Association of obesity with COVID-19 diseases severity and mortality: A meta-analysis of studies.

Background: The literature on COVID-19 infection is growing every single day, and evidence of presence or absence of association between obesity and COVID-19 adverse outcomes should be revisited. Therefore, this study summarizes the pooled association of obesity with COVID-19 adverse outcomes and mortality.
Methods: We searched PubMed and Science direct databases using specific terms and defined criteria. Data were analyzed using Comprehensive Meta-Analysis V2 (Biostat, Englewood, NJ, USA)) random-effect models were used to calculate the odds ratio (OR) with 95% confidence intervals (95% CIs) of infection severity and mortality associated with obesity.
Results: Results revealed that obesity is not associated with COVID-19 mortality (OR = 1.1; 95%CI: 0.8 to 1.3) but with other adverse outcomes (OR = 2.4; 95%CI: 1.7 to 3.3).
Conclusion: Our findings support previous findings that obesity is associated with COVID-19 severity.

Introduction

The 2019 novel coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was reported early in December 2019 in Wuhan, China. On March 11, 2020, the World Health Organization announced COVID-19 as a pandemic (Deng et al., 2020). Due to its rapid spread globally, it has resulted in major global public health concerns with an estimated 15–20% of cases requiring hospitalization and 3–5% requiring critical care while the mortality rate of 50–97% in those who need mechanical ventilation. (Argyropoulos et al., 2020; Auld et al., 2020). The main clinical manifestations of the disease were respiratory symptoms including fever, cough, and fatigue and it may progress to pneumonia, acute respiratory distress syndrome (ARDS), shock, and death (Angeli et al., 2020).

Obesity, as defined by a body mass index (BMI) ≥ 30 kg/m2, is known to be strongly associated with comorbid disorders such as diabetes, cardiovascular disease, and cancer (Pi-sunyer, 2015). It is also linked with respiratory symptoms and diseases, including obstructive sleep apnea syndrome (OSAS), obesity hypoventilation syndrome (OHS), chronic obstructive pulmonary disease (COPD), asthma, pulmonary embolism, and aspiration pneumonia (Zammit et al., 2010). Furthermore, obesity is a risk factor for bacterial and viral pneumonia, ARDS, and acute respiratory failure after lung transplantation (Fezeu et al., 2011; Gong et al., 2010; Lederer et al., 2011; Mertz et al., 2013).

Regarding obesity and COVID-19, early descriptive studies did not clearly state a direct association between obesity and disease severity, while preliminary data has implicated major risk factors associated with worsening disease severity, including older age and comorbidities such as diabetes and hypertension (Zeng et al., 2020; Zhou et al., 2020).

Many studies have indicated that obesity was more common among cases that required hospitalization or mechanical ventilation (Lighter et al., 2020; Peng et al., 2020). Moreover, subsequent cohort studies from the United States and the United Kingdom indicated that obesity may increase the risk for severe illness and death from COVID-19 (Docherty et al., 2020; Petrilli et al., 2020). There are also emerging data that obesity is an independent predictor of intensive care unit (ICU), as obese patients were more likely to have critical care requirements, ICU admission, or death compared to normal-weight individuals (Hajifathalian et al., 2020).

While other studies did not find any association between obesity and clinical outcomes of COVID-19. For instance, there was no association between overweight and the increase in odds for in-hospital mortality nor between obesity and invasive mechanical ventilatory (IMV) support or supplemental oxygen use/noninvasive ventilatory support in diabetic patients (Longmore et al., 2021).

When comparing hospital admission rates between healthy weight and obese patients with a BMI between 30 and 34.9, results showed no significant difference, and therefore no association between hospital admission and BMI. Moreover, mortality rates were not statistically significant among obese patients with a BMI between 30 and 34.9 in compare with overweight patients with a BMI between 25 and 29.9 (Yang et al., 2021, Yang et al., 2021).

