Health Education Research, Vol. 14, No. 5, 611-618,
October 1999
© 1999 Oxford University Press
Patterns and predictors of tobacco consumption among women
Department of Applied Social Science, Cartmel College, Lancaster University, Lancaster LA1 4YL and
1 MRC Medical Sociology Unit, 6 Lilybank Gardens, Glasgow G12 8RZ, UK
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Abstract |
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The study examines the patterns and predictors of cigarette consumption among 920 female smokers aged 16–49 who formed part of the British Household Panel Survey, a representative survey of households in Britain. The study assesses the influence of three key factors: socio-economic circumstances, psychological health and partner's smoking status. The study confirms that female smokers are more disadvantaged than the broader population of women, both with respect to their socio-economic circumstances and their psychological health. Within this disadvantaged group, higher cigarette consumption was linked to greater socio-economic disadvantage and poorer psychological health but not partner's smoking status. Age and pregnancy status also had an independent effect on consumption. Of these factors, being in poor psychological health was the single most powerful predictor of high rates of consumption. The implications of the findings for health promotion are discussed.
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Introduction |
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TopAbstractIntroductionThe study: methods and...ResultsDiscussionConclusionsReferences |
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In countries where manufactured cigarettes achieved an early dominance of the tobacco market, the prevalence of cigarette smoking is declining. It is a decline marked out by increasingly sharp socio-economic gradients in tobacco use. In northern Europe, north America and Australia, it is those in disadvantaged circumstances who are most likely to smoke cigarettes (Nicolaides-Bauman, 1993). While socio-economic differentials in smoking are only one determinant of socio-economic inequalities in health, they are an important contributing factor. It has been estimated that health-related behaviours, like smoking, diet and exercise, account for around one-third of the socio-economic variation in mortality (Marmot, 1984; Stronks, 1997
). Among these behavioural factors, cigarette smoking has been singled out for its disease burden (Peto, 1994). Since the early 1970s, it has been a major focus of national and international health promotion programmes (Raw, 1990).
The evidence suggests that health education programmes have contributed to the overall decline in tobacco use (Townsend, 1995). However, tobacco education and smoking cessation programmes appear to be differentially effective, achieving greater reductions in prevalence among those in higher socio-economic groups (Whitehead, 1989; Townsend, 1994, 1995). In Britain, rates of cessation among those in better-off circumstances more than doubled between the early 1970s and the early 1990s. Among the poorest groups, cessation rates have changed little across the last two decades. The result is an increasingly pronounced socio-economic gradient in cessation, with markedly higher quit rates reported among those in higher socio-economic groups (Jarvis, 1997).
The socio-economic differentials in prevalence and cessation represent a major challenge to the health promotion community. There is an urgent need to identify and to address the pathways of risk which run between socio-economic status and smoking behaviour. Tobacco dependence is a long-recognized but under-explored link in these pathways (Shiffman, 1991; Bott, 1997; Parry, 1997). Its influence has been highlighted both in broad population surveys (Jarvis, 1997; Son, 1997) and in studies of smoking in pregnancy (Olsen, 1993; Severson, 1995). Tobacco dependence is recognized to be a complex phenomenon, in which physiological addiction, psychological need and social reinforcement all play a part (Shiffman, 1991). While complex in its origins and its effects, it is relatively straight-forward to measure. Average daily consumption is regarded as a reliable proxy for tobacco dependence, with a daily consumption of about 20 cigarettes needed to maintain steady-state nicotine levels through the day (Todd, 1989; Shiffman, 1991). In Britain, this key influence on prevalence and cessation is strongly age-related, with consumption levels lower in younger and older age groups (Office of Population Censuses and Surveys, 1996).
Average daily consumption has been identified as an independent predictor of cessation. In both self-initiated attempts and in formal treatment programmes, light smokers report more quit attempts, and have higher cessation rates and lower relapse rates than heavy smokers (Ershoff, 1989; COMMIT Research Group, 1995; Jarvis, 1997). In northern Europe, as in the US, cigarette consumption also displays a strong socio-economic gradient among both men and women (Künst, 1997; Son, 1997). Among women in Britain, for example, the proportion of smokers smoking 20 or more cigarettes a day rises from 23% in the highest socio-economic group to 41% in the lowest socio-economic group (OPCS, 1996).
