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Factors associated with health behaviour among mothers of lower socio-economic status: A British example
SOC.Sci. Med. Vol. 36, No. 9, pp. 1137-1144, 1993 Printed in Great Britain. All rights reserved
Copyright
0
0277-9536193 $6.00 + 0.00 1993 Pergamon Press Ltd
FACTORS ASSOCIATED WITH HEALTH BEHAVIOUR AMONG MOTHERS OF LOWER SOCIO-ECONOMIC STATUS: A BRITISH EXAMPLE ROISIN PILL’, ‘Department
T. J. PETERS’*
and M. R. ROBLING’
of General Practice and 2Department of Medical Computing Statistics, University College of Medicine, Heath Park, Cardiff CF4 4XN, Wales, U.K.
of Wales
Abstract-The Health and Lifestyle Survey is the first survey in the U.K. to compare with the databases available in North America. For the first time detailed information on the health status, beliefs, attitudes and behaviour of a representative sample of the British population is available to compare with the findings drawn from smaller locally based samples. Here the focus is on the factors associated with the performance of more low-risk health behaviours among mothers of low socioeconomic status (social class IV and V), specifically on whether the findings from a South Wales survey could be general&d to the equivalent group in a national sample. The outcome measure used was the Health Practices Index, developed by the Alameda County Researchers. Seventeen factors were modelled, using multi-way analyses of variance, to produce a final set of statistically independent factors related to health behaviour. The most striking findings were the importance of the association between type of tenure and health behaviour in both the local and the national sample for this social class group; the lack of any association between education and health behaviour in the national sample; the failure, now well recognised, to find statistically independent associations between measures of attitudes/beliefs and health behaviour. Finally, the implications of the results are discussed in the light of recent and current trends in health education and promotion. Key words-health United Kingdom
behaviour,
health
practices
index,
INTRODUCTION
Much
of
the
theoretical
and
empirical
work
into
in recent decades has been dominated by research carried out in North America. Research on this topic in Britain tends to have been smaller scale and more qualitative in nature. Indeed, until recently there was no national data base to compare with the nationwide studies in the U.S.A. and Canada [l, 21. This situation has changed with the completion of the Health and Lifestyle Survey [3] which provides data on the health knowledge, attitudes to health, lifestyle and health status of a national sample survey of over 9000 men and women aged 18 years and over living in private households in England, Wales and Scotland. The starting point for the research on which this paper is based was the realisation that the Health and Lifestyle Survey (HALS) offered a unique opportunity to explore the nature and correlates of health behaviour in a British sample, testing not only the theoretical insights and empirical findings of American research but also the findings drawn from smaller locally based British samples [4-71. The rich data to be found in the HALS enables the distribution and patterning of a range of health-related behaviours to health
behaviour
*Present address: Health Care Evaluation Unit, Department of Epidemiology, Public Health Medicine, University of Bristol, Bristol BS8 ITH, U.K..
low socioeconomic
status,
tenure,
education,
be studied for a variety of population groups. Furthermore, within each group, it is also possible to explore which socio-demographic characteristics, attitudes and beliefs are linked to the performance of particular individual behaviours or sets of behaviours. This approach has dominated much of the research into health behaviour for the past decade and follows the traditional epidemiological model of research using survey techniques for data collection and quantitative methods for analysis. As a research strategy it has much to commend it to those interested in the promotion of health and who wish to use descriptive data to inform their interventions. In order to design more effective programmes it is necessary to be able to identify target groups or individuals who need special attention. Basic information on the relative frequer :y with which health-related behaviours are practised can provide this. Moreover, it seems plausible that information on the factors related to health behaviour could well provide insight into the determinants of health behaviour. At the very least, evidence of systematic variation may provide clues for further experimental work on the direction of causality and guidance about potential ‘levers’ that could be the focus of intervention evaluations. The focus of this paper is the health behaviour of a national sample of mothers of lower socio-economit status and the factors (socio-demographic, characteristics, attitudes and beliefs, environmental)
1137
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ROBIN PILL e/ al.
that best explain the performance of more low-risk health behaviours. The choice of this particular subgroup was determined by earlier studies on a sample of working-class mothers in Cardiff, S. Wales [4-61 and the desire to see whether the findings from this local study could be generalised. In this local survey working class mothers only were studied since:
occupation or previous occupation, the conventional measure produced clearer trends for most ‘lifestyle’ characteristics such as levels of family income, housing and even behaviours such as diet and social activities [8]. It was for this reason that the RGSC classification was principally used in her investigations and likewise for the analyses presented here.
(9 women
Measures used
with children are amongst the most frequent users of primary care services and are therefore more accessible for planned interventions; (ii) mothers are key figures whose health habits and daily behaviour are likely to influence the health of their families as well as their own health status; groups have (iii) women from lower socio-economic traditionally been seen as posing greater problems for health professionals and educators because of their reluctance to undertake preventive activities or modify poor health practices. Analysis of the data from the original Cardiff study showed that five factors explained approximately 10% of the variance in the measure of health behaviour used. These were: being married; having received further education or training; perceiving more relatives as available for support; being in paid employment and having a higher score on a scale designed to measure the importance of lifestyle choices for health status. The specific aim was therefore to find out whether the factors that provided the best explanation of variation in health behaviour for the Cardiff sample could be generalised to the equivalent group in the national sample-that is lower working class women with children.
