International Journal for Equity in Health (Aug 2024)

A new model to understand the complexity of inequalities in dementia

  • Clarissa Giebel

DOI
https://doi.org/10.1186/s12939-024-02245-w
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 7

Abstract

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Abstract Many people living with dementia and unpaid carers experience inequalities in care related to challenges in receiving a correct diagnosis, care and support. Whilst complexities of the evidence are well recognised including barriers in receiving a diagnosis or post-diagnostic care, no coherent model has captured the far-reaching types and levels of inequalities to date. Building on the established Dahlgren & Whitehead Rainbow model of health determinants, this paper introduces the new Dementia Inequalities model. The Dementia Inequalities model, similar to the original general rainbow model, categorises determinants of health and well-being in dementia into three layers: (1) Individual; (2) Social and community networks; and (3) Society and infrastructure. Each layer comprises of general determinants, which have been identified in the original model but also may be different in dementia, such as age (specifically referring to young- versus late-onset dementia) and ethnicity, as well as new dementia-specific determinants, such as rare dementia subtype, having an unpaid carer, and knowledge about dementia in the health and social care workforce. Each layer and its individual determinants are discussed referring to existing research and evidence syntheses in the field, arguing for the need of this new model. A total of 48 people with lived, caring, and professional experiences of dementia have been consulted in the process of the development of this model. The Dementia Inequalities model provides a coherent, evidence-based overview of inequalities in dementia diagnosis and care and can be used in health and social care, as well as in commissioning of care services, to support people living with dementia and their unpaid carers better and try and create more equity in diagnosis and care.

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