Can We Trust National Smoking Prevalence Figures? Discrepancies Between Biochemically Assessed and Self-Reported Smoking Rates in Three Countries

West, Robert; Zatoński, Witold; Przewoźniak, Krzysztof; Jarvis, Martin J.

doi:10.1158/1055-9965.epi-06-0679

Cited by 128 publications

(110 citation statements)

References 16 publications

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“…Most studies implement different criteria and methods to measure tobacco use [21][22][23]. As a potential limitation of GATS, the recall bias due to self-reported data on tobacco use should be mentioned.…”

Section: Study Limitations and Strengthsmentioning

confidence: 99%

Determinants of heavy smoking: Results from the global adult tobacco survey in Poland (2009–2010)

Kaleta¹,

Makowiec-Dąbrowska²,

Dziankowska-Zaborszczyk³

et al. 2012

International Journal of Occupational Medicine and Environmental Health

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Objective: The aim of current analysis was to identify socio-demographic correlates of heavy smoking. Materials and Methods: Global Adult Tobacco Survey (GATS), a nationally representative household study was implemented in Poland between 2009 and 2010. We used data on representative sample of 1915 adults, age 25 years and older. The Odds Ratios (OR) and 95% Confidence Intervals (CI) for heavy smoking to the broad number of variables including age, age at smoking onset, education, occupational classification, living conditions, place of residence, place of residence at age about 14 years, awareness of smoking health consequences were tested in logistic regression model. Results: Among daily smokers the rate of heavy smokers was 63% in males and 45% in females (p < 0.001). The present study indicated that three characteristics: age, early age at smoking onset and lack of awareness of smoking health consequences were significantly associated with heavy smoking among both genders. Significantly higher risk of heavy smoking was observed among the 50-59 years of age population compared to the youngest group. The heavy smoking rate was highest among males who started smoking under age 14 years (OR = 3.1; 95% CI: 1.4-6.7; p < 0.001) and females that started smoking at age 14-17 years (OR = 2.3; 95% CI: 1.5-3.5; p < 0.0001) compared to those who started smoking at age 21 years or older. Heavy smoking was significantly correlated to lack of awareness of adverse health consequences of smoking (OR = 1.5; 95% CI: 1.1-2.03; p < 0.01 and OR = 1.5; 95% CI: 1.0-2.2; p < 0.01 for men and women, respectively) compared to aware respondents. Conclusions: These outcomes should be taken into account while developing tobacco control measures. Among other things, educational interventions to increase knowledge of adverse tobacco health effects should be widely implemented.

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Section: Study Limitations and Strengthsmentioning

confidence: 99%

Determinants of heavy smoking: Results from the global adult tobacco survey in Poland (2009–2010)

Kaleta¹,

Makowiec-Dąbrowska²,

Dziankowska-Zaborszczyk³

et al. 2012

International Journal of Occupational Medicine and Environmental Health

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“…This study highlights the importance of how assessments are conducted, particularly given concerns that traditional surveillance systems may underestimate smoking (Substance Abuse and Mental Health Services Administration, 2006;West, W., Przewozniak, & Jarvis, 2007). In research, this scale could be investigated to determine if young adults' schemas of what constitutes a smoker may be related to smoking initiation, maintenance of a low level of smoking over time, and lack of intent to quit smoking ).…”

Section: Implications For Research and Practicementioning

confidence: 99%

The Development and Validation of a Scale Assessing Individual Schemas Used in Classifying a Smoker: Implications for Research and Practice

Berg¹,

Nehl²,

Sterling³

et al. 2011

Nicotine & Tobacco Research

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Introduction: Half of college students who have smoked in the past month do not consider themselves smokers. Understanding one's schema of smokers is important, as it might relate to smoking behavior. Thus, we aimed to develop a scale assessing how young adults classify smokers and establish reliability and validity of the scale. Methods:Of 24,055 students at six Southeast colleges recruited to complete an online survey, 4,840 (20.1%) responded, with complete smoking and scale development data from 3,863.Results: The Classifying a Smoker Scale consisted of 10 items derived from prior research. Factor analysis extracted a single factor accounting for 40.00% of score variance (eigenvalue = 5.52). Higher scores (range 10-70) indicate stricter criteria in classifying a smoker. The scale yielded a Cronbach's alpha of .91. Current smoking (past 30-day) prevalence was 22.8%. Higher Classifying a Smoker Scale scores (p = .001) were significant predictors of current smoking, controlling for sociodemographics. Higher scores were related to being nondaily versus daily smokers (p = .009), readiness to quit in the next month (p = .04), greater perceived smoking prevalence (p = .007), not identifying as smokers (p < .001), less perceived harm of smoking (p < .001), greater concern about smoking health risks (p = .01), and less favorable attitudes toward smoking restrictions (p < .001). Among current smokers, higher scores were related to greater smoking frequency (p = .02), not identifying as smokers (p < .001), and less perceived harm of smoking (p < .001), controlling for sociodemographics. Conclusion:This scale, demonstrating good psychometric properties, highlights potential intervention targets for prevention and cessation, as it relates to smoking, risk perception, and interest in quitting.

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“…It is also likely that these self-reported figures represent an underestimate of actual alcohol and tobacco consumption. 23,24 Although a significant proportion of patients attending the access centre have risk factors for oral cancer, few oral cancers will present clinically, as patients are predominantly under the age of 45 years. 20 The value of oral screening and provision of information about self-examination for these individuals may therefore be limited, unless the trend of increasing prevalence of oral cancer in younger patients continues.…”

Section: Discussionmentioning

confidence: 99%

Patient awareness of oral cancer health advice in a dental access centre: a mixed methods study

Williams

Bethea

2011

Br Dent J

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Can We Trust National Smoking Prevalence Figures? Discrepancies Between Biochemically Assessed and Self-Reported Smoking Rates in Three Countries

Cited by 128 publications

References 16 publications

Determinants of heavy smoking: Results from the global adult tobacco survey in Poland (2009–2010)

Determinants of heavy smoking: Results from the global adult tobacco survey in Poland (2009–2010)

The Development and Validation of a Scale Assessing Individual Schemas Used in Classifying a Smoker: Implications for Research and Practice

Patient awareness of oral cancer health advice in a dental access centre: a mixed methods study

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