Early Release / June 17, 2020 / 69 Marie E. Killerby, VetMB1; Ruth
Link-Gelles, PhD1; Sarah C. Haight, MPH1; Caroline A.
Schrodt, MD1,2; Lucinda England, MD1,2; Danica J. Gomes,
MD1,2; Mays Shamout, MD1,2; Kristen Pettrone, MD1,2;
Kevin O’Laughlin, MD1,2; Anne Kimball, MD1,2; Erin F.
Blau, DNP1,2; Eleanor Burnett, MPH1; Chandresh N. Ladva,
PhD1; Christine M. Szablewski, DVM2,3; Melissa
Tobin-D’Angelo, MD3; Nadine Oosmanally, MSPH3; Cherie
Drenzek, DVM3; David J. Murphy, MD, PhD4; James M. Blum,
MD4; Julie Hollberg, MD4; Benjamin Lefkove, MD5;
Frank W. Brown, MD4,5; Tom Shimabukuro, MD1; Claire M.
Midgley, PhD1; Jacqueline E. Tate, PhD1; CDC COVID-19
Response Clinical Team (View author
affiliations) View suggested citation
Summary
What is already known about this topic?
Hospitalized COVID-19 patients are more commonly
older, male, of black race, and have underlying conditions. Less is known about
factors increasing risk for hospitalization.
What is added by this report?
Data for 220 hospitalized and 311
nonhospitalized COVID-19 patients from six metropolitan Atlanta hospitals and
associated outpatient clinics found that older age, black race, diabetes, lack
of insurance, male sex, smoking, and obesity were independently associated with
hospitalization.
What are the implications for public health
practice?
To reduce severe outcomes from COVID-19,
measures to prevent infection with SARS-COV-2 should be emphasized for persons
at highest risk for hospitalization with COVID-19. Potential barriers to the
ability to adhere to these measures need to be addressed.

The first reported U.S. case of coronavirus
disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15,
2020, approximately 2 million cases and 115,000 COVID-19–associated deaths have
been reported in the United States.* Reports of U.S. patients hospitalized with
SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions
of older, male, and black persons (2–4). Similarly, when
comparing hospitalized patients with catchment area populations or
nonhospitalized COVID-19 patients, high proportions have underlying conditions,
including diabetes mellitus, hypertension, obesity, cardiovascular disease,
chronic kidney disease, or chronic respiratory disease (3,4). For
this report, data were abstracted from the medical records of 220 hospitalized
and 311 nonhospitalized patients aged ≥18 years with laboratory-confirmed
COVID-19 from six acute care hospitals and associated outpatient clinics in
metropolitan Atlanta, Georgia. Multivariable analyses were performed to
identify patient characteristics associated with hospitalization. The following
characteristics were independently associated with hospitalization: age ≥65
years (adjusted odds ratio [aOR] = 3.4), black race
(aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of
insurance (aOR = 2.8), male sex (aOR = 2.4), smoking
(aOR = 2.3), and obesity (aOR = 1.9). Infection with
SARS-CoV-2 can lead to severe outcomes, including death, and measures to
protect persons from infection, such as staying at home, social distancing (5),
and awareness and management of underlying conditions should be emphasized for
those at highest risk for hospitalization with COVID-19. Measures that prevent
the spread of infection to others, such as wearing cloth face coverings (6),
should be used whenever possible to protect groups at high risk. Potential
barriers to the ability to adhere to these measures need to be addressed.
Patients were selected from six acute care
hospitals and associated outpatient clinics affiliated with a single academic
health care system in metropolitan Atlanta. Hospitalized patients were selected
sequentially from hospital-provided lists of patients aged ≥18 years who were
hospitalized with laboratory-confirmed COVID-19 (defined as a positive
real-time reverse transcription–polymerase chain reaction [RT-PCR] test result
for SARS-CoV-2) during March 1–30. The 220 selected hospitalized patients were
described previously (2); hospitalizations included stays for observation
and deaths that occurred in an emergency department (ED). All 311
nonhospitalized patients (i.e., evaluated at outpatient clinics or an ED and
not admitted) aged ≥18 years with laboratory-confirmed COVID-19 during March
1–April 7, were included, unless they stayed for observation or died in an ED.
