benachmuntaner_asociación clase social y estratificación

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The two major variables used to operationalize socioeconomic

position in studies of social inequalities in health are social

stratification and social class. Social stratification refers to theranking of individuals along a continuum of economic or cultural

attributes such as income or years of education. These rankings

are known as simple gradational measures.1 Most social epi-

demiologists use several measures of social stratificationsimultaneously because single measures have been insufficient

to account for social inequalities in the health of populations.

Measures of social stratification are important predictors of pat-

terns of mortality and morbidity,2 and during the last decade,

a number of investigations of social inequalities in health have

assessed the relation between indicators of social stratification and

health outcomes. However, despite their usefulness in predicting

health outcomes, these measures do not reveal the social mech-

anisms that explain how individuals arrive at different levels

of economic, political, and cultural resources,3 in part perhaps

IJE vol.32 no.6 International Epidemiological Association 2003; all rights reserved. International Journal of Epidemiology 2003;32:950958

DOI: 10.1093/ije/dyg170

SPECIAL THEME: MENTAL HEALTH

The associations of social class and social

stratification with patterns of general andmental health in a Spanish populationCarles Muntaner,1 Carme Borrell,2 Joan Benach,3 M Isabel Pasarn2 and Esteve Fernandez4

Accepted 28 February 2003

Background Social class, as a theoretical framework, represents a complementary approach to

social stratification by introducing social relations of ownership and control over

productive assets to the analysis of inequalities in economic, political, and

cultural resources. In this study we examined whether measures of social class

were able to explain and predict self-reported general and mental health over

and above measures of social stratification.

Methods We tested this using the Barcelona Health Interview Survey, a cross-sectional

survey of 10 000 residents of the citys non-institutionalized population in 2000.

We used Erik Olin Wrights indicators of social class position, based on ownership

and control over productive assets. As measures of social stratification we used

the Spanish version of the British Registrar General (BRG) classification, and

education. Health-related variables included self-perceived health and mental

health as measured by Goldbergs questionnaire.

Results Among men, high level managers and supervisors reported better health than all

other classes, including small business owners. Low-level supervisors reported

worse mental health than high-level managers and non-managerial workers,

giving support to Wrights contradictory class location hypothesis with regard tomental health. Social class indicators were less useful correlates of health and

mental health among women.

Conclusions Our findings highlight the potential health consequences of social class positions

defined by power relations within the labour process. They also confirm that

social class taps into parts of the social variation in health that are not captured

by conventional measures of social stratification and education.

Keywords Social class, social stratification, socioeconomic status, mental health, self-rated health

1 Department of Behavioral and Community Health Nursing and Department

of Epidemiology and Preventive Medicine, University of Maryland at

Baltimore, USA.2 Municipal Institute of Public Health of Barcelona, Barcelona, Spain.3 Universitat Pompeu Fabra, Barcelona, Spain.4 Institut Catal dOncologia, Barcelona, Spain.

Correspondence: Carles Muntaner Bonet, Suite 645/BCH, University of

Maryland-Baltimore, 655 West Lombard Street, Baltimore, MD 21201, USA.

E-mail: [email protected]

950


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because they have generally been selected for pragmatic

considerations, i.e. availability of data, rather than for theoretical

reasons.

Social class is defined by relations of ownership or control over

productive resources (i.e. physical, financial, organizational).

Social class has important consequences for the lives of indi-

viduals: the extent of an individuals legal right and power to

control productive assets determines an individuals strategiesand practices devoted to acquire income and, as a result, deter-

mines the individuals standard of living.1 Thus the class position

of business owner compels its members to hire workers and

extract labour from them, while the worker class position

compels its members to find employment and perform labour.

Although there have been few empirical studies of social class

and health, the need to study social class has been noted by

social epidemiologists.2,4 Social class provides an explicit

relational mechanism (property, management) that explains

how economic inequalities are generated and how they may

affect health. For example, in a recent study,5 a team of US

epidemiologists found that low-level supervisors, who could

hire and fire front line personnel but did not have policy or

decision-making authority in the firm, showed higher rates ofdepression and anxiety disorders than both upper management

(who had authority and decision-making attributes) and non-

management workers (who had neither). This finding was

predicted by the contradictory class location hypothesis (super-

visors are in conflict with both workers and upper management

and do not have control over policy) but was not predicted or

explained by indicators of years of education or income gradients.

