Abstract:
Background Long COVID (LC) is a complex and multisystemic condition marked by a diverse range of symptoms, yet its associated risk factors remain poorly defined.
Methods Leveraging data from the 2022 Behavioral Risk Factor Surveillance System (BRFSS) and National Health Interview Survey (NHIS), both representative of the United States population, this study aimed to identify demographic characteristics associated with LC. The sample was restricted to individuals aged 18 years and older who reported a positive COVID-19 test or doctor’s diagnosis. We performed a descriptive analysis comparing characteristics between participants with and without LC. Furthermore, we developed multivariate logistic regression models on demographic covariates that would have been valid at the time of the COVID-19 infection.
Results Among the 124,313 individuals in BRFSS and 10,131 in the NHIS reporting either a positive test or doctor’s diagnosis for COVID-19 (Table), 26,783 (21.5%) in BRFSS and 1,797 (17.1%) in NHIS reported LC. In the multivariate logistic regression model, we found middle age, female gender, Hispanic ethnicity, lack of a college degree, and residence in non-metropolitan areas associated with higher risk of LC. Notably, the initial severity of acute COVID-19 was strongly associated with LC risk. In contrast, significantly lower ORs were reported for Non-Hispanic Asian and Black Americans compared to Non-Hispanic White.
Conclusions In the United States, there is marked variation in the risk of LC by demographic factors and initial infection severity. Further research is needed to understand the underlying cause of these observations.
Source: Risk factors for experiencing Long-COVID symptoms: Insights from two nationally representative surveys.