Impact of Obesity on Outcomes of Patients With Coronavirus Disease 2019 in the United States: A Multicenter Electronic Health Records Network Study.

During the 2009 H1N1 influenza A virus pandemic, obesity was significantly associated with increased risk for hospitalization and mortality. In 2020, the coronavirus disease 2019 (COVID-19) pandemic has a higher estimated case fatality rate. It has hit the United States at a time when obesity has also reached epidemic status, with the prevalence of obesity increasing from 30.5% to 42.4% and of severe obesity increasing from 4.7% to 9.2% over the past decade. Comorbidities associated with obesity are widely recognized risk factors for poor COVID-19 outcomes; however, larger population-based data evaluating obesity as an independent risk factor continue to be sparse.

Methods

We performed a retrospective cohort study using TriNetX (Cambridge, MA), a global federated health research network that provided access to electronic medical records of patients from multiple large member health care organizations in the United States. Details of the data source are described in the Supplementary Materials.

A search query was performed to identify all adult patients (≥18 years) with a diagnosis of COVID-19 between January 20, 2020, and May 31, 2020. The search criteria to identify potential patients with COVID-19 were based on specific COVID-19 diagnosis codes (Supplementary Materials) or positive laboratory confirmation of COVID-19. Identified patients with COVID-19 were stratified based on a body mass index (BMI) or a diagnosis code for obesity. Patients with a documented BMI of ≥30 kg/m2 or a diagnosis of obesity within 1 year before the diagnosis of COVID-19 were included in the obesity group. Patients with a documented BMI of <30 kg/m2 or with no documented diagnosis of obesity within the last year were included in the control group. We excluded all patients for whom BMI varied between ≥30 kg/m2 and <30 kg/m2 in the preceding year before the diagnosis of COVID-19 or for whom diagnosis of obesity was present but BMI was reported as <30 kg/m2 in the preceding year. Details of patient selection are outlined in Supplementary Figure 1.

Supplementary Figure 1

Flow diagram showing patient selection in the obesity group and control group. SARS, severe acute respiratory syndrome.

The obesity group and control groups were compared after 1:1 propensity score matching (PSM). The primary outcome was a composite of intubation or death up to 30 days after diagnosis of COVID-19. Sensitivity analysis and subgroup analysis based on the obesity class were also performed. Details of the statistical analysis, sensitivity analysis, and limitations are also provided in the Supplementary Materials.

Results

A total of 41,513 adult patients with COVID-19 from 26 health care organizations in the United States were identified. Out of these patients with COVID-19, 8,641 patients with documented BMI of ≥30 kg/m2 (n = 5,879) or diagnosis of obesity (n = 2,762) were included in the obesity group, and 31,273 patients with BMI of <30 kg/m2 (n = 6437) or without any reported diagnosis of obesity were included in the control group (Supplementary Figure 1). Sex, racial, and ethnic differences were seen between the groups, and patients in the obesity group had a significantly higher proportion of comorbidities compared to the control group (Table 1 ). In the crude unadjusted analysis, patients in the obesity group were more likely to have a 30-day composite outcome of death or mechanical ventilation compared to the control group (Risk Ratio [RR] 1.99; 95% confidence interval, 1.84–2.15).

Table 1

Characteristics and Outcomes of Patients With COVID-19 in the Obesity Group and Control Group Before and After Propensity Score Matching

