Is Obesity a Potential Risk factor for Poor Prognosis of COVID-19?

BACKGROUND: Coronavirus disease 2019 (COVID-19) continues to cause major mortality and morbidity worldwide even after a year of its emergence. In its early days, hypertension, diabetes, and cardiovascular diseases were noted as poor prognostic factors, while obesity gained attention at a later stage. In the present study, unfavorable clinical outcomes (transfer to the intensive care unit, invasive mechanical ventilation, and mortality) were investigated in obese patients with COVID-19.
MATERIALS AND METHODS: In this retrospective study we analyzed patients with positive polymerase chain reaction test in tertiary care hospital between March-May 2020. They were divided into 3 groups according to body mass index (BMI) as normal, overweight, and obese (BMI: 18.5 - 24.99 kg/m², 25 - 29.99 kg/m², and ≥ 30 kg/m², respectively). We compared clinical features and laboratory findings of these groups and recorded adverse clinical outcomes. Multivariate logistic analysis was performed for unfavorable outcomes.
RESULTS: There were 99 patients (35%), 116 (41%), and 69 patients (24%) in the normal-weight, overweight, and obese group, respectively. Among all patients, 52 (18%) patients were transferred to the intensive care unit (ICU), 30 (11%) patients received invasive mechanical ventilation (IMV), and 22 patients (8%) died. Obese patients had minimum 1 more comorbidity than normal BMI patients (73% vs. 50%, P = 0.002), and a longer median (interquartile range [IQR]) duration of hospitalization (8 [5 - 12] vs. 6 [5 - 9]) days, P = 0.006). Obese participants had higher concentrations of serum C-reactive protein, procalcitonin, ferritin than non-obese patients (P <0.05 in all). In a multivariate analysis, obesity was associated with ICU admission (adjusted odds ratio [aOR]: 2.99, 95% confidence interval [CI]: 1.26 - 7.04, P = 0.012). Moreover, IMV requirement was associated with obesity (aOR: 8.73, 95% CI: 2.44 - 31.20, P = 0.001). Mortality occurred in 16%, 9%, and 1% of the obese group, overweight group, and normal-weight group, respectively (Chi-square trend analysis, P = 0.002).
CONCLUSION: Obesity is a risk factor for adverse outcomes and caused increased mortality, hence requiring close follow-up.

Introduction

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is the agent causing the new coronavirus disease, started to spread rapidly all over the world after it was first identified in China on January 7, 2020 [1]. After the World Health Organization (WHO) declared the disease as a pandemic on March 11, 2020, the number of confirmed cases worldwide was 98 million as of January 2020, and the number of deaths was 2 million [2]. In Turkey, the total number of patients exceeded 2 million and the total number of deaths exceeded 25,000 as of end of January 2020 since March 11, 2020 (the date at which the country's first case was reported) [3].

In the early days of the pandemic; advanced age, hypertension, diabetes, chronic heart, and lung diseases were included in the risk group, while obesity began to be included in this group at a later stage [4567]. Indeed, obesity was previously demonstrated to be a risk factor for disease severity and mortality in viral infections during the H1N1 Influenza A outbreak [8].

Obesity is defined as the accumulation of abnormal or excessive fat tissue that can impair health [9]. The body mass index (BMI) is used for its definition and grading, however, different cut-off values were used for BMI in coronavirus disease 2019 (COVID-19) studies according to characteristics of the geographical region in question [691011]. In the majority of these studies, obesity has been demonstrated to be an independent risk factor that adversely affects the prognosis in COVID-19. Obesity has been shown to increase the rate of hospital admissions, the severity of the disease, and the need for intensive care and invasive mechanical ventilation (IMV), and lead to a longer duration of hospitalization and higher mortality rates [67111213]. On the contrary, there are few studies which reported that obesity is not an independent risk factor for COVID-19 and does not increase mortality [1415].

The prevalence of obesity is gradually increasing worldwide in the adult population over the age of 18. According to WHO estimates, 39% of adults were overweight and 13% were obese in 2016 [9]. Given the increasing prevalence of obesity and persistence of COVID-19, the impact of obesity on the course of COVID-19 is worthy of attention.

The aim of this study was to investigate whether obesity is a poor prognostic factor in COVID-19 and to examine the factors of obesity that may be associated with poor clinical outcome.

Materials and Methods

This single-center observational, cross-sectional, and retrospective study was conducted between March 11, 2020 and May 31, 2020 in patients hospitalized with suspected and confirmed COVID-19 diagnosis at Sureyyapasa Thoracic Diseases and Thoracic Surgery Training and Research Hospital. The data of all the patients were retrieved from the electronic medical database of the hospital.

