Smoking behaviours of Australian adults in 1995: trends and concerns

Abstract

Introduction

Methods

Survey method: A large market research company carried out the sampling and interviewing as part of an omnibus survey in September/October 1995. Procedures were the same as in our previous surveys. In brief, interviews were conducted on the weekend, with respondents within a census collector's district selected at random within specified strata, including State and rural or urban divisions. Within each collector's district an individual residence was chosen at random for the first contact and the adjacent house was contacted next. Further adjacent households were approached until the required number of interviews for that collector's district were obtained (usually eight from about 200 households in each census collector's district).

Response rate: Of the households contacted 47% agreed to participate in the survey, 42% refused, and in the remaining 11% either the residents were too old or ill or could not speak English, or call-back was unsuccessful. The response rate for this survey was similar to the rates for the 1992 and 1989 surveys, but it was lower than response rates in earlier years. Thus, if variable response rates influence reported prevalences, this could only have occurred for the period before 1989; recent comparisons are not confounded by response rates.

Data collected: Respondents indicated their smoking status by choosing a category from the following list:

• Current smoker -- cigarettes only, cigarettes plus cigars or pipes, cigars only (ex-cigarettes), pipes only (ex-cigarettes), cigars only (never cigarettes), or pipes only (never cigarettes);

• Past smoker -- of cigarettes only, of cigarettes plus pipe or cigar, of cigars or pipes only; and

• Never smoker -- those who had never smoked regularly.

Current smokers of factory-made cigarettes indicated the brand usually smoked, the size of the pack usually bought and the number of cigarette packets usually smoked in a week.

Respondents' sex, age (in five-year age groups), country of birth, highest level of education achieved, and occupation were recorded, as well as the occupation of the household's main income earner.

Analysis of data: We calculated 95% confidence intervals (95% CI) associated with estimates of smoking prevalence among men and women and the difference between estimates. Confidence intervals around prevalence estimates for particular subgroups (eg, men aged 50-59 years) are not given. We used chi-squared tests of association to examine differences in the prevalence of smoking between groups, and logistic regression analyses to explore whether associations between smoking prevalence, educational level, occupation and, for women, country of birth were independent of associations between age and smoking. We used analyses of variance and t tests to examine whether the mean number of cigarettes smoked differed between groups. Finally, to compare the prevalence of smoking across recent years, we age-standardised the data from the 1995, 1992 and 1989 surveys to the age distribution of the 1986 sample.  

Results

Smoking status: Of the 5699 participants, 51% (2880) were women and 49% (2819) were men. A comparison of the distributions of age, occupation, education and country of birth in the sample data with those in the census data indicated no bias in the socio demographic variables in the dataset. Eighty-two per cent of respondents were interviewed on the first visit to their home. The smoking status of these respondents was similar to that of the more hard-to-reach respondents (those who were interviewed on the second or third contact).

Cigarettes dominated tobacco use, with only 1% of men and less than 1% of women indicating that they smoked only pipes or cigars. Only 8% of men and 4% of women had smoked roll-your-own cigarettes in the month before the survey. The smoking status of the males and females in the sample is shown in Table 1.

Smoking prevalence: In 1995, the estimated prevalence of smoking among Australian men aged 16 years and over was 27.1% (95% CI, 25.6%-28.7%), while among women the prevalence was estimated to be 23.2% (95% CI, 21.7%-24.7%); this difference was significant (3.9%; 95% CI, 1.6%-6.2%). The prevalence of smoking peaked between the ages of 25 and 29 in men (34.7%) and in women (35%), after which age smoking generally decreased among both men and women.

Past smoking or non-smoking: More men (32.1%; 95% CI, 30.4%-33.8%) than women (21.7%; 95% CI, 20.2%-23.2%) were past smokers, a highly significant difference (10.4%; 95% CI, 8.1%-12.7%). More women (53.4%; 95% CI, 51.6%-55.2%) than men (39.3%; 95% CI, 37.5%-41.1%) had never been regular smokers, and again this difference was highly significant (14.1%; 95% CI, 11.5%-16.7%).

Men and women differed in their age-related patterns of past smoking. Among men, the proportion of past smokers increased with age to reach a peak of 54.4% in those over 70. Although among women the proportion of past smokers peaked at 26% for those over 70, the proportion of past smokers in the other age groups showed little variation from the overall rate of 21.7%.

The proportion who had ever smoked was calculated by adding the percentage of those who had smoked in the past to the percentage of current smokers. Overall, 59.2% (95% CI, 57.4%-61.0%) of men and 44.9% (95% CI, 43.1%-46.7%) of women had smoked at some stage in their life. The association between age and ever having smoked differed for men and women. While among men the proportion who had ever smoked increased with increasing age, for women the proportions of ever smokers began to decrease after the age of 35.

