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Ecological Impacts of Structural Racism on Health Disparity Through Its Determinants and Mediating Factors: A Case Study on Low Birthweight in Three Race/Ethnicity Groups in the United States

PMCID: PMC12111462

PMID:

Abstract

Health disparities among populations across geographic regions, demographic and socio-economic groups are well documented; however, ecological studies which visually demonstrate health disparities associated with structural racism among racialized populations are limited. The purpose of this study was to examine low birthweight (LBW) as a measurable indicator of disproportionate health impacts across three race/ethnicity groups—non-Hispanic Black, Hispanic and non-Hispanic White–in the United States (US) for visualizing ecological manifestation of this disparity attributed to structural racism. We begin by providing the contextual background of structural racism through a literature review, and then more specifically, we examine LBW as a selected health indicator characterized with a socio-biological pathway of structural racism via socio-economic and politico–legal determinants and associated mediating factors to health disparities, from which we synthesized a visualization model with the indicators of structural racism reported in the literature reviewed. To further visualize these impacts, publicly available US County Health Ranking data for LBW, at the county level in two US states, Tennessee and Ohio, were analyzed to uncover area-based ecological health outcome—LBW. Significant correlation and scatter plots provided evidence of LBW as a racially sensitive health indicator associated with impacts of structural racism. These findings were further notable through examination of socio-economic determinants (e.g., race/ethnicity, income, education, and employment) and environmental factors such as housing issues as well as other underlying health conditions. Our case study has opened a window for visualizing disparity across non-Hispanic Black, Hispanic, non-Hispanic White populations as demonstrated by the prevalence of LBW disparity through its determinants and mediating factors at the county level. Potentially important policy implications for reparative change are drawn through our study findings that are salutary and/or reductive for addressing impacts of structural racism. Further studies are needed to fully understand the comprehensive web of area-based ecological factors impacting various health outcomes through the impacts of structural racism.

Full Text

Health inequities, the differences in health outcomes between populations, are avoidable and preventable, and are therefore unjust [1]. The evidence of extant disparities in health indicators, including morbidity and mortality among populations across geographic regions, demographic groups and socio-economic factors as determinants of health, has been officially reported in the United States (US) [2] and Canada [3,4] in the North American context. While both countries are grappling with extant structural racism, research on the various determinants associated with health disparities in Canada [5,6] and particularly in US life expectancy at the county level [7] among racial-ethnic groups has been reported. More specifically, several studies have reported racial discrimination against Black and African American people leading to health disparities that are structurally embedded in the US society [8,9,10,11,12]. Structural racism refers to the totality of ways in which societies embody racial discrimination through mutually reinforcing systems of housing, education, employment, earnings, benefits, credit, media, health care and criminal justice, while these patterns and practices in vogue at the system level, in turn, reinforce discriminatory beliefs, values and the distribution of resources [10]. A recent cross-disciplinary scoping review of the literature has comprehensively presented theoretical underpinnings and impacts of structural racism that are associated with health disparities across populations [13]. Yet, limited evidence visualizes ecological indicators of structural racism to health disparities among multiple racialized populations.
Birth outcomes such as low birthweight (LBW) serve as barometers of health system performance [14] and are generally reported as indicators of overall health and well-being of populations. Birth outcomes are significant risk factors for infant mortality, reflecting a serious public health concern that could have severe lifelong health impacts in terms of quality of life and costly societal burden [15,16]. In high-income North America, the US ranked the highest prevalence of LBW, 8.26% (95% UI, 8.15–8.36), as reported [14]. It is well documented in the US that racial disparities in birth outcomes are attributed to interpersonal and structural racism, but not due to other causes such as discrete genetic differences [15,17,18]; yet, the visualization of such disparities at the area-based ecological level has not been evidently demonstrated in the literature to inform the local-area-level policy planning for reparative changes.
An overwhelming body of empirical evidence shows that there exists an association of local-area (neighborhood) adversity factors such as poverty, segregation, crime, and eviction rates with poor infant outcomes [10,19]. Pervasive socio-economic differences occurring across race/ethnic subgroups are associated with resulting measures of disadvantage in birth outcomes, which continue from childhood to adulthood [20]. The physical, social, and political environments which are currently characterized through the contemporary social determinants of health are fundamentally rooted in structural racism [19]. For example, Black mothers are reported typically twice as likely to give birth to a LBW infant than their White counterparts; this Black–White disparity is due to impact of interpersonal or structural racism along with other risk factors such as mother’s age, education, smoking, and access to prenatal care [15,17,21].
