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Background. Obesity is now well recognised as a risk factor for severe COVID‑19, but the true prevalence of obesity in hospitalised adults
with COVID‑19 remains unclear because formal body mass indices (BMIs) are not routinely measured on admission.
Objectives. To describe the true prevalence of obesity measured by the BMI, and associated comorbidities, in patients hospitalised with
severe COVID‑19, including people with HIV (PWH).
Methods. We conducted a point‑prevalence study of measured BMI in consecutive patients with severe COVID‑19 admitted to the medical
COVID‑19 wards in a tertiary academic hospital in Cape Town, South Africa (SA). Patients were enrolled over a 2‑week period during the
peak of the rst COVID‑19 wave in SA.
Results. We were able to measure the BMI in 122 of the 146 patients admitted during the study period. e prevalence of HIV was 20%
(n=24/122). Most of the participants were overweight or obese (n=104; 85%), and 84 (68.9%) met criteria for obesity. e mean (standard
deviation) BMI was 33 (7.5), and 34.5 (9.1) in PWH. Of PWH, 83% (n=20/24) were overweight or obese and 75% (n=18) met criteria for
obesity. Multimorbidity was present in 22 (92%) of PWH.
Conclusion. We found that most patients, including PWH, met criteria for being overweight or obese. e high prevalence of obesity in
PWH and severe COVID‑19 reinforces the need for targeted management of non‑communicable diseases, including obesity, in PWH.
Keywords. HIV, obesity, body mass index, COVID‑19, multimorbidity.
Afr J Thoracic Crit Care Med 2023;29(3):e660. https://doi.org/10.7196/AJTCCM.2023.v29i3.660
A point-prevalence study of body mass indices in HIV-positive
and HIV-negative patients admitted to hospital with COVID-19
inSouth Africa
A Parker,1,2 MB ChB, FCP (SA), MMed (Int), Cert ID (SA); A G B Broadhurst,1 MB ChB; M S Moolla,1,3 MB ChB, FCP (SA), MMed (Int);
L Amien,1 MB ChB; R Ahmed,1 MB ChB; J J Taljaard,2 MB ChB, DTM&H, MMed (Int); G Meintjes,4,5 MB ChB, FCP (SA), FRCP, MPH, PhD;
P Nyasulu,3 PhD; C F N Koegelenberg,6 MB ChB, MMed (Int), FCP (SA), FRCP, Cert Pulmonology (SA), PhD
1
Division of General Medicine, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University and Tygerberg Hospital, Cape Town, South Africa
2
Division of Infectious Diseases, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University and Tygerberg Hospital, Cape Town, South Africa
3
Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, SouthAfrica
4
Department of Medicine, Faculty of Health Sciences, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa
5
Wellcome Centre for Infectious Disease Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, South Africa
6
Division of Pulmonology, Department of Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University and Tygerberg Hospital, Cape Town, SouthAfrica
Corresponding author: A Parker (aparker@sun.ac.za)
Obesity has emerged as a significant risk factor for COVID‑19
severity and mortality.[1,2] Models have estimated that 30.2% of adult
COVID‑19 hospitalisations are attributable to obesity.[3] A limitation
to many studies is that anthropometric measurements such as the
body mass index (BMI) are not routinely performed during hospital
admission, which may have resulted in over‑ or underestimation of
the true prevalence of obesity.[4] Reasons for not routinely recording
anthropometric measurements are multifactorial.[2,5] e patient may
Study synopsis
What the study adds
• We found that the true prevalence of obesity, including in people with HIV (PWH), measured with the formal body mass index in
hospitalised patients with severe COVID‑19 was much higher than reported previously.
• Multimorbidity was present in over half of all patients, and in 92% of PWH.
Implications of the ndings
• Urgent public health measures are required to tackle the rise in obesity, including in low‑ and middle‑income countries.
• HIV care must integrate management of non‑communicable diseases, including obesity.
• e pathogenic mechanism of the link between obesity and severe COVID‑19 needs further research.
128 AJTCCM VOL. 29 NO. 3 2023
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have been too ill to stand for weight measurement, or sta may have
wanted to limit non‑essential interactions with patients owing to the
infectious nature of SARS‑CoV‑2.
