Monitoring the tobacco use epidemic I. Overview: Optimizing measurement to facilitate change

Department of Health Behavior, School of Public Health and Health Professions, University at Buffalo, The State University of New York, 312 Kimball Tower, Buffalo, New York 14214-8028, USA.
Preventive Medicine (Impact Factor: 3.09). 10/2008; 48(1 Suppl):S4-10. DOI: 10.1016/j.ypmed.2008.08.007
Source: PubMed


This Overview paper (I of V) summarizes research work to date on monitoring the tobacco use epidemic, discusses the recommendations made at the November, 2002 National Tobacco Monitoring, Research and Evaluation Workshop sponsored by the U.S. National Cancer Institute (NCI), Centers for Disease Control and Prevention (CDC), the American Legacy Foundation, and the Robert Wood Johnson Foundation on the topic of tobacco surveillance and evaluation, and discusses the current state of affairs.
A conceptual model based on the classical infectious diseases framework/paradigm focusing on the Agent, Host, Vector and Environment is used to integrate the work presented in the four other papers that appear in this supplemental issue of Preventive Medicine.
The Agent paper (II) describes surveillance on tobacco products and biomarkers; the Host paper (III) describes surveillance on the smoker/user, or potential smoker/user; the Vector paper (IV) describes monitoring of industry activity; and the Environment paper (V) describes several key strategies for monitoring influential environmental factors. Overall, some improvements to the nation's surveillance system have been made in recent years. However, additional steps are needed to optimize measurement of tobacco use and factors influencing use in the United States.
Tobacco monitoring efforts play a vital role in combating the epidemic of addiction and disease produced by various tobacco products. The knowledge and experience gained by the tobacco use prevention and control community through this commitment to linkages of data collected in the domains of Vector and Environment, in addition to Agent and Host, could inform monitoring of a wide range of other public health issues as well, including diet and nutrition, physical activity, overweight and obesity, and substance abuse.