Moreover, the income hypothesis would have failed to provide

a mechanism and would have led to the expectation that super-

visors, because of their higher incomes, would present lower

rates of anxiety and depression than workers. A handful of

studies in psychiatric epidemiology57 suggest that social strati-

fication and social class are not equivalent; rather, they capture

different parts of the social variation in population mentalhealth. Therefore, the purpose of our study was to examine the

relationships between measures of social stratification (education,

British Registrar General Classification [BRG]), measures of

social class (Wrights social class indicators, i.e. relationship to

productive assets), and indicators of general health and mental

health.

The measures of social class used in our investigation

originate from a social class model that has been accumulating

empirical support over the last 20 years (e.g. refs 814). Wrights

social class indicators assess ownership of productive assets, and

control and authority relations in the workplace (control over

organizational assets1). Property rights over the financial or

physical assets used in the production of goods and services

generate three class positions: employers, who are self-employed and hire labour; the traditional petit bourgeoisie, who

are self-employed but do not hire labour; and workers who sell

their labour.1 These social class positions reflect the relational

properties underlying economic inequality.15 Indicators of

productive asset ownership gauge a relational mechanism that

generates economic inequality (i.e. deriving income from

owning property). Both neo-material16 and psychological5

mechanisms suggest that owners might present better overall

health and mental health than workers. Large property owners

tend to be wealthier17 than others and thus might be expected

to experience the greater material well-being that is conducive

to better health.3 In addition, large owners enjoy the predict-

ability and control in life that are predictive of better mental

health.18 They are not subject to the stressors of unpredict-

ability and lack of control associated with relying exclusively on

salaries or wages for income. As a result, they may enjoy better

health. Even small property owners can derive economic security

from wealth, which is more concentrated among propertyowners than income.19,20 However, since most small businesses

go bankrupt, the suitability of this hypothetical mechanism to

small capitalist class positions is less evident.21 These hypothetical

mechanisms linking property ownership to economic security

were part of the underlying rationale for this study.

Control over organizational assets (power and control in the

workplace) is determined by two kinds of relations at work:

(1) influence over company policy (e.g. making decisions over

number of people employed, products or services delivered,

amount of work performed, size and distribution of budgets);

and (2) sanctioning authority (granting or preventing pay raises

or promotions, hiring, firing, or temporally suspending a sub-

ordinate).1 The supervisory and policy making functions of

managers allow them to enjoy greater wealth than workers,for example, through income derived from shares of stock,

incentives, bonuses, and hierarchical pay scales.22 As a conse-

quence, we anticipate that managers will present better health

and mental health than non-managers, in accordance with the

hypothesis derived from asset ownership. Furthermore,

workplace authority relations add another mechanism that may

impact health, i.e. control over ones work and the ability to

extract labour effort from others, increasing ones sense of control

and predictability at work.23 Indeed, the work organization

literature,23 including the Whitehall study,24 suggests that in

addition to greater access to income, wealth, and job security,

control over work may be a mechanism linking managerial class

positions to better health.

Following Erik Wrights class theory, we defined andmeasured managerial class positions according to policy-making

power within the labour process and supervisory functions over

others labour. Social stratification (e.g. occupational categories)

does not define or measure relational mechanisms within the

labour process. Popular stratification measures such as occu-

pational groups cannot generate specific hypotheses because

they are compatible with many potential mechanisms (e.g.

occupational prestige categories, income, authority).

According to Wrights contradictory class locations hypoth-

esis, supervisors are in a special position (i.e. a contradictory

class position in production relations9), subjected both to the

pressure of upper management to discipline the workforce and

the antagonism of subordinate workers, while exerting little

influence over company policy.1 This situation may exposesupervisors to high demands and low control at work, which

are risk factors for mental disorders.5 Therefore, supervisors are

more likely to present poorer mental health than managers.

Wright includes skills/credentials relations as part of his map

of class positions (Figure 1, the expert, semi-skilled, and un-

skilled class positions1). Experts are defined as those holding

jobs that require skills, particularly accredited credentialed

skills, which are scarce relative to their demand by the market.

Experts enjoy a credential rent: their wages are usually above

the cost of the reproduction of their training.9 Semi-skilled and

SOCIAL STATUS AND HEALTH IN SPAIN 951


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bivariate regressions. However, in multivariate Model 1(adjusted by education), the only associations that remained

significant were those involving semi-skilled workers and those

with less than primary education; and in Model 2 only BRG

class V remained associated with poor mental health (Table 5).

