Social status and the health of families: A model

Pergamon

0277-9536(94)EOO45-T

SOCIAL

STATUS

Ser. Sri. Med. Vol. 39, No. 12, Pp. 160~1613, 1994 Copyright 0 1994 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0277-9536/94 $7.00 + 0.00

AND THE HEALTH A MODEL

OF FAMILIES:

WILLIAM W. DRE~SLER Department

of Behavioral

and Community Tuscaloosa,

Medicine, School of Medicine, AL 35487-0326, U.S.A.

University

of Alabama,

Abstract-The aim of this study is to examine the association of family health and social status, taking the family as the unit of analysis. One particular dimension of social status, lifestyle incongruity, is examined as a predictor of family health, relative to other stressors and sociodemographic variables. Lifestyle incongruity refers to the degree to which style of life (measured by the accumulation of consumer goods and the adoption of specific leisure activities) exceeds economic status (as assessed by occupational class and educational credentials). Using the 1980 General Household Survey of the United Kingdom, it was found that lifestyle incongruity discriminated between households with and without chronically ill members, and was associated with a global rating of family health, controlling for a variety of factors. The logic of studying the health of families, and the implications of these results for future research are discussed. Key words-status

incongruence,

family health,

job stressors,

Household

Survey

for example, occupational prestige or educational credentials. In Goffman’s [16, p. 2961 words:

INTRODUCTION

The aim of this paper is to extend and refine a model of status incongruence and health, by examining both as family variables. The links between lifestyles, economic status, and health have been explored in a variety of studies [l-lo]. A conception of social status consistent with the work of Veblen [l 11,Weber [12], Bourdieu (13) and others [14, 151, has guided this research. In this model, ‘lifestyle’ is viewed as a set of behaviors intended to signify or communicate to others a claim to a particular social status (or prestige or social honor). These behaviors include the consumption of material goods and the adoption of particular (especially leisure) activities. It is the adoption of these behaviors that project into mundane social interaction the claim to an esteemed social identity. As Veblen [l 1, p. 361 pointed out years ago: In order to gain and to hold the esteem of men it is not sufficient merely to possess wealth or power. The wealth or power must be put in evidence, for esteem is awarded only on evidence. Bourdieu [13] has elegantly extended the study of lifestyles and social status by demonstrating that the ‘evidence’ to which Veblen refers permeates social behavior and social interaction as a sense of ‘taste’. But as Goffman [16] pointed out, esteem is not awarded solely on a claim to social status, irrespective of the convincing nature of the evidence of taste. Rather, he argues, there is a complex algorithm by which individuals assess the lifestyle of another in combination with other indicators of social class. In some cases, a lifestyle may not be consistent with,

General

It is always possible, therefore, that symbols may come to be employed in a ‘fraudulent’ way, i.e. to signify a status which the claimant does not in fact possess. We may say, then, that continuing use of status symbols in social situations requires mechanisms for restricting the opportunities that arise for misrepresentation. In short,

the claim to higher social status based on lifestyle can only be a tentative one, subject to the confirmation of that status on the basis of indicators of status less prone to manipulation, e.g. occupation, or educational credentials. In previous studies, the degree to which lifestyle exceeds occupational/educational (or, in shorthand, economic) status has been associated with higher blood pressure [l-4,6, lo], higher depressive symptoms [5], higher serum cholesterol [7,8], and higher plasma glucose [6,9]. Furthermore, in different studies the effect of this discrepancy, referred to as ‘lifestyle incongruity’, has been examined relative to measures of psychological stressors, social role stressors, and stressful life events; in every case where such comparisons have been made, lifestyle incongruity has had an independent effect on health outcomes. This has led me to argue that the true mediators of this effect are a linked set of social and psychophysiological processes. The individual attempting to assert claims to a higher social status than that consistent with his or her economic status may be in a state of more-or-less continuous struggle and vigilance, attempting always to ‘convince’, as it were, others of the validity of this status claim. Laboratory evidence has shown that physiological arousal accompanies such social

