Finally a Smoking Gun? Compensating Differentials and the Introduction of Smoking Bans

Using the staggered introduction of smoking bans in the German hospitality industry over 2007–2008, I find a robust 2.4 percent decline in the daily earnings of workers in bars and restaurants associated with the most comprehensive smoking ban. This effect is unlikely to be driven by a decline in hospitality revenues or hours worked but is consistent with a simple model of compensating differentials. (JEL I12, I18, J22, J31, J81, L83)

Comparison of Levels of Three Tobacco Smoke Exposure Biomarkers in Children of Smokers

Objectives: Cotinine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and N-oxides are biomarkers of tobacco smoke exposure (TSE) used to assess short- and longer-term TSE. The objective of this study was to assess the associations between these TSE biomarkers, sociodemographics, parental smoking, and child TSE patterns among 0–17-year-olds. Methods: A convenience sample of 179 pediatric patients (mean (SD) age = 7.9 (4.3) years) who lived with ≥1 smoker and who had parental assessments completed and urine samples analyzed for the three TSE biomarkers of interest were included. Biomarker levels were log-transformed, univariate regression models were built and Pearson correlations were assessed. Results: In total, 100% of children had detectable levels of cotinine and >96% had detectable NNAL and N-oxide levels. The geometric means of cotinine, NNAL, and N-oxide levels were 10.1 ng/mL, 25.3 pg/mL, and 22.9 pg/mL, respectively. The mean (SD) number of daily cigarettes smoked by parents was 10.6 (6.0) cigarettes. Child age negatively correlated with urinary cotinine (r = −0.202, p = 0.007) and log NNAL levels (r = −0.275, p < 0.001). The highest log-cotinine levels were in children who were younger, of African American race, and whose parents had a lower education, an annual income ≤USD15,000, and no smoking bans. The highest log-NNAL and N-oxide levels were in children whose parents had a lower education, had no smoking bans, and were around higher numbers of cigarettes. Conclusion: Children of smokers who were younger, African American, and had no smoking bans had the highest TSE biomarker levels. Targeted interventions are needed to reduce TSE levels among high-risk children.

The Role of Ethnicity and Nativity in the Correspondence between Subjective and Objective Measures of In-Home Smoking

Background: Studies are needed to understand the association between self-reported home smoking bans and objective measures of in-home smoking according to smokers’ ethnicity/nativity.Methods: Data came from a trial that used air particle monitors to reduce children’s secondhand smoke exposure in smokers’ households (N = 251). Linear regressions modeled (a) full home smoking bans by ethnicity/nativity, and (b) objectively measured in-home smoking events, predicted by main and interaction effects of self-reported home smoking bans and ethnicity/nativity.Results: Among smokers reporting &lt; a full ban, U.S.-born and foreign-born Latinos had fewer in-home smoking events than US-born Whites (p&lt;0.001). Participants who reported a full smoking ban had a similar frequency of smoking events regardless of ethnicity/nativity.Discussion: Self-reported home smoking bans can be used as a proxy for in-home smoking. Establishing smoking bans in the households of US-born White smokers has the largest impact on potential exposure compared to other ethnic/nativity groups.

Complete Home Smoking Ban Survey Analysis: An Opportunity to Improve Health Equity Among Sexual Minority Adults in California, USA

Introduction: Increasing the proportion of adults living in smoke-free homes is a US Healthy People 2020 objective. Complete home smoking bans are associated with higher odds of smoking cessation attempts and cessation duration. Sexual minority adults have disproportionality higher rates of smoking. This study investigates correlates of having a complete home smoking ban among sexual minority adults in California. Methods: Secondary data analyses of the California Behavioral Risk Factor Surveillance System (CA BRFSS), 2014-2016. The CA BRFSS telephone survey of adults was conducted in English and Spanish and used random digit dial for landline and cell numbers. Weighted descriptive, bivariate, and multivariable logistic regression analyses were stratified by sexual orientation and biological sex.Results: Sexual minority adults in California had a lower prevalence of complete home smoking bans (Female 76.2%; Male 75.7%), higher prevalence of current cigarette smoking (Female 23.3%; Male 17.4%) and of e-cigarette use (Female 5.8%; Male 6.4%) than their straight counterparts. Sexual minorities that currently smoke “everyday” (Female AOR 0.26, 95% CI 0.11-0.63; Male AOR 0.24, 95% CI 0.01-0.56) or “somedays” (Female AOR 0.28, 95% CI 0.090.90) had lower adjusted odds of having a complete home smoking compared to those who “never smoked”. Conclusions: Currently smoking everyday was the strongest predictor of not having a complete home smoking ban among sexual minority adults. Focused efforts to increase prevalence of complete home smoking bans should address smoking status to improve health equity among sexual minority adults.

