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Original research
Dynamic changes in place-based measures of structural racism and preterm birth in the USA
  1. Abhery Das1,
  2. Joan A Casey2,3,
  3. Alison Gemmill4,
  4. Ralph Catalano5,
  5. Hedwig Lee6,
  6. Allison Stolte7,8,
  7. Brenda Bustos7,8,
  8. Tim A Bruckner7,8
  1. 1 Health Policy and Administration, University of Illinois Chicago, Chicago, Illinois, USA
  2. 2 Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
  3. 3 Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
  4. 4 Department of Family, Population and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
  5. 5 Public Health, University of California Berkeley, Berkeley, California, USA
  6. 6 Department of Sociology, Duke University, Durham, North Carolina, USA
  7. 7 Health, Society and Behavior, University of California Irvine, Irvine, California, USA
  8. 8 Center for Population, Inequality, and Policy, University of California Irvine, Irvine, California, USA
  1. Correspondence to Abhery Das, Health Policy and Administration, University of Illinois Chicago, Chicago, Illinois, USA; abhery{at}uic.edu

Abstract

Background Structurally racist systems, ideologies and processes generate and reinforce inequities among minoritised racial/ethnic groups. Prior cross-sectional literature finds that place-based structural racism, such as the Index of Concentration at the Extremes (ICE), correlates with higher infant morbidity and mortality. We move beyond cross-sectional approaches and examine whether a decline in place-based structural racism over time coincides with a reduced risk of preterm birth across the USA.

Methods We used as the outcome count of preterm births overall and among non-Hispanic (NH) black and NH white populations across three epochs (1998–2002, 2006–2010, 2014–2018) in 1160 US counties. For our measure of structural racism, we used ICE race/income county measures from the US Census Bureau. County-level fixed effects Poisson models include a population offset (number of live births) and adjust for epoch indicators, per cent poverty and mean maternal age within counties.

Results An SD increase in ICE (0.11) over time corresponds with a 0.6% reduced risk of preterm birth overall (incidence rate ratio (IRR): 0.994, 95% CI 0.990, 0.998), a 0.6% decrease in preterm risk among NH black births (IRR: 0.994, 95% CI 0.989, 0.999) and a 0.4% decrease among NH white births (IRR: 0.996, 95% CI 0.992, 0.999).

Conclusions Movement away from county-level concentrated NH black poverty preceded reductions in preterm risk, especially among NH black populations. Our longitudinal design strengthens inference that place-based reductions in structural racism may improve perinatal health. These improvements, however, do not appear sufficient to redress large disparities.

  • INFANT, NEWBORN
  • MATERNAL HEALTH
  • POVERTY
  • PUBLIC HEALTH
  • LONGITUDINAL STUDIES

Data availability statement

Data are available upon reasonable request. Aggregated datasets and statistical code are available from the corresponding author upon request.

https://doi.org/10.1136/jech-2023-221750

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Cross-sectional literature finds that greater place-based structural racism (Index of Concentration at the Extremes) correlates with adverse birth outcomes, especially among non-Hispanic (NH) black populations. Previous work evaluates this relation within neighbourhoods in individual cities or states after 2010.

    WHAT THIS STUDY ADDS

    • We use data from 1998 to 2018 and examine longitudinal relationships between declines in place-based structural racism and risk of preterm birth among NH black populations across more than 1,000 counties in the USA. These counties comprise ~83% of total US births.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • Our study strengthens internal validity of prior correlational work in that reduced racial and economic segregation, as well as movement away from concentrated NH black poverty, may benefit birth outcomes over time.