Patients with positive real-time polymerase chain reaction (RT-PCR) test in nasal and/or oropharyngeal swabs used for the diagnosis of COVID-19 were included in the study [16]. Swab samples were evaluated at the General Directorate of Public Health Microbiology Reference Laboratory and designated Public Health Laboratories.

1. Study population

BMI was calculated by dividing body weight (kg) by the square of height (m2) [9].

Patients were divided into 3 groups based on BMI;

Normal weight (BMI: 18.5 - 24.99 kg/m2)

Overweight (BMI: 25 - 29.99 kg/m2)

Obese (BMI ≥ 30.00 kg/m2)

Patients' vital signs (heart rate, heart rhythm, respiratory rate, blood pressure, body temperature, and oxygen saturation), radiological images, and laboratory values were recorded starting from their admission to the ward. The disease was classified as mild, moderate, and severe according to the guidelines of the Ministry of Health, and treatment was given according to their classification [17].

1) Symptoms of fever, muscle/joint pain, cough, and a sore throat without respiratory distress (respiratory rate <24, saturation of percutaneous oxygen (SpO2) >93% at room air).

2) No underlying co-morbid disease (mainly cardiovascular disease, diabetes mellitus, hypertension, cancer, chronic pulmonary disease, and other immunosuppressive conditions), and patients under 50 years old.

3) A normal chest X-ray and/or thorax tomography.

1) Symptoms such as fever, muscle/joint pain, cough, and a sore throat without respiratory distress (respiratory rate ≤30, SpO2 >90% at room air).

2) Evidence of bilateral pneumonia on chest-X ray or thorax tomography.

4. Severe disease

Patients with severe pneumonia, acute respiratory distress syndrome, sepsis, septic shock, myocarditis, arrhythmia, and cardiogenic shock as well as multiple organ failure. These patients were followed up in the intensive care unit (ICU) [17].

5. Indication for Intensive Care Unit admission

COVID-19 treatment was performed in the ICU according to the criteria determined in the guidelines of the Ministry of Health [17].

6. Invasive mechanical ventilation (IMV)

IMV was employed in cases of refractory hypoxemia, tachypnea, aspiration risk, impaired hemodynamics, multiorgan failure, or impaired mental state [17].

7. Inclusion criteria

Patients hospitalised for mild, moderate and severe COVID-19 infection due to positive nasal and/or oranasal swabs PCR test.

Age <18 years,

COVİD-19 patients followed up in outpatient clinic,

Patients with negative RT-PCR test,

BMI value not recorded

BMI <18.5 kg/m2 (Fig. 1).

Figure 1

Flow chart.

COVID-19, coronavirus disease 2019; RT-PCR, polymerase chain reaction; BMI, body mass index; ICU, intensive care unit.

8. Exclusion criteria

Demographic characteristics, comorbidities, symptoms at presentation, length of hospital stay, ICU requirement, in-hospital mortality, laboratory values, and radiological findings of all three groups were compared.

Unfavorable clinical outcomes of all patients, i.e., transfer to ICU, IMV, and in-hospital mortality, were examined and univariate and multivariate logistic regression analyses were performed for possible risk factors such as age, gender, comorbidity, and obesity.

9. Statistical analysis

The IBM SPSS-22 portable package program (IBM Corporation, Chicago, IL, USA) was used to perform the statistical analyses. Data distributions were examined using the Kolmogorov–Smirnov test. Comparisons between two groups were made by using the independent samples t-test, the chi-square test, or the Mann–Whitney U-test, as appropriate. When comparing more than two groups, normally distributed data were analyzed using one-way analysis of variance whereas non-normally distributed data were analyzed using the Kruskal–Wallis test. Normally distributed data were expressed as mean (SD) and non-normally distributed data as median (interquartile range [IQR]). Categorical variables were presented as frequency and percentage. Spearman's correlation analysis was performed between BMI and inflammatory markers. Intensive care, IMV, and mortality rates of all three groups were compared with Chi-square trend analysis. Among the possible risk factors for transfer to the ICU and need of IMV; age, gender and presence of comorbidity and obesity were evaluated first by univariate analysis and then by multivariate logistic analysis. The results were expressed as odds ratios (ORs) with 95% confidence interval (CI). All statistical tests were 2-tailed, and statistical significance was defined as P <0.05.

