AUTHOR=Lu Katherine , Kornas Kathy , Rosella Laura C. 

TITLE=Predictive Modelling of Diabetes Risk in Population Groups Defined by Socioeconomic and Lifestyle Factors in Canada: A Cross-Sectional Study

JOURNAL=International Journal of Public Health

VOLUME=Volume 69 - 2024

YEAR=2024

URL=https://www.ssph-journal.org/journals/international-journal-of-public-health/articles/10.3389/ijph.2024.1607060

DOI=10.3389/ijph.2024.1607060

ISSN=1661-8564

ABSTRACT=Objective: This study modelled diabetes risk for population groups in Canada defined by socioeconomic and lifestyle characteristics and investigate inequities in diabetes risk using a validated population risk prediction algorithm. Methods: We defined population groups, informed by determinants of health frameworks. We applied the Diabetes Population Risk Tool (DPoRT) to 2017/2018 Canadian Community Health Survey data to predict 10-year diabetes risk and cases across population groups. We modelled a preventive intervention scenario to estimate reductions in diabetes for population groups and impacts on the inequity in diabetes risk across income and education. Results: The population group with at least one lifestyle and at least one socioeconomic/structural risk factor had the highest estimated 10-year diabetes risk and number of new cases. When an intervention with a 5% relative risk reduction was modelled for this population group, diabetes risk decreased by 0.5% (females) and 0.7% (males) and the inequity in diabetes risk across income and education levels was reduced. Conclusions: Preventative interventions that address socioeconomic and structural risk factors have potential to reduce inequities in diabetes risk and overall diabetes burden.