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Type: Journal article
Title: Can we target smoking groups more effectively? A study of male and female heavy smokers
Author: Wilson, D.
Taylor, A.
Roberts, L.
Citation: Preventive Medicine, 1995; 24(4):363-368
Publisher: Academic Press
Issue Date: 1995
ISSN: 0091-7435
Statement of
David Wilson, Anne Taylor and Lyn Roberts
Abstract: BACKGROUND: In recent years a number of studies have examined subgroups within the smoking population. These studies have provided information which facilitate improved targeting of programs and interventions to help smokers quit. Despite this there have been few population studies which have described male and female heavy smokers and compared their characteristics. METHODS: We used representative population data on 789 smokers to examine differences between light and heavy smokers of each gender and between male and female heavy smokers directly. RESULTS: Of those who smoked, 35% of males and 24% of females were classified as heavy smokers and represent a large target group within the smoking population. Whereas a light smoker was characterized as smoking a median of 12.5 cigarettes per day, the heavy smoker smoked a median of 32 cigarettes per day. Univariate comparison of heavy smokers and light smokers showed a number of statistically significant differences according to demographics, in smoking behaviors and knowledge, in beliefs about smoking, in smoking characteristics, and in other health indicators. Because of interactions between gender and work/leisure day smoking variation, separate logistic regression models based on gender were fitted to the data. Again, compared with light smokers, several significant differences emerged for both heavy female and heavy male smokers under the headings mentioned above. Further logistic regression analyses showed differences between male and female heavy smokers when compared directly. CONCLUSIONS: The smoking population of South Australia is not homogeneous and this segmentation study has shown the need for varying approaches to different segments when developing intervention programs.
Keywords: Chi-Square Distribution; Life Style; Smoking; Health Behavior; Logistic Models; Risk Factors; Sex Factors; Socioeconomic Factors
Rights: © 1995 Academic Press, Inc.
RMID: 0030021649
DOI: 10.1006/pmed.1995.1059
Appears in Collections:Medicine publications

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