Quantitative Life Sciences Program, McGill University, Montreal, QC, Canada.
Quantitative Life Sciences Program, McGill University, Montreal, QC, Canada; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada.
Environ Res. 2022 Apr 15;206:112566. doi: 10.1016/j.envres.2021.112566. Epub 2021 Dec 17.
The exacerbation of asthma and respiratory allergies has been associated with exposure to aeroallergens such as pollen. Within an urban area, tree cover, level of urbanization, atmospheric conditions, and the number of source plants can influence spatiotemporal variations in outdoor pollen concentrations.
We analyze weekly pollen measurements made between March and October 2018 over 17 sites in Toronto, Canada. The main goals are: to estimate the concentration of different types of pollen across the season; estimate the association, if any, between pollen concentration and environmental variables, and provide a spatiotemporal surface of concentration of different types of pollen across the weeks in the studied period.
We propose an extension of the land-use regression model to account for the temporal variation of pollen levels and the high number of measurements equal to zero. Inference is performed under the Bayesian framework, and uncertainty of predicted values is naturally obtained through the posterior predictive distribution.
Tree pollen was positively associated with commercial areas and tree cover, and negatively associated with grass cover. Both grass and weed pollen were positively associated with industrial areas and TC brightness and negatively associated with the northing coordinate. The total pollen was associated with a combination of these environmental factors. Predicted surfaces of pollen concentration are shown at some sampled weeks for all pollen types.
The predicted surfaces obtained here can help future epidemiological studies to find possible associations between pollen levels and some health outcome like respiratory allergies at different locations within the study area.
哮喘和呼吸道过敏的恶化与暴露于花粉等气传过敏原有关。在城市地区，树木覆盖率、城市化程度、大气条件和源植物数量会影响户外花粉浓度的时空变化。
我们分析了 2018 年 3 月至 10 月期间在加拿大多伦多的 17 个地点进行的每周花粉测量。主要目标是：估计整个季节不同类型花粉的浓度；估计花粉浓度与环境变量之间的任何关联，并提供研究期间每周不同类型花粉浓度的时空曲面。
我们提出了一种扩展的土地利用回归模型，以考虑花粉水平的时间变化和大量等于零的测量值。推断是在贝叶斯框架下进行的，预测值的不确定性通过后验预测分布自然获得。
树木花粉与商业区和树木覆盖率呈正相关，与草地覆盖率呈负相关。草花粉和杂草花粉与工业区和 TC 亮度呈正相关，与北纬坐标呈负相关。总花粉与这些环境因素的组合有关。对于所有花粉类型，在一些采样周显示了花粉浓度的预测曲面。
这里获得的预测曲面可以帮助未来的流行病学研究在研究区域内的不同地点发现花粉水平与某些健康结果（如呼吸道过敏）之间的可能关联。
