Commentary: Cheap but cheerless. Is it the underpaid or the overworked who die young?

Chris Metcalfe

Medical Research Council Biostatistics Unit, Institue of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, UK. E-mail: chris.metcalfe{at}mrc-bsu.cam.ac.uk


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 Introduction
 References
 
It has long been recognized that members of families dependent upon manual work for their subsistence experience higher rates of many diseases, and have a shorter life expectancy than those in families depending upon non-manual work. Efforts to explain this disparity have as long a history as those directed at its evaluation. In his account of the living and working conditions of factory employees and their families in northern England during the 1840s, Engels proposes a number of ways in which manual work may impact on the health of the worker.1 He describes the very direct consequences of work with inadequately guarded machinery, citing several accounts of dismemberment and death. Engels also suspected that other characteristics of factory work, such as long hours, shift work, protracted periods of standing, and the sheer dehumanizing monotony of being a machine operative, may have less immediate but more widespread consequences for poor health. Out of necessity Engels based his account on the observation of simple associations between working conditions and the prevalence of disease; he had neither the data nor the statistical methods at his disposal to do otherwise. Once the census data, mortality returns, and statistical techniques required for a more sophisticated analysis became available, Engels' broad perspective had become unfashionable. As stated in ‘The Black Report‘, concern at that time was focused on the occurrence of accidents and the chemical hazards associated with particular industries.2 Following publication of The Black Report by Penguin Books in 1982, there has been a renewed interest in the effects of a broader range of working conditions on health.3

This is the perspective taken by Virtanen and Notkola in this issue of the International Journal of Epidemiology.4 Virtanen and Notkola have measures of a broad range of working conditions for a cohort representing a sizable portion of the late 1970s Finnish workforce. The data are linked to national statistics on cardiovascular caused deaths over the subsequent 15 years. Such a data set allows investigation of the relative importance of different factors, while account is taken of their inter-relationships. Unfortunately it does not appear that information was available on recognized cardiovascular disease risk factors such as cigarette smoking and alcohol consumption.

Virtanen and Notkola use a job exposure matrix (JEM) to evaluate exposure to chemical hazards and particular working conditions. Hence data were not available on the exposure of individual workers; a JEM describes different occupations in terms of the average exposure of those so employed to different potential pathogens.5 Consequently, for chemical hazards and working conditions, each cohort member's exposure is estimated as the average for the job they hold. In contrast, individual-level measures of education and income were directly available from relevant census questions. Occupation was also available from a census question, and responses to this question were used to categorize each individual according to occupational class and occupational category.

In general, more accurate assessments of exposure will result when measurements are at the level of the individual, rather than at the level of occupation. This presents a problem when evaluating the relative contribution of different phenomena to socioeconomic mortality differences. All else being equal, multiple regression analysis will tend to highlight the factors that are measured most accurately, especially when those factors are correlated.6 It is possible that the relative importance of income and education have been overestimated in Virtanen and Notkola's study, due to their more accurate measurement.

A further well-recognized problem is that the observed importance of particular factors to the explanation of socioeconomic mortality differentials will depend, in part, on how socioeconomic position is derived.7 For example, when using occupational class as the measure, working conditions such as autonomy are likely to be found to be more important than measures of material circumstances such as income and home ownership. The autonomy of workers in a particular occupation is, after all, one aspect of an occupation that places it on the occupational class continuum. As suggested by Macleod and colleagues, in this way studies such as Virtanen and Notkola's study may overestimate the relative importance of working conditions.8

In their regression analyses Virtanen and Notkola use an unusual comparison (baseline) group. The comparison group comprises those in the most privileged socioeconomic or occupational group who also, as far as possible, experience minimal exposure to potentially harmful working conditions. This choice of comparison group, as the authors state, will amplify the observed effects of social class and occupational group, because not only are we observing the effect of membership of socioeconomic groups, but also the full effect of working conditions. As the effect of working conditions is ‘controlled’ by their inclusion in an adjusted regression model, their influence on the observed effects will, as usual, be removed.

Virtanen and Notkola conclude that differences in income and education are more important than working conditions as mediators of the socioeconomic inequalities in cardiovascular mortality. The importance of these factors did not escape Engels and he discusses them extensively. Limited education and low income are likely to exert their influence on health through multiple pathways. For example, impeded access to adequate housing and nutritious food are discussed by Engels and in more contemporary accounts.9 Whether we accept Virtanen and Notkola's conclusion that income and education are of primary importance depends upon the extent to which we feel a fair comparison has been made. While we now have data and statistical methods of much greater sophistication than those available to Engels, difficulties remain in the measurement of working conditions. This, and the complex inter-relations between the different aspects and consequences of manual work, make it unfeasible that any single data set will be sufficient to uncover the nature of socioeconomic mortality differences. However, Virtanen and Notkola have contributed to the growing evidence base for this important issue.


    References
 Top
 Introduction
 References
 
1 Engels F. The Condition of the Working Class in England. Harmondsworth: Penguin, 1987. (First edition: 1845).

2 Townsend P, Davidson N. Inequalities in Health: The Black Report. Harmondsworth: Penguin, 1982.

3 Davey Smith G, Bartley M, Blane D. The Black report on socioeconomic inequalities in health 10 years on. BMJ 1990;301:373–77.[ISI][Medline]

4 Virtanen SV, Notkola V. Socio-economic inequalities in cardiovascular mortality and the role of work: a register study of Finnish men. Int J Epidemiol 2002;31:614–21.[Abstract/Free Full Text]

5 Goldberg M, Kromhout H, Guénel P et al. Job exposure matrices in industry. Int J Epidemiol 1993;22(Suppl.2):S10–S15.[ISI][Medline]

6 Phillips AN, Davey Smith G. How independent are ‘independent’ effects? Relative risk estimation when correlated exposures are measured imprecisely. J Clin Epidemiol 1991;44:1223–31.[ISI][Medline]

7 Geyer S, Peter R. Income, occupational position, qualification and health inequalities—competing risks? (Comparing indicators of social status). J Epidemiol Community Health 2000;54:299–305.[Abstract/Free Full Text]

8 Macleod J, Davey Smith G, Heslop P, Metcalfe C, Carroll D, Hart C. Are the effects of psychosocial exposures attributable to confounding? Evidence from a prospective observational study on psychological stress and mortality. J Epidemiol Community Health 2001;55:878–84.[Abstract/Free Full Text]

9 Blane D, Bartley M, Davey Smith G. Disease aetiology and materialist explanations of socioeconomic mortality differentials. Eur J Public Health 1997;7:385–91.[Abstract]





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