    Introduction

    Preterm birth (delivery of a live birth at less than 37 weeks of gestation) increases the risk of infant death, developmental delays and low educational attainment.1 In the USA, non-Hispanic (NH) black birthing persons have a 1.5-fold increased risk of delivering preterm as opposed to NH white birthing persons (ie, 13.0 vs 8.9 per 100 live births).2 Scholars contend that both macro-level (eg, structural racism) and micro-level (eg, access to healthcare) factors drive this disparity.1 3

    Structural racism is defined as the systems, social forces, institutions, ideologies and processes that interact with one another to generate and reinforce inequities among racial and ethnic groups.4 This term emphasises the most influential levels at which racism affects health disparities.5 Manifestations of structural racism include, but are not limited to, systems and policies related to employment, education, residential segregation, housing, healthcare and the criminal legal system. These macro-level factors introduce, and reproduce, an unequal distribution of health-promoting resources (eg, educational and economic opportunities) across places by race/ethnicity.

    Cross-sectional literature finds that several proxies of place-based structural racism, such as the Index of Concentration at the Extremes (ICE), correlate with higher infant morbidity and mortality, especially among NH black births.6–16 The ICE measure draws from a multitude of scholars including, but not limited to, Massey and Denton’s seminal work on residential segregation by race and class,17–23 as well as Western’s work on race-based disparities in the criminal legal system.24 ICE reveals how groups spatially concentrate by race and socioeconomic deprivation and privilege.10 25 Researchers routinely assign ICE measures to specific places such as census tracts and counties, given the recognition of distinct variation across place in the unequal distribution of resources by race.

    The above literature on place-based structural racism and birth outcomes, however, remains limited for three key reasons. First, the work is largely cross-sectional in that it measures place-based structural racism and health outcomes at one point in time.7 8 10 14 26 This circumstance makes it challenging to draw causal claims or to inform policy change. As much spatial work has demonstrated, places are not exchangeable and therefore not directly comparable ‘holding constant’ all factors except for structural racism.27 A more rigorous alternative design would involve examination of changes in place-based structural racism over time within a community. Such a longitudinal focus would establish temporal precedence between structural racism and birth outcomes, and determine whether reductions in historical structural racism have the potential to reduce subsequent racial/ethnic health disparities. This longitudinal approach, moreover, may assist with identifying places in which measures of deprivation from place-based structural racism appear to decline over time.

    Second, prior work on ICE and birth outcomes uses mostly contemporary (2010 and later) data.7 8 10 14 16 28 Given the dynamic nature of places, a historical perspective which uses >20 years of data could help identify shifts over time in structural racism. In addition, use of a larger time span covers an epoch in which the USA continued its ‘hollowing out’ of the middle class and a substantial widening between the rich and poor—a phenomenon which may adversely affect racial/ethnic disparities in preterm birth.29

    Third, previous work evaluates changes in infant morbidity and mortality as a function of ICE within neighbourhoods in individual cities or states in the USA, including Boston, Detroit, New York City and California.7 8 10–12 14 26 The dynamic changes in racial composition and socioeconomic opportunity in other metropolitan locations over time may also warrant evaluation across the USA.

    Prior work reports that the incidence of preterm among NH black births is associated with ICE race/income.7 8 10 14 Building on this work, we evaluate the role of changing ICE race/income over time on preterm among NH black births. We incorporate nationwide longitudinal, county-level ICE measures, dating back to 1998, with the potential to uncover important contributors to how changes in place-based structural racism affect changes in NH black and NH white preterm birth over a 21-year period in the USA. We hypothesise that the risk of NH black preterm birth will decline over time following place-based increases in ICE (ie, moving away from spatially concentrated NH black poverty). We base this hypothesis on the cross-sectional literature which finds greater infant morbidity and mortality in deprived neighbourhoods.7–11 13 14 16 26

