How can socioeconomic inequalities in hospital admissions be explained? A cohort study. Issue 8 (30th August 2013) - McCartney, Gerry; Hart, Carole; Watt, Graham
Abstract : Objectives: To investigate which antecedent risk factors can explain the social patterning in hospital use. Design: Prospective cohort study with up to 37 years of follow-up. Setting: Representative community sample in the West of Scotland. Participants: 7049 men and 8353 women aged 45–64 years were recruited into the study from the general population between 1972 and 1976 (78% of the eligible population). Primary and secondary outcome measures: Hospital admissions and bed days by cause and by classification into emergency or non-emergency. Results: All-cause hospital admission rate ratios (RRs) were not obviously socially patterned for women (RR 1.04, 95% CI 0.98 to 1.10) or men (RR 1.0, 95% CI 0.94 to 1.06) in social classes IV and V compared with social classes I and II. However, cardiovascular disease, coronary heart disease and stroke in women, and respiratory disease for men and women were socially patterned, although this attenuated markedly with the addition of baseline risk factors. Hospital bed days were generally socially patterned and the differences were largely explained by baseline risk factors. The overall RRs of mental health admissions in contrast were socially patterned for women (RR 1.77, 95% CI 1.38 to 2.27) and men (RR 1.51, 95% CI 1.11 to 2.06) in social classes IV and V compared with social classes I and II, but the pattern did not attenuate with the addition of baseline risk factors. Emergency hospital admissions were associated with lower social class, but there was an inverse relationship for non-emergency hospital admissions. Conclusions: Overall admissions to hospital were only marginally socially patterned, and less than would be expected on the basis of the gradient in baseline risk. However, there was marked social patterning in admissions for mental health problems. Non-emergency hospital admissions were patterned inversely according to risk. Further work is required to explain and address this inequitable gradient in healthcare use.