Southern Africa is the region with the largest HIV‑infected
population globally.[6] An estimated 68% of females and 31% of males
are reported to be either overweight or obese in South Africa (SA), with
the highest rates in Western Cape Province (73% of females and 44%
of males).[7] While large epidemiological studies have reported HIV as
an independent risk factor for adverse COVID‑19 outcomes, data on
obesity and concurrent opportunistic infections were lacking, which
may have inuenced these ndings.[8,9] Other studies have shown that
HIV was not associated with increased COVID‑19 mortality when
comorbidities such as obesity were accounted for.[2,10]
With the introduction of eective antiretroviral therapy (ART),
mortality among people with HIV (PWH) has declined over the past
15 years,[6] and the life expectancy of PWH is now nearing that of the
general population.[11] Non‑communicable diseases such as obesity are
now a major threat in people ageing with HIV.[12]
It remains unclear whether HIV infection itself, or comorbidities
in PWH, have been the major driver of COVID‑19 mortality in this
patient population. Data on measured BMIs in PWH admitted to
hospital with severe COVID‑19 are lacking. We therefore aimed to
describe the true prevalence of obesity in a population of HIV‑positive
and HIV‑negative patients with severe COVID‑19 who were admitted
to medical wards during the rst COVID‑19 wave in SA.
Methods
Study design, population and setting
is was a cross‑sectional study to measure the BMIs of patients
with severe COVID‑19 admitted to the medical wards of Tygerberg
Hospital, Cape Town, over a 2‑week period from 15 to 29 May 2020,
during the rst COVID‑19 wave in SA. Tygerberg Hospital is a tertiary
hospital with 1 384 active beds, making it the largest hospital in the
Western Cape and the second‑largest hospital in SA. During the rst
COVID‑19 wave, the hospital was a designated COVID‑19 hospital
for the province.
Inclusion and exclusion criteria
All adults with a positive SARS‑CoV‑2 polymerase chain reaction
test requiring admission to the COVID wards with severe
COVID‑19 (asdened by chest radiograph inltrates and the need
for supplemental oxygen) were included. Patients admitted to the
intensive care unit (ICU) and those who were unable to stand for
height and weight measurement were excluded.
Data collection
We captured data on age, sex, and the presence of four comorbidities:
hypertension, diabetes mellitus, HIV and obesity. Multimorbidity was
dened as the presence of two or more of these chronic conditions.
Obesity was assessed by formally measuring the BMI. All patients had
weight and height measurements performed. e BMI was calculated
by dividing the weight in kilograms by the height in metres squared.
Weights and heights were measured by the same three members of the
study team, using the same protocol. A single measurement was done
in a standing position and within 24 hours of admission. e same
medical‑grade column scale (Charder Electronic Co. Ltd, Taiwan),
which is calibrated annually, was used for both height and weight
measurement. e scale was disinfected between patients. e BMI
was categorised into underweight (<18.5), normal weight (18.5 ‑ 24.9),
overweight (25 ‑ 29.9) and obesity (>30). Obesity was subclassied
into class I obesity (30 ‑ 34.9), class II obesity (35 ‑ 39.9) and class III
(formerly morbid) obesity, which was dened as a BMI ≥40. As per
routine practice at our hospital, all patients received an HIV test (HIV
chemiluminescence assay) where HIV status was not known. We also
captured data on outcome, which was dened as the need for ICU
admission or death.
Ethical considerations
Ethics approval with a waiver of informed consent for this study was
obtained from the Health Research Ethics Committee of Stellenbosch
University (ref. no. N20/04/002_COVID‑19)
Statistical analysis
Data were analysed using Stata soware, version 16.1 (StataCorp,
USA). For data that were normally distributed we used means and
standard deviations (SDs) to describe the variables. For non‑normal
data we used medians and interquartile ranges (IQRs). Chi‑square
and Fisher’s exact tests where appropriate were used to describe
signicant dierences between categorical factors. We used Student’s
t‑test to compare means of continuous variables for data that were
normally distributed, and the Mann‑Whitney U‑test for non‑normally
distributed continuous variables. Statistical signicance was set at
p<0.05 with corresponding 95% condence intervals.
