Who's at greater risk for long-COVID? New study sheds light on vulnerable demographics

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In a recent study uploaded to the medRxiv preprint* server, researchers in the United States used a combined cohort comprising 124,313 Behavioral Risk Factor Surveillance System 2022 (BRFSS) and 10,131 National Health Interview Survey (NHIS) participants to reveal the demographic factors that alter long-COVID risk both descriptively and using multivariate logistic regression. Results indicated that 21.5% of the BRFSS cohort and 17.1% of the NHIS cohort suffer from the condition. Risk was highest in those who experienced severe COVID-19 infections, with age (middle age), sex (female), ethnicity (Hispanic), education level (pre-college), and area of residence significantly increasing long-COVID-associated risk.

Study: Risk factors for experiencing Long-COVID symptoms: Insights from two nationally representative surveys. Image Credit: Donkeyworx / ShutterstockStudy: Risk factors for experiencing Long-COVID symptoms: Insights from two nationally representative surveys. Image Credit: Donkeyworx / Shutterstock

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Are some people more vulnerable to long-COVID than others?

‘Long-COVID,’ also called ‘long-haul COVID,’ ‘post-COVID, and clinically ‘post-acute sequelae of COVID-19 (PASC)’ is an umbrella term for a group of health symptoms that persist for months or even years following initial infection recovery. Symptoms including post-exertional malaise, fatigue, muscle and chest pain, and cognitive dysfunction characterize it.

While a universal definition for the disease does not yet exist, the World Health Organization (WHO) has defined the condition as preexisting or novel symptoms that persist for at least three months following COVID-19-related hospital discharge. Alarmingly, between 5% and 60% of the almost 700 million coronavirus disease 2019 (COVID-19) survivors are estimated to suffer from the condition.

While reports on disease prevalence are numerous, investigations into the medical and demographic variables influencing long-COVID risk remain lacking.

About the study

In the present study, researchers used a combined cohort derived from the Behavioral Risk Factor Surveillance System 2022 (BRFSS) and the National Health Interview Survey (NHIS), two nationally representative United States (US) medical databases. Study inclusion criteria comprised age (above 18) and clinically confirmed COVID-19 infections.

Since there hitherto remains no clinically accepted diagnostic test for long-COVID, participants were asked to self-report the prevalence of any medical symptoms that persisted or arose following COVID-19 infection recovery. Data collection included medical COVID-19 infection severity records (exclusive to the NHIS cohort) and demographic variables.

Statistical analyses included within- and between-group estimates of long-COVID prevalence and risk associations, as revealed by chi-squared and multivariant logistic regression models, respectively. Risk factors were identified and hierarchically categorized using computed odds ratios (ORs).

 

Study findings

The BRFSS and NHIS presented 124,313 and 10,131 individuals who met the study inclusion criteria and were therefore included in downstream analysis. Of these, 26,783 (21.5%) and 1,979 (17.1%) of each cohort were found to suffer from long-COVID.

Medical data revealed that severe COVID-19 infections presented the highest ORs of subsequent long-COVID conditions. Demographic variable analysis depicted that middle-aged individuals, women, those of Hispanic ethnicity, and those with a college degree were at higher risk than the remaining population. While not as strong, associations between residential development and long-COVID risk were further revealed.

Asian ethnicity was found to have the lowest OR among all tested variables.

Conclusions

The present study uses data from the Behavioral Risk Factor Surveillance System 2022 (BRFSS) and the National Health Interview Survey (NHIS) databases to reveal the risk factors associated with developing long-COVID symptoms for the first time. Results present that between 17.1% and 21.5% of the American people suffer from long-COVID, with acute infection severity having the highest OR and Asian ethnicity the lowest among tested variables.

Age (24-35), sex (female), Hispanic ethnicity, lack of a college degree, and living in an underdeveloped residential locality were all variables identified as increasing long-COVID risk. While these findings are generalizable only in the American context, they present the first step in identifying and combatting long-COVID-associated risks, thereby significantly improving the quality of life of patients suffering from COVID-19.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
  • Preliminary scientific report. Yixuan Wu, Mitsuaki Sawano, Yilun Wu, Rishi M. Shah, Pamela Bishop, Akiko Iwasaki, Harlan M. Krumholz. Risk factors for experiencing Long-COVID symptoms: Insights from two nationally representative surveys (2024). medRxiv 2024.01.12.24301170, DOI – 10.1101/2024.01.12.24301170, https://www.medrxiv.org/content/10.1101/2024.01.12.24301170v1
Hugo Francisco de Souza

Written by

Hugo Francisco de Souza

Hugo Francisco de Souza is a scientific writer based in Bangalore, Karnataka, India. His academic passions lie in biogeography, evolutionary biology, and herpetology. He is currently pursuing his Ph.D. from the Centre for Ecological Sciences, Indian Institute of Science, where he studies the origins, dispersal, and speciation of wetland-associated snakes. Hugo has received, amongst others, the DST-INSPIRE fellowship for his doctoral research and the Gold Medal from Pondicherry University for academic excellence during his Masters. His research has been published in high-impact peer-reviewed journals, including PLOS Neglected Tropical Diseases and Systematic Biology. When not working or writing, Hugo can be found consuming copious amounts of anime and manga, composing and making music with his bass guitar, shredding trails on his MTB, playing video games (he prefers the term ‘gaming’), or tinkering with all things tech.

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