Smoking, Nicotine, and COVID-19: Triangulation of Methods and Preregistration Are Required for Robust Causal Inference

Incidence and Determinants of COVID-19 Among People Who Smoke (2018-2021): Findings From the ITC EUREST-PLUS Spain Surveys

OBJECTIVE

To estimate the cumulative incidence of COVID-19 and its determinants among a nationally representative sample of adults from Spain who smoke.

METHODS

This is a prospective cohort study that uses data from two waves (Wave 2 in 2018 and Wave 3 in 2021) of the ITC EUREST-PLUS Spain Survey. At baseline (Wave 1 in 2016), all respondents were adults (aged ≥18) who smoked. In total, 1008 respondents participated in Wave 2, and 570 out of 888 eligible participants were followed up in Wave 3 (64.2%). We estimated the cumulative incidence and the relative risk of COVID-19 (RR) and 95% confidence intervals (CI) during follow-up using self-reported information on sociodemographic, smoking-related and health-related characteristics and identified associated factors using multivariable Poisson models with robust variance adjusted for the independent variables.

RESULTS

The overall cumulative incidence of self-reported COVID-19 was 5.9% (95% CI: 3.9-8.0%), with no significant differences between males (6.3%; 95% CI: 3.6-9.0%) and females (5.6%; 95% CI: 3.2-8.0%). After adjusting for age, sex, and educational level, COVID-19 incidence was positively associated with moderate nicotine dependence (RR: 2.37; 95% CI: 1.04-5.40) and negatively associated with having a partner who smoked (RR: 0.12; 95% CI: 0.03-0.42), and having friends but not a partner who smoked (RR: 0.28; 95% CI: 0.14-0.56).

CONCLUSION

The correlates of having had COVID-19 among people who smoke should be considered when tailoring information and targeted non-pharmacological preventive measures.

Brief interventions for smoking and alcohol associated with the COVID-19 pandemic: a population survey in England

BACKGROUND

Following the onset of the COVID-19 pandemic, in March 2020 health care delivery underwent considerable changes. It is unclear how this may have affected the delivery of Brief Interventions (BIs) for smoking and alcohol. We examined the impact of the COVID-19 pandemic on the receipt of BIs for smoking and alcohol in primary care in England and whether certain priority groups (e.g., less advantaged socioeconomic positions, or a history of a mental health condition) were differentially affected.

METHODS

We used nationally representative data from a monthly cross-sectional survey in England between 03/2014 and 06/2022. Monthly trends in the receipt of BIs for smoking and alcohol were examined using generalised additive models among adults who smoked in the past-year (weighted N = 31,390) and those using alcohol at increasing and higher risk levels (AUDIT score 38, weighted N = 22,386), respectively. Interactions were tested between social grade and the change in slope after the onset of the COVID-19 pandemic, and results reported stratified by social grade. Further logistic regression models assessed whether changes in the of receipt of BIs for smoking and alcohol, respectively, from 12/2016 to 01/2017 and 10/2020 to 06/2022 (or 03/2022 in the case of BIs for alcohol), depended on history of a mental health condition.

RESULTS

The receipt of smoking BIs declined from an average prevalence of 31.8% (95%CI 29.4-35.0) pre-March 2020 to 24.4% (95%CI 23.5-25.4) post-March 2020. The best-fitting model found that after March 2020 there was a 12-month decline before stabilising by June 2022 in social grade ABC1 at a lower level (~ 20%) and rebounding among social grade C2DE (~ 27%). Receipt of BIs for alcohol was low (overall: 4.1%, 95%CI 3.9-4.4) and the prevalence was similar pre- and post-March 2020.

CONCLUSIONS

The receipt of BIs for smoking declined following March 2020 but rebounded among priority socioeconomic groups of people who smoked. BIs for alcohol among those who use alcohol at increasing and higher risk levels were low and there was no appreciable change over time. Maintaining higher BI delivery among socioeconomic and mental health priority groups of smokers and increasing and higher risk alcohol users is important to support reductions in smoking and alcohol related inequalities.

Seroprevalence of SARS-CoV-2 antibodies among healthcare workers in Dutch hospitals after the 2020 first wave: a multicentre cross-sectional study with prospective follow-up

BACKGROUND

We aimed to estimate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence and describe its determinants and associated symptoms among unvaccinated healthcare workers (HCWs) after the first wave of the pandemic.

METHODS

HCWs from 13 Dutch hospitals were screened for antibodies against the spike protein of SARS-CoV-2 in June-July 2020 and after three months. Participants completed a retrospective questionnaire on determinants for occupational and community exposure to SARS-CoV-2 and symptoms suggestive of COVID-19 experienced since January 2020. The seroprevalence was calculated per baseline characteristic and symptom at baseline and after follow-up. Adjusted odds ratios (aOR) for seropositivity were determined using logistic regression.

