Obesity augments the disease burden in COVID-19: Updated data from an umbrella review.
Nickolai M KristensenSigrid Bjerge GribsholtAnton Lund AndersenBjørn RichelsenJens Meldgaard BruunPublished in: Clinical obesity (2022)
The ongoing coronavirus disease 2019 (COVID-19) pandemic calls for identification of risk factors, which may help to identify people at enhanced risk for severe disease outcomes to improve treatment and, if possible, establish prophylactic measures. This study aimed to determine whether individuals with obesity compared to individuals with normal weight have an increased risk for severe COVID-19. We conducted a systematic literature search of PubMed, Embase and Cochrane Library and critically reviewed the secondary literature using AMSTAR-2. We explored 27 studies. Findings indicate that individuals with obesity (body mass index ≥ 30 kg/m 2 ), as compared to individuals without obesity, experience an increased risk for hospitalization (odds ratio [OR]: 1.40-2.45), admission to the intensive care unit (OR: 1.30-2.32), invasive mechanical ventilation (OR: 1.47-2.63), and the composite outcome 'severe outcome' (OR or risk ratio: 1.62-4.31). We found diverging results concerning death to COVID-19, but data trended towards increased mortality. Comparing individuals with obesity to individuals without obesity, findings suggested younger individuals (<60 years) experience a higher risk of severe disease compared to older individuals (≥60 years). Obesity augments the severity of COVID-19 including a tendency to increased mortality and, thus, contributes to an increased disease burden, especially among younger individuals.
Keyphrases
- coronavirus disease
- weight loss
- insulin resistance
- weight gain
- metabolic syndrome
- body mass index
- type diabetes
- risk factors
- high fat diet induced
- sars cov
- mechanical ventilation
- systematic review
- physical activity
- adipose tissue
- respiratory syndrome coronavirus
- skeletal muscle
- acute respiratory distress syndrome
- electronic health record
- deep learning
- big data
- coronary artery disease