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WILLIAM W. DRFSLER

interactions, arousal which, in the long run, could produce sustained disease [17]. The aim of this paper is to extend the study of lifestyle incongruity by examining the locus of incongruity. That is, does this form of status incongruence occur in, and affect, individuals alone, or should it apply to larger units of analysis, such as families or households? In one sense it is obvious that the concept applies to more than individuals because of the way lifestyle has been operationalized. Very straightforward items have been employed to assess lifestyle, such as the ownership of major consumer durables (refrigerators, microwave ovens, furniture suites, etc.); microtechnology (televisions, stereos, cameras); and self-reported behaviors such as watching television, going to the cinema, reading magazines, and traveling for leisure. (Note too that desires or aspirations have not been examined, only actual behaviors have been.) Clearly, the consumption of items such as these can involve investment decisions that are made at the level of the family or household. Even seemingly individual decisions such as devoting spare time to television viewing or reading magazines, both behaviors necessary to maintain what Douglas and Isherwood [18] term ‘information goods’, can depend on household-level decisions regarding the allocation of time. Wallman [19], in her ethnographic study of eight households in London, found just such a household pattern of decision-making regarding allocation of scarce resources. Her description of ‘two typical English households’ is particularly instructive. In her discussion of these families, especially with respect to the allocation of financial resources, it is a ‘standard of living’ that looms large in their decisions to expend (or not) scarce resources on consumer goods or leisure activities. One family member even noted that it was ‘no good’ if one could not ‘live up to’ a particular standard. Of course, these observations echo Lockwood’s [20] well-known discussion of the privatized worker, whose model of status distinction is based on the competitive assumption and display of a conventional middle-class lifestyle. And this competitive status display need not involve terribly ostentatious or outlandish modes of consumption. Rather, what is at stake is the struggle to maintain, in the face of limited economic resources, what Veblen [l l] succinctly referred to as ‘a conventional standard of decency’. Additionally, the examination of social status and family health, viewing both explicitly as family (or household) variables, is consonant with recent theory regarding social class, and with the tenor of the literature in family medicine. In the social class literature, numerous discussions of the appropriate unit for class analysis have appeared in recent years. While a complete examination of this literature would be well beyond the scope of this paper, there does seem to be a growing consensus that the household is the appropriate unit of analysis, and that infor-

mation on all members of the household should be employed in constructing indices of social class [21,22]. Similarly, the literature in family medicine (or general practice) commonly assumes the importance of the family in health, yet rarely is the family per se ever examined as the unit of health analysis. Most often, characteristics of the family are viewed as predictors of the health of individuals within the family, as opposed to the family unit as a whole [23,24]. It would appear, therefore, that a convergence of these perspectives could prove fruitful in examining the health of families. The approach to examining family health taken here is meant to be complementary to related work in this area, especially that of Huygen and associates [25,26], Fisher et al. [27], and Fletcher [28]. All of these researchers have taken the examination of familial illness patterns as their focus, especially how the characteristics of one family member (e.g. experience of occupational stress) can be associated with illness in other family members. In this research, intra-family associations of illnesses, or of individual characteristics and family members’ illnesses, are examined; individuals are retained as the unit of analysis, the aim being to observe patterns within family units. My emphasis here is somewhat different, to examine the family itself as a unit of analysis, taking illness patterns and other variables (e.g. lifestyle incongruity) as attributes of families. The current study was undertaken to determine if lifestyle incongruity would be a significant correlate of self-reported family health in a large and representative sample of families. The 1980 General Household Survey of Great Britain provided the relevant data for this study. SAMPLE AND METHODS

To the best of my knowledge, the General Household Survey (GHS) is the only large, representative set of data in which information relevant to testing the lifestyle incongruity hypothesis is available. The 1980 GHS was selected because it contained the largest number of items appropriate to the construction of indices (of the recent surveys), and because it was readily available from the Economic and Social Research Council Data Archive at the University of Essex. The 1980 GHS sample was reduced in three ways. First, only respondents who were 25-64yr old were included, under the assumption that this age range would encompass those persons for whom issues of social status would be most salient and for whom measures of current economic status would be most accurate. Second, the data were aggregated by household. The GHS data are supplied as a rectangular data matrix in which the rows are individuals and the columns are variables. Data are collected by personal interview for the household and for each individual (over 16 yr of age) within the household; each individ-

