Obesity as a risk factor for hospitalization in COronaVirus Disease-19 (COVID-19) patients: Analysis of the Tuscany regional database.


Journal

Nutrition, metabolism, and cardiovascular diseases : NMCD
ISSN: 1590-3729
Titre abrégé: Nutr Metab Cardiovasc Dis
Pays: Netherlands
ID NLM: 9111474

Informations de publication

Date de publication:
10 03 2021
Historique:
received: 25 09 2020
revised: 27 11 2020
accepted: 27 11 2020
pubmed: 8 2 2021
medline: 11 3 2021
entrez: 7 2 2021
Statut: ppublish

Résumé

Aim of the present study is to determine the role of obesity as a risk factor for COronaVirus Disease-19 (COVID-19) hospitalization. This observational study was performed using Istituto Superiore di Sanità (ISS) Tuscany COVID-19 database by the Agenzia Regionale Sanità (ARS), including all COVID-19 cases registered until April 30th, 2020, with reported information on chronic diseases. The principal outcome was hospitalization. An age and gender-adjusted logistic regression model was used to assess the association of clinical and demographic characteristics with hospitalization. Further multivariate models were applied. Of 4481 included subjects (36.9% aged over 70 years), 1907 (42.6%) were admitted to hospital. Obesity was associated with hospitalization after adjusting for age and gender. The association of obesity with hospitalization retained statistical significance in a fully adjusted model, including possible confounders (OR: 2.99 [IC 95% 2.04-4.37]). The effect of obesity was more evident in younger (<70 years) than in older (≥70 years) subjects. The present data confirm that obesity is associated with an increased risk of hospitalization in patients with COVID-19. Interestingly, the association of obesity with hospitalization was greater in younger (<70 years) patients.

Sections du résumé

BACKGROUND AND AIMS
Aim of the present study is to determine the role of obesity as a risk factor for COronaVirus Disease-19 (COVID-19) hospitalization.
METHODS AND RESULTS
This observational study was performed using Istituto Superiore di Sanità (ISS) Tuscany COVID-19 database by the Agenzia Regionale Sanità (ARS), including all COVID-19 cases registered until April 30th, 2020, with reported information on chronic diseases. The principal outcome was hospitalization. An age and gender-adjusted logistic regression model was used to assess the association of clinical and demographic characteristics with hospitalization. Further multivariate models were applied. Of 4481 included subjects (36.9% aged over 70 years), 1907 (42.6%) were admitted to hospital. Obesity was associated with hospitalization after adjusting for age and gender. The association of obesity with hospitalization retained statistical significance in a fully adjusted model, including possible confounders (OR: 2.99 [IC 95% 2.04-4.37]). The effect of obesity was more evident in younger (<70 years) than in older (≥70 years) subjects.
CONCLUSIONS
The present data confirm that obesity is associated with an increased risk of hospitalization in patients with COVID-19. Interestingly, the association of obesity with hospitalization was greater in younger (<70 years) patients.

Identifiants

pubmed: 33549434
pii: S0939-4753(20)30507-X
doi: 10.1016/j.numecd.2020.11.030
pmc: PMC7722497
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

769-773

Informations de copyright

Copyright © 2020. Published by Elsevier B.V.

Auteurs

Benedetta Bellini (B)

ARS Agenzia Regionale Sanità, Toscana Italy.

Barbara Cresci (B)

Diabetology, Careggi Hospital, Florence, Italy.

Claudia Cosentino (C)

Diabetology, Careggi Hospital, Florence, Italy.

Francesco Profili (F)

ARS Agenzia Regionale Sanità, Toscana Italy.

Simone Bartolacci (S)

ARS Agenzia Regionale Sanità, Toscana Italy.

Daniele Scoccimarro (D)

University of Florence, Florence, Italy.

Fabio Voller (F)

ARS Agenzia Regionale Sanità, Toscana Italy.

Daniela Balzi (D)

Azienda Sanitaria Locale Centro, Toscana Italy.

Paolo Francesconi (P)

ARS Agenzia Regionale Sanità, Toscana Italy.

Edoardo Mannucci (E)

University of Florence, Florence, Italy. Electronic address: edoardo.mannucci@unifi.it.

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Classifications MeSH