Types of working-life sequences among people recently diagnosed with multiple sclerosis in Sweden: a nationwide register-based cohort study.

OBJECTIVES

To explore sequences of annual states of activity and sickness absence (SA) or disability pension (DP) (SA/DP) among working-aged people with multiple sclerosis (PwMS) as well as characteristics associated with the identified types of working-life sequences.

DESIGN

Nationwide Swedish register-based cohort study from 1 year prior to 5 years after the year of multiple sclerosis (MS) diagnosis.

SETTING

Sweden.

PARTICIPANTS

PwMS diagnosed in 2008-2011 when aged 20-55 (n=2652, 69.9% women).

PRIMARY AND SECONDARY OUTCOME MEASURES

Individual-level sequences spanning 7 years were constructed with annual states regarding activity (income from paid work, student allowances, parental leave or unemployment compensation) and/or SA/DP. Types of working-life sequences were identified among the individuals' sequences using hierarchical cluster analysis with optimal matching dissimilarity measures.

RESULTS

Six types of working-life sequences were identified. The largest cluster, Stable High Activity, represented 48.4% of the cohort. Other types were: Stable High SA/DP (14.5%); Other (4.5%); and three types with mixed activity and varying SA/DP regarding the number of days/year and timing (32.6%). Characteristics of the different identified types of sequences were subsequently investigated. All types of sequences had lower odds for university education (OR range: 0.18-0.72) compared with Stable High Activity. Increasingly higher odds of having anxiety/depression compared with Stable High Activity were observed across the types of sequences, by increasing proportions of SA/DP. Stable High SA/DP sequences were less likely than Stable High Activity to be prescribed MS drugs in the MS diagnosis year (OR 0.61; 95% CI 0.47 to 0.78). All types of sequences had higher disposable income in the final study year than the first, except for Stable High SA/DP sequences (Swedish Krona 4669, 95% CI -1892 to 11 230).

CONCLUSIONS

Diversity in working life was influenced by sociodemographic and clinical characteristics resulting in different activity and SA/DP patterns across the six identified types of working-life sequences.