Elliott P, Martuzzi M, Shaddick G
London School of Hygiene and Tropical Medicine, UK.
Stat Methods Med Res. 1995 Jun;4(2):137-59. doi: 10.1177/096228029500400204.
Despite recent advances in the available statistical methods for geographical analysis, there are many constraints to their application in environmental epidemiology. These include problems of data availability and quality, especially the lack in most situations of environmental exposure measurements. Methods for disease 'cluster' investigation, point source exposures, small-area disease mapping and ecological correlation studies are critically reviewed, with the emphasis on practical applications and epidemiological interpretation. It is shown that, unless dealing with rare diseases, high specificity exposures and high relative risks, cluster investigation is unlikely to be fruitful, and is often complicated by the post hoc nature of such studies. However, it is recognized that in these circumstances proper assessment of the available data is often required as part of the public health response. Newly available methods, particularly in Bayesian statistics, offer an appropriate framework for geographical analysis and disease mapping. Again, it is uncertain whether they will give important clues as to aetiology, although they do give valuable description. Perhaps the most satisfactory approach is to test a priori hypotheses using a geographical database, although problems of interpretation remain.
尽管在地理分析的现有统计方法方面最近取得了进展，但这些方法在环境流行病学中的应用仍存在许多限制。这些限制包括数据可用性和质量问题，尤其是在大多数情况下缺乏环境暴露测量数据。对疾病“聚集”调查、点源暴露、小区域疾病绘图和生态关联研究的方法进行了批判性审查，重点是实际应用和流行病学解释。结果表明，除非处理罕见疾病、高特异性暴露和高相对风险，否则聚集调查不太可能取得成果，而且这类研究往往因事后性质而变得复杂。然而，人们认识到，在这些情况下，作为公共卫生应对措施的一部分，通常需要对现有数据进行适当评估。新出现的方法，特别是贝叶斯统计学中的方法，为地理分析和疾病绘图提供了一个合适的框架。同样，尽管这些方法确实提供了有价值的描述，但它们是否会为病因学提供重要线索仍不确定。也许最令人满意的方法是使用地理数据库来检验先验假设，尽管解释问题仍然存在。
