IJE Advance Access originally published online on April 30, 2007
International Journal of Epidemiology 2007 36(2):365-367; doi:10.1093/ije/dym028
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Commentary: Disability and education—the Madonna factor?
Department of Health Sciences, University of York, Heslington, York YO10 5DD, UK.
E-mail: JA14{at}york.ac.uk
Accepted 8 February 2007
Whilst many studies have considered the relationship between socio-economic position and mortality and other chronic illness, less work has been done on the association with measures of disability in older age. However, there is a growing literature on this topic, to which the article by Jagger et al.1 is a welcome addition. Where this contribution is particularly useful is in consideration of the patterns of incidence and recovery from disability, which are currently less well documented. Jagger et al.1, using data from the Medical Research Council Cognitive Function and Ageing Study (MRC CFAS), describe educational differences in disability transitions among individuals over 65 years, finding those with less education have higher prevalence and incidence of mobility disability and ADL disability alongside lower recovery from mobility disability. The large number of participants in this study makes it possible to consider recovery from disability, as some study populations have been hampered by low numbers of individuals experiencing an improvement.
As well as being a good piece of epidemiological research, the article also raises several issues for debate, namely, the measurement of socio-economic position among older people and what this growing body of evidence tells us about the nature of the relationship between socio-economic position and disability.
Researchers consider the relationship between socio-economic position and health for largely one of two reasons. First, to describe any gradient between socio-economic group and a particular health outcome (for example, as an indicator of health and/or social care need). Whilst this may be of interest per se—perhaps more important is the second reason, to provide evidence for a particular mechanism by which socio-economic position is ‘causing’ any observed inequality.
Several studies have considered the relationship between socio-economic position (measures including education, social class, housing tenure, area deprivation, income, perceived financial well-being and material assets) and disability (as measured by mobility disability, overall disability, activities of daily living and disability-free life expectancy)2–5 highlighting that there are inequalities in disability outcome (independent of chronic illness) into old age. However, the presence and magnitude of the association does appear to vary according to the measures used and the study context. Therefore, the findings from Jagger et al.1 are not surprising. This literature does appear to be telling us that disability is preventable, or at least can be compressed, but how does this inform us about potential causal mechanisms, and hence, strategies for intervention to reduce the inequalities?
When setting out to highlight a possible relationship between socio-economic position and outcome, then the particular choice of indicator may not be crucial.6 However, the most appropriate way to measure socio-economic position among older people has been debated, with the conclusion that a combination of measures, in particular, either education or housing tenure be used together with a deprivation score.7 Yet, much of the inequalities literature now advocates that measures with a theoretical underpinning be utilized, in particular to answer questions of potential mechanisms.8 Despite such guidance on the measurement of socio-economic position, the extent to which this is possible—in a field which largely bases its findings from analyses of pre-existing cohort studies, is questionable. Many large data sets, and particularly those which are included in cross-country comparisons have only single (and often different measures of socio-economic position). In many cases, the theoretical standpoint may be post-hoc rationalization for the measure that is available. This was not the case, however, for Jagger et al.1 who selected education as the measure of socio-economic position, from a range of variables available in the MRC CFAS data set.
Education is a commonly used measure among older people, fitting the criteria set out by Grundy and Holt7 to be sufficiently sensitive to enable the identification of a manageable number of hierarchical classifications so that gradients in health inequalities can be observed; and is less likely to suffer from the effects of reverse causation as it reflects achievements in early life. There have been questions around the ability to differentiate well between groups, given that most older people today left school at the minimum age.7 However, in the article by Jagger et al.1, whilst the majority of respondents did fall within the lowest educational category, the cohort included relatively large numbers in the higher two categories (indicating greater years of education). Therefore as a variable with which to highlight inequality in disability, in this case years of education worked well.
The theoretical origins of education lie mainly in attempting to capture ‘knowledge related assets’.6 However, it is important to note that several of the most commonly used indicators of socio-economic position are highly interrelated and do not distinctly map the theoretical domains they are intended to represent. To assume otherwise is likely to be oversimplistic.7 Jagger et al.1 do comment that full time education is a good measure of long-term socio-economic position and, as others also highlight, it will partly determine adult occupation, income, as well as parental characteristics.6 This is discussed by the authors who, after dismissing alternative explanations for their findings, conclude that the impact of education may manifest itself in the ability to adapt to increasing disability either through modifying tasks or employing technical aids. Whilst this may be the case, in the present article this is perhaps a conclusion too far, however, it does raise interesting questions for further research.
If Jagger et al.1 are suggesting that rather than the underlying physical ‘impairment’ being affected by education, it is the experience of ‘disability’ that is patterned by education, then we may wish to consider in more detail the process of ‘adaptation’. For example, is it those older people who have the ‘Madonna factor’, that is, the ability to continually reinvent themselves in the light of progressive physical changes who report less disability as a consequence? Is this simply a matter of individual differences (for example, in psychological resources) or might education impact on the ability to do so and would any impact vary across men and women? Such complex phenomena may appropriately be addressed using qualitative techniques in the first instance. If adaptation is indeed the key to reduced disability would it then, taking this to its logical conclusion, be possible to design interventions based around, for example, strategies for adjustment?
Perhaps more straightforwardly, consideration could be given to the educational patterning of the employment of technical aids. Given equivalent levels of impairment, are those with greater knowledge-related assets more likely to utilize walking sticks, stair lifts or extra rails in the bathroom? If this is indeed the case then—does this highlight an area of unmet need? More information on the barriers to obtaining such equipment among those less educated may provide at least part of the solution.
Disability in old age is a complex phenomenon. Perhaps the identification of detailed data sets which not only have data on socio-economic position across the life course but different measures of disability, use of technical aids and individual differences may hold the key to unpicking some of these observed associations.
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1 Jagger C, Matthews R, Melzer D, Matthews F, Brayne C, MRC CFAS. Educational differences in the dynamics of disability incidence, recovery and mortality: findings from the MRC cognitive function and ageing study (MRC CFAS). Int J Epedemiol (2007) 36:358–65.
2 Matthews RJ, Jagger C, Hancock RM. Does socio-economic advantage lead to a longer, healthier old age? Soc Sci Med (2006) 62:2489–99.[CrossRef][ISI][Medline]
3 Rautio N, Adamson J, Heikkinen E, Ebrahim S. Associations of socio-economic position and disability among older women in Britain and Jyvaskyla, Finland. Arch Gerontol Geriat (2006) 42:141–55.[CrossRef][ISI][Medline]
4 Adamson J, Ebrahim S, Hunt K. The psychosocial versus material hypothesis to explain observed inequality in disability among older adults: Data from the West of Scotland Twenty-07 study. J Epidemiol Community Health (2006) under review.
5 Melzer D, Izmirlian G, Leveille SG, Guralnik JM. Educational differences in the prevalence of mobility disability in old age: the dynamics of incidence, mortality and recovery. J Gerontol: Soc Sci (2001) 56B:S294–S301.
6 Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G. Indicators of socioeconomic position (part 1). J Epidemiol Community Health (2006) 60:7–12.
7 Grundy E, Holt G. The socioeconomic status of older adults: How should we measure it in studies of health inequalities? J Epidemiol Community Health (2001) 55:895–904.
8 Bartley M, Sacker A, Firth D, Fitzpatrick R. Understanding social variation in cardiovascular risk factors in women and men: the advantage of theoretically based measures. Soc Sci Med (1999) 49:831–45.[CrossRef][ISI][Medline]
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