Latent variable modeling of disability in people aged 65 or more

This paper aims at classifying, on the basis of their disability profile, the population of elderly and quantifying the number of those with a very low level of functioning in a central region of Italy. This is accomplished using a set of variables on the difficulty of accomplishing everyday tasks (Activities of Daily Living, ADL) and functions. This issue is very important for National and Local Health organizations in order to evaluate the need for care, planning services, elaborating policies and allocating resources. Latent class models are applied on data coming from the Italian National Survey on Health Conditions and Appeal to Medicare to extract the latent trait of disability and classify the elder population according to their disability profile. Model selection brings to a classification into four latent classes. Looking at posterior probabilities, classes may be interpreted as follows: elderly without disability, with difficulties in movements, with difficulties in movements and daily tasks, with very low functioning level. Estimates of the amount of population aged 65 or more falling in each class is also provided. Cross-validation shows evidence of the robustness of such classification. Item response theory models are also applied to the items considered to study how functions are lost with increasing levels of disability. In particular, the abilities of climbing stairs and stooping down are those lost first, while those of eating and getting washed are those lost last.