Abstract
Objectives
While ecological studies indicate that high levels of structural racism within US states are associated with elevated infant mortality rates, studies using individual-level data are needed.
To determine whether indicators of structural racism are associated with the individual odds for infant mortality among white and black infants for in the United States.
Methods
We used data on 2,163,096 white and 590,081 black infants from the 2010 U.S. Cohort Linked Birth/Infant Death Data Files. Structural racism indicators were ratios of relative proportions of blacks to whites for these domains: electoral (registered to vote and voted; state legislature representation), employment (civilian labor force; employed; in management; with a bachelor’s degree), and justice system (sentenced to death; incarcerated). Multilevel logistic regression was used to determine whether structural racism indicators were risk factors of infant mortality.
Results
Compared to the lowest tertile ratio of relative proportions of blacks to whites with a bachelor’s degree or higher–indicative of low structural racism–black infants, but not whites, in states with moderate (OR=1.12, 95% CI=0.94, 1.32) and high tertiles (OR=1.25, 95% CI=1.03, 1.51) had higher odds of infant mortality.
Conclusions
Educational and judicial indicators of structural racism were associated with infant mortality among blacks. Decreasing structural racism could prevent black infant deaths.
Keywords: Structural racism, infant mortality, racial disparities, birth cohort
INTRODUCTION
The infant mortality rate (IMR: number of deaths before age one per 1,000 live births) and neonatal mortality rate (NMR: number of deaths within 28 days of life per 1,000 live births) influence a nation’s life expectancy [1]. In 2016 the US IMR was 5.9, significantly higher than the OECD average of 4 [2]. In the US, a striking racial disparity exists, with IMR significantly higher among blacks than among whites [3]. Although the gap in infant mortality rate between black and white infants has decreased during 2005 to 2015, the gap has since increased [4]. More specifically, the excess black infant deaths fell from 8.6 to 6.9 deaths per 1,000 between 2005 and 2015, but rose to 6.9 in 2015 [4].
Leading causes of infant mortality include congenital malformations; chromosomal abnormalities; disorders related to short gestation or low birthweight; accidents; and sudden infant death syndrome [5–8, 9]. The majority of neonatal deaths, specifically, are precipitated by respiratory distress; maternal complications of pregnancy; intrauterine hypoxia and birth asphyxia; complications of the placenta, umbilical cord, or other membranes; or neonatal hemorrhage [9]. Economic and social conditions influencing the health of mothers and newborns are associated with IMRs as well [10]. Individual, familial, home, neighborhood, and state characteristics, e.g., health policies and access to healthcare, are important determinants [11].
For example, socioeconomic characteristics and social conditions significantly affect infant health [11]. Low household income, maternal education, and employment status are risk factors for infant mortality [11]. Variability in opportunity could explain the racial disparity in infant mortality in the US [11]. However, evidence suggests that disparities in birth outcomes persist for babies born to black women compared to those of white women across all levels of income, including for college-educated women [12–15].
Structural racism has been associated with adverse health outcomes including stress, depression, and heart disease [16–18]. As a construct, it describes how social systems, institutions, policies, and practices, together with historical trends, reinforce and perpetuate inequality [18]. Education, housing, the economy, criminal justice, and political systems can foster a culture of discrimination against minorities. This system might disproportionately incarcerate minorities at higher rates through discriminatory policing practices or harsh school and community policies. Structural racism could harm mothers and their infants, especially among marginalized groups.
Structural racism has been operationalized in several ways. An index of concentration at the extremes (ICE) was developed to measure spatial social polarizations of deprived and privileged socioeconomic groups in one measure [19]; this was later expanded to include race and income disparities [20]. With multiple dimensions, ICE characterizes the extremes of disparities between groups within a particular area. ICE measures of structural racism have been used to describe zip code regions and census tracts. For larger geographical units (e.g., counties and states), structural racism can be measured by the degree of racial inequality across socioeconomic and judicial domains, e.g., prison incarceration rates; educational attainment; unemployment; occupational status; and median household income [21]. These measures have been captured through a ratio of relative proportions of black to white population values for each indicator [21]. Furthermore, social epidemiologists contend that structural racism may act on various levels within a state that are more proximal to the individual, such as city- or county-level characteristics such as racial residential segregation, or concentrated disadvantage [21].
Previous research suggests that structural racism harms the health of black but not of white Americans [21–24]. Studies have revealed an association between structural racism and infant health. Using data from ten states and the District of Columbia, researchers observed a significant relationship between indicators of structural racism and odds for babies to be born small-for-gestational-age [22]. In ecological studies examining the risk of infant mortality, structural racism was correlated with rising infant mortality rates [21]. However, most research has used only population-level data, leaving analyses vulnerable to the ecological fallacy. We address this gap by exploiting rich, individual-level mortality data to determine the relationship between indicators of structural racism and odds for infant and neonatal mortality among infants born in the US in 2010, and to determine if structural racism explains any observed racial disparity.