As an alternative to Wrights detailed social class structure,

we explored social class relations of property, organizational,

and credential assets separately from each other. Results indicate

that poor health status is associated with supervisor, non-

managerial, semi-skilled, and unskilled class positions among

men and with semi-skilled and unskilled class positions among

women. Poor mental health was also associated with semi-

skilled and unskilled class positions among women. Among

both men and women, credentials are associated with general

health after adjustment for education and BRG. Having acredentialed occupation is protective of health over and above

the amount of education needed to gain access to that kind of

occupation. That is, the same amount of education would not

protect a persons health that much if that person did not use it

to gain a more advantaged social class.

Discussion

The findings from the Barcelona 2000 HIS support several of

our hypotheses with regard to the relationships between social

class and health. Among men, managers and supervisors withhigh credentials had better self-perceived health than men in

other class positions, most notably semi-skilled and unskilled

workers, semi-skilled and unskilled supervisors, petit bourgeois,

and small employers. Although the findings for women were

consistent with those for men, the managerial (i.e. organ-

izational assets) hypothesis could not be confirmed among

women or for mental health outcomes, except for low-level

supervisors, due to large CI, particularly in multivariate models.

Neither social stratification nor social class are related to mental

health in men. This is commonly found with the GHQ.3436 It

is important to note that although social class was not associated

with mental health, the stratification measures, including the

education measure, were not associated with mental health

either. On the other hand, among women both measures ofsocial stratification were associated with mental health.

Among those in capitalist class positions, poor self-perceived

health was rare; however, the small number of representatives

of this class in our sample (46 men and 16 women) reduced the

power of tests involving ownership relations in multivariate

analyses. This problem has also been noted in sociological

surveys.37 In addition, as shown in a British survey on class

structure,38 capitalists who participate in general surveys are

more prone to be misclassified than members of other class

positions, and further the wealth and power held by large


Table 4 Bivariate and multivariate associations between poor self-perceived health status, social class, and social stratification. Working men and

women population, 1664 years old. Barcelona 2000

Men Women

Bivariatea Model 1 Model 2 Bivariatea Model 1 Model 2

Variables OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI

EO Wright classification

Capitalists 2.39 0.49, 11.7 1.99 0.40, 9.86 1.93 0.38, 9.83 1.95 0.37, 10.29 1.60 0.30, 8.60 1.44 0.26, 8.13

Small employers 5.86 2.14, 16.02 4.22 1.50, 11.87 4.39 1.46, 13.2 1.92 0.69, 5.30 1.28 0.43, 3.78 1.09 0.34, 3.42Petit bourgeoisie 4.49 1.63, 12.36 2.98 1.04, 8.50 2.92 0.95, 8.93 1.41 0.51, 3.93 0.92 0.31, 2.73 0.63 0.20, 2.03

Managers experts and

semi-skilled,

supervisors experts 1 1 1 1 1 1

Supervisors

semi-skilled 6.55 2.33, 18.45 4.97 1.72, 14.37 5.05 1.60, 15.9 1.14 0.30, 4.39 1.04 0.27, 4.04 0.78 0.19, 3.18

Supervisors unskilled 6.64 2.30, 19.19 4.15 1.36, 12.66 4.41 1.33, 14.6 2.74 0.95, 7.91 1.78 0.56, 5.67 1.27 0.37, 4.36

Workers experts 2.20 0.70, 6.87 2.34 0.75, 7.32 2.50 0.79, 7.90 0.63 0.19, 2.07 0.64 0.19, 2.07 0.54 0.16, 1.81

Workers semi-skilled 4.91 1.87, 12.83 3.43 1.27, 9.24 3.41 1.16, 10.0 1.79 0.72, 4.47 1.50 0.59, 3.80 1.11 0.40, 3.08

Workers unskilled 7.63 2.99, 19.47 4.49 1.65, 12.16 4.37 1.47, 13.0 3.29 1.38, 7.82 2.00 0.75, 5.32 1.25 0.43, 3.65

2 log likelihood 1464.8 (P 0.00b) 1464.1 (P 0.00b) 1459.0 (P 0.00b) 1376.2 (P 0.00b) 1376.2 (P 0.00b) 1376.2 (P 0.00b)

British Registrar General classification

I 1 1 1 1

II 0.75 0.35, 1.59 0.55 0.25, 1.21 1.57 0.75, 3.27 1.56 0.72, 3.38

III 2.16 1.34, 3.48 1.19 0.65, 2.18 2.37 1.30, 4.32 1.74 0.83, 3.68

IV 3.40 2.15, 5.39 1.96 1.07, 3.56 4.53 2.49, 8.24 3.39 1.58, 7.28V 4.11 2.15, 7.86 2.19 1.00, 4.76 6.19 3.31, 11.59 4.54 2.02, 10.2