10. Ethics statement

Permission was obtained from the scientific committee of the hospital and the Ministry of Health, and approval was obtained from the local ethics committee for the study (No: 2020.41.172).

Results

The data of 284 patients hospitalized at the Chest Diseases clinic and according to inclusion criteria were analyzed.

There were 99 normal-weight patients (35%), 116 overweight patients (41%), and 69 obese (24%) patients according to the BMI classification. Among obese patients, the majority (14%) had class I obesity (BMI: 30 - 34.9 kg/m2) (n = 40), 7% had class II obesity (BMI: 35 - 39.9 kg/m2) (n = 19), and 3% had class III obesity (BMI ≥ 40 kg/m2) (n = 10) (Fig. 2).

Figure 2

Distribution of BMI classification according to gender.

Normal BMI 18.5 - 24.99 kg/m2; Overweight 25 - 29.99 kg/m2; Obese ≥30 kg/m2.

BMI, body mass index.

Table 1 shows the general characteristics of all three groups. In the obese group (BMI ≥ 30), female gender was more common than in the non-obese groups (55% vs. 37 - 40%, P = 0.049). Similarly, the presence of any comorbidity including diabetes, hypertension, and chronic lung diseases was more common in the obese group than in the other groups (P = 0.001 - 0.029). In terms of the duration of hospitalization, the duration of hospitalization of obese patients was longer than those with normal weight (median [IQR], 8 [5 - 12] vs. 6 [5 - 9] days, P = 0.006) (Table 1).

Table 1

Demographic and general characteristics of patients according to BMI categories

		BMI, kg/m2
		Total (n = 284)	Normal (n = 99, 35%)	Overweight (n = 116, 41%)	Obese (n = 69, 24%)	P-value
Age, year		54 (41 - 65)	50 (38 - 65)	54 (41 - 63)	55 (46 - 68)	0.13
Gender, male		163 (57)	59 (60)	73 (63)	31 (45)	0.049
BMI, kg/m2		25.9 (18.8 - 48.8)	23.5 (18.8 - 24.9)	26.6 (25 - 29.8)	33.8 (30.2 - 48.8)	0.001
Comorbidities
	Any	154 (54)	49 (50)	55 (47)	50 (73)	0.002
	Diabetes mellitus	60 (2)	21 (21)	16 (14)	23 (33)	0.007
	Hypertension	87 (31)	26 (26)	31 (27)	30 (44)	0.029
Chronic cardiac diseasea		32 (11)	12 (12)	11 (10)	9 (13)	0.71
Chronic respiratory diseaseb		53 (19)	15 (15)	13 (11)	25 (36)	0.001
Chronic renal disease		4 (1)	2 (1)	-	2 (1)	0.79
Symptoms on admission
	Fever	138 (49)	46 (16)	55 (19)	37 (13)	0.56
	Dyspnea	112 (39)	35 (12)	44 (16)	33 (12)	0.18
	Dry cough	157 (56)	53 (19)	64 (23)	40 (14)	0.79
	Diarrhea	19 (7)	8 (2)	10 (4)	1 (0)	0.14
Duration of the symptoms, days		5 (3 - 8)	5 (3 - 7)	5 (3 - 7)	7 (3 - 10)	0.47
Length of hospital stay, days		7 (7 - 11)	6 (5 - 9)	8 (5 - 12)	8 (5 - 12)	0.006
Radiological findins on chest CT						0.09
	Bilateral opacity	232 (82)	74 (75)	98 (84)	61 (88)
	Unilateral opacity	26 (9.2)	11 (11)	9 (8)	6 (9)

aChronic cardiovasculary disease, including diagnoses of coronary artery disease, congestive heart failure, arrhythmias.

bChronic respiratory disease, including diagnoses of asthma, chronic obstructive pulmonary disease, interstitial fibrosis.

Data are expressed as number (%), median (IQR) interquartile range (25th - 75th percentile).

BMI, body mass index; CT, computed tomography.

When laboratory values of all three groups were compared, there were significant differences in obese patients compared to non-obese patients. Leucocyte count (median 5.9 vs. 5.1) and neutrophil count (median 3.8 vs. 3.3) were significantly higher. Median glucose, and lactate dehydrogenase (LDH) values were found to be significantly higher (P = 0.002, P = 0.03, respectively), while albumin and Ca+ values were significantly lower (P = 0.019, P = 0.012, respectively) in obese patients (Table 2). When Ca+ was calculated as corrected for blood albumin value, it was found to be normal (Ca+: 10.90 mmol/L).

