Aims: Extending our earlier findings from a longitudinal cohort study, this study examines parents' early and late smoking cessation as predictors of their young adult children's smoking cessation.
Design: Parents' early smoking cessation status was assessed when their children were aged 8 years; parents' late smoking cessation was assessed when their children were aged 17 years. Young adult children's smoking cessation, of at least 6 months duration, was assessed at age 28 years.
Setting: Forty Washington State school districts.
Participants And Measurements: Participants were 991 at least weekly smokers at age 17 whose parents were ever regular smokers and who also reported their smoking status at age 28. Questionnaire data were gathered on parents and their children (49% female and 91% Caucasian) in a longitudinal cohort (84% retention).
Findings: Among children who smoked daily at age 17, parents' quitting early (i.e. by the time their children were aged 8) was associated with a 1.7 times higher odds of these children quitting by age 28 compared to those whose parents did not quit [odds ratio (OR) 1.70; 95% confidence interval (CI) 1.23, 2.36]. Results were similar among children who smoked weekly at age 17 (OR 1.91; 95% CI 1.41, 2.58). There was a similar, but non-significant, pattern of results among those whose parents quit late.
Conclusions: Supporting our earlier findings, results suggest that parents' early smoking cessation has a long-term influence on their adult children's smoking cessation. Parents who smoke should be encouraged to quit when their children are young.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2720994 | PMC |
http://dx.doi.org/10.1111/j.1360-0443.2009.02547.x | DOI Listing |
Radiologie (Heidelb)
January 2025
Klinik für Diagnostische, und Interventionelle Neuroradiologie, Universitätsklinikum des Saarlandes, Kirrberger Straße, 66424, Homburg-Saar, Deutschland.
Stroke is one of the most common causes of disability in older adults. It remains a common cause of death and permanent functional limitation in individuals who are older than 80 years. Approximately 50% of all strokes occur in people over the age of 75, and 30% in those over 85.
View Article and Find Full Text PDFFront Public Health
January 2025
Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Introduction: Smoking causes lung cancer and a wide range of acute and chronic diseases annually throughout the world. A fourth-generation behavioral framework, namely the Multi-Theory Model (MTM) of health behavior change was used to predict the initiation and maintenance of smoking cessation among health worker smokers.
Methods: A cross-sectional study of 170 smoking healthcare workers was conducted in Kabul.
Front Public Health
January 2025
HEOA Group, School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Purpose: This study explored the effect of four different smoking statuses (non-smokers, moderate smokers, heavy smokers, and former smokers) on health-related quality of life (HRQOL) among residents aged 15 years and older in Sichuan Province, China with consideration of potential differences among age groups (young, middle-aged, and older adults).
Methods: The EQ-5D-5L utility index and EQ-VAS score were used to measure HRQOL. Self-reporting and salivary cotinine test were used to determine the smoking status of respondents, and the Tobit regression model was used to explore the relationship between smoking status and HRQOL.
Depress Anxiety
January 2025
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Background: Individuals with mental health disorders face major barriers in accessing smoking cessation care, often due to the stigmas associated with mental disorders and addiction. Consequently, accessible population-based smoking cessation interventions are needed for this vulnerable group.
Objective: This secondary analysis utilized data from a 12-month randomized trial to examine whether an acceptance and commitment therapy-based app (iCanQuit) demonstrated greater efficacy, engagement, and satisfaction compared to a United States (US) Clinical Practice Guidelines-based app (QuitGuide) in helping adults with mental health disorders quit smoking.
Toxicol Rep
June 2025
Division of Molecular Medicine, Bose Institute, Kolkata 700054, India.
Machine learning (ML) has the potential to transform tobacco research and address the urgent public health crisis posed by tobacco use. Despite the well-documented health risks, cessation rates remain low. ML techniques offer innovative solutions by analyzing vast datasets to uncover patterns in smoking behavior, genetic predispositions, and effective cessation strategies.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!