Elliott P
Department of Public Health and Policy, London School of Hygiene and Tropical Medicine.
Occup Environ Med. 1995 Dec;52(12):785-9. doi: 10.1136/oem.52.12.785.
The investigation of disease risks in small areas is complicated by many issues including data quality, the retrospective nature of the statistical testing, the problems of boundary definitions in time and space around a putative disease cluster, and the lack of generally accepted definitions of the key terminology. Routine data systems have revolutionised the initial investigation of disease risks near sources of environmental pollution, although problems of data analysis and interpretation remain. This is especially true of unmeasured socioeconomic confounding, which could generate apparent positive results near a pollution source.
小区域疾病风险的调查因诸多问题而变得复杂，这些问题包括数据质量、统计检验的回顾性本质、围绕假定疾病聚集区的时间和空间边界定义问题，以及关键术语缺乏普遍接受的定义。常规数据系统彻底改变了对环境污染源附近疾病风险的初步调查，尽管数据分析和解释问题依然存在。未测量的社会经济混杂因素尤其如此，它可能在污染源附近产生明显的阳性结果。
