Obesity is associated with increased severity of disease in COVID-19 pneumonia: a systematic review and meta-analysis

Yanan Chu, Jinxiu Yang, Jiaran Shi, Pingping Zhang, Xingxiang Wang, Yanan Chu, Jinxiu Yang, Jiaran Shi, Pingping Zhang, Xingxiang Wang

Abstract

Background: Obesity has been widely reported to be associated with the disease progression of coronavirus disease 2019 (COVID-19); however, some studies have reported different findings. We conducted a systematic review and meta-analysis to investigate the association between obesity and poor outcomes in patients with COVID-19 pneumonia.

Methods: A systematic review and meta-analysis of studies from the PubMed, Embase, and Web of Science databases from 1 November 2019 to 24 May 2020 was performed. Study quality was assessed, and data extraction was conducted. The meta-analysis was carried out using fixed-effects and random-effects models to calculate odds ratios (ORs) of several poor outcomes in obese and non-obese COVID-19 patients.

Results: Twenty-two studies (n = 12,591 patients) were included. Pooled analysis demonstrated that body mass index (BMI) was higher in severe/critical COVID-19 patients than in mild COVID-19 patients (MD 2.48 kg/m2, 95% CI [2.00 to 2.96 kg/m2]). Additionally, obesity in COVID-19 patients was associated with poor outcomes (OR = 1.683, 95% CI [1.408-2.011]), which comprised severe COVID-19, ICU care, invasive mechanical ventilation use, and disease progression (OR = 4.17, 95% CI [2.32-7.48]; OR = 1.57, 95% CI [1.18-2.09]; OR = 2.13, 95% CI [1.10-4.14]; OR = 1.41, 95% CI [1.26-1.58], respectively). Obesity as a risk factor was greater in younger patients (OR 3.30 vs. 1.72). However, obesity did not increase the risk of hospital mortality (OR = 0.89, 95% CI [0.32-2.51]).

Conclusions: As a result of a potentially critical role of obesity in determining the severity of COVID-19, it is important to collect anthropometric information for COVID-19 patients, especially the younger group. However, obesity may not be associated with hospital mortality, and efforts to understand the impact of obesity on the mortality of COVID-19 patients should be a research priority in the future.

Keywords: COVID-19; Meta-analysis; Obesity; Poor outcomes.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flow diagram of study selection process. COVID-19: coronavirus disease 2019
Fig. 2
Fig. 2
a Forest plot of MD in BMI between COVID-19 patients with and without severe disease. b Funnel plot of the included studies addressing the association between BMI and the severity of COVID-19. MD mean difference
Fig. 3
Fig. 3
Obesity and poor composite outcomes. a Forest plot showed that obesity was associated with an increased risk of composite poor outcomes and its subgroup, which comprised severe COVID-19, need for ICU care, need for IMV, and disease progression in patients with COVID-19. b Filled funnel plot for obesity and the composite poor outcomes of COVID-19. c Funnel plot for obesity and severe COVID-19. d Funnel plot for obesity and COVID-19 progression. ICU intensive care unit, IMV invasive mechanical ventilation
Fig. 4
Fig. 4
Bubble-plot for meta-regression. Meta-regression analysis showed that the association between obesity and composite poor outcome was affected by age (a) but not by diabetes (b), cardiovascular disease (c), hypertension (d), or COPD (e). COPD chronic obstructive pulmonary disease. Circles in the picture indicate studies. The red lines indicate fitted meta-regression line
Fig. 5
Fig. 5
a Subgroup analyses based on age groups suggested that the association between obesity and poor composite outcomes was stronger in patients with a mean age < 60 years. b Funnel plot for obesity and composite poor outcomes of younger COVID-19 patients. c Funnel plot for obesity and composite poor outcomes of older COVID-19 patients

