Current smoking and SARS-CoV-2 infection: findings from the Italian cross-sectional EPICOVID19 internet-based survey.

Background: Several studies reported a low prevalence of current smoking among hospitalized COVID-19 cases however, no definitive conclusions can be drawn. Objective: We investigated the association of tobacco smoke exposure with the nasopharyngeal swab (NPS) test result for SARS-CoV-2 infection and the disease severity accounting for possible confounders. Methods: The cross-sectional EPICOVID19 web-based survey was performed in an Italian population of 198,822 adults who filled in an online questionnaire between April 13 and June 2, 2020. For the present study we analyzed 6857 individuals with known NPS test result. The association of smoking status and the dose-response relationship with the positivity to NPS test and infection severity were analyzed using logistic and multinomial regression models adjusting for socio-demographic, clinical and behavioral characteristics. Results: Out of the 6857 individuals, 63.2% had never smoked, 21.3% were former and 15.5% were current smokers. Compared to non-smokers, current smokers were younger, more educated, less affected by chronic diseases, reported less frequently COVID-like symptoms, were less hospitalized and tested for COVID-19. In multivariate analysis current smokers had almost halved odds of a positive NPS test (OR 0.54, 95% CI 0.45-0.65) compared to non-smokers. We also found a dose-dependent relationship with tobacco smoke: mild smokers (OR 0.76, 95% CI 0.55-1.05), moderate (OR 0.56, 95% CI 0.42-0.73) and heavy smokers (OR 0.38, 95% CI 0.27-0.53). This inverse association persisted also when considering the severity of the infection. Conclusions: Current smoking was negatively associated with SARS-CoV-2 infection with a dose-dependent relation. Ad-hoc experimental studies are needed to elucidate the mechanisms underlying this association. Clinical Trial: ClinicalTrials.gov ABSTRACT Background Several studies reported a low prevalence of current smoking among hospitalized COVID-19 cases however, no definitive conclusions can be drawn. Objective We investigated the association of tobacco smoke exposure with the nasopharyngeal swab (NPS) test result for SARS-CoV-2 infection and the disease severity accounting for possible confounders. multivariate analysis current smokers had almost halved odds of a positive NPS test (OR 0.54, 95% CI 0.45-0.65) compared to non-smokers. We also found a dose-dependent relationship with tobacco smoke: mild smokers (OR 0.76, 95% CI 0.55-1.05), moderate (OR 0.56, 95% CI 0.42-0.73) and heavy smokers (OR 0.38, 95% CI 0.27-0.53). This inverse association persisted also when considering the severity of the infection. Current smokers had a statistically significant lower probability of having asymptomatic (OR 0.50 95%CI 0.27-0.92), mild (OR 0.65 95%CI 0.53-0.81), and severe infection (OR 0.27 95%CI 0.17-0.42) compared to never smokers. Current smoking was negatively associated with SARS-CoV-2 infection with a dose-dependent relation. Ad-hoc experimental studies are needed to elucidate the mechanisms underlying this association.


Table of Contents
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ABSTRACT Background
Several studies reported a low prevalence of current smoking among hospitalized COVID-19 cases however, no definitive conclusions can be drawn.

Objective
We investigated the association of tobacco smoke exposure with the nasopharyngeal swab (NPS) test result for SARS-CoV-2 infection and the disease severity accounting for possible confounders.

Methods
The nationwide self-administered cross-sectional EPICOVID19 web-based survey was performed in an Italian population of 198,822 voluntary adults who filled in an online questionnaire between April 13 and June 2, 2020. For the present study, we analyzed 6857 individuals with known NPS test result. The associations of smoking status and the doseresponse relationship with the positivity to NPS test and infection severity were calculated as odds ratios with 95% Confidence Intervals (OR, 95%CI) by means of analyzed using logistic and multinomial regression models adjusting for socio-demographic, clinical, and behavioral characteristics.  [20][21] Nevertheless, possible explanations for these findings could be due to biases in the available data. In fact, considering the emergency of the epidemic, it has been suggested that the smoking status and smoking history (included the duration, the quantity or the time from possible smoking cessation) of patients could have not been accurately recorded or some patients were unable to report their smoking habits, leading to a misclassification of smoking status. Moreover, the ascertainment of smoking exposure has not been supported by the use of objective biomarkers [19][20], or again, smokers may be taking medications or having behaviors, inducing some protection against COVID-19 [CITATION Leu \l 1040 ].