Home Smoking Bans and Urinary NNAL Levels to Measure Tobacco Smoke Exposure in Chinese American Household Pairs

Home smoking bans can reduce tobacco smoke exposure, but little is known about the impact for Chinese American household pairs. In this study of 202 household pairs with low acculturation, 53.9% reported a home smoking ban, 31.7% had inconsistent reports, and 14.4% reported no ban. With decreasing home smoking ban enforcement, more nonsmokers had tobacco smoke exposure (66.1%–86.2%) as measured by the tobacco-specific nitrosamine biomarker urine NNAL (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol). Despite reported bans, about one-quarter of nonsmokers still reported tobacco smoke exposure at home (23.6%–30%) within the past 2 months and three-quarters reported outdoor exposure. In adjusted regression analyses of geometric mean NNAL ratios, nonsmokers in households with no ban had over two times higher levels than nonsmokers in households with a ban: adjusted log NNAL ratio = 2.70 (95% CI 1.21, 6.03). Higher smoker NNAL level and nonsmoker English fluency were also significantly associated with nonsmoker NNAL levels. Nonsmoker levels in households with an inconsistent ban were not significantly different compared to those with a ban. Although home smoking bans were generally associated with lower NNAL levels, tobacco smoke exposure in this immigrant population with low English proficiency was higher than that of the general population. From a health equity standpoint, there is a need for broader implementation and enforcement of comprehensive smoke-free policies.

Smoking in Malaysia: Main issues and ways to overcome

Smoking is a public health problem worldwide and in Malaysia. According to serial Malaysian data, the age of initiation of smoking are at a younger age and the prevalence of smoking in Malaysia among adults and adolescents have not reduced much over the years. Smoking has a detrimental heath effect to smokers as well as those passively smoking. Younger age of smoking is linked to increased dependence of nicotine and many other high-risk behaviours. The two main issues which is addressed here is younger age of initiation of smoking and smoking bans in Malaysia. The factors which contribute to younger age of smoking initiation is tobacco factors, school factors, family factors and social factors. Challenges to smoking bans in Malaysia includes poor enforcement and innovation of tobacco products in Malaysia. A comprehensive approach including the mPOWER strategy should be carried out to address this problem towards achieving Tobacco Endgame.

Characterizing Self-Reported Tobacco, Vaping, and Marijuana-Related Tweets Geolocated for California College Campuses

Introduction: College-aged youth are active on social media yet smoking-related social media engagement in these populations has not been thoroughly investigated. We sought to conduct an exploratory infoveillance study focused on geolocated data to characterize smoking-related tweets originating from California 4-year colleges on Twitter.Methods: Tweets from 2015 to 2019 with geospatial coordinates in CA college campuses containing smoking-related keywords were collected from the Twitter API stream and manually annotated for discussions about smoking product type, sentiment, and behavior.Results: Out of all tweets detected with smoking-related behavior, 46.7% related to tobacco use, 50.0% to marijuana, and 7.3% to vaping. Of these tweets, 46.1% reported first-person use or second-hand observation of smoking behavior. Out of 962 tweets with user sentiment, the majority (67.6%) were positive, ranging from 55.0% for California State University, Long Beach to 95.8% for California State University, Los Angeles.Discussion: We detected reporting of first- and second-hand smoking behavior on CA college campuses representing possible violation of campus smoking bans. The majority of tweets expressed positive sentiment about smoking behaviors, though there was appreciable variability between college campuses. This suggests that anti-smoking outreach should be tailored to the unique student populations of these college communities.Conclusion: Among tweets about smoking from California colleges, high levels of positive sentiment suggest that the campus climate may be less receptive to anti-smoking messages or adherence to campus smoking bans. Further research should investigate the degree to which this varies by campuses over time and following implementation of bans including validating using other sources of data.