    Methods

    Data

    We retrieved data on all live births in the USA, from 1998 to 2018, from natality files assembled by the National Center of Health Statistics (NCHS), Division of Vital Statistics. These files include the longest series of natality data, with individual-level variables, available to us at the time of our inquiry. We excluded birth records missing gestational age (GA; <3% of all records) and restricted the analyses to live birth records with plausible GA (ie, 22–45 weeks). The files contain month and year of birth, as well as GA in weeks. We used the NCHS combined last menstrual period (LMP) estimate (based on date of LMP or, if missing or improbable, obstetric estimate) of GA. As the only consistent measure of GA during the study period, we classified preterm birth as any live birth with GA<37 weeks, as done in previous literature.3 7–9 12 We used preterm birth as the outcome for two reasons. First, prior literature reports cross-sectional associations between ICE race/income and this outcome.7 8 10 14 Our analysis may therefore permit comparisons with earlier work. Second, unlike infant and fetal deaths, preterm deliveries are sufficiently common to permit stable estimation of ‘rates’ for less populated counties with relatively few births (described in more detail in the ‘Analysis’ section).

    We focused on NH black and NH white births given the persistently large disparity in preterm birth between these two groups.30 We classified race/ethnicity of the birth according to the race/ethnicity of the birthing person. The restricted-use US natality file has a geographical resolution at the county level. Given our focus on place-based changes in ICE at higher ecological levels, we aggregated race-specific counts of preterm birth to the county level for each year. We then (for reasons described below) aggregated race-specific preterm births for three epochs: (1) 1998–2002; (2) 2006–2010; and (3) 2014–2018. We used race-specific live births to identify the population at risk.

    We compiled data needed to construct our dynamic ICE race/income for all US counties from the 2000 US Decennial Census, as well as the 2006–2010 and 2014–2018 American Community Survey (ACS) 5-year estimates for household income by race/ethnicity.31–33 These three time periods compelled us to align the preterm birth data in the USA for these years. We could not obtain data to calculate ICE race/income for 1998, 1999, 2001 and 2002 and instead used the publicly available 2000 US Decennial Census given that it serves as a midpoint. As described by Krieger and colleagues,10 we calculated ICE for each county by subtracting the number of NH black households with an annual income equal to or below the 20th percentile from the number of NH white households with an annual income equal to or above the 80th percentile. Because our analysis spanned the entire USA, we benchmarked our percentiles to each county’s state-specific thresholds for income levels. The difference is then divided by the total number of county households, bounding our measure from −1 (indicating that all county households are NH black with annual incomes at or below the 20th percentile) to 1 (indicating that all households are NH white with annual incomes at or above the 80th percentile).10 We then created a z-score using our continuous ICE measure for better interpretation of our findings since counties average a 0.3 change in ICE over time rather than a one-unit change in our study sample. Z-scores therefore measure changes in preterm birth as a function of an SD of ICE within our specific sample.

    Analysis

    We grouped several years of birth data, by county, into three discrete epochs to ensure stable rates of preterm by county epoch. Each of these epochs (1998–2002; 2006–2010; and 2014–2018) overlaps closely with the timing of census-based estimates of ICE race/income and provides a sufficiently large denominator of race-specific births (n>100 per county) to permit stable estimates of preterm. We further restricted our analysis to urban counties as identified by the Rural-Urban Continuum Codes from the US Department of Agriculture, given that black segregation is exceedingly high in large, urban areas with concentrated poverty.20 34 This process yielded 1160 counties, which comprise an estimated 83% of total US births during the study period.

    We used a fixed effects Poisson regression to quantify the relation between changes in ICE (from epoch to epoch) and changes in the counts of preterm overall and by race/ethnicity. When using fixed effects, Poisson regression remains preferred over negative binomial models regardless of overdispersion.35 Importantly, unlike earlier work, the county serves as the ‘fixed effect’, such that the mean level of preterm birth for each county is removed to measure within county changes over time.

