Multimorbidity and Socioeconomic Deprivation among Older Adults: A Cross-sectional Analysis in Five Canadian Cities Using the CLSA

Abstract

Individual socioeconomic status is known to correlate with multimorbidity, but the role of neighbourhood-level socioeconomic deprivation is uncertain. Participants from five cities (n = 16,313) from the Canadian Longitudinal Study on Aging were mapped by postal code and their local area socioeconomic deprivation scores were calculated using the Vancouver Area Neighbourhood Deprivation Index. Logistic regression models were used to estimate deprivation-associated odds of multimorbidity, controlling for age, sex, obesity, alcohol consumption, and tobacco use, and validated using a Bayesian machine learning technique. Significant associations with neighbourhood deprivation were observed, underscoring the importance of a person’s local socioeconomic environment in multimorbidity risk, net of key covariates. The implications of the results are discussed in terms of community and health care organization and intervention programs targeting multimorbidity.

Keywords:

• CLSA
• GIS
• machine learning
• multimorbidity
• socioeconomic deprivation

Acknowledgements

This research was made possible using the data/biospecimens collected by the Canadian Longitudinal Study on Aging (CLSA). The opinions expressed in this manuscript are the authors; own and do not reflect the views of the CLSA.

Additional information

Funding

Funding for the Canadian Longitudinal Study on Aging (CLSA) data collection is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference [LSA 9447] and the Canada Foundation for Innovation. This research has been conducted using the CLSA Comprehensive Cohort dataset [version 1.0], under Application Number [#150914] (https://www.clsa-elcv.ca/). The current study was funded through a CIHR CLSA Catalyst Grant [RN302177 – 373073].