Abstract
Purpose: In this article we apply the age perspective to assess the quality of life (QoL) of persons with disabilities. Using a single measurement tool, we compare age profiles in the quality of life of persons with disabilities to the population without disabilities. By doing so, we examine whether the general patterns (such as U-shaped profile) are observed also among the population with disabilities, hence assessing how heterogenous this group is.
 Methods: We have constructed a multidimensional measurement model identifying overall and nine dimensions of the quality of life using structural equation modelling. The model conceptually is based on the Eurostat guidelines. All analyses are based on EU-SILC survey data, carried out in Poland in 2015.
 Results: The quality of life for both groups has inverse, right-skewed U-shape. The maximum value is achieved for the age group of 30–34 and after this threshold a constant decline is observed. The QoL scores for the population with disabilities are obviously significantly lower. Additionally, they are more heterogenous, and with greater variation between men and women. In a majority of the domains we also observe lower scores for persons with disabilities. However, people with disabilities are similarly diversified by age as persons without disabilities.
 Conclusion: Our study suggests that people with disabilities are similarly diversified by age as persons without disabilities. Therefore, disability means something different for younger and older persons and this difference is reflected in their quality of life. It means that public policy for persons with disabilities should also be diversified, avoiding ‘one-for-all’ policy.
Highlights
Nowadays, many social and economic phenomena are seen through the prism of age
We may say that age is a significant determinant of quality of life in each of the 9 dimensions and it is always significant on the p-level
These findings prove that age perspective is significant in determining quality of life
Summary
Many social and economic phenomena are seen through the prism of age. Analysis of age effects is present in scientific discourse, and social policy is developed and operationalised in many countries through the lenses of age. Age is often an eligibility criterion to many social policy measures and entitlements. Different age groups have their own characteristics and own needs – many policymakers try to address the differences in the socio-economic situation of different age groups. Even if we take a holistic view at life course with overlapping periods of education and work, still demand for social services follows the age profile. Age profiles vary by gender (Mortimer & Shanahan, 2003)
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