    The race-specific count of preterm in each county epoch serves as the dependent variable. Our models include a population offset (number of race-specific live births), which allows us to interpret the outcome as county-level rates. We then include our z-score measure of ICE by county epoch, which is the independent variable of interest. In this specification, we approximate the change in the incidence rate of preterm as a function of an SD change in ICE over time, net of time-invariant county-level differences. In addition, we include binary indicator variables for each of the three epochs to control for time-dependent factors that affect the risk of preterm or ICE across the USA. We also adjust for the per cent of the population below the federal poverty line in each county to differentiate between concentration of racial/economic segregation and poverty. Lastly, we adjust for mean maternal age within counties to account for differing maternal age composition as birthing persons of older ages show a greater likelihood of preterm birth.36

    As a sensitivity check, we then reran all analyses but categorised ICE into quintiles to permit comparability to previous studies and assess whether counties that change to higher or lower quintiles of privilege show changes in preterm birth.7 8 10 We used clustered, robust SEs to account for heteroscedasticity and correlations within clusters (eg, county).

    Results

    Table 1 provides descriptive characteristics of NH black and NH white preterm births and ICE across 1160 counties included in analyses. Of the urban counties with more than 100 live births per epoch, NH black preterm birth prevalence exceeds that of NH white preterm birth prevalence (16.42 vs 11.05 per 100 live births). These estimates, in addition to overall preterm births (11.97 per 100 live births), cohere with national trends, although slightly higher given our focus on urban counties30 37 (table 1). ICE averages 0.12 across all epoch counties with an SD of 0.11 in our study sample. ICE values for counties in our sample range from −0.33 to 0.92 (table 1).

    View this table:
    Table 1

    Preterm birth, Index of Concentration at the Extremes (ICE) race/income, sociodemographic and maternal characteristics in 1160 urban counties in the USA with more than 100 NH black and NH white live births in 1998–2002, 2006–2010 and 2014–2018.

    In figure 1, overall, NH black and NH white preterm births increase during epoch 2 (2006–2010) and then decline in epoch 3 (2014–2018). The choropleth map of ICE by quintile (figure 2) shows variation across place. The Southeastern United States, as well as some urban centres (eg, Chicago, Houston, Dallas) and regions of California, shows persistently high concentrations of NH black poverty (ie, lowest quintile of ICE). Overall, mean ICE increases slightly over time (ie, less concentrated NH black poverty), as does its variability (figure 3).

    Figure 1
    Figure 1

    Preterm births (per 100 live births) among all, non-Hispanic (NH) black and NH white mothers from 1160 urban counties in the USA with more than 100 live births (live births specific to race/ethnicity) in 1998–2002, 2006–2010 and 2014–2018.

    Figure 2
    Figure 2

    Quintiles of the Index of Concentration at the Extremes (ICE) race/income for 1160 urban counties in the USA with more than 100 live births in 2000 (A), 2006–2010 (B) and 2014–2018 (C).

    Figure 3
    Figure 3

    Mean, SD and range (blue barbell) of the Index of Concentration at the Extremes (ICE) race/income for 1160 urban counties in the USA with more than 100 live births in 1998–2002, 2006–2010 and 2014–2018.

    Fixed effects Poisson regression results (table 2) show that an SD increase in ICE (0.11) corresponds with a 0.6% decrease in risk of preterm birth overall (incidence rate ratio (IRR): 0.994, 95% CI 0.990, 0.998). We find a 0.6% decrease in preterm incidence among NH black and a 0.4% decrease in NH white preterm births as ICE increases (moving away from concentrated NH black poverty) (NH black—IRR: 0.994, 95% CI 0.989 to 0.999; NH white—IRR: 0.996, 95% CI 0.992 to 0.999).

    View this table:
    Table 2

    Fixed effects Poisson regression results predicting change in preterm births (with a population offset) as a function of change in z-score of ICE race/income (SD) across urban counties with greater than 100 live births* in the USA, between 1998–2002, 2006–2010 and 2014–2018.