Table 2

Comparison of the laboratory values of the patients according to BMI categories

		n	Total (n = 284)	Normal (n = 99, 35%)	Overweight (n = 116, 41%)	Obese (n = 69, 24%)	P-value
Total blood count
	Leukocyte count, × 109/L	284	5.4 (4 - 7)	5.1 (4.1 - 6.9)	5.4 (3.9 - 6.5)	5.9 (4.5 - 8.5)	0.023
	Hemoglobin, g/dL	284	13.1 (12 - 14)	12.9 (11.8 - 14)	13.2 (12.3 - 14.2)	12.9 (11.4 - 13.7)	0.048
	Platelet count, × 109/L	284	206 (161 - 260)	203 (158 - 260)	205 (160 - 259)	214 (165 - 269)	0.82
	Lymphocyte count, × 109/L	284	1.2 (0.8 - 1.6)	1.2 (0.9 - 1.6)	1.1 (0.8 - 1.5)	1.2 (0.8 - 1.6)	0.38
	Eosinophil count, × 109/L	284	0.01 (0 - 0.06)	0.02 (0 - 0.08)	0.01 (0 - 0.04)	0.01 (0 - 0.05)	0.46
	Neutrophil count, × 109/L	284	3.4 (2.5 - 4.9)	3.33 (2.4 - 4.7)	3.4 (2.4 - 4.5)	3.78 (2.8 - 6.9)	0.031
Biochemistry
	Glucose, mg/dL	281	108 (96 - 139)	104 (91 - 130)	104 (95 - 132)	127 (99 - 166)	0.002
	Albumin, g/dL	276	39 (35 - 42)	39 (35 - 43)	39 (36 - 42)	37 (33 - 41)	0.019
	Ca, mmol/L	281	8.72 (0.61)	8.86 (0.53)	8.68 (0.63)	8.5 (0.67)	0.012
	LDH, U/L	281	236 (189 - 303)	227 (185 - 299)	228 (183 - 293)	267 (212 - 355)	0.030
	D-Dimer, μg/L	257	0.58 (0.4 - 0.9)	0.60 (0.4 - 1.0)	0.57 (0.4 - 0.9)	0.61 (0.3 - 1.2)	0.96
Inflammatory marker
	NLR	284	2.93 (2 - 4.6)	2.59 (2 - 3.8)	3.0 (2 - 4.6)	3.4 (2.2 - 5.5)	0.12
	CRP, mg/mL	281	23.5 (7.8 - 7.3)	20.85 (4.8 - 49.9)	21.6 (6.9 - 57.0)	47.7 (10.9 - 111)	0.004
	Procalcitonin, μg/L	255	0.067 (0.050 - 0.122)	0.060 (0.047 - 0.097)	0.065 (0.049 - 0.106)	0.089 (0.053 - 0.184)	0.044
	Ferritin (ng/mL)	259	161.40 (78.7 - 337.6)	126.50 (65.7 - 239.2)	219.80 (109.3 - 396.6)	190.15 (59.2 - 351.1)	0.007

BMI, body mass index; LDH, lactate dehydrogenase; NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein.

Data are expressed as mean (SD), median interquartile range (IQR) (25th – 75th percentile).

Similarly, significant differences were found in inflammatory markers. Among the inflammatory markers, C-reactive protein (CRP) (median 47.7 vs. 20.85 mg/mL), procalcitonin (median 0.089 vs. 0.060 µg/L), ferritin (median 190.15 vs. 126.50 ng/mL) were significantly higher in obese patients than in non-obese patients (Table 2).

Spearman's Rho correlation analysis was performed between BMI and inflammatory markers (Table 3). There was a weak but significant positive correlation between BMI and leucocyte count, neutrophil count, neutrophil/lympochyte ratio (NLR), CRP, LDH, glucose and procalcitonin (P = 0.001 - 0.026) and negative between BMI and lymphocyte percentage (P = 0.016). The strongest positive correlation was found between BMI and CRP (R = 0.205, P = 0.001).

Table 3

Correlation analysis between BMI and inflammatory markers

	BMI
	R	P-value
Leucocyte count	0.132	0.026
Neutrophil count	0.152	0.010
Lymphocyte %	−0.143	0.016
NLR	0.153	0.010
CRP	0.205	0.001
LDH	0.138	0.021
Albumin	−0.105	0.081
Glucose	0.177	0.003
Procalcitonin	0.150	0.017
Ferritin	0.117	0.060

Correlation analysis of nonparametric Spearman's rho test.

BMI, body mass index; NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein; LDH, lactate dehydrogenase.

