Bang Jensen Britt, Brun Edgar, Fineid Birgitte, Larssen Rolf Bjerke, Kristoffersen Anja B
Norwegian Veterinary Institute, Section for Epidemiology, 0106 Oslo, Norway.
Dis Aquat Organ. 2013 Dec 12;107(2):141-50. doi: 10.3354/dao02678.
Cardiomyopathy syndrome (CMS) has been an economically important disease in Norwegian aquaculture since the 1990s. In this study, data on monthly production characteristics and case registrations were combined in a cohort study and supplemented with a questionnaire-based case-control survey on management factors in order to identify risk factors for CMS. The cohort study included cases and controls from 2005 to 2012. From this dataset differences between all cases and controls were analyzed by a mixed effect multivariate logistic regression. From this we found that the probability of CMS increased with increasing time in the sea, infection pressure, and cohort size, and that cohorts which had previously been diagnosed with heart and skeletal muscle inflammation or which were in farms with a history of CMS in previous cohorts had double the odds of developing CMS. The model was then used to calculate the predicted value for each cohort from which additional data were obtained via the questionnaire-based survey and used as offset for calculating the probability of CMS in a semi-univariate analysis of additional risk factors. Finally, the model was used to calculate the probability of developing CMS in 100 different scenarios in which the cohorts were subject to increasingly worse conditions with regards to the risk factors from the dataset. We believe that this exercise is a good way of communicating the findings to farmers, so they can make informed decisions when trying to avoid CMS in their fish cohorts.
自20世纪90年代以来,心肌病综合征(CMS)一直是挪威水产养殖中一种具有重要经济影响的疾病。在本研究中,将月度生产特征数据和病例登记数据纳入一项队列研究,并辅以基于问卷的病例对照调查,以了解管理因素,从而确定CMS的风险因素。队列研究涵盖了2005年至2012年的病例和对照。通过混合效应多变量逻辑回归分析了该数据集中所有病例与对照之间的差异。由此我们发现,CMS的发病概率随着在海水中停留时间的增加、感染压力以及群体规模的增大而上升,并且之前被诊断患有心脏和骨骼肌炎症的群体,或者所在养殖场在之前的群体中有CMS病史的群体,发生CMS的几率是其他群体的两倍。然后,该模型被用于计算每个群体的预测值,通过基于问卷的调查获取额外数据,并将其用作偏移量,以便在对其他风险因素进行半单变量分析时计算CMS的发病概率。最后,该模型被用于计算100种不同情况下发生CMS的概率,在这些情况下,群体面临的数据集中风险因素方面越来越恶劣的条件。我们相信,这样的操作是向养殖户传达研究结果的一种好方法,以便他们在试图避免鱼群发生CMS时能够做出明智的决策。