Obesity a predictor of outcomes of COVID-19 hospitalized patients-A systematic review and meta-analysis

J Med Virol. 2021 Feb;93(2):1188-1193. doi: 10.1002/jmv.26555. Epub 2020 Oct 7.


Coronavirus disease 2019 (COVID-19) pandemic is a global health crisis. Very few studies have reported association between obesity and severity of COVID-19. In this meta-analysis, we assessed the association of obesity and outcomes in COVID-19 hospitalized patients. Data from observational studies describing the obesity or body mass index and outcomes of COVID-19 hospitalized patients from December 1, 2019, to August 15, 2020, was extracted following PRISMA guidelines with a consensus of two independent reviewers. Adverse outcomes defined as intensive care units, oxygen saturation less than 90%, invasive mechanical ventilation, severe disease, and in-hospital mortality. The odds ratio (OR) and 95% confidence interval (95% CI) were obtained and forest plots were created using random-effects models. A total of 10 studies with 10,233 confirmed COVID-19 patients were included. The overall prevalence of obesity in our study was 33.9% (3473/10,233). In meta-analysis, COVID-19 patient with obesity had higher odds of poor outcomes compared with better outcomes with a pooled OR of 1.88 (95% CI: 1.25-2.80; p = 0.002), with 86% heterogeneity between studies (p < 0.00001). Our study suggests a significant association between obesity and COVID-19 severity and poor outcomes. Our results findings may have important suggestions for the clinical management and future research of obesity and COVID-19.

Keywords: 2019-nCoV; COVID-19; SARS-CoV-2; body mass index (BMI); coronavirus disease; mechanical ventilation; mortality; obesity; severe acute respiratory syndrome.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Body Mass Index
  • COVID-19 / physiopathology*
  • Hospital Mortality*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Intensive Care Units / statistics & numerical data
  • Obesity / complications*
  • Obesity / virology
  • Observational Studies as Topic
  • Prevalence
  • Respiration, Artificial / statistics & numerical data