ArticleInternational journal of health geographics2012
Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain).
Article in International journal of health geographics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 27 citations in OpenAlex.
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- Using Geospatial Analysis to Inform Development of a Place-Based Integrated Care Initiative: The Healthy Homes and Neighbourhoods Experience.International journal of integrated care · 2021Article
- No man is an island: spatial clustering and access to primary care as possible targets for the development of new community mental health approaches.BMC health services research · 2020Observational
- Development of the Australian neighborhood social fragmentation index and its association with spatial variation in depression across communities.Social psychiatry and psychiatric epidemiology · 2019Article
- Spatial structure of depression in South Africa: A longitudinal panel survey of a nationally representative sample of households.Scientific reports · 2019Article
- A spatiotemporal analysis of invasive cervical cancer incidence in the state of Maryland between 2003 and 2012.Cancer causes & control : CCC · 2018Article
- Article
- Spatial distribution of individuals with symptoms of depression in a periurban area in Lima: an example from Peru.Annals of epidemiology · 2016Article
- Use of an integrated Atlas of Mental Health Care for evidence informed policy in Catalonia (Spain).Epidemiology and psychiatric sciences · 2015Article
- Is a geographical approach worthwhile for epidemiological research in mental health?Epidemiology and psychiatric sciences · 2015Article
- 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.Canadian journal of public health = Revue canadienne de sante publique · 2014Article
- Spatial epidemiology of dry eye disease: findings from South Korea.International journal of health geographics · 2014Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSpatial analysis is a relevant set of tools for studying the geographical distribution of diseases, although its methods and techniques for analysis may yield very different results. A new hybrid approach has been applied to the spatial analysis of treated prevalence of depression in Catalonia (Spain) according to the following descriptive hypotheses: 1) spatial clusters of treated prevalence of depression (hot and cold spots) exist and, 2) these clusters are related to the administrative divisions of mental health care (catchment areas) in this region.
methodsIn this ecological study, morbidity data per municipality have been extracted from the regional outpatient mental health database (CMBD-SMA) for the year 2009. The second level of analysis mapped small mental health catchment areas or groups of municipalities covered by a single mental health community centre. Spatial analysis has been performed using a Multi-Objective Evolutionary Algorithm (MOEA) which identified geographical clusters (hot spots and cold spots) of depression through the optimization of its treated prevalence. Catchment areas, where hot and cold spots are located, have been described by four domains: urbanicity, availability, accessibility and adequacy of provision of mental health care.
resultsMOEA has identified 6 hot spots and 4 cold spots of depression in Catalonia. Our results show a clear spatial pattern where one cold spot contributed to define the exact location, shape and borders of three hot spots. Analysing the corresponding domain values for the identified hot and cold spots no common pattern has been detected.
conclusionsMOEA has effectively identified hot/cold spots of depression in Catalonia. However these hot/cold spots comprised municipalities from different catchment areas and we could not relate them to the administrative distribution of mental care in the region. By combining the analysis of hot/cold spots, a better statistical and operational-based visual representation of the geographical distribution is obtained. This technology may be incorporated into Decision Support Systems to enhance local evidence-informed policy in health system research.
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