Results
BMI measurements were done in 122 of 146 patients admitted during
the 14‑day study period. We excluded 24 patients because they did not
meet the study eligibility criteria or were unable to provide informed
consent for BMI testing. e mean (SD) age of the patients was 49.4
(11.2) years, and most were female (n=71; 58%). e mean (SD) height
was 1.66 (0.08) m and the mean (SD) weight 90.9 (22.7) kg (Table1).
e prevalences of HIV, hypertension and diabetes mellitus were
20% (n=24), 44% (n=54) and 38% (n=46), respectively. e median
(IQR) CD4 cell count in PWH was 321 (160 ‑ 579) cells/µL. HIV
viral load (VL) was only available for 13/24 PWH, of whom 12 had
a suppressed VL (<1 000 copies/mL). Eighty‑ve percent (n=104) of
the patients were overweight or obese. In this group, 84 (69% of the
total) were obese, of whom 17 (14% of the total) met the criteria for
class III obesity (Table1).
In PWH, 20/24 (83%) were overweight or obese; 18 (75%) met
the criteria for obesity and 5 (21%) had class III obesity. PWH had
higher mean (SD) BMIs than HIV‑negative patients, but this was not
statistically signicant (34.5 (9.1) v. 32.6 (7.0), respectively; p=0.355)
(Table2). ere was no dierence in BMI between patients with and
without hypertension or in patients with and without diabetes mellitus
(Table2).
Multimorbidity was present in 59% (n=72) of the sample population,
of whom 39 (32% of the total) had two comorbidities, 30 (25%) had
three comorbidities, and 3 (2.5%) had all four comorbidities. Only 2
patients had none of the four comorbidities. Of PWH, 22 (92%) had
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multimorbidity, with 11 (46%) having one additional comorbidity, 8
(33%) two additional comorbidities, and 3 (13%) all four comorbidities.
Only 2 PWH did not have an additional comorbidity.
Seven percent (n=9) of the study sample required ICU admission,
and 4 patients (3%) died. ere was a trend towards higher BMIs in
the ICU/death group, but this was not statistically signicant.
Discussion
In this point‑prevalence study of non‑immune COVID‑19 patients
who were admitted to hospital during the rst COVID‑19 wave in
SA, we found that the proportion of patients who met criteria for
being overweight or obese on measured BMI (85%) was far higher
than previously reported in similar settings.[2,4,8,13] e prevalence
of overweight/obesity in previous studies ranged from 19% to 39%,
with one study not reporting obesity data.[8] ese studies are likely to
have underestimated the true prevalence of obesity, since data were
reliant on medical records which may have been incomplete, BMI was
not formally measured,[4,13] or data were dependent on the clinician’s
‘impression of obesity’, which may have been inaccurate.[2] ere was
also a very high prevalence of obesity in PWH hospitalised with severe
COVID‑19, with a non‑signicant trend towards a higher mean BMI
in this population compared with HIV‑negative patients.
Obesity as a risk factor for severe infections of pandemic potential
is not unique to SARS‑CoV‑2. Obesity was a signicant risk factor for
mortality during the 2009 H1N1 (swine u) pandemic.[14] Obesity is
also reported as a risk factor for severity in Middle East respiratory
syndrome coronavirus (MERS‑CoV)[15] and dengue virus infections.
[16,17]
Adipocytes are known to become infected by SARS‑CoV‑2,[18] with
SARS‑CoV‑2 demonstrated in visceral adipocytes in postmortem
samples. ere is an abundance of angiotensin‑converting enzyme2
receptors on visceral adipocytes.[18] This direct infection of the
adipocyte is likely to promote the pro‑inammatory reaction seen
in patients with severe COVID‑19.[19] Further studies are required
to investigate whether PWH have a higher SARS‑CoV‑2 adipocyte
viral load or disproportionate cytokine response driven by adipocytes
compared with HIV‑negative patients with moderate to severe
COVID‑19. Understanding the pathogenic link between obesity and
COVID‑19 may provide important insights into the link between
obesity and other severe infections such as inuenza, and may help to
mitigate against future viruses of pandemic potential.
