Smoking and heavy drinking amongst British middle classes 669. Little is thus .... significant differences are differences in relation to a stated reference cate-.
Sociology of Health & Illness Vol. 17 No. 5 1995 ISSN 0141-9889 pp. 668-680
Going agaii^t the gnuhi: ^Mridi^ wiA 'heavy' drinking amongst tl^ British m i d ^ classes Roger Burrows* and Sarah Nettleton^ ' Centre for Housing Policy, University of York ^ Department of Social Policy & Social Work, University of York
Abstract This paper examines the characteristics of those members of the British middle classes who 'go against the grain' of healthy living by both smoking and drinking alcohol over recommended levels. Using logistic regression procedures on GHS data, it concludes that there are significant gender differences, with men being much more likely to adopt such risky health behaviours than women. Further, the social correlates of such behaviours differ for men and women. For men, such behaviours are significantly associated with marital status, the experience of social mobility and region. For women, such behaviours are associated with the presence of dependent children, educational level and the number of hours worked in paid employment. The paper attempts some tentative interpretations of these results by drawing upon the available sociological literature.
iDtroduction Current health policy emphasises the importance of individual health behaviours for the determination of health status (Department of Health, 1992). However, there is some evidence to suggest that such behaviours do not have a uniform impact upon the population. For instance, Blaxter concludes from her study of Health and Lifestyles that '[only] in the more favourable circumstances is there "room" for considerable damage or improvement by the adoption of voluntary health-related habits' (Blaxter, 1990: 223).' Despite this the vast majority of research into health-related behaviours has focused on the structurally disadvantaged (Pill and Stott 1985, Blackburn 1991, Graham 1993) with only a few studies giving any explicit sociological attention to the health-related habits of structurally advantaged social groups (Calnan 1987, Backett 1990, 1992, Cainan and Williams 1991, Mullen 1993). O Blackwel) Publishers Ltd/Editorial Board 1995. Published by Blackwell Publishers. 108 Cowley Road, Oxford 0X4 IJF, UK and 238 Main Street. Cambridge. MA 02142, USA.
Smoking and heavy drinking amongst British middle classes 669 Little is thus known about the social correlates, if any, of differences in health behaviours amongst the middle classes. There is therefore some merit in exploring the social context of the behaviours of those in structurally advantaged positions who engage in habits likely to be disadvantageous to their health. We know much about the structural constraints on health behaviours amongst the disadvantaged (Graham 1990, 1993), but we know little about the social processes which determine healthrelated behaviours under conditions of relative autonomy. Just what are the social factors which contribute to increased propensities towards 'risky' health behaviours amongst social groups advantaged in terms of resources and choice? Given the ubiquity of the discourse of health promotion in contemporary consumer culture and the hegemonic role that the middle classes are playing in its promulgation (Bunton and Burrows 1995), those minority members of the class who deviate from 'healthy lifestyles' deserve at least some sociological attention. This paper offers a quantitative sketch of aspects of middle class health-related behaviour via a secondary analysis of a large scale nationally representative data set - the General Household Survey (GHS) for 1990/91.^ Rather than explore the full range of risk factors associated with health (McKie 1994) we concentrate on just two: the smoking of cigarettes and the consumption of alcohol over and above recommended levels. Throughout this paper we refer to the combination of these habits as risky health behaviours. Middle class health-related behaviours The GHS contains data on 23,663 individuals living in households in England, Scotland and Wales. Our analysis concentrates on those in the sample aged between 18 and 60 whom we have classified as being members of the middle classes. Although the GHS contains data on the smoking habits of those aged from 16 we decided to examine only those persons legally able to combine both smoking and drinking. The GHS contains various questions on smoking and drinking behaviours which allow a range of derived variables to be constructed. Of interest to us here are those who both currently smoke and drink alcohol over and above the levels recommended by the Royal College of Physicians - 21 units of alcohol for men and 14 units for women.^ Although these measures are subject to the usual limitations of self-reported data they currently provide the most robust nationally-representative source of data. Our approach to defining the middle classes is a pragmatic one. We adopt a procedure which allocates people into the middle class on the basis of both their own socio-economic group (SEG) and that of the head of the household within which they live (Dahl, 1991). We define membership of the middle class in terms of each individual's relationship to the (0 Blackwell Publishers Ltd/Editorial Board 1995