Demographic characteristics and the presence of obesity, which are among the possible risk factors for transfer to ICU, were evaluated by univariate and multivariate logistic regression analyses (Table 4). Age and obesity (BMI ≥ 30 kg/m2) posed a significant risk for transfer to ICU both together and independently (adjusted for gender and comorbidity). In multivariate analysis, transfer to the ICU increased by 4% per unit of increase in age (adjusted odds ratio [aOR]: 1.04, 95% CI: 1.02 - 1.07, P <0.001), whereas male gender and obesity increased the risk approximately 3 times (aOR: 2.65, 95% CI: 1.29 - 5.43, P = 0.008; aOR: 2.99, 95% CI: 1.26 - 7.04, P = 0.012, respectively) (Table 4).

Table 4

Univariate and multivariate analysis for possible risk factors for intensive care unit transfer among all patients

		Univariate		Multivariate
		Odd ratio (95% CI)	P-value	Odd ratio (95% CI)	P-value
Age		1.04 (1.02 - 1.06)	<0.001	1.04 (1.02 - 1.07)	<0.001
Male		1.67 (0.89 - 3.16)	0.11	2.65 (1.29 - 5.43)	0.008
Comorbidity		1.96 (1.04 - 3.69)	0.038	1.04 (0.48 - 2.23)	0.93
BMI categories
	Overweight vs. normal weight	1.60 (0.75 - 3.45)	0.23	1.56 (0.67 - 3.49)	0.28
	Obese vs. normal weight	2.76 (1.24 - 6.14)	0.013	2.99 (1.26 - 7.04)	0.012

BMI, body mass index; CI, confidence interval.

In Table 5, patients' ICU, non-IMV, IMV demand and mortality risk were analyzed using chi-square trend analyses according to BMI classifications. Transfer to ICU was required in 52 (18%) of 284 patients. While 12% of normal-weight patients, 18% of overweight patients, and 28% of obese patients were transferred to ICU, the difference was statistically significant (P = 0.039). In addition, IMV was employed in 4% of normal-weight patients, 9% of overweight patients, and 22% of obese patients, and the difference was significant (P = 0.001). While one patient with normal weight died (1%), 10 patients (9%) died in the overweight group, and 11 patients (16%) died in the obese group (P = 0.002).

Table 5

NIMV, IMV and mortality rates in patients in need of ICU

			BMI, kg/m2
			Total (n = 284)	Normal (n = 99, 35%)	Overweight (n = 116, 41%)	Obese (n = 69, 24%)	P-valuea
Hospitalization unit							0.039
	Pulmonology ward		232 (82)	87 (88)	95 (82)	50 (72)
	ICU		52 (18)	12 (12)	21 (18)	19 (28)
		Only nasal oxygen therapy	21 (7)	8 (8)	10 (9)	3 (4)	0.53
		NIMV	1 (0.4)	-	-	1 (100)
		IMV	30 (11)	4 (4)	11 (9)	15 (22)	0.001
	In hospital mortality		22 (8)	1 (1)	10 (9)	11 (16)	0.002

aChi-square trend, by column.

Data are presented as number (%).

NIMV, non invasive mechanical ventilation; IMV, invasive mechanical ventilation; ICU, intensive care unit; BMI, body mass index.

When univariate and multivariate regression analyses were performed for IMV, age and obesity were found to be significant risk factors in both analyses. In multivariate analysis (adjusted for gender and comorbidity), while the IMV risk was increased by 7% per unit of increase in age (aOR: 1.07, 95% CI: 1.03 - 1.10, P <0.001), male gender increased the risk three times (aOR: 3.09, 95% CI: 1.19 - 8.04, P = 0.020) and presence of obesity increased the risk approximately 9 times (aOR: 8.73, 95% CI: 2.44 - 31.20, P = 0.001) (Table 6).

Table 6

Univariate and multivariate analysis for possible risk factors in invasive mechanical ventilation in all patients

		Univariate		Multivariate
		Odd ratio (95% CI)	P	Odd ratio (95% CI)	P-value
Age		1.06 (1.04 - 1.10)	<0.001	1.07 (1.03 - 1.10)	<0.001
Male		1.32 (0.60 - 2.89)	0.49	3.09 (1.19 - 8.04)	0.02
Comorbidity		3.09 (1.28 - 7.45)	0.012	1.14 (0.40 - 3.29)	0.80
BMI categories
	Overweight vs. normal weight	2.49 (0.77 - 8.08)	0.13	2.70 (0.77 - 9.47)	0.12
	Obese vs. normal weight	6.60 (2.08 - 20.89)	0.001	8.73 (2.44 - 31.20)	0.001

BMI, body mass index.

