We use a set of biomarkers to measure inequality of opportunity (IOp) in the risk of major chronic conditions in the UK. Applying a direct ex ante IOp approach, we find that inequalities in biomarkers attributed to circumstances account for a non-trivial part of the total variation. For example, observed circumstances account for 20 % of the total inequalities in our composite measure of multi-system health risk, allostatic load. We propose an extension to the decomposition of ex ante IOp to complement the mean-based approach, analysing the contribution of circumstances across the quantiles of the biomarker distributions. Shapley decompositions show that, for most of the biomarkers, the percentage contribution of socioeconomic circumstances (education and childhood socioeconomic status), relative to differences attributable to age and gender, increase towards the right tail of the biomarker distribution, where health risks are more pronounced.
Keywords: Biomarkers; Equality of opportunity; Non-communicable diseases; Shapley decomposition; Unconditional quantile regression.
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