Millions of Americans struggle with long COVID, as new data reveals how income, geography, and gender amplify its debilitating effects.

Research Letter: Prevalence of Post–COVID-19 Condition and Activity-Limiting Post–COVID-19 Condition Among Adults. Image Credit: p.ill.i / Shutterstock

In a recent study published in JAMA Network Open, researchers from the Centers for Disease Control and Prevention explored the prevalence and impact of post-coronavirus disease 2019 (COVID-19) condition (PCC), commonly known as long coronavirus disease (long COVID)  among adults in the United States (U.S.). Utilizing recent survey data, they examined how long-term symptoms following COVID-19 affect daily functioning.

Background

Post-COVID-19 condition, or long COVID, refers to persistent symptoms lasting three months or more after an initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. These symptoms can include fatigue, difficulty concentrating, and respiratory issues, which may interfere with everyday activities.

While initial studies highlighted its widespread presence, there continues to be a lack of detailed understanding regarding its overall prevalence and the degree of activity limitations it imposes. Emerging data suggest that factors such as age, gender, socioeconomic status, and geographic location may influence the likelihood and severity of PCC, but these associations have yet to be fully quantified on a national scale.

Additionally, the study acknowledges that PCC estimates are based on self-reported symptoms, which were not clinically validated. This reliance on self-reporting is a key limitation. Variations in reporting methods and definitions have contributed to inconsistencies in prevalence estimates. These gaps underscore the need for comprehensive, standardized data to better understand the burden of PCC across diverse populations. Addressing these issues is also essential for tailoring healthcare policies and resource allocation to mitigate its long-term impacts.

About the study

In this cross-sectional study, the researchers used data from the 2023 National Health Interview Survey (NHIS), a nationally representative survey of U.S. households conducted by the National Center for Health Statistics. The survey regularly gathers health information from non-institutionalized civilians, with one adult randomly selected per household to answer detailed health-related questions.

The data collection began by asking the participants about their history of COVID-19. Those with a history of infection were queried on the presence of symptoms lasting three months or more that were absent before their COVID-19 diagnosis.

Respondents with such symptoms were further asked whether they were currently experiencing those symptoms and, if so, to what extent these symptoms impacted their ability to perform daily activities compared to their pre-COVID state. Responses were categorized into “not at all,” “a little,” or “a lot” of activity limitation, with any reported limitation being classified as activity-limiting PCC.

The researchers analyzed the survey responses using statistical software designed for complex sample surveys. The results were tested for statistical significance, including linear and trend analyses for certain demographic factors. The analysis accounted for demographic variables such as sex, age, race, ethnicity, sexual orientation, family income, and urbanization. Additionally, the estimates were weighted to ensure national representation, and statistical significance was assessed. The study ensured that the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were followed to maintain clarity and reproducibility.

Overall, the survey design, incorporation of demographic diversity, and use of imputed income data for missing values allowed for a robust evaluation of PCC prevalence and its functional impacts. The researchers interpreted the results within the context of the broader population to inform health policy and interventions targeting long-term COVID-19 effects.

Results

The study found that 8.4% of U.S. adults reported experiencing PCC, while 3.6% were currently experiencing symptoms characteristic of PCC. Among these individuals, 2.3% reported symptoms severe enough to limit daily activities. Women, bisexual individuals, and adults aged 35 to 64 had the highest reported rates of PCC and activity-limiting PCC.

Economic status was also observed to influence prevalence, with higher rates of PCC observed among individuals with lower family incomes. Rural residents also reported higher rates of both PCC and activity-limiting PCC compared to urban residents.

Additionally, the findings revealed significant racial and ethnic disparities, with Hispanic adults and non-Hispanic American Indian and Alaska Native adults experiencing higher rates than other groups. Conversely, non-Hispanic Asian adults reported the lowest prevalence.

Nearly 65% of those with current PCC indicated that their symptoms limited their daily activities, with “a little” or “a lot” of interference in their ability to function. The prevalence of PCC and activity limitations showed clear trends based on urbanization, with rural populations consistently more affected.

These findings highlighted significant demographic and socioeconomic disparities in the burden of PCC, suggesting that certain populations may require targeted interventions to address the long-term impacts of COVID-19.

Conclusions

To summarize, the study revealed the substantial and uneven burden of PCC among U.S. adults, emphasizing significant activity limitations for many affected individuals. The findings revealed disparities based on sex, age, income, and geographic location, offering valuable insights for public health strategies.

However, the authors caution that the findings rely on self-reported symptoms, which may introduce reporting bias. The researchers stated that addressing these disparities will be critical in mitigating PCC’s impact and informing healthcare planning, resource allocation, and support systems tailored to the needs of affected populations.