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    • "Our analysis has revealed, albeit with some limitations, that comparable estimates of current tobacco use can be obtained from DHS. However, future DHS in more than 85 LMICs should include more questions about previous tobacco use and quit attempts to provide data for monitoring of the global tobacco epidemic [45],[46]. Although GATS intends to include more countries [34] in future surveys, DHS cover most LMICs [30] where the majority of tobacco-attributable deaths occur [4]. "
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    ABSTRACT: Background In South and Southeast Asian countries, tobacco is consumed in diverse forms, and smoking among women is very low. We aimed to provide national estimates of prevalence and social determinants of smoking and smokeless tobacco use among men and women separately. Methods Data from Demographic and Health Surveys completed in nine countries (India, Pakistan, Nepal, Bangladesh, Maldives, Philippines, Cambodia, Indonesia, and Timor Leste) were analyzed. Current smoking or smokeless tobacco use was assessed as response “yes” to one or more of three questions, such as “Do you currently smoke cigarettes?” Weighted country-level prevalence rates for socio-economic subgroups were calculated for smoking and smokeless tobacco use. Binary logistic regression analyses were done on STATA/IC (version 10) by ‘svy’ command. Results Prevalence and type of tobacco use among men and women varied across the countries and among socio-economic sub groups. Smoking prevalence was much lower in women than men in all countries. Smoking among men was very high in Indonesia, Maldives, and Bangladesh. Smokeless tobacco (mainly chewable) was used in diverse forms, particularly in India, among both men and women. Chewing tobacco was common in Nepal, Bangladesh, Maldives, and Cambodia. Both smoking and smokeless tobacco use were associated with higher age, lower education, and poverty, but their association with place of residence and marital status was not uniform between men and women across the countries. Conclusion Policymakers should consider type of tobacco consumption and their differentials among various population subgroups to implement country-specific tobacco control policies and target the vulnerable groups. Smokeless tobacco use should also be prioritized in tobacco control efforts.
    Population Health Metrics 08/2014; 12(22). DOI:10.1186/s12963-014-0022-0 · 2.11 Impact Factor
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    • "Annual telephone surveys have been the principal tobacco control sentinel for decades (Giovino et al., 2009). However, the value of such surveys is diminishing due to respondents' increasing unwillingness to participate (Curtin, Presser, & Singer, 2005; Groves, 2006) and rising administration costs (Boland, Sweeney, Scallan, Harrington, & Staines, 2006). "
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    ABSTRACT: The Internet is revolutionizing tobacco control, but few have harnessed the Web for surveillance. We demonstrate for the first time an approach for analyzing aggregate Internet search queries that captures precise changes in population considerations about tobacco. We compared tobacco-related Google queries originating in the United States during the week of the State Children's Health Insurance Program (SCHIP) 2009 cigarette excise tax increase with a historic baseline. Specific queries were then ranked according to their relative increases while also considering approximations of changes in absolute search volume. Individual queries with the largest relative increases the week of the SCHIP tax were "cigarettes Indian reservations" 640% (95% CI, 472-918), "free cigarettes online" 557% (95% CI, 432-756), and "Indian reservations cigarettes" 542% (95% CI, 414-733), amounting to about 7,500 excess searches. By themes, the largest relative increases were tribal cigarettes 246% (95% CI, 228-265), "free" cigarettes 215% (95% CI, 191-242), and cigarette stores 176% (95% CI, 160-193), accounting for 21,000, 27,000, and 90,000 excess queries. All avoidance queries, including those aforementioned themes, relatively increased 150% (95% CI, 144-155) or 550,000 from their baseline. All cessation queries increased 46% (95% CI, 44-48), or 175,000, around SCHIP; including themes for "cold turkey" 19% (95% CI, 11-27) or 2,600, cessation products 47% (95% CI, 44-50) or 78,000, and dubious cessation approaches (e.g., hypnosis) 40% (95% CI, 33-47) or 2,300. The SCHIP tax motivated specific changes in population considerations. Our strategy can support evaluations that temporally link tobacco control measures with instantaneous population reactions, as well as serve as a springboard for traditional studies, for example, including survey questionnaire design.
    Nicotine & Tobacco Research 12/2013; 16(5). DOI:10.1093/ntr/ntt186 · 3.30 Impact Factor
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    • "However nicotine dependence is the single most consistent predictor of success following a quit attempt (Vangeli et al., 2011). Various key indicators have been defined for population level monitoring and evaluation of tobacco cessation/ control programs, which include classification of smokers by intention and attempts to quit smoking (WHO, 1998; Giovino et al., 2009). Global Adult Tobacco Survey (GATS) is a part of Global Adult Tobacco Surveillance System (GTSS) that monitors tobacco control indicators among adults of 15 years old and above. "
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    ABSTRACT: Background: Tobacco use and quit attempts are two key indicators of the Global Adult Tobacco Survey (GATS) that assess quit attempts among current as well as former tobacco users. The relevant data have inherent policy implications for tobacco cessation programme evaluation. This study aimed to review the concepts of quit attempt assessment and quantifying invalid responses considering GATS-India data. Materials and methods: GATS assessment of tobacco use and quit attempts were examined in the current literature. Two categories of invalid responses were identified by stratified analysis of the duration of last quit attempt among current users and duration of abstinence among former users. Category A included absolute invalid responses when time- frame of assessment of current tobacco use and less than former tobacco use were violated. Category B included responses that violated the unit of measurement of time. Results: Current daily use, current less than daily use and former use in GATS were imprecisely defined with overlapping of time-frame of assessment. Overall responses of 3,102 current smokers, 4,036 current smokeless users, 1,904 former smokers and 1,343 former smokeless users were analyzed to quantify invalid responses. Analysis indicated overall 21.2% (category A: 7.32%; category B: 17.7%) and 22.7% (category A: 8.05%; category B: 18.1%) invalid responses among current smokers and smokeless users respectively regarding their duration of last quit attempt. Similarly overall 6.62% (category A: 4.7%; category B: 2.3%) and 10.6% (category A: 8.6%; category B: 3.5%) invalid responses were identified among former smokers and smokeless users respectively regarding their duration of abstinence. Conclusions: High invalid responses for a single assessment are due to the imprecise definition of current use, former use and quit attempt; and failure to utilize opportunity of direct data entry interface use during the survey to validate responses instantly. Redefining tobacco use and quit attempts considering an appropriate timeframe would reduce invalid responses.
    Asian Pacific journal of cancer prevention: APJCP 11/2013; 14(11):6563-8. DOI:10.7314/APJCP.2013.14.11.6563 · 2.51 Impact Factor
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