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德国成年人 2 型糖尿病风险的社会差异的交叉分析:一项全国性基于人群的调查结果。

Intersectional analysis of social disparities in type 2 diabetes risk among adults in Germany: results from a nationwide population-based survey.

机构信息

Institute of Medical Sociology and Rehabilitation Science, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Einstein Center Population Diversity (ECPD) , Berlin, Germany.

出版信息

BMC Public Health. 2024 Feb 16;24(1):498. doi: 10.1186/s12889-024-17903-5.

Abstract

BACKGROUND

Differences in type 2 diabetes risk have been reported for several sociodemographic determinants including sex/gender or socioeconomic status. From an intersectional perspective, it is important to not only consider the role of social dimensions individually, but also their intersections. This allows for a deeper understanding of diabetes risk and preventive needs among diverse population groups.

METHODS

As an intersectionality-informed approach, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was used in a population-based sample of adults without known diabetes in Germany from the cross-sectional survey "Disease knowledge and information needs- Diabetes mellitus (2017)". Diabetes risk was assessed by the German Diabetes Risk Score (GDRS, range 0-122 points), estimating the individual risk of developing type 2 diabetes within the next 5 years based on established self-reported risk factors. Nesting individuals in 12 intersectional strata defined by combining sex/gender, educational level, and history of migration, we calculated measures to quantify the extent to which individual differences in diabetes risk were explained at strata level, and how much this was due to additive or multiplicative intersectional effects of social determinants.

RESULTS

Drawing on data of 2,253 participants, we found good discriminatory accuracy of intersectional strata (variance partition coefficient = 14.00% in the simple intersectional model). Model-predicted GDRS means varied between 29.97 (corresponding to a "low risk" of < 2%) in women with high educational level and a history of migration, and 52.73 ("still low risk" of 2-5%) in men with low educational level without a history of migration. Variance in GDRS between strata was mainly explained by additive effects of social determinants (proportional change in variance to intersectional interaction model = 77.95%) with being male and having low educational level being associated with higher GDRS. There was no evidence of multiplicative effects in individual strata.

CONCLUSIONS

Type 2 diabetes risk differed between intersectional strata and can to some extent be explained at strata level. The role of intersectional effects was minor and needs to be further investigated. Findings suggest a need for specific preventive measures targeted at large groups with increased diabetes risk, such as men and persons with low educational level.

摘要

背景

已有研究报告指出,多种社会人口决定因素(包括性别/性别认同或社会经济地位)会导致 2 型糖尿病风险的差异。从交叉视角来看,不仅要单独考虑社会维度的作用,还要考虑它们的交叉作用。这可以更深入地了解不同人群群体的糖尿病风险和预防需求。

方法

作为一种交叉视角的方法,多层次个体异质性和判别准确性分析(MAIHDA)被用于德国一项基于人群的横断面调查“疾病知识和信息需求-糖尿病(2017 年)”中的成年人样本中,这些成年人没有已知的糖尿病。使用德国糖尿病风险评分(GDRS,范围 0-122 分)评估糖尿病风险,该评分根据已建立的自我报告风险因素,估计个体在未来 5 年内患上 2 型糖尿病的风险。我们将个体嵌套在 12 个交叉层中,这些层是通过结合性别/性别认同、教育水平和移民史定义的,我们计算了衡量个体糖尿病风险在层内水平上的解释程度以及社会决定因素的加性或乘法交叉效应在多大程度上导致了这种解释程度的指标。

结果

基于 2253 名参与者的数据,我们发现交叉层的判别准确性较好(简单交叉模型中的方差划分系数为 14.00%)。模型预测的 GDRS 平均值在女性中差异较大,高教育水平和有移民史的女性 GDRS 平均值为 29.97(对应于<2%的“低风险”),而低教育水平且无移民史的男性 GDRS 平均值为 52.73(仍为“低风险”,2-5%)。层间 GDRS 的差异主要由社会决定因素的加性效应解释(交叉交互模型中比例变化方差为 77.95%),男性和低教育水平与较高的 GDRS 相关。在个体层中没有证据表明存在乘法效应。

结论

2 型糖尿病风险在交叉层之间存在差异,在一定程度上可以在层内水平上解释。交叉效应的作用较小,需要进一步研究。研究结果表明,需要针对高糖尿病风险的人群制定具体的预防措施,例如男性和受教育程度低的人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ec1/10874065/d8fe9c730288/12889_2024_17903_Fig1_HTML.jpg

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