Study design, setting and population
The study population was derived from the EPICOVID19 national internet-based survey [24] conducted using a cross-sectional research design in a self-selected sample of adult volunteers living in Italy during the lockdown in March-May 2020 (during this same period the total confirmed COVID-19 infected cases in Italy were 233,515 [25]). The study procedures were described elsewhere [24]. Briefly, the link to the web-based survey was implemented using the EUSurvey management tool, uploaded, and shared from April 13 to participants for the present analysis (Figure 1).

Data Collection and variables definition
The EPICOVID19 study was established as a collaborative project of a working group including epidemiologists, physicians expert in infectious diseases, biostatisticians, and

Smoke exposure
A number of questions on present and past smoking habit were asked in the questionnaire.
These included smoking status defined as never smoked (persons who had never smoked regularly or had smoked less than 100 cigarettes), former smokers (regular smokers who have smoked at least 100 cigarettes during the lifetime and did not smoke at the time of the survey), and current smokers [ CITATION htt6 \l 1040 ]. In order to explore the doseresponse effect, we created a variable by collapsing data on smoking status and number of years of smoke as follows: former smokers (categorized for smoking duration ≤ 10 years or > 10 years) and current smokers grouped in mild smoker (<10 cigarettes/day for <15 years), moderate smokers (< 10 cigarettes/day for more than 15 years or >10 cigarettes/day for less than 15 years), and heavy smoker (>10 cigarettes/day for more than 15 years).

Main outcomes
We investigated two different outcomes: 1) positive result to the NPS molecular test; and 2) SARS-CoV-2 infection severity by combining information on NPS test, symptoms and hospitalization for COVID-19 defined as follows: 

Statistical analysis
The continuous variables were represented as mean and standard deviation (SD) and the categorical variables as counts and percentages. Continuous and categorical data according to smoking status were compared using one-way analysis of variance (ANOVA) and chi-square test respectively. To explore the association between smoking habit and positive versus negative NPS test results and 4-level infection severity dependent variable (no infection, asymptomatic infection, mild infection, and severe infection), logisticregression and multinomial-regression models were used to estimate the odds ratios (ORs) and 95% Confidence Intervals (CIs). A first model (model 1) was only adjusted for age and sex. In the fully adjusted model (model 2) we further controlled for variables considered potential confounders as education, occupation, area of residence, heart diseases, lung diseases, hypertension, metabolic diseases, contact with suspected/confirmed COVID-19 cases, living area, crowding index, and living with at risk co-habitants. Models were applied considering separately the smoking status and the dose-response relationship as exposures. We explored our data for potential effect modification by sex, age, and education by adding cross-product terms of these variables to the regression models. When heterogeneity was present, stratum-specific estimates were evaluated. Three sensitivity analyses were performed in order to evaluate whether the effect of smoking on SARS-CoV-2 infection was primarily due to the current amount of cigarettes smoked and/or to the smoking history during lifespan. In the first sensitivity analysis, we categorized current smokers based on years of smoking classified as ≤15, 15-30, and >30 years. Second sensitivity analysis explored the association between the number of cigarettes smoked categorized as less than 10 cigarettes/day or more than 10 cigarettes/day and NPT test.
Third sensitivity analysis repeated the analysis by calculating the pack-years of smoking.
We assigned a median number of cigarettes/day to each current smoking category (5 for 'less than 10 cig/day'; 15 for '10 to 20 cig/day'; 25 for 'more than 20 cig/day'), then we multiplied the number of packs per day (1 pack=20 cigarettes) by the number of years the person had smoked, and finally we tertilized the variable. All statistical analyses were performed using Stata 15.0 version (StataCorp LP, College station, Texas, USA), and a twosided P-value <.05 was considered statistically significant.