Quit proportions: The quit proportion (ie, proportion of ever smokers who had given up smoking in each age and sex group) is also shown in Table 1. The overall quit proportion for men (0.54) was slightly higher than that among women (0.48). However, as Table 1 shows, there is little difference in the quit proportions for men and women in most age groups, except for the 16 to 19 years and 60 to 69 years age groups.

Factory-made cigarettes: The mean number of factory-made cigarettes smoked per day by smokers was 19.7 (SD, 11.6) for men and 18.1 (SD, 10.8) for women; this difference was statistically significant (t=2.55, df=1238, P=0.01). In 1995, the cigarettes smoked by women had a lower average tar content than the cigarettes smoked by men (t=5.56, df=1022, P<0.001). The average tar content of cigarettes smoked by men was 8.2 mg (SD, 2.8), while for women it was 7.2 mg (SD, 3.0).

Education: As in previous reports of this survey series, the prevalence of smoking and the mean number of cigarettes smoked per day differed for people in various sociodemographic groups. As Table 2 shows, smoking prevalence decreased with increased education, so that only 17.0% of men and 14.2% of women who were university graduates smoked. The association between education level and smoking prevalence was significant for both sexes, but was stronger for men (chi-squared=91.3, df=6, P<0.001) than women (chi-squared=35.5, df=6, P<0.001). The proportions of ex-smokers in the different education levels indicate that quitting was common in all groups. However, the greater proportion of never smokers in the better-educated groups indicates that the lower prevalence of smoking among this group was due to their never having smoked in the first place. For both men and women, smokers with more years of formal education smoked fewer cigarettes per day than did those who had fewer years of education (men: F_3,618 = 3.15, P<0.05; women: F_3,614=8.92, P<0.001).

Occupational levels: Respondents were classified into one of four occupation levels based on the occupation of the household's main income earner. Occupational levels differed in the level of skill required for the job, such that unskilled workers (eg, labourers) were classified as "lower blue collar", while skilled workers (eg, plumbers) were classified as "upper blue collar". As occupation status increased, the prevalence of smoking decreased (Table 2). Among men from "upper white collar" households, 18.7% smoked compared with 40.9% of men from "lower blue collar" households. The association between occupation status and smoking was significant for both men (chi-squared=102.3, df=6, P<0.001) and women (chi-squared=46.8, df=6, P<0.001). Among men, the proportion of ex-smokers was slightly lower among "lower blue collar" households than other groups . Among women, the proportion of ex-smokers was similar among all occupation groups. The proportion of never smokers was greatest among higher occupation levels. This pattern of results indicates that the lower prevalence of smoking seen in higher occupation groups is due to the relatively lower rate of taking up smoking among these groups rather than their greater success at quitting. The differences in the mean number of cigarettes consumed per day between occupation groups was not statistically significant for men (F_3,618 = 2.0, P=0.12) or women (F_3,614=1.4, P=0.24).

Country of birth: The prevalence of smoking was lowest among both men and women born in Asian countries. However, while the prevalence of 19.8% among Asian-born men was not significantly different from that found for groups born elsewhere, the prevalence of smoking among Asian-born women was significantly lower than the prevalence of smoking among women born in Australia (chi-squared=7.2, df=1, P<0.01) or the United Kingdom (chi-squared=6.6, df=1, P<0.01). The number of cigarettes smoked per day showed little variation according to place of birth. The overall association between place of birth and cigarette consumption was not significant for either men (F_4,617=1.3, P=0.26) or women (F_4,614=1.0, P=0.40). However, Asian-born men consumed significantly fewer cigarettes per day than did men born elsewhere (t=2.14, df=620, P<0.05).

Logistic regression analyses of demo graphic data: In separate analyses, age was entered before the predictor variable of education level, occupational status or country of birth (for women only), and in each case the association between smoking prevalence and the predictor variable remained significant.

Pack size and number of cigarettes smoked: The cigarette packet size most commonly used was 25 (by 36% of smokers), followed by packets of 30 and 40 (19% each), 50 (17%), 20 (6%) and 35 (4%). The number of cigarettes smoked per day was related to packet size (F_5,1205=34.93, P<0.001). The mean number of cigarettes smoked per day by those who used packets of 20 was 13, for packets of 25 it was 16, for packets of 30 it was 17, for packets of 40 the mean was 23, and for packets of 50 it was 25. Except for women from lower blue collar households, the packet of 25 cigarettes was the most popular size for all occupation and education groups. After collapsing pack-size categories and combining sexes, 55% of blue collar smokers used pack sizes of 20, 25 or 30 compared with 68% of white collar smokers, and 32% of white collar smokers used packs of 35, 40 or 50 compared with 45% of blue collar smokers (chi-squared=20.0, df=1, P<0.001).  

