ArticleBMJ public health2026
Which social determinants of health and long-term conditions contribute to inequalities in avoidable emergency hospital admissions? A decomposition analysis of small-area data in England.
Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The burden of avoidable emergency admissions (AEAs) to hospital is an international concern. AEAs are unequally distributed across society with areas of socioeconomic disadvantage experiencing far more than their more affluent counterparts. Tackling inequalities in AEAs, through a better understanding of the contributing factors, could potentially free up resources for other parts of the health and care system. This study is the first to track income-inequality in AEAs over time and decompose which health and socio-economic factors contribute to those inequalities in England, an understanding of which is vital for policymakers to take effective action to reduce the burden of AEAs. Methods: Counts of AEAs for the 6,791 administrative areas in England for 2012/13 and 2018/19 were linked to household income, social determinants of health (SDOH) and the prevalence of long-term conditions (LTCs) data. Concentration indices were estimated to measure income-inequality in AEAs which were decomposed to estimate the contribution of income, age and sex, LTCs, SDOH factors and regional differences to income-inequality in AEAs. Results: The negative but increasing concentration indices indicate substantial but improving income-inequality in AEAs between 2012/13 and 2018/19. Over this time, income contributed to just a quarter of the observed income-inequality in AEAs. The aggregate contribution of SDOH factors rose from 39% to 51% while the contribution of the LTCs shrank from 20% to 7%. Significant, unexplained regional differences in AEAs indicate an ingrained North-South divide. Conclusion: Policy should target the reduction of AEAs in Northern post-industrial towns where the top contributing factors cluster.
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