Characteristics	Before Propensity Matching			After Propensity Matching
	COVID-19 with obesity (n = 8,641)	COVID-19 without obesity (n = 31,273)	P value	COVID-19 with obesity (n = 8,112)	COVID-19 without obesity (n = 8,112)	P value
Age, y, mean ± SD	49.68 ± 15.84	49.87 ± 19.27	.395	49.47 ± 16.07	50.68 ± 16.93	<.001
Age, y, n (%)
<40	2,563 (29.66)	11,087 (35.45)	<.001	2,496 (30.77)	2,388 (29.44)	.065
40–60	3,596 (41.62)	10,409 (33.28)	<.001	3,260 (40.19)	3,237 (39.9)	.712
60–80	2,216 (25.65)	6,986 (22.34)	<.001	2,090 (25.76)	2,217 (27.33)	.024
>80	266 (3.08)	2,791 (8.93)	<.001	266 (3.28)	270 (3.33)	.861
Female, n (%)	5,374 (62.19)	16,469 (52.66)	<.001	4,963 (61.18)	4,929 (60.76)	.584
Race, n (%)
White	3,901 (45.15)	14,302 (45.73)	.332	3,719 (45.85)	3,698 (45.59)	.741
Black or African American	3,114 (36.04)	7,534 (24.09)	<.001	2,818 (34.74)	2,886 (35.58)	.264
Asian	96 (1.11)	1,050 (3.36)	<.001	96 (1.18)	110 (1.36)	.326
Unknown race	1,482 (17.15)	8,202 (26.23)	<.001	1,434 (17.68)	1,369 (16.88)	.177
Ethnicity: Hispanic or Latino, n (%)	1,308 (15.14)	4,047 (12.94)	<.001	1,235 (15.22)	1,246 (15.36)	.81
Hypertensive disease, n (%)	4,661 (53.94)	8,091 (25.87)	<.001	4,138 (51.01)	4,202 (51.80)	.315
Disorders of lipoprotein metabolism and other lipidemias, n (%)	3,453 (39.96)	5,823 (18.62)	<.001	2,998 (36.96)	3,037 (37.44)	.526
Diabetes mellitus, n (%)	2,816 (32.59)	3,945 (12.62)	<.001	2,359 (29.08)	2,379 (29.33)	.73
Chronic lower respiratory diseases, n (%)	2,606 (30.16)	4,355 (13.93)	<.001	2,224 (27.42)	2,279 (28.09)	.335
Ischemic heart diseases, n (%)	1,252 (14.49)	2,488 (7.96)	<.001	1,092 (13.46)	1,095 (13.5)	.945
Heart failure, n (%)	1,016 (11.76)	1,618 (5.17)	<.001	844 (10.4)	793 (9.78)	.184
Pulmonary heart diseases, n (%)	395 (4.57)	496 (1.59)	<.001	290 (3.58)	261 (3.22)	.209
Cerebrovascular diseases, n (%)	669 (7.74)	1,768 (5.65)	<.001	603 (7.43)	629 (7.75)	.441
Chronic kidney disease, n (%)	1,051 (12.16)	2,043 (6.53)	<.001	913 (11.26)	933 (11.5)	.621
Fatty liver disease, n (%)	599 (6.93)	511 (1.63)	<.001	409 (5.04)	386 (4.76)	.403
Cirrhosis of liver, n (%)	130 (1.5)	270 (0.86)	<.001	106 (1.31)	105 (1.29)	.945
Malignant neoplasm of breast, n (%)	143 (1.66)	317 (1.01)	<.001	130 (1.6)	138 (1.7)	.622
Malignant neoplasms of lymphoid, hematopoietic and related tissue, n (%)	140 (1.62)	308 (0.99)	<.001	115 (1.42)	125 (1.54)	.515
Malignant neoplasms of digestive organs, n (%)	112 (1.3)	278 (0.89)	<.001	95 (1.17)	94 (1.16)	.942
Malignant neoplasm of prostate, n (%)	79 (0.91)	296 (0.95)	.7832	75 (0.93)	80 (0.99)	.687
Nicotine dependence, n (%)	931 (10.77)	1,891 (6.05)	<.001	817 (10.07)	865 (10.66)	.216
Anthropometric parameters (within last 1 year)a
Body height, inches, mean ± SD	66.08 ± 4.54 (nb = 7,407)	66.32 ± 4.28 (nb = 14,376)	.0001	66.13 ± 4.49 (nb = 6,880)	66.12 ± 4.29 (nb = 4,920)	.891
Body weight, lb, mean ± SD	224.72 ± 62.38 (nb = 6,739)	171.59 ± 46.95 (nb = 14,892)	<.001	223.64 ± 61.98 (nb = 6,275)	175.88 ± 48.73 (nb = 4,811)	<.001
BMI, kg/m2, mean ± SD	37.07 ± 6.74 (nb = 5,879)	24.62 ± 3.23 (nb = 6,437)	<.001	36.89 ± 6.58 (nb = 5,508)	24.70 ± 3.16 (nb = 1,995)	<.001
Body surface area, m2	2.18 ± 0.71 (nb = 994)	1.83 ± 0.27 (nb = 2,132)	<.001	2.17 ± 0.36 (nb = 922)	1.86 ± 0.27 (nb = 750)	<.001