Cigarette consumption is not only strongly patterned by socio-economic status, it is also associated with psychological factors which display a marked socio-economic gradient. Poor psychological health is related to low socio-economic status and, among smokers, to higher levels of consumption (Blaxter, 1990; Graham, 1993; Son, 1997). The smoking status of partners has also been identified as another important influence and one which is again strongly patterned by socio-economic status. Higher rates of cessation and lower rates of relapse are reported among smokers living with non-smoking partners (Jones, 1995; Severson, 1995; Nafstaad, 1996; Jarvis, 1997). Among women, pregnancy status also exerts an influence on smoking behaviour, lowering levels of consumption and increasing rates of cessation. There are socio-economic differentials in these effects, with women in higher socio-economic groups more likely to reduce consumption and to give up smoking in pregnancy than women in lower socio-economic groups (Waterson and Murray-Lyon, 1989; White, 1992; Graham, 1993; Ockene, 1993).
Such findings suggest that psychological health, partner's smoking status and, for women, pregnancy status may be important intermediary factors in the link between socio-economic status and cigarette consumption. However, because these influences on tobacco use cluster together and vary with socio-economic status, multivariate analyses are needed to tease out their separate and cumulative effects. Such analyses require large-scale representative surveys with the appropriate range of measures, including the main independent and intermediary factors (including socio-economic status, psychological health and partner's smoking status), and the outcome variable (cigarette consumption). The present study draws on a British survey, the British Household Panel Survey (BHPS), which meets these criteria. Because the BHPS is a household survey, the majority of respondents live in households with other survey participants. In order to obtain an independent sample of respondents, the study reported here is restricted to women.
The study examines the patterns of cigarette consumption among women aged 16–49 in the early 1990s, describing the influence of socio-economic circumstances, psychological health and partner's smoking status on this key dimension of tobacco use. Subsequent stages of the study will analyse the patterns and predictors of male tobacco consumption.
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The study: methods and measures |
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The study is based on the baseline survey of the BHPS, a representative longitudinal survey of the adult population of Britain (England, Scotland and Wales) living in private households in 1991 (Buck, 1994). The survey is designed as a resource for the social science and policy communities, to enable analyses of individual and household behaviour, including socio-economic circumstances and health-related behaviour. While the survey contains limited data on cigarette smoking, its inclusion of socio-economic, domestic and psychological measures, together with its size and representativeness, permits analysis not possible in other national datasets.
The BHPS is based on a two-stage stratified clustered design, the standard design used in household surveys in Britain. All resident members of the household aged 16 and over were eligible for inclusion. The baseline survey in 1991 achieved a 95% response rate and a household sample of 5538 (Freed Taylor, 1995). The majority (75%) of the female respondents lived in households with relatives (partners, adult children and parents) who were also respondents in the survey. Because the smoking status of respondents is influenced by the smoking status of other household members, only one woman per household was selected for our study of cigarette smoking. Six-hundred and fifteen of the 5431 female respondents were excluded by this procedure. To ensure the comparability of the socio-economic measures across the sample, our study was restricted to women under the age of 50. It included 2782 women, of whom 920 (33%) smoked one or more cigarettes a day.
The variables included in the study are summarized in Table I. Recognizing the limitations of measures of women's socio-economic status based on the occupation of head of household, a range of alternative indicators of socio-economic circumstances are used: school leaving age, educational qualifications, own social class based on current/last occupation and housing tenure. A more direct measure of material circumstances, degree of crowding, is also included, based on the official definition of over-crowding in the UK (one or more persons per room). Psychological health is measured by the 12-item version of the General Health Questionnaire, a self-completed questionnaire designed to detect psychiatric morbidity in the general population. It consists of a suite of 12 questions about general levels of happiness, depression, anxiety and sleep disturbance over the previous 4 weeks. Responses are scored and a score of 3 or more can be taken to indicate poor psychological health (Goldberg and Williams, 1988). This threshold was used to construct a dichotomous measure of psychological well-being (<3/
3).
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Partner's smoking status was measured through a composite indicator of cohabitation status and partner's smoking status (living with a non-smoker/living with a smoker/not cohabiting). Pregnancy and ethnic group are included in Table I
because, while the sample contained very few pregnant and non-white respondents, both variables are known to be associated with smoking behaviour. Their potentially confounding effects could therefore be included in the analysis. Data on pregnancy status are not collected in the BHPS. However, a measure was derived for the study from the birth data included in the 1992 follow-up survey. It should be noted that this derived measure of pregnancy status excludes expectant mothers for whom, because of termination, perinatal death or adoption, no births were recorded at the follow-up interview. A 3-fold classification of ethnic group (white and other/black/Asian) is used.
