Commentary: Modelling multiple pathways to explain social inequalities in health and mortality

Abstract

Investigations into socioeconomic inequalities in health and mortality have primarily been carried out in the US and in Europe, 1‐3 therefore reports from other parts of the world are a welcome addition to the effort to explicate pathways linking social structure to health and mortality. Research on social inequalities in Korea is particularly interesting as it has undergone rapid industrialization, with the GDP per head increasing 100-fold in � 40 years. 4 In this issue of the International Journal of Epidemiology, Khang and colleagues show socioeconomic differentials in mortality in South Korea to be better explained by early life exposures compared with biological risk factors, health behaviours, and psychosocial factors. 5 The authors point out that it is the latter that explain more of the social gradient in mortality in the western countries. They argue that this discrepancy in the relative importance of different pathways might lie in the differential cause-specific structure of mortality in Korea. The authors recognize that this hypothesis needs to be further tested in agespecific analyses in order to control for cohort effects, before firm conclusions about the relative importance of different pathways can be drawn. In this commentary, I suggest that another aspect that requires further effort is attention to the modelling of interrelationships between variables. The examination of pathways explaining socioeconomic differentials in mortality is not straightforward. Consider a simple example with three variables: an exposure (X), here socioeconomic position; an outcome (Y), here mortality, and a third related variable (A). These variables could be associated with each other in at least four different ways (Figure 1), described below; each of which would require a different statistical treatment to assess the impact of X and A on Y. 1. The relationship between X and Y could be mediated by an intervening causal variable, A. This could either be a single variable (A) or a series of variables (A1, A2, A3, etc). Thus the exposure would have a ‘direct’ effect (pathway XY) on the outcome and (or) an ‘indirect’ effect (pathway XA + AY), mediated through its effect on A. 2. The relationship between X and Y could be moderated by a variable, A. This implies that the strength of the relationship between the exposure (X) and the outcome (Y) would depend upon the moderator (or effect modifier), as this variable specifies the conditions under which X will produce Y.