e present study also demonstrated a large burden of multimorbidity,
including in PWH. Multimorbidity is associated with a decline in
functional status and quality of life, and increased mortality.[20,21]
e increase in multimorbidity, and specically obesity, in PWH is
recognised as concerning.[22] Uncontrolled HIV infection is associated
with weight loss that is reversed by ART.[23] With the availability of ART,
PWH are now living longer and are reaching the age groups where
metabolic comorbidities are more likely.[21]
Our ndings suggest that the prevalence of obesity was probably
grossly underestimated in studies from our region where formal BMI
measurements were not performed. e prevalence of obesity in the
present study was also much higher than reported in a hospitalised
cohort of patients prior to the COVID pandemic,[24] as well as higher
than the background prevalence of obesity in the study setting.[7] e
results of this study further strengthen the link between obesity and
COVID‑19 severity and suggest that obesity also played a signicant
role in COVID‑19 hospital admissions in PWH.
The strengths of our study are that weights and heights were
measured, providing an accurate estimate of the BMI, and that the
study population included a high proportion of PWH. A limitation to
the study is the small sample size, which was limited by the technical
diculty of measuring the BMI in ill patients. A control group of
patients without COVID‑19 may have strengthened the study and
would have allowed for deeper inferential statistics. As this was a
single‑centre study, the ndings may not be generalisable to other
settings.
Conclusion
We found that most patients, including PWH, who were admitted
with severe COVID‑19 in the rst wave in SA over a 14‑day period
met criteria for being overweight or obese when the BMI was formally
measured. e high prevalence of obesity and multimorbidity in PWH
hospitalised with severe COVID‑19 reinforces the need for targeted
Table 1. Baseline demographic features and comorbidities
(N=122 patients)
n (%)*
Age (years), mean (SD) 49.4 (11.2)
Female 71 (58)
Weight (kg), mean (SD) 90.9 (22.7)
Height (m), mean (SD) 1.66 (0.08)
BMI (measured), mean (SD) 33.0 (7.5)
BMI distribution
Underweight (<18.5) 3 (3)
Normal weight (18.5 ‑ 24.9) 15 (12)
Overweight (25 ‑ 29.9) 20 (16)
All obese >30 84 (69)
Class I 44 (36)
Class II 23 (19)
Class III 17 (14)
Hypertension 54 (44)
Diabetes 46 (38)
HIV 24 (20)
SD = standard deviation; BMI = body mass index.
*Except where otherwise indicated.
Table2. BMI stratied by HIV status, hypertension and
diabetes mellitus
nBMI, mean (SD) p-value
HIV status 0.36
Positive 24 34.5 (9.1)
Negative 98 32.6 (7.0)
Hypertension 0.23
Ye s 54 32.0 (7.4)
No 68 33.7 (7.4)
Diabetes 0.54
Ye s 46 32.4 (8.0)
No 76 33.3 (7.1)
BMI = body mass index; SD = standard deviation.
130 AJTCCM VOL. 29 NO. 3 2023
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management of non‑communicable diseases, including obesity, in
PWH. e relationship between obesity, HIV and COVID‑19 needs
further investigation.
Declaration. CFNK is a member of the editorial board.
Acknowledgements. None.
Author contributions. AP and AGBB designed the study and AP wrote
the manuscript. AGBB, MSM, LA and RA collected the data, which were
analysed by PN. e study was supervised by JJT, GM and CFNK. All co‑
authors reviewed and approved the manuscript.
Funding.No study‑specic funding. GM was supported by the Wellcome
Trust (214321/Z/18/Z and 203135/Z/16/Z) and the South African
Research Chairs Initiative of the Department of Science and Technology
and the National Research Foundation of South Africa (grant no. 64787).
e funders had no role in the study design, data collection, data analysis,
data interpretation, or the writing of this report. e opinions, ndings
and conclusions expressed in this manuscript reect those of the authors
alone.Given that this research was funded, in part, by the Wellcome
Trust for the purposes of open access, GM has applied a CC BY public
copyright licence to any Author Accepted Manuscript version arising from
this submission.
Conicts of interest.None.
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Submitted 6 January 2023. Accepted 11 July 2023. Published 22 August 2023.