Characteristics of participants
The participants' characteristics according to smoking status are summarized in Table 1  They lived less frequently with co-habitants at risk, after the lockdown more frequently went out and used public transport, contacted less frequently the emergency number and were more afraid about the infection for themselves and for family members than no smokers ( Table 3). 16 In comparison with never-and current smokers, former smokers were significantly older, retired, more affected by chronic conditions as heart diseases and hypertension, assumed more frequently aspirin, drugs for lowering cholesterol, oncological and thyroid drugs. They reported less frequently COVID-19 like symptoms and were more likely to be hospitalized for COVID-19.   *Adjusted for age, sex, education, occupation, area of residence, heart diseases, lung diseases, hypertension, metabolic and oncological diseases, contact with COVID-19 cases, living area, crowding index, and living with at risk co-habitants.. Mild smokers (<10 cigarettes/day and <15 yrs); Moderate smokers (< 10 cigarettes/day for more than 15 years or >10 cigarettes/day for less than 15 years); Heavy smokers (>10 cigarettes/day for more than 5 yrs).  (Figure 3, Supplementary table 4).

Principal findings
The present study evaluated the association between smoking habit and the odds for positive SARS-CoV-2 molecular test and infection severity in an Italian adult population recruited on-line during the first national lockdown. We found that current smoking was associated with a significant risk reduction of having a positive SARS-CoV-2 test and with a severe infection in a dose-response relationship even after taking into account for all the available confounding factors.
In our sample, the percentage of positive tests was 24 inpatients and outpatients showed that, in both groups active smokers were less infected by COVID-19 when compared with the general population [33].
When we analysed the association between smoking habits and SARS-CoV-2 infection severity, we found that active smokers were less likely to develop severe infection. colleagues reported that, although the risk for current smokers to be hospitalized was 25 lower than among non-smokers, current smokers were more likely to have an adverse outcome during the hospital admission [19]. In a population of over 2.4 million UK users of the Zoe COVID-19 Symptom Study app, Hopkinson found for current smokers a statistically significant OR of 1.14 of self-reporting a triad of three symptoms (fever, persistent cough, and shortness of breath) that, although to some extent attributable also to constipation or normal flu, the authors identified as suggestive of COVID-19. On the contrary, when analysing the stronger endpoint of positive SARS-CoV-2 test, they observed a lower smoking rate (7.4% among positive vs 9.3% among negative) leading to a reduced adjusted OR of 0.7 that they considered not generalizable to their general population, due to the physiological difference between tested and non-tested individuals [34]. In their systematic review, Vardavas and Nikitara concluded that smoking was associated with disease progression and increased adverse outcomes in COVID-19 positive patients [35], even though, in both meta-analyses, the authors acknowledged that their studies were conducted with limited availability of data, the included studies came mostly from hospital contexts, and their analyses were not adjusted for confounding factors. Similar methodological limitations have been reported in the meta-analysis conducted by Patanavanich who found smoking as a risk factor for progression of COVID-19 [36] conversely, Lippi and Henry did not observe any association [37].
Our findings, which highlight the existence of a negative association of current smoking with SARS-CoV-2 infection and its severity, drive the focus to possible suggestive explanations. Since ACE2 is necessary for infection of cells by SARS-CoV-2 [38], the risk of contracting a SARS-CoV-2 severe infection, as well as the risk of a disadvantageous clinical outcome, could be influenced by the number of available ACE2 receptors and by the receptor-ligand interaction of ACE2 and SARS-CoV-2 S protein [39]. As concerns the number of ACE2 receptors, nicotine would seem to have a controversial role. Recent evidence indicates that a higher number of receptors are expressed in smoker's lung tissues [40]. On the other hand, it has been suggested that nicotine downregulates the expression and/or the activity of ACE2 [41]. However, a better disease outcome was associated to an overexpression of ACE2, able to compensate the negative effects of the ACE2 downregulation induced by the cell entry of SARS-CoV-2 [42]. Moreover, a direct role of nicotine on disrupting spike protein glycosylation, could in turn directly affect the ability of SARS-CoV-2 to infect [43]. A recent study performed on a mice model proposes the modulation of the reninangiotensin pathways as therapeutic target to protect individuals with SARS from developing acute severe lung failure and acute respiratory distress syndrome [44]. In addition to that, nicotine might exert an anti-inflammatory effect by protecting against the 'cytokine-storm syndrome' responsible of severe SARS-CoV-2 infections [45] [21]. It has been also hypothesized that the cytokine storm, with excessive production of pro-inflammatory molecules, could possibly more easily be triggered in individual who never smoked rather than in smokers, whose immune system is more tolerant and less reactive [46].
Another potential mechanism of action involves nitric oxide (NO) produced during smoking that, due to its reported antiviral effect, might inhibit the virus replication/entry in the cells [21] [47].
Alternatively, from the behavioural perspective, we cannot exclude that smokers, considering themselves at higher risk of developing the disease, were more careful than never smokers in adopting preventative measures, such as physical distancing, hand hygiene, covering coughs, wearing masks when appropriate, having fewer socialrelationship, etc. [48].

