Han Minjung, Kang Heewon, Chun Hae-Ryoung, Cho Sung-Il
Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
Department of Family Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Republic of Korea.
Tob Induc Dis. 2025 Jul 23;23. doi: 10.18332/tid/205795. eCollection 2025.
Alcohol dependence may hinder smoking cessation, yet few studies have examined how long-term patterns of alcohol use influence quit outcomes. This study assessed how alcohol dependence trajectories affect smoking cessation among Korean men who smoke.
We performed a secondary analysis using waves 1-7 (2006-2018) of the Korean Longitudinal Study of Aging (KLoSA). Latent class growth analysis (LCGA) identified alcohol dependence trajectories among 2356 men aged ≥45 years who participated in at least three consecutive waves. Multinomial logistic regression (n=1959) was used to assess predictors of trajectory class membership, and Cox proportional hazards models (n=1122) were used to evaluate the association between class membership and smoking cessation. Statistical significance was set at a two-sided p<0.05.
Three alcohol dependence trajectories were identified: stable low (80.7%), decreasing (14.3%), and increasing (5.0%). Participants in the decreasing (adjusted hazard ratio, AHR=0.77; 95% CI: 0.63-0.95) and increasing (AHR=0.60; 95% CI: 0.42-0.86) groups were less likely to quit smoking than the stable low group. Multinomial regression showed that, compared to non-smokers, both former smokers (AOR=1.83; 95% CI: 1.24-2.70) and current smokers (AOR=2.23; 95% CI: 1.60-3.09) were associated with higher odds of belonging to the decreasing trajectory. Only current smoking was significantly associated with the increasing trajectory (AOR=2.28; 95% CI: 1.36-3.84). In stratified analyses, the inverse association between increasing trajectory and quitting was significant only in those aged 45-54 years. Sensitivity analyses using weighted and complete-case data confirmed the robustness of the findings.
Alcohol dependence trajectories were significantly associated with smoking cessation outcomes, especially among younger individuals. Smoking status was also a significant predictor of trajectory class membership, with current smokers more likely to belong to the increasing trajectory. Integrated interventions addressing both behaviors may improve cessation outcomes in high-risk groups.
酒精依赖可能会阻碍戒烟，但很少有研究探讨长期饮酒模式如何影响戒烟结果。本研究评估了酒精依赖轨迹如何影响韩国吸烟男性的戒烟情况。
我们使用韩国老年纵向研究（KLoSA）的第1 - 7波（2006 - 2018年）数据进行了二次分析。潜在类别增长分析（LCGA）确定了2356名年龄≥45岁且至少连续参与三波调查的男性的酒精依赖轨迹。多项逻辑回归（n = 1959）用于评估轨迹类别归属的预测因素，Cox比例风险模型（n = 1122）用于评估类别归属与戒烟之间的关联。统计学显著性设定为双侧p < 0.05。
确定了三种酒精依赖轨迹：稳定低依赖（80.7%）、下降（14.3%）和上升（5.0%）。下降组（调整后风险比，AHR = 0.77；95%置信区间：0.63 - 0.95）和上升组（AHR = 0.60；95%置信区间：0.42 - 0.86）的参与者戒烟的可能性低于稳定低依赖组。多项回归显示，与非吸烟者相比，既往吸烟者（优势比，AOR = 1.83；95%置信区间：1.24 - 2.70）和当前吸烟者（AOR = 2.23；95%置信区间：1.60 - 3.09）属于下降轨迹的几率更高。只有当前吸烟与上升轨迹显著相关（AOR = 2.28；95%置信区间：1.36 - 3.84）。在分层分析中，上升轨迹与戒烟之间的负相关仅在45 - 54岁人群中显著。使用加权和完全病例数据的敏感性分析证实了研究结果的稳健性。
酒精依赖轨迹与戒烟结果显著相关，尤其是在年轻人中。吸烟状态也是轨迹类别归属的重要预测因素，当前吸烟者更有可能属于上升轨迹。针对这两种行为的综合干预可能会改善高危人群的戒烟结果。
