We measure seasonal variation in enrolments, total clinical visits, visits per enrolment, and treatment outcome (7-day abstinence at 6 month follow-up) from 2015 to 2018 in a large (n=85,869) clinical cohort from 454 clinics across Ontario, Canada. We model seasonality using harmonic logistic and negative binomial regression. For individual-level outcomes, we adjust for variables, selected a priori, known to be associated with treatment use or outcomes. Data are nearly complete for 3 outcomes, but 6m abstinence is missing for 45% of participants. We use multiple imputation to adjust for missing data.
All four outcomes showed significant seasonal variation (all p<0.001). Total enrolments and visits were 20-25% higher in January-April than in June-September. Visits per enrolment varied slightly, with lowest levels from May-July. Abstinence at 6 months was lowest among individuals enrolled from February-May and highest for those enrolled from July-November, with an absolute peak-trough difference of 4.3% (95% CI = 3.2%-5.5%).
There is meaningful seasonal variation in demand for, and outcomes of, smoking cessation treatment. Climate and weather may be indirectly responsible. Seasonal differences underscore the general importance of contextual factors in smoking cessation, may be useful in program promotion, and may explain some variability in outcomes in evaluation and research.
Demand for tobacco cessation treatment and clinical outcomes vary seasonally. This underscores the importance of context in substance-related problems, and implies that some variability in research and evaluation results may be due to the time of year data were collected. Promotion efforts might usefully consider seasonal effects to smooth out demand and possibly improve outcomes.
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