There exists limited knowledge regarding the utilisation of services and benefits associated with long-term unemployment. In this study, our objective is to identify distinct pathways into long-term unemployment by analysing patterns of healthcare and social benefit utilisation in relation to individuals’ prior labour market positions. This research aims to generate insights that facilitate the early identification and implementation of supportive measures for individuals experiencing or at risk of long-term unemployment.

Within the Finnish working-age population, individuals predominantly unemployed during the years 2020 and 2021, and for whom labour market position data for 2013–2021 was available, were identified (n = 72,485). The analysis utilised register data from Statistics Finland and the Finnish Institute for Welfare and Health. To identify distinct pathways based on labour market history, sequence analysis was employed. Variations in healthcare and social benefit utilisation across the identified clusters were examined using linear regression models, with adjustments made for potential confounders age, sex, education, living situation, migrant background, and low income.

Five distinct clusters were identified based on labour market status during years 2013–2021: unemployed (54%), students (3%), employed (23%), inactive (10%), and those with unstable labour market positions (10%). Healthcare utilisation was most prevalent among individuals who were inactive or unemployed. These clusters also had the highest proportions of individuals with mental and musculoskeletal disorders, as well as elevated rates of sickness absence and recipients of basic social assistance. In the associations between healthcare utilisation and benefit use across clusters, confounding from sociodemographic factors appeared to be minimal, except among students, who showed reduced risk of mental health diagnoses compared to the unemployed after adjusting for age and sex. At the beginning of the observation period, income disparities between clusters were pronounced. By the end, income levels among the unemployed, inactive, and students had converged, while those employed or with unstable employment history had higher income levels.