Background: Intersectionality has contributed to novel insights in epidemiology. However, participants of epidemiological studies have rarely been characterised from an intersectional perspective. We aimed to show the gained insights of an intersectionality-informed approach to describing a study population by comparing it to a conventional approach.

Methods: We used data of the German National Cohort (NAKO), which recruited 205,415 participants between 2014 and 2019. In the conventional approach, marginal proportions of educational level, cohabitation status, and country of birth were compared between the study populations of the NAKO and the German census survey (MZ) of 2014. In the intersectionality-informed approach, so-called intersectional population strata were constructed by cross-classifying educational level, cohabitation status, and country of birth. Proportions of these strata were also compared between NAKO and MZ. All analyses were stratified by sex and age group.

Results: The conventional approach showed that the proportion of people with low education was lower in the NAKO compared to the MZ in all sex and age strata. Similarly, proportions of all intersectional population strata with low education were lower in the NAKO. Concerning cohabitation, the conventional approach showed that the proportion of those living without a partner was lower in the NAKO than in the MZ for women under 60 and men. The intersectionality-informed approach revealed that the proportions of some subgroups of those living without a partner were higher in the NAKO than in the MZ. These were intersectional population strata who lived without a partner, had a high level of education and were born in Germany. The intersectionality-informed approach revealed similar within-group heterogeneity for country of birth, showing that not all proportions of foreign-born people were lower in the NAKO compared to the MZ. Proportions of foreign-born with high education who lived with a partner were higher.

Conclusions: Our results showed that heterogeneity within social categories can be revealed by applying the concept of intersectionality when comparing study participants with an external population. This way, an intersectionality-informed approach contributes to describing social complexity among study participants more precisely. Furthermore, results can be used to reduce participation barriers in a more targeted way.

Keywords: Cohort study; Intersectionality; Social inequality; Study participants.

© 2025. The Author(s).

背景： 交叉性为流行病学提供了新颖的见解。然而，流行病学研究中的参与者很少从交叉性的角度来看进行特征描述。我们的目标是通过将其与传统方法比较来展示从交叉性视角出发描述研究人群所获得的新颖洞见。

方法： 我们使用了德国国家队列研究（NAKO）的数据，该研究在2014年至2019年间招募了205,415名参与者。传统的方法比较了教育水平、同居状态和出生国的边际比例，这些数据分别来自NAKO和德国人口普查调查（MZ）中的研究人群。交叉性视角方法则通过将教育水平、同居状态和出生国进行交乘分类来构建所谓的交叉群体分层，并且也对比了这些群体在NAKO与MZ中的比例。所有分析按性别和年龄组进行了细分。

结果： 传统方法显示，在所有性别和年龄组中，与德国人口普查调查相比，NAKO中低教育程度的比例较低。同样地，交叉性群体分层中的低教育比例在NAKO中也更低。关于同居状态，传统的方法表明，未与伴侣同住的女性（60岁以下）以及男性在NAKO中的比例低于MZ。而采用交叉性的方法揭示了一些特定组别的情况，在这些组别中，具有较高教育水平且出生在德国、但未与伴侣同住的人口在NAKO中的比例高于MZ。这种交叉性视角还展示了按出生国划分的内部异质性，即并非所有非德国外来人口的比例在NAKO中都低于MZ，而是那些具有高教育水平并与其伴侣共同居住的外国人的比例较高。

结论： 我们的研究结果表明，在比较研究参与者和外部人群时，应用交叉性的概念可以揭示社会分类内部的异质性。这种方法有助于更精确地描述参与者的社会复杂性，并且可以通过更有针对性的方式降低参与障碍。

关键词： 队列研究；交叉性；社会不平等；研究参与者。