The relationship of respiratory air carbonmonoxide levels with the use of smoking and one-year smoking cessation: Prospective cohort study

Objective: Smoking is the leading cause of preventable death. Although smoking intensive fighting programs have been implemented, smoking cessation rates have not reached a satisfactory level. The aim of our study was to investigate the relationship between nicotine addiction levels and CO levels in respiratory air, the effect of respiratory air CO levels on quitting success and other factors affecting quitting success. Methods: In this prospective descriptive-analytical study, the smokers who applied to the ADU family medicine smoking cessation clinic between October 2018 and March 2019 participated in smoking. The control group, relatives of smokers, and non-smoker volunteers who applied to ADU family medicine outpatient clinic were selected. The data were collected through the smoking cessation outpatient follow-up protocol form. CO measurements were made using the Bedfont piCO Smokerlyzer device. Data analysis was done with SPSS 25.0 package program. In addition to descriptive statistical methods, Mann-Whitney U and Student t test were used to compare quantitative data, chi-square and Fisher's exact test to compare categorical data, and Spearman correlation test to determine correlation. Correlation coefficient (r) between 0,000-0,249 weak; Medium between 0.250-0.499; Strong between 0.500-0.749; It was evaluated as a very strong relationship between 0.750-1.000. ROC curve analysis was performed to predict the nicotine dependence performance of CO levels. Besides the sensitivity and selectivity for different breakpoints, the area under the ROC curve was reported. 0.05 was used as the level of significance. Results: The success rate of smoking cessation in 82 patients who participated in our study was 25.6%. A significant correlation was found between the CO value measured in breathing air and the Fagerström nicotine dependence test (p = 0,000), HSI score (p = 0,000) and the amount of cigarettes smoked daily (p = 0,000). The CO values measured between the control group and the study group were also significantly different (p = 0,000). In the ROC curve analysis, when the cutoff point was taken 4.5 ppm, the sensitivity of the CO measurement to predict smoking was 86.6% and the selectivity was 95.1%. The area under the ROC curve (AUC) was 0.961 (95% Confidence Interval 0.936-0.9898; p = 0.000). Having thought about quitting smoking before (p = 0.050), the reason for quitting is disease-disease fear (p = 0.011), regular visits to controls (p = 0,000), compliance with treatment (p = 0,000), taking prescribed medications (p = 0.016) and the CO level initially measured (p = 0.015) was found to be effective on smoking cessation success. The success of quitting was found to be inversely related to the number of quitting attempts (p = 0.006). As a result of the multiple regression analysis, smoking cessation success was 18.0 times (95% CI: 3.7-87.6) more in those who used the treatment regularly compared to those who did not use the treatment regularly. The success of smoking cessation is 1.8 times (95% CI: 1.0-3.1) for each previous cessation attempt and 1.2 times (95% CI: 1.013-1.379) for each 1 ppm increase in CO level measured at the first meeting, was found to be lower. Conclusion: Success in quitting, HSI and Fagerström scores are significantly related with respiratory air CO levels . It can be used to distinguish between smokers and non-smokers and to evaluate nicotine addiction. The most effective factor on the success of quitting is compliance with treatment. Then comes the number of previous release attempts and the initial CO level. Therefore, it should not be forgotten that every trial is important in all cases applying for smoking cessation and should develop common strategies in patient-physician cooperation to increase compliance with treatment. Keywords: CO, carbon monoxide, Fagerström, smoking cessation, smoking