Rivera Laura A, Lebenbaum Michael, Rosella Laura C
Public Health Ontario, 480 University Avenue, Toronto, Ontario, M5G 1 V2, Canada.
Dalla Lana School of Public Health, University of Toronto, 155 College Street, Health Sciences Building 6th Floor, Toronto, Ontario, M5T 3 M7, Canada.
Int J Equity Health. 2015 Oct 24;14:101. doi: 10.1186/s12939-015-0245-0.
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.
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.
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).
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.
在人群层面明确未来患糖尿病的风险可为预防策略提供依据。虽然此前的研究已根据社会经济地位(SES)对糖尿病负担进行了特征描述,但尚无研究探讨未来风险。
我们使用糖尿病人群风险工具(DPoRT)量化了SES的多个构成因素对未来糖尿病风险的影响,DPoRT是一种经过验证的风险预测算法,可生成新糖尿病病例的10年发病率。我们将DPoRT应用于2011 - 2012年加拿大社区健康调查中年龄在30 - 64岁的成年人(n = 65372),并计算了2021 - 2022年的风险。创建了一个多类别结果,将风险分为低(≤5%)、中(大于5%且小于20%)和高(≥20%),然后使用多项逻辑回归评估个体层面的SES指标以及边缘化的区域层面测量对处于中风险或高风险的影响,并按性别分层。
我们发现了按性别划分的细微社会决定因素特征,即女性对社会环境更为敏感。生活在最高教育程度低于中学的家庭中的女性风险更高[高糖尿病风险与低糖尿病风险相比的优势比(OR)为3.10,95%置信区间(CI)为2.19 - 4.40,p < 0.0001]。男性的这种关系不太明显(OR为2.17,95% CI为1.42 - 3.32,p = 0.0004)。较低的家庭收入和粮食不安全预示着女性未来患糖尿病的高风险(将第一五分位数与第五五分位数相比,OR为1.37,95% CI为1.01 - 1.86,p = 0.0418;将严重粮食不安全与粮食安全相比,OR为2.64,95% CI为1.78 - 3.92,p < 0.0001),但男性并非如此(OR为1.15,95% CI为0.84 - 1.57,p = 0.3818;OR为1.22,95% CI为0.71 - 2.10,p = 0.4815)。在区域层面,将最贫困地区与最不贫困地区相比,物质匮乏与未来风险增加显著相关(女性OR为2.39,95% CI为1.77 - 3.23;男性OR为1.61,95% CI为1.22 - 2.14)。此外,观察到生活在种族密集地区的女性有很强的保护作用(OR为0.75,95% CI为0.63 - 0.89,p = 0.0011),而男性则不那么明显(OR为0.95,95% CI为0.76 - 1.18,p = 0.6351)。
本研究描述了未来糖尿病风险的社会环境预测因素,显示出性别特异性影响。糖尿病预防必须考虑个体层面行为生活方式改变之外的因素,并积极采取措施减轻社会环境因素的不利影响。