A multifactorial study on duration of temporary disabilities in Spain

ABSTRACT

The extreme variability of temporary disability duration has a deep effect in public health. We tried to understand what factors duration of disability depends on. Through cohort study with data of temporary disabilities collected by Ibermutuamur from 2008 to 2012, we used statistical multivariate methods. The most reliable and convenient algorithm to predict duration was a categorical classification tree that distinguished between brief and long disabilities, taking into account both medical-biological and socioeconomic factors. The influence of socioeconomic factors in the disability process made numeric predictive models not accurate enough. Some of these socioeconomic factors were isolated and their influences were quantified. In particular, the one we named factor unemployment could explain a huge increase in duration for certain common diagnoses such as anxiety, low back pain, headache, and depression.

KEYWORDS:

• Classification tree
• multifactorial ANOVA
• prediction model
• temporary disability
• unemployment

Funding

This work was supported by the Junta de Extremadura (Autonomous Government of Extremadura, Spain) under the project GR15013.