    Sensitivity results (online supplemental table A1), in which we converted ICE to quintiles and used the highest quintile of ICE (ie, Q5) as the referent exposure, yielded similar inference to the original test. In online supplemental table A1, the relation between lower ICE values and greater risk of preterm concentrates in the first ICE quintile for both NH black and NH white births, as well as overall preterm births (online supplemental table A1). Counties in Q1 (more deprived) see a 2.6% increase in risk of preterm per county epoch relative to a prior Q5 ICE measure (more privileged) in that same county epoch (IRR: 1.026, 95% CI 0.995 to 1.058). The magnitude of the result is slightly larger for NH black births when compared with NH white births (NH black—IRR: 1.030, 95% CI 1.003, 1.058; NH white—IRR: 1.025, 95% CI 0.997, 1.953). Online supplemental table A2 shows that, whereas most counties undergo modest ICE changes over time, almost all transitional possibilities (ie, for combinations of Q1–Q5, Q2–Q5, Q3–Q5, etc) occur in our dataset. In online supplemental table A3, we show that our results remain robust to very preterm births (GA<28 weeks) among all, NH white and NH black mothers. We also find no relation between ICE race/income and Hispanic preterm births (online supplemental table A4).

    Supplemental material

    To estimate preterm births statistically averted by a one SD increase in ICE race/income, we applied the 0.6% reduction to the number of NH black and NH white preterm births in the study. An estimated 1 285 085 preterm births occurred during epoch 3 (2014–2018) in our 1141 test counties. Application of the ICE race/income coefficient to this value indicates an estimated 7710 preterm births statistically averted during a 5-year period if ICE race/income rose by one SD in all study counties. Despite the potentially minimal clinical relevance, the population relevance remains substantial given preterm birth’s association with infant mortality, development and educational attainment.2

    Discussion

    Extensive work supports the use of ICE race/income as an important indicator of structural racism.5–7 12 16 That literature, however, remains cross-sectional and uses populations with unknown external validity. We used data on a 21-year period in the USA to quantify the extent to which movements of ICE away from concentrated NH black poverty precede reductions in the risk of preterm among NH black births. Results suggest that an SD increase in ICE over time corresponds to a 0.6% reduction in NH black preterm birth. Although not expected, positive changes in county-level ICE also vary with a reduced risk of preterm among NH white births.

    These findings cohere with cross-sectional and individual-level studies identifying higher risks of adverse pregnancy and birth outcomes in areas with lower ICE scores.6–8 14 Mothers living in racially segregated and relatively low-income communities are often exposed to chronic and acute stressors that physically manifest in ways that harm maternal health16 and increase risk of early deliveries.25 28 Similar processes likely explain excess counts of preterm births at the county level, such that increases in ICE may indicate fewer exposures to stressors and reduced rates of adverse outcomes. Still, our findings indicate relatively small effects of ICE compared with cross-sectional studies.6 8 14 It is possible that while ICE increases suggest reductions in relative deprivation, the changing racial income structure may also indicate disruptions to neighbourhoods. For example, clustering is a component of racial segregation that identifies the geographical proximity of black neighbourhoods and may reflect political empowerment, social support and cohesion.28 Prior work suggests that higher levels of clustering are associated with higher birth weights and reduced risk of preterm birth.28 Thus, if county ICE is changing because of or alongside significant neighbourhood changes, then the protective birth effects of higher ICE scores may be muted by disruptions to political power, social support and cohesion. Our results suggest that any benefits conferred from reductions in ICE-based structural racism extend to both NH black and NH white births, joining related work in demonstrating how macro-level structural inequities may harm both oppressed and privileged groups.38 Taken together, although increases in ICE values over time precede county-level improvements in perinatal health, they do not appear sufficiently large to substantially reduce rates of preterm birth or related racial/ethnic disparities.

    The fact that racial and economic segregation changes over time means that other research examining historical processes that gauge place-based structural racism may consider including repeated measures for geographical units of interest. Future studies may also wish to look at unique employment, residential or community characteristics that initiate increases in ICE values. Higher ICE or less concentrated NH black poverty could, for example, indicate higher incomes and improved living conditions for black populations residing in a specific area or, alternatively, gentrification where NH black individuals reluctantly or unwillingly relocate.39 Whereas we do not conduct a case study for specific counties that undergo increases in ICE over time, we encourage future research in this area as it may reveal the mechanisms that specifically enhance birth outcomes in minoritised populations.

