ArticleBMC public health2025
Predictors of prolonged sickness absence after work injuries: a retrospective study using Tukey's Fence in 66,658 Hong Kong workers.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
objectivesTo identify key predictors of prolonged sickness absence among workers with occupational injuries in Hong Kong, with a focus on demographic, occupational, and injury-related factors.
methodsWe conducted a retrospective analysis of 66,658 occupational injury cases managed by a major rehabilitation coordination provider in Hong Kong, representing approximately 20% of all such cases in the region between 2003 and 2020. Prolonged absence outliers were defined as cases of sickness absence exceeding 129 days, based on Tukey’s Fence, a non-parametric method based on interquartile range. Multivariable logistic regression was used to examine associations between outlier status and the following predictors: age, gender, year of accident, physical demand, industry sector, skill level, injury type, and injured body region. All covariates were mutually adjusted in a single multivariable model.
resultsOutliers constituted 16.0% of the total sample. Older age and female gender were significant individual-level predictors. Fractures were strongly associated with extended sickness absence, whereas soft tissue injuries were linked to shorter recovery durations. Torso injuries—particularly to the back and pelvis—carried higher risks of prolonged absence, while lower limb injuries were associated with earlier return to work. Workers in physically demanding roles, especially within the construction and transportation industries, were associated with elevated risk. Notably, semiskilled workers had higher odds of prolonged absence than unskilled workers.
conclusionThis study identifies patterns that may influence prolonged sickness absence, suggesting that intersecting demographic, occupational, and injury-related factors contribute to variation in recovery outcomes. The present findings may help inform future efforts to prioritize tailored interventions for high-risk subgroups, including older employees, women, semiskilled laborers, and those engaged in physically strenuous jobs. Future research should also incorporate psychosocial variables to better capture additional drivers of delayed recovery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.