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

复杂系统方法确定减少城市饮食和肥胖方面种族/民族差异的政策杠杆

基本信息

批准号：
10475601
负责人：
Brent Alan Langellier
金额：
$ 53.96万
依托单位：
DREXEL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-26 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10475601
关键词：
Address Affect Asian Behavioral Beverages Black Populations Black race Body Weight Changes Budgets Buffers COVID-19 pandemic Categories Charge Cities Communities Complex Diet Dietary Fiber Disadvantaged Eating Economic Conditions Eligibility Determination Enrollment Environment Environmental Policy Equipment and supply inventories Federal Government Food Food Access Food Assistance Programs Food Preferences General Population Gold Grain Harvest Health Food Household Immigrant Income Individual Inequality Latino Latino Population Lead Legal Life Low income Maps Methods Minority Modeling Neighborhoods Nutritional Obesity Occupations Oils Participant Pattern Philadelphia Policies Poverty Prevalence Price Proteins Psyche structure Reducing diet Reporting Research Series System Thinking Time Travel Unemployment United States Department of Agriculture Variant Vegetables Work base cost data standards disparity reduction economic impact ethnic minority farmers markets federal policy food insecurity high risk inequitable distribution model building models and simulation nutrition obesogenic programs racial and ethnic racial and ethnic disparities residential segregation scale up simulation social social disadvantage urban area urban setting virtual

项目摘要

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.

项目概要饮食和肥胖方面的种族/民族差异在美国城市中始终存在。首先，我们将使用。建立团体模型，系统地吸引学术、政策和社区利益相关者参与能力建设对于系统思维，开发和完善驱动饮食差异的多层次因素的“地图”，并确定这项工作的必要性是由于缺乏现有的政策杠杆。解释肥胖环境和系统性肥胖机制的概念框架结构性劣势不成比例地影响少数群体并导致先前的研究和结果的差异。现有的概念框架已经确定了对普通人群饮食的多种影响，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因素综合起来限制了黑人、拉丁裔和其他少数种族/族裔的健康食品选择。其次，我们将实施基于代理的模拟模型（ABM）来检查住宅隔离如何食品销售点分配不公平、不健康食品价格较低以及收入不平等在组合限制了少数种族/族裔的食物选择并导致饮食和肥胖差异。 ABM 桥接了我们小组和其他使用 ABM 来检查食物如何影响的研究。通过整合这些单独的建模范式，我们可以分别影响饮食。研究由于食品获取和负担能力的交叉劣势如何出现饮食差异。 ABM，虚拟城市中的个人代理做出一系列日常决定，包括去哪里购买食物、买什么购买的食物类型以及吃什么每个决定都是基于反映影响的简单规则。食品采购和饮食，包括家庭食品预算；商店之间的旅行费用；价格、库存和质量的变化；以及 12 种重要营养食品类别的价格（例如，我们使用有关家庭收入和 6 种饮料的黄金标准数据。食品支出、食品价格和采购以及饮食我们提出 ABM 的两个用途：首先，我们将评估。与 COVID-19 大流行以及限制资格的联邦政策相关的工作和收入损失的影响以及移民参加粮食援助计划——这两者都对其次，我们将让政策利益相关者参与进来，以提供信息。传播并评估如何扩大现有试点计划（例如健康食品配送、增加在农贸市场上花费的 SNAP 资金的价值，增加少数族裔社区的健康食品获取）并实施当前的政策建议（例如，美国农业部建议用“收获箱”取代 SNAP）将加剧或减少饮食差异 ABM 是基于费城的背景，但该研究。问题和调查结果与几乎所有美国城市的饮食差异高度相关。