METHODS
Data Sources
Infant and maternal data were obtained from the 2010 U.S. Cohort Linked Birth/Infant Death Data Files, provided by the National Center for Health Statistics (NCHS). State laws require certificates to be completed for all births, and federal law mandates national collection and publication of births and other vital statistics. The National Vital Statistics System compiles these data and is the result of the cooperation between NCHS and the states. LBID contains information on socio-demographic characteristics, place of birth, and risk factors for infant health. In 2010, over 98% of LBID records were linked to their corresponding birth certificates. Foreign residents, those with missing information or with records indicating mismatch between state of birth and state residence were excluded from analyses. Infants were followed until their first birthday.
Structural racism indicators came from several sources, and were linked to vital records by state Federal Information Processing Standard code. The 2013 Sentencing Project [25] provided 2010 estimates of prison incarceration and juvenile custody rates by race and state, based on records of the US Bureau of Justice Statistics and the US Office of Juvenile Justice and Delinquency Prevention. Data on representation in state legislatures for the year 2009 was provided by the National Black Caucus of State Legislatures and the National Conference of State Legislatures. Data for the remaining indicators came from the Census Bureau’s American Community Survey 3-year estimates for 2007–2010. Ethical approval was obtained from the University of Nevada, Reno’s Institutional Review Board.
Measures
Outcome
Since different risk factors and mechanisms might play a different role in odds for neonatal and infant mortality, we looked at two outcomes [9]. Infant mortality (death within 365 days of birth) and neonatal mortality (death within 28 days of birth) were our outcomes of interest. Roughly two-thirds of infant deaths occur within the first month, with nearly all deaths related to low birthweight and premature birth [9].
State-level structural racism indicators
Our exposure of interest was structural racism within each US state, a measure constructed in previous work [21, 22]. State-level indicators included: prison incarceration and juvenile custody rates; sentencing rates and capital punishment; educational attainment (proportion of population aged 25+ with bachelor’s degree or higher); unemployment (proportion of civilian labour force not currently employed); professional occupational status (proportion employed in management, business, science, and arts occupations); and median household income. Structural racism was operationalized as the ratio of relative proportions of blacks to whites for each indicator. For the black representation, we divided the percentage of total seats occupied by black legislators in each state by percentage of that state’s population that was black, based on 2010 US Census data.
All structural racism ratios were categorized as low, moderate, or high, based on tertiles. For example, we used the distribution of each of the indicators across the US states to identify thresholds at the 33th, 66th percentiles to categorize the states into low, moderate, and high. For indicators, such as the ratio of relative proportions of blacks to whites with a bachelor’s degree or higher, proportion employed in management, the categories were reverse coded so that the greater tertile category is indicative of greater structural racism. We treated race (black, white) as a moderator and controlled for state-level characteristics (proportion black, proportion in poverty, median income, population size, and census region), and individual-level characteristics (mother’s age, marital status, education, nativity, and infant’s birth order).
Statistical Analysis
Individual- and state-level characteristics were examined. Infants with missing information were excluded from the analyses. Since mothers and infants were nested within states, we used multilevel logistic modeling to test the association between each state-level structural racism indicator and infant and neonatal mortality. For simplicity, we stratified analyses by mother’s race (white vs. black). We tested interaction terms for each indicator of structural racism and black race to determine if racial differences were statistically significant. Interaction terms that included educational attainment ratios were significant when the odds for infant and neonatal mortality were tested.
To investigate the potential effect of structural racism on the likelihood of infant and neonatal mortality, we adopted a step-up approach and conducted three sets of analyses [26]. For each indicator, we first estimated the null model to compute the 95% plausible value range, which measures variability in likelihood of infant and neonatal mortality. It allows us to compute a plausible range of proportions of births ending in infant and neonatal mortality across states. Significant variability by state indicates that state-level factors explain some variability in odds for mortality. Second, crude analyses were conducted to test the association between each of the structural racism indicators and the likelihood of infant and neonatal mortality. Finally, we ran models adjusting for state-level and individual-level socioeconomic characteristics.
RESULTS
Characteristics
In 2010, 2,163,096 white (54.0%) and 590,081(14.7%) black infants were born in the US. Mothers and infants were excluded from this study if they had missing information (n=18,837; 0.7%), moved out of state (n=72,408; 2.6%), or were foreign residents (n=963; 0.03%). Excluded babies were more likely to have mothers who were black, single, and older. When stratified by race, similar characteristics were associated with the likelihood of being excluded from the investigation, with the exception of marital status. Among black infants, those who had single mothers (OR=0.88, 95% CI=0.83, 0.93) were significantly less likely to be excluded from the analyses in comparison to those whose mothers were married. Conversely, among white infants, single mothers (OR=1.22, 95% CI=1.18, 95% CI-1.27) were significantly more likely to be excluded from the study in comparison to mothers who were married. Compared to those born in New England, those born in the South Atlantic, Mountain, and Pacific census regions were more likely to be excluded, while those from the Mid-Atlantic, East North Central, West North Central, and West South Central were less likely to be excluded. Compared to infants who were first-born, those excluded were also less likely to be second- or third-born, but more likely to be fourth-born or later.