670 Roger Burrows and Sarah Nettleton professional and employer and manager SEGs. The middle classes are defined as: (i) those whose own SEG is either professional or employer and manager; or (ii) those who live in a household where the head of household is in either a professional or an employer and manager SEG and their own SEG is in the intermediate non-manual SEG. Table 1 shows the consequen(%s for our sample of taking this approach for both men and women. Our sample thus consists of 2830 cases. However this reduces to 2729 when we take out those with missing data on smoking and/or drinking behaviours. Table 1. Procedure adopted for defining the middle classes Men
Own SEG
SEG of Head of Household
Professionai
Employer-Manager
Intermed Non-Manual
Professional Employer and Manager Intennediate Non-Man Junior Non-Manual Skilled Manual Semi-Skilled Unskilled Manual
421 13 8 3 7 5
3 1188 11 9 16 17
10 32
1
1
Totals
457
1245
42 = 1744
Women
Owrt SEG
SEG of Head of Household
Professional
Employer-Manager
Intermed Non-Manual
Professional Employer and Manager Intermediate Non-Man Junior Non-Manual Skilled Manual Semi-Sktlled Unskilled Manual
53 15 8 1 9 5 4
41 332 6 17 117 17 23
127 273
595
400 = 1086
Totals
91
Our concern in this analysis is to understand what social factors increase or decrease the odds of smoking and drinking above recommended levels for members of this middle class sample. This is most appropriately approached using logistic regression techniques. Logistic regression allows us to examine the influence of individual variables whilst, at the same time, controlling for the influence of other variables. In some respects this is analogous to the more familiar techniques of O Biackwell Publishers Ltd/Editorial Board 1995
Smoking and heavy drinking amongst British middle classes 671 statistical elaboration but allows us to deal with independent variables at any level of measurement in a more systematic way. We explore the social correlates of middle class risky health behaviours in separate models for both men and women rather than include a gender variable in a generic model (Arber 1991). Not only are the determinants of health status known to be different for men and women, but a simple cross-tabulation, shown in Table 2, shows that the distribution of risky health behaviours across gender is highly significant (p < O.OOI). Men are almost twice as likely both to smoke and drink above recommended levels than are women. Table 2. Risky health behaviours (smoking plus 'heavy' drinking) by gender amongst the middle classes Male
Female
total
Does Not Combine Smoking + 'Heavy' Drinking
1468 89,1%
1021 94.4%
2489 91.2%
Does Combine Smoking + 'Heavy' Drinking
180 10.9%
60 5.6%
240 8.8%
N
1648
1081
2729
Some variables, which on a priori grounds one might have expected to possess at least some explanatory power, did not do so: variables such as ethnicity, income and economic sector (the results for which are not reported here). Unfortunately, we were not able to investigate the influence of religion, which in previous research has been linked to differences in drinking behaviour (Mullen 1994, Murray and McMillan 1993). The variables displaying a significant bivariate relationship (as summarised in Table 3) were entered simultaneously into a logistic regression model: age; marital status; the presence of dependent children in the household; educational level; hours worked in paid employment (if any); class background; and region. Each parameter estimate in Table 3 shows the hndividual estimated odds ratio within a simple bivariate relationship"*, whilst each parameter estimate in Table 4 shows the estimated odds ratio after controlling for the influence of all the other variables in the equation,/' There are a number of ways in which compaHsoos can be made between the effects of each category of a variable. In this instance we have chosen to discuss the results in relation to an indicated reference category within each variable because we have found this the simplest way of interpreting the influence of nominal level variables. Thus, all significant differences are differences in relation to a stated reference category or paradigmatic instance. For example, in relation to marital status all of the estimated odds ratios for the different categories of the variable © Blackwcil ftiblishers Ltd/Editorial Board 1995
672 Roger Burrows and Sarah Nettleton
Table 3. indivUbml bivariate logistic regression results Females
Males Odds Ratio
Sig.
N
Odds Ratio
Sig.
128 423 477 428 192
LOO 0.84 0.86 0.53* 0.28*
0.54 0.59 0.03 0.00
102 296 348 221 114
LOO 0.55 0.73 0.54 0.19*
0.17 0.45 0.19 0.03
1209 274 69
1.00 3.61* 2.64' 3.97*
0.00 0.00 0.00
782 79 143 77
LOO L52 1.70 0.49
0,35 0.12 0.34
Other Qual Higher Qual
213 663 770
1.00 1.40 1.04
0.20 0.88
152 475 453
LOO 0.87 0.40*
0-69 0.02
Children No Children Children
928 720
LOO 0.63'
0.01
625 455
LOO 0.44*
001
Region Provinces South East Greater London
1024 412 212
LOO 1.41 1.80*
0.06 0.01
682 257 142
LOO L08 1.04
0.81 0.92
Hours Worked Fuil-Time Part-Time Not Working
1531 31 86
LOO L53 0.39
0.39 0.07
603 262 603
LOO 0.24* 0.53
0.00 0.09
1562
1.00
0.87
865
1.03*
0.00
LOO 0.76 0.49* 0.52* 0.27* 0.19'
0.26 0.05 0.01 0.00 0.03
97 347 105 350 92 33
LOO L51 2.94 2.3! L42 3.!3
0.52 O.U 0.18 0.65 0.18
Variable Age 18 to 25 to 35 to 45 to 55 to
24 34 44 54 60
Marital Status Married Cohabiting Single Separated/Widow
N
96
Education
None
Hours Worked' (Continuous)
Social Class of Father 163 I 529 Ii 140 HIN 511 HIM )68 IV 53 V
' Estimate is only for those currently working.
