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. 2021 Dec;36(12):3737-3742.
doi: 10.1007/s11606-020-06584-6. Epub 2021 Jul 8.

Socio-Demographic Health Determinants Are Associated with Poor Prognosis in Spanish Patients Hospitalized with COVID-19

Affiliations

Socio-Demographic Health Determinants Are Associated with Poor Prognosis in Spanish Patients Hospitalized with COVID-19

F Javier Martín-Sánchez et al. J Gen Intern Med. 2021 Dec.

Abstract

Introduction: Social vulnerability is a known determinant of health in respiratory diseases. Our aim was to identify whether there are socio-demographic factors among COVID-19 patients hospitalized in Spain and their potential impact on health outcomes during the hospitalization.

Methods: A multicentric retrospective case series study based on administrative databases that included all COVID-19 cases admitted in 19 Spanish hospitals from 1 March to 15 April 2020. Socio-demographic data were collected. Outcomes were critical care admission and in-hospital mortality.

Results: We included 10,110 COVID-19 patients admitted to 18 Spanish hospitals (median age 68 (IQR 54-80) years old; 44.5% female; 14.8% were not born in Spain). Among these, 779 (7.7%) cases were admitted to critical care units and 1678 (16.6%) patients died during the hospitalization. Age, male gender, being immigrant, and low hospital saturation were independently associated with being admitted to an intensive care unit. Age, male gender, being immigrant, percentile of average per capita income, and hospital experience were independently associated with in-hospital mortality.

Conclusions: Social determinants such as residence in low-income areas and being born in Latin American countries were associated with increased odds of being admitted to an intensive care unit and of in-hospital mortality. There was considerable variation in outcomes between different Spanish centers.

Keywords: COVID-19; health inequalities; in-hospital mortality; intensive care unit admission; socio-demographic factors.

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Conflict of interest statement

The authors have nothing to disclose in relationship with this manuscript.

Figures

Fig. 1
Fig. 1
Probability of death according to the models considering postal code areas according to country reference. Dots represent observed mortality rates for each age and group. Lines represent the predicted probability according to the mode. In the left pannel it is shown how according to our model, the probability of death of an individual born in Latin American countries (LATAM) can be as the one of an spanish born individual 4 years older. In the right pannel is shown how patients who live in the poorer areas of the country have the same mortality as an individual 4.5 years older living in the richer areas

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