Characteristics of the infants and their mothers can be found in Table 1. Of all 2010 births, 38.6% of mothers were single, 92.1% were US-born, and 12.4% did not complete high school. Average maternal age was 27.7 years (SD=6.0). A significantly greater proportion of black mothers were single, foreign-born, and educated below high school level, compared to white mothers.
Table 1.
Characteristics of white and black mothers who gave birth to infants and of US states and the District of Columbia in 2010.
| All mothers | White mothers | Black mothers | |||
| Characteristic | n | % | n | % | n |
| Marital Status | |||||
| Single | 1,027,194 | 38.6 | 609,127 | 29.2 | 418,067 |
| Couple | 1,634,287 | 61.4 | 1,477,742 | 70.8 | 156,545 |
| Nativity | 2,661,481 | 2,086,869 | 574,612 | ||
| Foreign born | 210,405 | 7.9 | 131,526 | 6.3 | 78,879 |
| US born | 2,451,076 | 92.1 | 1,955,343 | 93.7 | 495,733 |
| Education | |||||
| Less than High school | 329,539 | 12.4 | 207,374 | 9.9 | 122,165 |
| High school | 692,051 | 26.0 | 493,453 | 23.6 | 198,598 |
| Post high school | 1,639,891 | 61.6 | 1,386,042 | 66.4 | 253,849 |
| Birth order | |||||
| 1st born | 904,096 | 34.0 | 726,461 | 34.8 | 177,635 |
| 2nd born | 746,952 | 28.1 | 606,890 | 29.1 | 140,062 |
| 3rd born | 463,517 | 17.4 | 364,617 | 17.5 | 98,900 |
| 4th or more | 546,916 | 20.5 | 388,901 | 18.6 | 158,015 |
| Census Division | |||||
| New England | 115,893 | 4.4 | 102,734 | 4.9 | 13,159 |
| Mid Atlantic | 335,100 | 12.6 | 259,984 | 12.5 | 75,116 |
| South Atlantic | 554,455 | 20.8 | 363,943 | 17.4 | 190,512 |
| East North Central | 465,166 | 17.5 | 376,880 | 18.1 | 88,286 |
| East South Central | 205,381 | 7.7 | 149,232 | 7.2 | 56,149 |
| West North Central | 221,537 | 8.3 | 197,484 | 9.5 | 24,053 |
| West South Central | 304,156 | 11.4 | 224,309 | 10.7 | 79,847 |
| Mountain | 185,977 | 7.0 | 174,092 | 8.3 | 11,995 |
| Pacific | 273,816 | 10.3 | 238,211 | 11.4 | 35,605 |
| Mortality | |||||
| Infant (within 12 months) | 16,463 | 0.62 | 10,145 | 0.49 | 6,318 |
| Neonatal (within 28 days) | 10,526 | 0.40 | 6,528 | 0.31 | 3,998 |
| Mean | SD | Mean | SD | Mean | |
| Mother’s age, years | 27.7 | 6.0 | 28.2 | 5.9 | 25.9 |
| State-level Characteristic | Mean | SD | Min | Max | |
| Population | 5,699,069 | 6,572,937 | 563,626 | 37,253,956 | |
| Median income | $51,385.18 | $8,376.04 | $37,838.00 | $70,976.00 | |
| Proportion African-American | 12.1 | 11.1 | 0.8 | 52.2 | |
| Proportion living in poverty | 14.8 | 3.1 | 8.3 | 22.4 | |
| Registered to vote (total) ratio | 0.92 | 0.16 | 0.51 | 1.15 | |
| Registered to vote (citizens) ratio | 0.92 | 0.12 | 0.6 | 1.14 | |
| Voted (total) ratio | 0.91 | 0.18 | 0.53 | 1.21 | |
| Voted (citizens) ratio | 0.92 | 0.13 | 0.58 | 1.16 | |
| Labor force ratio | 0.99 | 0.10 | 0.70 | 1.24 | |
| Employed ratio | 0.91 | 0.11 | 0.59 | 1.25 | |
| Management ratio | 0.65 | 0.26 | 0.19 | 1.70 | |
| Professional ratio | 0.78 | 0.20 | 0.17 | 1.10 | |
| Higher education ratio | 0.65 | 0.16 | 0.28 | 1.10 | |
| Black representation ratio | 0.6 | 0.43 | 0 | 1.77 | |
| Death row ratio | 4.33 | 3.47 | 0 | 12.19 | |
| Incarcerated ratio | 6.27 | 2.34 | 2.5 | 11.80 | |
| Juvenile custody ratio | 8.41 | 4.28 | 0 | 24.89 | |
| Black disenfranchisement ratio | 7.73 | 6.28 | 0 | 24.87 | |
| Median household income ratio | 0.64 | 0.09 | 0.39 | 0.85 | |
Variability in socioeconomic characteristics was considerable across states (Table 1). The state-level median income was $51,385, with a standard deviation (SD) of $8,376, and the range of was $37,838 to $70,976. Values of structural racism indicators also varied widely across states. For example, the average ratio of relative proportions of blacks to whites with a college degree in a state was 0.65 (SD=0.26), and ranged from 0.28 to 1.10. The average relative proportion ratio of blacks to whites with a college degree ranged from 0.28 (high structural racism) in Washington, DC, to 1.10 (low structural racism) in North Dakota.