Table 1 provides baseline data on the demographic, socio-economic and psychological profile of the sample (Graham and Der, 1999). It also provides comparative data on the 2782 women aged 16–49 (smokers and non-smokers) who met the study criteria. The majority of smokers were white women (99%), aged between 25 and 44 (70%). Smokers were more disadvantaged than the broader population of women in the 16–49 age range. For example, only 15% of the smokers had stayed on at school beyond the minimum school leaving age, compared with an overall rate of 27% and a lower proportion were in the owner-occupied sector of the housing market (56% compared with 71%). Smokers were also more at risk of psychological problems, with 34% scoring above the GHQ-12 threshold compared with 29% in the broader population of women aged 16–49. A higher proportion of smokers also lived with a partner who smoked (43% compared with 25%) or were not in a cohabiting relationship (34% compared with 25%).
Our study is restricted to the smokers (n = 920). The analysis of the patterns and predictors of consumption proceeds in two stages. The first and preliminary stage is to examine the bivariate association between each of the demographic, socio-economic and psychological factors listed in Table I and mean daily consumption. The results at this stage provide a descriptive mapping of relationships which informs the second stage of the analysis. One-way analysis of variance was used to determine variables with a significant relationship to consumption (P < 0.05). The second stage focuses on the factors identified as significantly related to consumption and tests whether their effect disappears after taking account of the influence of other variables. Multiple regression was chosen for this analysis, with age included in years and social class dummy coded, with social classes 1 and 2 combined as the reference category. Backwards elimination was used to identify the factors which exert significant and independent effects on consumption. The coefficients represent the predicted effect of the factor on consumption, estimated in terms of additional number of cigarettes a day. Thus, for example, the coefficient for over-crowding is 1.63, indicating that living in over-crowded accommodation adds 1.63 cigarettes a day to estimated daily consumption.
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Results |
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Patterns of cigarette consumption
Only a small minority of the 920 smokers in the study (18%) smoked less than 10 cigarettes a day, while over 40% smoked more than 20 cigarettes a day (Table I
). Mean daily consumption was 15.5 cigarettes.
As Table II records, a strong socio-economic gradient in consumption was evident in all measures of socio-economic status. Smokers with educational qualifications had a mean consumption of 14.4, compared with 17.1 among smokers with no qualifications. School leaving age, housing tenure and degree of crowding were also significantly related to consumption. Daily consumption increased from 13.5 cigarettes a day among women in social class 1 and 2 to 16.5 among women in social class 3M, 4 and 5. Women with no current or previous occupation, which included a high proportion of younger women in higher education and training, had consumption rates comparable to women in non-manual groups. Expectant mothers reported lower levels of consumption than non-pregnant women. Neither partner's smoking status nor ethnic group were significantly related to consumption. However, there was a significant association between psychological health and consumption, with those in poorer health smoking more cigarettes a day. Age was also significantly related to consumption, with mean consumption at its lowest among women in the 16–24 age group.
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Predictors of consumption
Table III
presents the results of the multivariate analysis. It identifies the factors whose influence remained when all the key variables were considered together. The independent predictors of cigarette consumption are socio-economic circumstances (educational qualifications, degree of crowding and social class), pregnancy status, psychological health and age in years. In the multivariate model, these factors all increased mean daily consumption, significantly and independently of the effect of other influences.
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In modelling the effects of these independent factors, Table III
indicates that having no educational qualifications added an estimated 1.54 cigarettes a day to consumption, while living in an over-crowded home added a further estimated 1.64 cigarettes a day to consumption. Social class has a just significant effect: in comparison with smokers in social classes 1 and 2, being in social class 3NM added an estimated 1.74 cigarettes to daily consumption, while being in a manual occupation (3M, 4 and 5) increased mean consumption by an estimated 1.89. Having no occupation had a non-significant effect on mean consumption. Being older also had a significant effect on consumption, adding an estimated 0.11 cigarettes (1.1 cigarettes per 10 years of age) to predicted consumption. Being pregnant had a just-significant effect on consumption, reducing it by an estimated 3.22 cigarettes a day. However, it was psychological well-being which had the most significant effect on consumption, with poor psychological health adding 2.56 cigarettes a day to predicted consumption. There were no interactions between the predictors of consumption identified in Table III. A second analysis was performed in which pregnancy was not included. In this reduced model, social class was no longer significant. Living in over-crowded accommodation and having no educational qualifications, together with age, continued to have a significant effect on consumption. Psychological well-being remained the most powerful predictor of consumption. |
Discussion |
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As well as its direct health effect, high levels of cigarette consumption are recognized to be a major barrier to quitting. The study has focused on this key but under-researched aspect of tobacco use, through the secondary analysis of a large representative survey of British women in the 1990s. The study was restricted to current smokers, a group characterized by their poorer socio-economic circumstances and their poorer psychological health. Within this disadvantaged sample, tobacco use continued to be patterned by socio-economic status and psychological health.