Nevertheless, obesity can contribute to the adverse outcomes of COVID-19 through increased reninangiotensin and aldosterone system (RAAS) activity and insulin resistance. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) penetrates human cells through direct binding with angiotensin converting enzyme 2 (ACE2) receptors on the cell surface, and since obesity is associated with insulin resistance and overactivity of the reninangiotensin-aldosterone system (RAAS), it is implicated with worse COVID-19 outcomes (Bornstein et al., 2020; Lakkis and Weir, 2018). Moreover, the ACE2 expression in adipose tissue is higher than that in the lung, a major target organ affected by COVID-19, and thus, allows entry of SARS-CoV-2 into adipocytes, making adipose tissue an important viral reservoir that allows the spread of infection to other organs (Kruglikov and Scherer, 2020) and thereby explaining how higher levels of adipose tissue as well as ACE2 levels among the obese population exacerbate infection outcomes.

The literature on COVID-19 disease is growing every single day and evidence of presence or absence of association between obesity and COVID-19 adverse outcomes should be revisited. Therefore, this study aims to summarize the pooled association of obesity with COVID-19 adverse outcomes and mortality.

Methods

This study is part of a larger protocol that is registered as is registered at PROSPERO CRD42020191768.

Search strategy

We searched PubMed and Science direct databases until the 9th of August 2020. The following terms were used: (obesity) OR (body mass index) OR (underweight) OR (overweight) OR (weight) OR (body mass) OR (anthropometric) OR (adiposity) OR (anthropometry) AND (covid-19), (Obesity OR Weight OR Overweight OR Anthropometric OR Adiposity OR Body mass index OR BMI) AND (COVID-19).

Study selection and data extraction

Retrospective and prospective observational studies were retrieved if they met the following criteria: 1) the study provided event rate data on obesity and any adverse outcome such as mortality, severity as defined in the study: Fever, shortness of breath, according to a respiratory rate (RR) ≥ 30 times/min, and oxygen saturation ≤93% in the resting state and arterial blood oxygen partial pressure (PaO2)/oxygen concentration (FiO2) ≤ 300 mm Hg2; 2) presented data by obesity status or by body mass index (BMI) categories; 3) patients were adults from the general population diagnosed with COVID-19; and 4) written in English. To minimize selection bias, studies were excluded if they specifically sampled patients with certain illnesses such as organ transplant patients, cancer, or HIV. Moreover, we excluded articles stated as clinical trials, case reports, reviews or systematic reviews, meta-analyses, conference abstracts, animal experiments, international surveys, correspondences, and letters to the editor. Data were extracted by WA and double-checked by FA, and SA. Any discrepancies were resolved by SA. The following pieces of information were extracted using a spreadsheet: authorship, year of publication, country, study type, sample size, study time, age, female percentage, smoker percentage, diagnosis method, exposure and outcomes.

Study quality

Study quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklist for case series to assess the risk of bias (Moola et al., 2017). The JBI assesses the internal validity of studies by considering items related to confounding, selection, and information bias.

Data analysis

We carried out data analysis using Comprehensive Meta-Analysis V2 (Biostat, Englewood, NJ, USA)) and used random-effects models to estimate the odds ratios (ORs) with 95% confidence intervals (95%CI) of disease adverse outcomes and mortality associated with obesity. A p-value of <0 0.05 was considered statistically significant. The I2 statistic (p-value of <0.1) was used to test for heterogeneity in any analysis. The I2 statistic estimates the percentage of variation in study results that is explained by between-study heterogeneity rather than sampling error. Usually, an I2 value > 50% indicates considerable heterogeneity (Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;). Lastly, Funnel plots and Egger's test were used to assess the presence of publication bias.

Results

Fig. 1 presents the study flowchart. An initial total of 2259 studies were identified using our search terms and a total of 57 studies comprising 272,882 patients were included in the quantitative analysis. Studies were excluded for the following reasons: case reports, clinical trials, reviews or systematic reviews, meta-analyses, correspondence, conference abstracts, animal experiments, international surveys, not enough information on exposure, not relevant content, and no outcome of interest.

