EA4360 APEMAC Lorraine University, Paris Descartes, Nancy, France.
Curr Opin Rheumatol. 2012 Mar;24(2):187-92. doi: 10.1097/BOR.0b013e32834ff314.
Producing descriptive epidemiology data is essential to understand the burden of rheumatic diseases (prevalence) and their dynamic in the population (incidence).
No matter how simple such indicators may look, the correct collection of data and the appropriate interpretation of the results face several challenges: distinguishing indicators, facing the costs of obtaining data, using appropriate definition, identifying optimal sources of data, choosing among many survey methods, dealing with estimates precision, and standardizing results.
This study describes the underlying methodological difficulties to be overcome so as to make descriptive indicators reliable and interpretable.
生成描述性流行病学数据对于了解风湿性疾病的负担（患病率）及其在人群中的动态（发病率）至关重要。
无论这些指标看起来多么简单，正确收集数据和恰当地解释结果都面临着几个挑战：区分指标、面对获取数据的成本、使用适当的定义、确定最佳数据来源、在众多调查方法中进行选择、处理估计精度问题以及标准化结果。
本研究描述了克服这些基本方法学困难的方法，以确保描述性指标的可靠性和可解释性。
