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Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis
AIM: A disadvantaged socioeconomic status (SES) was previously associated with higher incidence and poor outcomes both of non-communicable diseases (NCDs) and infectious diseases. Inequalities in health services also have a negative effect on the coronavirus disease 2019 (COVID-19) morbidity and mor...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9257564/ https://www.ncbi.nlm.nih.gov/pubmed/35815193 http://dx.doi.org/10.1007/s10389-022-01730-2 |
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author | Boglione, Lucio Dodaro, Valentina |
author_facet | Boglione, Lucio Dodaro, Valentina |
author_sort | Boglione, Lucio |
collection | PubMed |
description | AIM: A disadvantaged socioeconomic status (SES) was previously associated with higher incidence and poor outcomes both of non-communicable diseases (NCDs) and infectious diseases. Inequalities in health services also have a negative effect on the coronavirus disease 2019 (COVID-19) morbidity and mortality. SUBJECT AND METHODS: The study analysed the role of SES measured by the educational level (EL) in hospitalised patients with COVID-19 between 9 March 2020 and 20 September 2021 at our centre of infectious diseases. Clinical outcomes were: length of hospitalisation, in-hospital mortality and the need of intensive-care-unit (ICU) support. RESULTS: There were 566 patients included in this retrospective analysis. Baseline EL was: illiterate (5, 0.9%), primary school (99, 17.5%), secondary school (228, 40.3%), high school (211, 37.3%), degree (23, 4.1%); median age was higher in low EL (72.5 years vs 61 years, p = 0.003), comorbidity (56% in low EL, 34.6% in high EL, p < 0.001), time from the symptoms and PCR diagnosis (8.5 days in low EL, 6.5 days in high EL, p < 0.001), hospitalisation length (11.5 days in low EL, 9.5 days in high EL, p = 0.011), mortality rate (24.7% in low EL, 13.2% in high EL, p < 0.001). In the multivariate analysis there were predictors of mortality: age (OR = 4.981; 95%CI 2.172–11.427; p < 0.001), comorbidities (OR = 3.227; 95%CI 2.515–11.919; p = 0.007), ICU admission (OR = 6.997; 95%CI 2.334–31.404; p = 0.011), high vs low EL (OR = 0.761; 95%CI 0.213–0.990; p = 0.021). In survival analysis, higher EL was associated with a decreased risk of mortality up to 23.9%. CONCLUSION: Even though the EL is mainly related to the age of patients, in our analysis, it resulted as an independent predictor of in-hospital mortality and hospitalisation time. Unfortunately, this is a study focused only on hospitalised patients, and we did not examine the possible effect of EL in outpatients. Further analyses are required to confirm this suggestion and provide novel information. |
format | Online Article Text |
id | pubmed-9257564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-92575642022-07-06 Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis Boglione, Lucio Dodaro, Valentina Z Gesundh Wiss Original Article AIM: A disadvantaged socioeconomic status (SES) was previously associated with higher incidence and poor outcomes both of non-communicable diseases (NCDs) and infectious diseases. Inequalities in health services also have a negative effect on the coronavirus disease 2019 (COVID-19) morbidity and mortality. SUBJECT AND METHODS: The study analysed the role of SES measured by the educational level (EL) in hospitalised patients with COVID-19 between 9 March 2020 and 20 September 2021 at our centre of infectious diseases. Clinical outcomes were: length of hospitalisation, in-hospital mortality and the need of intensive-care-unit (ICU) support. RESULTS: There were 566 patients included in this retrospective analysis. Baseline EL was: illiterate (5, 0.9%), primary school (99, 17.5%), secondary school (228, 40.3%), high school (211, 37.3%), degree (23, 4.1%); median age was higher in low EL (72.5 years vs 61 years, p = 0.003), comorbidity (56% in low EL, 34.6% in high EL, p < 0.001), time from the symptoms and PCR diagnosis (8.5 days in low EL, 6.5 days in high EL, p < 0.001), hospitalisation length (11.5 days in low EL, 9.5 days in high EL, p = 0.011), mortality rate (24.7% in low EL, 13.2% in high EL, p < 0.001). In the multivariate analysis there were predictors of mortality: age (OR = 4.981; 95%CI 2.172–11.427; p < 0.001), comorbidities (OR = 3.227; 95%CI 2.515–11.919; p = 0.007), ICU admission (OR = 6.997; 95%CI 2.334–31.404; p = 0.011), high vs low EL (OR = 0.761; 95%CI 0.213–0.990; p = 0.021). In survival analysis, higher EL was associated with a decreased risk of mortality up to 23.9%. CONCLUSION: Even though the EL is mainly related to the age of patients, in our analysis, it resulted as an independent predictor of in-hospital mortality and hospitalisation time. Unfortunately, this is a study focused only on hospitalised patients, and we did not examine the possible effect of EL in outpatients. Further analyses are required to confirm this suggestion and provide novel information. Springer Berlin Heidelberg 2022-07-06 /pmc/articles/PMC9257564/ /pubmed/35815193 http://dx.doi.org/10.1007/s10389-022-01730-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Boglione, Lucio Dodaro, Valentina Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis |
title | Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis |
title_full | Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis |
title_fullStr | Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis |
title_full_unstemmed | Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis |
title_short | Impact of socioeconomic status on the clinical outcomes in hospitalised patients with SARS-CoV-2 infection: a retrospective analysis |
title_sort | impact of socioeconomic status on the clinical outcomes in hospitalised patients with sars-cov-2 infection: a retrospective analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9257564/ https://www.ncbi.nlm.nih.gov/pubmed/35815193 http://dx.doi.org/10.1007/s10389-022-01730-2 |
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