Chronic effects of weather fluctuations: population susceptibility and adaptation

描述（由申请人提供）：短期暴露于较高的温度和热浪与不良的急性心血管和呼吸系统死亡率有关，但对天气的慢性影响知之甚少。我们建议在全国范围内评估与64岁以上人群长期暴露于天气参数波动相关的慢性不良健康风险，重点关注所有医疗保险参保者以及特定心血管和神经系统疾病受试者的死亡率。我们将确定这些年来健康风险如何变化，并利用这些信息预测在不同气候情景下风险将如何变化。在最近的一篇论文中，我们表明，长期暴露于夏季温度的高逐日变化（定义为夏季温度每日水平的标准差）可能会增加老年人易感人群不同亚组的死亡风险。在这个项目中，我们将与哈佛大学的大气化学模型组合作：（1）评估长期暴露于夏季（6月至8月）内温度和水蒸气压（WVP）的日常变化对所有医疗保险登记者死亡率的慢性影响;（2）检查特定条件下受试者死亡率的慢性影响，如 （3）确定改变死亡风险的城市特征（例如社会经济地位、绿色空间气候区的百分比、贫困人口、按种族划分的人口百分比、空调普及率）。具体而言，我们将确定天气相关风险随时间和空间的变化是否与城市结构、空调普及率和城市内及城市间社会经济状况的变化相关，以及不同地点对天气变化的敏感性差异是否与绿色空间和人口特征相关。重要的是，这些城市级别的特征将在邮政编码级别上定义，而不是城市级别，使我们能够捕捉到真正的当地土地使用的影响。(4)最后，我们将预测预期寿命将如何随着未来大气中夏季温度变化的增加而变化。我们调查的一个创新方面是，我们将专注于较少探索的天气参数，如温度和WVP的变化。我们将使用新的统计方法（含时变因素的生存模型和荟萃回归模型）分析数据。这项全国性分析的结果将促进对气候变化数据的统计分析，并了解温度和湿度变化对预期寿命的影响。通过产生可以外推到未来的结果，通过确定解释温度相关死亡率随时间和城市差异的协变量，我们将确定对适应和缓解战略重要的关键因素。我们的研究结果将通过识别特定的 心血管疾病可能会加剧风险，这将导致有针对性和成本效益的干预措施。

DESCRIPTION (provided by applicant): Short-term exposures to higher temperature and heat waves have been associated with adverse acute cardiovascular and respiratory mortality, but less is known about the chronic effects of weather. We propose to evaluate the chronic adverse health risks associated with long-term exposure to fluctuations in the weather parameters in persons aged over 64 years on a national scale, focusing on mortality in all Medicare enrollees, and in subjects with specific cardiovascular and neurological conditions. We will identify how the health risks changed over the years, and use this information to make predictions of how the risks will change under different climate scenarios. In a recent paper we showed that long-term exposure to high day-to-day variability in summer temperatures (defined as the standard deviation of daily levels of summer temperature) might elevate the risk of mortality in different subgroups of susceptible populations of elderly1. In this project we will partner with the Atmospheric Chemistry Modeling Group at Harvard: (1) to estimate the chronic effects associated with long-term exposure to higher day-to-day variability in temperature and in water vapor pressure (WVP) within summer months (June-August) on mortality in all Medicare enrollees; (2) to examine the chronic effects on mortality in subject with specific conditions such as cardiovascular and neurological disease; (3) to identify characteristics of city (e.g. socio-economic status, percent of green space climate zone, population in poverty, percent of population by race, air conditioning prevalence) which modify the risk of dying. Specifically, we will identify whether changes in weather related risk over time and space are associated to changes in urban structure, air conditioning prevalence, and socioeconomic status both within city and across cities, and whether differences in sensitivity to weather variability across locations are related to green space and population characteristics. Importantly, these city level characteristics will be defined on the zip-code level, not the city level, allowing us to capture te impact of true local land use. (4) Finally, we will predict how life expectancy will change with increasing variability of summertime temperatures in a future atmosphere. An innovative aspect of our investigation is that we will focus on less explored weather parameters such as variability in temperature and variability in WVP. We will analyze the data using novel statistical methods (survival models with time-varying factors and meta-regression models). The findings of this national analysis will advance statistical analyses of climate change data and knowledge of the impacts of temperature and humidity variability on life expectancy. By producing results that can be extrapolated to the future, by identifying the covariates that explain the differences in temperature related mortality over time and across cities, we will identify key factors important for adaptation and mitigation strategies. Results of our study will aid NIH by identifying specific cardiovascular disease that might exacerbate risk, which will lead to targeted and cost effective interventions.