The primary aim of stratification using an intersectional sex/gender score is to form subgroups with comparable intersectional profiles with regard to different social categories. By doing so, it is possible to compare frequencies of health outcomes between different sexes/genders (e.g. the groups women and men as often studied in health reporting) with comparable intersectional profiles. If differences between men and women are shown within the subgroups of the intersectional profiles, this can be interpreted as an indication that the health differences are independent of the intersectional profiles and can thus be attributed to other aspects associated with sex/gender. 

Stratification according to an intersectional sex/gender score is particularly suitable for comparative analyses. The procedure creates several subgroups on the basis of the score, which are characterised by different intersectional profiles. If men and women differ with regard to the social categories used to calculate the score, then the statistical procedure will result in different proportions of men and women in the subgroups: for example, most men will be in the first subgroup, and most women in the last subgroup. Within the individual subgroups, women and men each have a comparable profile with regard to the intersectional expression of different social categories. This means that within each subgroup, the proportions of people who work part-time, are on parental leave or have a worker status are comparable for men and women. The prevalence of different health outcomes can be compared between women and men within a subgroup of an intersectional profile and between subgroups. If different prevalences are found between the sexes/genders, these can be interpreted against the background of the characteristic intersectional profile of the corresponding subgroup.

The method enables a descriptive, sex/gender-comparative analysis of the prevalence of health outcomes in groups of women and men who are comparable with regard to a large number of social categories, such as age, education and employment status. While in other multivariable methods, such as traditional adjusted regression analyses, a higher number of social categories can lead to overadjustment, the consideration of a large number of categories for the calculation of an intersectional sex/gender score to form subgroups is not an obstacle.

The results may reveal existing health inequalities between sexes/genders based on social categories and can be interpreted in the context of the social categories that are particularly characteristic of the respective subgroup. It should also be noted that the method is not designed to identify the subgroups with the highest prevalence of a health-related outcome or to conclude on needs for intervention.

Accordingly, interpretation on the basis of the formed subgroups can also be challenging, since the method shows intersectional relationships at the group level, which are constituted by different expressions of social categories within the subgroups.