In Table 7, the demographic and laboratory characteristics of the patients who were transferred to ICU (n = 19) and those who were not (n = 50) among patients with obesity (n = 69) were compared. The mean age of the patients who were transferred to ICU was higher than those who were not transferred to ICU (67 vs. 51, P <0.001), and also mean neutrophil count and percentage, glucose, urea, creatinine, LDH, pro-brain natriuretic peptide (P-BNP), D-dimer, troponin, and international normalized ratio (INR) values were significantly higher in the ICU group (from P <0.001 to 0.019). On the other hand, mean lymphocyte count, lymphocyte percentage, albumin, and Ca+ values were significantly lower in the ICU group (from P <0.001 to 0.018). Ca+ corrected for blood albumin level was normal (Ca+: 13.53 mmol/L).

Table 7

Comparison of demographic and laboratory values of patients transferred to ICU with BMI ≥ 30

			n	Non-ICU (n = 50)	ICU (n = 19)	P-value
Age, year			69	51 (13.8)	67 (16.08)	<0.001
Gender			69			0.40
	Female		38	26 (52)	12 (63)
	Male		31	24 (48)	7 (37)
Any comorbidity			69	35 (70)	15 (79)	0.45
Total blood count
	Leukocyte count, × 109/L		69	6.43 (3.3)	8.30 (4.7)	0.07
	Hemoglobin, g/dL		69	12.9 (11.4 - 13.7)	12.4 (9 - 13.2)	0.18
	Platelet count, × 109/L		69	222 (165 - 276)	194 (166 - 246)	0.37
	Lymphocyte count, × 109/L		69	1.36 (1.10 - 1.67)	0.81 (0.50 - 0.98)	<0.001
	Lymphocyte, %, mean (SD)		69	25.13 (11.14)	10.33 (5.90)	<0.001
	Eosinophil, %		69	0.20 (0.08 - 1.38)	0.08 (0.01 - 0.32)	0.029
	Eosinophil, %			0.02 (0 - 0.07)	0 (0 - 0.03)	0.08
	Neutrophil count, × 109/L		69	3.3 (2.7 - 5.5)	5.9 (4.3 - 9.7)	0.003
	Neutrophil, %, mean (SD)		69	63 (13)	82 (8)	<0.001
Biochemistry
	Glucose, mg/dl, mean (SD)		69	134 (59)	195 (94)	0.016
	BUN, mg/dL, mean (SD)		69	30 (14)	53.74 (27)	<0.001
	Creatinine, mg/dL, mean (SD)		69	0.70 (0.23)	0.89 (0.41)	0.019
		ALT, U/L	69	30 (20 - 41)	22 (14 - 47)	0.42
		AST, U/L	69	30 (25 - 38)	33 (23 - 57)	0.28
	Albumin, g/dl, mean (SD)		68	38.5 (4.6)	33.42 (4)	<0.001
	LDH, U/L		69	246 (205 - 301)	365 (254 - 480)	0.004
	Calcium, mmol/L, mean (SD)		69	8.7 (0.7)	8.3 (0.5)	0.018
	D-Dimer, μg/L		68	0.5 (0.3 - 1)	0.9 (0.5 - 1.9)	0.010
	INR		67	1.04 (1.01 - 0.98)	1.08 (1.02 - 1.20)	0.002
	Pro BNP, pg/ml		29	43 (19 - 72)	431 (234 - 2,648)	0.001
	Troponin, μg/L		67	3.00 (1.55 - 4.95)	11.80 (5.10 - 24.60)	<0.001
Inflammatory markers
	NLR		69	2.4 (1.7 - 4.4)	8.03 (4.3 - 17.9)	<0.001
	CRP, mg/mL		69	34 (8 - 70)	117 (79 - 184)	<0.001
	Procalcitonin, μg/L, mean (SD)		67	0.20 (0.65)	0.38 (0.32)	0.27
	Ferritin, ng/mL		66	146 (56 - 298)	306 (124 - 609)	0.026
	Length of hospital stay, day		66	7 (5 - 10)	16 (10 - 26)	<0.001

Data are expressed as mean (SD), number (%), median (IQR) interquartile range (25th – 75th percentile).

ICU, intensive care unit; BMI, body mass index; BUN, blood urea nitrogen; ALT, alanine amino transferase; AST, aspartate amino transferase; LDH, lactate dehydrogenase; INR, international normalized ratio; Pro BNT, pro-brain natriuretic peptide; NLR, neutrophil-to-lymphocyte ratio; CRP, C-reactive protein.

