Income, education, and hospitalization in Canada: results from linked census and administrative data

• Main Authors: Jenny Godley (Author), Karen L. Tang (Author)
• Format: Book
• Published: Springer, 2022-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1007/s44155-022-00023-z; 2731-0469
• Keywords: Socio-economic inequality; Hospitalization; Canada; Data Linkage; Public aspects of medicine; RA1-1270; Social Sciences; H
• Source: Discover Social Science and Health, Vol 2, Iss 1, Pp 1-17 (2022)

Abstract Background Addressing population health inequities begins with quantifying how social factors affect the health and health care utilization of individuals. Such quantification relies on the availability of detailed health and demographic data. Unfortunately, administrative health care data rarely includes detailed demographic information. Data linkage, which combines administrative health data with national-level census or survey data, enables researchers to examine socio-economic inequalities in health care utilization in greater detail. Data and methods With access to a unique Canadian dataset linking data from the Hospital Discharge Abstract Database (DAD) from 2006 to 2007 with detailed individual-level socio-demographic data from the 2006 Canadian Census, we are able to examine the patterning of hospitalization in Canada in the early 2000s across a variety of socio-demographic variables. We examine the association of education and income, controlling for immigration status, rural residence, marital status and ethnicity, with hospitalization rates for both ambulatory care sensitive conditions (ACSCs) and non-ambulatory care sensitive conditions (non-ACSCs) for children and youth, working-age adults, and older adults, in models stratified by sex. Results Age standardized hospitalization rates show that there is a clear socio-economic gradient in hospitalization in Canada in the 2000s. Education and income are independently, inversely associated with hospitalization for males and females across three broad age groups. These associations are stronger for ACSCs than non-ACSCs. The association of other socio-demographic variables, such as immigrant status, and rural residence is also stronger for hospitalization for ACSCs. The association of socio-economic status with hospitalization for ACSCs is strongest for working age women and men, and is somewhat attenuated for older adults. Conclusions Lower socio-economic status is associated with a higher likelihood of hospitalization for men and women in Canada across three broad age groups in the 2000s. These associations are stronger for ACSCs, suggesting that in addition to increased likelihood of disease, decreased access to preventative care may be driving up hospitalization rates for marginalized groups. We conclude with the recommendation that in order to track progress in reducing health inequities, health systems should either collect detailed individual-level socio-demographic data or link their administrative health data to existing demographic data sets.