Not included in PSM.

Number of patients with available data.

After PSM, a relatively balanced cohort of obese and nonobese patients were obtained (n = 8,112 patients in each group) (Table 1). The risk of composite outcome was higher in the obesity group compared to the control group (RR, 1.56; 95% confidence interval, 1.41–1.73). Kaplan-Meier survival analysis showed that the cumulative probability of being composite event-free up to 30 days remained significantly lower in the obesity group than the control group (87.7% vs 90.5%; P log rank < .0001) (Supplementary Figure 2). The risk of mortality, intubation, and hospitalization was higher in the obesity group compared to the control group in the matched cohort (Table 1). In a propensity-matched subgroup analysis based on obesity class, the risk of composite outcome and other poor outcomes was highest in patients with obesity class 3 (Table 1). The results of the sensitivity analysis confirmed the robustness of our main findings (Supplementary Materials).

Supplementary Figure 2

Kaplan-Meier survival curve showing the probability of being composite event (intubation or death)–free up at the end of 30 days after COVID-19 diagnosis.

Discussion

Our study using a large nationally representative database showed that patients with COVID-19 with any degree of obesity had a significantly higher risk of hospitalization and intubation or death compared to patients without obesity. A substantial incremental risk of intubation or death in the obesity cohort persisted even after meticulous PSM to adjust for confounding comorbidities. Patients with severe obesity were at highest risk of these poor outcomes.

The COVID-19 pandemic has exposed the delivery of health care in the United States and has provoked a reckoning regarding our health care model moving forward. The US obesity epidemic has continued to grow for decades without any signs of abating. Obesity and its associated comorbidities are now a significant determinant of COVID-19 outcomes in a population where more than 90 million adults have obesity and are highly susceptible. The disproportionate prevalence of obesity and associated comorbidities probably also have played a significant role in the racial and ethnic disparities seen during the COVID-19 pandemic. The obesity cohort derived from our data source showed a higher proportion of African Americans and Hispanics in the obesity group. Obesity increases the risk of poor outcomes in this vulnerable population with limited access to health care. Advanced age and male sex are major risk factors for worse prognosis and higher mortality in patients with COVID-19. However, a larger proportion of patients with obesity in our cohort were female, and the impact of this can be dramatic enough to shift severe COVID-19 outcomes toward female patients. Similarly, a large number of younger patients with obesity are also affected by severe COVID-19 with poor outcomes. In the United States where obesity is an epidemic, its impact is not only limited to clinical outcomes. Along with the psychosocial impacts of social distancing and quarantining that are applicable to the entire society, persons with obesity must contend with “weight stigma.” Derogation of persons with obesity is not uncommon and, unfortunately, more socially acceptable than other marginalized groups. These biases and behaviors are not limited to the general public, and studies have shown that many health care workers can also have negative attitudes and stereotypes about persons with obesity.

Our findings highlight the need for a vast improvement in the care of patients with obesity during this pandemic and moving forward. Physicians should manage patients with COVID-19 with obesity aggressively because outcomes can be significantly worse than in the general population. In the long term, to prepare for future pandemics or if COVID-19 becomes seasonal, there is also a serious need to develop and implement weight-loss strategies. There is a necessity for more health care professionals, including gastroenterologists, to play a central role in caring for patients with obesity.

