Modeling Drinking Behavior Progression in Youth with Cross-sectional Data: Solving an Under-identified Probabilistic Discrete Event System.
BACKGROUND
The probabilistic discrete event systems (PDES) method provides a promising approach to study dynamics of underage drinking using cross-sectional data. However, the utility of this approach is often limited because the constructed PDES model is often non-identifiable. The purpose of the current study is to attempt a new method to solve the model.


METHODS
A PDES-based model of alcohol use behavior was developed with four progression stages (never-drinkers [ND], light/moderate-drinker [LMD], heavy-drinker [HD], and ex-drinker [XD]) linked with 13 possible transition paths. We tested the proposed model with data for participants aged 12-21 from the 2012 National Survey on Drug Use and Health (NSDUH). The Moore-Penrose (M-P) generalized inverse matrix method was applied to solve the proposed model.


RESULTS
Annual transitional probabilities by age groups for the 13 drinking progression pathways were successfully estimated with the M-P generalized inverse matrix approach. Result from our analysis indicates an inverse "J" shape curve characterizing pattern of experimental use of alcohol from adolescence to young adulthood. We also observed a dramatic increase for the initiation of LMD and HD after age 18 and a sharp decline in quitting light and heavy drinking.


CONCLUSIONS
Our findings are consistent with the developmental perspective regarding the dynamics of underage drinking, demonstrating the utility of the M-P method in obtaining a unique solution for the partially-observed PDES drinking behavior model. The M-P approach we tested in this study will facilitate the use of the PDES approach to examine many health behaviors with the widely available cross-sectional data.
Xingdi
X
Hu
Department of Epidemiology, University of Florida, Gainesville, Florida, USA. jimax.chen@ufl.edu.
Xinguang
X
Chen
Robert L
RL
Cook
Ding-Geng
DG
Chen
Chukwuemeka
C
Okafor
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002648:Child; D003430:Cross-Sectional Studies; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D012307:Risk Factors; D000066608:Underage Drinking; D055815:Young Adult