METHODS
The sample The genera1 criteria for sample selection from the 9003 adults in the HALS data set were based on age, number of dependent children and social class. The first subset consisted of women aged between 20-45 years who had at least one child under 17 living at home (.” = 1671). Then those women classified as Registrar General Social Class IV or V were further selected out to give a final sample of 360. Socio-economic status was recorded in the HALS using both socio-economic group and the Registrar General’s classification of social class (RGSC). This classifies married women by their husband’s occupation, widowed by ex-husbands occupation and single and divorced women by their own occupation. Use of this classification for married women has been criticised on the grounds that it ignores the women’s own qualifications/employment status. However, using the HALS data, Blaxter reported that compared with a classification based on the women’s own
(a) The outcome variable. The outcome measure (dependent variable) used to represent health behaviour was the Health Practice Index (HPI). the same measure that had been used in the earlier Cardiff studies. The Health Practices Index is unique in that it is based on research carried out in Alameda County in the U.S.A. which has looked at the relationship of everyday health behaviour and health status with subsequent mortality and morbidity over a period of twenty years and more [9]. Seven health-related behaviours were chosen by the American researchers to form the index on the basis that they were each important and independent prcdictors of mortality risk at a 5-year follow up. On the same basis each behaviour was then dichotomised into ‘low risk’ or ‘high risk’ with respondents scoring either I or 0 respectively. In detail, a point was awarded in the HP1 for each of the following low-risk practices: never having smoked; no/moderate use of alcohol; regular exercise; eating breakfast regularly; not snacking between meals; regularly sleeping 7 -8 hr each night and being the correct weight for one’s weight. Hence the higher the score on the index (range O-7) the better the individual’s health bchaviour and the greater his/her chances of longevity and of delaying the deterioration of physical health. Furthermore, the American researchers were able to demonstrate that the association between HP1 and mortality was independent of a wide range of factors including self-reported physical health status at the time of the survey, year of death, socio-economic status, race, obtaining medical and dental checks and many psychological factors. The advantages of the HP1 for our purposes was that it is a well-validated summary measure of health behaviour much used in the U.S.A. Previously it had only been used on small samples in the British context but the detail collected in the HALS survey allowed the index to be constructed so that, for the first time, comparable data was available for a British national sample. (Full details of how the HP1 was constructed from the HALS data are available on application to the authors.) (b) The explanatory variables. A set of 17 factors were selected for modelling as potential explanatory (or independent) variables on the grounds of theoretical interest and previous research work. The working assumption adopted in the earlier local studies was that attitudes, modified by a number of other factors which could act either as barriers or facilitates. influenced the performance of health behaviour. It
Health behaviour among mothers of lower socio-economic status was also assumed that attitudes, beliefs and behaviour would be largely consistent and that the attitudes held would be determined by past experience and socialisation. Associations were therefore expected between socio-demographic variables such as education, religious commitment and socioeconomic status of the household in which the respondent was brought up and the attitudes being expressed. Finally, it was felt that social networks could act to reinforce positive health practices and therefore measures of contact and support were also included. The explanatory variables in the present analyses were thus considered in six main groups: presence or absence of limiting disease (level of disability); socioeconomic factors; basic socio-demographic characteristics; measures of social network and support; measures of belief and attitude; religious attendance. For the individual variables, the operational definitions adopted here were partly based on those used in the earlier local studies and partly determined by the data available in the HALS survey. Along with the groups used, the definitions are given in detail in the Appendix. The indices measuring aspects of social support and presence or absence of disease and/or impairment were drawn directly from the definitions and analyses used by Blaxter and colleagues in the publications on the original HALS data. These include: extent of disease/disability [8, p. 2441; social contact represented by the extent to which an individual has had contact of several forms with family and friends [3, p. 1551; perceived social support measured by the degree of support an individual perceived that they received from family (including the extended family) or from friends if no family was reported [8, p. 2471. Apart from the detail of the definitions and how they are derived, several of the variables chosen need further comment. The Salience of Lifestyle indices (SLI) were based on a measure developed and validated in the earlier work on the local Cardiff sample [lo]. Salience of Lifestyle was defined as the relative importance that an individual attaches to the concept that individual lifestyle choices can affect future health status. Operationally this was measured by the extent to which respondents mentioned lifestyle factors spontaneously in the course of general discussion, using open questions about illness causation and ways of promoting health. (A lifestyle factor was defined as any mention of food, exercise, personal habits or behaviour where the individual has some control over whether or not it is performed.) In the Cardiff studies quantification was achieved by awarding 1 point for any spontaneous mention of factors such as diet, exercise, smoking and drinking in the replies given to five key questions couched in general terms. The same general approach was used to construct the indices for the present analysis since the HALS survey used four of these five questions. However, two separate indices were produced in the
1139
HALS survey since the questions were put to the respondents in personal as well as general terms. In all instances, high scores represent those who view lifestyle choices as important for health. The reason for the inclusion of the presence or absence of disease and/or impairment stems from the recognition that current health behaviour must to some extent be affected by the presence of ‘limiting’ disease. This was clearly documented in the analysis of the original HALS survey. For example, those with particular diseases may have been told to stop smoking or drinking alcohol and those with conditions which limit mobility or energy are unlikely to take part in sporting activities [8, p. 1881. The inclusion of housing tenure among the sociodemographic variables is based on the growing evidence of the value of this measure in the study of inequalities in health [1 1, 121. Three tenure groups are usually identified, depending on whether the house is owner occupied, privately rented or rented from a local authority, and this reveals persistent differences in mortality and morbidity [13]. Traditionally such differences have been explored using measures of occupational class but increasingly measures based on assets, such as house and car ownership, are being used for this purpose. Like class they are being used as indirect indicators of wealth and command over resources. Housing tenure has proved particularly useful in discriminating within occupational class samples; owner-occupiers have lower mortality than private tenants who, in turn, have lower mortality than local authority tenants [I 11. Given these findings the relationship between tenure and health behaviour is worth investigating. In the local Cardiff studies of Social Class IV and V mothers, two categories of tenure were employed: owner-occupier and local authority tenant. In the present analysis of these social class groups in the national HALS sample the same two categories were used since the number of private tenants was very small. Statistical methodology Although there is obviously an underlying continum for some of the explanatory variables given in the Appendix (for example, income and age), in many instances the information from the HALS was such that only categories were available (for example, of total household income). The treatment of the explanatory variables in the present analysis in part reflects this, as well as being influenced by the somewhat skewed distributions of a number of the indices-in particular those of social network and support. Furthermore, especially for the (basically arbitrary) ordinal scales and for the (quantitative) age variable, we neither expected linear relationships nor wished to complicate interpretation by introducing quadratic and possibly higher order polynomial terms. Notwithstanding the loss of information in a few instances, then, all the explanatory variables
1140
ROBIN PILL et al.
were used in the (categorical) form as shown in the Appendix. The first stage of the analysis therefore involved modelling each explanatory factor in turn with the outcome variable, HPI, using on a one-way basis the analysis of variance procedure (ANOVA) of the SPSS-X package [14]. Then, to investigate possible confounding, significant factors from the one-way models were analysed using multiway analysis of variance in the following structured procedure. The factors selected for this second stage were ordered into their groups of related factors as shown in the Appendix. The factors within each group were then modelled together to adjust for any confounding between related variables (the ‘within-group’ analyses). Significant factors from each group were then modelled with those of other groups to produce a final set of statistically independent factors (the ‘across-group’ analyses). The procedure followed here was first to combine Groups I and II. then to introduce Group III and so on until all groups were covered. Throughout these analyses a cut-point for the P-value of 5% was used to indicate statistical significance. The order in which the groups were considered was not intended to reflect any rigid theoretical hierarchy. It is most unlikely that the final selection will be affected by the ordering since in the across-group modelling, variables remaining within any of the groups after being modelled separately were able to confound factors in any other group. RESULTS
The distribution of the HP1 scores for the 360 mothers categorised as Social Class IV or V was not noticeably skewed (mean score = 4.06; standard deviation = 1.23). The modal and median score, obtained by 119 women, was 4. Nobody registered a score of less than 1 and there were 10 missing values. When the scores for the individual items are examined 97% of the women reported drinking 15 units of alcohol or less per week; 77% reported taking regular exercise; 67% had 7 or 8 hours sleep every night; 57% ate breakfast regularly; 53% were the correct weight for their height; 36% claimed never to have smoked; and 22% not to ‘snack’ between meals on a regular basis. Table 1 shows the results of the first stage of analysis using the one-way models. Five (29%) of the 17 factors were found to be individually significantly associated with the health practices score at the 5% level. The five factors-namely, tenure, own work status, marital status, Perceived Social Support Index and Salience of Lifestyle (personaltwere ordered into their (pre-determined) three groups for the second stage of the analysis. The first group (Group II) represented socio-economic factors and included work status and tenure. Group IV contained the social support variables of marital status and
Table I. The statistical significance of the relationships between HP1 and each of 17 so&-demographic and attitudinal variables amongst social class IV, V wanen (n = 360) df
Factor Disability Education T‘Z”UX Income Work status (partner) Work status (self) Age No. children under 5 No. children under I7 No. in household Crowding index Marital status PSSI Social contact index SLI (personal) SLI (general) Religious attendance ***p
F-ratio
I I I
0.0 I.8 5.6 2.8 0.2 3.5 1.5 0.6 0.1 0.0 0.3 4.7 5.0 2.3 5.4 2.1 I.5
I I 2 2 2 2 I 2
I I I
I 3 I
P-value
0.99 0.18 0.021 0.09 0.66 0.03’ 0.22 0.57 0.89 0.98 0.73 0.03’ 0.03’ 0.13 0.02* 0.10 0.23
i 0.001.