References

    1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506. doi: 10.1016/S0140-6736(20)30183-5.
    1. Mahase E. Covid-19: WHO declares pandemic because of "alarming levels" of spread, severity, and inaction. BMJ. 2020;368:m1036. doi: 10.1136/bmj.m1036.
    1. WHO. WHO COVID-19 dashboard. 2020. .
    1. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 2020;395(10224):565–574. doi: 10.1016/S0140-6736(20)30251-8.
    1. Song R, Preston G, Yosypiv IV. Ontogeny of angiotensin-converting enzyme 2. Pediatr Res. 2012;71(1):13–19. doi: 10.1038/pr.2011.7.
    1. Wrapp D, Wang N, Corbett KS, Goldsmith JA, Hsieh CL, Abiona O, et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science. 2020;367(6483):1260–1263. doi: 10.1126/science.abb2507.
    1. Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol. 2020;92(6):552–555. doi: 10.1002/jmv.25728.
    1. Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol. 2020;146(1):110–118. doi: 10.1016/j.jaci.2020.04.006.
    1. Kass DA, Duggal P, Cingolani O. Obesity could shift severe COVID-19 disease to younger ages. Lancet. 2020;395(10236):1544–1545. doi: 10.1016/S0140-6736(20)31024-2.
    1. Morgan OW, Bramley A, Fowlkes A, Freedman DS, Taylor TH, Gargiullo P, et al. Morbid obesity as a risk factor for hospitalization and death due to 2009 pandemic influenza A (H1N1) disease. PLoS ONE. 2010;5(3):e9694. doi: 10.1371/journal.pone.0009694.
    1. Louie JK, Acosta M, Winter K, Jean C, Gavali S, Schechter R, et al. Factors associated with death or hospitalization due to pandemic 2009 influenza A (H1N1) infection in California. JAMA. 2009;302(17):1896–1902. doi: 10.1001/jama.2009.1583.
    1. Sun Y, Wang Q, Yang G, Lin C, Zhang Y, Yang P. Weight and prognosis for influenza A (H1N1) pdm09 infection during the pandemic period between 2009 and 2011: a systematic review of observational studies with meta-analysis. Infect Dis. 2016;48(11–12):813–822. doi: 10.1080/23744235.2016.1201721.
    1. Maier HE, Lopez R, Sanchez N, Ng S, Gresh L, Ojeda S, et al. Obesity increases the duration of influenza A virus shedding in adults. J Infect Dis. 2018;218(9):1378–1382. doi: 10.1093/infdis/jiy370.
    1. Luzi L, Radaelli MG. Influenza and obesity: its odd relationship and the lessons for COVID-19 pandemic. Acta Diabetol. 2020;57(6):759–764. doi: 10.1007/s00592-020-01522-8.
    1. Simonnet A, Chetboun M, Poissy J, Raverdy V, Noulette J, Duhamel A, et al. High prevalence of obesity in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) requiring invasive mechanical ventilation. Obesity. 2020;28(7):1195–1199. doi: 10.1002/oby.22831.
    1. Zhang F, Xiong Y, Wei Y, Hu Y, Wang F, Li G, et al. Obesity predisposes to the risk of higher mortality in young COVID-19 patients. J Med Virol. 2020 doi: 10.1002/jmv.26039.
    1. Peng YD, Meng K, Guan HQ, Leng L, Zhu RR, Wang BY, et al. Clinical characteristics and outcomes of 112 cardiovascular disease patients infected by 2019-nCoV. Zhonghua Xin Xue Guan Bing Za Zhi. 2020;48(6):450–455.
    1. Onder G, Rezza G, Brusaferro S. Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy. JAMA. 2020;323(18):1775–1776.
    1. Zhi G, Xin W, Ying W, Guohong X, Shuying L. "Obesity paradox" in acute respiratory distress syndrome: asystematic review and meta-analysis. PLoS ONE. 2016;11(9):e0163677. doi: 10.1371/journal.pone.0163677.
    1. Ni YN, Luo J, Yu H, Wang YW, Hu YH, Liu D, et al. Can body mass index predict clinical outcomes for patients with acute lung injury/acute respiratory distress syndrome? A meta-analysis. Crit Care. 2017;21(1):36. doi: 10.1186/s13054-017-1615-3.
