TY - JOUR
T1 - Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)
AU - Salinas-Pérez, José A.
AU - García-Alonso, Carlos R.
AU - Molina-Parrilla, Cristina
AU - Jordà-Sampietro, Esther
AU - Salvador-Carulla, Luis
N1 - Funding Information:
This study is part of the project entitled ‘Development of a health map of services and facilities for the integral care of people with mental illness and the application of geographic information systems for decision support in planning services in Catalonia’ [Project: CPA 73.10.15], which was funded by the Health Department of Catalonia. This study is also partly subsidised by the Carlos III Health Institute (Ministry of Health of Spain) [project PI11/ 02008] and co-funded by FEDER funds. We also thank the reviewers for their helpful comments that improved the quality of our final manuscript.
PY - 2012/8/24
Y1 - 2012/8/24
N2 - Background: Spatial 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.Methods: In 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.Results: MOEA 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.Conclusions: MOEA 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.
AB - Background: Spatial 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.Methods: In 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.Results: MOEA 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.Conclusions: MOEA 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.
KW - Catalonia
KW - Cold spots
KW - Depression
KW - Hot spots
KW - Mental health
KW - Spatial analysis
UR - http://www.scopus.com/inward/record.url?scp=84866983281&partnerID=8YFLogxK
U2 - 10.1186/1476-072X-11-36
DO - 10.1186/1476-072X-11-36
M3 - Article
C2 - 22917223
AN - SCOPUS:84866983281
SN - 1476-072X
VL - 11
JO - International Journal of Health Geographics
JF - International Journal of Health Geographics
M1 - 36
ER -