Supplementary Table 1

Codes Used

Variable	Coding System and Codes
Codes Used for Patient Characteristics Included in the PSM
Race	HL7 version 3
White	2106-3
Black or African American	2054-5
Unknown race	2131-1
Asian	2028-9
Ethnicity	HL7 version 3
Hispanic or Latino	2135-2
Hypertensive diseases	ICD-10 I10-I16
Disorders of lipoprotein metabolism and other lipidemias	ICD-10 E78
Diabetes mellitus	ICD-10 E08-E13
Chronic lower respiratory diseases	ICD-10 J40-J47
Chronic kidney disease	ICD-10 N18
Ischemic heart diseases	ICD-10 I20-I25
Heart failure	ICD-10 I50
Nicotine dependence	ICD-10 F17
Cerebrovascular diseases	ICD-10 I60-I69
Fatty (change of) liver	ICD-10 K76.0
Cirrhosis of liver	ICD-10 K74.6
Pulmonary heart diseases	ICD-10 I27
Malignant neoplasm of breast	ICD-10 C50
Malignant neoplasms of lymphoid, hematopoietic and related tissue	ICD-10 C81-C96
Malignant neoplasm of prostate	ICD-10 C61
Malignant neoplasms of digestive organs	ICD-10 C15-C26
Codes Used for Anthropometric Parameters and Obesity Diagnosis
Body height	TNX 9077 (Included LOINC codes 8307-1 Body height –preoperative, 8306-3 Body height –lying, 8302-2 Height, 8301-4 Body height Estimated, 3138-5 Body height Stated, 8308-9 Body height –standing, 8305-5 Body height –postpartum, 3137-7 Body height Measured)
Body weight	TNX 9081 (Included LOINC codes 8335-2 Body weight Estimated, 3142-7 Body weight Stated, 3141-9 Weight, 29463-7 Body weight)
Body surface area	TNX 9087 (Included LOINC codes 8277-6 Body surface area, 3139-3 Body surface area Measured, 3140-1 Body surface area)
BMI	LOINC code 39156-5 Body mass index ICD-10 Z68
Obesity	ICD-10 E66 (excluding ICD-10 E66.3 overweight)
Codes Used to Define Outcomes of the Study
Variable	Codes and
Mortality	“Deceased” (Known deceased documented)
Mechanical Ventilation	“31500” (CPT: Intubation, endotracheal, emergency procedure) OR “1015098” (CPT: Ventilator management) OR “5A1935Z” (ICD-10: Respiratory Ventilation, Less than 24 Consecutive hours) OR “5A1945Z” (ICD-10: Respiratory Ventilation, 24–96 Consecutive hours) OR “5A1955Z” (ICD-10: Respiratory Ventilation, Greater than 96 Consecutive hours) OR “0BH17EZ” (ICD-10: Insertion of Endotracheal Airway into Trachea, Via Natural or Artificial Opening) OR 0BH18EZ (ICD-10: Insertion of Endotracheal Airway into Trachea, Via Natural or Artificial Opening Endoscopic) OR 0BH13EZ (ICD-10: Insertion of Endotracheal Airway into Trachea, Percutaneous Approach) OR 1022227 (CPT: Extracorporeal membrane oxygenation [ECMO]/extracorporeal life support [ECLS] provided by physician) OR 39.65 (ICD9: Extracorporeal membrane oxygenation [ECMO])
Hospitalization:	“1013659” (CPT: Hospital Inpatient Services) OR “1013609” (CPT: Initial Inpatient Consultation) OR “1013729” (CPT: Critical Care Services) OR “Visit: Inpatient Acute” OR “Visit: Inpatient Encounter” OR “Visit: Inpatient Non-acute” OR “Visit: Short Stay”