| Summary: | Introduction
Tobacco control policies intend to impact long-term indicators of population health via reducing the prevalence of tobacco use (POTU). Interrupted time series (ITS) analysis gives opportunities in analyzing routinely collected longitudinal data to see the effects of interventions.
Methods
ARIMA models were applied to routinely collected data on POTU in Ukraine. Dependent series reflected POTU in 2000-2017 collected by the national statistics service. Independent series reflected the adoption of tobacco control policies including tobacco taxation, smoke-free policies, and tobacco pack health warnings. Independent variables had ordinal format to characterize the level of adopted policy and binary format to denote the year of policy introduction.
Results
All the considered population groups were responsive to tobacco taxation. POTU showed delayed decreases next year after the new level of tobacco taxation was achieved. This POTU change per average tax increase reached -1% for all, almost -2% for men and -0.4% for women. Sharp declines in tobacco affordability caused immediate reactions of similar size in all groups which were more obvious in men and more affluent groups. Introduction of new health warnings (stronger textual in late 2006 and pictorials in 2012) caused immediate reactions more expressed among men and poorer population groups. Smoke-free policies introduced in 2006 and 2012 did not reveal associated changes in POTU which could be masked by contemporary policies.
Conclusions
ITS analysis of POTU data in Ukraine shows the predominant impact of tobacco taxation on all population groups and the impact of health warnings on men and poorer smokers.
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