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Int J Equity Health. 2015 Oct 24;14:101. doi: 10.1186/s12939-015-0245-0.

The influence of socioeconomic status on future risk for developing Type 2 diabetes in the Canadian population between 2011 and 2022: differential associations by sex.

Author information

1
Public Health Ontario, 480 University Avenue, Toronto, Ontario, M5G 1 V2, Canada. laura.rivera@gmail.com.
2
Public Health Ontario, 480 University Avenue, Toronto, Ontario, M5G 1 V2, Canada. michael.lebenbaum@ices.on.ca.
3
Public Health Ontario, 480 University Avenue, Toronto, Ontario, M5G 1 V2, Canada. laura.rosella@utoronto.ca.
4
Dalla Lana School of Public Health, University of Toronto, 155 College Street, Health Sciences Building 6th Floor, Toronto, Ontario, M5T 3 M7, Canada. laura.rosella@utoronto.ca.
5
Institute for Clinical Evaluative Sciences, G1 06, 2075 Bayview Avenue, Veterans Hill Trail, Toronto, Ontario, M4N 3 M5, Canada. laura.rosella@utoronto.ca.

Abstract

BACKGROUND:

Articulating future risk of diabetes at the population level can inform prevention strategies. While previous studies have characterized diabetes burden according to socioeconomic status (SES), none have studied future risk.

METHODS:

We quantified the influence of multiple constructs of SES on future diabetes risk using the Diabetes Population Risk Tool (DPoRT), a validated risk prediction algorithm that generates 10-year rates of new diabetes cases. We applied DPoRT to adults aged 30-64 in the 2011-2012 Canadian Community Health Survey (n = 65,372) and calculated risk for 2021-22. A multi-category outcome was created classifying risk as low (≤5%), moderate (greater than 5% and less than 20%), and high (≥20%), then assessed the impact of individual-level SES indicators, and area-level measures of marginalization on being moderate or high risk using multinomial logistic regression, stratified by sex.

RESULTS:

We found nuanced profiles of social determinants by sex, where women are more sensitive to social context. Women living in households where highest educational attainment was less than secondary school were at greater risk [odds ratio (OR) of high compared to low diabetes risk 3.10, 95% confidence interval (CI) 2.19-4.40, p < 0.0001). The same relationship was less pronounced for males (OR 2.17, 95% CI 1.42-3.32, p = 0.0004). Lower household income and being food insecure predicted high future diabetes risk for women (OR 1.37, 95% CI 1.01-1.86, p = 0.0418 comparing quintile 1 to quintile 5; OR 2.64, 95% CI 1.78-3.92, p < 0.0001 comparing severely food insecure to food secure), but not men (OR 1.15, 95% CI 0.84-1.57, p = 0.3818 and OR 1.22, 95% CI 0.71-2.10, p = 0.4815). At the area-level, material deprivation was significantly associated with increased future risk comparing the most to the least deprived (OR females 2.39, 95% CI 1.77-3.23; OR males 1.61, 95% CI 1.22-2.14). Additionally, a strong protective effect was observed for women living in ethnically dense areas (OR 0.75, 95% CI 0.63-0.89, p = 0.0011) which was not as pronounced for men (OR 0.95, 95% CI 0.76-1.18, p = 0.6351).

CONCLUSIONS:

This study characterized socio-contextual predictors for future diabetes risk, showing sex-specific effects. Diabetes prevention must consider factors beyond individual-level behavioral lifestyle change and actively take steps to mitigate the adverse impacts of socio-contextual factors.

PMID:
26496768
PMCID:
PMC4619358
DOI:
10.1186/s12939-015-0245-0
[Indexed for MEDLINE]
Free PMC Article

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