Doctoral Dissertation Research in Economics: Heat Exposure and Dietary Choices

全球肥胖症流行和热量长期增加是世界面临的两个问题。 热浪可能对人类健康产生负面影响，但目前尚不清楚增加热量是通过何种机制影响人类健康的。 这项研究项目将使用经济理论和数据来调查长期热浪对肥胖的影响，通过其对饮食选择的影响。 该研究项目结合了经济学、心理学和行为学文献，通过饮食选择将不断上升的热浪和肥胖联系起来。 该项目将在很长一段时间内将三个大型数据集连接起来进行研究。 这是为数不多的将肥胖与热浪联系起来的研究之一，其主要创新来自其对长期热浪的关注，而不是短期温度升高。 这项研究还探索了热浪影响肥胖和其他健康问题的潜在机制。 该研究项目的结果将为减少气候变化对健康结果的影响的政策提供投入。拟议的研究将综合三个大型数据集：尼尔森家庭扫描消费者小组，这是2004年至2017年美国家庭零售购买超过200万个独特的通用产品代码（UPC）的全国代表性小组; NOAA每日全球历史气候学网络（GHCN-Daily）数据库和Nielsen面板中代表的Nutritionix消费包装商品（CPG）数据集。研究人员将构建一个家庭杂货购买小组，这些购买的营养成分，以及基于家庭地理位置的历史天气数据的同期热暴露测量。拟议的研究将应用广义加性模型（GAM），考虑到温度对经济行为和结果的非线性影响的先前文献中的常见发现，以估计温度与购买的营养成分之间的关系。研究人员将利用这些发现来阐明热量影响饮食选择的机制，并确定针对性缓解政策最有价值的地区或亚群。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Global obesity epidemic and secular increases in heat are two problems facing the world. Heat waves may have negative consequences on human health but it is not clear through which mechanisms increasing heat affect human health. This research project will use both economic theory and data t investigate the effects of long-term heat waves on obesity through its effects on dietary choices. The research project combines the economics and psychological and behavioral literature to link changing rising heatwaves and obesity through dietary choices. The project will link three large data sets over long periods of time for the study. This is one of the few studies that links obesity to heat waves with the major innovation coming from its focus on long-term heatwaves as opposed to short term increases in temperature. This research also explores the potential mechanisms through which heat waves affect obesity and other health problems. The results of this research project will provide inputs into policies to reduce the effects of climate change on health outcomes.The proposed research will synthesize three large datasets: the Nielsen HomeScan Consumer Panel, a nationally representative panel of U.S. household retail purchases of more than two million unique Universal Product Codes (UPCs) from 2004 to 2017; the NOAA Daily Global Historical Climatology Network (GHCN-Daily) database, and the Nutritionix Consumer Packaged Goods (CPG) dataset represented in the Nielsen panel. The researcher will construct a panel of household grocery purchases, the nutritional content of those purchases, and measures of contemporaneous heat exposure based on historical weather data from the household's geographic location. The proposed research will apply generalized additive models (GAMs), allowing for the common finding in prior literature of nonlinear effects of temperature on economic behavior and outcomes, to estimate the relationship between temperature and nutritional content of purchases. The researcher will then use these findings to elucidate the mechanisms by which heat influences dietary choices and identify regions or subpopulations for which targeted mitigating policies would be most valuable.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.