Título Analysis of the funding of social services from a spatial approach in Andalusia (Spain)
Autores SALINAS PÉREZ, JOSÉ ALBERTO, Ruiz-Ballesteros E. , González-Portillo A.
Publicación externa No
Medio HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
Alcance Article
Naturaleza Científica
Cuartil JCR 1
Cuartil SJR 1
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187902078&doi=10.1057%2fs41599-024-02912-x&partnerID=40&md5=ed470ba8d8265c6d5f2d35cf1679bafc
Fecha de publicacion 01/01/2024
ISI 001185882900008
Scopus Id 2-s2.0-85187902078
DOI 10.1057/s41599-024-02912-x
Abstract In Andalusia, Community Social Service Centres (CSSCs) are funded by regulations following demographic, geographic, economic, and social disadvantage criteria. This study aims to analyse the geographical distribution of funding per inhabitant of CSSC by catchment area in Andalusia in 2019, and to study the statistical associations between funding and a range of demographic and socioeconomic indicators. The study spatial units (n = 184) included the catchment areas of CSSCs and, in the case of intramunicipal areas in large municipalities, they were grouped at the municipal level. Spatial autocorrelation measures were used to identify spatial clusters of high/low funding rates per inhabitant. Later, nonspatial and spatial regressions were applied to search for associations with different indicators (sex ratio, ageing index, dependency index, emigration rate, immigration rate, unemployment rate, population density, and employment rate in the primary sector). The geographical distribution of the funding of social services in Andalusia was not random since the analyses identified several spatial clusters with significantly high (hot spots) and low (cold spots) funding per inhabitant (p < 0.05). The funding rates were significantly (p < 0.05) and directly associated with the ageing index and the percentage of primary sector employees, and indirectly with the proportion of foreigners in the population and the population density. The hot spots were mainly located in rural and deprived areas, while the cold spots were in urban areas. The variables related to the regulated funding distribution criteria were not fully associated with higher financing. Instead, other additional variables showed significant associations (p < 0.05), such as primary-sector workers and foreign populations. The results showed that spatial analyses may support service assessment and decision-making in social policy. © The Author(s) 2024.
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