Fig. 1

Flow diagram of the study selection process for meta-analysis of obesity and COVID-19 outcomes.

Table 1 summarizes the characteristics of the included studies. Studies were conducted in different parts of the world including China, the USA, Italy, Germany, Spain, France, Mexico, Taiwan, Brazil, Switzerland, and Rhode Island. Al studies were published in 2020. Most studies were cohort studies, prospective cohort and retrospective cohort, and case series. Some studies did not provide a specific definition of obesity. Other studies defined obesity as a BMI ≥30 while Studies from Asia defined obesity as BMI ≥28. COVID-19 was diagnosed using tests including reverse-transcription polymerase chain reaction (RT-PCR) and real-time RT-PCR (rRT-PCR). For the majority of the studies included in this analysis, the diagnosis of COVID-19 complied with the World Health Organization interim guidance 2020 (World Health Organization, 2020). Studies reported outcome data on adverse clinical outcomes including: mortality (n = 20), ICU admission (n = 12), invasive mechanical ventilation (IMV) or intubation (n = 14.), acute respiratory distress, ARDS, (n = 4) and pneumonia (n = 2).

Table 1

Design and characteristics of the included studies on obesity and COVID-19.

Study	Country	Study Design	Age years	Female %	Current smoker %	Diagnosis method	Sample size	Exposure	Exposure definition	Exposure (n)	Nonexposure (n)	Outcome	Outcome definition
Giacomelli et al. (2020)	Italy	A prospective cohort study					233	Obesity	BMI ≥30	38	195	mortality	non-survivor
Nguyen et al. (2020)	Paris	retrospective cohort study	64.8	34.40%	4.70%	RT-PCR	279	BMI	BMI >25	122	71	Unfavourable outcome	artificial ventilation or death
Xie et al. (2020)	China		55	39.40%	13.50%	RT-PCR	104	Obese	BMI ≥28 =	12	92	without outcome improvement	ICU pts
Argyropoulos et al. (2020)	USA	retrospective observational study	52.5	44.50%	Not measured	RT-PCR	205	Obesity	BMI ≥30	48	157	Severity	haspitalized/not hospitalized
Kalligeros et al. (2020)	Rhode Island	retrospective cohort	60	38.80%	11.70%	RT-PCR	103	BMI	BMI ≥30	49	54	Severity	ICU-admitted/Non-ICU
Mani et al. (2020)	USA		64.72	39.67%	Not measured	PCR	184	Obesity	BMI ≥30	66	118	Severity	intubated/non intubated
Anderson et al. (2020)	USA	Retrospective cohort study.	67	42%	13.60%	RT-PCR	2466	Obesity	BMI>30	259	1853	Severity	Death or Intubation
Karagiannidis et al. (2020)	Germany	observational cohort study	68.3	48.10%	Not measured	RT-PCR	10,021	obesity	BMI ≥30	513	9508	Severity	Pts with need for ventilation
Berenguer et al. (2020)	Spain	retrospective cohort	70	39%	6.70%	RT-PCR	4035	obesity	BMI >30	497	3109	mortality	death
Claudia et al. (2020)	Switzerland	retrospective cohort	67	37%	8%	PCR	99	obesity	BMI >30	27	72	Severity	severe COVID-19 progression/ICU transfer
Argenziano et al. (2020)	USA	retrospective cohort	63	40.40%	4.90%	RT-PCR	1000	obesity	BMI >30	352	489	Severity	Admitted to ICU
Toussie et al. (2020)	USA	retrospective cohort	39	38%	15%	RT-PCR	338	obesity	BMI >30	133	205	Severity	hospital admission and intubation.
Gavin et al. (2020)	USA	retrospective evaluation	60	48.60%	7.10%	PCR	140	obesity	BMI >30	75	65	severity	Mechanical Ventilation
Buckner et al. (2020)	USA	retrospective cohort study	69	50%	26%	RT-PCR	105	obesity	BMI >30	44	49	severity	ICU admission or Mortality
Huang et al. (2020)	China	multi-center study retrospective	44.0	42.60%	smoking history:7.9%	RT-PCR	202	obesity	BMI≥28	24	178	severity
Giacomelli et al. (2020)	Italy	prospective cohort study	61.0	30.90%	history of smoking = 30%	RT-PCR	233	obesity	BMI≥ 30	38	195	mortality	died during hospitlization
Shah et al. (2020)	USA		63.0	58.20%	17%	PCR	522	obesity	BMI ≥30	347	175	mortality	died during hospitlization
Sinha et al. (2020)	USA	Cohort study	59.0	36.90%	Not measured	PCR	255	obesity	BMI ≥30	135	120	Severity	fraction of inspired oxygen: ≤45% FiO2 (termed as stage IIB) or >45% FiO2 (classified as stage III)/severity: stage III)
Langer-gould et al. (2020)	USA	retrospective cohort study	59.3	31.70%	ever smoker = 31.75%		93	obesity	BMI ≥30	55	38	mortality	died during hospitlization
Mccullough et al. (2020)	USA	retrospective cohort study	63.3	36.80%	3.80%	RT-PCR	756	obesity	BMI ≥30	267	449	mortality	died during the follow-up period
Ciceri et al. (2020)	Italy	Cohort study	65.0	27.10%	Not measured	RT-PCR	410	obesity	BMI ≥30	78	332	mortality	outcome: died during hospitlization/no outcome: discharged pts
Petrilli et al. (2020)	USA	Prospective cohort study.	54.0	50.50%	5.50%	RT-PCR	5279	obesity	BMI ≥30	1865	3414	Severity	critical illness (intensive care, mechanical ventilation, discharge to hospice care, or death)
Hur et al. (2020)	USA	Retrospective observational study	59.0	44.20%	33.50%	RT-PCR	486	obesity	BMI ≥30	259	227	Severity	intubated pts (require invasive mechanical ventilation)
Auld et al. (2020)	USA	observational cohort study	64.0	45.20%	Not measured	PCR	217	Obesity	BMI ≥40	21	196	Mortality	Died in the ICU