Infant and Neonatal Mortality
Among births in our sample, 16,463 (0.62%) resulted in infant death and 10,526 (0.40%) in neonatal death. Proportions of these deaths were significantly higher among blacks than among whites (Table 1), and varied across states. In 2010, the overall predicted probabilities for infant and neonatal mortality were 0.57% and 0.37%, respectively. The plausible value range for each was 0.38–0.86% and 0.25–0.54%, respectively, indicating considerable variation in cumulative incidence across states. The overall predicted variability and plausible value range for infant and neonatal mortality were significantly higher among blacks (infant mortality: 1.08; 0.82–1.43; neonatal mortality: 0.69; 0.50–0.95) than among whites (infant mortality: 0.47; 0.32–0.71; neonatal mortality: 0.30; 0.21–0.42). The proportion of infant deaths was highest in the South Atlantic states (n=1,643; 0.80%) and lowest in New England (n=503; 0.43%).
Associations between structural racism and infant and neonatal mortality
For all results, the lowest tertile of categories represents the lowest structural racism value. Among whites bom in 2010, those in states from the second (OR=1.13, 95% CI: 1.05,1.23) and third (OR=1.11, 95% CI: 1.02,1.21) tertiles of median income ratio were significantly more likely to experience infant death compared to those born in the lowest tertile states (Table 2c). Conversely, those born in states with the lowest tertile of ratio of black to white voters in the state ( higher structural racism) were significantly less likely to experience neonatal death (OR=0.87, 95% CI: 0.77, 0.96) compared to whites born in the highest tertile states (Table 3a).
Table 2c-.
The adjusted association between socioeconomic indicators of structural racism and infant mortality stratified by White-and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | |||||
|---|---|---|---|---|---|---|---|---|
| Area level Exposures | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Higher education attainment ratio | ||||||||
| Low (ref) | 1.00 | 1.00 | ||||||
| Moderate | 1.00 | (0.89,1.10) | 1.12 | (0.94,1.32) | ||||
| High | 1.03 | (0.92,1.15) | 1.25 | (1.03,1.51) | ||||
| Household income ratio | ||||||||
| Low (ref) | 1.00 | 1.00 | ||||||
| Moderate | 1.13 | (1.04,1.22) | 1.09 | (0.96,1.23) | ||||
| High | 1.11 | (1.01,1.20) | 1.08 | (0.93,1.24) | ||||
Table 3a-.
The adjusted association between political participation indicators of structural racism and infant mortality stratified by White- and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | Whites | Blacks | Whites | Blacks | Whites | Blacks | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Political Participation Indicators | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Registered to vote ratio (all) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.07 | (0.96,1.18) | 1.09 | (0.94,1.25) | ||||||||||||||||
| High | 1.02 | (0.91,1.12) | 1.08 | (0.91,1.26) | ||||||||||||||||
| High Registered to vote ratio (citizens) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.03 | (0.93,1.13) | 1.08 | (0.94,1.24) | ||||||||||||||||
| High | 0.95 | (0.84,1.05) | 1.1 | (0.93,1.31) | ||||||||||||||||
| High Voted ratio (all) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.04 | (0.95,1.14) | 1.07 | (0.92,1.23) | ||||||||||||||||
| High | 0.93 | (0.81,1.06) | 1.05 | (0.83,1.30) | ||||||||||||||||
| Voted ratio (citizen) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.01 | (0.93,1.08) | 1.06 | (0.93,1.20) | ||||||||||||||||
| High | 0.87 | (0.77,0.96) | 0.96 | (0.78,1.17) | ||||||||||||||||
| Black Representation | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.04 | (0.93,1.16) | 0.83 | (0.73,0.94) | ||||||||||||||||
| High | 0.97 | (0.85,1.10) | 0.99 | (0.83,1.18) | ||||||||||||||||
Among black infants born in 2010, those in the states with the second (OR=1.12, 95%CI:0.94,1.32) and third (OR=1.25, 95%CI: 1.03,1.52) lowest tertiles of ratio of proportion of blacks with a college degree, which is indicative of higher structural racism, were more likely to experience infant mortality in comparison to those born in the highest tertile states (Table 2c). Similarly, black infants in the states from the second (OR=1.24, 95% CI:0.98, 1.57) and third (OR=1.35, 95% CI: 1.04, 1.76) tertiles of ratio of proportion of blacks with a college degree were at greater odds of neonatal mortality (Table 3c).
Table 3c-.