are calculated in relation to those who are currently married. An alternative way of expressing the results would be to examine the deviations of each of the odds ratios for each category of a variable in relation to the overall effect of a variable. This would have the advantage of providing © Blackwell Publishers Ltd/Editorial Board 1995
Smoking and heavy drinking amongst British middle classes 673
Table 4. Simultaneous logistic regression results Males
females
Odds Ratio
Sig.
N
Odds Ratio
Sig.
1.00 1.65 2.45* 1.55 1.00
-
100 283 343 206 91
1.00 1.07 1.86 0.95 0.34
-
0.13 0.0 i 0.26 1.00
1138
t.oo
95 266 63
2.92* 2.42* 4.20*
~ 0.00 0.00 000
747 75 133 68
1.00 0.96
.0.93 0.73 0.14
Children No Children Children
866 696
1.00 0 77
0.22
581 442
1,00 0.40*
Education None Other Qual Higher Qual
198
626 738
1.00 0.75 1.11
0.33 0.72
140 444 439
1.00 0.82 0.34*
1.00 0.52 1.12
0.23 0.84
574 249 200
1.00 0.32* 0.78
_ 0.03 0.55
1.00 0.78 0.51 0.56* 0.30* 0.19-
0.34 0.07 0.03 0.00 0.03
97 347 104 350 92 33
1.00 1.40 2.90 2,00 1.21 2.44
_ 0.60 0.13 0.28 0.8! 0.31
1.00 1.38 1.74*
0.10 0.02
647 243 133
1.00 1.20 0.89
_ 0.58 0.79
Variable Age
18 to 24 25 Io34 35 to 44 45 to 54 55 to 60 Marital Status Married Cohabiting Single SeparatedAVidow
Hours Worked Futl-Time Part-Time Not Working
123 417 462 408 152
1467 30 65
1.16 0.33
0.23 0.23 0.92 0.22
0.0!
„
0.61 0.02
Social Class of Father I II
163
529
IIIN
140
HIM IV
509 168 53
V
Region Provinces South East Greater London
927 394 196
US with a global test of heterogeneity between the odds ratios - that is, can the hypothesis that they all come from a population of sub-groups with a common level of risk be rejected? However, we find the interpretation of such deviations in relation to an abstract overall variable effect more difficult to decipher than deviations calculated in relation to a more concrete paradigmatic person. © Blackweil Publishers Ltd/Editorial Board 1995
674 Ro^r Burrows and Sarah NetUeton We shall discuss the results of this simultaneous logistic regression model in relation to each of the variables entered, making comparisons with the bivariate results when necessary. Age After controlling for all of the other variables, age - in its categorical form - is not associated with risky health behaviours for middle class women. For men the nature of the association is fundamentally altered compared to the bivariate results which suggested that it was the young who had the highest propensity to smoke and drink. Compared to the 18to-24 age category alt other age categories now have higher odds of risky health behaviours, although only those aged 35 to 44 are statistically significant. Thus, we suggest, it is not youthfulness per se which accounts for the higher odds of such behaviour, sts suggested by the bivariate results, but the effects of other variables acting through age. In particular it is likely that the marital status of men, which differs markedly over the life-course, has an influence. Marital status After controlling for al! the other variables, the influence of marital status on the odds of risky health behaviours is significant in its impact for men but has no influence on women. Of the men, those who were married were the least likely to engage in risky health behaviours. Compared to married men those who were single were over 2.4 times more likely, those who were cohabiting almost 3 times more likely and those either divorced, separated or widowed over 4.2 times more likely to engage in risky health behaviours^ The finding that marital status has an impact on men's health behaviours has been explored by Umberson (1992). She argues that differences in health status between married and unmarried men can be largely accounted for in Durkheimian tenns in relation to differences in social integration. In a large-scale survey she explored the 'key mechanism' of social control and found that women were significantly more likely to influence the health behaviours of their spouses than vice versa. It was of interest, however, that in our analysis the 'protective' effect of marriage was not replicated amongst those who cohabit. Clearly, this finding needs to be explored in further research. We might speculate however that the decision to cohabit may well be indicative of a set of norms and values that are very different from those found amongst married couples. Under such circumstances it might be that the social-control function is less pronounced. Dependent children
After controlhng for all the other variables the impact on the odds of engaging in risky health behaviours of having a dependent child under the age of 16 in the household vanishes for men, although it was evident in © Blackwell Publishers Ltd/Editorial Board 1995
