Methodological considerations in developing local-scale health impact assessments: balancing national, regional, and local data
Methodological considerations in developing local-scale health impact assessments: balancing national, regional, and local data
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DOI：
10.1007/s11869-009-0037-z
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发表时间：
2009-06-01
影响因子：
5.1
通讯作者：
Levy, Jonathan I.
中科院分区：
文献类型：
--
作者：
Hubbell, Bryan J.;Fann, Neal;Levy, Jonathan I.
国家规模的健康影响评估(HIA)已进行多年，并已相当系统化。最近，人们越来越有兴趣在地方范围内、在环境公共卫生跟踪的背景下以及在其他环境中利用环境影响评估方法。本文研究了估计与当地尺度上空气污染浓度变化相关的健康影响发生率的数据和分析挑战，重点关注臭氧和细颗粒物。虽然可以争辩说，地方规模的高风险评估只是国家规模评估在地理上更加离散的版本，因此面临着类似的挑战，但在实践中，国家规模评估中的许多关键投入被假定为在空间上是统一的，或者只在粗略的地理分辨率下有所不同。对于全国范围的评估，这一假设可能不会带来明显的偏差，但对于任何个人地点来说，偏差都可能是显著的。因此，地方规模的评估需要比通常使用的更多的地理分辨率的空气质量数据、浓度-反应(C-R)函数和基线发病率。然而，全面的当地数据可能无法获得，可能不完整，或者可能需要耗费时间和资源来开发，特别是对于小规模流行病学研究往往动力不足的C-R功能。在此背景下，本文考虑了如何最好地制定可信的地方规模的高风险影响指标，找出导致不同地理区域、研究设计和时间段的变异性的因素。本文还描述了随着范围从国家范围转移到地方范围，分析不确定度的主要来源发生了变化。尽管存在这些挑战，但论文的结论是，遵循关键原则和建议，设计良好的地方规模的高风险投资，既可以提供信息，也可以进行辩护。
National-scale health impact assessments (HIAs) have been conducted for many years and have become reasonably systematized. Recently, there has been growing interest in utilizing HIA methods at local scales, in the context of Environmental Public Health Tracking and in other settings. This paper investigates the data and analytical challenges to estimating the incidence of health effects associated with changes in air pollution concentrations at the local scale, focusing on ozone and fine particulate matter. Although it could be argued that the local-scale HIA is simply a more geographically discrete version of the national-scale assessment and, therefore, has similar challenges, in practice, many key inputs in national-scale assessments are assumed to be spatially uniform or vary only at coarse geographic resolution. For a nationalscale assessment, this assumption may not contribute appreciable bias, but the bias could be significant for any individual location. Thus, local-scale assessments require more geographically resolved air quality data, concentration-response (C-R) functions, and baseline incidence rates than are often used. However, comprehensive local data may not be available, may be incomplete, or may be time-intensive and resource-intensive to develop, especially for C-R functions for which small-scale epidemiological studies will often be underpowered. Given this context, this paper considers how best to develop credible local-scale HIAs, identifying factors that contribute to variability across geographic areas, study designs, and time periods. This paper also describes which key sources of analytical uncertainty change as the scope shifts from the national to the local scale. These challenges notwithstanding, the paper concludes that a well-designed local-scale HIA, following key principles and recommendations, can be both informative and defensible.