Social status and family health ual’s data record contains his or her personal data along with all the household information. There are household and individual identification numbers. Data for all individuals in the household were combined by keying on the household identification numbers, using the SPSSX AGGREGATE program [29]. The precise derivation of family variables will be described later for each variable. Finally, from the aggregated data set, only those households in which a husband and wife were present were included in data analyses (although it should be noted that the analyses reported here remain essentially unchanged if other household types are added in). This resulted in a final sample, excluding cases with missing data, of 4489 households. Four variables indicative of family health were derived. In the GHS, a question regarding longstanding illness is asked of each respondent, ‘longstanding illness’ referring to anything that has affected or is likely to affect the respondent over a long period of time. This is a dichotomy. Also, the same question is asked regarding children in the household; the sum of positive responses for the household is termed ‘family chronic illness’. Family chronic illness was also broken into its two components: ‘adult chronic illness’ and ‘child chronic illness’. Not surprisingly, these variables are skewed, so each was dichotomized, with households containing no ill members coded ‘O’, and households with ill members coded ‘1’. Finally, each member of the household interviewed (including ‘proxy’ interviews, i.e. schedules completed for a household member by another household resident) rates his or her health on a 3-point scale: good = 0; fairly good = 1; and, not good = 2. These scores were summed for all family members to yield a ‘family health rating’. Not surprisingly, again, this variable is badly skewed, so that it too was dichotomized to zero and one; a zero score means that the health of every member of the family was rated good. Style of life was measured following previous studies. It is a 24-item scale assessing the ownership of material goods and the adoption of particular leisure activities. The scale, shown in Table 1, has acceptable internal consistency reliability (a = 0.70). Scale scores are created by summing the unweighted items, and converting the scale to a mean of 50 and a standard deviation of 10. Economic status was measured as a weighted average of the Registrar General’s 6-point occupational class ranking and an 8-point ranking of educational credentials, which also was converted to a mean of 50 and a standard deviation of 10. These variables were calculated for individuals prior to family aggregation. Then, following the recommendation of Erikson [21] and Duke and Edge11 [22], the maximum score on each variable for the household was selected as the family variable. Style of life and economic status, having been converted to comparable metrics, were then used to calculate two theoretically relevant variables. The

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first, ‘lifestyle incongruity’, is the signed difference of the two, i.e. (style of life) - (economic status). These scores take a negative sign when economic status exceeds style of life; they are approximately zero when the two are equal; and, they take a positive sign as style of life exceeds economic status. The second calculated variable, ‘socioeconomic status’, is the sum of the two scales, i.e. (style of life) + (economic status). As a family’s style of life, occupational class rank, and educational credentials all increase, the socioeconomic status score also increases. As Hope [30] and Whitt [31] have shown, these two variables decompose household economic differences into vertical (socioeconomic status) and nonvertical (lifestyle incongruity) components. Furthermore, when the two variables are derived in this way, the correlation between them is zero. Lifestyle incongruity and socioeconomic status are thus independent dimensions of social stratification. ‘Job stressors’ is a 9-item scale assessing employed respondents’ satisfaction with their jobs. Each respondent rated his or her job characteristics on a 5-point Likert response format scale. The scale, shown in Table 2, has acceptable internal consistency reliability (a = 0.79). The scores for individuals were averaged over all employed family members to yield a ‘family job stressor’ scale. The remaining variables included in the analysis are regarded as potential confounding variables. ‘Age of the household head’ is self-explanatory and is indicative of the stage in the family lifecycle. ‘Sex

Table 1. Scale of style of life Variable

Descriptive statistics

Item-total correlation

(1) (2) (3) (4) (5) (6) (7) (8) (9) (IO) (I 1) (12) (13) (14) (I 5) (16) (17) (18) (19) (20) (21) (22) (23) (24)

2.9(*0.5) lS(kO.7) 0.65 0.83 0.96 0.63 0.97 0.90 0.30 0.05 0.82 0.59 0.62 0.20 0.88 0.68 0.52 0.9 1 0.42 0.65 0.57 0.65 2.8(+2.3) 0.03