Limitations and Strengths
The present study has some limitations. Firstly, because of the observational nature of 27 the study and the cross-sectional design, we cannot infer any causal relationship between smoking habit and COVID-19. In addition, a misclassification of the outcome of severity may exist, since some cases (although numerically limited) might have worsened their conditions a few days after the survey with a subsequent potential distortion of measures of association. Secondly, smoking habit was self-reported therefore recall bias might have led to misclassification of the exposure. Thirdly, the sample was self-selected and not entirely representative of the Italian population because restricted to relatively younger, females, highly educated, and relatively healthy participants, therefore results should be treated with caution when generalized to different populations [49]. Moreover, the low percentage of asymptomatic subjects in our sample may have influenced the evaluation of smoking habit effect on asymptomatic NPS positive subjects. Nevertheless, in a previous study smokers were proportionally represented in asymptomatic patients [50]. Lastly, although we controlled for several potential confounders, we cannot completely rule out the possibility of residual confounding due to unmeasured factors (e.g. passive smoking). Our study has also several strengths. The first one was that evaluating the effect of smoking was the primary goal of the work. The presence in our study sample of subjects from a general population with negative NPS test allows an internal control group (NPS negative individuals). The web-survey reached a large sample of adults with an acceptable geographical coverage reflecting the distribution of SARS-CoV-2 infection in the study period[ CITATION Sel \l 1040 ] and a proportion of smokers that is almost overlapped with the prevalence of current smoking in the Italian population. Finall, and differently from previous published works, we recorded factors not easy to obtain from medical records of inpatients such as the exhaustive details regarding smoking habits (distinguishing between former, active, or never-smokers) and those suspected to play a role of confounders in the observed association, i.e. the socioeconomic status, clinical, 28 behavioural, and environmental characteristics.

Conclusions
In summary, we are aware that our findings must be carefully evaluated. This article takes as its premise the need to strengthen prevention actions of the most powerful human carcinogen known, which is also a heavy risk factor for many non-communicable diseases [51] and for disease progression in COVID-19 patients. However, we are now Title: Figure 2. Adjusted odds ratios° and relative 95%CI for smoking status and intensity and duration (N=6,857).
Legend: °Age, sex, education, occupation, area of residence, heart diseases, lung diseases, hypertension, metabolic and oncological diseases, contact with confirmed or suspected COVID-19 cases, living area, crowding index, and living with at risk cohabitants. Mild smokers (<10 cig/day and <15 yrs); Moderate smokers (< 10 cigarettes/ day for more than 15 years or >10 cigarettes/day for less than 15 years); Heavy smokers (>10 cigarettes/day for more than 5 yrs). Dots and vertical lines indicate ORs and 95%CI.
Title: Figure 3. Adjusted odds ratios* for positive SARS-CoV-2 test by smoke-related variables (intensity, duration, and pack-years of smoking) (N=6,857) Legend: °Age, sex, education, occupation, area of residence, heart diseases, lung diseases, hypertension, metabolic and oncological diseases, contact with COVID-19 cases, living area, crowding index, and living with at risk co-habitants.