Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands.
National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands.
Environ Health Perspect. 2018 Jan 11;126(1):017003. doi: 10.1289/EHP2252.
Results from studies on residential health effects of livestock farming are inconsistent, potentially due to simple exposure proxies used (e.g., livestock density). Accuracy of these proxies compared with measured exposure concentrations is unknown.
We aimed to assess spatial variation of endotoxin in PM (particulate matter ≤10μm) at residential level in a livestock-dense area, compare simple livestock exposure proxies to measured endotoxin concentrations, and evaluate whether land-use regression (LUR) can be used to explain spatial variation of endotoxin.
The study area (3,000km) was located in Netherlands. Ambient PM was collected at 61 residential sites representing a variety of surrounding livestock-related characteristics. Three to four 2-wk averaged samples were collected at each site. A local reference site was used for temporal variation adjustment. Samples were analyzed for PM mass by weighing and for endotoxin by using the limulus amebocyte lysate assay. Three LUR models were developed, first a model based on general livestock-related GIS predictors only, followed by models that also considered species-specific predictors and farm type-specific predictors.
Variation in concentrations measured between sites was substantial for endotoxin and more limited for PM (coefficient of variation: 43%, 8%, respectively); spatial patterns differed considerably. Simple exposure proxies were associated with endotoxin concentrations although spatial variation explained was modest (R<26%). LUR models using a combination of animal-specific livestock-related characteristics performed markedly better, with up to 64% explained spatial variation.
The considerable spatial variation of ambient endotoxin concentrations measured in a livestock-dense area can largely be explained by LUR modeling based on livestock-related characteristics. Application of endotoxin LUR models seems promising for residential exposure estimation within health studies. https://doi.org/10.1289/EHP2252.
由于使用了简单的暴露指标（例如，牲畜密度），关于畜牧业对居民健康影响的研究结果不一致。这些代理指标与测量暴露浓度的准确性尚不清楚。
我们旨在评估畜牧业密集地区居民水平 PM（≤10μm 颗粒物）中内毒素的空间变异性，比较简单的牲畜暴露指标与测量的内毒素浓度，并评估土地利用回归（LUR）是否可用于解释内毒素的空间变异性。
研究区域（3000km）位于荷兰。在 61 个住宅点采集环境 PM，这些住宅点代表了各种与牲畜相关的特征。在每个地点采集 3 到 4 个为期 2 周的平均样本。使用当地参考点进行时间变化调整。通过称重法对 PM 质量进行分析，并用鲎变形细胞溶解物试验对内毒素进行分析。开发了三种 LUR 模型，首先是仅基于一般牲畜相关 GIS 预测因子的模型，其次是还考虑了特定物种预测因子和农场类型特定预测因子的模型。
在测量的浓度之间，站点之间的变化对于内毒素来说很大，而对于 PM 来说则更为有限（变异系数：43%，8%）；空间模式差异很大。尽管解释的空间变异性较小（R<26%），但简单的暴露指标与内毒素浓度有关。使用动物特异性牲畜相关特征组合的 LUR 模型表现更好，可解释高达 64%的空间变异性。
在畜牧业密集地区测量的环境内毒素浓度存在相当大的空间变异性，这主要可以通过基于牲畜相关特征的 LUR 建模来解释。在内毒素健康研究中，应用内毒素 LUR 模型似乎有很大的前景用于居民暴露估计。https://doi.org/10.1289/EHP2252.