0.28 0.22 0.32 0.22 0.16 0.30 0.21 0.28 0.20 0.21 0.37 0.10 0.38 0.23 0.20 0.22 0.21 0.20 0.36 0.08 0.26 0.28 0.36 0.16 a = 0.70

Bedrooms Other rooms Central heat Color TV Fridge Freezer Vacuum Washing machine Dryer Dishwasher Telephone Car House ownership Holiday Radio listening Record listening Book reading Visiting Go out for meal Go out for drinks Gardening Do-it-yourself Number of activities Foreign holiday

Items I and 2 are simple counts. Items 3-13 are dichotomies (i.e. ownership). Items 14-22 are dichotomies referring to the activity occurring within the family in the 4 weeks prior to the interview. Item 23 is a count of activities in the prior 4 weeks from a maximum of 16 activities (e.g. sports, etc.). Item 24 refers to the most recent holiday.

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WILLIAM W. DRESSLER Table

Descriptive statistic

Itern (I) (2) (3) (4) (5) (6) (7) (8) (9)

Table 3. Descriptive

2. Scale of job stressors

Overall job satisfaction Satisfied with take-home pay Satisfied with work hours Satisfied with paid holiday Pay is reasonable compared to others Pay is reasonable for work Pay keeps pace with living costs Pay is reasonable given training Good chances for advancement

i.S(?l.O) 2.3(f1.2) l.S(+l.O) l.S(fl.1) 2.2(?l.l) 2.2(+1.1) 2.7 (+ I .2) 2.3(+1.1) 2.7(11.2)

Item-total correlation

(I) (2) (3) (4)

0.58 0.68 0.59 0.59 0.26 OL= 0.79

(5) (6) (7) (8) (9) (IO) (I I) (I 2) (I 3) (14) (15) (161

ratio’ equals the proportion of males in the household. ‘Family size’ is the total number of persons in the family residing in the household. ‘Income’ is the total weekly income (in pounds) of the family. ‘Dependency ratio’ is the ratio of the family size to the total number of employed persons in the household. is a dichotomy indicating ‘Cigarette smoking’ whether or not anyone in the household smokes. ‘Alcohol use’ is a family average of the number of drinks per week reported by family members. ‘Urban residence’ is a dichotomy indicative of whether or not the family resides in one of the major metropolitan counties. Finally, ‘region’ is a dichotomy indicating whether or not a family resides in the north of England. Data analysis proceeded in three stages. In the first stage, discriminant function analysis was used to select, employing a stepwise procedure, a ‘best’ set of variables that distinguished between households with and without ill members. Discriminant analysis was used at this first stage because the size of the data set precluded the use of stepwise logistic regression on the local facility; under these conditions, Cleary and Angel [32] recommend the initial use of discriminant function analysis because, in large data sets, the results differ so little from the (computationally) more expensive logistic technique. In the second stage, the models selected by discriminant function analysis were re-examined using logistic regression with simultaneous entry of variables. Variables not achieving the conventional (i.e. P < 0.05) level of statistical significance in these analyses were then deleted, and the third stage of the analysis was the estimation of logistic regression coefficients and their associated standard errors for a final best set of predictors.

Descriptive statistic

Family chronic illness (% households) Adult chronic illness (% households) Child chronic illness (% households) Family health rating (% fairly good/ not good) Lifestyle incongruity Family job stressors Socioeconomic status Sex ratio (proportion males) Age of household head Family size Dependency ratio Household income (weekly) Alcohol use Cigarette smokmg (% households) Urban residence (X metropolitan) Region (% North)

57.8 49.1 20.0 50.8 l.26(?10.3) 19.15(+5.99) 103.01 (+ 16.21) 0.32(+0.13) 44.86 (+ 12.3) 3.52(* 1.27) 2.43 (i I .25) 178.18(+90.2) 14.03 (+ 3.87) 65.5 38.4 27.8