During April 8–May 1, trained personnel abstracted information from electronic
medical records on patient demographics, occupation, underlying conditions, and
symptoms using REDCap software (version 8.8.0; Vanderbilt University) (7).
This investigation was determined by CDC to be public health surveillance and
by the Georgia Department of Public Health as an institutional review
board–exempt public health evaluation.
During March 1–April 7, 2020, the health care
system operated a telephone triage line to manage incoming patients with
COVID-19–compatible symptoms. Patients with signs of severe illness (e.g.,
severe shortness of breath, confusion, or hemoptysis) were directed to an ED.
Other symptomatic persons could receive outpatient SARS-CoV-2 testing; however,
testing was limited, and appointments were prioritized for health care
personnel and persons considered to be at higher risk for severe
COVID-19–associated illness (e.g., persons aged ≥65 years and those with
underlying conditions, including diabetes mellitus, cardiovascular disease, and
chronic respiratory disease).
For analyses, race was categorized as black or
other race; obesity was defined as body mass index ≥30 kg/m2; age
was categorized as 18–44, 45–64, and ≥65 years; smoking was defined as being a
current or former smoker; cardiovascular disease excluded hypertension alone;
and chronic kidney disease included end stage renal disease. Health care
personnel were classified as persons whose occupations included patient contact
or possible exposure to infectious agents in a health care setting.† Univariable
and multivariable logistic regressions were used to compare hospitalized with
nonhospitalized patients; variables included age group, race, sex, smoking
status, insurance status, obesity, hypertension, diabetes mellitus,
cardiovascular disease, chronic respiratory disease, and chronic kidney
disease. These variables were selected based upon risk factors for severe COVID-19
identified in other studies (3,4) rather than a defined
statistical endpoint. Persons lacking a health care visit during which a
medical history could be recorded (25) were excluded from analyses. Because of
small sample sizes for some variables, Firth’s correction was used to provide
bias-reduction (8). Because information on race was missing for nearly
one quarter (23%) of nonhospitalized patients, sensitivity analyses were
performed. Multivariable analyses were repeated and any patient with missing race
was reclassified, first as black, then as other race. This method of
sensitivity analysis was used to avoid implicit assumptions about the nature of
missing data. Data were analyzed using SAS statistical software (version 9.4;
SAS Institute).
Compared with nonhospitalized patients (311),
hospitalized patients (220) were older (median age = 61 years) and
more frequently male (52%) and black (79%) (Table). Obesity, smoking, hypertension,
diabetes mellitus, and chronic kidney disease were more prevalent among
hospitalized patients than among nonhospitalized patients. Among those whose
occupations were reported, nonhospitalized patients were more likely to be health
care personnel (54%) than were hospitalized patients (4%). Fever or cough were
commonly reported among both hospitalized and nonhospitalized patients, whereas
shortness of breath was reported more often among hospitalized patients.
Chills, headache, loss of smell or taste, or sore throat were reported more
often among nonhospitalized patients.
After controlling for age, sex, race, obesity,
smoking status, insurance status, hypertension, diabetes mellitus,
cardiovascular disease, chronic respiratory disease, and chronic kidney
disease, characteristics independently associated with hospitalization were age
≥65 years (aOR = 3.4, 95% confidence interval
[CI] = 1.6–7.4); black race (aOR = 3.2, 95%
CI = 1.8–5.8); having diabetes mellitus (aOR = 3.1, 95%
CI = 1.7–5.9); lack of insurance (aOR = 2.8, 95% CI
1.1–7.3); male sex (aOR = 2.4, 95% CI = 1.4–4.1); smoking
(aOR = 2.3, 95% CI = 1.2–4.5); and obesity
(aOR = 1.9, 95% CI = 1.1–3.3) (Figure). When missing race was reclassified as
black or other race in sensitivity analyses, associations with hospitalization
did not appreciably change for any variables.
