Abstract
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.