Modelling Deprivation Level and Multimorbidity in a Health District

María Pilar Botija Yagüe, Sofía Sorbet-Santiago, Javier Díaz-Carnicero, Silvia González- de-Julián and Ruth Usó-Talamantes
Additional contact information
María Pilar Botija Yagüe: Hospital Valencia Clínico—La Malvarrosa, 46011 Valencia, Spain
Sofía Sorbet-Santiago: Research Unit for Health Economics and Management, Universitat Politècnica de València, 46022 Valencia, Spain
Javier Díaz-Carnicero: Research Unit for Health Economics and Management, Universitat Politècnica de València, 46022 Valencia, Spain
Silvia González- de-Julián: Research Unit for Health Economics and Management, Universitat Politècnica de València, 46022 Valencia, Spain
Ruth Usó-Talamantes: Conselleria de Sanitat i Salut Pública, Generalitat Valenciana, 46010 Valencia, Spain

Mathematics, 2022, vol. 10, issue 4, 1-14

Abstract: Deprivation is associated with an increased risk of developing chronic health conditions and with worse outcomes in multimorbidity. The goal of our study was to develop an integrated population index of deprivation (IPID) to observe the influence of deprivation on morbidity and the subsequent use of healthcare resources in one health district, using the socioeconomic, clinical and geographical data from its administrative health records. Eight socioeconomic indicators were identified and weighted using the methodology of two-phase principal component analysis, providing an index that allowed each census section to be classified into seven deprivation groups. Secondly, the possible relation between the IPID and the variables for multimorbidity and healthcare resources was analysed using the theory of multiple comparisons. It was observed that places with a greater proportion of healthy people presented lower values of deprivation and that, at lower levels of deprivation, there were fewer hospital admissions. The results show that living in an area with a higher deprivation index is associated with greater consumption of healthcare resources and disease burden. Identifying areas of sociosanitary vulnerability can help to identify health inequalities and allow intervention by clinical practices and healthcare management to reduce them.

Keywords: deprivation; socioeconomic position; multimorbidity; modelling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/4/659/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/4/659/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:4:p:659-:d:753808

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().