Discussion
Older age, as measured by age ≥65 years, was
associated with hospitalization, consistent with previous findings (3,4).
Hospitalized patients with COVID-19 were more likely to have diabetes mellitus
and obesity than were nonhospitalized patients, suggesting a relationship
between these underlying conditions and increased severity of illness. Diabetes
mellitus has been determined to be associated with more severe illness in
hospitalized patients with COVID-19 (4) and in persons with illness
caused by Middle East respiratory syndrome coronavirus (9). Obesity has
previously been reported to be overrepresented in hospitalized patients with
COVID-19 (3) and associated with hospitalization (4). After
controlling for other underlying conditions and patient characteristics,
hypertension was no longer associated with hospitalization, suggesting that
other underlying conditions or factors associated with hypertension might be
partially responsible for the higher prevalence of hypertension in hospitalized
COVID-19 patients.
The COVID-19 pandemic has highlighted persistent
health disparities in the United States. In a previous investigation of hospitalized
patients in Georgia, including the subset of hospitalized patients reported
here, the proportion of patients who were black was higher than expected based
on overall hospitalizations during the same period (2). Racial and
ethnic minority groups are at higher risk for severe complications from
COVID-19 because of the increased prevalence of diabetes, cardiovascular
disease, and other underlying conditions among racial and ethnic minority
groups.§ Social determinants of health might also contribute to
the disproportionate incidence of COVID-19 in racial and ethnic minority
groups, including factors related to housing, economic stability, and work
circumstances.¶ In the United States, black workers are more
likely than other workers to be frontline industry or essential workers,**
which increases their likelihood of infection with SARS-CoV-2 while performing
their jobs. This and other social factors could contribute to the
disproportionate diagnoses of COVID-19 among black persons in metropolitan Atlanta.
Black race has previously been associated with
increased hospitalization among COVID-19 patients (10); however, race
has not been associated with mortality among patients who were hospitalized (2,10).
The independent association between black race and hospitalization in this investigation
remained, even when the analysis controlled for other characteristics
(including diagnosed underlying conditions), suggesting underlying conditions
alone might not account for the higher rate of hospitalization among black
persons. This might indicate that black persons are more likely to be
hospitalized because of more severe illness, or it might indicate that black
persons are less likely to be identified in the outpatient setting, potentially
reflecting differences in health care access or utilization or other factors
not identified through medical record review. Additional research is needed to
more fully understand the association between black race and hospitalization.
CDC and state and local partners are working to ensure completeness of race and
ethnicity data and will continue to analyze and report on racial and ethnic
disparities to further elucidate factors and health disparities associated with
COVID-19 incidence and illness severity.
The findings in this report are subject to at
least five limitations. First, although this investigation identified COVID-19
patients from a single health care system, hospitalized patients likely
represent a broader population than nonhospitalized patients because those
experiencing mild illness might have accessed outpatient services outside of
this health care system or chosen not to seek care. Differences in these two
populations caused by selection bias might therefore result in nonhospitalized
patients differing beyond having milder illness than hospitalized patients.
Thus, in this report, hospitalization status might not only represent severity
of illness but also care seeking and potentially other confounding
characteristics. Second, given that outpatient testing was prioritized for
certain persons, older patients and those with underlying conditions might be
overrepresented among outpatients receiving testing, resulting in
underestimated odds ratios for hospitalization. In addition, overrepresentation
of health care personnel in the outpatient setting could result in
overestimation of odds ratios if health care personnel were disproportionately
young or healthy. Third, outpatient visits did not always include a full
medical history; thus, underlying conditions and other characteristics might be
underreported. Fourth, data on age was stratified into groups, and because of
sample size, smaller age group categories could not be explored. Finally, data
on race, body mass index, and smoking status were missing for a substantial proportion
of nonhospitalized patients. Data could not be disaggregated for other races or
analyzed by ethnicity because of small sample sizes.
