Literature DB >> 25279247

Estimating Transitional Probabilities with Cross-Sectional Data to Assess Smoking Behavior Progression: A Validation Analysis.

Xinguang Chen1, Feng Lin2.   

Abstract

BACKGROUND AND
OBJECTIVE: New analytical tools are needed to advance tobacco research, tobacco control planning and tobacco use prevention practice. In this study, we validated a method to extract information from cross-sectional survey for quantifying population dynamics of adolescent smoking behavior progression.
METHODS: With a 3-stage 7-path model, probabilities of smoking behavior progression were estimated employing the Probabilistic Discrete Event System (PDES) method and the cross-sectional data from 1997-2006 National Survey on Drug Use and Health (NSDUH). Validity of the PDES method was assessed using data from the National Longitudinal Survey of Youth 1997 and trends in smoking transition covering the period during which funding for tobacco control was cut substantively in 2003 in the United States.
RESULTS: Probabilities for all seven smoking progression paths were successfully estimated with the PDES method and the NSDUH data. The absolute difference in the estimated probabilities between the two approaches varied from 0.002 to 0.076 (p>0.05 for all) and were highly correlated with each other (R2 =0.998, p<0.01). Changes in the estimated transitional probabilities across the 1997-2006 reflected the 2003 funding cut for tobacco control.
CONCLUSIONS: The PDES method has validity in quantifying population dynamics of smoking behavior progression with cross-sectional survey data. The estimated transitional probabilities add new evidence supporting more advanced tobacco research, tobacco control planning and tobacco use prevention practice. This method can be easily extended to study other health risk behaviors.

Entities:  

Keywords:  Adolescent smoking; Cross-sectional data; PDES method; Validation

Year:  2012        PMID: 25279247      PMCID: PMC4178951          DOI: 10.4172/2155-6180.S1-004

Source DB:  PubMed          Journal:  J Biom Biostat


  23 in total

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4.  State Estimation and Detectability of Probabilistic Discrete Event Systems.

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5.  Tobacco smoking trajectory and associated ethnic differences among adolescent smokers seeking cessation treatment.

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Journal:  J Adolesc Health       Date:  2004-09       Impact factor: 5.012

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7.  A multilevel analysis examining the association between school-based smoking policies, prevention programs and youth smoking behavior: evaluating a provincial tobacco control strategy.

Authors:  D A Murnaghan; S T Leatherdale; M Sihvonen; P Kekki
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8.  Can population-based tobacco-control policies change smoking behaviors of adolescents from all socio-economic groups? Findings from Australia: 1987-2005.

Authors:  Victoria M White; Jane Hayman; David J Hill
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9.  Current cigarette smoking among in-school American youth: results from the 2004 National Youth Tobacco Survey.

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Journal:  Int J Equity Health       Date:  2009-04-03

10.  The Global Youth Tobacco Survey (GYTS): linking data to the implementation of the WHO Framework Convention on Tobacco Control.

Authors:  Charles W Warren
Journal:  BMC Public Health       Date:  2008-12-15       Impact factor: 3.295

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2.  Modeling Drinking Behavior Progression in Youth with Cross-sectional Data: Solving an Under-identified Probabilistic Discrete Event System.

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4.  Estimating of Net Transition Probabilities in Triple Stages of Cigarette Consumption in Iranian Men.

Authors:  Mahshid Aryanpur; Ahmad Khosravi; Mahmoud Yousefifard; Mostafa Hosseini; Alireza Oraii; Gholamreza Heydari; Mehdi Kazempour-Dizaji; Hooman Sharifi; Zahra Hessami; Hamidreza Jamaati
Journal:  Tanaffos       Date:  2018-10

5.  Estimating the Transitional Probabilities of Smoking Stages with Cross-sectional Data and 10-Year Projection for Smoking Behavior in Iranian Adolescents.

Authors:  Ahmad Khosravi; Mohammad Ali Mansournia; Mahmood Mahmoodi; Ali Akbar Pouyan; Kourosh Holakouie-Naieni
Journal:  Int J Prev Med       Date:  2016-08-17
  5 in total

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