Moderators of changes in smoking, drinking and quitting behaviour associated with the first COVID‐19 lockdown in England
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Abstract
Aim
To estimate changes in smoking, drinking and quitting behaviour from before to during the first COVID‐19 lockdown in England, and whether changes differed by age, sex or social grade.
Design
Representative cross‐sectional surveys of adults, collected monthly between August 2018 and July 2020.
Setting
England.
Participants
A total of 36 980 adults (≥ 18 years).
Measurements
Independent variables were survey month (pre‐lockdown: August–February versus lockdown months: April–July) and year (pandemic: 2019/20 versus comparator: 2018/19). Smoking outcomes were smoking prevalence, cessation, quit attempts, quit success and use of evidence‐based or remote cessation support. Drinking outcomes were high‐risk drinking prevalence, alcohol reduction attempts and use of evidence‐based or remote support. Moderators were age, sex and occupational social grade (ABC1 = more advantaged/C2DE = less advantaged).
Findings
Relative to changes during the same time period in 2018/19, lockdown was associated with significant increases in smoking prevalence [+24.7% in 2019/20 versus 0.0% in 2018/19, adjusted odds ratio (aOR) = 1.35, 95% confidence interval (CI) = 1.12–1.63] and quit attempts (+39.9 versus –22.2%, aOR = 2.48, 95% CI = 1.76–3.50) among 18–34‐year‐olds, but not older groups. Increases in cessation (+156.4 versus –12.5%, aOR = 3.08, 95% CI = 1.86–5.09) and the success rate of quit attempts (+99.2 versus +0.8%, aOR = 2.29, 95% CI = 1.31–3.98) were also observed, and did not differ significantly by age, sex or social grade. Lockdown was associated with a significant increase in high‐risk drinking prevalence among all socio‐demographic groups (+39.5 versus –7.8%, aOR = 1.80, 95% CI = 1.64–1.98), with particularly high increases among women (aOR = 2.17, 95% CI = 1.87–2.53) and social grades C2DE (aOR = 2.34, 95% CI = 2.00–2.74). Alcohol reduction attempts increased significantly among high‐risk drinkers from social grades ABC1 (aOR = 2.31, 95% CI = 1.78–3.00) but not C2DE (aOR = 1.25, 95% CI = 0.83–1.88). There were few significant changes in use of support for smoking cessation or alcohol reduction, although samples were small.
Conclusions
In England, the first COVID‐19 lockdown was associated with increased smoking prevalence among younger adults and increased high‐risk drinking prevalence among all adults. Smoking cessation activity also increased: more younger smokers made quit attempts during lockdown and more smokers quit successfully. Socio‐economic disparities in drinking behaviour were evident: high‐risk drinking increased by more among women and those from less advantaged social grades (C2DE), but the rate of reduction attempts increased only among the more advantaged social grades (ABC1).
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SciScore for 10.1101/2021.02.15.21251766: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable In order to test for moderation of associations, we ran a series of models for each outcome (fully adjusted for any relevant covariates, as described in the previous paragraph) in which the three-way interactions between the survey month (before vs. during lockdown), year (pandemic vs. comparator), and (i) age (18-34, 35-59, and ≥60 years), (ii) sex (male vs. female), and (iii) social grade (ABC1 vs. Table 2: Resources
Software and Algorithms Sentences Resources Data were analysed using SPSS v.24. SPSSsuggested: (SPSS, RRID:SCR_002865)These models … SciScore for 10.1101/2021.02.15.21251766: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable In order to test for moderation of associations, we ran a series of models for each outcome (fully adjusted for any relevant covariates, as described in the previous paragraph) in which the three-way interactions between the survey month (before vs. during lockdown), year (pandemic vs. comparator), and (i) age (18-34, 35-59, and ≥60 years), (ii) sex (male vs. female), and (iii) social grade (ABC1 vs. Table 2: Resources
Software and Algorithms Sentences Resources Data were analysed using SPSS v.24. SPSSsuggested: (SPSS, RRID:SCR_002865)These models adjusted for time trends within years (i.e. from August=1 through July=12) and across the entire analysed period (i.e. from August 2018=1 through July 2020=24). Augustsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There were also several limitations. First, despite the large overall sample, analyses for some of the outcomes (e.g. use of support) were limited to relatively small numbers of participants (i.e. smokers/high-risk drinkers who had made a quit/reduction attempt). This resulted in estimates with wide confidence intervals, and limited statistical power to detect significant interactions with age, sex, or social grade. As such, we emphasise the need to interpret results as providing no evidence of differences between these groups, rather than evidence of no differences. Secondly, it is possible that the change in modality of data collection from face-to-face (before lockdown) to telephone interviews (during lockdown) may have contributed to some of the changes in smoking and drinking behaviour we observed. However, the diagnostic analyses we undertook comparing the face-to-face and telephone data, combined with previous studies showing a high degree of comparability between face-to-face and telephone interviews (24,25), suggest it is reasonable to compare data collected via the two methods. Finally, we did not model changes within the lockdown period, so our analyses cannot conclusively tell us whether immediate changes after lockdown was implemented were sustained, decayed, or even increased over the four months of lockdown. We plan to conduct more sophisticated interrupted time series modelling when sufficient post-lockdown data points are available. However, we provide descri...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
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- No protocol registration statement was detected.
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