Optimized spatial information for 1990, 2000, and 2010 U.S. census microdata.

We report on the successful completion of a project to upgrade the positional accuracy of every response to the 1990, 2000, and 2010 U.S. decennial censuses. The resulting data set, called Optimized Spatial Census Information Linked Across Time (OSCILAT), resides within the restricted-access data warehouse of the Federal Statistical Research Data Center (FSRDC) system where it is available for use with approval from the U.S. Census Bureau. OSCILAT greatly improves the accuracy and completeness of spatial information for older censuses conducted prior to major quality improvements undertaken by the Bureau. Our work enables more precise spatial and longitudinal analysis of census data and supports exact tabulations of census responses for arbitrary spatial units, including tabulating responses from 1990, 2000, and 2010 within 2020 block boundaries for precise measures of change over time for small geographic areas.

Multidimensional structural racism predicts birth outcomes for Black and White Minnesotans.

OBJECTIVE: The objective of this study is to determine the linkage between multidimensional structural racism typologies and preterm birth (PTB), low birthweight (LBW), and small-for-gestational-age (SGA) birth among infants of White, US-born Black, and foreign-born Black pregnant people in Minnesota. DATA SOURCES: The measures of structural racism were based on the 2017 American Community Survey 5-year estimates and the 2017 jail incarceration data from the Vera Institute of Justice. Birth outcomes of infants born in 2018 were based on birth records from the Minnesota Department of Health. STUDY DESIGN: We conducted a latent class analysis to identify multidimensional structural racism typologies in 2017 and related these typologies to birth outcomes of pregnant people who gave birth in Minnesota in 2018 using Vermunt's 3-step approach. Racial group-specific age-adjusted risks of PTB, LBW, and SGA by structural racism typologies were estimated. DATA COLLECTION: Study data were from public sources. PRINCIPAL FINDINGS: Our analysis identified three multidimensional structural racism typologies in Minnesota in 2017. These typologies can have high structural racism in some dimensions but low in others. The interactive patterns among various dimensions cannot simply be classified as "high" (i.e., high structural racism in all dimensions), "medium," or "low." The risks of PTB, LBW, and SGA for US-born Black pregnant Minnesotans were always higher than for their White counterparts regardless of the typologies in which they lived during pregnancy. Furthermore, these excess risks among US-born Black pregnant people did not vary significantly across the typologies. We did not find clear patterns when comparing the predicted risks for infants of US- and foreign-born Black pregnant people. CONCLUSION: Multidimensional structural racism increases the risks of adverse birth outcomes for US-born Black Minnesotans. Policy interventions to dismantle structural racism and eliminate birth inequities must be multi-sectoral as changes in one or a few dimensions, but not all, will unlikely reduce birth inequities.

Where are the labor markets?: Examining the association between structural racism in labor markets and infant birth weight.

Racist policies and practices that restrict Black, as compared to white workers, from employment may drive racial inequities in birth outcomes among workers. This study examined the association between structural racism in labor markets, measured at a commuting zone where workers live and commute to work, and low-birthweight birth. We found the deleterious effect of structural racism in labor markets among US-born Southern Black pregnant people of working age, but not among African- or Caribbean-born counterparts in any US region. Our analysis highlights the intersections of structural racism, culture, migration, and history of racial oppression that vary across regions and birth outcomes of Black workers.

Association of Residence in High-Police Contact Neighborhoods With Preterm Birth Among Black and White Individuals in Minneapolis.

Importance: Police contact may have negative psychological effects on pregnant people, and psychological stress has been linked to preterm birth (ie, birth at <37 weeks' gestation). Existing knowledge of racial disparities in policing patterns and their associations with health suggest redesigning public safety policies could contribute to racial health equity. Objective: To examine the association between community-level police contact and the risk of preterm birth among White pregnant people, US-born Black pregnant people, and Black pregnant people who were born outside the US. Design, Setting, and Participants: This cross-sectional study used medical record data of 745 White individuals, 121 US-born Black individuals, and 193 Black individuals born outside the US who were Minneapolis residents and gave birth to a live singleton at a large health system between January 1 and December 31, 2016. Data were analyzed from March 2019 to October 2020. Exposures: Police contact was measured at the level of the census tract where the pregnant people lived. Police incidents per capita (ie, the number of police incidents divided by the census tract population estimate) were dichotomized into high if the value was in the fourth quartile and low for the remaining three quartiles. Main Outcomes and Measures: Preterm birth status was based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision, Clinical Modification (ICD-10-CM) code. Preterm infants were those with ICD-10-CM codes P07.2 and P07.3 documented in their charts. Results: Of 1059 pregnant people (745 [70.3%] White, 121 [11.4%] US-born Black, 193 [18.2%] Black born outside the US) in the sample, 336 White individuals (45.1%) and 62 Black individuals who were born outside the US (32.1%) gave birth between the ages of 30 and 34 years, while US-born Black individuals gave birth at younger ages, with 49 (40.5%) aged 25 years or younger. The incidence of preterm birth was 6.7% for White individuals (50 pregnant people), 14.0% for US-born Black individuals (17 pregnant people), and 5.7% for Black individuals born outside the US (11 pregnant people). In areas with high police contact vs low police contact, the odds of preterm birth were 90% higher for White individuals (odds ratio [OR], 1.9; 95% CI, 1.9-2.0), 100% higher for US-born Black individuals (OR, 2.0; 95% CI, 1.8-2.2), and 10% higher for Black individuals born outside the US (OR, 1.1; 95% CI, 1.0-1.2). Secondary geospatial analysis further revealed that the proportion of Black residents in Minneapolis census tracts was correlated with the number of police incidents reported between 2012 and 2016 (P = .001). Conclusions and Relevance: In this study, police contact was associated with preterm birth for both Black and White pregnant people. Predominantly Black neighborhoods had greater police contact than predominantly White neighborhoods, indicating that Black pregnant people were more likely to be exposed to police than White pregnant people. These findings suggest that racialized police patterns borne from a history of racism in the United States may contribute to racial disparity in preterm birth.

