A longitudinal analysis of predictors of quitting smoking among participants in a self-help intervention trial.
Predictors of 7-day abstinence from smoking were identified among participants in a randomized self-help smoking-cessation intervention trial conducted from 1985 to 1988 in Seattle, WA. Subjects were adult smokers belonging to a health maintenance organization who responded to an offer of free quitting assistance. Self-reported smoking status was assessed at 8, 16, and 24 months following enrollment. Predictors of abstinence were identified by longitudinal data analysis using Generalized Estimating Equations (GEEs), a modeling approach which handles repeated-measures data and accommodates time-dependent as well as time-independent covariates. Seventeen items emerged as significant (p < .05) predictors, with odds ratios ranging from 1.3 to 2.1. While much of the previous work in smoking-cessation research has focused on demographic and smoking history variables, results of this study indicate that emphasis should also be placed on psychosocial/motivational factors and quitting activities as important predictors of abstinence. Longitudinal data analysis represents a powerful technique for handling correlated (repeated measures) data, which may prove very useful for future studies of smoking cessation as well as other dynamic processes.
Division of Epidemiology, School of Public Health, Emory University, Atlanta, GA 30329.
H A
HA
Hill
V J
VJ
Schoenbach
D G
DG
Kleinbaum
V J
VJ
Strecher
C T
CT
Orleans
V J
VJ
Gebski
B H
BH
Kaplan
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015986:Confounding Factors, Epidemiologic; D005260:Female; D006304:Health Status; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D015995:Prevalence; D012307:Risk Factors; D012648:Self Care / Q000523:psychology; D016540:Smoking Cessation / Q000523:psychology* / Q000706:statistics & numerical data; D013997:Time Factors