In the ICU group, compared with the group not transferred to the ICU, median NLR (8.03 vs. 2.46, P <0.001), CRP (117 vs. 34 mg/mL, P <0.001), and ferritin (306 vs. 146 ng/mL, P = 0.026) values, which are among inflammatory markers, were higher. Median procalcitonin value (0.38 vs. 0.20 μg/L, P = 0.278) did not differ significantly between the two groups.

Discussion

In this study, the prevalence of overweight (25 kg/m2 ≤ BMI <29.99 kg/m2) and obese (BMI ≥ 30 kg/m2) patients in the PCR positive COVID-19 patient group was 41% and 24%, respectively. Obese patients were found to have more comorbidities (especially hypertension), higher inflammatory markers and longer length of stay in hospital than patients with normal weight. A BMI ≥ 30 kg/m2 was shown to increase the risk for transfer to the ICU by about 3 times and the risk for IMV by 9 times compared with normal BMI, regardless of age, gender, and comorbidities.

It has been reported that obese patients are at risk for infection with the SARS-CoV-2 virus and that COVID-19 has a more severe course in this patient group [61112]. The most frequently suggested hypothesis regarding this issue is that the angiotensin converting enzyme (ACE-2), which is used as a receptor by the SARS-CoV-2 virus for entering into the human cell, is found in abundant amounts in adipose tissue as well as in tissues, such as lung, heart, and kidney [1819]. ACE-2 receptors in adipose tissue enable the entrance of SARS-CoV-2 into adipocytes, making adipose tissue an important organ for viral reservoir [20]. Turkey is regarded as one of the countries with the highest prevalence of obesity in Europe with an obesity prevalence of 29.5% [9]. The prevalence of obesity in our study was found to be slightly lower than that in the national data (24% vs. 29.4%). The missing BMI data of some patients (n = 96) in the study may have affected the prevalence of obesity in the study. In the COVID-19 and obesity studies conducted in other countries, the prevalence of obesity was reported to be 5 - 48% [710121421]. The lowest prevalence was reported in China, the highest prevalence was reported in France, USA, and Italy, and these rates were higher than these countries' own obesity prevalences (6.2% in China, 18% in France, 40% in the USA, and 20% in Italy) [9]. These findings suggest that the prevalence of obesity is higher in hospitalized COVID-19 patients than in the normal population.

In the present study, the presence of at least 1 comorbidity was significantly higher in obese patients than in normal-weight patients with COVID-19 (73% vs. 50%). Hypertension was the most common (44%) comorbidity in obese patients, followed by chronic lung diseases (36%), and diabetes (33%). These results were consistent with other similar COVID-19 obesity studies [614]. Indeed, obesity alone is a condition closely associated with comorbidities, and comorbidities have been reported as risk factors for patients with severe COVID-19 [152223]. The most frequently suggested hypothesis regarding obesity and comorbidity is the presence of a continuous and low-grade systemic inflammation in the adipose tissue of obese individuals. It is considered that inflammation leads to endothelial damage in the liver, insulin resistance, and consequently many interrelated organ dysfunctions, such as diabetes, cardiovascular disease, and hypertension [22]. In the present study, the presence of comorbidity alone posed a significant risk for transfer to the ICU and use of IMV, but when evaluated independently of age, gender, and categorized BMI, it did not pose a significant risk as in some other studies [612]. These findings should be re-evaluated with a higher number of patients in the future.