these data reporting a chronic condition is 29.9%.) The lower proportions for adult chronic illness, and especially for child chronic illness, makes this high total figure more comprehensible. Data analyses are presented in Tables 4-7. Each table shows the final stage in the data analysis: the unstandardized logistic regression coefficient associated with each predictor variable; its associated standard error; and, the t-ratio (or ratio of the coefficient to its standard error). Variables have been ordered by the magnitude of the t-ratio, which gives an indication of the relative importance of these explanatory variables. For family chronic illness, after household head’s age, family job stressors and lifestyle incongruity are the most important variables that distinguish between families with and without chronically ill members. Family size and the dependency ratio also contribute to the prediction of family chronic illness. The analysis for adult chronic illness is very similar, with family job stressors and lifestyle incongruity following age of household head and sex ratio in relative explanatory importance. Again, these effects are independent of other factors, including family size, dependency ratio, and the protective effect of moderate alcohol use. With respect to the analysis of child chronic illness, sex ratio, family size, age of the household head, lifestyle incongruity and family job stressors (in that order) distinguish between families with and without chronically ill children.

Table 4. Logistic

regression

analysis of family chronic

illness

Variable

Logistic regression coefficient

Standard error

r-ratio

(I) Age of household head (2) Family job stressors (3) Lifestyle incongruity (4) Dependency ratio (5) Family size Constant

0.4370 0.1925 0.1510 0.1 167 0.0942 -0.2737

0.0349 0.0318 0.0307 0.0339 0.0332 0.0918

12.52*** 6.05*“* 4.91*** 3.44*** 2.83** -2.98**

RESULTS

Descriptive statistics for all variables included in this analysis are shown in Table 3. The high percentage of households with chronically ill members is striking, but it must be kept in mind that the denominator for this fraction is households, not individuals. (By comparison, the percentage of individuals in

(n = 4489 households)

Variable

0.41 0.64 0.31 0.34

Items l-4 are rated on a 5-point scale from very satisfied to very dissatisfied. Items 5-9 are rated on a 4-point scale from agree strongly to disagree strongly.

statistics

‘P < 0.05; **p

<

0.01; ***p

< 0.001

Social status and family health Table 5.

Logistic regression

analysis

of adult chronic

Variable

Logistic regression coefficient

Standard error

r-ratio

(I) Age of household head (2) Sex ratio (3) Family job stressors (4) Lifestyle incongruity (5) Family size (6) Dependency ratio (7) Alcohol use Constant

0.3770 2.5853 0.1914 0. I305 0. I580 0. I079 -0.0241 - I .3370

0.0350 0.4075 0.0317 0.0306 0.0445 0.0336 0.0080 0.2852

10.77*** 6.34’” 6.03*** 4.26’” 3.55*** 3.21*** 3.01” -4.68***

‘P < 0.05; **p < 0.01; ***p

illness

< 0.001.

Table 7. Logistic

1609 regression

Variable

Logistic regression coefficient

(I) Socioeconomic status (2) Age of household head (3) Family job stressors (4) Sex ratio (5) Household income (6) Cigarette smoking (7) Family size (8) Urban residence (9) Lifestyle incongruity Constant

-0.2529 0.2576 0.1979 2.2032 -0.0017 0.2361 0. I574 0.1779 0.0831 -1.1317

lP < 0.05; **P < 0.01; ***p

Finally, with respect to the family health rating, a larger number of variables enter the analysis, with lifestyle incongruity being the least important of the significant variables. Also, it is only in this analysis that conventional indicators of socioeconomic status figure prominently. DISCUSSION

The results of this study support the proposed model, namely, that an incongruity in status attainment (as assessed by lifestyle) and economic status (as assessed by occupation and education) is appropriately viewed as pertaining to families, and that this incongruity is related to poorer family health. Before any further discussion of the theoretical implications of these results, however, it is important to consider somewhat broader issues. First, there is an epistemological question to be addressed. Are there important health processes that can best be understood by taking the family as the unit of study, as opposed to any one (or even more than one) individual within the family? It is this latter strategy, one of examining the impact of family characteristics on the health status of individuals, which is the common research strategy in family medicine and social epidemiology [23,24]. Is there any utility in developing an alternative orientation using collective terms? From a logical point of view, there is. Take, for example, the health outcomes studied here: selfreported chronic illness. There are ample data to demonstrate that the assumption of a simple isomorphism between biomedical diagnosis and the selfreport of illness would be false [33,34]. Quite the contrary, illness is a contested cultural category. Generalized symptoms, from which we all suffer in Table 6. Logistic

regression

analysis

of child chronic

Variable

Logistic regression coefficient

Standard error

r-ratio

(I) Sex ratio (2) Family size (3) Age of household head (4) Lifestyle incongruity (5) Family job stressors Constant