2 log likelihood 1450.3 (P 0.00b) 1437.1 (P 0.00c) 1359.6 (P 0.00b) 1345.9 (P 0.00c)

Educational level

University 1 1 1 1

Secondary 1.88 1.24, 2.84 1.28 0.79, 2.07 2.00 1.34, 2.98 1.29 0.75, 2.22

Primary 3.25 2.23, 4.74 2.15 1.35, 3.40 2.65 1.81, 3.87 1.68 0.98, 2.88

Less than primary 3.82 2.22, 6.60 2.58 1.41, 4.73 6.78 3.99, 11.54 4.43 2.31, 8.51

2 log likelihood 1462.1 (P 0.00b) 1445.1 (P 0.00c) 1368.5 (P 0.00b) 1350.3 (P 0.00c)

a Different regressions models for each variable.b P-value of the model.c P-value of adding the new variable (BRG classification or educational level) to the model after inclusion of other measures.

Age was also included in the models.


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employers makes them less likely to be reached or to be

motivated to participate in surveys. This may be a limitation ofcontemporary survey research that could be overcome with

qualitative research (e.g. ref. 39). The poor health of the petit

bourgeois in our sample could reflect the competition (and high

rates of business failure) that this social class typically experi-

ences, especially in the 21st century marketplace dominated by

large corporations.1,8,10 Similar results were described by

Benach et al.40 Using the 3rd European Survey on Working

Conditions, they found that in the European Union (EU) small

employers were at greater risk of reporting high levels of stress

and fatigue and low dissatisfaction and absenteeism.

Interestingly, in our study men in low-level supervisory class

positions (i.e. unskilled supervisors) showed a higher rate of

poor mental health than semi-skilled and unskilled workers.

This is consistent with the notion that contradictory classrelations are mentally hazardous. Multivariate results showing

that unskilled supervisors, but not semi-skilled or unskilled

workers, were more likely to present poor mental health

than managers and expert supervisors, are also consistent

with this. Low-level supervisors are the de facto management

to workers, while simultaneously occupying the position of

workers in relation to upper management, and they are in

conflict with both.9 These findings are consistent with the

results from a survey conducted in Baltimore (USA), in the

mid 1990s.5

As expected, experts were found to enjoy better health than

non-experts. The health consequences of the skill-credentialsdimension may be crucial for individuals occupying dual class

positions. Scarce credentials (i.e. expertise) confer a notable

health benefit to low-level supervisors. However, because Wrights

indicators of skills/credentials are similar to occupational strati-

fication, it is unclear whether the skill/credential measure is

actually a measure of social stratification or a measure of social

class proper.

The finding that credentialed occupations are protective of

health over and above the amount of education needed to gain

access to that occupation is consistent with a materialist rather

than a psychosocial interpretation.16

In addition to the limitations of cross-sectional data for draw-

ing causal inferences, our survey was restricted to the employed

population and thus we were not able to ascertain the social classpositions of those working outside the labour market, such as the

mediated class positions of family members (dependent elderly,

children, housewives devoted to unpaid household labour), or

class trajectory positions (students). This is important mainly for

women because in Spain the participation of women in the

labour market is lower than in other countries of the EU (in

1998 womens activity rate was 37%, whereas the mean of the

EU was 46%).41 Although the survey was large, some lack of

power was noted in using Wrights class scheme given the number

of categories it contains. In future research involving general

956 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Table 5 Bivariate and multivariate associations between poor mental health status, social class and social stratification. Working men and women

population, 1664 years old. Barcelona 2000

Men Women

Bivariatea Model 1 Model 2 Bivariatea Model 1 Model 2

Variables OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CI

EO Wright classification

Capitalists 1.62 0.48, 5.45 1.54 0.45, 5.26 1.69 0.49, 5.87 1.52 0.25, 9.21 1.34 0.22, 8.25 1.60 0.25, 9.99

Small employers 1.87 0.85, 4.10 1.79 0.79, 4.03 1.98 0.83, 4.73 2.74 1.04, 7.24 2.16 0.78, 5.95 2.51 0.88, 7.17Petit bourgeoisie 1.77 0.80, 3.88 1.69 0.74, 3.86 1.71 0.71, 4.14 2.08 0.78, 5.57 1.72 0.62, 4.79 1.69 0.58, 4.85

