Predictive Modelling of Diabetes Risk in Population Groups Defined by Socioeconomic and Lifestyle Factors in Canada: A Cross-Sectional Study.
Int J Public Health
; 69: 1607060, 2024.
Article
in En
| MEDLINE
| ID: mdl-39229383
ABSTRACT
Objectives:
This study modelled diabetes risk for population groups in Canada defined by socioeconomic and lifestyle characteristics and investigated 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.Conclusion:
Preventative interventions that address socioeconomic and structural risk factors have potential to reduce inequities in diabetes risk and overall diabetes burden.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Socioeconomic Factors
/
Diabetes Mellitus
/
Life Style
Limits:
Adolescent
/
Adult
/
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Country/Region as subject:
America do norte
Language:
En
Journal:
Int J Public Health
Journal subject:
SAUDE PUBLICA
Year:
2024
Document type:
Article
Affiliation country:
Country of publication: