662Factors associated with smoking continuation and indoor smoking among pregnant women’s partners

Background Secondhand smoke by partners is a major source of exposure for non-smoking women. However, factors associated with smoking continuation and indoor smoking among pregnant women’s partners remain unknown. Methods We used data from 6348 partners of non-smoking pregnant women who participated in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study in Japan from 2013 to 2017. Partners’ age, educational attainment, equivalent household income, and pregnant women’s smoking history (never, quitting before pregnancy awareness, quitting after pregnancy awareness) were used as explanatory variables. Multivariate logistic regression analyses were conducted to examine the associations between these variables and smoking continuation/indoor smoking of partners. Results Among 6348 partners, 2506 partners had been smokers at pregnancy awareness. Among them, the prevalence of smoking continuation after pregnancy awareness was 92.0%. Partners whose wives had quitted smoking after pregnancy awareness were less likely to continue smoking than partners whose wives had never smoked; the odds ratio was 0.57 (95% confidence interval, 0.41–0.80). Among partners who continued smoking, the prevalence of indoor smoking was 30.7%. Partners with ≤high school education were more likely to smoke indoors than partners with ≥university education; the odds ratio was 1.60 (95% confidence interval, 1.23–2.07). Conclusions Women’s smoking cessation after pregnancy awareness was associated with decreased risk of partners’ smoking continuation, and lower level of partners’ education was associated with increased risk of partners’ indoor smoking. Key messages Interventions for both women and their partners may be effective in reducing secondhand smoke exposure during pregnancy.

Detection of Smoking in Indoor Environment Using Machine Learning

Revealed by the effect of indoor pollutants on the human body, indoor air quality management is increasing. In particular, indoor smoking is one of the common sources of indoor air pollution, and its harmfulness has been well studied. Accordingly, the regulation of indoor smoking is emerging all over the world. Technical approaches are also being carried out to regulate indoor smoking, but research is focused on detection hardware. This study includes analytical and machine learning approach of cigarette detection by detecting typical gases (total volatile organic compounds, CO2 etc.) being collected from IoT sensors. In detail, data set for machine learning was built using IoT sensors, including training data set securely collected from the rotary smoking machine and test data set gained from actual indoor environment with spontaneous smokers. The prediction accuracy was evaluated with accuracy, precision, and recall. As a result, the non-linear support vector machine (SVM) model showed the best performance with 93% in accuracy and 88% in the F1 score. The supervised learning k-nearest neighbors (KNN) and multilayer perceptron (MLP) models also showed relatively fine results, but shows effectivity simplifying prediction with binary classification to improve accuracy and speed.

104 House Rules and Clean Kids: The down-low on Tobacco

Background Despite multiple published guidelines outlining the potential health risks caused by tobacco smoke, young children continue to be exposed to the detrimental effects of household smoking. Environmental factors also have the potential to influence levels of tobacco exposure in children. Many factors such as comfort can influence the decisions of smoking parents to smoke indoors, increasing potential harm for children. Understanding the correlation between various locations within the household and tobacco exposure is helpful in informing a harm reduction strategy for smokers. This project compared the location of reported tobacco use to detection of the nicotine byproduct cotinine in children’s urine samples. Objectives To determine the impact of smoking location on unintentional tobacco exposure in children. Design/Methods This prospective cross-sectional study focused on children under age ten, since 13% of Canadian children in grades 6 and up have tried a cigarette at least once. Of 286 parents approached during a pediatrician visit, 231 agreed to complete an exposure questionnaire and 132 children were able to provide a urine sample during the visit. A standard ELISA assay was used to measure urine cotinine. Results About half of the 31% of households that reported smoking had an indoor smoking ban. Some indoor smokers isolated their activity to the garage (56%). Of the 84 children with detectable urine cotinine, 62 lived in homes that reported smoking. This suggests that some children were exposed to tobacco smoke through other sources or the underestimation of potential tobacco exposure. Fifteen percent of children from smoking homes had cotinine levels similar to nonsmoking homes. Children of indoor smokers were more likely to have detectable cotinine than those of outdoor smokers. Conclusion Roughly 50% of smokers with children have an indoor smoking ban as a harm reduction strategy. In our study, children of smokers with an indoor smoking ban were less likely to have detectable urine cotinine. Although not smoking is the best strategy, limiting smoking to outside is an optimal harm mitigation strategy. For families with indoor smokers, encouraging them to isolate smoking to a single space like the garage may decrease unintentional pediatric exposure.

Compliance with smoke-free policy at tuberculosis facilities in Armenia: a mixed-methods study

Background Smoke-free environments in tuberculosis (TB) facilities promote a tobacco-free lifestyle among patients and healthcare providers and advance their healthy image. Though the national law of Armenia prohibits indoor smoking in healthcare facilities, enforcement of the law is still insufficient. This study aimed to explore compliance with the smoke-free policy in TB facilities in Armenia. Methods An exploratory sequential mixed-methods study was conducted. Overall 21 TB physicians and five key informants in the field of TB and tobacco control participated in qualitative interviews. To further quantify and validate the findings, structured observations of smoke-free policy implementation were conducted in 36 facilities. Results All physicians expressed a positive attitude towards the smoke-free environment and were satisfied with the level of implementation of a smoke-free policy in their TB facilities. According to the respondents, they already have smoke-free environments established in their facilities. “No smoking” signs, warnings about health consequences and financial penalties, and pictures of damaged lungs were the most common measures against indoor smoking. However, only in 17.1% (n = 6) and 8.6% (n = 3) of observed TB facilities there were posted “No smoking” signs and financial penalties, respectively. In 5.7% (n = 2) of facilities, the research team found ashtrays inside the building, and in 20.0% (n = 7) of facilities, there were smoking patients, physicians, and visitors. Conclusions While the qualitative study indicated good compliance, the quantitative findings were controversial with this regard. In fact, in most of the facilities, the smoke-free policy was not properly implemented and enforced. Additional efforts are needed to harmonize the current practices with national policies and recommendations. Key messages There was a discrepancy between practices reported by physicians and the actual observed compliance. Further interventions are needed to ensure 100% compliance with smoke-free policy in TB healthcare facilities.