Department of Epidemiology and Public Health, University College London, 119 Torrington Place, London WC1E 6BT, UK. E-mail: m.bartley{at}public-health.ucl.ac.uk
Muntaner et al.1 have taken on one of the major issues for social epidemiology today. For many years now, we have seen study after study showing relationships between health and some measure or other of socioeconomic position and circumstances. But, with honourable exceptions, studies have rarely faced up directly to the problems involved in the conceptualization and measurement of socioeconomic position (SEP).26 There is seldom any account of how it has been decided to use one or other method. Studies are then compared with little consideration for the fact that some use indicators of income, others use indicators of prestige, and others use education.7,8 Even to make the distinction between class and prestige is likely to sound rather strange to many readers.
As Muntaner et al. point out, the most commonly used measures of SEP have been indicators of position in a system of stratification. The term stratification is used in sociology to refer to social hierarchies in which individuals or groups can be arranged along a ranked order of some attribute. Income is one such. A more popular one is social status or prestige.9 In the US, there have been several large scale surveys that ask respondents to rank large numbers of occupations10 in terms of prestige. However, these lists cannot be exhaustive. The most widely used measures in the US therefore extrapolate prestige for all other occupations on the basis of income and education levels.1012 This is a perfectly consistent procedure, because prestige, income, and education are all ordered from high to low. There may be problems in mixing the three up together, rather than trying to estimate their relationships to health separately, but that is a different story.13
The measurement of social class, if we use this term in the sociological sense, is quite different. Class, in contrast to stratification, indicates the employment relations and conditions of each occupation. The criteria used to allocate occupations into classes vary somewhat between the two major systems presently in widespread use: the Goldthorpe schema (and its developments) and the Wright schema.1417 Muntaner et al. describe clearly the classificatory principals of the Wright schema, which they used in their paper. Official statistics in Great Britain now 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, but according 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 and the 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 in the 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 distinction 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 education 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 government 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 and concentrate on those that are better supported by the data.
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