The adjusted association between socioeconomic indicators of structural racism and infant mortality stratified by White-and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | |||||
|---|---|---|---|---|---|---|---|---|
| Socioeconomic indicators | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Higher education attainment ratio | ||||||||
| Low (ref) | 1.00 | 1.00 | ||||||
| Moderate | 0.99 | (0.86,1.14) | 1.24 | (0.97,1.56) | ||||
| High | 1.03 | (0.88,1.20) | 1.35 | (1.03,1.76) | ||||
| Household income ratio | ||||||||
| Low (ref) | 1.00 | 1.00 | ||||||
| Moderate | 1.08 | (0.96,1.22) | 1.14 | (0.95,1.35) | ||||
| High | 1.05 | (0.91,1.20) | 1.13 | (0.93,1.38) | ||||
Higher state-level relative proportion ratio of blacks to whites sentenced to death (higher structural racism) was associated with elevated risk for infant and neonatal mortality among both whites and blacks (tables 2d, 3d). However, the interaction term was not significant, revealing no significant heterogeneity by race in the relationship between the capital punishment indicator of structural racism and infant/neonatal mortality.
Table 2d-.
The adjusted association between judicial indicators of structural racism and infant mortality stratified by White-and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | Whites | Blacks | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | |
| Capital punishment ratio | ||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||
| Moderate | 1.09 | (1.02,1.16) | 1.21 | (1.11,1.33) | ||||||||
| High | 1.09 | (1.00,1.18) | 1.15 | (1.01,1.31) | ||||||||
| Incarceration ratio | ||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||
| Moderate | 1.02 | (0.91,1.13) | 1.06 | (0.92,1.22) | ||||||||
| High | 1.06 | (0.94,1.19) | 0.96 | (0.80,1.14) | ||||||||
| Disenfranchisement | ||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||
| Moderate | 0.99 | (0.91,1.97) | 1.03 | (0.90,1.18) | ||||||||
| High | 0.93 | (0.85,1.01) | 1.01 | (0.88,1.17) | ||||||||
Table 3d-.
The adjusted association between judicial indicators of structural racism and infant mortality stratified by White-and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | Whites | Blacks | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Judicial indicators | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Capital punishment ratio | ||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||
| Moderate | 1.13 | (1.04,1.22) | 1.24 | (1.08,1.43) | ||||||||
| High | 1.17 | (1.06,1.30) | 1.20 | (0.99,1.46) | ||||||||
| Incarceration ratio | ||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||
| Moderate | 1.00 | (0.86,1.16) | 0.90 | (0.73,1.12 | ||||||||
| High | 1.04 | (0.88,1.23) | 0.90 | (0.70,1.14) | ||||||||
| Disenfranchisement | ||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||
| Moderate | 0.99 | (0.88,1.10) | 1.05 | (0.87,1.26) | ||||||||
| High | 0.88 | (0.79,0.98) | 1.01 | (0.84,1.22) | ||||||||
DISCUSSION
Our findings suggest that state-level structural racism related to education and incarceration are risk factors for infant and neonatal mortality. When education was used as an indicator, adverse effects were found among blacks but not among whites after controlling for individual-level characteristics such as mother’s age and education, and state-level factors such as median income and percent in poverty. When the capital punishment indicator was used, an adverse association with infant and neonatal mortality for black and white babies was found.
These results corroborate a recent ecological study that found decreased racial inequity in educational attainment was associated with an almost 10%-reduction in the black infant mortality rate measured at the population level[21]. Our findings also echo those from an observational study suggesting that racial disparities in education and income were related to increased odds for babies being born small-for-gestational-age [22]. In addition, we observed that Blacks born in states with higher relative proportions of blacks to whites sentenced to death (elevated structural racism), were at greater risk for infant mortality compared to blacks born in states with low relative proportions of blacks to whites sentenced to death. This current study improves upon previous work by employing individual-level mortality data to determine the relationship between structural racism and odds for infant and neonatal mortality. It is innovative in that it is, to our knowledge, the only study to examine how state-level structural racism across a variety of domains is associated with these adverse birth outcomes.
Racial disparities in maternal education were found to be a significant risk factor for infant and neonatal mortality among black babies. Although college completion rates in the US have risen, achievement gaps remain. As of 2015, nearly half of white women aged 25–35 had a college degree, while just 35% of their black counterparts had that reached same level [27]. These achievement gaps stem from policies rooted in anti-literacy laws from the days of slavery and to the once legally-sanctioned segregated and unequal schools. Additionally, social norms and a lack of federal intervention in educational funding have kept higher education disproportionately attainable for whites [28]. In many parts of the US, the vestiges of discriminatory laws and entrenched attitudes have kept many blacks from pursuing a college degree even today [28]. For example, many primary schools still remain racially segregated as a result of residential segregation [29].
Affirmative action programs have been implemented to advance equality of educational opportunity for individuals from groups that have experienced systematic historical discrimination [30]. The current US federal administration has abandoned its predecessor’s urging of universities to consider race as a factor in diversifying campuses. As a result, these practices may no longer be in place to decrease racial disparities in college educational attainment, with potentially harmful health consequences for maternal and infant health.