Managers experts and

semi-skilled,

supervisors experts 1 1 1 1 1 1

Supervisors

semi-skilled 1.77 0.76, 4.10 1.67 0.70, 3.97 1.82 0.71, 4.65 2.08 0.66, 6.55 1.97 0.62, 6.21 1.98 0.61, 6.41

Supervisors unskilled 2.99 1.35, 6.65 2.80 1.18, 6.65 3.28 1.27, 8.51 2.95 1.08, 8.03 2.25 0.77, 6.58 2.55 0.84, 7.78

Workers experts 1.30 0.57, 2.97 1.32 0.58, 3.03 1.17 0.50, 2.75 1.48 0.56, 3.90 1.52 0.58, 4.01 1.35 0.51, 3.62

Workers semi-skilled 1.90 0.96, 3.77 1.82 0.89, 3.73 1.89 0.85, 4.19 2.65 1.12, 6.28 2.44 1.02, 5.82 2.40 0.95, 6.02

Workers unskilled 1.79 0.92, 3.49 1.69 0.80, 3.50 1.92 0.83, 4.44 2.57 1.11, 5.93 1.91 0.76, 4.79 1.94 0.73, 5.14

2 log likelihood 1394.3 (P= 0.42b) 1393.0(P= 0.42b) 1386.2 (P= 0.42b) 1563.4 (P= 0.21b) 1563.4 (P= 0.21b) 1563.4 (P= 0.21b)

British Registrar General classification

I 1 1 1 1

II 1.64 0.96, 2.79 1.37 0.76, 2.46 1.50 0.88, 2.57 1.33 0.76, 2.35

III 1.40 0.89, 2.22 0.91 0.50, 1.65 1.29 0.82, 2.04 1.02 0.58, 1.79

IV 1.40 0.89, 2.20 0.96 0.53, 1.73 1.91 1.21, 3.02 1.55 0.86, 2.81

V 1.80 0.91, 3.57 1.18 0.52, 2.66 2.35 1.39, 3.97 2.01 1.03, 3.93

2 log likelihood 1391.2 (P= 0.46b) 1383.4 (P= 0.58c) 1565.6 (P 0.00b) 1550.8 (P= 0.01c)

Educational level

University 1 1 1 1

Secondary 1.44 1.00, 2.07 1.17 0.75, 1.83 1.56 1.13, 2.15 1.46 0.93, 2.28

Primary 1.27 0.88, 1.84 1.03 0.65, 1.64 1.28 0.91, 1.79 1.22 0.76, 1.95

Less than primary 1.15 0.57, 2.34 0.94 0.44, 2.01 2.21 1.27, 3.84 2.10 1.10, 4.00

2 log likelihood 1400.2 (P= 0.40b) 1392.0 (P= 0.83c) 1571.1 (P= 0.02b) 1557.0 (P= 0.09c)

a Different regressions models for each variable.b P-value of the model.c P-value of adding the new variable (BRG classification or educational level) to the model after inclusion of the other measures.

Age was also included in the models.


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population samples, the number of categories in Wrights class

framework should perhaps be reduced. Additionally, in studies of

social class inequalities in health, specific class positions (managers,

capitalists) may need to be over-sampled, just as ethnic and

racial minorities must be over-sampled.

Among men, neither the occupation-based BRG nor education

seems to be a better predictor of self-perceived health than social

class. Among women, we did not obtain strong associations. How-ever, non-measured aspects of gender (exposure to worse working

conditions and lack of access to labour markets; household labour

and social networks9,14,42) could account for these results.

Our findings add to the literature on comparative indicators of

social inequalities and highlight the importance of control over

material resources,4347 or in Wrights terms, control over organ-

izational assets. Our results confirm recent studies57 in which

social class, understood as a social relation of ownership or control

over productive assets, explains some aspects of the variation in

health outcomes, while social stratification explains others.

We can draw several conclusions from this study. Our find-

ings suggest that surveys in social epidemiology could benefit

from over-sampling large employers in order to assess the

health impact of capitalist class positions, which are poorlyrepresented in general population samples.38,48 The poor

mental health found among low-level supervisors, replicating a

previous study, suggests that inquiry into the mental health

effects of contradictory class positions may be a fruitful venue

for future research. Furthermore, our study findings indicate that

control over organizational assets, as captured by the power to

hire and fire labour and decision-making power over company

policy, may be an important determinant of social inequalities

in health. Thus, our findings highlight the potential health

consequences of social class positions defined by power

relations within the labour process. They also confirm that

social class taps into parts of the social variation in health that

are not captured by conventional measures of social stratification

and education.

