Early in the COVID-19 pandemic, clinicians noticed that some patients with pre-existing medical conditions were at higher risk of severe illness and death. Since then, many observational studies confirmed that people with diabetes, asthma, or cardiovascular disease had a substantially higher risk of COVID-19-related complications and death1,2. Such studies typically use hospital patient records to study relationships between individual risk factors, like age and sex, and long-term health outcomes. However, studies using hospital record data revealed that smokers may be underrepresented among patients with COVID-19, as highlighted by a recent review study of publications reporting smoking prevalence and clinical outcomes in patients diagnosed with COVID-193. The review highlights that only a single study out of 15 research articles examined had reported a prevalence of smokers among patients with COVID-19 that resembles the smoking prevalence of the general population. Such findings, raises the question of whether a smoker’s paradox exists with the COVID-19 pandemic. The smoker’s paradox refers to the observational phenomenon of smokers exhibiting improved prognosis and decreased short-term mortality, following cardiovascular events. This idea has been mostly debunked now as a bias in the analysis of observational data and smoking is not considered to be a causative factor that improves health outcomes4. So, what considerations should be taken when interpreting health records of patients in order understand whether smokers fare worse COVID-19 outcomes than non-smokers?
Questioning Data Quality and Biases in Patient Record Data
Smoking is associated with many immediate and long-term health consequences, and initiates disease promoting mechanism in cardiopulmonary tissues. A low representation of smokers in hospitalized COVID-19 patients may be due to biases in patient record data collection. A small percentage of people who perceive stigma associated with smoker status may actually conceal smoker status during a primary care visit5. Furthermore, smoker screening often does not include questions about smokeless tobacco, electronic cigarette use, and second-hand smoke use, despite the rise in popularity in electronic nicotine delivery systems and cigarette alternatives6. Standardization and improved tobacco-related electronic health record questionnaires may begin to address the question of how much tobacco smoke a person is exposed to by including questions that cover sources of exposure, quantity of use, and duration of exposure. Collecting patient data that covers a larger range of exposure possibilities including having someone else in the home that smokers, or individual behaviors of switching from traditional cigarettes to electronic cigarettes, smoking cessation patterns, and years of use may provide better insight into how smoking behaviors influence health outcomes. In the context of the COVID-19 pandemic, smokers’ status is difficult to ascertain in patients who are intubated, sedated, and unresponsive. Closely tracking individual smoker status over time is helpful in those situations when a patient’s care plan should include tobacco withdrawal symptom management.
Smoking directly influences cardiovascular and respiratory health outcomes and using hospital data to derive associations with COVID-19 health outcomes is prone to confounding bias, reverse causation, and inappropriate adjustments in analysis models. In the future, it be possible to use human biomarkers to uncover the specific health effects from smoking. This might include correlating urinary levels of nicotine and cotinine to understand the burden of different tobacco products. For now, research using animal models to assess the health effects of traditional smoking and electronic cigarettes provide insight into the short- and long-term consequences of smoking and elucidates the biochemical processes that exacerbate disease including tissue repair processes, inflammation, and oxidative stress. Understanding the mechanistic processes involved in the exacerbation of COVID-19 disease among smokers may ultimately help identify biomarkers of disease progression and pharmacological treatments for vulnerable populations.
- Williamson EJ, Walker AJ, Bhaskaran K, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584(7821):430-436. doi:1038/s41586-020-2521-4
- Why lighting up and COVID-19 don’t mix. American Heart Association News. https://www.heart.org/en/news/2020/05/05/why-lighting-up-and-covid-19-dont-mix#:~:text=Studies%20from%20Wuhan%2C%20China%2C%20where,%2C%20compared%20to%20non%2Dsmokers.
- Usman MS, Siddiqi TJ, Khan MS, et al. Is there a smoker’s paradox in COVID-19? BMJ EBM. 2021;26(6):279-284. doi:1136/bmjebm-2020-111492
- Doi SA, Islam N, Sulaiman K, et al. Demystifying Smoker’s Paradox: A Propensity Score–Weighted Analysis in Patients Hospitalized With Acute Heart Failure. JAHA. 2019;8(23). https://www.ahajournals.org/doi/10.1161/JAHA.119.013056
- Stuber J, Galea S. Who conceals their smoking status from their health care provider? Nicotine & Tobacco Research. 2009;11(3):303-307. doi:1093/ntr/ntn024
- LeLaurin JH, Theis RP, Thompson LA, et al. Tobacco-Related Counseling and Documentation in Adolescent Primary Care Practice: Challenges and Opportunities. Nicotine & Tobacco Research. 2020;22(6):1023-1029. doi:1093/ntr/ntz076
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