RESULTS

Among 2328 HCWs, 323 (13.9%) were seropositive at enrolment, 49 of whom (15%) reported no previous symptoms suggestive of COVID-19. During follow-up, only 1% of the tested participants seroconverted. Seroprevalence was higher in younger HCWs compared to the mid-age category (aOR 1.53, 95% CI 1.07-2.18). Nurses (aOR 2.21, 95% CI 1.34-3.64) and administrative staff (aOR 1.87, 95% CI 1.02-3.43) had a higher seroprevalence than physicians. The highest seroprevalence was observed in HCWs in the emergency department (ED) (aOR 1.79, 95% CI 1.10-2.91), the lowest in HCWs in the intensive, high, or medium care units (aOR 0.47, 95% CI 0.31-0.71). Chronic respiratory disease, smoking, and having a dog were independently associated with a lower seroprevalence, while HCWs with diabetes mellitus had a higher seroprevalence. In a multivariable model containing all self-reported symptoms since January 2020, altered smell and taste, fever, general malaise/fatigue, and muscle aches were positively associated with developing antibodies, while sore throat and chills were negatively associated.

CONCLUSIONS

The SARS-CoV-2 seroprevalence in unvaccinated HCWs of 13 Dutch hospitals was 14% in June-July 2020 and remained stable after three months. A higher seroprevalence was observed in the ED and among nurses, administrative and young staff, and those with diabetes mellitus, while a lower seroprevalence was found in HCWs in intensive, high, or medium care, and those with self-reported lung disease, smokers, and dog owners. A history of altered smell or taste, fever, muscle aches and fatigue were independently associated with the presence of SARS-CoV-2 antibodies in unvaccinated HCWs.

Potential Bias in Assessing the Tobacco/Nicotine-COVID-19 Association-How to Improve Our Level of Understanding

The causative agents of COVID-19 are the variants of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) [...].

The influence of pro-vaping “gatewatchers” on the dissemination of COVID-19 misinformation on Twitter (Preprint)

Background

Objective

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Results

Conclusions

Association of smoking status with hospitalisation for COVID-19 compared with other respiratory viruses a year previous: a case-control study at a single UK National Health Service trust

Background: It is unclear whether smoking increases the risk of COVID-19 hospitalisation. We first examined the association of smoking status with hospitalisation for COVID-19 compared with hospitalisation for other respiratory viral infections a year previous. Second, we examined the concordance between smoking status recorded on the electronic health record (EHR) and the contemporaneous medical notes. Methods: This case-control study enrolled adult patients (446 cases and 211 controls) at a single National Health Service trust in London, UK. The outcome variable was type of hospitalisation (COVID-19 vs. another respiratory virus a year previous). The exposure variable was smoking status (never/former/current smoker). Logistic regression analyses adjusted for age, sex, socioeconomic position and comorbidities were performed. The study protocol and analyses were pre-registered in April 2020 on the Open Science Framework. Results: Current smokers had lower odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous (OR adj=0.55, 95% CI=0.31-0.96,  p=.04). There was no significant association among former smokers (OR adj=1.08, 95% CI=0.72-1.65,  p=.70). Smoking status recorded on the EHR (compared with the contemporaneous medical notes) was incorrectly recorded for 168 (79.6%) controls (χ 2(3)=256.5,  p=<0.001) and 60 cases (13.5%) (χ 2(3)=34.2,  p=<0.001). Conclusions: In a single UK hospital trust, current smokers had reduced odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous, although it is unclear whether this association is causal. Targeted post-discharge recording of smoking status may account for the greater EHR-medical notes concordance observed in cases compared with controls.

Association of smoking status with hospitalisation for COVID-19 compared with other respiratory viruses a year previous: a case-control study at a single UK National Health Service trust

Background: It is unclear whether smoking increases the risk of COVID-19 hospitalisation. We first examined the association of smoking status with hospitalisation for COVID-19 compared with hospitalisation for other respiratory viral infections a year previous. Second, we examined the concordance between smoking status recorded on the electronic health record (EHR) and the contemporaneous medical notes. Methods: This case-control study enrolled adult patients (446 cases and 211 controls) at a single National Health Service trust in London, UK. The outcome variable was type of hospitalisation (COVID-19 vs. another respiratory virus a year previous). The exposure variable was smoking status (never/former/current smoker). Logistic regression analyses adjusted for age, sex, socioeconomic position and comorbidities were performed. The study protocol and analyses were pre-registered in April 2020 on the Open Science Framework. Results: Current smokers had lower odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous (OR adj=0.55, 95% CI=0.31-0.96,  p=.04). There was no significant association among former smokers (OR adj=1.08, 95% CI=0.72-1.65,  p=.70). Smoking status recorded on the EHR (compared with the contemporaneous medical notes) was incorrectly recorded for 168 (79.6%) controls (χ 2(3)=256.5,  p=<0.001) and 60 cases (13.5%) (χ 2(3)=34.2,  p=<0.001). Conclusions: In a single UK hospital trust, current smokers had reduced odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous, although it is unclear whether this association is causal. Targeted post-discharge recording of smoking status may account for the greater EHR-medical notes concordance observed in cases compared with controls.