Introduction Pulmonary rehabilitation (PR) programmes have been shown to reduce symptoms and improve exercise tolerance in COPD. Improving rates of attendance at PR sessions is vital to ensuring a cost-effective service. The role of seasonality in attendance at PR programmes has not previously been evaluated.
Methods Attendance rates, between 2007 and 2010, at a PR programme in one London borough were reviewed. The number of patients attending assessment and subsequent bi weekly PR sessions was examined and demographic information collected. The data were divided by season – winter months incorporating October to March and summer months, April to September. The null hypothesis that there would be no difference between attendance rates in summer months compared to winter months was tested using a Mann–Whitney U test. The attendance data were correlated, using Pearson′s product-moment correlation coefficient, with local monthly weather data, obtained from the Met Office, for temperature, hours of sunshine and rainfall over the time period.
Results In total 506 assessment appointments were made to achieve 258 attendances, an attendance rate of 51%. For assessments, there was no difference in attendance between the winter and summer months (50 and 51% respectively). For the group PR sessions, 2325 appointments were made to achieve 1613 attendances (69%). The overall attendance rate at group sessions during winter was 64% compared to 74% during summer. Non-parametric testing of the data revealed the seasonal difference to be statistically significant (p<0.05). Attendance rates show weak, positive correlation with maximum and minimum temperatures (r =+0.51, +0.44 respectively) and sunlight hours (r =+0.55), and weak negative correlation with amount of rainfall (r =−0.33).
Conclusion Attendance rates were significantly worse during winter compared to summer. This needs to be taken into account when planning PR services and in local efforts to maximise patient participation. The weak correlation between attendance and specific weather indicators suggests that weather conditions may contribute to this pattern. Confounding patient factors such as illness exacerbation and environmental issues such as transport need to be further evaluated in the context of seasonality to better understand this relationship.
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