Social polarization refers to the measurement of the distance between different social groups, defined on the basis of variables such as race, religion, or ethnicity. We propose two approaches to measuring social polarization in the case where the distance between groups is based on an ordinal variable, such as self-assessed health status. The first one, the 'stratification approach', amounts to assessing the degree of non-overlapping of the distributions of the ordinal variable between the different population subgroups that are distinguished. The second one, the 'antipodal approach', considers that the social polarization of an ordinal variable will be maximal if the individuals belonging to a given population subgroup are in the same health category, this category corresponding either to the lowest or to the highest health status. An empirical illustration is provided using the 2009 cross-sectional data of the European Union Statistics on Income and Living Conditions (EU-SILC). We find that Estonia, Latvia, and Ireland have the highest degree of social polarization when the ordinal variable under scrutiny refers to self-assessed health status and the (unordered) population subgroups to the citizenship of the respondent whereas Luxembourg is the country with the lowest degree of social polarization in health.