ArticleHeliyon2024
The epidemiology of employee injuries in a monitoring sentinel unit of a coastal area in China:A nine-year retrospective analysis of clinical data.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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7 authors.
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Abstract
The epidemiology of injury among subgroups of minors, older adults, students, and athletes has previously been investigated; however, studies investigating employee-related injuries are limited. We aimed to retrospectively analyze the epidemiological characteristics and dynamic change trends of injury among employees over a nine-year period in a coastal area in China to provide a reference for formulating injury prevention and control measures among employees. All 14,168 employee injury cases registered in a hospital injury monitoring system were analyzed from January 2013 to December 2021. The male-to-female sex ratio of the employee injury cases was 3.52:1. The floating-to-registered residence population ratio was 2.05:1. March, May, July, and September-October were peak months for employee injuries. Within the day, the injury cases of employees reached five peaks at 0800, 1000, 1500, 1800, and 2000 h. The highest five causes of injury were falling, blunt injuries, motor vehicle accidents, sharps injuries, and non-motor vehicle accidents. The highest five injury types were fracture; concussion or contusion of the brain; injury from a sharp instrument, bite, or open wound; contusion or abrasion; and sprain or strain. The main locations of the injuries were roads and streets, industrial and building sites, and homes. Vulnerable body regions included the upper limbs, lower limbs, head, trunk, and multiple regions. The independent predictors of all outcomes were census register classification; age; injury causes, locations and types; vulnerable body regions; and injury severity; on multivariate logistic regression analysis (
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