New research uncovers how excess weight not only worsens COVID-19 outcomes but also heightens the chances of contracting the virus in the first place.

Study: Obesity and age are transmission risk factors for SARS-CoV-2 infection among exposed individuals. Image Credit: Halfpoint / Shutterstock

In a recent study published in the journal PNAS Nexus, researchers investigated the risk associations between severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection susceptibility and risk factors (notably obesity, age, and comorbidities). They leveraged an extensive dataset comprising 687,813 patients (72,613 SARS-CoV-2 positive for exposure) from the electronic medical records (EMRs) of the Mass General Brigham’s (MGB) database. The study focused on patients tested between March 2020 and January 25, 2021, to avoid potential biases introduced by vaccination, which was not widespread during this period. They found that obesity significantly increased the risk of productive coronavirus disease 2019 (COVID-19) in patients exposed to SARS-CoV-2.

These findings add to existing literature demonstrating the enhanced severity of COVID-19 pathology in obese patients, thereby highlighting weight management as a critical preventive measure in the war against the causative agent of the most horrific human pandemic in recent times. However, the study’s authors caution that these findings should be interpreted in the context of certain limitations, including reliance on self-reported exposure data, which may introduce subjectivity and potential inaccuracies in EMRs due to medical transcription errors.

Background

The coronavirus disease 2019 (COVID-19) is the most devasting pandemic in modern human history, having infected more than 775 million individuals and claimed over 7 million lives since its discovery in late 2019. Its causative agent, the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) virus, is spread by exposure to infected individuals, their body fluids, or articles they have recently contacted, making social distancing critical in limiting the disease’s transmission, especially during the early days of the pandemic.

The subsequent development and widespread dissemination of anti-SARS-CoV-2 vaccines have played a pivotal role in controlling the transmission and severity of COVID-19. However, the rapid rate of SARS-CoV-2 evolution has resulted in numerous strains with varying responses to conventional vaccines, making identifying intrinsic risk factors essential for further curbing disease spread.

Previous research has focused on predispositions that influence the pathology and severity of COVID-19 infections, revealing that old age, cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), obesity, and hypertension can significantly worsen COVID-19 outcomes. Unfortunately, knowledge of predispositions affecting the susceptibility to SARS-CoV-2 infections following exposure remains limited.

About the study

The present study aims to assess the rate of SARS-CoV-2 transmission to individuals following suspected viral exposure and its association with potential risk factors, particularly abnormal weight (obesity), hypertension, and age. Data for the study was acquired from the Mass General Brigham (MGB) COVID-19 Data Mart, which is comprised of electronic medical records (EMRs) from across the United States (US). The study was geographically restricted to Massachusetts and temporally limited to patients tested before January 25, 2021, to minimize confounding effects from vaccination. To reduce the impacts of confounding variables, the study was temporally and geographically restricted to Massachusetts between March 2020 and 25 January 2021 (before widespread vaccination in the state).

Data collection included demographic, socioeconomic, and medical history data (obtained from MGB records). Data was segmented via Massachusetts County (n =14) to account for any geographical heterogeneity. ‘Exposure’ was self-reported by patients and was defined as suspected contact with an infected individual or a proxy of the same. ‘Susceptibility’ was defined as medically confirmed (via polymerase chain reactions [PCRs]) COVID-19 infections that occurred following exposure. While the study relied on self-reported exposure data, which introduces some subjectivity, the use of PCR-confirmed cases strengthens the reliability of the findings. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to diagnose obesity (body mass index [BMI] > 30), hypertension, and comorbidities.

To evaluate risk associations between COVID-19 susceptibility and potential predispositions, logistic regression models were used to compute odds ratios (ORs), correcting for confounding variables (age, sex, T2DM, hypertension, and county). These variables were independently fitted to the model to evaluate their relative effects.

Study findings

After excluding participants with incomplete data, 72,613 patients (58.8% female) were included in the present analysis. Age-class stratification revealed patients in the 40-64 yr group to predominate the dataset (39.7%) followed by >64 yrs (30%), 20-39 yrs (24.7%), and 13-19 (3.5%). Pediatric patients comprised 2.2%. Obesity was prevalent across all age groups, with the highest rates observed in middle-aged adults (40-64 years). 33.7% (n = 24,438) of individuals were found to be obese during the study period.

“We had a comparable distribution of obesity across ages tested (64 years: 30.77%) with the highest rates in middle-aged adults. We observed similar rates of obesity in both sexes (women—34.2% and men—32.9%). Our population had varying rates of obesity across races with low prevalence in Asians (15.4%) and increased prevalence in Black (46.3%) and Hispanic (43.8%) individuals.”

Results of the logistic model revealed that 18,447 out of the 72,613 exposed patients developed COVID-19 infections. Susceptibility by age ranged from 22.8% (>64 yrs) to 28% (13-19 yrs), with men and women expressing susceptibility of 26.4% and 24.6%, respectively. Since all these results are statistically indistinguishable, these findings suggest that age and sex are not intrinsic risk factors in SARS-CoV-2 susceptibility. However, obesity was identified as a significant predictor of COVID-19 infection, with an odds ratio (OR) of 1.34, indicating a 34% higher likelihood of infection in obese individuals. Stratification by age, sex, and county revealed that obesity remained a significant risk factor across all groups.

In contrast, obese exposed patients were substantially more likely to be COVID-19 positive than their non-obese counterparts (OR = 1.34, indicating a 34% higher likelihood of COVID-19 infection). Demographic evaluations (age, sex, county) did not alter these findings, revealing obesity to consistently be a significant predictor of COVID-19 infections across age, sex, and geography.

Conclusions

The present study highlights obesity as a risk factor associated with a 34% higher likelihood of SARS-CoV-2 susceptibility than non-obese individuals, highlighting the utility of weight management programs as effective preventive measures against COVID-19 transmission. The study’s authors note that while obesity is a significant risk factor, the self-reported nature of exposure data and potential EMR inaccuracies are limitations that should be considered when interpreting the results. Additionally, future research could focus on mechanistic studies to explore shared signaling pathways in obese individuals, which may lead to the identification of drug targets to reduce SARS-CoV-2 infectivity.

“Future mechanistic studies evaluating shared signaling pathways in obese individuals could lead to the identification of drug targets that can be used to assail the infectivity of SARS-CoV-2.”