This investigation found that age ≥65 years,
black race, and having diabetes mellitus were independently associated with
hospitalization. Among the underlying conditions included in the multivariable
analysis, diabetes mellitus was most strongly associated with hospitalization.
The reported association between black race and hospitalization, which remained
even after controlling for diagnosed underlying conditions, suggests that
underlying conditions alone might not account for the higher rate of hospitalization
among black persons. Other factors that might explain higher rates of
hospitalization include health care access, other social determinants of
health, or the possibility of bias. Infection with SARS-CoV-2 can lead to
severe outcomes, including death, and measures to protect persons from
infection such as staying at home, social distancing (5), and awareness
and management of underlying conditions should be emphasized for those at
highest risk for hospitalization with COVID-19. To protect groups at high risk,
measures that prevent the spread of infection to others, such as wearing cloth
face coverings (6), should be used whenever possible. Potential barriers
to the ability to adhere to these measures need to be addressed.
Acknowledgments
Stephanie R. Bialek, William Bornstein, Deron C.
Burton, Mary E. Evans, Nathan W. Furukawa, Debra Houry, CDC COVID-19 Response
Team; Kymmi Cooley; C. Hernandez-Romieu; Alfonso Mohleen Kang; Guru Patel;
Jonathan Perkins; informatics and information technology staff members at
collaborating hospitals; Atlanta health care personnel.
CDC COVID-19 Response
Clinical Team
Sean D. Browning, CDC; Beau B. Bruce, CDC;
Juliana da Silva, CDC; Jeremy A.W. Gold, CDC; Brendan R. Jackson, CDC; Sapna
Bamrah Morris, CDC; Pavithra Natarajan, CDC; Robyn Neblett Fanfair, CDC; Priti
R. Patel, CDC; Jessica Rogers-Brown, CDC; John Rossow, CDC; Karen K. Wong, CDC.
Corresponding author: Marie Killerby, MKillerby@cdc.gov,
404-626-73
1CDC COVID-19 Emergency Response Team; 2Epidemic
Intelligence Service, CDC; 3Georgia Department of Public
Health; 4Emory University School of Medicine, Atlanta,
Georgia; 5Emory Decatur Hospital, Decatur, Georgia.
All authors have completed and submitted the
International Committee of Medical Journal Editors form for disclosure of
potential conflicts of interest. James M. Blum reports personal fees from Clew
Medical, outside the submitted work. No other potential conflicts of interest
were disclosed.
References
1.
Holshue ML, DeBolt C,
Lindquist S, et al.; Washington State 2019-nCoV Case Investigation Team. First
case of 2019 novel coronavirus in the United States. N Engl J Med
2020;382:929–36. CrossRefexternal icon PubMedexternal icon
2.
Gold JAW, Wong KK,
Szablewski CM, et al. Characteristics and clinical outcomes of adult patients
hospitalized with COVID-19—Georgia, March 2020. MMWR Morb Mortal Wkly Rep 2020;69:545–50. CrossRefexternal icon PubMedexternal icon
3.
Garg S, Kim L, Whitaker
M, et al. Hospitalization rates and characteristics of patients hospitalized
with laboratory-confirmed coronavirus disease 2019—COVID-NET, 14 states, March
1–30, 2020. MMWR Morb Mortal Wkly Rep 2020;69:458–64. CrossRefexternal icon PubMedexternal icon
4.
Petrilli CM, Jones SA,
Yang J, 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. Epub May 22, 2020. CrossRefexternal icon PubMedexternal icon
5.
CDC. Coronavirus disease
2019 (COVID-19): what you can do. Atlanta, GA: US Department of Health and
Human Services, CDC; 2020. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/what-you-can-do.html
6.
CDC. Coronavirus disease
2019 (COVID-19): how to protect yourself & others. Atlanta, GA: US
Department of Health and Human Services, CDC; 2020. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html
7.
Harris PA, Taylor R,
Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture
(REDCap)—a metadata-driven methodology and workflow process for providing
translational research informatics support. J Biomed Inform 2009;42:377–81. CrossRefexternal icon PubMedexternal icon
8.