The intricacy of structural racism measurement: A pilot development of a latent-class multidimensional measure.

BACKGROUND: Structural racism is a complex system of inequities working in tandem to cause poor health for communities of color, especially for Black people. However, the multidimensional nature of structural racism is not captured by existing measures used by population health scholars to study health inequities. Multidimensional measures can be made using complex analytical techniques. Whether or not the multidimensional measure of structural racism provides more insight than the existing unidimensional measures is unknown. METHODS: We derived measures of Black-White residential segregation, inequities in education, employment, income, and homeownership, evaluated for 2,338 Public Use Microdata Areas (PUMAs) in the United States (US), and consolidated them into a multidimensional measure of structural racism using a latent class model. We compared the median COVID-19 vaccination rates observed across 54 New York City (NYC) PUMAs by levels (high/low) of structural racism and the multidimensional class using the Kruskal-Wallis test. This study was conducted in March 2021. FINDINGS: Our latent class model identified three structural racism classes in the US, all of which can be found in NYC. We observed intricate interactions between the five dimensions of structural racism of interest that cannot be simply classified as "high" (i.e., high on all dimensions of structural racism), "medium," or "low." Compared to Class A PUMAs with the median rate of two-dose completion of 6·9%, significantly lower rates were observed for Class B PUMAs (5·5%, p = 0·04) and Class C PUMAs (5·2%, p = 0·01). When the vaccination rates were evaluated based on each dimension of structural racism, significant differences were observed between PUMAs with high and low Black-White income inequity only (7·2% vs. 5·3%, p = 0·001). INTERPRETATION: Our analysis suggests that measuring structural racism as a multidimensional determinant of health provides additional insight into the mechanisms underlying population health inequity vis-à-vis using multiple unidimensional measures without capturing their joint effects. FUNDING: This project is funded by the Robert J. Jones Urban Research and Outreach-Engagement Center, University of Minnesota. Additional support is provided by the Minnesota Population Center, which is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (Grant P2C HD041023).

Because Muncie's Densities Are Not Manhattan's: Using Geographical Weighting in the EM Algorithm for Areal Interpolation.

Areal interpolation transforms data for a variable of interest from a set of source zones to estimate the same variable's distribution over a set of target zones. One common practice has been to guide interpolation by using ancillary control zones that are related to the variable of interest's spatial distribution. This guidance typically involves using source zone data to estimate the density of the variable of interest within each control zone. This article introduces a novel approach to density estimation, the geographically weighted expectation-maximization (GWEM) algorithm, which combines features of two previously used techniques, the expectation-maximization (EM) algorithm and geographically weighted regression. The EM algorithm provides a framework for incorporating proper constraints on data distributions, and using geographical weighting allows estimated control-zone density ratios to vary spatially. We assess the accuracy of GWEM by applying it with land-use/land-cover ancillary data to population counts from a nationwide sample of 1980 United States census tract pairs. We find that GWEM generally is more accurate in this setting than several previously studied methods. Because target-density weighting (TDW)-using 1970 tract densities to guide interpolation-outperforms GWEM in many cases, we also consider two GWEM-TDW hybrid approaches, and find them to improve estimates substantially.

Patterns of obesogenic neighborhood features and adolescent weight: a comparison of statistical approaches.

BACKGROUND: Few studies have addressed the potential influence of neighborhood characteristics on adolescent obesity risk, and findings have been inconsistent. PURPOSE: Identify patterns among neighborhood food, physical activity, street/transportation, and socioeconomic characteristics and examine their associations with adolescent weight status using three statistical approaches. METHODS: Anthropometric measures were taken on 2682 adolescents (53% female, mean age=14.5 years) from 20 Minneapolis/St. Paul MN schools in 2009-2010. Neighborhood environmental variables were measured using GIS data and by survey. Gender-stratified regressions related to BMI z-scores and obesity to (1) separate neighborhood variables; (2) composites formed using factor analysis; and (3) clusters identified using spatial latent class analysis in 2012. RESULTS: Regressions on separate neighborhood variables found a low percentage of parks/recreation, and low perceived safety were associated with higher BMI z-scores in boys and girls. Factor analysis found five factors: away-from-home food and recreation accessibility, community disadvantage, green space, retail/transit density, and supermarket accessibility. The first two factors were associated with BMI z-score in girls but not in boys. Spatial latent class analysis identified six clusters with complex combinations of both positive and negative environmental influences. In boys, the cluster with highest obesity (29.8%) included low SES, parks/recreation, and safety; high restaurant and convenience store density; and nearby access to gyms, supermarkets, and many transit stops. CONCLUSIONS: The mix of neighborhood-level barriers and facilitators of weight-related health behaviors leads to difficulties disentangling their associations with adolescent obesity; however, statistical approaches including factor and latent class analysis may provide useful means for addressing this complexity.