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From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands.
Meulman, Iris; Uiters, Ellen; Cloin, Mariëlle; Struijs, Jeroen; Polder, Johan; Stadhouders, Niek.
Afiliação
  • Meulman I; Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands. iris.meulman@rivm.nl.
  • Uiters E; Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands. iris.meulman@rivm.nl.
  • Cloin M; Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
  • Struijs J; Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
  • Polder J; Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands.
  • Stadhouders N; Department of Public Health and Primary Care, Leiden University Medical Center-Health Campus The Hague, The Hague, The Netherlands.
Eur J Health Econ ; 25(9): 1581-1594, 2024 Dec.
Article em En | MEDLINE | ID: mdl-38499952
ABSTRACT

INTRODUCTION:

The COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands.

METHODOLOGY:

This retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results.

RESULTS:

Among the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result.

DISCUSSION:

Our findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Fatores Socioeconômicos / COVID-19 Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Eur J Health Econ Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Fatores Socioeconômicos / COVID-19 Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Eur J Health Econ Ano de publicação: 2024 Tipo de documento: Article