- 6.2524 0.1593 0.1587 0.1236 0.1057 -0.1801

0.5106 0.0425 0.0459 0.0386 0.0398 0.2829

- 12.24”’ 3.74*** 3.45*** 3.20** 2.65’. 0.63

lf < 0.05; l*P < 0.01; l**P < 0.001.

illness

analysis of family health rating Standard error

t-ratio

0.0409 0.0430 Of0365 0.5239 0.0005 0.0740 0.0546 0.0708 0.0355 0.3494

-6.18*** 5.99”’ 5.42*** 4.20”’ -3.40”’ 3.19” 2.88” 2.50’ 2.34’ 3.25’:

< 0.001.

sufficient profusion from time-to-time to be labeled ‘ill’, become translated into a diagnosis through a process of negotiation within primary social groups (i.e. families), who are aided and abetted by health care professionals [35]. Therefore, the answer to the question regarding health or illness put to the GHS respondents was most likely one generated by a social relational process taking place within that family. Thus, health or illness, defined in this way, is perhaps more accurately a characteristic of the collective termed ‘the family’ than it is of the individual. In this sense, chronic illness is more accurately a collective term rather than an individual term, and in the philosophy of social science there is no objection to the use of collective terms [36,37]. Similarly, status attainment as symbolized and signified by lifestyle, and the economic means to achieve that status, more appropriately refer to the family. Much of the focus in family theory and research is on social interaction and the associated emotional climate of the family [38]. Unfortunately, especially from the perspective of social epidemiology, the family as a system of economic production (class), redistribution, and consumption (status) can get ignored. When stated this way, it becomes clear that the investment of resources in the material culture and behaviors which represent to the world outside the household the status of the family (and its members) also depends upon negotiation (or, perhaps, unilateral and despotic decisions) within the family. These social-relational processes may have health implications per se, not to mention the ways in which such processes constrain the social identities of individual family members in their mundane social interactions outside the household. In short, not only can health and social status processes be viewed as referring to a collective, the family, it may be that these variables are more appropriately viewed as family variables. Shifting from a logical to a methodological perspective, it is important to assess the efficacy of the measures used here as indicators of family processes. Ransom and associates [39,40] have discussed these issues in some detail, especially with respect to the correspondence between what the researcher intends to measure and what actually is measured. They are particularly critical of research in which variables

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WILLIAM W. DRFSSLER

that are actually measurements of individuals are inappropriately interpreted as measurements of families. This mistaken inference can occur either when an individual’s perception of something going on within the family is assumed to accurately measure that characteristic, or when individual characteristics are uncritically combined (summed or averaged across individuals) to create family variables. In the former situation, unless the variable assessed is very straightforward (e.g. family size), one individual’s perception is just that. In the latter case, an average across family members may simply reflect the old saying that anything can be averaged, rather than reflect theoretically relevant characteristics. The most important variables to evaluate in the present study from this perspective are the dependent variables and the two main variables of interest-lifestyle incongruity and family job stressors. Number of chronically ill in the household as a family variable seems thoroughly unproblematic. There is perhaps more potential difficulty with the family health rating, in that individual ratings are summed to yield a family score. Does this truly represent a family characteristic, or is it simply the inappropriate summation of individual variables? At face value, it would seem that the family health rating would at least order families along a continuum of good to poor perceived health. And, the idea that the perceived and expressed health of the family is an outcome of intra-familial negotiation would seem to apply to this rating. Therefore, at this point it would not seem inappropriate to tentatively accept this rating as a useful family variable, subject to further scrutiny. Both lifestyle incongruity and socioeconomic status are truly family variables. As argued in the Introduction, the items making up the style of life index are goods and behaviors the consumption of which are unlikely to be controlled solely by any single family member. This is not to say that particular family members do (or do not) exert greater (or lesser) influence over the definitions of particular items as status-enhancing and the decisions to invest resources in those particular terms. Nor am I suggesting that resource investment decisions are not contested. Merely it is argued that the ultimate referent for these items is the family, not just an individual. Similarly, the occupational and educational resources pertaining to individuals do not benefit those individuals alone, but rather those resources are redistributed within households, a process which of course can be contested. This being the case, the decision by the researcher to combine these variables in particular ways to measure family characteristics becomes a purely technical one, which is not our primary concern here and is extensively discussed by others [30,31]. The major point to be emphasized here is that the family is an appropriate referent for the theoretical terms of lifestyle incongruity and socioeconomic status.