Limiting access to education might have serious health consequences not only for women themselves, but for their children as well. According to the WHO, education is the first step in ensuring that women realize their full potential; it is critical in empowering women with the knowledge, skills, and confidence necessary to fully participate in their health and well-being [31]. Education, over and above income and occupation, might have a more beneficial impact on the health of women and their children. Addressing the parallel racial inequity in women’s post-secondary educational attainment could result in a shrinking of the race-based gap in infant mortality risk.
Several mechanisms through which structural racism might influence infant mortality risk have been proposed. Structural racism could limit blacks’ access to resources necessary for optimal health. Resources include avenues to employment, healthcare and health services, and affordable and safe housing—all determinants of health that could impact birth outcomes [18]. Second, structural racism might directly and indirectly (through racial prejudice and discrimination) increase stress and anxiety [32]. One study examined structural racism in the form of racial segregation and its associated with self-reported stress among a cohort of pregnant American women. Researchers observed that some forms of segregation are associated with reported stress [32]. These adverse psychological mediators could potentially lead to greater risk for infant mortality.
We also found evidence that states with high structural racism in terms of death row ratio was a significant risk factor for infant and neonatal mortality among both races in our sample. Blacks are disproportionately represented on death row and among those executed. Blacks comprise 13% of the US population, but 42% of death row inmates and 35% of those put to death [33]. This discrepancy could be a marker of discrimination in policing or in sentencing, and warrants serious criminal justice reform. This form of structural racism can have detrimental effect on the psychological well-being of the public, especially among black mothers, detrimentally affect their health and their infants.
This study’s findings must be interpreted with acknowledgment of several limitations. First, there could be residual confounding, since we did not have mother’s income information. Household income might act as a confounder of the relationship between structural racism and infant mortality. Since the data for this investigation were not initially gathered for research purposes, they could be subject to some misclassification. Nevertheless, the validity of the mortality data is very high. We acknowledge that there could be differences in mothers exposed to structural racism and those not exposed that might explain the relationship between structural racism and infant mortality. Finally, infants and mothers with missing information and those whose state at birth and current residence differed were excluded from the analyses, exclusions that might not be random, possibly leading to selection bias. Regardless of these limitations, the implications of this investigation are meaningful, and this study has many strengths. This investigation is one of the first to examine structural racism in several domains, and related to infant and neonatal mortality. It is also among the first to use nationally representative, individual-level outcome data.
In conclusion, this novel, multilevel study found that state-level structural racism in education and incarceration are significantly associated with increased odds of neonatal and infant mortality for blacks compares to whites after controlling for socioeconomic factors. While individual factors contribute to disparities in these outcomes, this study highlights how legal and contextual factors create enduring structural barriers to optimal health for blacks in the US. Our findings suggest that, in order to address racial disparities in health within the United States, we need to directly address social inequalities that are a product of structural racism, such as unequal access to higher education. Future research should investigate the mechanisms through which structural racism influences infant health, and should evaluate policies and interventions implemented to decrease this racial disparity. Studies should also include measures of structural racism on a spatio-temporal scale, perhaps at a smaller area-level unit (e.g., counties or cities), since focusing at the state-level might not capture nuanced variation.
Table 2a-.
The adjusted association between political participation indicators of structural racism and infant mortality stratified by White- and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | Whites | Blacks | Whites | Blacks | Whites | Blacks | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Area level Exposures | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Registered to vote ratio (all) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.05 | (0.97,1.12) | 1.03 | (0.92,1.14) | ||||||||||||||||
| High | 1.03 | (0.95,1.11) | 1.03 | (0.91,1.15) | ||||||||||||||||
| Registered to vote ratio (citizens) | 1.00 | |||||||||||||||||||
| Low (ref) | 1.04 | (0.96,1.11) | 1.00 | |||||||||||||||||
| Moderate | 1.00 | (0.92,1.08) | 1.01 | (0.91,1.12) | ||||||||||||||||
| High | 1.04 | (0.91,1.18) | ||||||||||||||||||
| Voted ratio (all) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.03 | (0.96,1.10) | 1.04 | (0.93,1.15) | ||||||||||||||||
| High | 0.98 | (0.88,1.08) | 1.01 | (0.85,1.19) | ||||||||||||||||
| Voted ratio (citizen) | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.00 | (0.94,1.06) | 1.06 | (0.96,1.15) | ||||||||||||||||
| High | 0.93 | (0.85,1.01) | 1.02 | (0.87,1.18) | ||||||||||||||||
| Black Representation | ||||||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||||||
| Moderate | 1.02 | (0.94,1.11) | 0.88 | (0.81,0.97) | ||||||||||||||||
| High | 0.98 | (0.90,1.07) | 1.03 | (0.90,1.18) | ||||||||||||||||
Table 2b-.
