Ulbricht Sabina, Richter Adrian, Kotz Daniel, Kastaun Sabrina
Department SHIP-KEF, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
Epidemiology and Health Services Research, German Rheumatology Research Centre Berlin, Berlin, Germany.
Addiction. 2025 Mar 21. doi: 10.1111/add.70045.
To illustrate robust intersections of co-occurring factors for two predictors of smoking cessation, motivation to stop smoking (MTSS) and past year-quit attempts (QA), by using means to develop robust predictive models such as bootstrap resampling, scoring rules to evaluate the predictive accuracy and spline functions.
DESIGN, SETTING AND PARTICIPANTS: Cross-sectional data from the German Study on Tobacco Use (DEBRA). Past-years smokers (≥18 years, n = 13 245) from 22 survey waves (2016-2020) were included. The sample (mean age 46.8 years, 46.7% women) was randomly divided into learning (70%) and validation data (30%). Less than 20% in both data sets had tried to stop smoking within the preceding 12 months.
Multinomial regression (for MTSS) and logistic regression (for QA) were used to evaluate whether age, sex, education, monthly net household income per person and the region of residence form intersections with relevant differences in the two outcomes.
MTSS compared with the absence of MTSS was associated with middle [95% confidence interval (CI) = 1.02-1.39] and high education (95% CI = 1.37-1.98). Regarding MTSS, the highest probabilities were observed in participants aged 30 to 50 years from lower and middle (30-40 years) income groups. Regarding QA, the probability of at least one past-year QA was highest in females aged between 20 and 40 years and independent from educational level. Similar probabilities in males were seen only among those from the highest educated group. The predictive accuracy of the results was reduced by 3.1% for MTSS and 3.4% for QA when comparing learning with validation data.
This German study provides compelling evidence linking highest motivation to stop smoking to those aged 30 to 50 years with lower or middle household income. Regardless of educational level, females' probabilities of reporting at least one past-year quit attempt appears to be highest in those aged 20 to 40 years. These findings highlight the need for adopting an intersectional approach when studying predictors of smoking cessation.
通过使用诸如自助重采样、评估预测准确性的评分规则和样条函数等方法来开发稳健的预测模型,以阐明戒烟的两个预测因素——戒烟动机(MTSS)和过去一年的戒烟尝试(QA)——同时出现的因素之间的稳健交集。
设计、设置和参与者:来自德国烟草使用研究(DEBRA)的横断面数据。纳入了来自22次调查波次(2016 - 2020年)的过去一年吸烟者(≥18岁,n = 13245)。样本(平均年龄46.8岁,46.7%为女性)被随机分为学习数据(70%)和验证数据(30%)。两个数据集中均少于20%的人在过去12个月内尝试过戒烟。
多项回归(用于MTSS)和逻辑回归(用于QA)用于评估年龄、性别、教育程度、人均家庭月净收入和居住地区是否与这两个结果中的相关差异形成交集。
与没有戒烟动机相比,有戒烟动机与中等教育程度[95%置信区间(CI)= 1.02 - 1.39]和高等教育程度(95% CI = 1.37 - 1.98)相关。关于戒烟动机,在收入较低和中等(30 - 40岁)的30至50岁参与者中观察到最高概率。关于戒烟尝试,过去一年至少有一次戒烟尝试的概率在20至40岁的女性中最高,且与教育程度无关。在男性中,只有在受教育程度最高的群体中才观察到类似的概率。将学习数据与验证数据进行比较时,戒烟动机结果的预测准确性降低了3.1%,戒烟尝试结果的预测准确性降低了3.4%。
这项德国研究提供了令人信服的证据,将最高的戒烟动机与家庭收入较低或中等的30至50岁人群联系起来。无论教育程度如何,20至40岁女性报告过去一年至少有一次戒烟尝试的概率似乎最高。这些发现凸显了在研究戒烟预测因素时采用交叉性方法的必要性。