been actively involved in their co-design and implementation in service planning.

CONCLUSIONS

Atlases allow detecting care gaps and duplications in care provision; monitoring changes of the system over time, and carrying out national and international comparisons, efficiency modelling and benchmarking. The knowledge provided by atlases could be incorporated to decision support systems in order to support an efficient mental health service planning based on evidence-informed policy.

No man is an island: spatial clustering and access to primary care as possible targets for the development of new community mental health approaches

BACKGROUND

to understand if patients seen at Centro Hospitalar Psiquiátrico de Lisboa (CHPL) live in geographical clusters or randomly throughout the city, as well as determine their access to the psychiatric hospital and primary care facilities (PCF).

METHODS

spatial autocorrelation statistics were performed (queen criterion of contiguity), regarding all patients observed at CHPL in 2017 (at the census subsection level), and considering not only their overall number but also main diagnosis, and admission to the psychiatric ward - voluntary or compulsory. Distance to the hospital and to the closest PCF was measured (for each patient and the variables cited above), and the mean values were compared. Finally, the total number of patients around each PCF was counted, considering specified radius sizes of 656 and 1000 m.

RESULTS

All 5161 patients (509 psychiatric admissions) were geolocated, and statistical significance regarding patient clustering was found for the total number (p-0.0001) and specific group of disorders, namely Schizophrenia and related disorders (p-0.007) and depressive disorders (p-0.0002). Patients who were admitted in a psychiatric ward live farther away from the hospital (p-0.002), with the compulsory admissions (versus voluntary ones) living even farther (p-0.004). Furthermore, defining a radius of 1000 m for each PCF allowed the identification of two PCF with more than 1000 patients, and two others with more than 800.

CONCLUSIONS

as patients seem to live in geographical clusters (and considering PCFs with the highest number of them), possible locations for the development of programs regarding mental health treatment and prevention can now be identified.

Development of the Australian neighborhood social fragmentation index and its association with spatial variation in depression across communities

PURPOSE

We know little about how community structures influence the risk of common mental illnesses. This study presents a new way to establish links between depression and social fragmentation, thereby identifying pathways to better target mental health services and prevention programs to the right people in the right place.

METHOD

A principal components analysis (PCA) was conducted to develop the proposed Australian neighborhood social fragmentation index (ANSFI). General practice clinical data were used to identify cases of diagnosed depression. The association between ANSFI and depression was explored using multilevel logistic regression. Spatial hot spots (clusters) of depression prevalence and social fragmentation at the statistical area level 1 (SA1) were examined.

RESULTS

Two components of social fragmentation emerged, reflecting fragmentation related to family structure and mobility. Individuals treated for depression in primary care were more likely to live in neighborhoods with lower socioeconomic status and with higher social fragmentation related to family structure. A 1-SD increase in social fragmentation was associated with a 16% higher depression prevalence (95% CI 11%, 20%). However, the association attenuated with adjustment for neighborhood socio-economic status. Considerable spatial variation in social fragmentation and depression patterns across communities was observed.

CONCLUSIONS

Developing a social fragmentation index for the first time in Australia at a small area level generates a new line of knowledge on the impact of community structures on health risks. Findings may extend our understanding of the mechanisms that drive geographical variation in the incidence of common mental disorders and mental health care.

Spatial structure of depression in South Africa: A longitudinal panel survey of a nationally representative sample of households

Wider recognition of the mental health burden of disease has increased its importance as a global public health concern. However, the spatial heterogeneity of mental disorders at large geographical scales is still not well understood. Herein, we investigate the spatial distribution of incident depression in South Africa. We assess depressive symptomatology from a large longitudinal panel survey of a nationally representative sample of households, the South African National Income Dynamics Study. We identified spatial clusters of incident depression using spatial scan statistical analysis. Logistic regression was fitted to establish the relationship between clustering of depression and socio-economic, behavioral and disease risk factors, such as tuberculosis. There was substantial geographical clustering of depression in South Africa, with the excessive numbers of new cases concentrated in the eastern part of the country. These clusters overlapped with those of self-reported tuberculosis in the same region, as well as with poorer, less educated people living in traditional rural communities. Herein, we demonstrate, for the first time, spatial structuring of depression at a national scale, with clear geographical ‘hotspots’ of concentration of individuals reporting new depressive symptoms. Such geographical clustering could reflect differences in exposure to various risk factors, including socio-economic and epidemiological factors, driving or reinforcing the spatial structure of depression. Identification of the geographical location of clusters of depression should inform policy decisions.

