Dynamic, data-driven typologies of long-term smoking, cessation, and their correlates: Findings from the International Tobacco Control (ITC) Netherlands Survey

Valéria Lima Passos; Rik Crutzen; Johannes T Feder; Marc C Willemsen; Paul Lemmens; Karin Hummel

doi:10.1016/j.socscimed.2019.112393

Dynamic, data-driven typologies of long-term smoking, cessation, and their correlates: Findings from the International Tobacco Control (ITC) Netherlands Survey

Soc Sci Med. 2019 Aug:235:112393. doi: 10.1016/j.socscimed.2019.112393. Epub 2019 Jul 4.

Authors

Valéria Lima Passos¹, Rik Crutzen², Johannes T Feder³, Marc C Willemsen⁴, Paul Lemmens⁵, Karin Hummel⁶

Affiliations

¹ Department of Methodology and Statistics, Maastricht University, CAPHRI Care and Public Health Research Institute, Peter Debyeplein, 1, 6229, HA, Maastricht, the Netherlands. Electronic address: valeria.limapassos@maastrichtuniversity.nl.
² Department of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, the Netherlands. Electronic address: rik.crutzen@maastrichtuniversity.nl.
³ Department of Methodology and Statistics, Maastricht University, CAPHRI Care and Public Health Research Institute, Peter Debyeplein, 1, 6229, HA, Maastricht, the Netherlands. Electronic address: marc.willemsen@maastrichtuniversity.nl.
⁴ Department of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, P. Debyeplein 1, 6229, HA, Maastricht, the Netherlands. Electronic address: marc.willemsen@maastrichtuniversity.nl.
⁵ Department of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, P. Debyeplein 1, 6229, HA, Maastricht, the Netherlands. Electronic address: p.lemmens@maastrichtuniversity.nl.
⁶ Department of Health Promotion, CAPHRI Care and Public Health Research Institute, Maastricht University, P.O. Box 616, 6200, MD, Maastricht, the Netherlands. Electronic address: karin.hummel@maastrichtuniversity.nl.

PMID: 31302376
DOI: 10.1016/j.socscimed.2019.112393

Abstract

Rationale: Efforts towards tobacco control are numerous, but relapse rates for smoking cessations remain high. Behavioral changes necessary for continuous cessation appear complex, variable and subject to social, biological, psychological and environmental determinants. Currently, most cessation studies concentrate on short-to midterm behavioral changes. Besides, they use fixed typologies, thereby failing to capture the temporal changes in smoking/cessation behaviors, and its determinants.

Objective: To obtain long-term, data-driven longitudinal patterns or profiles of smoking, cessation, and related determinants in a cohort of adult smokers, and to investigate their dynamic links.

Methods: The dataset originated from the International Tobacco Control (ITC) Netherlands Project, waves 2008 to 2016. Temporal dynamics of smoking/cessation, psychosocial constructs, and time-varying determinants of smoking were extracted with Group-Based Trajectory Modeling technique. Their associations were investigated via multiple regression models.

Results: Substantial heterogeneity of smoking and cessation behaviors was unveiled. Most respondents were classified as persistent smokers, albeit with distinct levels of consumption. For a minority, cessation could be sustained between 1 and 8 years, while others showed relapsing or fluctuating smoking behavior. Links between smoking/cessation trajectories with those of psychosocial and sociodemographic variables were diverse. Notably, changes in two variables were aligned to behavioral changes towards cessation: decreasing number of smoking peers and attaining a higher self-perceived control.

Conclusion: The unveiled heterogeneity of smoking behavior over time and the varied cross-dependencies between smoking data-driven typologies and those of underlying risk factors underscore the need of individually tailored approaches for motivational quitting.

Keywords: Cessation trajectories; Constructs; Group-based; International Tobacco Control (ITC) Netherlands; Long term; Psychosocial; Smoking; Trajectory modeling.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Analysis of Variance
Attitude to Health
Data Science / methods*
Data Science / statistics & numerical data
Female
Humans
Longitudinal Studies
Male
Middle Aged
Motivation
Netherlands
Smoking / psychology
Smoking / trends*
Smoking Cessation / methods*
Smoking Cessation / statistics & numerical data
Socioeconomic Factors
Surveys and Questionnaires