Deng et al. (2020)	China	retrospective cohort study	33.75	44.60%	Not measured	RT-PCR	65	Obesity	BMI ≥28	10	55	Severity	severity: (1) shortness of breath, according to a respiratory rate (RR) ≥ 30 times/min; (2) an oxygen saturation ≤93% in the resting state; and (3) arterial blood oxygen partial pressure (PaO2)/oxygen concentration (FiO2) ≤ 300 mm Hg.
Halasz et al. (2020)	Italy	Retrospective cohort study	64	18.20%	Not measured		242	Obesity	BMI ≥30	48	143	Mortality	non survivors
Wang et al. (2020)	China	retrospective	44.3	44.80%	Not measured	RT-PCR	297	obesity	BMI ≥28	40	257	Severity	sever illness
Hu et al. (2020)	China	retrospective review	61	48.60%	11.80%	RT-PCR	323	obesity	BMI ≥30	13	310	severity	not defined
Urra et al. (2020)	Spain	retrospective case-control study	61.8	39.50%	Not measured	RT-PCR	172	obesity	BMI >30	17	155	severity	ICU admission
Klang et al. (2020)	USA	retrospective cohort study	less than 50 (43.25) and more than 50 (72)	42.43%	23.30%	PCR	3406	obesity	BMI ≥30	1231	2175	mortality	non survivors
Dreher et al. (2020)	Germany	case series	65	34%	6%	RT-PCR	50	obesity	BMI ≥30	17	33	severity	ARDS
Price et al. (2020)	USA	observational study	64	47.48%	Not measured	PCR	239	obesity	BMI ≥30	112	119	severity	requiring ventilatory support
Lodigiani et al. (2020)	Italy	retrospective cohort study	66	32%	11.60%		388	obesity	BMI ≥30	87	274	severity	ICU admission
Goyal et al. (2020)	USA	Retrospective Cohort Study	66.5	40%	5%		1687	obesity	BMI ≥30	525	1162	mortality	death
Cai et al. (2020)	China	case series	34.63	52.20%	Not measured	RT-PCR	383	obesity	BMI ≥28	41	342	mortality	death
Palaiodimos et al. (2020)	USA	retrospective cohort study	64	51%	32.50%		200	obesity	BMI ≥35	46	154	mortality	death
Pettit et al. (2020)	USA	retrospective cohort study	58.5	52.50%	Not measured	RT-PCR	238	obesity	BMI ≥30	146	92	mortality	death
Hajifathalian et al. (2020)	USA	retrospective review	64	39.20%	Not measured	RT-PCR	770	obesity	BMI ≥30	277	493	Severity	ICU admission
Moriconi et al. (2020)	Italy	retrospective observational study	69.5	48%	17%	RT-PCR	100	obesity	BMI ≥30	29	71	Severity	chronic obstructive pulmonary disease (COPD)
Nakeshbandi et al. (2020)	USA	retrospective cohort study	68	48%	14%	RT-PCR	504	Obesity	BMI ≥30	215	289	Mortality	death
Petersen et al. (2020)	Germany	cross-sectional	65.6	40%	13.33%	PCR	30	obesity	BMI ≥25	19	11	severity	ICU with mechanical ventilation
Steinberg et al. (2020)	USA	retrospective cohort study	no median age	not measured	not measured	RT-PCR	210	obesity	BMI >30	100	110	severity	mechanical ventilation
Tsai et al. (2020)	Taiwan	retrospective cohort study	41	50%	Not measured	RT-PCR	28	obesity	BMI ≥25	7	21	severity	pneumonia
Zhang et al. (2020)	China	retrospective observational study	62	51.40%	Not measured		74	overweight	BMI ≥23	58	16	Severity	Disease severity
Gao et al. (2020)	China	cohort study	48	37.30%	Not measured	RT-PCR	150	obesity	BMI ≥25	50 *75	100 *75	Severity	severity of illness
Ferrando et al. (2020)	Spain	prospective cohort study	64	31.90%	Not measured	PCR	742	obesity	not defined	262	419	severity	Mild and sever ARDS
Russo et al. (2020)	Italy	Cohort study	67.7	40.10%	8.30%	RT- PCR	192	obesity	not defined	26	166	mortality	not survived
Antinori et al. (2020)	Italy	prospective cohort study	63	25.75	Not measured	RT-PCR	35	Obesity	not defined	3	32	Severity	ICU admission
Guillo et al. (2020)	France	single center retrospective study	62	44%	Not measured	RT-PCR	129	obesity	not defined	25	104	Severity	death or intubation at 3 weeks follow-up).
Bartoletti et al. (2020)	Italy	retrospective cohort study	65.7	36.70%	Not measured	RT-PCR	1113	obesity	not defined	196	917	Severity	Severe respiratory failure
(Hern andez-Galdamez et al., 2020)	Mexico	cross-sectional study	45.7	45.29%	7.79%		110,987	obesity	not defined	41,344	69643	severity	Hospitalized pts
Harmouch et al. (2020)	USA	retrospective cohort stud	63	42.90%	34.10%		563	obesity	(stated as morbid obesity)	120	443	mortality	died during hospitalization
Soares et al. (2020)	Brazil	cohort study	less than and mpre than 60	55.16%	2% *50%	RT-PCR	10,713	obesity	not defined	597	10116	mortality	non survivors
Leonardi et al. (2020)	Italy	retrospective study	61	36%	Not measured	RT-PCR	189	obesity	not defined	14	175	severity	critical illness
Goshua et al. (2020)	USA	cross-sectional study	62	40%	Not measured	PCR	68	obesity	not defined	25	43	severity	ICU admission
Baqui et al. (2020)	Brazil	cross-sectional observational study	56.1	42%	Not measured	RT-PCR	7371	obesity	not defined	324	7047	mortality	died during hospitalization *ICU and non ICU admission
Hirsch et al. (2020)	USA	Cohort study	64	39.10%	Not measured		5449	obesity	BMI >30 obese, morbid obesity not specified	obese + morbid obese = 1931	obese + morbid obese -total = 3518	Acute Kidney Injury (AKI)	Acute Kidney Injury developed during hospitalization.