The appropriateness of the variable of family job stressors is more questionable in this respect. Three considerations motivated inclusion of this variable. First, occupational stress as a correlate of poor health has been widely studied [41], and I wanted to compare the strength of association between job stressors and health with the association of lifestyle incongruity and health. Second, as noted in the Introduction, the association of lifestyle incongruity and health has been observed to be independent of various measures of perceived stress in different studies and the inclusion of this variable allowed me to determine if this independence was true for these data. Third, I hoped to use family job stressors as a proxy for interpersonal stress (upset, arguments, lack of cohesion, etc.) within the family. The reasoning here was that those persons who were more dissatisfied with their jobs would be more likely to translate a certain amount of that negative affect into a negative emotional climate in the home. As Ransom et al. [39,40] argue, it is precisely this latter use of a summed or averaged term as a family variable that can be fallacious. Assuming an isomorphism between job dissatisfaction for individuals and a negative emotional climate in the home is an unwarranted inference. As these authors argue, it is incumbent upon the researcher to measure as directly as possible emotional conflict within the family if that is what he intends to measure. Averaging across individuals may or may not have much to do with that conflict. Of course, in the present study using as it does a secondary data source, there was no alternative. Nevertheless, this is an important shortcoming that needs to be acknowledged. Finally, with respect to methodological issues, all of the covariates can unambiguously be considered family variables. Some of them are imperfect to be sure, such as age of the household head as an indicator of stage of the family lifecycle. Similarly, household alcohol use might be more effectively measured with an indicator of differential use in the family, depending on the aims of the investigation. Taken as a whole, however, the covariates are probably measured well enough as family variables to serve their purpose within this study, which is to partial out the variability due to these factors to better assess the effects of the variables of interest. With these epistemological and methodological issues clarified, the substantive implications of these results can be discussed. With respect to family chronic illness, adult chronic illness and child chronic illness, after controlling for demographic variables (stage of family lifecycle, sex ratio and size), family job stressors and lifestyle incongruity are the best predictors of family health. The discriminating power of these variables exceeds that either of more conventional sociodemographic variables (income, dependency ratio, socioeconomic status) or of health behaviors (cigarette smoking, alcohol use).

Social status and family health These results both confirm the importance of social and psychological factors in health in general, and point to the importance of extending a consideration of those factors beyond the typical intra-psychic, perceptual stress variables employed in research. The effects of lifestyle incongruity are dependent neither on the assessment of individuals’ expressed desires for a particular lifestyle, nor on individuals’ conflicts, worries, or concerns regarding issues of finances (at least as these are partially reflected here in the family job stressor measure). Again, it appears that the effects of lifestyle incongruity are outside the conscious awareness of persons, and in turn have ramifications throughout the family system. This interpretation is actually supported by the fact that lifestyle incongruity is the least important variable in the regression equation for the family health rating. Of all the health variables studied, this seems like the one in which perceived stresses would be most evident, and it in turn is the one variable on which lifestyle incongruity has the smallest impact. This result is consistent with the notion that the process by which incongruity influences health is outside the conscious awareness of persons. Elsewhere [17] I have discussed at length the social relational processes through which the effects of lifestyle incongruity might be mediated. Anticipating these empirical results, we recently suggested how status incongruence at a household level might influence infant growth and development [42]. Such a process could begin in utero; the struggle to maintain the high status social identity explicit in lifestyle incongruity could result in maternal physiologic responses that impair fetal growth. In the postpartum period, parental depression in association with incongruity could lead to caregiving inconsistent with adequate child growth and development, the result being child chronic illness. These results may, however, demand an even broader view of the process. There of course needs to be a consideration of the emotional climate within the family. The struggle to maintain a high status lifestyle may create intra-familial conflict, a chronic lack of cohesion and disorganization. This would be especially so within those families in which the maintenance of a high status lifestyle is the agenda of one individual or of a particular family coalition. But even if the maintenance of such a lifestyle is the agreed-upon family agenda, the lack of confirmation by persons outside the family can lead to chronic struggle and vigilance in social interaction of the type I have discussed elsewhere [17] among all family members. Still, there are other possibilities. Veblen [l l] argued nearly a century ago that the ‘responsibility’ of status consumption for a family unit might fall to a single family member. He suggested that the female head of household, to the extent that she could be seen devoting her time and effort to nonproductive, conspicuous consumption, would enhance the pres-