The adjusted association between labor indicators of structural racism and infant mortality stratified by White- and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | Whites | Blacks | Whites | Blacks | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Area level Exposures | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Labor force ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.98 | (0.89,1.06) | 1.00 | (0.88,1.12) | ||||||||||||
| High | 0.97 | (0.87,1.07) | 1.04 | (0.87,1.23) | ||||||||||||
| Employed ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.99 | (0.91,1.07) | 1.00 | (0.88,1.13) | ||||||||||||
| High | 1.01 | (0.90,1.13) | 0.99 | (0.83,1.17) | ||||||||||||
| Management ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 1.01 | (0.92,1.09) | 0.90 | (0.81,0.98) | ||||||||||||
| High | 1.00 | (0.92,1.08) | 0.99 | (0.90,1.10) | ||||||||||||
| Professional employment ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.97 | (0.90,1.05) | 0.96 | (0.86,1.06) | ||||||||||||
| High | 1.00 | (0.91,1.09) | 1.05 | (0.92,1.19) | ||||||||||||
Table 3b-.
The adjusted association between labor indicators of structural racism and infant mortality stratified by White- and Black American infants born in 2010.
| Whites | Blacks | Whites | Blacks | Whites | Blacks | Whites | Blacks | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Labor Indicators | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI |
| Labor force ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.98 | (0.86,1.11) | 0.95 | (0.80,1.12) | ||||||||||||
| High | 0.93 | (0.81,1.07) | 0.90 | (0.70,1.14) | ||||||||||||
| Employed ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.98 | (0.87,1.10) | 0.95 | (0.80,1.12) | ||||||||||||
| High | 1.00 | (0.86,1.17) | 0.89 | (0.70,1.12) | ||||||||||||
| Management ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.98 | (0.86, 1.10) | 0.85 | (0.73,0.97) | ||||||||||||
| High | 1.01 | (0.90,1.13) | 0.96 | (0.82,1.10) | ||||||||||||
| Professional employment ratio | ||||||||||||||||
| Low (ref) | 1.00 | 1.00 | ||||||||||||||
| Moderate | 0.94 | (0.84,1.05) | 0.91 | (0.78,1.04) | ||||||||||||
| High | 0.94 | (0.83,1.06) | 0.98 | (0.81,1.16) | ||||||||||||
Acknowledgments
Research has taken place at the University of Nevada, Reno. Roman Pabayo is now at the University of Alberta, School of Public Health.
Funding: This study was funded by the National Institutes of Health Research, National Institute on Minority Health and Health Disparities 1R15MD010223-01
Footnotes
Compliance with Ethical Standards:
Conflict of Interest: Roman Pabayo declares no conflict of interest. Amy Ehntholt declares no conflict of interest. Kia Davis declares no conflict of interest. Sze Y Liu declares no conflict of interest. Peter Muennig declares no conflict of interest. Daniel Cook declares no conflict of interest.
Ethical Approval: This article does not contain any studies with human participants or animals performed by any of the authors.
Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of a an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.
References
- 1.Anderson RN: A method for constructing complete annual U.S. life tables. Vital Health Stat 2 2000(129): 1–28. [PubMed] [Google Scholar]
- 2.MacDorman MF, Matthews TJ, Mohangoo AD, Zeitlin J: International comparisons of infant mortality and related factors: United States and Europe, 2010. Natl Vital Stat Rep 2014, 63(5): 1–6. [PubMed] [Google Scholar]
- 3.Kochanek KD, Murphy S, Xu J, Arias E: Mortality in the United States, 2016. NCHSData Brief 2017(293): 1–8. [PubMed] [Google Scholar]
- 4.Riddell CA, Harper S, Kaufman JS: Trends in Differences in US Mortality Rates Between Black and White Infants. JAMA Pediatr 2017, 171(9):911–913. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Blair PS, Sidebotham P, Berry PJ, Evans M, Fleming PJ: Major epidemiological changes in sudden infant death syndrome: a 20-year population-based study in the UK. Lancet 2006, 367(9507):314–319. [DOI] [PubMed] [Google Scholar]
- 6.Parker JD, Schoendorf KC, Kiely JL: Associations between measures of socioeconomic status and low birth weight, small for gestational age, and premature delivery in the United States. Annals of epidemiology 1994, 4(4):271–278. [DOI] [PubMed] [Google Scholar]
- 7.Yang J, Carmichael SL, Canfield M, Song J, Shaw GM, National Birth Defects Prevention S: Socioeconomic status in relation to selected birth defects in a large multicentered US case-control study. American journal of epidemiology 2008, 167(2): 145–154. [DOI] [PubMed] [Google Scholar]
- 8.Larson CP: Poverty during pregnancy: Its effects on child health outcomes. Paediatrics & child health 2007, 12(8):673–677. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Mayer SE, Sarin A: Some mechanisms linking economic inequality and infant mortality. Social science & medicine 2005, 60(3):439–455. [DOI] [PubMed] [Google Scholar]