One of the challenges of studying effects of structural racism on health is identifying appropriate geographical units for aggregation of the data to demonstrate its area-based impacts [16]. Thus, research to confirm the role of racism and to evaluate trends in the impact of racism on health outcomes by geographical areas has been hampered by the challenge of measuring racism [15]. In the empirical measurement of structural racism with its complex, insidious, and ecologic nature, residential segregation has been used as a key exposure factor and is highly predictive of a range of adverse birth outcomes [22], whereby three area-based measures of racial/ethnic composition serve as an indicator for residential segregation: the proportion of residents who are non-Hispanic Black, the proportion of residents of color, and the Index of Concentrations at the Extreme (ICE). The ICE measure captures geographical social polarization by looking at extremes of privilege and deprivation within a given neighborhood or census tract. In addition, exploitative revenue generation (the practice of using excessive municipal fines and fees) has a disproportionate impact on residents of color and is associated with preterm and LBW [22]. The discrete residential segregation in certain areas over time could potentially turn into area-based ecological diffusion of its impacts across a geographic jurisdiction. Therefore, we hypothesized that a measurable indicator can be identified at the county level for visualizing ecological impacts of structural racism in health outcomes such as LBW such that the ecological evidence can be used in local-level planning for reparative policy changes.
Using publicly available US County Health Ranking data for the year 2021 extracted from the 2023 Annual Report of the Wisconsin University Population Health Initiative (URL Link for 2023 County Health Rankings National Findings Report—County Health Rankings & Roadmaps: https://www.countyhealthrankings.org/findings-and-insights/2023-county-health-rankings-national-findings-report, accessed on 17 November 2023), an ecological health disparity visualization analysis was carried out for area-based case studies of two selected states, one state in the deep South and another in the North, respectively, Tennessee and Ohio. The two states represent two different paths in the history of racial slavery in the US—Tennessee as a slave state deeply embedded in the Southern plantation system and Ohio as a free state with abolitionist influences. However, both states grappled with racial discrimination long after slavery was formally abolished. The two states provide appropriate representative samples for structural racism in the US. While the first author explored and conducted this research when stationed in Tennessee as a visiting scholar to the US, he also had the opportunity to visit Ohio, providing him a first-hand sense of the current geography and populations of both states during the time of this study in the fall 2023. The charts on the LBW data reported for all counties of the two states, measured in proportion of livebirths, were plotted against the proportions of non-Hispanic Black, Hispanic and non-Hispanic White populations by county to examine trends associated across the two variables. Correlation analyses using SPSS Version 25 software were conducted between LBW and the proportion of three racial-ethnic groups and selected other indicators that were hypothesized to have some link with the structural racism. Low birthweight is considered as a racism-sensitive health indicator, with its socio-economic and politico–legal policy inequities and mediating factors (e.g., race/ethnicity, income, education, and employment) and environmental factors (e.g., severe housing problems). We used the theoretical framework of structural racism with respect to measuring its area-based ecological impact on LWB across counties, whereas the area-based racial segregation as reviewed in the literature [22,23] would be localized within certain parts of the county. Thus, we were able to visualize disparity in the prevalence of LBW among non-Hispanic Black, Hispanic, non-Hispanic White populations across whole counties in the state. Finally, we have drawn potential policy implications for reparative change based on our findings for addressing the impacts of structural racism.
We identified influencing determinants and mediating factors as having an effect on LBW and resulting from structural racism. We tabulated these factors into a summary table (Table 1). The included studies highlight the pervasive impact of structural racism on low birthweight and other adverse birth outcomes, particularly among Black populations in the US.