The Minimum Basic Data Set (MBDS) as a tool for cancer epidemiological surveillance

OBJECTIVE

This work aims to evaluate the Minimum Basic Data Set (MBDS) as a data source in the detection of malignant tumors and explore its usefulness as a tool for epidemiological surveillance of cancer.

MATERIALS AND METHODS

MBDS hospital data discharge from Prince of Asturias University Hospital (HUPA, Alcalá de Henares, Madrid, Spain) and cancer cases recorded in the Hospital Cancer Registry (HCR) have been collected for the period between January 2012 and June 2014. Both databases have been linked by the number of clinical history. For the process of evaluation of MBDS, the types of cancer with more than 100 cases have been analyzed and sensitivity, specificity, positive and negative predictive values(PPV, NPV) of MBDS were calculated using as reference the diagnoses recorded in the HCR.

RESULTS

3438 cases of cancer were accounted in the MBDS and 2445 in the HCR. The MBDS has a sensitivity to detect cases of cancer above 60%, although it varies depending on the type of tumor, reaching the highest values for bladder cancer. The specificity and the VPN were very high for all types of cancer studied, always on top of 95%. Finally, the VPP is generally moderate, between 50% and 70%.

CONCLUSIONS

The systematic exploitation of the MBDS can provide a valuable tool in the monitoring of cancer by its acceptable sensitivity and high specificity, allowing obtaining information without the delays involved in the consolidation of the annotations of the HCR. Furthermore, its use could partly mitigate the lack of data in important regions of Spain.

A multi-level analysis of the relationship between spatial clusters of outpatient-treated depression, risk factors and mental health service planning in Catalonia (Spain)

BACKGROUND

Previous research identified high/low clusters of prevalence of outpatient-treated depression at municipal level in Catalonia (Spain). This study aims to analyse potential risk factors, both socioeconomic and related to the mental health service planning, which could influence the occurrence of hot/cold spots of depressed outpatients at two geographical levels: municipalities and service catchment areas.

METHOD

Hot/cold spots were examined in relation to socioeconomic indicators at municipal level, such as population density, unemployment, university education, personal income, and also those related to service planning at catchment area level, such as adequacy of healthcare, urbanicity, accessibility and the availability of mental health community centres. The analysis has been carried out through multilevel logistic regression models in order to consider the two different scales.

RESULTS

Hot spots are related to high population density, unemployment, urbanicity, the adequacy of provision of mental health services, and accessibility to mental health community centres at both study levels. On the other hand, the multilevel model weakly explains cold spots, associating them with high personal incomes.

LIMITATIONS

The dependent variables of the multi-level models are binary. This limits the interpretation of the results, since they cannot provide information about the variance of the dependent variables explained by the models.

CONCLUSIONS

The results described diverse risk factors at two levels which are related to a high likelihood of hot and cold spots of depression. The findings show the relevance of health planning in the distribution of diseases and the utilisation of healthcare services.

Does emergency department use and post-visit physician care cluster geographically and temporally for adolescents who self-harm? A population-based 9-year retrospective cohort study from Alberta, Canada

BACKGROUND

Clustering of adolescent self-harming behaviours in the context of health care utilization has not been studied. We identified geographic areas with higher numbers of adolescents who (1) presented to an emergency department (ED) for self-harm, and (2) were without a physician follow-up visit for mental health within 14 days post-ED visit.

METHODS

We extracted a population-based cohort of adolescents aged 15-17 years (n = 3,927) with ED visits during 2002-2011 in Alberta, Canada. We defined the case as an individual with one or more ED presentations for self-harm in the fiscal year of the analysis. Crude case rates were calculated and clusters were identified using a spatial scan.

