We have located links that may give you full text access.
Learning from the census: the Socio-economic Factor Index (SEFI) and health outcomes in Manitoba.
OBJECTIVES: Using data from the Canadian census, researchers at the Manitoba Centre for Health Policy sought to create an area-based socio-economic measure (ABSM). The degree of association between the ABSM and health was evaluated.
METHODS: Values on several census variables (including income, education, employment and family structure) were captured at the enumeration-area or dissemination-area level and submitted to a principal components factor analysis to create three ABSMs: an updated version of the Socio-economic Factor Index (SEFI-2) and modified versions of Pampalon's material deprivation and social deprivation indices. Factor scores from these analyses were then compared with several population health measures: Premature Mortality Rate (PMR), Potential Years of Life Lost (PYLL), life expectancy, and self-rated health.
RESULTS: SEFI-2 scores were strongly related not only to the other ABSMs but also to every measure of health status. The strongest correlations between an ABSM and health measure were for SEFI-2 and PYLL(r=0.85), and SEFI-2 and PMR (r=0.80). The weakest correlations were found with the social deprivation ABSM measure and the self-rated health measure.
CONCLUSIONS: ABSMs based on measures from the Canadian census are a valuable resource to population health researchers. Importantly, depending on the research question and reason for the inclusion of an ABSM, these composite measures may perform better than a simple measure of income alone. The ability to adjust for socio-economic status when assessing population health status or population health interventions contributes to the validity of conclusions drawn when conducting this type of research, and ABSMs may be able to substitute for area health status where it may not be easily determined.
METHODS: Values on several census variables (including income, education, employment and family structure) were captured at the enumeration-area or dissemination-area level and submitted to a principal components factor analysis to create three ABSMs: an updated version of the Socio-economic Factor Index (SEFI-2) and modified versions of Pampalon's material deprivation and social deprivation indices. Factor scores from these analyses were then compared with several population health measures: Premature Mortality Rate (PMR), Potential Years of Life Lost (PYLL), life expectancy, and self-rated health.
RESULTS: SEFI-2 scores were strongly related not only to the other ABSMs but also to every measure of health status. The strongest correlations between an ABSM and health measure were for SEFI-2 and PYLL(r=0.85), and SEFI-2 and PMR (r=0.80). The weakest correlations were found with the social deprivation ABSM measure and the self-rated health measure.
CONCLUSIONS: ABSMs based on measures from the Canadian census are a valuable resource to population health researchers. Importantly, depending on the research question and reason for the inclusion of an ABSM, these composite measures may perform better than a simple measure of income alone. The ability to adjust for socio-economic status when assessing population health status or population health interventions contributes to the validity of conclusions drawn when conducting this type of research, and ABSMs may be able to substitute for area health status where it may not be easily determined.
Full text links
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app