Data analyses revealed that obesity is not associated with COVID-19 mortality (OR = 1.1; 95%CI: 0.8 to 1.3) (Fig. 2 ), but was associated with other adverse outcomes (OR = 2.4; 95%CI: 1.7 to 3.3) (Fig. 3 ). Heterogeneity measured by I2 was 79% for mortality and 97% for severity. Usually, an I2 value > 50% indicates considerable heterogeneity. Studies defined severity using various terms such as hospital admission, severe symptoms, ICU admission, mechanical ventilation, and mortality (Argenziano et al., 2020; Argyropoulos et al., 2020; Claudia et al., 2020; Gavin et al., 2020; Giacomelli et al., 2020). COVID-19 severity refers to oxygen saturation <90% on room air, respiratory rate >30 breaths/min in adults or signs of severe respiratory distress (accessory muscle use, inability to complete full sentences) as defined according to the interim guidelines from the World Health Organization (World Health Organization, 2020). Some studies measured outcomes that can be considered as a measure of COVID-19 severity. Thus, these studies were considered to measure the severity of COVID-19 disease and analyzed. A few studies did not clearly define severity. For example, Zhang et al. Gao et al., Wang et al., Deng et al. (Deng et al., 2020; Gao et al., 2020; Wang et al., 2020; Zhang et al., 2020) defined severity as severe illness while Cai et al. defined severity as exacerbation of the disease (Cai et al., 2020b).