Two broad conclusions can be drawn about these patterns. Firstly, the study confirms that there is a steep socio-economic gradient in tobacco dependence among female smokers in Britain. Because of the dose–response relationship between tobacco intake and disease risk, the socio-economic gradient in consumption means that the risk of smoking-related disease is higher among disadvantaged smokers than among affluent smokers. The gradient was evident both in measures of life chances like school leaving age, educational qualifications and social class, and in measures which provide a more direct index of current living standards, like housing tenure and degree of crowding in the home. Multivariate analyses enabled us to identify the dimensions of life chances and living standards with the most powerful effect on consumption. No educational qualifications, low social class and over-crowding stood out from the cluster of socio-economic influences on consumption, in terms of the independence and strength of their effect on consumption. Of these factors, living in over-crowded conditions was the more powerful predictor of consumption.
Secondly, while socio-economic background and current living conditions had a pronounced effect, socio-economic disadvantage provided only a partial explanation of heavy smoking. Age and pregnancy status are also part of the explanation, but it is psychological well-being which has the most significant effect on consumption. Of the factors tested in the analysis, being in poor psychological health was the single most powerful predictor of high rates of consumption.
Before drawing policy conclusions from the study, two methodological points should be noted about the study. Firstly, like other social surveys, the BHPS relies on self-reported measures of tobacco use. Self-reports tend to under-estimate both prevalence and consumption (Patrick, 1994). However, this will only bias the results if the degree of under-estimation varies by socio-economic status and by psychological health. The most recent national data for British women found no evidence of a socio-economic differential in under-reporting (Prescott-Clarke and Primatesta, 1998). It is possible that the findings on psychological health may reflect an element of reporting bias but it is unlikely to explain the marked effect of this factor on cigarette consumption.
Secondly, a note needs to be added about inferring causality from the statistical analysis. It is possible, but unlikely, that the key predictors uncovered in the analysis—no educational qualifications, low social class, over-crowding, poor psychological health and age—directly raise levels of consumption. What is more plausible is that the predictive power of these variables reflects other, and more complex, influences with greater precision than the other measures used in the study. In other words, these variables are likely to be reflections of and proxies for broader causative processes. For example, in the absence of other psychological measures, the GHQ-12 is likely to be capturing broader affective processes known to influence smoking behaviour, including self-efficacy and optimism, processes which themselves may also be influenced by tobacco dependency (Cohen and Lichtenstein, 1990; Steptoe, 1994). Similarly, educational qualifications are known to be the outcome of longer-term processes of advantage and disadvantage, including parental social class and school experiences (Kuh, 1997). This suggests that health promotion programmes need to target, not specific risk factors, but the broader socio-economic and psychological domains which shape and modify them. The message is therefore one about the importance of primary prevention, about addressing the upstream precursors of tobacco use.
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Conclusions |
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Two messages about upstream prevention can be drawn from the study. Firstly, it requires health promotion programmes which do more than educate, advice and support smokers as they attempt to cut down and give up. It requires, too, interventions which act directly on the socio-economic and psychological environments that militate against positive changes in smoking behaviour. The low cessation rates reported by those who attempt to quit smoking underlines this point. It suggests that changes in behaviour, whether self-initiated or supported by a formal cessation programme, are unlikely to be sustained, if individuals return to an unchanged environment and its indigenous stressors.
Secondly, primary prevention includes the future as well as the current generation of heavy smokers. Future heavy smokers are likely to be disproportionally drawn from those experiencing disadvantage in childhood and through adolescence. Tackling these precursors requires strategies that promote the social and psychological welfare of young people exposed to disadvantage. It points again to the importance of an inter-sectorial perspective and programme, where investments in education, housing and employment are integrated in ways that improve the life chances of those most at risk of heavy smoking in and through their adult lives.
There is increasing recognition that strategies to promote individual health and to reduce health inequalities require investment in the sectors which provide security for individuals and families. While challenging more traditional approaches to health promotion, it is one which is gaining political support (Dahlgren and Whitehead, 1992). The disease burden of tobacco use and its contribution to the wider socio-economic differentials in health suggest that such a strategy would yield significant health gains.
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Acknowledgments |
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The study was supported by an ESRC Senior Research Fellowship (H52427504395) held at the MRC Medical Sociology Unit, Glasgow. Access to the BHPS data was made available through the ESRC Data Archive. The data were originally collected by the ESRC Research Centre on Micro-social Change at the University of Essex. The ESRC, the ESRC Data Archive and the original collectors of the data bear no responsibility for the analyses or interpretations presented here.
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References |
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Received on March 10, 1998; accepted on September 26, 1998
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