RESULTS

The rates decreased over time for ED visits for self-harm (differences: girls -199.6/100,000; p < 0.01; boys -58.8/100,000; p < 0.01), and for adolescents without a follow-up visit within 14 days following an ED visit for self-harm (differences: girls -108.3/100,000; p < 0.01; boys -61.9/100,000; p < 0.01). Two space-time clusters were identified: (1) a North zone cluster during 2002-2006 (p < 0.01) and (2) a South zone cluster during 2003-2007 (p < 0.01). These clusters had higher numbers of adolescents who presented to the ED for self-harm (relative risks [RRs]: 1.58 for cluster 1, 3.54 for cluster 2) and were without a 14-day physician follow-up (RRs: 1.78 for cluster 1, 4.17 for cluster 2). In 2010/2011, clusters in the North, Edmonton, and Central zones were identified for adolescents with and without a follow-up visit within 14 days following an ED visit for self-harm (p < 0.01).

CONCLUSIONS

The rates for ED visits for adolescents who self-harm and rates of adolescents without a 14-day physician follow-up visit following emergency care for self-harm decreased during the study period. The space-time clusters identified the areas and years where visits to the ED by adolescents for self-harm were statistically higher than expected. These clusters can be used to identify locations where adolescents are potentially not receiving follow-up and the mental health support needed after emergency-based care. The 2010/2011 geographic cluster suggests that the northern part of the province still has elevated numbers of adolescents visiting the ED for self-harm. Prospective research is needed to determine outcomes associated with adolescents who receive physician follow-up following ED-based care for self-harm compared to those who do not.

Spatial distribution of individuals with symptoms of depression in a periurban area in Lima: an example from Peru

PURPOSE

To map the geographical distribution and spatial clustering of depressive symptoms cases in an area of Lima, Peru.

METHODS

Presence of depressive symptoms suggesting a major depressive episode was assessed using a short version of the Center for Epidemiologic Studies Depression Scale. Data were obtained from a census conducted in 2010. One participant per selected household (aged 18 years and above, living more than 6 months in the area) was included. Residence latitude, longitude, and elevation were captured using a GPS device. The prevalence of depressive symptoms was estimated, and relative risks (RRs) were calculated to identify areas of significantly higher and lower geographical concentrations of depressive symptoms.

RESULTS

Data from 7946 participants, 28.3% male, mean age 39.4 (SD, 13.9) years, were analyzed. The prevalence of depressive symptoms was 17.0% (95% confidence interval = 16.2%-17.8%). Three clusters with high prevalence of depressive symptoms (primary cluster: RR = 1.82; P = .003 and secondary: RR = 2.83; P = .004 and RR = 5.92; P = .01), and two clusters with significantly low prevalence (primary: RR = 0.23; P = .016 and secondary: RR = 0; P = .035), were identified. Further adjustment by potential confounders confirmed the high prevalence clusters but also identified newer ones.

CONCLUSIONS

Screening strategies for depression, in combination with mapping techniques, may be useful tools to target interventions in resource-limited areas.

Use of an integrated Atlas of Mental Health Care for evidence informed policy in Catalonia (Spain)

BACKGROUND

This paper aims to present the Integrated Atlas of Mental Health of Catalonia (2010) focusing on: (a) the importance of using a taxonomy-based coding and standard system of data collection when assessing health services; and (b) its relevance as a tool for evidence-informed policy.

METHOD

This study maps all the care-related services for people with mental disorders available in Catalonia in 2010, using the 'Description and Evaluation of Services and Directories in Europe for long-term care' (DESDE-LTC). The unit of analysis is the Basic Stable Input of Care (BSIC), which is the minimal organisation unit composed by a set of inputs with temporal stability. We presented data on: (a) availability of BSICs and their capacity; (b) the adequacy of the provision of care, taking into account availability and accessibility; (c) the evolution of BSCIs from 2002 to 2010; and (d) the perceived relevance of Atlas of Mental Health as a tool for evidence-informed policy.

RESULTS

We identified a total of 639 BSICs. A lack of Health services was detected in highly rural areas, although there was moderate availability of Social Services. Overall, more than 80% of the small mental health areas in Catalonia had an adequate core mental health service. Since 2002 the availability of mental health services has increased. Decision makers found the Atlas a useful and relevant tool for evidence informed policy.

CONCLUSIONS

Policy makers can use Atlases to detect gaps and inequities in the provision of care for people with mental health needs.

Assessing spatial patterns of HIV knowledge in rural Mozambique using geographic information systems

OBJECTIVES

To conduct a cross-sectional mapping analysis of HIV knowledge in Zambézia Province, Mozambique, and to examine spatial patterns of HIV knowledge and associated household characteristics.