Fig. 2

Forest plot of the odds ratios of obesity in non-survivor compared to survivor COVID-19 patients.

Fig. 3

Forest plot of the odds ratios of obesity in severe compared to non-severe COVID-19 cases.

As shown in Fig. 4 that evaluates publication bias using a funnel plot based on mortality. A visual symmetry indicates the absence of publication bias. Also, Egger's test revealed no significant publication bias (Egger's test: p = 0.99369). However, Fig. 5 shows a funnel plot based on severity that indicates publication bias (Egger's test: p = 0.01937).

Fig. 4

Funnel plot for publication bias based on mortality.

Fig. 5

Funnel plot for publication bias based on severity.

Discussion

This analysis pooled the results from recent publications on the association of obesity with COVID-19 adverse outcomes and mortality. Evidence accumulated to date shows that obesity is associated with COVID-19 adverse outcomes but not mortality.

Several potential mechanisms could explain how obesity may lead to adverse COVID-19 outcomes. The first possible mechanism is that adipose tissue produces and secretes several pro-and anti-inflammatory cytokines that have been engaged as active players in the development of metabolic diseases such as type 2 diabetes mellitus and cardiovascular disease (Lee et al., 2013). In particular, the increased level of cytokines like interleukin 6 in obese people, stimulates the liver to produce and secrete C-reactive protein (Ellulu et al., 2017). C-reactive protein is associated with adverse outcomes in patients suffering from COVID-19 (Alzoughool et al., 2020).

Numerous studies in humans described the relation between excess adiposity and impaired immune function, they revealed that the incidence and severity of infectious diseases are higher in obese individuals as compared to healthy individuals (Martí et al., 2001; Torres et al., 2018). On the other hand, ACE2, the receptor used by coronaviruses to enter the affected cells, was found to be highly expressed in adipocytes of obese patients (Frel et al., 2020). This could also add another good possible explanation and support our results as it was previously discussed in more depth that the adipose tissue of obese patients could play a role in the progression of severe COVID-19 through secreting pro-inflammatory cytokines, mitochondrial dysfunction, and impaired immune response to viral infection all of which boost the formation of cytokines that lead to poor progression of even mild COVID-19 cases (Yu et al., 2022).

