Overweight/obesity as the potentially most important lifestyle factor associated with signs of pneumonia in COVID-19

  • Published: November 18, 2020



The occurrence of pneumonia separates severe cases of COVID-19 from the majority of cases with mild disease. However, the factors determining whether or not pneumonia develops remain to be fully uncovered. We therefore explored the associations of several lifestyle factors with signs of pneumonia in COVID-19.


Between May and July 2020, we conducted an online survey of 201 adults in Germany who had recently gone through COVID-19, predominantly as outpatients. Of these, 165 had a PCR-based diagnosis and 36 had a retrospective diagnosis by antibody testing. The survey covered demographic information, eight lifestyle factors, comorbidities and medication use. We defined the main outcome as the presence vs. the absence of signs of pneumonia, represented by dyspnea, the requirement for oxygen therapy or intubation.


Signs of pneumonia occurred in 39 of the 165 individuals with a PCR-based diagnosis of COVID-19 (23.6%). Among the lifestyle factors examined, only overweight/obesity was associated with signs of pneumonia (odds ratio 2.68 (1.29–5.59) p = 0.008). The observed association remained significant after multivariate adjustment, with BMI as a metric variable, and also after including the antibody-positive individuals into the analysis.


This exploratory study finds an association of overweight/obesity with signs of pneumonia in COVID-19. This finding suggests that a signal proportional to body fat mass, such as the hormone leptin, impairs the body’s ability to clear SARS-CoV-2 before pneumonia develops. This hypothesis concurs with previous work and should be investigated further to possibly reduce the proportion of severe cases of COVID-19.

For More Information: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0237799

Mapping the human genetic architecture of COVID-19

  1. COVID-19 Host Genetics Initiative, Nature (2021)


The genetic makeup of an individual contributes to susceptibility and response to viral infection. While environmental, clinical and social factors play a role in exposure to SARS-CoV-2 and COVID-19 disease severity1,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. We describe the results of three genome-wide association meta-analyses comprised of up to 49,562 COVID-19 patients from 46 studies across 19 countries. We reported 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian Randomization analyses support a causal role for smoking and body mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19, with unprecedented speed, was made possible by the community of human genetic researchers coming together to prioritize sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

For More Information: https://www.nature.com/articles/s41586-021-03767-x

Body mass index and severity/fatality from coronavirus disease 2019: A nationwide epidemiological study in Korea

  1. Authors: In Sook Kang , Kyoung Ae Kong Published: June 22, 2021


Obesity has been reported as a risk factor for severe coronavirus disease 2019 (COVID-19) in recent studies. However, the relationship between body mass index (BMI) and COVID-19 severity and fatality are unclear.

Research design and methods

This study included 4,141 COVID-19 patients who were released from isolation or had died as of April 30, 2020. This nationwide data was provided by the Korean Centers for Disease Control and Prevention Agency. BMI was categorized as follows; < 18.5 kg/m2, 18.5–22.9 kg/m2, 23.0–24.9 kg/m2, 25.0–29.9 kg/m2, and ≥ 30 kg/m2. We defined a fatal illness if the patient had died.


Among participants, those with a BMI of 18.5–22.9 kg/m2 were the most common (42.0%), followed by 25.0–29.9 kg/m2 (24.4%), 23.0–24.9 kg/m2 (24.3%), ≥ 30 kg/m2 (4.7%), and < 18.5 kg/m2 (4.6%). In addition, 1,654 (41.2%) were men and 3.04% were fatalities. Multivariable analysis showed that age, male sex, BMI < 18.5 kg/m2, BMI ≥ 25 kg/m2, diabetes mellitus, chronic kidney disease, cancer, and dementia were independent risk factors for fatal illness. In particular, BMI < 18.5 kg/m2 (odds ratio [OR] 3.97, 95% CI 1.77–8.92), 25.0–29.9 kg/m2 (2.43, 1.32–4.47), and ≥ 30 kg/m2 (4.32, 1.37–13.61) were found to have higher ORs than the BMI of 23.0–24.9 kg/m2 (reference). There was no significant difference between those with a BMI of 18.5–22.9 kg/m2 (1.59, 0.88–2.89) and 23.0–24.9 kg/m2.


This study demonstrated a non-linear (U-shaped) relationship between BMI and fatal illness. Subjects with a BMI of < 18.5 kg/m2 and those with a BMI ≥ 25 kg/m2 had a high risk of fatal illness. Maintaining a healthy weight is important not only to prevent chronic cardiometabolic diseases, but also to improve the outcome of COVID-19.

For More Information: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0253640

Associations between body-mass index and COVID-19 severity in 6·9 million people in England: a prospective, community-based, cohort study

  1. Authors: Min Gao, MSc *, Carmen Piernas, PhD  , Nerys M Astbury, PhD, Prof Julia Hippisley-Cox, FRCPProf Stephen O’Rahilly, FRS, Prof Paul Aveyard, FRCGP 



Obesity is a major risk factor for adverse outcomes after infection with SARS-CoV-2. We aimed to examine this association, including interactions with demographic and behavioural characteristics, type 2 diabetes, and other health conditions.


In this prospective, community-based, cohort study, we used de-identified patient-level data from the QResearch database of general practices in England, UK. We extracted data for patients aged 20 years and older who were registered at a practice eligible for inclusion in the QResearch database between Jan 24, 2020 (date of the first recorded infection in the UK) and April 30, 2020, and with available data on BMI. Data extracted included demographic, clinical, clinical values linked with Public Health England’s database of positive SARS-CoV-2 test results, and death certificates from the Office of National Statistics. Outcomes, as a proxy measure of severe COVID-19, were admission to hospital, admission to an intensive care unit (ICU), and death due to COVID-19. We used Cox proportional hazard models to estimate the risk of severe COVID-19, sequentially adjusting for demographic characteristics, behavioral factors, and comorbidities.


