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Age-Period-Cohort Analysis of daily smoking trends in Turkey using Global Adult Tobacco Survey Data: Insights for effective tobacco control policies
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1
Public Health, School of Public Health, KIIT Deemed to be University, Bhubaneswar, India
2
Community Medicine, VMMC & Safdarjung Hospital, New Delhi, India
3
Tobacco Free Initiative, World Health Organization (SEA), New Delhi, India
4
Community Medicine, ISM & SUM Hospital, SOA Deemed to be University, Bhuabneswar, India
5
Community Medicine, Kalinga Institute of Medical Sciences, Bhubaneswar, India
6
Biostatistics, ICMR-Regional Medical Research Centre, Bhubaneswar, Bhubaneswar, India
Publication date: 2025-06-23
Tob. Induc. Dis. 2025;23(Suppl 1):A721
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ABSTRACT
BACKGROUND: The patterns of tobacco use are shaped by a complex interplay of factors such as age, historical periods, and generational influences. Understanding these dynamics is essential for creating effective, targeted interventions. This study uses Age-Period-Cohort Interaction (APC-I) modeling to explore daily smoking trends in Turkey and provide actionable insights to inform and strengthen tobacco control policies.
METHODS: The GATS data from three waves (2008, 2012, and 2016), were analysed focusing on daily smoking prevalence across eight age groups (15-19 to 65+), three time periods, and overlapping generational cohorts. The APC-I model was employed using 'apci' function in R-Software to estimate age, period, and cohort effects, along with inter- and intra-cohort deviations from expected smoking behaviors. Data visualization were made using heatmaps and bar plots.
RESULTS: Daily smoking was most prevalent among adults aged 30 to 44 years, with the highest rates observed in the 30-34 years (OR:1.67) and 35-44 years (OR:1.65) age groups. In contrast, smoking rates were significantly lower among the youngest (15-19 years, OR 0.55) and oldest (65+ years, OR 0.29) age groups. Over time, daily smoking prevalence decreased notably between 2008 and 2012 (OR 0.83, p<0.001) but picked again by 2016 (OR:1.17, p<0.001). When looking at generational patterns, cohorts born in 1950, 1970, and 2000 had higher-than-expected smoking rates. Interestingly, the 1950 birth cohort showed the steepest decline in smoking rates over their lifetime (slope -0.13, p<0.05).
CONCLUSIONS: This study using Age-Period-Cohort Interaction (APC-I) modeling, highlights the need for tailored tobacco control strategies to address the unique smoking behaviors of different age groups and generations in Turkey. Cessation efforts should focus on middle-aged adults, while preventive measures are critical for younger generations to reduce early smoking initiation. Strengthened regulations to limit access to tobacco and improved access to cessation resources are essential to tackling these challenges.