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Modelling Deprivation Level and Multimorbidity in a Health District

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Listed:
  • 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)

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.

Suggested Citation

  • María Pilar Botija Yagüe & Sofía Sorbet-Santiago & Javier Díaz-Carnicero & Silvia González-de-Julián & Ruth Usó-Talamantes, 2022. "Modelling Deprivation Level and Multimorbidity in a Health District," Mathematics, MDPI, vol. 10(4), pages 1-14, February.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:4:p:659-:d:753808
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    References listed on IDEAS

    as
    1. Diez Roux, A.V., 2001. "Investigating neighborhood and area effects on health," American Journal of Public Health, American Public Health Association, vol. 91(11), pages 1783-1789.
    2. Silja Leiser & Anouk Déruaz-Luyet & A Alexandra N’Goran & Jérôme Pasquier & Sven Streit & Stefan Neuner-Jehle & Andreas Zeller & Dagmar M Haller & Lilli Herzig & Patrick Bodenmann, 2017. "Determinants associated with deprivation in multimorbid patients in primary care—A cross-sectional study in Switzerland," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-12, July.
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