Interuniversity Institute for Biostatistics and Statistical Bioinformatics, University of Hasselt, Hasselt, Belgium.
J Antimicrob Chemother. 2011 Dec;66 Suppl 6:vi79-87. doi: 10.1093/jac/dkr460.
Resistance to antibiotics is a major public health problem and antibiotic use is being increasingly recognized as the main selective pressure driving this resistance. Yearly and quarterly data on outpatient antibiotic use were collected by the European Surveillance of Antimicrobial Consumption (ESAC) project for the period 1997-2009 from 33 and 27 European countries, respectively, and expressed in defined daily doses per 1000 inhabitants per day. Since repeated measures were taken for the countries, correlation has to be taken into account when analysing the data. This paper illustrates the application of mixed-effects models to the study of country-specific outpatient antibiotic use in Europe. Mixed models are useful in a wide variety of disciplines in the biomedical, physical and social sciences. In this application for outpatient antibiotic use, the linear mixed model is extended to a non-linear mixed model, allowing analysis of seasonal variation on top of a global trend, with country-specific effects for global mean use and amplitude, and trends over time in use and in amplitude.
抗生素耐药性是一个主要的公共卫生问题,抗生素的使用越来越被认为是导致这种耐药性的主要选择压力。欧洲抗菌药物消耗监测(ESAC)项目分别于 1997 年至 2009 年在 33 个和 27 个欧洲国家收集了年度和季度门诊抗生素使用数据,并以每 1000 居民每天的限定日剂量表示。由于各国都进行了重复测量,因此在分析数据时必须考虑相关性。本文说明了混合效应模型在欧洲国家特定门诊抗生素使用研究中的应用。混合模型在生物医学、物理和社会科学的各个领域都有广泛的应用。在这种门诊抗生素使用的应用中,线性混合模型扩展到了非线性混合模型,允许在全球趋势的基础上分析季节性变化,具有特定国家的全球平均使用和幅度效果,以及随时间推移的使用和幅度趋势。