    1. Tamara A, Tahapary DL. Obesity as a predictor for a poor prognosis of COVID-19: a systematic review. Diabetes Metab Syndr. 2020;14(4):655–659. doi: 10.1016/j.dsx.2020.05.020.
    1. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. JAMA. 2000;283(15):2008–2012. doi: 10.1001/jama.283.15.2008.
    1. WHO Expert Consultation Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–163. doi: 10.1016/S0140-6736(03)15268-3.
    1. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 2014;63(25 Pt B):2985–3023. doi: 10.1016/j.jacc.2013.11.004.
    1. Wang X, Fang X, Cai Z, Wu X, Gao X, Min J, et al. Comorbid chronic diseases and acute organ injuries are strongly correlated with disease severity and mortality among COVID-19 patients: a systemic review and meta-analysis. Research. 2020;2020:2402961.
    1. Liu J, Li S, Liu J, Liang B, Wang X, Wang H, et al. Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients. EBioMedicine. 2020;55:102763. doi: 10.1016/j.ebiom.2020.102763.
    1. Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–605. doi: 10.1007/s10654-010-9491-z.
    1. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–634. doi: 10.1136/bmj.315.7109.629.
    1. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56(2):455–463. doi: 10.1111/j.0006-341X.2000.00455.x.
    1. Wan W, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135. doi: 10.1186/1471-2288-14-135.
    1. McGrath S, Zhao X, Steele R, Thombs BD, Benedetti A, DEPRESSD Collaboration Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Stat Methods Med Res. 2020 doi: 10.1177/0962280219889080.
    1. Aggarwal S, Garcia-Telles N, Aggarwal G, Lavie C, Lippi G, Henry BM. Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): early report from the United States. Diagnosis. 2020;7(2):91–96. doi: 10.1515/dx-2020-0046.
    1. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O'Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966. doi: 10.1136/bmj.m1966.
    1. Zheng KI, Gao F, Wang XB, Sun QF, Pan KH, Wang TY, et al. Letter to the Editor: obesity as a risk factor for greater severity of COVID-19 in patients with metabolic associated fatty liver disease. Metabolism. 2020;108:154244. doi: 10.1016/j.metabol.2020.154244.
    1. Goyal P, Choi J, Pinheiro LC, Schenck EJ, Chen R, Jabri A, et al. Clinical characteristics of Covid-19 in New York City. N Engl J Med. 2020;382(24):2372–2374. doi: 10.1056/NEJMc2010419.
    1. Klang E, Kassim G, Soffer S, Freeman R, Levin MA, Reich DL. Severe obesity as an independent risk factor for COVID-19 mortality in hospitalized patients younger than 50. Obesity. 2020;28(9):1595–1599. doi: 10.1002/oby.22913.
    1. Argenziano MG, Bruce SL, Slater CL, Tiao JR, Baldwin MR, Barr RG, et al. Characterization and clinical course of 1000 patients with COVID-19 in New York: retrospective case series. medRxiv. 2020 doi: 10.1101/2020.04.20.20072116.
    1. Giacomelli A, Ridolfo AL, Milazzo L, Oreni L, Bernacchia D, Siano M, et al. 30-day mortality in patients hospitalized with COVID-19 during the first wave of the Italian epidemic: a prospective cohort study. Pharmacol Res. 2020;158:104931. doi: 10.1016/j.phrs.2020.104931.
    1. Kalligeros M, Shehadeh F, Mylona EK, Benitez G, Beckwith CG, Chan PA, et al. Association of obesity with disease severity among patients with COVID-19. Obesity. 2020;28(7):1200–1204. doi: 10.1002/oby.22859.
    1. Buckner FS, McCulloch DJ, Atluri V, Blain M, McGuffin SA, Nalla AK, et al. Clinical features and outcomes of 105 hospitalized patients with COVID-19 in Seattle, Washington. Clin Infect Dis. 2020 doi: 10.1093/cid/ciaa632.
    1. Auld SC, Caridi-Scheible M, Blum JM, Robichaux C, Kraft C, Jacob JT, et al. ICU and ventilator mortality among critically ill adults with coronavirus disease 2019. Crit Care Med. 2020;48(9):e799–e804.
