Immigrant Families and Children's Health: The Intergenerational Health Impact of Federal and State Immigration Policy

移民家庭和儿童健康：联邦和州移民政策对代际健康的影响

• 批准号: 10374174
• 负责人: Jens Hainmueller
• 金额: $ 61.04万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-25 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10374174
• 关键词: Address; Adopted; Affect; Anxiety; Anxiety Disorders; Arizona; Birth Records; California; Caring; Child; Child Health; Childhood; Communities; Complex; Data; Data Set; Databases; Decision Making; Documentation; Eligibility Determination; Family; Family health status; Fright; Generations; Geographic Locations; Goals; Health; Health Policy; Health Services Accessibility; Health Status; Healthcare; Hospitalization; Household; Immigrant; Immigrant community; Immigrant family; Immigration; Incidence; Infant Health; Information Systems; Laws; Licensing; Link; Local Government; Maternal Health; Measures; Medicaid; Medical; Mental Health; Methodology; Mothers; Natural experiment; Oregon; Outcome; Outpatients; Parents; Pattern; Personal Satisfaction; Policies; Population; Population Group; Prenatal care; Preventive; Primary Health Care; Public Health; Public Policy; Quasi-experiment; Regulation; Research; Research Design; Research Personnel; Role; Services; Shapes; Side; State Government; Statutes and Laws; Stress; Surveys; System; Techniques; Testing; Time; United States; Visit; Vulnerable Populations; Woman; Workplace; authority; cost effective; federal policy; health care availability; health care service utilization; health data; health disparity; health service use; hospital utilization; improved; innovation; intergenerational; member; obstetric outcomes; prenatal; programs; response; social determinants; stress disorder; stress related disorder

ABSTRACT One in four children in the United States lives in an immigrant family (i.e., with at least one immigrant parent in the household), and at least one in twenty lives in a mixed-immigration status family (i.e., variability in immigration status). While several studies have demonstrated the importance of a family’s immigration status as a social determinant of child health – few have analyzed the role of immigration policy (including national, state and local immigration policies) in shaping child health outcomes. Historically, such analyses have been challenging because of the limited availability of nationwide data sets containing the requisite measures of immigration status, and the use of insufficiently-rigorous analytic techniques that are unable to go beyond statistical associations. Our interdisciplinary group has shown its capacity to overcome these issues in a recent study using state Medicaid data and innovative analytic techniques to examine the impact of immigration policy on infant, child, and maternal health. For this proposal, our overarching goal is to extend this capacity nationwide by using Medicaid data to assess the impact of public policy on health care access, health-service utilization, and health outcomes for US-born children of first-generation immigrant parents. Specifically, we will fulfill the following aims. Aim 1: we will build a national, longitudinal, linked Medicaid data set to examine the effect of immigration policies on children’s health. Aim 2: using this national database, we will examine the impact of national immigration policy on child health (e.g., mental health) and health care use (e.g., primary-care access, hospital utilization). Aim 3: we will examine state and local immigration policies to determine the differential impact of various policies on immigrant parents and their US-born children. We use eligibility requirements for Medicaid to identify immigrant mothers and their US-born children, and then use probabilistic matching (via household billing identification systems and birth records) to link family units. To conduct the analyses in Aims 2-3, we will use causal inference research designs (such as difference-in-difference) to explore the impact of external public policy changes – taking advantage of “natural experiments” in policy implementation over time and across geographic areas. This includes federal and state immigration policies (e.g., immigration laws, regulations that include or exclude immigrants from particular services), state and local immigration actions (e.g., workplace-level and community-level enforcement), and federal and state health policies (e.g., federal Medicaid legislation, regulation or guidance specific to prenatal care, pediatric care) that may differentially impact first- generation immigrant parents and their US-born children. We hypothesize that these policies will have important intergenerational impacts on the health and wellbeing of US-born children of immigrants. Answering these specific aims is essential to inform decision-making by policymakers, public health leaders, and medical professionals who are committed to addressing health disparities and improving health trajectories for children in immigrant families, one of the most rapidly growing child population groups.

摘要 在美国，每四个孩子中就有一个生活在移民家庭(即至少有一名移民父母 家庭)，并且至少每二十个家庭中就有一个生活在混合移民身份的家庭中(即移民的可变性 状态)。虽然一些研究已经证明了家庭的移民身份作为一种社会地位的重要性 儿童健康的决定因素--很少有人分析移民政策(包括国家、州和地方)的作用 移民政策)在塑造儿童健康结果方面的作用。从历史上看，这样的分析一直具有挑战性 因为包含必要移民措施的全国性数据集的可获得性有限 状况，以及不能超越统计学的不够严格的分析技术的使用 联想。我们的跨学科小组在最近的一项研究中展示了它克服这些问题的能力 州医疗补助数据和创新的分析技术，以检查移民政策对婴儿的影响， 儿童和产妇健康。对于这项提议，我们的总体目标是通过以下方式在全国范围内扩展这一能力 使用医疗补助数据评估公共政策对卫生保健可获得性、卫生服务利用率和 第一代移民父母在美国出生的孩子的健康结果。具体地说，我们将履行 遵循目标。目标1：我们将建立一个全国性的、纵向的、相互关联的医疗补助数据集，以检查 关于儿童健康的移民政策。目标2：利用这个国家数据库，我们将审查 关于儿童健康(例如，精神健康)和医疗保健使用(例如，初级保健服务， 医院利用率)。目标3：我们将检查州和地方的移民政策，以确定差异 各种政策对移民父母及其在美国出生的子女的影响。我们使用资格要求来 医疗补助以识别移民母亲及其在美国出生的孩子，然后使用概率匹配(通过 家庭帐单识别系统和出生记录)来连接家庭单元。在AIMS中进行分析 2-3，我们将使用因果推理研究设计(如差异中的差异)来探索影响 外部公共政策变化--在一段时间内的政策执行中利用“自然实验” 并跨越地理区域。这包括联邦和州移民政策(例如，移民法、 包括移民或将移民排除在特定服务之外的法规)、州和地方移民行动(例如， 工作场所一级和社区一级的执行)以及联邦和州卫生政策(例如，联邦医疗补助 专门针对产前护理、儿科护理的立法、法规或指导)，可能首先产生不同的影响- 一代移民父母和他们在美国出生的孩子。我们假设这些政策将具有重要的 对在美国出生的移民子女的健康和福祉的代际影响。回答这些问题 具体目标对于政策制定者、公共卫生领导人和医务人员的决策至关重要 致力于解决健康差距和改善儿童健康轨迹的专业人员 在移民家庭中，儿童人口增长最快的群体之一。