Growth and decline in SNAP generosity: Outcome and equity implications

SNAP 慷慨程度的增长和下降：结果和公平影响

• 批准号: 10780132
• 负责人: Rajan Anthony Sonik
• 金额: --
• 依托单位: ALTAMED HEALTH SERVICES CORPORATION
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-21 至 2023-09-22
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10780132
• 关键词: Address; Administrative Supplement; Affect; Age; Attention; COVID-19; Caring; Chronic; Clinical; Coronavirus; Data; Disabled Persons; Disease Management; Disparity; Dose; Economic Conditions; Economics; Emergency Care; Equity; Ethnic Origin; Event; Excision; Expenditure; Exposure to; Factor Analysis; Family; Food; Funding; Geography; Goals; Growth; Health; Health Expenditures; Healthcare; Healthcare Systems; Heterogeneity; Hospitalization; Household; Individual; Inequity; Institute of Medicine (U.S.); Intervention; Lead; Link; Longevity; Machine Learning; Massachusetts; Measures; Medicaid; Medical; Methods; Modeling; Natural experiment; Outcome; Performance; Persons; Pharmaceutical Preparations; Policies; Preventive; Public Health; Public Policy; Race; Reduce health disparities; Resources; Social Welfare; Techniques; Thinness; Time; United States National Institutes of Health; Work; care outcomes; cooking; disability; disorder prevention; disparity reduction; ethnic minority; experience; food insecurity; health care disparity; health data; health definition; health determinants; health difference; health disparity populations; improved; improved outcome; inpatient service; insight; novel; nutrition; outcome disparities; pandemic disease; programs; racial disparity; racial minority; response; social; stem; trend

Project Summary/Abstract This project will examine the effects of added Supplemental Nutrition Assistance Program (SNAP) benefits on healthcare outcomes and disparities by race/ethnicity and disability. SNAP has been found to alleviate food insecurity (albeit not fully), and is disproportionately utilized by racial/ethnic minorities and people with disabilities, who have greater sensitivities to food insecurity (given “thinner margins of health” stemming from exposures to other inequities). SNAP policy changes could therefore affect healthcare outcomes for racial/ethnic minorities and people with disabilities in different ways than for their counterparts. Further, these groups experience healthcare disparities (e.g., in disease prevention and management, unfavorable clinical events, and expenditures) that are likely affected by food insecurity: individuals exposed to food insecurity miss needed care and medications, use emergency and inpatient care, and require expenditures all at higher rates than unexposed individuals, and effects are elevated among people with chronic conditions. We will use both national Medicaid data and a novel set of linked claims, public health, and administrative SNAP data from Massachusetts to exploit a staggered set of natural experiments created by the Families First Coronavirus Response Act: (i) April 2020: ~60% of SNAP households were given variable amounts of added monthly benefits (up to over $1,000/month, with an average of $161/unit/month over the first year), (ii) May 2021: those with no/small boosts were given up to $95/month in added benefits, and (iii) since April 2021: 18 states have ended the new benefits, which will end for remaining states in March 2023. In MA, SNAP-linked data will allow us to use these changes to model dose-responses and treatment removal precisely. T-MSIS Medicaid data and state variability will broaden insights and improve the generalizability of our findings. As these SNAP changes occurred, multiple contemporaneous disruptions to healthcare, public health, social welfare policies, and economic conditions were occurring as well. To address this issue, we will leverage the significant heterogeneity in the geography and timing of the disruptions, in addition to the robust efforts that have taken place during the pandemic to provide detailed, publically available data on these disruptions. We will use confirmatory factor analysis, machine learning techniques, and an expert panel to guide our understanding of and adjustment for these factors (Aim 1). We will then use growth curve models to measure the effects of each SNAP change on healthcare outcomes (i.e., preventive use, unfavorable events, and expenditures) (Aim 2) and on healthcare disparities based on race/ethnicity and disability status (Aim 3) in MA and the US. Changes to SNAP’s funding and administration are routinely debated. This study will inform these debates by offering rigorous, actionable evidence on the potential public health impact of these policy choices.

项目概要/摘要 该项目将研究补充营养援助计划 (SNAP) 额外福利的影响 已发现 SNAP 可以缓解医疗保健结果以及种族/民族和残疾方面的差异。 不安全（尽管不完全），并且不成比例地被种族/族裔少数群体和有种族歧视的人利用 残疾人，他们对粮食不安全更加敏感（考虑到因 因此，SNAP 政策的变化可能会影响以下人群的医疗保健结果： 与他们的邻居相比，少数族裔/族裔和残疾人的方式也不同。 群体经历医疗保健差异（例如，在疾病预防和管理、不利的临床 可能受到粮食不安全影响的事件和支出）：面临粮食不安全的个人错过了 所需的护理和药物，使用紧急和住院护理，并需要更高的费用 与未接触过的个体相比，慢性病患者的影响更大。 我们将使用国家医疗补助数据和一组新颖的关联索赔、公共卫生和行政数据 来自马萨诸塞州的 SNAP 数据，用于利用 Families First 创建的一组交错自然实验 《冠状病毒应对法案》：(i) 2020 年 4 月：约 60% 的 SNAP 家庭获得了不同数量的添加物 每月福利（最高超过 1,000 美元/月，第一年平均为 161 美元/单位/月），(ii) 5 月 2021 年：那些没有/有小幅提升的人每月可获得高达 95 美元的额外福利，并且 (iii) 自 2021 年 4 月以来：18 各州已结束新福利，其余州将于 2023 年 3 月结束。在马萨诸塞州，与 SNAP 相关的福利 数据将使我们能够利用这些变化来精确模拟剂量反应和治疗去除。 医疗补助数据和州的可变性将拓宽我们的见解并提高我们研究结果的普遍性。 随着这些 SNAP 变化的发生，医疗保健、公共卫生、 为了解决这个问题，我们将利用社会福利政策和经济条件。 除了采取强有力的努力之外，中断的地理和时间也存在显着的异质性 我们在大流行期间进行了一些活动，以提供有关这些干扰的详细、公开的数据。 将使用验证性因素分析、机器学习技术和专家小组来指导我们 了解并调整这些因素（目标1）然后我们将使用增长曲线模型来衡量。 每个 SNAP 变更对医疗保健结果的影响（即预防性使用、不利事件和 支出）（目标 2）以及马萨诸塞州基于种族/民族和残疾状况的医疗保健差异（目标 3） SNAP 资金和管理的变化经常受到争论，本研究将为这些问题提供信息。 通过提供关于这些政策选择的潜在公共卫生影响的严格、可操作的证据来进行辩论。