Various immunological, hormonal, and physical characteristics in obese patients have been shown to lead to major challenges in the medical management of these patients. These characteristics include, above all, susceptibility to infections due to impaired immunity and high glucose levels, lipo-toxicity, vitamin D deficiency, obesity–hypoventilation syndrome, decreased lung volume due to increased intrabdominal pressure, decreased diaphragm contractility, ventilation/perfusion abnormalities, pulmonary embolism risk, and increased tendency to develop hypoxemia as a result of all these conditions [23242526]. Failure to provide effective drug doses in obese patients, ineffective exercise of care by the personnel due to excessive body weight, and difficulty in prone positions are other challenging physical factors [242728]. In a meta-analysis, it was shown that adverse outcomes such as ICU requirement, IMV employment, and in-hospital mortality were approximately twice as high in obese patients with COVID-19 (OR: 1.88; 95% CI: 1.25 - 2.80; P = 0.002) [29]. Simonnet et al. [12] reported that obesity increased the risk of IMV in line with its severity; the presence of class II obesity (BMI ≥ 35 kg/m2) increased this risk by 7 times compared with normal BMI. Lighter et al. [7] reported that younger patients who were obese (BMI 30 kg/m2) had twice more hospital admissions and 1.8 times higher ICU requirements than non-obese patients in their study, where they classified patients as under 60 and over 60 years of age. They reported that a BMI ≥ 35 kg/m2 further increased the risk of hospital admissions by 2.2 times and ICU requirement by 3.6 times. Gao et al. [11] showed that the severity of COVID-19 increased by 13% with each unit of increase in BMI. Similar to all these studies, obesity was found to be a significant risk factor in both univariate analysis and multivariate analysis in COVID-19 patients in the present study. In the multivariate analysis, it was shown to lead to an approximately 3-fold increase in risk for transfer to the ICU and a 9-fold increase in risk for IMV, regardless of age, gender, and comorbidity. Social isolation, staying at home, and physical activity limitation, are crucial in reducing COVID-19 transmission, which have been shown to cause significant weight gain and increase in BMI [30]. Since the negative effect of obesity in COVİD-19 infection is recognized, the clinical importance of obesity during pandemic might be the one of the main issue to be considered.

Different mortality results were defined according to the results of the studies on obesity and COVID-19. In a study by Nakeshband et al. [6], obesity increased the mortality risk by 1.3 times (95% CI: 1.0 - 1.7, P = 0.04), while in a study by Moriconi et al. [14], no difference in mortality was found between obese and non-obese patients (16% vs. 19%). In our study, 16% of the patients who died were obese, 9% were overweight, and 1% were normal weight, and the difference was significantly higher in favor of obese patients (P = 0.002, chi-square trend test).

Studies on inflammatory markers have generally been performed in patients hospitalized with the diagnosis of COVID-19, and laboratory findings such as elevated CRP, LDH, ALT, and AST, decreased albumin, and lymphopenia are non-specific. However, more severely elevated laboratory values have been associated with more severe disease [31]. There are a few studies in the literature that show the relationship between obesity and inflammatory markers in COVID-19. Among these studies, Moriconi et al. [14] reported that they found ferritin, CRP, and TNF-α values to be significantly higher in obese patients compared with non-obese patients with COVID-19. Gao et al. [11] reported that they found lymphopenia and elevated CRP, which are included as predictors for severe disease in the national guidelines, to be more severe in obese patients. In the present study, α-TNF and IL-6 values could not be measured; however, leucocyte, neutrophil, CRP, LDH, ferritin, and procalcitonin values, among other inflammatory markers, were significantly higher in obese patients compared with normal-weight patients. In addition, in our study, a significant increase in neutrophil, LDH, CRP, and ferritin values and a significant decrease in lymphocyte count, lymphocyte percentage, and albumin value were found in the subgroup analysis we performed in obese patients transferred to the ICU. When a correlation analysis was performed between BMI and the aforementioned inflammatory markers, a weak but significant positive relationship was found in all of them except ferritin. Among these markers, CRP showed the highest correlation with BMI. This chronic and low-grade inflammation in obese patients may aggravate the inflammation that develops in COVID-19 patients. In addition, this condition leads to impaired immune response and adverse effects of COVID-19 on lung parenchyma and bronchi in obese patients [18]. Further studies with a higher number of obese patients and inflammatory markers are needed regarding this issue.

The most important limitation of the study is that it is single centered and the sample size is small. Another limitation is that some data are missing due to its retrospective nature. In addition, although BMI that was used for the definition of obesity in the study, is the most common criterion, other anthropometric measurements showing central obesity such as waist/hip ratio are more sensitive measurements for cardiovascular health. Further studies can be performed in the future based on this information. Despite these limitations, to the best of our knowledge, this is the first study in Turkey to investigate the relationship between obesity and COVID-19 and provides important information for clinicians in that it showed the relationship between COVID-19 and obesity.

In our study, overweight and obese patients were found to be more common than normal-weight patients among patients with COVID-19. Comorbidities and inflammatory markers were significantly higher in obese patients than in patients with normal weight. Obesity (BMI ≥ 30 kg/m2) was identified as an important risk factor both together and independently of age, gender, and comorbidity in admission to the ICU and employment of IMV. Mortality was higher in obese patients than in non-obese patients. In summary, this study showed the clinicians that the obese patient group should be followed more closely in COVID-19. The findings of the study may be re-evaluated with a larger number of patients in the future.