What is the relationship between age and deprivation in influencing emergency hospital admissions? A model using data from a defined, comprehensive, all-age cohort in East Devon, UK

Objectives

To clarify the relationship between social deprivation and age as two factors associated with emergency admissions to hospital.

Design

Emergency admissions for 12 months were analysed for patients in the NHS NEW Devon CCG. Social deprivation was measured by the Index of Multiple Deprivation (IMD). Logistic regression models estimated the separate and combined effects of social deprivation and age on the risk of emergency admissions for people aged under and over 65.

Setting

East Devon, UK—area of the NEW Devon CCG.

Population

765 861 patients in the CCG database.

Main outcome measure

Emergency admission to any English hospital.

Results

Age (p<0.001) and social deprivation (p<0.001) were significantly associated with emergency admission to hospital, but there was a significant interaction between age and social deprivation (p<0.001). From the third quintile of age upwards, age progressively overtakes deprivation and age has a dominant effect on emergency admissions over the age of 65. The effect of age was J-shaped in all deprivation groups, increasing exponentially after age 40. For patients under 65, age and social deprivation had similar risks for emergency admissions, the differences in risk between the top and bottom quintiles of IMD and age being ~1.5 and 0.9 percentage points. In patients over 65, age had a much greater effect on the risk of admissions than social deprivation, the differences in risk between the top and bottom quintiles of IMD and age being ~2.8 and 18.7 percentage points.

Conclusions

Risk curves for all social groups have similar shapes, implying a common biological pattern for ageing in any social group. Over age 65, the biological effects of ageing outweigh the social effects of deprivation. Our model enables CCGs to anticipate and plan for emergency admissions to hospital. These findings provide a new logic for allocating resources to different populations.

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