METHODS

A population-based cluster survey was administered in 2010; data were analysed from 201 enumeration areas in three geographically diverse districts: Alto Molócuè, Morrumbala and Namacurra. We assessed HIV knowledge scores (0-9 points) using previously validated assessment tools. Using geographic information systems (GIS), we mapped hot spots of high and low HIV knowledge. Our multivariable linear regression model estimated HIV knowledge associations with distance to nearest clinic offering antiretroviral therapy, respondent age, education, household size, number of children under five, numeracy, literacy and district of residence.

RESULTS

We found little overall HIV knowledge in all three districts. People in Alto Molócuè knew comparatively most about HIV, with a median score of 3 (IQR 2-5) and 22 of 51 (43%) enumeration areas scoring ≥4 of 9 points. Namacurra district, closest to the capital city and expected to have the best HIV knowledge levels, had a median score of 1 (IQR 0-3) and only 3 of 57 (5%) enumeration areas scoring ≥4 points. More HIV knowledge was associated with more education, age, household size, numeracy and proximity to a health facility offering antiretroviral therapy.

CONCLUSIONS

HIV knowledge is critical for its prevention and treatment. By pinpointing areas of poor HIV knowledge, programme planners can prioritize educational resources and outreach initiatives within the context of antiretroviral therapy expansion.

Space and time clustering of adolescents' emergency department use and post-visit physician care for mood disorders in Alberta, Canada: A population-based 9-year retrospective study

OBJECTIVES

We used a statistical cluster detection technique to identify geographic areas with higher numbers of adolescents who 1) presented to an emergency department (ED) for a mood disorder, and 2) were without a physician follow-up visit for mental health within 30 days of an ED visit.

METHODS

We conducted a population-based analysis of ED visits (n = 6,829) made by adolescents aged 10-17 years (n = 5,877) using administrative databases from Alberta, Canada (2002-2011). Statistical analyses included summaries, directly standardized rates (DSRs per 100,000), and the spatial scan cluster test.

RESULTS

Sex- and age-adjusted DSRs increased by 21.8% from 2002 to 2011 (160.2/100,000 to 195.1/100,000). Northern Alberta had consistently higher DSRs than other areas of the province and areas in the north, southwest and central parts were identified as geographical and temporal clusters with relative risks of 1.67, 2.78 and 1.42 respectively. Many of these areas also had higher relative risks for adolescents who did not have a mental health-related visit with a physician within 30 days of the ED visit. About 32% (n = 1,870) did not have a post-ED physician visit.

CONCLUSION

The potential clusters identified may represent geographic areas with higher disease severity or more acute care sought because of less availability of other services. The clusters are not all likely to have occurred by chance and further investigations and discussions with local health care policy makers about reducing the number of ED visits for mood disorders and increasing physician follow-up after the ED visit is an important next step.

Spatial epidemiology of dry eye disease: findings from South Korea

BACKGROUND

DED rate maps from diverse regions may allow us to understand world-wide spreading pattern of the disease. Only few studies compared the prevalence of DED between geographical regions in non-spatial context. Therefore, we examined the spatial epidemiological pattern of DED prevalence in South Korea using a nationally representative sample.

METHODS

We analyzed 16,431 Korean adults aged 30 years or older of the 5th Korea National Health and Nutrition Examination Survey. DED was defined as previously diagnosed by an ophthalmologist as well as symptoms experienced. Multiple logistic regression analysis was used to assess the spatial pattern in the prevalence of DED, and effects of environmental factors.

RESULTS

Among seven metropolitan cities and nine provinces, three metropolitan cities located in the southeast of Korea revealed the highest prevalence of DED. After adjusting for sex, age and survey year, people living in urban areas had higher risk of having DED. Adjusted odds ratio for having previously diagnosed DED was 1.677 (95% CI 1.299-2.166) for metropolitan cities and 1.580 (95% CI 1.215-2.055) for other cities compared to rural areas. Corresponding odds ratio for presenting DED symptoms was 1.388 (95% CI 1.090-1.766) for metropolitan cities and 1.271 (95% CI 0.999-1.617) for other cities. Lower humidity and longer sunshine duration were significantly associated with DED. Among air pollutants, SO2 was associated with DED, while NO2, O3, CO, and PM10 were not.

CONCLUSION

Our findings suggest that prevalence of DED can be affected by the degree of urbanization and environmental factors such as humidity and sunshine duration.