    Strengths of our approach include the use of the universe of birth data in the USA over a 21-year period for all counties with a sufficient number of births to permit estimation of race-specific risk of preterm birth. This approach supports population-based generalisability of results. In addition, county fixed effects methods focus on changes within a county over time in structural racism, which enhances internal validity relative to cross-sectional work that compares distinct counties and assumes exchangeability despite much epidemiological and sociological evidence that indicates otherwise. The within-county approach, moreover, holds relevance to place-based policy interventions aimed to improve community health in specific places over time.

    Limitations of our study include reliance on NCHS birth records, which do not distinguish between spontaneous and induced preterm births, and the lack of annual ICE measures between 1998 and 2018 for the entire USA given the availability of data from the US Census outside of the three epochs we used. Neighbourhood-level changes in racial composition and economic opportunity such as gentrification or large-scale lay-offs may also coincide with changes in preterm birth among NH black populations across the USA. Changes in ICE may also co-occur with changes in environmental quality, such as levels of air pollution or greenspace that may be related to preterm birth.26 Additionally, Krieger and colleagues report that local, neighbourhood measures of ICE avoid underestimating the extent to which segregation affects health when compared with city-level measures.11 Although our analyses focus on counties, more localised research using neighbourhood-level data appears warranted over time for the entire USA. Finally, we do not include rural counties due to low birth counts of NH black persons, so our results may not generalise to rural populations.

    Whereas our results reach conventional levels of statistical detection and show stronger associations among NH black (vs NH white) births, we cannot rule out the possibility of a chance finding. Next, our county fixed effects study design, while precluding confounding by time-invariant factors that are unique to specific counties, remains open to bias by time-varying factors that correlate with, but are not caused by, ICE race/income. For instance, gentrification (ie, in-migration of wealthier NH white persons, along with out-migration of lower income NH black persons) could alter the composition of the community and affect risk of preterm birth.40 Such mobility processes, and their relation to ICE race/income, warrant more careful scrutiny and would benefit from detailed data on across-county migration patterns, by race/ethnicity, over time from the American Community Survey (ACS).41

    Measurement of structural racism in epidemiology is relatively new.5 While many researchers continue to create new measures of racism, the field has not reached a consensus on how best to capture the complexity of this phenomenon. However, scholars agree on the need for theoretically informed measurement and modelling. Our work seeks to build on this literature by directly modelling the dynamic nature of structural racism that has been elucidated by multiple critical race theorists.42

    Whereas scholars have used ICE as a proxy for structural racism, we do not aim to imply that it encapsulates all forms and dimensions of structural racism and its analogues (eg, cultural racism, structural sexism). Our analysis may therefore underestimate the relation between racism and risk of preterm birth. However, our work suggests the need for longitudinal research to better capture the changing nature of place-based racism, as well as racism in other social systems. Given that changes in ICE modestly reduced racial/ethnic disparities in preterm birth, future work must also consider the role of other place-based factors that serve to reinforce racial inequities over time. Equitable access to health-enhancing resources within communities such as healthcare, employment and housing may further contribute towards racial health equity in birth outcomes.

    Data availability statement

    Data are available upon reasonable request. Aggregated datasets and statistical code are available from the corresponding author upon request.

    Ethics statements

    Patient consent for publication

    Ethics approval

    The University of California, Irvine Committee for the Protection of Human Subjects approved this study (Protocol No 20195444).

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    Footnotes

    • Contributors AD conducted the data collection/analysis with AS. AD and TB drafted the manuscript. TB, AS, JAC, AG, HL, RC and BB reviewed the analysis and manuscript. TB provided funding and served as the guarantor.

    • Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development (Grant R01HD103736).

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    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.