**p < 0.01. ‘P
< 0.05.
Otherwise P z 0.05.
Perceived Social Support whilst the attitudinal variable Salience of Lifestyle (personal) was the sole factor from Group V. Within -group Group
II:
Group
IV:
analyses
and work status. Prior to controlling each of these two factors for the other one, higher health practices scores were associated with mothers in part-time as opposed to full-time work or those not in paid employment. The 118 mothers in part-time work had a mean HP1 score of 4.29 compared with means of around 3.9 for mothers in the other two categories respectively (Table 2). Relatively higher HP1 scores were also found for mothers living in owner-occupied housing. Controlling each factor for the other resulted in the relationship between work status and HP1 becoming statistically non-significant with a reduction in Fratio from 3.5 (P < 0.05) to 3.0 (Table 3, column B). At the same time tenure remained significant; this factor was then retained as the only Group II factor to be carried through for further (across-group) analysis. support.
Tenure
Marital
status
and
perceived
social
As shown in Table 2, a relatively high mean HP1 score was found for the 268 married women (mean = 4.1) and those perceiving a higher amount of social support from their family or friends (4.2). When the two social support factors were modelled together both remained significantly associated with HP1 at the 5% level (Table 3, column B); both factors were thus retained for further analysis. Group V: Salience of Lifestyle Qersonal). Only one factor remained in this group following the oneway analyses, with significantly higher HP1 scores observed amongst mothers who saw personal lifestyle choices as relevant to their subsequent health status (mean = 4.5 from Table 2). The SLI (personal) factor
Health
hehaviour
among
mothers
of lower socio-economic
status
1141
Table 2. Mean HP1 scores across the categories of the factors individually associated with HPI for 360 women in social class IV, V
frequency
Mean HP1 score
95% CI (lower limit, upper limit)
141 208 ?@
40 60
4.25 3.95
(4.05.4.45) (3.79.4.10)
44 118 -175
13 35 52
3.86 4.29 3.96
(3.49.4.24) (4.07,4.50) (3.79.4.13)
17
23
4.14 3.82
(3.99.4.28) (3.58.4.05)
Total
268 82 350
42 58
3.90 4.19
(3.71,4.10) (4.03,4.35)
Total
146 202 5;ls
Salience of Lifestyle (personal) Low High Total
309 41 m
88 12
4.01 4.46
(3.88,4.14) (4.12.4.81)
Factor Tenure Owns Rents Total Work status (self) Full-time Part-time Not in paid employment Marital status Married Other
Perceived social support LOW High
was therefore modelling.
retained
Relative
n %
for
the
across-group
Across-group analyses
The first step of the across-group analyses was to control support variables of Group IV for tenure, the remaining significant factor from Group II (Table 3, column C). Neither marital status nor PSSI was significant controlling for tenure, either singly or jointly. Within the chosen hierarchical framework of the groups of factors, both the social support variables were therefore omitted from further modelling. Finally, Salience of Lifestyle (personal) was entered in the analysis of variance model with tenure (Table 3, column C). Both tenure and SLI (personal) remained significant independently of one another, as depicted in Fig. 1. DISCUSSION
In considering these findings, the primary question examined is whether the two factors associated with better health behaviour, as measured by high scores on HPI, in this national sample of Social Class IV Table 3. Controlling
for confounding
amongst
and V mothers are the same as those identified in the earlier Cardiff studies on local samples. Where this is not the case, secondary questions arise as we consider possible explanations for any discrepancies. Direct comparison with the findings of the earlier Cardiff studies posed certain problems since the methods of analysis used were somewhat different, and moreover the operational definitions of a number of the explanatory variables used were perforce not always identical. For example, the Cardiff studies employed a stepwise modelling approach (that is, the selection of variables purely on statistical grounds) rather than the structured approach employed here. In addition, multiple regression was used (thus assuming linear relationships) and the tenure variable was not included in the analysis [4]. It was therefore decided to repeat analysis of the Cardiff data set but this time to include tenure and to use the structural analysis of variance modelling technique described above. Using one-way analysis of variance, five factors were initially statistically significant in the Cardiff data-namely, tenure, education, Salience of Lifestyle (general), support from relatives and work status (self). The overlap with the five the five initially
significant Adjusted
Factor
Grouu II IV V
Tenure Work status (self) Marital PSSI
status
SLI (personal)
l**f < 0.001. l*f < 0.01. ‘P < 0.05. Otherwise P > 0.05.
df
I
Unadjusted F-ratio A
(within groups) B
5.6* 3.5.
4.6* 3.0
I
4.78 5.0*
4.0’ 4.1’
I
5.4’
5.4’
2
1
factors (n = 360) F-ratio (final across-groups) C 4.2’
3.9’
1142
ROBIN POLL et al.
