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Diagnosis-specific sickness absence among injured working-aged pedestrians: a sequence analysis
Swedish National Road and Transport Research Institute, Traffic and road users, Traffic Safety and Traffic System. Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID iD: 0000-0002-4575-7483
Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Division of Vehicle Safety, Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden; Folksam Research, Folksam Insurance Group, Stockholm, Sweden.ORCID iD: 0000-0002-2409-1379
Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Faculty of Health and Occupational Studies, Department of Occupational Health Sciences and Psychology, University of Gävle, Sweden.
Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID iD: 0000-0001-9595-6627
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2023 (English)In: BMC Public Health, E-ISSN 1471-2458, Vol. 23, article id 367Article in journal (Refereed) Published
Abstract [en]

Background

The knowledge about the long-term consequences in terms of sickness absence (SA) among pedestrians injured in a traffic-related accident, including falls, is scarce. Therefore, the aim was to explore diagnosis-specific patterns of SA during a four-year period and their association with different sociodemographic and occupational factors among all individuals of working ages who were injured as a pedestrian.

Methods

A nationwide register-based study, including all individuals aged 20–59 and living in Sweden, who in 2014–2016 had in- or specialized outpatient healthcare after a new traffic-related accident as a pedestrian. Diagnosis-specific SA (> 14 days) was assessed weekly from one year before the accident up until three years after the accident. Sequence analysis was used to identify patterns (sequences) of SA, and cluster analysis to form clusters of individuals with similar sequences. Odds ratios (ORs) with 95% confidence intervals (CIs) for association of the different factors and cluster memberships were estimated by multinomial logistic regression.

Results

In total, 11,432 pedestrians received healthcare due to a traffic-related accident. Eight clusters of SA patterns were identified. The largest cluster was characterized by no SA, three clusters had different SA patterns due to injury diagnoses (immediate, episodic, and later). One cluster had SA both due to injury and other diagnoses. Two clusters had SA due to other diagnoses (short-term and long-term) and one cluster mainly consisted of individuals with disability pension (DP). Compared to the cluster “No SA”, all other clusters were associated with older age, no university education, having been hospitalized, and working in health and social care. The clusters “Immediate SA”, “Episodic SA” and “Both SA due to injury and other diagnoses” were also associated with higher odds of pedestrians who sustained a fracture. 

Place, publisher, year, edition, pages
Springer Nature, 2023. Vol. 23, article id 367
Keywords [en]
Sick leave, Disability pension, Pedestrians, Fall accidents, Trafc injury, Population-based
National Category
Public Health, Global Health and Social Medicine
Identifiers
URN: urn:nbn:se:vti:diva-20947DOI: 10.1186/s12889-023-15259-wISI: 000936899500001PubMedID: 36803378Scopus ID: 2-s2.0-85148396285OAI: oai:DiVA.org:vti-20947DiVA, id: diva2:1859971
Funder
AFA InsuranceAvailable from: 2024-05-23 Created: 2024-05-23 Last updated: 2025-02-20Bibliographically approved

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Kjeldgård, Linnea

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