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Linking Datasets to Characterize Injury and Illness in Alaska’s Fishing Industry
Journal of Agromedicine ( IF 2.4 ) Pub Date : 2021-02-01 , DOI: 10.1080/1059924x.2020.1845893
Laura N Syron 1 , Samantha L Case 1 , Jennifer R Lee 1 , Devin L Lucas 1
Affiliation  

ABSTRACT

Limited research has characterized nonfatal injury/illness in Alaska’s hazardous fishing industry. This study aimed to determine (a) the utility of linking datasets to conduct surveillance, and (b) injury/illness patterns during 2012–2016. Data were obtained from the Alaska Trauma Registry (ATR), Fishermen’s Fund (FF), and US Coast Guard (USCG). Datasets were coded to identify patterns in injury/illness characteristics and circumstances. Probabilistic linkage methods were utilized to identify unique incidents that appeared in more than one dataset. After linking datasets, 3,014 unique injury/illness cases were identified. By dataset, 2,365 cases appeared only in FF, 486 only in USCG, 110 only in ATR, 25 in ATR and FF, 15 in ATR and USCG, 10 in USCG and FF, and 3 in all datasets. FF mainly captured claims submitted by small, independently-owned vessels in Southcentral and Southeastern Alaska. In contrast, USCG mainly captured reports from large, company-owned vessels in Western Alaska. By nature, cases were most frequently sprains, strain, and tears (27%), cuts (15%), and fractures (11%). Across fleets, injuries/illnesses most frequently resulted from contact with objects and equipment (41%), overexertion and bodily reaction (27%), and slips, trips, and falls (20%). Work processes associated with traumatic injuries were most frequently hauling gear (18%) and walking, climbing, and descending (18%). Half of all injuries were of moderate severity (53%). Linking datasets, which capture different segments of Alaska’s fishing industry, provides the most comprehensive understanding of nonfatal injury/illness to date. These results, stratified by fleet and severity, will inform prevention strategies.



中文翻译:

连接数据集以表征阿拉斯加渔业的伤害和疾病

摘要

有限的研究表征了阿拉斯加危险渔业中的非致命伤害/疾病。本研究旨在确定 (a) 连接数据集进行监测的效用,以及 (b) 2012-2016 年期间的伤害/疾病模式。数据来自阿拉斯加创伤登记处 (ATR)、渔民基金会 (FF) 和美国海岸警卫队 (USCG)。对数据集进行编码以识别伤害/疾病特征和情况的模式。概率链接方法被用来识别出现在多个数据集中的独特事件。链接数据集后,确定了 3,014 个独特的伤害/疾病病例。从数据集来看,2365个案例只出现在FF中,486个只出现在USCG中,110个只出现在ATR中,25个在ATR和FF中,15个在ATR和USCG中,10个在USCG和FF中,3个在所有数据集中。FF 主要捕获由 small 提交的索赔,阿拉斯加中南部和东南部的独立船只。相比之下,USCG 主要从阿拉斯加西部的大型公司拥有的船只上获取报告。从本质上讲,最常见的病例是扭伤、拉伤和撕裂 (27%)、割伤 (15%) 和骨折 (11%)。在整个车队中,受伤/疾病最常见的原因是接触物体和设备 (41%)、过度劳累和身体反应 (27%),以及滑倒、绊倒和跌倒 (20%)。与外伤相关的工作过程最常见的是拖拉装备 (18%) 和步行、攀爬和下降 (18%)。一半的伤害属于中等严重程度 (53%)。连接数据集捕捉阿拉斯加渔业的不同部分,提供迄今为止对非致命伤害/疾病的最全面了解。这些结果,按机队和严重程度分层,

更新日期:2021-02-01
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