    1. Cao J, Tu WJ, Cheng W, Yu L, Liu YK, Hu X, et al. Clinical features and short-term outcomes of 102 patients with corona virus disease 2019 in Wuhan, China. Clin Infect Dis. 2020;71(15):748–755. doi: 10.1093/cid/ciaa243.
    1. Huang R, Zhu L, Xue L, Liu L, Yan X, Wang J, et al. Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: a retrospective, multi-center study. PLoS Negl Trop Dis. 2020;14(5):e0008280. doi: 10.1371/journal.pntd.0008280.
    1. Liu M, He P, Liu HG, Wang XJ, Li FJ, Chen S, et al. Clinical characteristics of 30 medical workers infected with new coronavirus pneumonia. Zhonghua Jie He He Hu Xi Za Zhi. 2020;43(3):209–214.
    1. Wu J, Li W, Shi X, Chen Z, Jiang B, Liu J, et al. Early antiviral treatment contributes to alleviate the severity and improve the prognosis of patients with novel coronavirus disease (COVID-19) J Intern Med. 2020;288(1):128–138. doi: 10.1111/joim.13063.
    1. Xiong F, Tang H, Liu L, Tu C, Tian JB, Lei CT, et al. Clinical characteristics of and medical interventions for COVID-19 in hemodialysis patients in Wuhan, China. J Am Soc Nephrol. 2020;31(7):1387–1397. doi: 10.1681/ASN.2020030354.
    1. Gao Y, Li T, Han M, Li X, Wu D, Xu Y, et al. Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19. J Med Virol. 2020;92(7):791–796. doi: 10.1002/jmv.25770.
    1. Gao F, Zheng KI, Wang XB, Sun QF, Pan KH, Wang TY, et al. Obesity is a risk factor for greater COVID-19 severity. Diabetes Care. 2020;43(7):e72–e74. doi: 10.2337/dc20-0682.
    1. Cai Q, Chen F, Wang T, Luo F, Liu X, Wu Q, et al. Obesity and COVID-19 severity in a designated hospital in Shenzhen, China. Diabetes Care. 2020;43(7):1392–1398. doi: 10.2337/dc20-0576.
    1. Hu L, Chen S, Fu Y, Gao Z, Long H, Wang JM, et al. Risk factors associated with clinical outcomes in 323 COVID-19 hospitalized patients in Wuhan, China. Clin Infect Dis. 2020 doi: 10.1093/cid/ciaa539.
    1. Thompson D, Jungk J, Hancock E, Smelser C, Landen M, Nichols M, et al. Risk factors for 2009 pandemic influenza A (H1N1)-related hospitalization and death among racial/ethnic groups in New Mexico. Am J Public Health. 2011;101(9):1776–1784. doi: 10.2105/AJPH.2011.300223.
    1. Ouchi N, Parker JL, Lugus JJ, Walsh K. Adipokines in inflammation and metabolic disease. Nat Rev Immunol. 2011;11(2):85–97. doi: 10.1038/nri2921.
    1. Yang H, Youm YH, Vandanmagsar B, Rood J, Kumar KG, Butler AA, et al. Obesity accelerates thymic aging. Blood. 2009;114(18):3803–3812. doi: 10.1182/blood-2009-03-213595.
    1. Mescher MF, Curtsinger JM, Agarwal P, Casey KA, Gerner M, Hammerbeck CD, et al. Signals required for programming effector and memory development by CD8+ T cells. Immunol Rev. 2006;211:81–92. doi: 10.1111/j.0105-2896.2006.00382.x.
    1. Zheng Q, Cui G, Chen J, Gao H, Wei Y, Uede T, et al. Regular exercise enhances the immune response against microbial antigens through up-regulation of toll-like receptor signaling pathways. Cell Physiol Biochem. 2015;37(2):735–746. doi: 10.1159/000430391.
    1. Smith AG, Sheridan PA, Harp JB, Beck MA. Diet-induced obese mice have increased mortality and altered immune responses when infected with influenza virus. J Nutr. 2007;137(5):1236–1243. doi: 10.1093/jn/137.5.1236.
    1. Zhang AJ, To KK, Li C, Lau CC, Poon VK, Chan CC, et al. Leptin mediates the pathogenesis of severe 2009 pandemic influenza A (H1N1) infection associated with cytokine dysregulation in mice with diet-induced obesity. J Infect Dis. 2013;207(8):1270–1280. doi: 10.1093/infdis/jit031.
