OP53 Defining the Long-Term Trend in a Public Health Intervention Study: A Cautionary Tale. (17th September 2012) - Salway, R; Gilmore, A; Sims, M
Abstract : Background: Numerous studies have reported on the impact of comprehensive smoke-free laws on population health. Many early studies have ignored the potential effect of the long-term trend of the health outcome, and when included, subsequent studies have focused on either linear or non-linear trends. However, the choice of appropriate trend is not always straightforward. We illustrate this by investigating the short-term impact of smoke-free legislation in England, introduced on 1st July 2007, on myocardial infarction mortality. Methods: We investigate the impact of the legislation using weekly counts of all cases aged 18 years or older residing in England with a primary cause of death of a myocardial infarction (ICD–10 I21) between July 2002 to December 2010 (providing 5 years pre-legislative and 3 years and 6 months post-legislative data). We compare a number of models based on an interrupted time series design with a quasi-Poisson generalised additive model that adjusts for seasonality and long-term trends. Results: Myocardial infarction mortality shows a marked decline over the study period. We identify two competing models. The first shows evidence of a complex interaction between the introduction of smoke-free legislation and the long-term trend. We observe an initial statistically significant reduction in mortality (–8.5%, 95% CI –11.1% to –5.8%) coupled with a change in the long-term trend from a reduction of 4% over a six month period to a reduction of 3.5%. The second model fits a nonlinear trend and shows no significant smoke-free effect. Both models offer an almost identical fit. Conclusion: Investigating small effects in the presence of a pronounced long-term trend is complicated by the limitations of the available data. In particular, it is not clear whether we observe a gradual change in the long term trend or a discrete effect directly attributable to the legislation. The two models have near-identical fitted values and GCV scores, but have very different interpretation. We conclude that the data alone are insufficient to distinguish between the two models and warn that overly-simplistic analyses in such situations may result in misleading conclusions.