Pack size, reported cigarette smoking rates, and public health.

Kozlowski, L T

doi:10.2105/ajph.76.11.1337

Cited by 29 publications

(15 citation statements)

References 8 publications

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“…42,44 Self-reported CPD are often rounded to a preferred number, 9–12 usually multiples of 5 or 10, and most often, 20 CPD. When self-reporting CPD, smokers may not recall an exact amount, and report a rounded estimation, often based on pack size.…”

Section: Discussionmentioning

confidence: 99%

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The Importance of Filter Collection for Accurate Measurement of Cigarette Smoking

Saddleson¹,

Wileyto²,

Darwar³

et al. 2017

tobacco reg sci

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Objectives We examined the impact of cigarette filter collection on reports of cigarettes per day (CPD) versus self-reported CPD and to assess the utility of a pre-intervention baseline period in smoking studies. Methods Using baseline data from 522 non-treatment seeking smokers, we assessed differences in self-reported CPD via phone screen (CPD PS) and during baseline (CPD BL). We analyzed self-reported cigarette measures to predict carbon monoxide (CO), a measure of smoke exposure. Results On average, CPD PS was 2.8 CPD more than CPD BL, and reporting multiples of 10 were more often found in CPD PS compared with CPD BL (54.7% vs17.2%, respectively). CPD BL was more strongly associated with CO than self-report CPD. Number of cigarettes smoked today, time since last cigarette, and nicotine dependence were significantly associated with CO. Conclusions CPD BL using filter collection is a more accurate measure of cigarette consumption than self-report, which may have implications for assessment of nicotine dependence. When feasible, studies should include a pre-intervention baseline period for comparison data with study outcomes. In addition to CPD BL, studies should assess time since last cigarette and the number of cigarettes smoked today when using CO as a biological measure of smoke exposure.

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Section: Discussionmentioning

confidence: 99%

“…Digit bias or, heaping, which is a clustering of reported estimates around rounded values 6–8 is common and has been well documented in the literature. 1,9–15 …”

mentioning

confidence: 99%

The Importance of Filter Collection for Accurate Measurement of Cigarette Smoking

Saddleson¹,

Wileyto²,

Darwar³

et al. 2017

tobacco reg sci

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“…Although regression analyses may favor the non-dichotomous HSI over the FTQ methods (In that there is a mathematical upper limit on correlations involving dichotomous variables when the proportions are unequal; Ghiselli et al, 1981), this handicap may not be large and especially in samples of very heavy smokers-such as sample three-the FTQ categorizations may be too broad, and information may be obscured. The HSI scheme allowed the typical digit bias infiuence of pack size (Kozlowski, 1986) to exert itself and provided greater discrimination among smokers than the FTQ scoring method. Nonetheless, the FTQ has proved a valuable outcome predictor, and one has to be careful not to 'throw the baby out with the bath water' (Pinto et al, 1987).…”

Section: Sample Threementioning

confidence: 99%

Measuring the Heaviness of Smoking: using self‐reported time to the first cigarette of the day and number of cigarettes smoked per day

Heatherton

Kozlowski

Frecker³

et al. 1989

British Journal of Addiction

1,164

826

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Two simple self-report measures have been used to assess the heaviness of smoking, 'number of cigarettes per day' (CPD) and 'time to the first cigarette of the day' (TTF). Little attention, however, has been given to the precise method of scoring this information. Using biochemical indicators of heaviness of smoking (alveolar carbon monoxide and cotinine), we explore the optimum data transformations for regression analysis and categorical analysis. We suggest a four category scoring scheme for both time to the first cigarette of the day (less than or equal to 5, 6-30, 31-60 and 61+ min) and average daily consumption of cigarettes (1-10, 11-20, 21-30, 31+ cigarettes) as the most powerful and practical categorical scoring of these variables. Due to possible ceiling effects on biochemical measures, we suggest using logarithmic transformations of CPD or TTF for regression or correlation analyses.

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“…The available smoking prevalence data was from 1997 to 2008, while the closest available cigarette price data to 2004 was from 2008 [34]. Cigarette price per pack does not accurately represent the price per cigarette because the number of cigarettes per pack (from 10 to 50) varies for different regions of the world [35, 36]. The highest smoking prevalence was in Nauru (47%), Russia (44%), and Austria (41%), while the lowest smoking prevalence was in Suriname (1%), Ethiopia (3%), and Ghana (4%) (Table S1).…”

Section: Methodsmentioning

confidence: 99%

Association of Carcinogenic Polycyclic Aromatic Hydrocarbon Emissions and Smoking with Lung Cancer Mortality Rates on a Global Scale

Motorykin

Matzke

Waters

et al. 2013

Environ. Sci. Technol.

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The objective of this research was to investigate the relationship between lung cancer mortality rates, carcinogenic polycyclic aromatic hydrocarbons (PAHs) emissions, and smoking on a global scale, as well as for different socioeconomic country groups. The estimated lung cancer deaths per 100,000 people (ED100000) and age standardized lung cancer death rate per 100,000 people (ASDR100000) in 2004 were regressed on PAH emissions in benzo[a]pyrene equivalence (BaPeq), smoking prevalence, cigarette price, gross domestic product per capita, percentage of people with diabetes, and average body mass index using simple and multiple linear regression for 136 countries. Using stepwise multiple linear regression, a statistically significant positive linear relationship was found between loge(ED100000) and loge(BaPeq) emissions for high (p-value<0.01) and for the combination of upper middle and high (p-value<0.05) socioeconomic country groups. A similar relationship was found between loge(ASDR100000) and loge(BaPeq) emissions for the combination of upper middle and high (p-value<0.01) socioeconomic country groups. Conversely, for loge(ED100000) and loge(ASDR100000), smoking prevalence was the only significant independent variable in the low socioeconomic country group (p-value<0.001). These results suggest that reducing BaPeq emissions in the U.S., Canada, Australia, France, Germany, Brazil, South Africa, Poland, Mexico, and Malaysia could reduce ED100000, while reducing smoking prevalence in Democratic People’s Republic of Korea, Nepal, Mongolia, Cambodia, and Bangladesh could significantly reduce the ED100000 and ASDR100000.

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Pack size, reported cigarette smoking rates, and public health.

Cited by 29 publications

References 8 publications

The Importance of Filter Collection for Accurate Measurement of Cigarette Smoking

The Importance of Filter Collection for Accurate Measurement of Cigarette Smoking

Measuring the Heaviness of Smoking: using self‐reported time to the first cigarette of the day and number of cigarettes smoked per day

Association of Carcinogenic Polycyclic Aromatic Hydrocarbon Emissions and Smoking with Lung Cancer Mortality Rates on a Global Scale

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