A total of 7 from the above-stated 21 selected US studies identified state- or county-level polices facilitating structural racism [15,17,18,19,22,29,33] that were negatively associated with LBW, while positive impact of policies were also reported [18,33] such as Safe Babes, Safe Mom and Paid Parent Leave supporting the birthing mothers. Other state- and county-level policy-related causes of structural racism negatively impacting birth weights reported in the literature include multiple level structural racism [21] and county-level eviction rates [36]. A Minnesota study showed that the higher risk of LBW for the US-born Black population compared to their White counterparts was explained by multidimensional structural racism of various typologies based on residential, income, education, employment, home ownership and criminal justice inequities [24,25], while inequities in three commonly known determinants of health—education, income and employment associated with structural racism resulting in LBW as birth outcome—were also reported [26]. Residential segregation typology of this association was also reported by other studies as well [23,36]. Criminal justice inequity was reported as a typology of structural racism associated with LBW by four studies [16,24,26,27]. Heteropatriarchal structural sexism were identified to explain structural racism associated with LBW in two studies [28,30]. The reported vulnerability factors of birthing mothers subject to impacts of structural racism on the birth outcome of LBW include their mental distress [27,34], life course impact such as Adverse Childhood Experiences (ACEs) and Adverse Adult Experiences (AAEs) [31]. The study that considered the status of prenatal mental health and substance use [34] indicated important implications for pregnant women as well as their developing children, and found positive associations between life course impact such as maternal childhood adversity (i.e., Adverse Childhood Experiences—ACEs) with prenatal mental health and substance use outcomes (e.g., severe anxiety, mood dysregulation measured by Mood Disorder Questionnaire—MDQ, and marijuana use) among urban, low-income, mostly minority women such as Black women. Further reports indicated the life course perspective with poorer birthing outcomes among Black people [31]. This originated from heightened exposure to stressors as adverse experiences early in life followed by cumulative exposure to the stressors later in life over time. Experiences of Discriminations (EoDs) at various settings such as school, job hiring, work, housing, medical care, sales and service, banking and mortgage, and in public settings and police or courts could impact on the psychophysiological status of pregnant women, leading to impairment of vasodilation during pregnancy [32]. This study found that impaired vasodilation during pregnancy as a potential mediating factor in the hypertension-related health disparities between African American women and European American women, and exposures to discrimination were associated with higher total peripheral resistance during pregnancy in the former with potential impact on the birth weight of their offspring [32].
While the report that Black mothers had dramatically higher rates of very low birthweight (VLBW) than White mothers [35], it was also reported that between 1989 and 2019 the relative odds that first births were VLBW increased by approximately 16 percent (from 0.030 to 0.034) for Black mothers and 13 percent (from 0.010 to 0.012) for White mothers. In addition, they showed that the maternal age-specific rate of VLBW had a widening gap with higher rates with the increasing age of the Black mothers compared to White mothers in 2017–2019. In summary, the most current literature provides the framework for using LBW as a lens for examining health disparities, such that LBW is characterized as a socio-biological pathway of structural racism. The framework necessitates visualization of these health disparities at the ecological level as vivid evidence of the impact of structural racism.
A pictorial chart model (Figure 1) was derived, summarizing the indicators of structural racism identified from the literature review, visualizing how it shows up in the characteristics of the population, how it impacts socio-economic and politico–legal determinants and mediating factors which, in turn, lead to health disparities such as low birthweight. The positive mediating factors are salutary to health equity, whereas negative ones are associated with health disparity.
County-level ecological socio-demographic and health characteristics of Tennessee and Ohio are summarized in Table 2. Tennessee in the US South, where slavery was legal, and Ohio in the US North, where slavery was illegal, are otherwise fairly comparable states in their demographic composition, though the former has a smaller population size. The former has also a relatively larger proportion of racialized populations, especially the non-Hispanic Black and has relatively lower status in health indicators such as birth outcomes, life expectancy, chronic disease especially diabetes that are generally reported to be linked with the impacts of structural racism. In particular among birth outcomes, LBW, can be considered as a case example indicator of health impact of structural racism in its local-area-based ecological analysis by counties, in both states showing certain distribution patterns as presented in scatter plots (Figure 2). In both states, the rate of LBW was lower in the counties that have lower proportion of non-Hispanic Black populations and increased with the proportion of that population within the county. Also in both states, the reverse pattern of lower LBW rate was observed with the increasing proportion of the non-Hispanic White population, while the Hispanic population did not show any significant pattern. These plots were consistent with Pearson’s correlations of LBW rate, which were significantly positive with the proportion of the non-Hispanic Black population (p < 0.01) and significantly negative with the proportion of the non-Hispanic White population (p < 0.01), whereas the Hispanic population was statistically non-significant in both states. It must be noted that the non-Hispanic Black population had suffered from extreme racial discrimination with the historical enslavement, followed by a series of racially discriminatory policies as illustrated in Figure 1, and their health outcomes such as LBW had been severely impacted by the socio-economic and politico–legal policy determinants and associated mediating factors. On the other hand, the Hispanic population might not have been subjected to racial discrimination practices that were of the same type or severity as the former. We suggest that this would help explain the difference in the health outcomes between the two populations.
