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.
Hill
H A
HA
Division of Epidemiology, School of Public Health, Emory University, Atlanta, GA 30329.
Schoenbach
V J
VJ
Kleinbaum
D G
DG
Strecher
V J
VJ
Orleans
C T
CT
Gebski
V J
VJ
Kaplan
B H
BH
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