Another possible mechanism that supports our finding is the association between obesity and thrombosis, whereas obesity induces thrombosis via two suggested mechanisms; proinflammatory and hypofibrinolytic (Blokhin and Lentz, 2013). The activation of prothrombotic signaling pathways in vascular cells is considered one of the primary outcomes of the chronic inflammatory state of obesity (Levi et al., 2012).

In addition to the above possible mechanisms, we should mention that obesity causes mechanical compression of the diaphragm muscle, chest cavity, and lungs, leading to restrictive pulmonary damage (Mafort et al., 2016). Besides, obese persons are normally with a reduced lung volume and capacity as compared to healthy persons (Melo et al., 2014), leading to adding more stress on COVID-19 patients. Also, complications of obesity such as hypertension (Naeini et al., 2021), diabetes (Shrestha et al., 2021), and sleep apnea (Abdelmassih et al., 2021) may contribute to the disease severity and mortality. Hypertension increases the OR of severe COVID-19 outcomes by 2.5 times through dysregulation of the immune system including CD8+ T cell dysfunction and possible overproduction of proinflammatory cytokines (Naeini et al., 2021). COVID-19 patients with diabetes have higher ICU admission and intubation rates as it is suggested that the production of cytokines involved in inflmmation and oxidative stress are enhanced by high blood glucose levels (Shrestha et al., 2021). Sleep apnea that is prevelant among obese pateints causes systemic intermittent hypoxia leading to reduced levels oxyhemoglobin saturation (Abdelmassih et al., 2021) and thus the need for ventilation.

Our results are in line with several previous meta-analyses. For instance, Yang and his colleagues found that positive COVID-19 detection was more obvious among obese cases and hospitalization rates were higher for obese compared with normal BMI patients (Yang et al., 2021, Yang et al., 2021). Moreover, of a total of 124 patients, 47.6% of cases were obese (BMI >30) and 28.2% were severely obese (BMI >35), in addition to 85.7% of total hospitalized patients cases who required mechanical ventilation their BMI was relatively higher, therefore there is a significant association between IMV introduction and BMI (Simonnet et al., 2020a). Similarly, obesity was highly associated with positive COVID-19 test, higher risk of ICU admission, critical illness, and mortality, furthermore, higher BMI was linked with higher rates of ICU admissions and critical illness (Ho et al., 2020). Another meta-analysis found that overweight individuals were at a higher risk of 1.31 times to develop severe COVID-19 symptoms while the risk among obese individuals was 2.41 times higher compared to healthy individuals (Islam et al., 2021). Obesity is associated with the risk of many diseases including acute respiratory distress syndrome, chronic inflammation, decreased immune system and increased susceptibility of individuals to infections (Hegde et al., 2013; Heredia et al., 2012) Thus, obesity may act as an independent risk factor for poor progression of COVID-19 (Tamara and Tahapary, 2020).

Our work as well as previous meta-analyses are not without limitations that consequent to limitations in the literature. First, studies have different definitions of severity. Second, studies define obesity using different BMI cut-off points. Nevertheless, evidence to date from multiple meta-analyses indicates obesity may exacerbate COVID-19 symptoms and higher BMI is significantly associated with IMV introduction for patients, consequently, obesity may be a marker of poor prognosis and patients with high BMI should be monitored closely and managed carefully in order to clinically manage the disease (Ho et al., 2020; Simonnet et al., 2020b; Yang et al., 2021, Yang et al., 2021).

In conclusion, our findings support previous findings in the other meta-analysis, hence, COVID-19 obese patients should be monitored for likely progression to severe outcomes.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

CRediT authorship contribution statement

Suhad Abumweis: Conceptualization, Formal analysis, Methodology, Visualization, Project administration, Resources, Supervision, Interpretation: all authors, Writing – review & editing, all authors. Waed Alrefai: Conceptualization, Data curation, Methodology, Visualization, Writing – review & editing, Interpretation: all authors; . Foad Alzoughool: Conceptualization, Data curation, Methodology, Writing – review & editing, Interpretation: all authors.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.