In a recent study uploaded to the medRxiv preprint* server, researchers in the USA used a combined cohort comprising 124,313 Behavioral Risk Factor Surveillance System 2022 (BRFSS) and 10,131 National Health Interview Survey (NHIS) participants to disclose the demographic aspects that alter long-COVID risk each 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 that 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 aspects for experiencing Long-COVID symptoms: Insights from two nationally representative surveys. Image Credit: Donkeyworx / Shutterstock

*Essential notice: medRxiv publishes preliminary scientific reports that usually are not peer-reviewed and, due to this fact, shouldn’t be thought to be conclusive, guide clinical practice/health-related behavior, or treated as established information.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 bunch of health symptoms that persist for months and 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 doesn’t yet exist, the World Health Organization (WHO) has defined the condition as preexisting or novel symptoms that persist for at the least three months following COVID-19-related hospital discharge. Alarmingly, between 5% and 60% of the virtually 700 million coronavirus disease 2019 (COVID-19) survivors are estimated to suffer from the condition.

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

In regards to the study

In the current 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 stays no clinically accepted diagnostic test for long-COVID, participants were asked to self-report the prevalence of any medical symptoms that persevered 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 aspects 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 due to this fact included in downstream evaluation. Of those, 26,783 (21.5%) and 1,979 (17.1%) of every cohort were found to suffer from long-COVID.

Medical data revealed that severe COVID-19 infections presented the very best ORs of subsequent long-COVID conditions. Demographic variable evaluation depicted that middle-aged individuals, women, those of Hispanic ethnicity, and people with a school 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 bottom OR amongst all tested variables.

Conclusions

The current study uses data from the Behavioral Risk Factor Surveillance System 2022 (BRFSS) and the National Health Interview Survey (NHIS) databases to disclose the chance aspects related to developing long-COVID symptoms for the primary time. Results present that between 17.1% and 21.5% of the American people suffer from long-COVID, with acute infection severity having the very best OR and Asian ethnicity the bottom amongst tested variables.

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

*Essential notice: medRxiv publishes preliminary scientific reports that usually are not peer-reviewed and, due to this fact, shouldn’t be thought to be conclusive, guide clinical practice/health-related behavior, or treated as established information.