Post-COVID-19 condition (PCC), also known as long COVID, is a phenomenon where individuals continue to experience COVID-19 symptoms for a minimum of four weeks after initial infection. The condition is estimated to impact 20-40% of people who have contracted COVID-19, with a higher prevalence among unvaccinated or hospitalized individuals. PCC is characterized by a range of respiratory, cardiovascular, metabolic, gastrointestinal, neurological, and psychiatric manifestations, which can have a significant impact on daily functioning.
In this prospective cohort study, the association between adherence to a healthy lifestyle prior to infection and the risk of developing PCC was investigated. The study participants, who were female nurses from the Nurses’ Health Study II cohort, reported their preinfection lifestyle habits in 2015 and 2017. Healthy lifestyle factors included: a healthy body mass index (BMI between 18.5-24.9), never smoking, moderate to vigorous physical activity for at least 150 minutes per week, moderate alcohol consumption (5 to 15 g/d), a high-quality diet and adequate sleep (7 to 9 h/d).
The findings of the study of 1981 participants who tested positive for SARS-CoV-2 from April 2020 and November 2021 showed a preinfection healthy lifestyle was inversely associated with the risk of PCC. Those with five or six healthy lifestyle factors had half the risk of PCC compared to those who did not adhere to any healthy lifestyle factors.
In conclusion, study results indicate adherence to a healthy lifestyle prior to SARS-CoV-2 infection was associated with a substantially lower risk of PCC. Further research is needed to explore whether lifestyle interventions can reduce risk of PCC or mitigate its symptoms among those with PCC or other postinfection syndromes.
The study was published online in JAMA Internal Medicine.
ODHA audiocast Episodes 38 and 48 of Conversations with Dr. Glogauer and Kim Ivan have discussed this condition. Additional keynotes and resources are included with the audiocast episodes to layer learning. Listen to Episodes 38 and 48 .
