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Objective: To examine Australian smokers' attitudes towards regulation of the tobacco industry and to compare their attitudes with those of three similar countries--the United Kingdom (UK), the United States (US), and Canada Method: A telephone survey of 2,056 adult Australian smokers and 6,166 Canadian, US, and UK smokers was conducted in 2004 as the third wave of the International Tobacco Control Policy Evaluation Four-Country Survey. Results: Australian smokers display the strongest support for regulation. Only 16% believe that tobacco companies should be allowed to advertise/promote cigarettes as they please, 70% agree that tobacco products should be more tightly regulated, and 64% agree that governments should do more to tackle the harms of smoking. Smokers see government failure to do so in cynical terms--77% agree that governments do not really care about smoking because of money from tobacco taxes. Opposition comes largely from smokers who hold self-exempting beliefs about smoking's risks, have a positive attitude to smoking, do not accept that smoking is socially denormalised, and do not hold tobacco companies responsible for harms caused by smoking. Conclusions and Implications: The majority of Australian smokers believe that the tobacco industry is partly responsible for the predicament they find themselves in and want governments to act more strongly in their real interests. The strong relationship between support for regulation and cynicism about government inaction should stimulate governments into action. Key words: Tobacco, government regulation, smokers' attitudes.

Objective: Lone mothers are among the most disadvantaged groups in many countries. Smoking prevalence among this demographic group is considerably higher than the general population. Previous work has shown that only part of this difference can be explained by age, not having a partner, living alone, and socio-economic factors. This study examined the contribution of mental health, the social environment, and the lifecourse in explaining the effect of lone motherhood on smoking status. Methods: Cross-sectional data from the 1995 National Health Survey and 2001 National Drug Strategy Survey were used. Smoking was defined as daily smoking. Mental health was assessed using a 14-item scale from the SF-36. Proportion of friends who smoke was used as an indicator of the social environment. Age started smoking daily ([less than or equal to] 18 and >18) was used as a lifecourse factor. Results: Mental health, proportion of friends who smoke and age of smoking initiation had strong associations with smoking status. However, they accounted for a small part of the association of being a lone mother and a smoker. After controlling for these factors, the odds of being a smoker among lone mothers were still twice those of mothers with partners (OR 2.1, 95% CI 1.7-2.7). Conclusions and Implications: Improving the socio-economic status (SES), mental health and the social environment of lone mothers could help reduce their high smoking prevalence. However, much of the effect of being a lone mother remains even after controlling for these factors. More research is needed to discover why prevalence is so high among this demographic group.

Background: Despite evidence to the contrary from overseas research, the introduction of smoke-free legislation in South Australia (SA), which required all restaurants to go smoke-free in January 1999, sparked concerns among the hospitality industry about loss of restaurant business. This study aimed to determine whether the law had a detrimental impact on restaurant business in SA. Methods: Using time series analysis, we compared the ratio of monthly restaurant turnover from restaurants and cafes in SA to (a) total retail turnover in SA (minus restaurants) for the years 1991 to 2001 and (b) Australian restaurant turnover (minus SA, Western Australia and the Australian Capital Territory) for the years 1991-2000. Results: There was no decline in the ratio of (a) SA restaurant turnover to SA retail turnover or (b) SA restaurant turnover to Australian restaurant turnover. Conclusion: The introduction of a smoke-free law applying to restaurants in SA did not adversely affect restaurant business in SA.

Objective: To report smoking prevalence among Australian lone mothers by age and socio-economic group and to examine the extent to which the difference in smoking prevalence between lone mothers and other women is due to socio-economic factors. Methods: This was a secondary analysis of data from the 1995 National Health Survey (NHS), which was conducted by the Australian Bureau of Statistics (ABS). Information was collected from 53,800 respondents using face-to-face interviews. This analysis was limited to single mothers (n=1,184) who had at least one dependent child aged under 15. The outcome measure was smoking status, distinguishing regular smokers from occasional smokers, ex-smokers and never-smokers. Results: The overall smoking prevalence among lone mothers was 46.3% (Cl 43.5%-49.1%). Lone mothers who were younger, less educated, received government pension/benefits, occupied rental housing or who lived in more disadvantaged areas were more likely to smoke than others. A strong `lone mother effect' remained after controlling for socio-economic variables. The odds of smoking for lone mothers were 2.4 times greater than for married mothers (95% Cl 2.0-2.9) and twice as large as those for women living alone (95% Cl 1.6-2.4). Conclusion: As the prevalence for this population group is considerably higher than the prevalence for other women within each age category, programs to assist lone mothers to quit smoking are a priority for the long-term health of these women and their children. Furthermore, we discuss how policies and interventions that enhance the material conditions and social circumstances of lone mothers can bring about a decline in their smoking prevalence.

Objective: To investigate the relationship between social integration and mortality at the aggregate level of analysis. Method: The data were compiled from several Australian Bureau of Statistics documents. The unit of analysis was State (Territory)-year. The multivariate regression analysis included data from all States and the Australian Capital Territory for 1990-96. Five indicators of social integration percentage of people living alone; divorce rate; unemployment rate; proportion of people who are discouraged job seekers; and unionisation rate - were used as predictors of nine measures of mortality. Results: Higher levels of social integration, as measured by all indicators except unionisation, were associated with lower mortality rates. In the case of unionisation, higher levels were associated with increased mortality rates. Conclusion: Studies concerning the relationship between social integration and health should investigate the 'type' and 'level' of social integration that is conducive to better health. Implications: To help reduce disparities in health and mortality across communities, public health researchers and policy makers need to closely monitor geographic and temporal trends in social integration measures. Social policies that emphasise investment in social integration or social capital through job creation and training, provision of gainful employment and social services for discouraged and marginalised workers, improved work conditions and social support may lower mortality directly or through their beneficial effects on health-promoting behaviours such as reduced levels of smoking, drinking and physical inactivity.

Reasons for preferring alternative medicine in Australia are explored. Personal health attitudes and beliefs seem to be the reason for selecting alternative medicine rather than dissatisfaction with traditional medicine.

Objective: To determine the association between socio-demographic variables and smoking status in a national sample of Australians aged [is greater than or equal to] 18. Method: The data came from the 1995 National Health Survey (NHS), which was conducted by the Australian Bureau of Statistics (ABS). Information was collected from 20,165 females and 18,948 males using face-to-face interviews. The dependent variable was smoking status distinguishing regular smokers from occasional, ex-smokers and never-smokers. Multiple logistic regression was used to examine the association of smoking status with gender, age, marital status, region of residence, country of birth and three socio-economic measures. Results: Analyses showed that gender, age, marital status, country of birth and socio-economic position were significantly related to smoking status. The odds of being a smoker were largest for respondents who were 20-34 years old, were not married, had a low socio-economic standing, and were born in the Middle East, southern and western Europe for men, and the United Kingdom/Ireland and western Europe for women. The results also revealed that the geographic measure of socio-economic status had a stronger association with smoking likelihood than the individual level indicators (education and income), suggesting the importance of the social environment. Conclusion: There is substantial socio-demographic variability in smoking status. Implication: Of groups identified as having higher smoking rates, the socio-economically disadvantaged groups have the highest priority for targeted campaigns.