Acknowledgements

This study was supported with funds from the Municipal

Institute of Public Health of Barcelona, Spain. The authors want

to thank Wylbur Hadden for his helpful comments.

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use a development of the Goldthorpe schema, the National

Statistics Socio-Economic Classification (NS-SEC).18,19 What

these have in common are a concern with power and control at

the workplace: control over ones own working day and work

career and power over the work of others. Thus, the conceptual

basis for social class is totally different to that underlying

stratification. Most importantly, class is an inherently relational

concept. It is not defined according to an order or hierarchy, butaccording to relations of power and control.

According to Wright, power or authority are organisational

assets that allow some workers to benefit from the abilities and

energies of other workers.17 The hypothetical pathway linking

class (as opposed to prestige) to health is that some members of

a work organization are expending less energy and effort and

getting more (pay, promotions, job security, etc.) in return,

while others are getting less for more effort. So the less

powerful are at greater risk of running down their stocks of

energy and ending up in some kind of physical or psychological

health deficit. French industrial sociologists called this lusure

de travailthe usury of work. At the most obvious level, the

manager sits in an office while the routine workers are exposed

to all the dangers of heavy loads, dusts, chemical hazards andthe like. But we are all familiar with other situations: the

academic supervisor who takes credit for the work of a graduate

student or junior researcher; the manager who takes the credit

for the efficiency of a secretary. The same process occurs in

every organization where power is unequal. So the use of the

Wright schema in health research, as Muntaner et al. point out

Provides an explicit relational mechanism that explains how

economic inequalities are generated and how they may affect

health.

The authors have used, as their contrast to the Wright class

measure, not one of the American socioeconomic status

measures but a Spanish derivation of the British Registrar-

Generals classification (RGSC). The RGSC has been described

variously as an indicator of skill level or of general standing inthe community (which sounds like prestige). But there was

never any system behind the measure, most occupations were

given the same class as in the previous decennium unless a

member of the decision making group happened to have

enough knowledge of any specific one to raise questions. The

story used to be told about one of the civil servants deciding on

the class position of a newly emerging occupation on the basis

of whether he would like his daughter to marry one. This is, of

course, a perfectly valid method for the allocation of caste

membership in ethnographic studies. Given that the measure

has been widely used in Spanish epidemiological studies, and

that it is used here as an indicator of the RG classification to

indicate a prestige dimension of stratification, it seems a

reasonable choice.Muntaner et al. directly address the extent to which the use

of a specific class measure actually tells us any more than we

could learn from a measure of income or of prestige by

considering the health of people in some of Wrights

contradictory class locations. Supervisors have higher incomes

and prestige than non-supervisory workers, so on this basis

their health should be better. However, taking account of the

relationships between supervisors and other workers might lead

to a different expectation. There are contradictory pressures on

supervisors, in that they are subject to the authority of those

above them but also suffer the antagonism of those below. Sure

enough, the worst mental (not physical) health in the authors

analysis was found amongst unskilled supervisors; the group

thought most likely to have responsibility without very much

power. This effect seems to have been independent of any

association between Wright class and education or the Spanish

version of the RG schema.

An important point to emerge from the results is the dis-tinction between expertise and education. In fact, the relative

weakness of education itself as a predictor of health is striking.

After adjustment for educational level, experts of various kinds

seem to have relatively low risk of ill-health, both mental and

physical. The paper is therefore showing us that it is not edu-

cation per se that favourably influences health, but the access

education gives to more dominant (or less-dominated) social

positions. Of course, any examination of the relationships of

class or education to health needs to take account of the relevant

national labour market. There may be very large differences

between the experience of being the owner of a small or medium

sized company in Spain, the UK, and the US. But in many

countries, the employment situation of someone designated as

an expert within a large organization, say a university or gov-ernment bureaucracy, may be little different to an extended

vacation. The owner/manager of a company employing

20 people (who counts as a capitalist by the Wright criteria), on

the other hand, may be consigned to near-slavery by

comparison.

Indiscriminate use of measures of social position with multiple

theoretical bases (or none at all) has hindered progress from the

description of health inequality towards its explanation. It has

been all too easy to slip into the kind of lazy thinking that

proceeds: high social class equals general superiority in lots

of ways equals better health, what do you expect?. Relational

social class measures may show weaker associations to some

health outcomes than prestige or income. But then we will at

least be able to eliminate some potential causal pathways andconcentrate on those that are better supported by the data.

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