NIRG Constrained estimation for the association between health and environmental exposures

具有重大公共卫生重要性的环境-卫生联系，特别是与天气和气候影响有关的环境-卫生联系，往往是复杂的。研究人员使用先进的统计方法来估计各种形式的关联，然后得出各种健康影响的测量方法，从而解决了这种复杂性。然而，在死亡率基线较低的情况下，这些统计方法可能缺乏效力，导致对环境-健康关联进行不切实际的估计，从而导致对健康影响的估计不准确。该项目建议对研究人员使用的统计方法增加限制，包括关于环境-健康关联形态的假设信息，并获得更准确的估计。这些限制可能会导致污染对健康的风险随着水平的增加而增加，或者与平均舒适温度相比，热和冷的风险都会增加。该项目将开发统计方法，分两个步骤包括这些限制。第一步是开发一种通用算法来拟合模型，估计与约束的关联，以及不确定性评估。第二步是关注更适合环境流行病学的模型，包括非线性关联和暴露后的延迟反应。将提供开源软件代码，以允许其他研究人员轻松应用和复制开发的方法。该项目的最后一部分是在使用国际死亡率和环境暴露数据集的两个案例研究中使用新开发的方法：1)评估最低死亡率温度（即舒适温度）的全球变化，以了解适应方面的差异；2)评估死亡率与细颗粒物之间的关联形式。

Environment-health associations of critical public health importance, in particular relating to impacts of weather and climate, are often complex. This complexity is addressed by advanced statistical methods, used by researchers to estimate various shapes of associations, and then derive various measures of health impacts. However, in contexts with lower mortality baseline, these statistical methods may lack power and lead to unrealistic estimates of environment-health associations, which in turn leads to unaccurate health impacts estimates. This project proposes to add constraints to the statistical methods used by researchers, to include information about assumptions on the shape of environment-health associations and obtain more accurate estimates. Such constraints can impose that the risk of pollution on health increases with the level, or that the risk increase fo both heat and cold compared to the average comfortable temperatures. The project will develop statistical method to include these constraints in two steps. The first step is to develop a general algorithm to fit models estimating association with constraints, along with uncertainty assessment. The second step is to focus on models more specifically suited to environmental epidemiology, including nonlinear associations and delayed response after exposition. Open source software code will be provided to allow other researcher easy application and replication of the developed methods. The final part of the project is to use the newly developed methods in two case studies using an international dataset of mortality and environmental exposures: i) assessment of global variations in the minimum mortality temperature, i.e. the comfortable temperature to understand differences in adaptation, and ii) assessment of the shape of the association between mortality and fine particulate matter.