Firth D. Bias reduction
of maximum likelihood estimates. Biometrika 1993;80:27–38. CrossRefexternal icon
9.
Alanazi KH, Abedi GR,
Midgley CM, et al. Diabetes mellitus, hypertension, and death among 32 patients
with MERS-CoV infection, Saudi Arabia. Emerg Infect Dis 2020;26:166–8. CrossRefexternal icon PubMedexternal icon
10. Price-Haywood EG, Burton J, Fort D, Seoane L.
Hospitalization and mortality among black patients and white patients with
Covid-19. N Engl J Med 2020. Epub May 27, 2020. CrossRefexternal icon PubMedexternal icon
|
Demographic characteristic
|
No. (%) of patients
|
||
|
Nonhospitalized
(n = 311) |
Hospitalized
(n = 220) |
||
|
Sex
|
|||
|
Male
|
114 (36.7)
|
114 (51.8)
|
|
|
Female
|
197 (63.3)
|
106 (48.2)
|
|
|
Age group (yrs)
|
|||
|
Median age, yrs (IQR)
|
45.0 (33.0–58.0)
|
61.0 (45.0–70.0)
|
|
|
18–44
|
151 (48.6)
|
54 (24.6)
|
|
|
45–64
|
120 (38.6)
|
76 (34.6)
|
|
|
≥65 years
|
40 (12.9)
|
90 (40.9)
|
|
|
Race
|
|||
|
White
|
90 (28.9)
|
29 (13.2)
|
|
|
Black
|
139 (44.7)
|
174 (79.1)
|
|
|
Other
|
10 (3.2)
|
7 (3.2)
|
|
|
Missing race
|
72 (23.2)
|
10 (4.6)
|
|
|
Ethnicity
|
|||
|
Hispanic
|
10 (3.2)
|
6 (2.7)
|
|
|
Non-Hispanic*
|
197 (63.3)
|
203 (92.3)
|
|
|
Missing ethnicity
|
104 (33.4)
|
11 (5.0)
|
|
|
Occupation
|
|||
|
Health care personnel†
|
168 (54.0)
|
8 (3.6)
|
|
|
Non-health care personnel
|
78 (25.1)
|
50 (22.7)
|
|
|
Missing occupation
|
65 (20.9)
|
162 (73.6)
|
|
|
Other characteristic
|
|||
|
Uninsured
|
20 (6.4)
|
22 (10.0)
|
|
|
Missing insurance status
|
6 (1.9)
|
3 (1.4)
|
|
|
Lives in a congregate living facility§
|
1 (0.3)
|
12 (5.5)
|
|
|
Pregnant
|
4 (1.3)
|
3 (1.4)
|
|
|
Past or current smoking
|
37 (11.9)
|
54 (24.6)
|
|
|
Missing smoking status
|
52 (16.7)
|
9 (4.1)
|
|
|
Underlying condition
|
|||
|
Obesity¶
|
104 (33.4)
|
123 (55.9)
|
|
|
Missing BMI
|
84 (27.0)
|
11 (5.0)
|
|
|
Cardiovascular disease
|
12 (3.9)
|
8 (3.6)
|
|
|
Hypertension
|
101 (32.5)
|
142 (64.6)
|
|
|
Diabetes mellitus
|
30 (9.7)
|
81 (36.8)
|
|
|
Type 1
|
2 (0.6)
|
2 (0.9)
|
|
|
Type 2
|
28 (9.0)
|
74 (33.6)
|
|
|
Chronic respiratory disease
|
56 (18.0)
|
45 (20.5)
|
|
|
Chronic kidney disease
|
7 (2.3)
|
38 (17.3)
|
|
|
Chronic kidney disease without dialysis
|
6 (1.9)
|
24 (10.9)
|
|
|
End stage renal disease
|
1 (0.3)
|
14 (6.4)
|
|
|
Any transplant
|
1 (0.3)
|
10 (4.6)
|
|
|
Liver disease
|
4 (1.3)
|
5 (2.3)
|
|
|
HIV infection
|
10 (3.2)
|
5 (2.3)
|
|
|
Cancer
|
28 (9.0)
|
6 (2.7)
|
|
|
Rheumatological disease
|
4 (1.3)
|
6 (2.7)
|
|
|
No. of underlying conditions**
|
|||
|
0
|
169 (54.3)
|
44 (20.0)
|
|
|
1
|
88 (28.3)
|
77 (35.0)
|
|
|
2
|
44 (14.2)
|
65 (29.6)
|
|
|
≥3
|
10 (3.2)
|
34 (15.5)
|
|
|
Symptoms at initial evaluation
|
|||
|
Fever††
|
240 (77.2)
|
188 (85.5)
|
|
|
