Health-related quality of life and socioeconomic status: inequalities among adults with a chronic disease

Abstract

Background: A number of studies have shown an association between health-related quality of life (HRQL) and socioeconomic status (SES). Indicators of SES usually serve as potential confounders; associations between SES and HRQL are rarely discussed in their own right. Also, few studies assess the association between HRQL and SES among those with a chronic disease. The study focuses on the question of whether people with the same state of health judge their HRQL differently according to their SES, and whether a bias could be introduced by ignoring these differences.

Methods: The analyses were based on a representative sample of the adult population in Germany (n = 11,177). HRQL was assessed by the EQ-5D-3 L, i.e. the five domains (e.g. 'moderate or severe problems' concerning mobility) and the Visual Analog Scale (VAS). SES was primarily assessed by educational level; age, sex and family status were included as potential confounders. Six chronic diseases were selected, each having a prevalence of at least 1% (e.g. diabetes mellitus). Multivariate analyses were conducted by logistic and linear regression.

Results: Among adults with a chronic disease, most 'moderate or severe problems' are reported more often in the low (compared with the high) educational group. The same social differences are seen for VAS values, also in subgroups characterized by 'moderate or severe problems'. Gender-specific analyses show that for women the associations with VAS values can just be seen in the total sample. For men, however, they are also present in subgroups defined by 'moderate or severe problems' or by the presence of a chronic disease; some of these differences exceed 10 points on the VAS scale.

Conclusions: Low SES groups seem to be faced with a double burden: first, increased levels of health impairments and, second, lower levels of valuated HRQL once health is impaired. These associations should be analysed and discussed in their own right, based on interdisciplinary co-operation. Social epidemiologists could include measures of HRQL in their studies more often, for example, and health economists could consider assessing whether recommendations based on HRQL scales might include a social bias.