Injury severity and increased socioeconomic differences: A population-based cohort study

Christian Madsen; Belinda J Gabbe; Kristin Holvik; Kari Alver; Else Karin Grøholt; Johan Lund; Jane Lyons; Ronan A Lyons; Eyvind Ohm

doi:10.1016/j.injury.2022.03.039

Injury severity and increased socioeconomic differences: A population-based cohort study

Injury. 2022 Jun;53(6):1904-1910. doi: 10.1016/j.injury.2022.03.039. Epub 2022 Mar 24.

Authors

Christian Madsen¹, Belinda J Gabbe², Kristin Holvik³, Kari Alver⁴, Else Karin Grøholt⁴, Johan Lund⁴, Jane Lyons⁵, Ronan A Lyons², Eyvind Ohm⁴

Affiliations

¹ Department of Health and Inequality, Norwegian Institute of Public Health, Oslo, Norway. Electronic address: Christian.Madsen@fhi.no.
² School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Health Data Research UK, Swansea University Medical School, Singleton Park, Swansea, UK.
³ Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway.
⁴ Department of Health and Inequality, Norwegian Institute of Public Health, Oslo, Norway.
⁵ Health Data Research UK, Swansea University Medical School, Singleton Park, Swansea, UK.

PMID: 35365351
DOI: 10.1016/j.injury.2022.03.039

Abstract

Background: Several studies have documented an inverse gradient between socioeconomic status (SES) and injury mortality, but the evidence is less consistent for injury morbidity. The aim of this study was to investigate the association between SES and injury severity for acute hospitalizations in a nationwide population-based cohort.

Methods: We conducted a registry-based cohort study of all individuals aged 25-64 years residing in Norway by 1st of January 2008. This cohort was followed from 2008 through 2014 using inpatient registrations for acute hospitalizations due to all-cause injuries. We derived two measures of severity: threat-to-life using the International Classification of Disease-based Injury Severity Score (ICISS), and threat of disability using long-term disability weights from the Injury-VIBES project. Robust Poisson regression models, with adjustment for age, sex, marital status, immigrant status, municipality population size and healthcare region of residence, were used to calculate incidence rate ratios (IRRs) by SES measured as an index of education, income, and occupation.

Results: We identified 177,663 individuals (7% of the population) hospitalized with at least one acute injury in the observation period. Two percent (n = 4,186) had injuries categorized with high threat-to-life, while one quarter (n = 43,530) had injuries with high threat of disability. The overall adjusted IRR of hospitalization among people with low compared to high SES was 1.57 (95% CI 1.55, 1.60). Comparing low to high SES, injuries with low threat-to-life were associated with an IRR of 1.56 (95% CI 1.54, 1.59), while injuries with high threat-to-life had an IRR of 2.25 (95% CI 2.03, 2.51). Comparing low to high SES, injuries with low, medium, and high threat of disability were associated with IRRs of respectively, 1.15 (95% CI 1.11, 1.19), 1.70 (95% CI 1.66, 1.73) and 1.99 (95% CI 1.92, 2.07).

Discussion: We observed an inverse gradient between SES and injury morbidity, with the steepest gradient for the most severe injuries. This suggests a need for targeted preventive measures to reduce the magnitude and burden of severe injuries for patients with low socioeconomic status.

Keywords: Hospitalization; ICISS; Injury; Injury-VIBES; Risk-adjusted severity; Socioeconomic status.

MeSH terms

Cohort Studies
Humans
Incidence
Income*
Injury Severity Score
Social Class*
Socioeconomic Factors