Cough
|
275 (88.4)
|
180 (81.8)
|
|
|
Shortness of breath (dyspnea)
|
135 (43.4)
|
149 (67.7)
|
|
|
Headache
|
171 (55.0)
|
35 (15.9)
|
|
|
Chills
|
178 (57.2)
|
58 (26.4)
|
|
|
Arthralgia
|
44 (14.2)
|
9 (4.1)
|
|
|
Myalgia
|
184 (59.2)
|
69 (31.4)
|
|
|
Sore throat
|
146 (47.0)
|
21 (9.6)
|
|
|
Loss of smell§§
|
130 (41.8)
|
4 (1.8)
|
|
|
Loss of taste
|
106 (34.1)
|
6 (2.7)
|
|
|
Gastrointestinal symptoms¶¶
|
137 (44.1)
|
88 (40.0)
|
|
|
Median interval between symptom onset and
testing, days (IQR)
|
4.0 (2.0–7.0)
|
6.0 (3.0–9.5)
|
|
Abbreviations: BMI = body mass index; HIV = human
immunodeficiency virus; IQR = interquartile range.
* Includes non-Hispanic white and other races/ethnicities.
† Includes any occupation with patient contact.
§ Includes nursing homes, assisted living facilities, shelters, and dormitories.
¶ BMI ≥30.0 kg/m2.
** Includes cardiovascular disease, hypertension, diabetes, chronic respiratory disease, and chronic kidney disease.
†† Includes subjective or objective fever (≥100.4°F [38°C]).
§§ Loss of smell or taste was first widely reported on April 23, 2020; differences in the periods of investigations between hospitalized and nonhospitalized patients might be responsible for differences in proportions reported.
¶¶ Includes abdominal pain, diarrhea, nausea, or vomiting.
* Includes non-Hispanic white and other races/ethnicities.
† Includes any occupation with patient contact.
§ Includes nursing homes, assisted living facilities, shelters, and dormitories.
¶ BMI ≥30.0 kg/m2.
** Includes cardiovascular disease, hypertension, diabetes, chronic respiratory disease, and chronic kidney disease.
†† Includes subjective or objective fever (≥100.4°F [38°C]).
§§ Loss of smell or taste was first widely reported on April 23, 2020; differences in the periods of investigations between hospitalized and nonhospitalized patients might be responsible for differences in proportions reported.
¶¶ Includes abdominal pain, diarrhea, nausea, or vomiting.

Abbreviation: COVID-19 = coronavirus disease 2019.
* Adjusted for age, sex, race, obesity, past or
current smoking, insurance status, obesity, and other underlying conditions
(hypertension, diabetes mellitus, cardiovascular disease, chronic respiratory
disease, and chronic kidney disease).
† Complete case analysis was used for multivariable analyses;
therefore, n = 368 for the multivariable model.
Suggested citation for this article: Killerby ME, Link-Gelles R, Haight SC, et
al. Characteristics Associated with Hospitalization Among Patients with
COVID-19 — Metropolitan Atlanta, Georgia, March–April 2020. MMWR Morb Mortal
Wkly Rep. ePub: 17 June 2020. DOI: http://dx.doi.org/10.15585/mmwr.mm6925e1external icon.
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