Research Supplement for Immigrant Families and Children's Health

R 01-MD 01384项目总结 在美国，每四个孩子中就有一个生活在移民家庭，每二十个孩子中至少有一个生活在 混合移民家庭虽然多项研究表明家庭的重要性 移民身份作为儿童健康的社会决定因素-很少有人分析移民的作用 政策影响儿童健康成果。以前的分析一直具有挑战性，因为有限的 提供包含移民身份必要衡量标准的全国数据集， 不严谨的分析技术，无法超越统计关联。我们 一个跨学科小组在最近一项研究中表明，它有能力克服这些问题， 医疗补助数据和创新的分析技术，以研究移民政策对婴儿的影响， 儿童和产妇保健。在我们的家长奖，我们的首要目标是扩大这种能力， 在全国范围内，通过使用医疗补助数据来评估公共政策对医疗保健服务的影响，健康， 第一代移民父母在美国出生的孩子的服务利用率和健康结果。我们 努力实现以下目标。目标1：建立一个全国性的、纵向的、相互关联的医疗补助数据集， 研究移民政策对儿童健康的影响。目标2：利用这一国家数据库， 检查国家移民政策对儿童健康的影响（例如，心理健康）和保健 使用（例如，初级保健服务、医院利用率）。目标3：审查州和地方移民政策， 确定各种政策对移民父母及其在美国出生的子女的不同影响。我们 使用医疗补助的资格要求来识别移民母亲及其在美国出生的孩子， 然后使用概率匹配（通过家庭账单识别系统和出生记录）将 家庭单位。为了进行目标2-3中的分析，我们将使用因果推理研究设计（如 差异中的差异），探讨外部公共政策变化的影响-利用 随着时间的推移和地理区域的不同，政策执行方面的“自然实验”。这包括 联邦和州的移民政策（例如，包括或不包括的移民法律、法规 来自特定服务的移民），州和地方移民行动（例如， 工作场所级别和社区级别的执行），以及联邦和州的健康政策（例如，联邦 医疗补助立法，法规或指导，具体到产前护理，儿科护理）， 影响第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 将对美国出生的儿童的健康和福祉产生重要的代际影响， 移民.明确这些具体目标对于决策者、公众和政府决策者的决策至关重要。 致力于解决健康差距的卫生领导者和医疗专业人员， 改善移民家庭儿童的健康轨迹，这是增长最快的儿童之一， 人口群体。

Project Summary of R01-MD01384 One in four children in the United States lives in an immigrant family, and at least one in twenty lives in a mixed-immigration status family. 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 in shaping child health outcomes. Previous 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 association. 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. In our parent award, 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. We are working to fulfill the following aims. Aim 1: to 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, 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: 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.