Comparisons with previous years

The mean number of cigarettes smoked by men in 1995 was lower than the 22.1 cigarettes smoked per day by men in 1992 (t=3.39, df=1348, P<0.001). Among women, however, the average number of cigarettes smoked per day in 1995 was not significantly less than the number smoked in 1992 (19.1) (t=1.59, df=1322, P=0.113).

The legislative and other activity to restrict advertising and promotion of tobacco, as well as expenditure on adult-directed antismoking campigns, between 1989 and 1995 are outlined in Box 1.  

Discussion

For every percentage point smoking prevalence in Australia exceeds the national goal, nearly 140 000 people are smoking who, had the goal been met, would not have been. So, if the goal is missed by 3%, which would be the case if the prevalence remains stable, nearly 420 000 more people than expected will be smoking. If they remain smokers, according to estimates of Doll et al,¹⁵ 210 000 will die prematurely as a result of their smoking.

Against the above fairly alarming observations must be set some auspicious trends -- smokers are smoking less and are probably less exposed to inhaled carcinogens and this should flow through to modest public health gains. As well as benefiting themselves, it seems plausible that a lower daily consumption by smokers is reducing the passive exposure of others to cigarette smoke, as forgone cigarettes may be some of those previously smoked at work or in public places where others would be exposed to sidestream smoke.

Assuming these data indicate a slow-down or stalling in the previous reduction in smoking prevalence, why has this occurred and what needs to be done? Figure 2 suggests one explanation for influences on smoking prevalence. At times when antismoking activity is high, whether it be in the form of policy or programs, smoking declines, but when these abate prevalence stagnates. Clearly, these data call for more extensive and rigorous analysis which might incorporate, in a multivariate analysis, other factors such as price, regulations and pro-cigarette promotions. This could determine the extent to which program expenditure affects smoking prevalence.

The trends are extremely worrying. Stasis in public policy and prevention programs paralleled by static smoking levels suggest the importance of continuing to extend antismoking programs in order to restart the reduction in smoking prevalence. The experience of some Scandinavian countries shows that public health authorities cannot rest on their laurels.¹⁶ Much remains to be done (Box 2).  

References

1. Commonwealth Department of Human Services and Health. Better Health Outcomes for Australians. Canberra: AGPS, 1994.
2. Australian Institute of Health and Welfare. Tobacco use and its health impact in Australia. Canberra: AIHW, 1996.
3. English D, Holman CD, Milne E, et al. The quantification of drug caused morbidity and mortality in Australia. Canberra: Commonwealth Department of Human Services and Health, 1995.
4. Gray N, Hill D. Patterns of tobacco smoking in Australia. Med J Aust 1975; 22: 819-822.
5. Gray NJ, Hill D. Patterns of tobacco smoking in Australia II. Med J Aust 1977; 20: 329-330.
6. Hill D, Gray N. Patterns of tobacco smoking in Australia III. Med J Aust 1982; 1: 23-25.
7. Hill D, Gray N. Australian patterns of tobacco smoking and related health beliefs in 1983. Community Health Stud 1983; 8: 307-316.
8. Hill D. Australian patterns of tobacco smoking in 1986. Med J Aust 1988; 149: 6-10.
9. Hill D, White V, Gray N. Australian patterns of tobacco smoking in 1989. Med J Aust 1991; 154: 797-801.
10. Hill D, White V. Australian adult smoking prevalence in 1992. Aust J Public Health 1995; 19: 305-308.
11. Chapman S, Wooward S. Australian court rules that passive smoking causes lung cancer, asthma attacks and respiratory disease. BMJ 1991; 302: 943-945.
12. Schollam v Dept of Health (NSW). District Court (NSW). 25 May 1992, Case 40830/86.
13. Borland R, Mullins R. The increasing prevalence of workplace smoking bans in Victoria. J Occup Health Safety Aust N Z 1994; 10: 35-40.
14. Borland R, Morand M, Mullins R. Prevalence of workplace smoking bans in Victoria. Aust N Z J Public Health 1997; 21: 694-698.
15. Doll R, Peto R, Wheatley K, et al. Mortality in relation to smoking: 40 years' observations on male British doctors. BMJ 1994; 309: 901-911.
16. Rimpela A. Critical analysis of the Finnish Tobacco Act: implementation and legitimacy 1977-89. Tobacco Control 1992; 1: 285-292.