The aim of applying the PROGRESS Plus framework in the context of multivariable data analysis is the comprehensive and targeted selection of social categories from an intersectionality-informed perspective. A comprehensive representation of social realities can support the identification of starting points for reducing health inequalities.

The PROGRESS Plus framework can promote a differentiated as well as appropriate selection of variables from an intersectionality-informed perspective by encouraging an intensive examination of different dimensions of socio-demographic, socio-cultural and socio-economic differences. In this context, the application of the PROGRESS Plus framework can help to uncover health inequalities.

By applying the PROGRESS Plus framework when selecting variables, a more precise formulation of research questions, as well as the interpretation of the corresponding results of the analysis from an intersectionality-informed perspective, can be promoted.

An application of the PROGRESS Plus framework is possible regardless of the selected health-related outcome measure or the multivariable analysis method used.

The PROGRESS Plus framework does not contain an exhaustive list of social categories that can be taken into account. Specific recommendations for selection as well as for a context- and time-specific adjustment of the variables used in multivariable analysis are not considered. The researchers themselves are required to define relevant social categories for their respective research question and study population.