(a) 5.0
-
a,
4,8
_
; $
4.6
-
;;:
4.4
-
’ 2 5
4.2
-
4.0
-
F = 4.2 (p
*\;
Adjusted Unadjusted
3.8 I
I
3.6
Rents
OWllS
(b) 5.0 2 0 $
4.8
-
4.6
-
z z
4.4
--
4.2
--
4.0
--
3.8
--
,” 0 E
means
3.6
Tenure F = 3.9 (p
means
K;“i.,;:“,,,
I Low SLI
High (personal)
Fig. 1.Mean Health Practices Index scores by (a) tenure and (b) Salience of Lifestyle (personal) both before and after adjustment for each other. (HALS) factors in Table. 2 is striking. Furthermore, after controlling for confounding, three factors remained independently associated with HP1 in the Cardiff data set: tenure, education and perceived support from relatives. This compares with tenure and SLI (personal) in the present analysis of the national data. The importance of tenure in both the national and local samples of Social Class IV and V mothers is thus upheld. Remaining to be considered, however, are (a) the failure of education to appear at any stage in the present analysis of the national data and (b) the inconsistencies in terms of SLI (personal) and perceived support. For Britain it has generally been assumed that education and income would be positively associated with low risk health behaviour (both across and within the broad categories of the Registrar General’s Social Classes) and, moreover, that the strength and direction of the associations would be dependent upon the actual behaviour under consideration. Indeed, one of the more consistent findings in this area of research has been that more positive health behaviour, including composite indices of health behaviour, is positively associated with higher socio-economic status [15]. Measures of socio-economit status have usually included education along with occupation and/or income-as, for example, in the original Alameda County studies [9]. Comparatively few studies have attempted to assess the relative contributions of education, income and occupation but, where this has been done, education usually emerges as the most reliable correlate [l&18]. Following this pattern, education was found to be significantly associated with higher HP1 scores for the
Cardiff samples of Social Class IV and V mothers and it is therefore surprising that no such relationship was found in the present analyses of the equivalent national group drawn from the HALS data. The mean HP1 score in the national sample was 4.0 for those with no qualifications (N = 214) compared with 4.2 for those with qualifications (N = 135). There was therefore not even a suggestion of a difference, and the lack of statistical significance is not attributable to insufficient numbers in the two categories. What is noticeable about both these local and national samples of lower social class groups is the high proportion who left school as soon as they could and obtained no further academic or vocational qualifications. This categorisation has clearly discriminated within the Cardiff sample-the 23% who had further education and training obtained significantly higher HP1 scores than the remainder of the sample. In order to make the operational definitions as comparable as possible the present analysis of the HALS data also dichotomised into those who did or did not have any qualifications. In order to check the possibility that this might have concealed a trend depending on the type of qualification obtained, the data were also analysed by the highest qualification reported. The following results were obtained: 62% of the HALS sample of Social Class IV and V mothers had no qualifications and their mean HP1 score was 4.0; the 23% who had at least one O-level or equivalent had a mean score of 4.2; the 9% with a vocational qualification had a mean score of 4.3; the 6% with at least an A-level or equivalent had a mean score of 4.0. The conclusion must be that there is no evidence of any differences. Furthermore, examination of the detailed relationships of education to the individual practices comprising HP1 in this sample revealed very little in the way of (positive) associations (with the exception of eating breakfast regularly). It was therefore not the case that negative and positive associations had simply cancelled each other out across the different practices. The failure to find any relationship between education and HP1 for the social class IV or V mothers in the HALS sample is thus not an artefact. It remains to account for the inconsistency with regard to perceived support from relatives and SLI (personal). In the local sample two sepnrate measures of perceived support were used, one for relatives and one for friends, whereas the national sample asked first about relatives, and, if none were reported, moved on to friends. Also, given the questions posed in the local study, only a general Salience of Lifestyle Index could be constructed, which would a priori be less likely than a personal version to be associated with a self-reported index of health behaviour. In contrast to education, therefore, both inconsistencies could well have arisen as a result of differences in the
Health behaviour among mothers of lower s&o-economic operational definitions used for the local and national samples. What is most striking in the comparison between the Cardiff study and the HALS data is the importance in both samples of the association between the type of tenure and health behaviour. Mothers in rented accommodation (predominantly local authority tenants) are significantly less likely than those buying their own houses to report low risk health behaviours. We investigated whether the strength of the association between tenure and HP1 in the HALS sample rested on a marked difference between owners and renters for just one or two items in the HPI, or whether the difference was observed for all the items. In the event, it appears that owners are significantly more likely to report never having smoked and eating breakfast regularly and less likely to report taking regular exercise. Housing tenure has again proved its value as a powerful discriminator within occupational classes (such as the Registrar General’s classification), this time through its association with health behaviour. Significant associations found in a cross-sectional survey cannot, of course, be interpreted as evidence of causation. It is clear that tenure is more than a simple measure of type and standard of housing [ 11, 131; rather, like social class its value lies in the fact that it reflects the influence of a wide range of socio-economic factors. Any hypotheses put forward to explain the association between tenure and health behaviour would therefore need to set out in detail the aspects of social circumstances and environment which might account for the observed variation in reported health behaviour scores. It may well be that further analyses along these lines might succeed in still explaining only a small part of the observed variation, as has been the experience of similar attempts to disentangle the various components of social class in relation to health behaviour [ 161. Different approaches, using more in depth and qualitative strategies, may therefore be needed to reach a better understanding of the constraints on health-related behaviour within particular social groups. Notwithstanding this, our findings are in accordance with much of the recent work on health-related behaviour that has identified sociodemographic variables as the dominant factors rather than attitudes and beliefs [8, 19,201. This has obvious implications for health promotion since, as noted in the introduction, the assumptions behind the research strategy were that systematic information on the factors associated with health behaviour within population groups would provide guidance for research in the direction of causality and the ‘levers’ that might form the basis of intervention programmes. Whilst our findings certainly suggest further direction for research into causation, the variables finally selected by the analysis are not readily susceptible to modification at the level of the individual. In turn this poses
status
1143
a major challenge for those whose prime concern is the modification of risk factors. As we have stressed throughout, it should also be noted that this analysis was applied to a very specific sub-group of the population. The question remains as to whether the factors identified as significantly and independently related to health behaviour for Social Class IV and V mothers as the same for mothers of the same ages in the other social class groups. This will be addressed in another paper. Acknowledgements-Our thanks are due to Professor N. C. H. Stott for his advice and encouragement and to Rosy Allcott for her patience in producing endless drafts.
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19. Anderson R. The development of the concept of health behaviour and its application in recent research. In Health Behaviour Research & Health Promotion (Edited by Anderson R. et al.), p. 22. Oxford University Press, Oxford, 1988. 20. Research Unit in Health & Behavioural Change. University of Edinburgh. Changing the Public Health. Wiley, Chichester, 1989.
17. Gray R. M., Kesler J. P. and Moody P. M. The effects of social class and friends expectations on oral polio vaccination participation. Am. J. Publ. Hlth 56, 2028-2032, 1966. 18. Gottlieb M. H. and Green L. W. Life events, social network, lifestyle and health: an analysis of the 1979 National Survey of Personal Health Practices and Consequences. Hlth Educ. Q. II, 91-105, 1984.
APPENDIX Explanatory
Variables
used in the Analyses
Group
Variable
Definition
I
Level of disability
11
Education
No physical disability vs those with any degree of disability. Those with some form of educational or vocational qualification vs those with no formal qualifications.
11
Tenure
II
Income
II II
Work Work
III III III III
Age
III
Crowding
IV IV
Marital status Perceived social support index (PSSI) Social contact index Salience of Lifestyle (personal) Salience of Lifestyle (general)
IV V V VI
status status
(partner) (self)
No. children <5 No. children < 17 Number in household
Religious
index
attendance
Those living in privately owned property vs those in rented accommodation (either private or council). Total household income less than E230 per month vs f230 or more. Employed vs not employed. Full time/vs part time/vs not in paid employment. 20-39/30-39140-45 years. None/one/two or more. One/two/three or more. Total living in household (including respondent) up to 4 vs 5 or more. Number in household/total number of living rooms and bedrooms (< l/l to 1.49/1.5+). Currently married vs other. Some lack of support (score i 2 1) vs no lack of support (21). High score (IO+) vs low score (O-9). High score (3,4) vs low score (O-2). O/1/2/3/4. Has attended church/place of worship within last fortnight vs has not done so.