Among 6 910 695 eligible individuals (mean BMI 26·78 kg/m2 [SD 5·59]), 13 503 (0·20%) were admitted to hospital, 1601 (0·02%) to an ICU, and 5479 (0·08%) died after a positive test for SARS-CoV-2. We found J-shaped associations between BMI and admission to hospital due to COVID-19 (adjusted hazard ratio [HR] per kg/m2 from the nadir at BMI of 23 kg/m2 of 1·05 [95% CI 1·05–1·05]) and death (1·04 [1·04–1·05]), and a linear association across the whole BMI range with ICU admission (1·10 [1·09–1·10]). We found a significant interaction between BMI and age and ethnicity, with higher HR per kg/m2 above BMI 23 kg/m2 for younger people (adjusted HR per kg/m2 above BMI 23 kg/m2 for hospital admission 1·09 [95% CI 1·08–1·10] in 20–39 years age group vs 80–100 years group 1·01 [1·00–1·02]) and Black people than White people (1·07 [1·06–1·08] vs 1·04 [1·04–1·05]). The risk of admission to hospital and ICU due to COVID-19 associated with unit increase in BMI was slightly lower in people with type 2 diabetes, hypertension, and cardiovascular disease than in those without these morbidities.

For More Information: https://www.thelancet.com/journals/landia/article/PIIS2213-8587(21)00089-9/fulltext

Lack of antibodies against seasonal coronavirus OC43 nucleocapsid protein identifies patients at risk of critical COVID-19

Authors: MartinDugasa1TanjaGrote-Westrickb1UtaMerledMichaelaFontenaylmAndreas E.KremerhFrankHansesijRichardVollenbergcEvaLorentzenbShilpaTiwari-BecklerdJérômeDucheminlSyrineEllouzelMarcelVetterhJuliaFürsthPhilippSchusterkTobiasBrixaClaudia M.DenkingerfgCarstenMüller-TidoweHartmutSchmidtcJoachimKühnb1


Does prior infection with seasonal human coronavirus OC43 protect against critical COVID-19?•

Findings: In an international multi-center study inpatients without anti-HCoV OC43 NP antibodies had an increased risk of critical disease.•

Meaning: Prior infections with seasonal HCoV OC43 have a protective effect against critical COVID-19.



The vast majority of COVID-19 patients experience a mild disease. However, a minority suffers from critical disease with substantial morbidity and mortality.


To identify individuals at risk of critical COVID-19, the relevance of a seroreactivity against seasonal human coronaviruses was analyzed.


We conducted a multi-center non-interventional study comprising 296 patients with confirmed SARS-CoV-2 infections from four tertiary care referral centers in Germany and France. The ICU group comprised more males, whereas the outpatient group contained a higher percentage of females. For each patient, the serum or plasma sample obtained closest after symptom onset was examined by immunoblot regarding IgG antibodies against the nucleocapsid protein (NP) of HCoV 229E, NL63, OC43 and HKU1.


Median age was 60 years (range 18-96). Patients with critical disease (n=106) had significantly lower levels of anti-HCoV OC43 nucleocapsid protein (NP)-specific antibodies compared to other COVID-19 inpatients (p=0.007). In multivariate analysis (adjusted for age, sex and BMI), OC43 negative inpatients had an increased risk of critical disease (adjusted odds ratio (AOR) 2.68 [95% CI 1.09 – 7.05]), higher than the risk by increased age or BMI, and lower than the risk by male sex. A risk stratification based on sex and OC43 serostatus was derived from this analysis.


Our results suggest that prior infections with seasonal human coronaviruses can protect against a severe course of COVID-19. Therefore, anti-OC43 antibodies should be measured for COVID-19 inpatients and considered as part of the risk assessment for each patient. Hence, we expect individuals tested negative for anti-OC43 antibodies to particularly benefit from vaccination against SARS-CoV-2, especially with other risk factors prevailing.

For More Information: https://www.sciencedirect.com/science/article/pii/S1386653221001141

Attributes and predictors of long COVID

  1. Authors: Carole H. SudreBenjamin MurrayClaire J. Steves


Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called ‘long COVID’, are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app1. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76–4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.


COVID-19 can manifest a wide severity spectrum from asymptomatic to fatal forms2. A further source of heterogeneity is symptom duration. Hospitalized patients are well recognized to have lasting dyspnea and fatigue in particular3, yet such individuals constitute only a small proportion of symptomatic COVID-19 (ref. 4). Few studies capture symptoms prospectively in the general population to ascertain with accuracy the duration of illness and the prevalence of long-lasting symptoms.

Here, we report a prospective observational cohort study of COVID-19 symptoms in 4,182 users of the COVID Symptom Study who reported testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and started logging on the app when feeling physically normal, enabling accurate determination of symptom onset (Methods)5,6. Symptom duration in these individuals was compared with that in age-, sex- and body mass index (BMI)-matched symptomatic controls who tested negative for COVID-19.

We then compared users with symptoms persisting over 28 d (LC28) to users with shorter duration of symptoms, that is, less than 10 d (short COVID). Our previous findings that clusters of symptoms predicted the need for acute respiratory support7 led us to hypothesize that persistent symptomatology in COVID-19 (long COVID) is associated with early symptom patterns that could be used for prediction.

For More Information: https://www.nature.com/articles/s41591-021-01292-y