Different Clinical Characteristics of Current Smokers and Former Smokers with Asthma: A Cross-Sectional Study of Adult Asthma Patients in China

Abstract

ObjectiveSmoking is a trigger for asthma, which has led to an increase in asthma incidence in China. In smokers, asthma management starts with smoking cessation. Data on predictors of smoking cessation in Chinese patients with asthma are scarce. The objective of this study was to find the differences in clinical characteristics between current smokers and former smokers with asthma in order to identify factors associated with smoking cessation.Patients and MethodsEligible adults with diagnosed asthma from the hospital outpatient clinics (n = 2312) were enrolled and underwent a clinical evaluation, asthma control test (ACT), and pulmonary function test. Information on demographic and sociological data, lung function, laboratory tests, ACT and asthma control questionnaire (ACQ) scores was recorded. Patients were divided into a current smokers group and a former smokers group based on whether they had quit smoking. Correlations of pack-years and years of smoking with clinical parameters were evaluated using Spearman’s rank correlation analysis. Logistic regression analysis was used to analyze the factors associated with smoking cessation. ResultsOf all patients with asthma, 34.6% were smokers and 65.4% were former smokers, and the mean age was 54.5 ± 11.5 years. Compared with current smokers, the former smokers were older, had more pack-years, had smoked for longer, had heavier dyspnea and had worse asthma control. The Spearman’s rank correlation analysis showed that pack-years and years of smoking were negatively correlated with forced expiratory volume in 1 second (FEV1), FEV1%predicted, FEV1/forced vital capacity (FVC) and ACT scores, but positively correlated with ACQ scores in all patients. Interestingly, pack-years and years of smoking were negatively correlated with serum immunoglobulin E (IgE), fractionated exhaled nitric oxide (FeNO), blood eosinophils, and blood neutrophils in all patients. The logistic regression model showed that smoking cessation was positively correlated with age, female sex, pack-years, years of smoking, FEV1, FEV1/FVC and blood eosinophils, but was negatively correlated with ACT, or widowed status, and body mass index (BMI). ConclusionsMore than 30% of asthma patients in the study were still smoking. Among those who quit smoking, many quit late, often not realizing they need to quit until they have significant breathing difficulties. The predictors of smoking cessation identified in this study indicate that there are still differences between continuing smokers and former smokers, and these predictors should be focused on in asthma smoking cessation interventions to improve the prognosis of patients with asthma.