Smoking and heavy drinking amongst British middle classes 675 the bivariate results. However, for women the relationship is maintained. Thus, for men the presence of a dependent child has no influence upon their odds, whilst for women the odds of engaging in risky health behaviours are significantly reduced. However, this effect was largely due to reductions in the odds of drinking above recommended levels because when we ran a bivariate logistic regression on the odds of smoking (not reported here) the presence of dqwndent children had no influence. In some ways this was a surprising finding because research amongst women more generally has concluded that the presence of children is associated with a greater likelihood of smoking (HEC, 1986; OPCS, 1990). Our results indicate that there may well be an interaction between the propensity to smoke, the presence of children and social class (see also Graham and Hunt (1994: 85)). Education After controlling for all the other variables there is an association for women but not for men. Women with some form of higher education are significantly less likely to engage in risky health behaviours than are those with no qualifications. This may be due to the effect of the relatively poor social conditions experienced by some unqualified women within the employers and managers SEG who, although classified into the middle class, are more likely to experience 'working class-like' conditions of physical and psycho-social health (Graham and Hunt, 1994: 85). This finding is also consistent with the conclusions of Savage et al. (1992: 112) that higher levels of educational attainment are associated with a concern for fitness and health amongst the middle classes. However, it is not clear why this relationship should only hold for women and not for men. Hours worked in paid employment After controlling for all of the other variables there is a relationship between hours worked and the odds of indulging in risky health behaviours for women. For men there is no association. For those women in paid employment the number of hours worked was also entered as a continuous variable. This showed a highly significant increase in the odds of risky health behaviours the greater the number of hours worked. Indeed, for those women who were categorised as engaging in risky health behaviours the mean number of hours worked was 43.0 whilst for those who were not it was 34.6 (p < 0.001). In order to investigate the effect of working as opposed to not working in paid employment we had to group the number of hours worked into 'full-time' (35 hours or more per week), 'part-time' (1 to 34 hours per week) and 'not working'. Using this categorisation suggests that women working part time are significantly less likely to engage in risky health behaviours compared to those working full time. Interestingly those not working did not significantly differ from those working full time, although the results are suggestive of a decrease '0 Blackwell Publishers Ltd/Editorial Board i995
676 Roger Burrows and Sarah Ncttleton in the odds. Of those women who are in paid employment the greater the number of hours they work the greater their odds of engaging in risky health behaviours. Class background After controlling for all of the other variables the impact of the sodal class background of the respondent's father has no effect on the odds of risky health behaviours for women. For men however, the impact is profound. Those from manual backgrounds who have been socially mobile into the middle classes are significantly less hkely to engage in risky health behaviours. Those who have been most mobile into the middle class have the lowest odds of risky health behaviours. The influence of the experience of social mobility into the middle class on decreasing the odds of risky health behaviours for men is a robust finding which requires further research. One might posit that those who move into the middle class wili tend to take on its dominant cultural characteristics. It may also be the case that such men arc keen culturally to distance themselves from their social class of origin. Followers of the health 'selection' thesis might suggest that men are upwardly mobile precisely because they do not partake in risky healthy behaviours. However, the fact that those middle class men who have remained within their class of origin have a greater odds of engaging in risky health behaviours would, on. the face of it, undermine such a claim. In a separate analysis we discovered that professional male smokers drink significantly more units of alcohol per week on average than smokers in any other SEG. Whilst male non-smokers in the professional SEG drink an average of only 15.0 units per week, smokers in the SEG drink an average of 27.0 units per week. Region After controlling for all the other variables the impact on the odds of engaging in risky health behaviours of geographical location has no impact on the odds for women, but living in Greater London significantly increases the odds of such behaviours for men. The same effect is also evident in a less pronounced and statistically insignificant fonn in the rest of the South East region. This finding is consistent with the results reported by Savage et al. (1992) who report distinctive pattems of healthrelated consumption in Greater London compared to the rest of the country (of which more below). Discussion One might assume that people who are materially advantaged and who have access to a range of resources engage in risky health behaviours as a result of 'free choice'. However, our analysis has demonstrated that even under conditions of such relative autonomy there are clear social - indeed structural - correlates of such 'choices'. As Davison et al. (1991: 3) put it
