Complex systems approaches to identify policy levers to reduce racial/ethnic disparities in diet and obesity in cities

项目总结 美国各城市在饮食和肥胖方面的种族/民族差异非常一致。首先，我们将使用 建立团队模型，系统地让学术、政策和社区利益相关者参与能力建设 对于系统思考，开发和提炼驱动饮食差异的多层次因素的“地图”，并确定 减少城市饮食差距的政策杠杆。对这项工作的需求是由于缺乏现有的 概念框架，解释肥胖环境和系统 结构性劣势对少数群体造成不成比例的影响，并导致差异。以前的研究和 现有的概念框架已经确定了对普通人群饮食的无数影响，但 更具体的概念框架可以促进对社会、环境和政策因素的理解 这些措施结合在一起，限制了黑人、拉丁裔和其他种族/少数民族的健康食品选择。 其次，我们将实施一个基于代理的模拟模型(ABM)来检查住宅隔离、 食品店分配不公、不健康食品价格较低以及收入不平等在 联合起来限制种族/族裔少数群体的食物选择，并导致饮食和肥胖差异。这个 ABM架起了我们小组和其他使用ABM检查食物如何 可获得性和食品价格分别影响饮食。通过集成这些独立的建模范例，我们可以 检查饮食差异是如何由于食物获取和可负担性方面的不利因素而出现的。在 ABM，个人--虚拟城市中的代理商每天都会做出一系列决定，比如去哪里买食物，买什么 要购买的食物类型，以及吃什么。每个决定都基于简单的规则，这些规则反映了对 食品采购和饮食，包括家庭食品预算；食品店的旅行费用；店间 价格、库存和质量的变化；以及12种营养上重要的食品类别的价格(例如， 蛋白质、全谷物)和6种饮料类别。我们使用关于家庭收入的金本位数据和 食品支出、食品价格和购买，以及饮食。我们建议ABM有两种用途：第一，我们将评估 与新冠肺炎疫情和限制资格的联邦政策相关的失业和收入损失的影响 以及移民参加食品援助计划--这两项都对 对少数群体的歧视，可能会加剧差异。第二，我们将与政策利益攸关方合作，向 传播和评估如何扩大现有试点方案(例如，提供健康食品、成倍增加 在农贸市场上花费的SNAP美元的价值，增加少数族裔社区获得健康食品的机会) 实施当前的政策建议(例如，美国农业部提出的以“收获箱”取代SNAP的建议)将 加剧或减少饮食差异。ABM植根于费城的背景下，但研究 问题和发现与美国几乎所有城市的饮食差异高度相关。

PROJECT SUMMARY Racial/ethnic disparities in diet and obesity are remarkably consistent across U.S. cities. First, we will use group model building to systematically engage academic, policy, and community stakeholders to build capacity for systems thinking, develop and refine a “map” of the multilevel factors that drive diet disparities, and identify policy levers to reduce diet disparities in cities. The need for this work is motivated by the lack of an existing conceptual framework that explicates mechanisms via which obesogenic environments and systematic structural disadvantage disproportionately affect minorities and lead to disparities. Previous research and existing conceptual frameworks have identified myriad influences on diet among the general population, but a more specific conceptual framework can advance understanding of social, environmental, and policy factors that work in combination to constrain healthy food choices of Blacks, Latinos, and other racial/ethnic minorities. Second, we will implement an agent-based simulation model (ABM) to examine how residential segregation, the inequitable distribution of food outlets, the lower price of unhealthy foods, and income inequality work in combination to constrain food choices of racial/ethnic minorities and lead to diet and obesity disparities. The ABM bridges lines of research conducted by our group and others that have used ABM to examine how food access and food prices separately affect diets. By integrating these separate modeling paradigms, we can examine how diet disparities emerge due to intersecting disadvantage in food access and affordability. In the ABM, individual-agents in a virtual city make a series of daily decisions about where to shop for food, what types of food to purchase, and what to eat. Each decision is based on simple rules that reflect influences on food purchasing and diet, including household food budgets; travel costs to food stores; between-store variation in price, inventory, and quality; and the prices of 12 nutritionally important food categories (e.g., protein, whole grains) and 6 beverage categories. We use gold standard data regarding household income and food spending, food prices and purchasing, and diet. We propose two uses for the ABM: First, we will assess the impact of job and income loss related to the COVID-19 pandemic and federal policies that restrict eligibility and enrollment of immigrants in food assistance programs – both of which have a disproportionate effect on minorities and thus are likely to exacerbate disparities. Second, we will engage policy stakeholders to inform dissemination and evaluate how scaling up existing pilot programs (e.g., healthy food delivery, multiplying the value of SNAP dollars spent at farmers’ markets, increasing healthy food access in minority neighborhoods) and implementing current policy proposals (e.g., USDA proposal to replace SNAP with “harvest boxes”) will exacerbate or reduce diet disparities. The ABM is grounded in the Philadelphia context, but the research questions and findings are highly relevant to diet disparities in essentially all U.S. cities.