Copyright
0
0277-9536193 $6.00 + 0.00 1993 Pergamon Press Ltd
FACTORS ASSOCIATED WITH HEALTH BEHAVIOUR AMONG MOTHERS OF LOWER SOCIO-ECONOMIC STATUS: A BRITISH EXAMPLE ROISIN PILL’, ‘Department
T. J. PETERS’*
and M. R. ROBLING’
of General Practice and 2Department of Medical Computing Statistics, University College of Medicine, Heath Park, Cardiff CF4 4XN, Wales, U.K.
of Wales
Abstract-The Health and Lifestyle Survey is the first survey in the U.K. to compare with the databases available in North America. For the first time detailed information on the health status, beliefs, attitudes and behaviour of a representative sample of the British population is available to compare with the findings drawn from smaller locally based samples. Here the focus is on the factors associated with the performance of more low-risk health behaviours among mothers of low socioeconomic status (social class IV and V), specifically on whether the findings from a South Wales survey could be general&d to the equivalent group in a national sample. The outcome measure used was the Health Practices Index, developed by the Alameda County Researchers. Seventeen factors were modelled, using multi-way analyses of variance, to produce a final set of statistically independent factors related to health behaviour. The most striking findings were the importance of the association between type of tenure and health behaviour in both the local and the national sample for this social class group; the lack of any association between education and health behaviour in the national sample; the failure, now well recognised, to find statistically independent associations between measures of attitudes/beliefs and health behaviour. Finally, the implications of the results are discussed in the light of recent and current trends in health education and promotion. Key words-health United Kingdom
behaviour,
health
practices
index,
INTRODUCTION
Much
of
the
theoretical
and
empirical
work
into
in recent decades has been dominated by research carried out in North America. Research on this topic in Britain tends to have been smaller scale and more qualitative in nature. Indeed, until recently there was no national data base to compare with the nationwide studies in the U.S.A. and Canada [l, 21. This situation has changed with the completion of the Health and Lifestyle Survey [3] which provides data on the health knowledge, attitudes to health, lifestyle and health status of a national sample survey of over 9000 men and women aged 18 years and over living in private households in England, Wales and Scotland. The starting point for the research on which this paper is based was the realisation that the Health and Lifestyle Survey (HALS) offered a unique opportunity to explore the nature and correlates of health behaviour in a British sample, testing not only the theoretical insights and empirical findings of American research but also the findings drawn from smaller locally based British samples [4-71. The rich data to be found in the HALS enables the distribution and patterning of a range of health-related behaviours to health
behaviour
*Present address: Health Care Evaluation Unit, Department of Epidemiology, Public Health Medicine, University of Bristol, Bristol BS8 ITH, U.K..
low socioeconomic
status,
tenure,
education,
be studied for a variety of population groups. Furthermore, within each group, it is also possible to explore which socio-demographic characteristics, attitudes and beliefs are linked to the performance of particular individual behaviours or sets of behaviours. This approach has dominated much of the research into health behaviour for the past decade and follows the traditional epidemiological model of research using survey techniques for data collection and quantitative methods for analysis. As a research strategy it has much to commend it to those interested in the promotion of health and who wish to use descriptive data to inform their interventions. In order to design more effective programmes it is necessary to be able to identify target groups or individuals who need special attention. Basic information on the relative frequer :y with which health-related behaviours are practised can provide this. Moreover, it seems plausible that information on the factors related to health behaviour could well provide insight into the determinants of health behaviour. At the very least, evidence of systematic variation may provide clues for further experimental work on the direction of causality and guidance about potential ‘levers’ that could be the focus of intervention evaluations. The focus of this paper is the health behaviour of a national sample of mothers of lower socio-economit status and the factors (socio-demographic, characteristics, attitudes and beliefs, environmental)
1137
1138
ROBIN PILL e/ al.
that best explain the performance of more low-risk health behaviours. The choice of this particular subgroup was determined by earlier studies on a sample of working-class mothers in Cardiff, S. Wales [4-61 and the desire to see whether the findings from this local study could be generalised. In this local survey working class mothers only were studied since:
occupation or previous occupation, the conventional measure produced clearer trends for most ‘lifestyle’ characteristics such as levels of family income, housing and even behaviours such as diet and social activities [8]. It was for this reason that the RGSC classification was principally used in her investigations and likewise for the analyses presented here.
(9 women
Measures used
with children are amongst the most frequent users of primary care services and are therefore more accessible for planned interventions; (ii) mothers are key figures whose health habits and daily behaviour are likely to influence the health of their families as well as their own health status; groups have (iii) women from lower socio-economic traditionally been seen as posing greater problems for health professionals and educators because of their reluctance to undertake preventive activities or modify poor health practices. Analysis of the data from the original Cardiff study showed that five factors explained approximately 10% of the variance in the measure of health behaviour used. These were: being married; having received further education or training; perceiving more relatives as available for support; being in paid employment and having a higher score on a scale designed to measure the importance of lifestyle choices for health status. The specific aim was therefore to find out whether the factors that provided the best explanation of variation in health behaviour for the Cardiff sample could be generalised to the equivalent group in the national sample-that is lower working class women with children.