    1. Chan JF, Zhang AJ, Yuan S, Poon VK, Chan CC, Lee AC, et al. Simulation of the clinical and pathological manifestations of coronavirus disease 2019 (COVID-19) in golden Syrian hamster model: implications for disease pathogenesis and transmissibility. Clin Infect Dis. 2020 doi: 10.1093/cid/ciaa325.
    1. Zhang Y, Somers KR, Becari C, Polonis K, Pfeifer MA, Allen AM, et al. Comparative expression of renin-angiotensin pathway proteins in visceral versus subcutaneous fat. Front Physiol. 2018;9:1370. doi: 10.3389/fphys.2018.01370.
    1. Mehta P, McAuley DF, Brown M, Sanchez E, Tattersall RS, Manson JJ, et al. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet. 2020;395(10229):1033–1034. doi: 10.1016/S0140-6736(20)30628-0.
    1. Feng G, Zheng KI, Yan QQ, Rios RS, Targher G, Byrne CD, et al. COVID-19 and liver dysfunction: current insights and emergent therapeutic strategies. J Clin Transl Hepatol. 2020;8(1):18–24. doi: 10.14218/JCTH.2020.00018.
    1. Giamarellos-Bourboulis EJ, Netea MG, Rovina N, Akinosoglou K, Antoniadou A, Antonakos N, et al. Complex immune dysregulation in COVID-19 patients with severe respiratory failure. Cell Host Microbe. 2020;27(6):992.e3–1000.e3. doi: 10.1016/j.chom.2020.04.009.
    1. Ryan PM, Caplice NM. Is adipose tissue a reservoir for viral spread, immune activation and cytokine amplification in COVID-19. Obesity. 2020;28(7):1191–1194. doi: 10.1002/oby.22843.
    1. Lighter J, Phillips M, Hochman S, Sterling S, Johnson D, Francois F, et al. Obesity in patients younger than 60 years is a risk factor for Covid-19 hospital admission. Clin Infect Dis. 2020;71(15):896–897. doi: 10.1093/cid/ciaa415.
    1. Bhasin A, Nam H, Yeh C, Lee J, Liebovitz D, Achenbach C. Is BMI higher in younger patients with COVID-19? Association between BMI and COVID-19 hospitalization by age. Obesity. 2020;28(10):1811–1814. doi: 10.1002/oby.22947.
    1. Deng M, Qi Y, Deng L, Wang H, Xu Y, Li Z, et al. Obesity as a potential predictor of disease severity in young COVID-19 patients: a retrospective study. Obesity. 2020;28(10):1815–1825. doi: 10.1002/oby.22943.
    1. Iacobellis G, Penaherrera CA, Bermudez LE, Mizrachi EB. Admission hyperglycemia and radiological findings of SARS-CoV2 in patients with and without diabetes. Diabetes Res Clin Pract. 2020;164:108185. doi: 10.1016/j.diabres.2020.108185.
    1. Zhang X, Yu J, Pan LY, Jiang HY. ACEI/ARB use and risk of infection or severity or mortality of COVID-19: a systematic review and meta-analysis. Pharmacol Res. 2020;158:104927. doi: 10.1016/j.phrs.2020.104927.
    1. Melo LC, Silva MA, Calles AC. Obesity and lung function: a systematic review. Einstein. 2014;12(1):120–125. doi: 10.1590/S1679-45082014RW2691.
    1. Selim BJ, Ramar K, Surani S. Obesity in the intensive care unit: risks and complications. Hosp Pract. 2016;44(3):146–156. doi: 10.1080/21548331.2016.1179558.
    1. Sockalingam S, Leung SE, Cassin SE. The impact of coronavirus disease 2019 on bariatric surgery: redefining psychosocial care. Obesity. 2020;28(6):1010–1012. doi: 10.1002/oby.22836.
    1. Koch A, Sanson E, Voigt S, Helm A, Trautwein C, Tacke F. Serum adiponectin upon admission to the intensive care unit may predict mortality in critically ill patients. J Crit Care. 2011;26(2):166–174. doi: 10.1016/j.jcrc.2010.07.015.
    1. Nie W, Zhang Y, Jee SH, Jung KJ, Li B, Xiu Q. Obesity survival paradox in pneumonia: a meta-analysis. BMC Med. 2014;12:61. doi: 10.1186/1741-7015-12-61.
    1. Rice TW. Obesity in acute lung injury: the “weight” is over. Chest. 2007;131(2):333–334. doi: 10.1378/chest.06-2584.

Source: PubMed

Sponsorer og samarbeidspartnere

Medisinsk tilstand

Legemiddelintervensjoner

3
Abonnere