Center for Life Course Health Research, Faculty of Medicine, University of Oulu, PO Box 5000, 90014, Oulu, Finland.
Kerava Health Care Center, Metsolantie 2, 04200, Kerava, Finland.
Sci Rep. 2020 Oct 1;10(1):16365. doi: 10.1038/s41598-020-73334-3.
Smoking remains among the leading causes of mortality worldwide. Obtaining a comprehensive understanding of a population's smoking behaviour is essential for tobacco control. Here, we aim to characterize lifelong smoking patterns and explore underlying sociodemographic and lifestyle factors in a population-based birth cohort population followed up for 46 years. Our analysis is based on 5797 individuals from the Northern Finland Birth Cohort 1966 who self-reported their tobacco smoking behaviour at the ages of 14, 31 and 46. Data on sex, education, employment, body mass index, physical activity, alcohol consumption, and substance addiction were also collected at the follow-ups. We profile each individual's annual smoking history from the age of 5 to 47, and conduct a latent class trajectory analysis on the data. We then characterize the identified smoking trajectory classes in terms of the background variables, and compare the heaviest smokers with other classes in order to reveal specific predictors of non-smoking and discontinued smoking. Six smoking trajectories are identified in our sample: never-smokers (class size 41.0%), youth smokers (12.6%), young adult quitters (10.8%), late adult quitters (10.5%), late starters (4.3%), and lifetime smokers (20.7%). Smoking is generally associated with male sex, lower socioeconomic status and unhealthier lifestyle. Multivariable between-class comparisons identify unemployment (odds ratio [OR] 1.28-1.45) and physical inactivity (OR 1.20-1.52) as significant predictors of lifetime smoking relative to any other class. Female sex increases the odds of never-smoking and youth smoking (OR 1.29-1.33), and male sex increases the odds of adult quitting (OR 1.30-1.41), relative to lifetime smoking. We expect future initiatives to benefit from our data by exploiting the identified predictors as direct targets of intervention, or as a means of identifying individuals who may benefit from such interventions.
吸烟仍然是全球主要的死亡原因之一。全面了解人口的吸烟行为对于烟草控制至关重要。在这里，我们旨在描述一个基于人群的出生队列人群的终身吸烟模式，并探讨其潜在的社会人口学和生活方式因素，该队列人群随访了 46 年。我们的分析基于芬兰北部出生队列 1966 年的 5797 名个体，他们在 14 岁、31 岁和 46 岁时报告了自己的吸烟行为。在随访中还收集了关于性别的数据、教育、就业、体重指数、身体活动、饮酒和物质成瘾。我们从 5 岁到 47 岁的个体每年吸烟情况进行分析，并对数据进行潜在类别轨迹分析。然后，我们根据背景变量描述确定的吸烟轨迹类别，并将最重度吸烟者与其他类别进行比较，以揭示非吸烟和戒烟的具体预测因素。在我们的样本中确定了六种吸烟轨迹：从不吸烟者（类别大小为 41.0%）、青少年吸烟者（12.6%）、年轻成年戒烟者（10.8%）、成年后期戒烟者（10.5%）、晚期开始吸烟者（4.3%）和终身吸烟者（20.7%）。吸烟通常与男性、较低的社会经济地位和不健康的生活方式有关。多变量组间比较确定失业（比值比[OR]1.28-1.45）和身体活动不足（OR1.20-1.52）是终生吸烟的显著预测因素，相对于任何其他类别。女性性别增加了从不吸烟和青少年吸烟的几率（OR1.29-1.33），而男性性别增加了成年戒烟的几率（OR1.30-1.41），相对于终生吸烟。我们预计未来的干预措施将受益于我们的数据，将确定的预测因素作为干预的直接目标，或作为识别可能受益于这些干预措施的个体的一种手段。