METHODS
The sample The genera1 criteria for sample selection from the 9003 adults in the HALS data set were based on age, number of dependent children and social class. The first subset consisted of women aged between 20-45 years who had at least one child under 17 living at home (.” = 1671). Then those women classified as Registrar General Social Class IV or V were further selected out to give a final sample of 360. Socio-economic status was recorded in the HALS using both socio-economic group and the Registrar General’s classification of social class (RGSC). This classifies married women by their husband’s occupation, widowed by ex-husbands occupation and single and divorced women by their own occupation. Use of this classification for married women has been criticised on the grounds that it ignores the women’s own qualifications/employment status. However, using the HALS data, Blaxter reported that compared with a classification based on the women’s own
(a) The outcome variable. The outcome measure (dependent variable) used to represent health behaviour was the Health Practice Index (HPI). the same measure that had been used in the earlier Cardiff studies. The Health Practices Index is unique in that it is based on research carried out in Alameda County in the U.S.A. which has looked at the relationship of everyday health behaviour and health status with subsequent mortality and morbidity over a period of twenty years and more [9]. Seven health-related behaviours were chosen by the American researchers to form the index on the basis that they were each important and independent prcdictors of mortality risk at a 5-year follow up. On the same basis each behaviour was then dichotomised into ‘low risk’ or ‘high risk’ with respondents scoring either I or 0 respectively. In detail, a point was awarded in the HP1 for each of the following low-risk practices: never having smoked; no/moderate use of alcohol; regular exercise; eating breakfast regularly; not snacking between meals; regularly sleeping 7 -8 hr each night and being the correct weight for one’s weight. Hence the higher the score on the index (range O-7) the better the individual’s health bchaviour and the greater his/her chances of longevity and of delaying the deterioration of physical health. Furthermore, the American researchers were able to demonstrate that the association between HP1 and mortality was independent of a wide range of factors including self-reported physical health status at the time of the survey, year of death, socio-economic status, race, obtaining medical and dental checks and many psychological factors. The advantages of the HP1 for our purposes was that it is a well-validated summary measure of health behaviour much used in the U.S.A. Previously it had only been used on small samples in the British context but the detail collected in the HALS survey allowed the index to be constructed so that, for the first time, comparable data was available for a British national sample. (Full details of how the HP1 was constructed from the HALS data are available on application to the authors.) (b) The explanatory variables. A set of 17 factors were selected for modelling as potential explanatory (or independent) variables on the grounds of theoretical interest and previous research work. The working assumption adopted in the earlier local studies was that attitudes, modified by a number of other factors which could act either as barriers or facilitates. influenced the performance of health behaviour. It
Health behaviour among mothers of lower socio-economic status was also assumed that attitudes, beliefs and behaviour would be largely consistent and that the attitudes held would be determined by past experience and socialisation. Associations were therefore expected between socio-demographic variables such as education, religious commitment and socioeconomic status of the household in which the respondent was brought up and the attitudes being expressed. Finally, it was felt that social networks could act to reinforce positive health practices and therefore measures of contact and support were also included. The explanatory variables in the present analyses were thus considered in six main groups: presence or absence of limiting disease (level of disability); socioeconomic factors; basic socio-demographic characteristics; measures of social network and support; measures of belief and attitude; religious attendance. For the individual variables, the operational definitions adopted here were partly based on those used in the earlier local studies and partly determined by the data available in the HALS survey. Along with the groups used, the definitions are given in detail in the Appendix. The indices measuring aspects of social support and presence or absence of disease and/or impairment were drawn directly from the definitions and analyses used by Blaxter and colleagues in the publications on the original HALS data. These include: extent of disease/disability [8, p. 2441; social contact represented by the extent to which an individual has had contact of several forms with family and friends [3, p. 1551; perceived social support measured by the degree of support an individual perceived that they received from family (including the extended family) or from friends if no family was reported [8, p. 2471. Apart from the detail of the definitions and how they are derived, several of the variables chosen need further comment. The Salience of Lifestyle indices (SLI) were based on a measure developed and validated in the earlier work on the local Cardiff sample [lo]. Salience of Lifestyle was defined as the relative importance that an individual attaches to the concept that individual lifestyle choices can affect future health status. Operationally this was measured by the extent to which respondents mentioned lifestyle factors spontaneously in the course of general discussion, using open questions about illness causation and ways of promoting health. (A lifestyle factor was defined as any mention of food, exercise, personal habits or behaviour where the individual has some control over whether or not it is performed.) In the Cardiff studies quantification was achieved by awarding 1 point for any spontaneous mention of factors such as diet, exercise, smoking and drinking in the replies given to five key questions couched in general terms. The same general approach was used to construct the indices for the present analysis since the HALS survey used four of these five questions. However, two separate indices were produced in the
1139
HALS survey since the questions were put to the respondents in personal as well as general terms. In all instances, high scores represent those who view lifestyle choices as important for health. The reason for the inclusion of the presence or absence of disease and/or impairment stems from the recognition that current health behaviour must to some extent be affected by the presence of ‘limiting’ disease. This was clearly documented in the analysis of the original HALS survey. For example, those with particular diseases may have been told to stop smoking or drinking alcohol and those with conditions which limit mobility or energy are unlikely to take part in sporting activities [8, p. 1881. The inclusion of housing tenure among the sociodemographic variables is based on the growing evidence of the value of this measure in the study of inequalities in health [1 1, 121. Three tenure groups are usually identified, depending on whether the house is owner occupied, privately rented or rented from a local authority, and this reveals persistent differences in mortality and morbidity [13]. Traditionally such differences have been explored using measures of occupational class but increasingly measures based on assets, such as house and car ownership, are being used for this purpose. Like class they are being used as indirect indicators of wealth and command over resources. Housing tenure has proved particularly useful in discriminating within occupational class samples; owner-occupiers have lower mortality than private tenants who, in turn, have lower mortality than local authority tenants [I 11. Given these findings the relationship between tenure and health behaviour is worth investigating. In the local Cardiff studies of Social Class IV and V mothers, two categories of tenure were employed: owner-occupier and local authority tenant. In the present analysis of these social class groups in the national HALS sample the same two categories were used since the number of private tenants was very small. Statistical methodology Although there is obviously an underlying continum for some of the explanatory variables given in the Appendix (for example, income and age), in many instances the information from the HALS was such that only categories were available (for example, of total household income). The treatment of the explanatory variables in the present analysis in part reflects this, as well as being influenced by the somewhat skewed distributions of a number of the indices-in particular those of social network and support. Furthermore, especially for the (basically arbitrary) ordinal scales and for the (quantitative) age variable, we neither expected linear relationships nor wished to complicate interpretation by introducing quadratic and possibly higher order polynomial terms. Notwithstanding the loss of information in a few instances, then, all the explanatory variables
1140
ROBIN PILL et al.
were used in the (categorical) form as shown in the Appendix. The first stage of the analysis therefore involved modelling each explanatory factor in turn with the outcome variable, HPI, using on a one-way basis the analysis of variance procedure (ANOVA) of the SPSS-X package [14]. Then, to investigate possible confounding, significant factors from the one-way models were analysed using multiway analysis of variance in the following structured procedure. The factors selected for this second stage were ordered into their groups of related factors as shown in the Appendix. The factors within each group were then modelled together to adjust for any confounding between related variables (the ‘within-group’ analyses). Significant factors from each group were then modelled with those of other groups to produce a final set of statistically independent factors (the ‘across-group’ analyses). The procedure followed here was first to combine Groups I and II. then to introduce Group III and so on until all groups were covered. Throughout these analyses a cut-point for the P-value of 5% was used to indicate statistical significance. The order in which the groups were considered was not intended to reflect any rigid theoretical hierarchy. It is most unlikely that the final selection will be affected by the ordering since in the across-group modelling, variables remaining within any of the groups after being modelled separately were able to confound factors in any other group. RESULTS
The distribution of the HP1 scores for the 360 mothers categorised as Social Class IV or V was not noticeably skewed (mean score = 4.06; standard deviation = 1.23). The modal and median score, obtained by 119 women, was 4. Nobody registered a score of less than 1 and there were 10 missing values. When the scores for the individual items are examined 97% of the women reported drinking 15 units of alcohol or less per week; 77% reported taking regular exercise; 67% had 7 or 8 hours sleep every night; 57% ate breakfast regularly; 53% were the correct weight for their height; 36% claimed never to have smoked; and 22% not to ‘snack’ between meals on a regular basis. Table 1 shows the results of the first stage of analysis using the one-way models. Five (29%) of the 17 factors were found to be individually significantly associated with the health practices score at the 5% level. The five factors-namely, tenure, own work status, marital status, Perceived Social Support Index and Salience of Lifestyle (personaltwere ordered into their (pre-determined) three groups for the second stage of the analysis. The first group (Group II) represented socio-economic factors and included work status and tenure. Group IV contained the social support variables of marital status and
Table I. The statistical significance of the relationships between HP1 and each of 17 so&-demographic and attitudinal variables amongst social class IV, V wanen (n = 360) df
Factor Disability Education T‘Z”UX Income Work status (partner) Work status (self) Age No. children under 5 No. children under I7 No. in household Crowding index Marital status PSSI Social contact index SLI (personal) SLI (general) Religious attendance ***p
F-ratio
I I I
0.0 I.8 5.6 2.8 0.2 3.5 1.5 0.6 0.1 0.0 0.3 4.7 5.0 2.3 5.4 2.1 I.5
I I 2 2 2 2 I 2
I I I
I 3 I
P-value
0.99 0.18 0.021 0.09 0.66 0.03’ 0.22 0.57 0.89 0.98 0.73 0.03’ 0.03’ 0.13 0.02* 0.10 0.23
i 0.001.
