A Three-Year Autoregressive Cross-Lagged Panel Analysis on Nicotine Dependence and Average Smoking

Tae Min Song, Ji Young An, Laura L. Hayman, Gye Soo Kim, Ju Yul Lee, Hae Lan Jang

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Objectives: Previous studies have been limited to the use of cross sectional data to identify the relationships between nicotine dependence and smoking. Therefore, it is difficult to determine a causal direction between the two variables. The purposes of this study were to test whether nicotine dependence or average smoking was a more influential factor in smoking cessation; and propose effective ways to quit smoking as determined by the causal relations identified. Methods: This study used a panel dataset from the central computerized management systems of community-based smoking cessation programs in Korea. Data were stored from July 16, 2005 to July 15, 2008. 711,862 smokers were registered and re-registered for the programs during the period. 860 of those who were retained in the programs for three years were finally included in the dataset. To measure nicotine dependence, this study used a revised Fagerström Test for Nicotine Dependence. To examine the relationship between nicotine dependence and average smoking, an autoregressive cross-lagged model was explored in the study. Results: The results indicate that nicotine dependence and average smoking were stable over time; the impact of nicotine dependence on average smoking was significant and vice versa; and the impact of average smoking on nicotine dependence is greater than the impact of nicotine dependence on average smoking. Conclusions: These results support the existing data obtained from previous research. Collectively, reducing the amount of smoking in order to decrease nicotine dependence is important for evidence-based policy making for smoking cessation.

Original languageEnglish (US)
Pages (from-to)115-124
Number of pages10
JournalHealthcare Informatics Research
Volume18
Issue number2
DOIs
StatePublished - Dec 1 2012

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All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Keywords

  • Community Health Centers
  • Health Policy
  • Nicotine Dependence
  • Smoking Cessation

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