- 10.OECD: Health at a Glance 2013: OECD Indicators; In.; 2013. [Google Scholar]
- 11.Kim D, Saada A: The social determinants of infant mortality and birth outcomes in Western developed nations: a cross-country systematic review. International journal of environmental research and public health 2013, 10(6):2296–2335. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Wise PH, Kotelchuck M, Wilson ML, Mills M: Racial and socioeconomic disparities in childhood mortality in Boston. NEngl J Med 1985, 313(6):360–366. [DOI] [PubMed] [Google Scholar]
- 13.Schoendorf KC, Hogue CJ, Kleinman JC, Rowley D: Mortality among infants of black as compared with white college-educated parents. NEngl J Med 1992, 326(23): 1522–1526. [DOI] [PubMed] [Google Scholar]
- 14.Alexander GR, Kogan MD, Himes JH, Mor JM, Goldenberg R: Racial differences in birthweight for gestational age and infant mortality in extremely-low-risk US populations. Paediatr Perinat Epidemiol 1999, 13(2):205–217. [DOI] [PubMed] [Google Scholar]
- 15.Foster HW, Wu L, Bracken MB, Semenya K, Thomas J, Thomas J: Intergenerational effects of high socioeconomic status on low birthweight and preterm birth in African Americans. J Natl Med Assoc 2000, 92(5):213–221. [PMC free article] [PubMed] [Google Scholar]
- 16.Mendez DD, Hogan VK, Culhane JF: Stress during pregnancy: the role of institutional racism. Stress Health 2013, 29(4):266–274. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Lukachko A, Hatzenbuehler ML, Keyes KM: Structural racism and myocardial infarction in the United States. Soc SciMed 2014, 103:42–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bailey ZD, Krieger N, Agenor M, Graves J, Linos N, Bassett MT: Structural racism and health inequities in the USA: evidence and interventions. Lancet 2017, 389(10077):1453–1463. [DOI] [PubMed] [Google Scholar]
- 19.Massey DS: The prodigal paradigm returns: ecology comes back to sociology In: Does it take a village? Community effects on children, adolescents, and families. edn. Edited by Booth A, Crouter AC. Mahwah, New Jersey: Erlbaum; 2001: 41–48. [Google Scholar]
- 20.Krieger N, Waterman PD, Spasojevic J, Li W, Maduro G, Van Wye G: Public Health Monitoring of Privilege and Deprivation With the Index of Concentration at the Extremes. Am J Public Health 2016, 106(2):256–263. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Wallace M, Crear-Perry J, Richardson L, Tarver M, Theall K: Separate and unequal: Structural racism and infant mortality in the US. Health Place 2017, 45:140–144. [DOI] [PubMed] [Google Scholar]
- 22.Wallace ME, Mendola P, Liu D, Grantz KL: Joint Effects of Structural Racism and Income Inequality on Small-for-Gestational-Age Birth. Am JPublic Health 2015, 105(8): 1681–1688. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Carty DC, Kruger DJ, Turner TM, Campbell B, DeLoney EH, Lewis EY: Racism, health status, and birth outcomes: results of a participatory community-based intervention and health survey. J Urban Health 2011, 88(1):84–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Chambers BD, Erausquin JT, Tanner AE, Nichols TR, Brown-Jeffy S: Testing the Association Between Traditional and Novel Indicators of County-Level Structural Racism and Birth Outcomes among Black and White Women. J Racial Ethn Health Disparities 2017. [DOI] [PubMed] [Google Scholar]
- 26.Raudenbush SW, Bryk AS: Hierarchical linear models: applications and data analysis methods (Advanced Quantitative Techniques in Social Sciences): Thousand Oaks: Sage Publications Inc; 2002. [Google Scholar]
- 27.Black women are earning more college degrees, but that alone won’t close race gaps [https://www.brookings.edu/blog/social-mobility-memos/2017/12/04/black-women-are-earning-more-college-degrees-but-that-alone-wont-close-race-gaps/]
- 28.Brock T: Young adults and higher education: barriers and breakthroughs to success. Future Child 2010, 20(1): 109–132. [DOI] [PubMed] [Google Scholar]
- 29.Rothstein R: The racial achievement gap, segregated schools, and segregated neighborhoods: A constitutional insult. Race and social problems 2015, 7(1):21–30. [Google Scholar]
- 30.Mickelson RA: Affirmative action in education In: Education and Sociology. edn. Edited by Levinson DL, Cookson PWJ, Sadovnik AR. New York, NY: RouteledgeFalmer; 2002. [Google Scholar]
- 31.Medel-Anoneuvo C: Women, Education and Empowerment: Pathways towards Autonomy. In. Hamburg, Germany: UNESCO Institute for Education; 1995. [Google Scholar]
- 32.Mendez DD, Hogan VK, Culhane J: Institutional racism and pregnancy health: using Home Mortgage Disclosure act data to develop an index for Mortgage discrimination at the community level. Public Health Rep 2011, 126 Suppl 3:102–114. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Phillips S: Continued racial disparities in the capital of capital punishment: the Rosenthal era. Houston Law Review 2012, 50(1): 1–30. [Google Scholar]