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tige of the family. More recently, Belk [43] has suggested that, within a family, other persons can be regarded as ‘possessions’ and extend the social identity of an individual. This is a particularly intriguing notion, especially when it is coupled with the question: who becomes ill within a family? Perhaps specific family members are ‘assigned the responsibility’, as it were, of carrying the social status of the family. It may be the responsibility of either the male or female household head to create a high status lifestyle. Or sometimes it may become the responsibility of a child to exceed and achieve, and to thus enhance the status of his or her parents. Through such an assignment of family roles, the responsibility of maintaining familial social status may be unequally divided within a household. That individual would then be trapped in a considerable dilemma to the extent that the status of the family expressed through its lifestyle is inconsistent with its true standing as measured by economic status. Not only would that individual fail to have his or her own status confirmed in mundane social interaction, he or she would be failing to uphold the social honor of the entire family unit. Perhaps, then, this is precisely the family member to withdraw from competitive status display by adopting the protective label of chronic illness. Finally, the effects (or lack thereof) of other variables are worth nothing. Conventional indicators of socioeconomic status proved overall to be relatively unimportant. This is not to say that economic factors were not important, because clearly lifestyle incongruity is a variable with complex meaning in terms of class and status. Similarly, dependency ratio proved relevant in these analyses, which perhaps provides greater insight into how economic differences between households are also related to what goes on within households. Sex ratio proved to be important in the explanation of family health, and is intriguing because the direction of its association with the dependent variables changes in different analyses. When the health of adults is considered, an increasing proportion of males contributes to the likelihood that someone in the family will be ill. When the health of children is examined, an increasing proportion of males is related to a decreasing likelihood that someone will be labeled ill. Of course, different processes may be operating in these two circumstances, and a full explanation is beyond the scope of this paper. What I would suggest, however, is that the same sort of negotiation of illness labels previously described for the effects of lifestyle incongruity be considered in the generation of hypotheses to account for these effects. The point to be emphasized is that sex ratio can be regarded as an indicator of some process of sociologic interest occurring within households, which in turn results in the assignment of illness labels. These, of course, are speculations. The major point to be gleaned from such a speculative discussion is a

WILLIAM W. DRF.SSLER

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direction (or directions) in which future research should move. These can be summed up in a few conclusions. First, conceptualizing health and the factors influencing it as family variables is a theoretically and empirically useful way to proceed. Second, family variables that take into account the social and economic status of the family in a dynamic way (lifestyle incongruity) are empirically useful correlates of family health beyond conventional sociodemographic factors, health behaviors, or psychological stressors. Third, family variables that are indicative of the intra-familial emotional climate (family job stressors) also have independent effects on family health. And fourth, the empirical demonstration of the utility of such a model suggests that refining and further testing this model m’ay prove fruitful. Acknowledgements-This research was funded in part by general faculty research support from my department, and I am grateful to Professor James D. Leeper for his encouragement The research was especially facilitated by my appointment as Honorary Research Fellow in the Department of Sociology, University of Exeter, and by Dr John Vincent, head of department. Finally, the ESRC Data Archive at the University of Essex was particularly gracious in providing the data that were compatible with my local facility. Dr K. S. Oths provided helpful comments on a previous draft of this paper. The idea of using the GHS to test the status incongruence model was suggested by Dr Cohn Pritchard. Preparation of this paper was supported in part by research grant ROI-HI45663 from the National Institutes of Health.

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