**p < 0.01. ‘P
< 0.05.
Otherwise P z 0.05.
Perceived Social Support whilst the attitudinal variable Salience of Lifestyle (personal) was the sole factor from Group V. Within -group Group
II:
Group
IV:
analyses
and work status. Prior to controlling each of these two factors for the other one, higher health practices scores were associated with mothers in part-time as opposed to full-time work or those not in paid employment. The 118 mothers in part-time work had a mean HP1 score of 4.29 compared with means of around 3.9 for mothers in the other two categories respectively (Table 2). Relatively higher HP1 scores were also found for mothers living in owner-occupied housing. Controlling each factor for the other resulted in the relationship between work status and HP1 becoming statistically non-significant with a reduction in Fratio from 3.5 (P < 0.05) to 3.0 (Table 3, column B). At the same time tenure remained significant; this factor was then retained as the only Group II factor to be carried through for further (across-group) analysis. support.
Tenure
Marital
status
and
perceived
social
As shown in Table 2, a relatively high mean HP1 score was found for the 268 married women (mean = 4.1) and those perceiving a higher amount of social support from their family or friends (4.2). When the two social support factors were modelled together both remained significantly associated with HP1 at the 5% level (Table 3, column B); both factors were thus retained for further analysis. Group V: Salience of Lifestyle Qersonal). Only one factor remained in this group following the oneway analyses, with significantly higher HP1 scores observed amongst mothers who saw personal lifestyle choices as relevant to their subsequent health status (mean = 4.5 from Table 2). The SLI (personal) factor
Health
hehaviour
among
mothers
of lower socio-economic
status
1141
Table 2. Mean HP1 scores across the categories of the factors individually associated with HPI for 360 women in social class IV, V
frequency
Mean HP1 score
95% CI (lower limit, upper limit)
141 208 ?@
40 60
4.25 3.95
(4.05.4.45) (3.79.4.10)
44 118 -175
13 35 52
3.86 4.29 3.96
(3.49.4.24) (4.07,4.50) (3.79.4.13)
17
23
4.14 3.82
(3.99.4.28) (3.58.4.05)
Total
268 82 350
42 58
3.90 4.19
(3.71,4.10) (4.03,4.35)
Total
146 202 5;ls
Salience of Lifestyle (personal) Low High Total
309 41 m
88 12
4.01 4.46
(3.88,4.14) (4.12.4.81)
Factor Tenure Owns Rents Total Work status (self) Full-time Part-time Not in paid employment Marital status Married Other
Perceived social support LOW High
was therefore modelling.
retained
Relative
n %
for
the
across-group
Across-group analyses
The first step of the across-group analyses was to control support variables of Group IV for tenure, the remaining significant factor from Group II (Table 3, column C). Neither marital status nor PSSI was significant controlling for tenure, either singly or jointly. Within the chosen hierarchical framework of the groups of factors, both the social support variables were therefore omitted from further modelling. Finally, Salience of Lifestyle (personal) was entered in the analysis of variance model with tenure (Table 3, column C). Both tenure and SLI (personal) remained significant independently of one another, as depicted in Fig. 1. DISCUSSION
In considering these findings, the primary question examined is whether the two factors associated with better health behaviour, as measured by high scores on HPI, in this national sample of Social Class IV Table 3. Controlling
for confounding
amongst
and V mothers are the same as those identified in the earlier Cardiff studies on local samples. Where this is not the case, secondary questions arise as we consider possible explanations for any discrepancies. Direct comparison with the findings of the earlier Cardiff studies posed certain problems since the methods of analysis used were somewhat different, and moreover the operational definitions of a number of the explanatory variables used were perforce not always identical. For example, the Cardiff studies employed a stepwise modelling approach (that is, the selection of variables purely on statistical grounds) rather than the structured approach employed here. In addition, multiple regression was used (thus assuming linear relationships) and the tenure variable was not included in the analysis [4]. It was therefore decided to repeat analysis of the Cardiff data set but this time to include tenure and to use the structural analysis of variance modelling technique described above. Using one-way analysis of variance, five factors were initially statistically significant in the Cardiff data-namely, tenure, education, Salience of Lifestyle (general), support from relatives and work status (self). The overlap with the five the five initially
significant Adjusted
Factor
Grouu II IV V
Tenure Work status (self) Marital PSSI
status
SLI (personal)
l**f < 0.001. l*f < 0.01. ‘P < 0.05. Otherwise P > 0.05.
df
I
Unadjusted F-ratio A
(within groups) B
5.6* 3.5.
4.6* 3.0
I
4.78 5.0*
4.0’ 4.1’
I
5.4’
5.4’
2
1
factors (n = 360) F-ratio (final across-groups) C 4.2’
3.9’
1142
ROBIN POLL et al.
