Measuring multidimensional structural racism as a driver of racial inequities in birth outcomes

项目摘要 拟议研究的目的是确定多层面的结构性种族主义与 美国出生的黑人、外国人、 黑人和白色孕妇该研究小组发表了一种创新的，理论驱动的方法， 将结构性种族主义作为健康的多维度决定因素进行衡量，称为多维度衡量 2022年的结构性种族主义（MMSR）与以前的结构性种族主义措施不同， 结构性种族主义领域（例如，黑人与白人的种族居住隔离， 教育、就业、收入、住房所有权、刑事司法），MMSR使用潜在类别分析-a 心理测量学家通常使用的识别复杂结构的方法（例如，人格类型）-至 确定多层面的结构性种族主义（称为“结构性种族主义类型学”）。MMSR捕获 结构性种族主义领域之间的相互联系及其综合健康影响。拟定研究 我将使用美国社区调查和维拉司法研究所的数据计算MMSR 数据库。首先，我们将制定（1）种族居住隔离，（2）教育不平等，（3） 就业不公平，（4）收入不公平，（5）住房拥有不公平，（6）刑事司法不公平。接下来， 我们将用潜在阶级分析来识别结构性种族主义类型，并将这些类型与出生联系起来 使用孕妇分娩时的住址记录。对于目标1，我们将使用 Vermunt的“三步法”将结构性种族主义类型学与早产风险联系起来， 出生体重，以及美国出生黑人、外国出生黑人和白色人所生婴儿的小于胎龄儿 2014-2021年明尼苏达州的孕妇。这一目标是扩大我们的试点项目， 仅关注2018年明尼苏达州的出生人数。我们将计算特定时期的，年龄调整的 预测的风险和95%的置信区间，并比较它们。对于目标2，我们将使用 与目标1中相同的分析方法;然而，我们将使用路易斯安那州，密歇根州， 华盛顿、加州、宾夕法尼亚和纽约市（即，一个州/城市来自所有美国地区）。我们将 计算各州的具体估计数，以检查区域异质性。此外，我们将计算多状态 估计并将其与特定州的估计进行比较，以评估其一致性。结果 拟议的项目将（1）阐明结构性种族主义与生育结果之间的联系， 是否存在跨时间和地点的效应异质性，（2）告知MMSR是否需要进一步 在将其用于研究存在种族不平等的其他健康结果之前进行改进，以及（3） 将为拟议项目计算的MMSR方法和措施提供给公众使用。

PROJECT SUMMARY The objective of the proposed study is to determine the linkages between multidimensional structural racism and preterm birth, low birthweight, and small-for-gestational-age birth among infants of US-born Black, foreign- born Black, and white pregnant people. The study team published an innovative, theory-driven approach to measuring structural racism as a multidimensional determinant of health called the Multidimensional Measure of Structural Racism (MMSR) in 2022. Unlike previous measures of structural racism, which focus on separate domains of structural racism (e.g., Black-white racial residential segregation, Black-white inequities in education, employment, income, homeownership, criminal justice), the MMSR uses Latent Class Analysis—a method commonly used by psychometricians to identify complex constructs (e.g., personality types)—to identify multidimensional structural racism (referred to as “structural racism typologies”). The MMSR captures the interconnection between structural racism domains and their combined health effects. The proposed study will calculate the MMSR using the data from the American Community Survey and the Vera Institute of Justice databases. First, we will create measures of (1) racial residential segregation, (2) education inequity, (3) employment inequity, (4) income inequity, (5) homeownership inequity, and (6) criminal justice inequity. Next, we will identify the structural racism typologies with Latent Class Analysis and link the typologies to birth records using the residential address of the pregnant people at the time of delivery. For Aim 1, we will use Vermunt's “3-step approach” to relate the structural racism typologies to the risks of preterm birth, low birthweight, and small-for-gestational-age birth for infants born to US-born Black, foreign-born Black, and white pregnant people in Minnesota during 2014-2021. This aim is an expansion of our pilot project, in which we focused only on births that occurred in 2018 in Minnesota. We will calculate period-specific, age-adjusted predicted risks, and 95% confidence interval for each group and compare them. For Aim 2, we will use the same analytical approach as in Aim 1; however, we will use birth records from Louisiana, Michigan, Washington, California, Pennsylvania, and New York City (i.e., one state/city from all US regions). We will calculate state-specific estimates to examine regional heterogeneity. Additionally, we will calculate multi-state estimates and compare them to the state-specific estimates to assess their consistency. Results of the proposed project will (1) elucidate the linkages between structural racism and birth outcomes and answer whether effect heterogeneity exists across time and place, (2) inform whether the MMSR needs further refinement before expanding its use to study other health outcomes in which racial inequities exist, and (3) make the MMSR methodology and the measure calculated for the proposed project available for public use.