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      Using Search Query Surveillance to Monitor Tax Avoidance and Smoking Cessation following the United States' 2009 “SCHIP” Cigarette Tax Increase

      1 , 2 , * , 3 , 4

      PLoS ONE

      Public Library of Science

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          Abstract

          Smokers can use the web to continue or quit their habit. Online vendors sell reduced or tax-free cigarettes lowering smoking costs, while health advocates use the web to promote cessation. We examined how smokers' tax avoidance and smoking cessation Internet search queries were motivated by the United States' (US) 2009 State Children's Health Insurance Program (SCHIP) federal cigarette excise tax increase and two other state specific tax increases. Google keyword searches among residents in a taxed geography (US or US state) were compared to an untaxed geography (Canada) for two years around each tax increase. Search data were normalized to a relative search volume (RSV) scale, where the highest search proportion was labeled 100 with lesser proportions scaled by how they relatively compared to the highest proportion. Changes in RSV were estimated by comparing means during and after the tax increase to means before the tax increase, across taxed and untaxed geographies. The SCHIP tax was associated with an 11.8% (95% confidence interval [95%CI], 5.7 to 17.9; p<.001) immediate increase in cessation searches; however, searches quickly abated and approximated differences from pre-tax levels in Canada during the months after the tax. Tax avoidance searches increased 27.9% (95%CI, 15.9 to 39.9; p<.001) and 5.3% (95%CI, 3.6 to 7.1; p<.001) during and in the months after the tax compared to Canada, respectively, suggesting avoidance is the more pronounced and durable response. Trends were similar for state-specific tax increases but suggest strong interactive processes across taxes. When the SCHIP tax followed Florida's tax, versus not, it promoted more cessation and avoidance searches. Efforts to combat tax avoidance and increase cessation may be enhanced by using interventions targeted and tailored to smokers' searches. Search query surveillance is a valuable real-time, free and public method, that may be generalized to other behavioral, biological, informational or psychological outcomes manifested online.

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          Most cited references 49

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          Stages and processes of self-change of smoking: toward an integrative model of change.

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            Estimates of global mortality attributable to smoking in 2000.

            Smoking is a risk factor for several diseases and has been increasing in many developing countries. Our aim was to estimate global and regional mortality in 2000 caused by smoking, including an analysis of uncertainty. Following the methods of Peto and colleagues, we used lung-cancer mortality as an indirect marker for accumulated smoking risk. Never-smoker lung-cancer mortality was estimated based on the household use of coal with poor ventilation. Relative risks were taken from the American Cancer Society Cancer Prevention Study, phase II, and the retrospective proportional mortality analysis of Liu and colleagues in China. Relative risks were corrected for confounding and extrapolation to other regions. We estimated that in 2000, 4.83 (uncertainty range 3.94-5.93) million premature deaths in the world were attributable to smoking; 2.41 (1.80-3.15) million in developing countries and 2.43 (2.13-2.78) million in industrialised countries. 3.84 million of these deaths were in men. The leading causes of death from smoking were cardiovascular diseases (1.69 million deaths), chronic obstructive pulmonary disease (0.97 million deaths), and lung cancer (0.85 million deaths). Smoking was an important cause of global mortality in 2000. In view of the expected demographic and epidemiological transitions and current smoking patterns in the developing world, the health loss due to smoking will grow even larger unless effective interventions and policies that reduce smoking among men and prevent increases among women in developing countries are implemented.
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              Digital disease detection--harnessing the Web for public health surveillance.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                16 March 2011
                : 6
                : 3
                Affiliations
                [1 ]Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
                [2 ]Center for Behavioral Epidemiology and Community Health, San Diego, California, United States of America
                [3 ]Gillings School of Global Public Health and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
                [4 ]Harvard Medical School and Children's Hospital Informatics Program, Boston, Massachusetts, United States of America
                Institute of Human Virology, United States of America
                Author notes

                Analyzed the data: JW A KMR JSB. Wrote the paper: JWA KMR JSB. Conceived and designed the study: JWA KMR JSB.

                Article
                PONE-D-10-05101
                10.1371/journal.pone.0016777
                3059206
                21436883
                Ayers et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 7
                Categories
                Research Article
                Computer Science
                Information Technology
                Medicine
                Epidemiology
                Epidemiological Methods
                Social Epidemiology
                Non-Clinical Medicine
                Health Care Policy
                Health Informatics
                Public Health
                Behavioral and Social Aspects of Health
                Tobacco Control
                Science Policy
                Science Policy and Economics
                Social and Behavioral Sciences
                Economics
                Public Finance
                Government Spending and Taxation
                Information Science
                Political Science
                Public Policy

                Uncategorized

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