(a) 5.0
-
a,
4,8
_
; $
4.6
-
;;:
4.4
-
’ 2 5
4.2
-
4.0
-
F = 4.2 (p
*\;
Adjusted Unadjusted
3.8 I
I
3.6
Rents
OWllS
(b) 5.0 2 0 $
4.8
-
4.6
-
z z
4.4
--
4.2
--
4.0
--
3.8
--
,” 0 E
means
3.6
Tenure F = 3.9 (p
means
K;“i.,;:“,,,
I Low SLI
High (personal)
Fig. 1.Mean Health Practices Index scores by (a) tenure and (b) Salience of Lifestyle (personal) both before and after adjustment for each other. (HALS) factors in Table. 2 is striking. Furthermore, after controlling for confounding, three factors remained independently associated with HP1 in the Cardiff data set: tenure, education and perceived support from relatives. This compares with tenure and SLI (personal) in the present analysis of the national data. The importance of tenure in both the national and local samples of Social Class IV and V mothers is thus upheld. Remaining to be considered, however, are (a) the failure of education to appear at any stage in the present analysis of the national data and (b) the inconsistencies in terms of SLI (personal) and perceived support. For Britain it has generally been assumed that education and income would be positively associated with low risk health behaviour (both across and within the broad categories of the Registrar General’s Social Classes) and, moreover, that the strength and direction of the associations would be dependent upon the actual behaviour under consideration. Indeed, one of the more consistent findings in this area of research has been that more positive health behaviour, including composite indices of health behaviour, is positively associated with higher socio-economic status [15]. Measures of socio-economit status have usually included education along with occupation and/or income-as, for example, in the original Alameda County studies [9]. Comparatively few studies have attempted to assess the relative contributions of education, income and occupation but, where this has been done, education usually emerges as the most reliable correlate [l&18]. Following this pattern, education was found to be significantly associated with higher HP1 scores for the
Cardiff samples of Social Class IV and V mothers and it is therefore surprising that no such relationship was found in the present analyses of the equivalent national group drawn from the HALS data. The mean HP1 score in the national sample was 4.0 for those with no qualifications (N = 214) compared with 4.2 for those with qualifications (N = 135). There was therefore not even a suggestion of a difference, and the lack of statistical significance is not attributable to insufficient numbers in the two categories. What is noticeable about both these local and national samples of lower social class groups is the high proportion who left school as soon as they could and obtained no further academic or vocational qualifications. This categorisation has clearly discriminated within the Cardiff sample-the 23% who had further education and training obtained significantly higher HP1 scores than the remainder of the sample. In order to make the operational definitions as comparable as possible the present analysis of the HALS data also dichotomised into those who did or did not have any qualifications. In order to check the possibility that this might have concealed a trend depending on the type of qualification obtained, the data were also analysed by the highest qualification reported. The following results were obtained: 62% of the HALS sample of Social Class IV and V mothers had no qualifications and their mean HP1 score was 4.0; the 23% who had at least one O-level or equivalent had a mean score of 4.2; the 9% with a vocational qualification had a mean score of 4.3; the 6% with at least an A-level or equivalent had a mean score of 4.0. The conclusion must be that there is no evidence of any differences. Furthermore, examination of the detailed relationships of education to the individual practices comprising HP1 in this sample revealed very little in the way of (positive) associations (with the exception of eating breakfast regularly). It was therefore not the case that negative and positive associations had simply cancelled each other out across the different practices. The failure to find any relationship between education and HP1 for the social class IV or V mothers in the HALS sample is thus not an artefact. It remains to account for the inconsistency with regard to perceived support from relatives and SLI (personal). In the local sample two sepnrate measures of perceived support were used, one for relatives and one for friends, whereas the national sample asked first about relatives, and, if none were reported, moved on to friends. Also, given the questions posed in the local study, only a general Salience of Lifestyle Index could be constructed, which would a priori be less likely than a personal version to be associated with a self-reported index of health behaviour. In contrast to education, therefore, both inconsistencies could well have arisen as a result of differences in the
Health behaviour among mothers of lower s&o-economic operational definitions used for the local and national samples. What is most striking in the comparison between the Cardiff study and the HALS data is the importance in both samples of the association between the type of tenure and health behaviour. Mothers in rented accommodation (predominantly local authority tenants) are significantly less likely than those buying their own houses to report low risk health behaviours. We investigated whether the strength of the association between tenure and HP1 in the HALS sample rested on a marked difference between owners and renters for just one or two items in the HPI, or whether the difference was observed for all the items. In the event, it appears that owners are significantly more likely to report never having smoked and eating breakfast regularly and less likely to report taking regular exercise. Housing tenure has again proved its value as a powerful discriminator within occupational classes (such as the Registrar General’s classification), this time through its association with health behaviour. Significant associations found in a cross-sectional survey cannot, of course, be interpreted as evidence of causation. It is clear that tenure is more than a simple measure of type and standard of housing [ 11, 131; rather, like social class its value lies in the fact that it reflects the influence of a wide range of socio-economic factors. Any hypotheses put forward to explain the association between tenure and health behaviour would therefore need to set out in detail the aspects of social circumstances and environment which might account for the observed variation in reported health behaviour scores. It may well be that further analyses along these lines might succeed in still explaining only a small part of the observed variation, as has been the experience of similar attempts to disentangle the various components of social class in relation to health behaviour [ 161. Different approaches, using more in depth and qualitative strategies, may therefore be needed to reach a better understanding of the constraints on health-related behaviour within particular social groups. Notwithstanding this, our findings are in accordance with much of the recent work on health-related behaviour that has identified sociodemographic variables as the dominant factors rather than attitudes and beliefs [8, 19,201. This has obvious implications for health promotion since, as noted in the introduction, the assumptions behind the research strategy were that systematic information on the factors associated with health behaviour within population groups would provide guidance for research in the direction of causality and the ‘levers’ that might form the basis of intervention programmes. Whilst our findings certainly suggest further direction for research into causation, the variables finally selected by the analysis are not readily susceptible to modification at the level of the individual. In turn this poses
status
1143
a major challenge for those whose prime concern is the modification of risk factors. As we have stressed throughout, it should also be noted that this analysis was applied to a very specific sub-group of the population. The question remains as to whether the factors identified as significantly and independently related to health behaviour for Social Class IV and V mothers as the same for mothers of the same ages in the other social class groups. This will be addressed in another paper. Acknowledgements-Our thanks are due to Professor N. C. H. Stott for his advice and encouragement and to Rosy Allcott for her patience in producing endless drafts.
REFERENCES
1. Danchik K. Highlighrs from Wave I of the National Survey of Personal Health Practices and Consequences: United States 1979. U.S. Department of Health and
Human Sciences. Publications 1981.
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APPENDIX Explanatory
Variables
used in the Analyses
Group
Variable
Definition
I
Level of disability
11
Education
No physical disability vs those with any degree of disability. Those with some form of educational or vocational qualification vs those with no formal qualifications.
11
Tenure
II
Income
II II
Work Work
III III III III
Age
III
Crowding
IV IV
Marital status Perceived social support index (PSSI) Social contact index Salience of Lifestyle (personal) Salience of Lifestyle (general)
IV V V VI
status status
(partner) (self)
No. children <5 No. children < 17 Number in household
Religious
index
attendance
Those living in privately owned property vs those in rented accommodation (either private or council). Total household income less than E230 per month vs f230 or more. Employed vs not employed. Full time/vs part time/vs not in paid employment. 20-39/30-39140-45 years. None/one/two or more. One/two/three or more. Total living in household (including respondent) up to 4 vs 5 or more. Number in household/total number of living rooms and bedrooms (< l/l to 1.49/1.5+). Currently married vs other. Some lack of support (score i 2 1) vs no lack of support (21). High score (IO+) vs low score (O-9). High score (3,4) vs low score (O-2). O/1/2/3/4. Has attended church/place of worship within last fortnight vs has not done so.