Using Pearson’s correlation analysis, further exploration of selected measurable indicators that have been generally considered examples of mediating factors associated with the impacts of structural racism (Table 2) showed that Education (Highschool completion in TN, Highschool graduation in OH, school segregation), Income (Income inequality, Median household income, Childhood poverty, Unemployment, Food insecurity, and Health (Life expectancy, Frequent physical stress, Diabetes prevalence, HIV prevalence) were all significantly correlated towards disadvantageousness for LBW. The selection of these measurable indicators for correlation analysis as presented in Table 3 was an opportunistic exercise, as the indicators were intuitively selected based on their relevance to the findings of the literature review with respect to impact of structural racism on the selected health outcome, LBW, from the available indicators in the database used.
Our case study-based analysis of LBW provides visualized ecological evidence of health disparities, particularly between non-Hispanic White and non-Hispanic Black populations to the disadvantage of the latter. We were able to show the nature of health disparity structurally embedded in the influencing factors measurable at the county level as elucidated by the racially disproportionate ecological distribution of LBW. Particularly, our two-state case study supports the notion that residential segregation is a reflection and reinforcement of structural and institutional racism resulting from racialized and economically segregated neighborhoods [10,23,24].
Mehra et al. introduced five distinct modes of operationalizations of segregation that could explain its impact at the county level [23]. These five modes that could be calculated for indexing cross micro-level spatial units (e.g., neighborhoods) within macro-level spatial units (e.g., regions) are comprised of Exposure—the degree of neighborhood isolation or interaction of minority with majority groups; Evenness—the degree to which each neighborhood has the same proportion of minority and majority members for even distribution; Clustering—the degree to which minority neighborhoods are contiguous and tightly clustered; Concentration—the degree to which minority members occupy a small proportion of the total area of a region; and Centralization—the degree to which a minority group is centrally located within a region. These modes of segregation could explain how the proportions of the LBW rate are positively and significantly correlated with the proportion of the non-Hispanic Black population and negatively correlated with the non-Hispanic White population, in both states studied. However, interestingly in our case studies, the Hispanic population did not show these patterns of significant health disparity at the ecological level, even though it could have been subjected to county-level exploitative revenue generation through fees and fines as described by Davies et al. [22]. Yet, it is important to note that Hispanics have not previously been reported to have these five modes of segregation, and the ethnic/racial discrimination against them was not the same in terms of its form and severity as in the non-Hispanic Black population to cause similar impact at the ecological level, and this may be an area for future study.
The disproportionate representation of Black people in the US penal system demonstrates longstanding mechanisms underlying inequities in incarceration (dating back to colonialism) and health at the population level [10]. The ecological concentration of incarceration measured as county-level prison rates has been reported to be associated with racial disparities in adverse birth outcome such as LBW mediated through two pathways—community-level mental stress and reduced health care access [27].
Inequity in education has been identified in the literature [24,26], and constitutes one determinant of the multidimensional structural racism typology which could be a factor explaining birth inequities leading to a higher risk of LBW for the US-born Black population [24]. This further resonates with our county-level results showing significant correlations of LBW with a degree of High School completion in Tennessee, High School graduation in Ohio and a degree of school segregation in both states as valid indicators of education (Table 2). Likewise, our background literature review indicated income, poverty and employment as three other determinants of the multidimensional structural racism typology, explaining the higher risk of LBW among the Black population [24,25,26,29]. These findings were consistent with significantly positive correlations of LWB with income inequality (negative correlation with median household income), child poverty and unemployment at the county level in both the states (Table 2).
Closely related with the residential segregation, homeownership has been well documented as one of the major components embedded in the structural racism in the US leading to health disparity such as impacting negatively on birth outcomes in the Black population [9,19,25,26]. This pattern of relationships has been consistently elucidated by the significant correlations of LBW negatively with homeownership and positively with severe housing problems at the county level in both the states.
Some of the factors intrinsic to the birthing Black mothers reported in the literature influencing their disproportionate rate of LWB include life course impacts of Adverse Childhood Experiences (ACEs) and Adverse Adult Experiences [31,34], prenatal mental health and substance use [34], maternal age at first births [35], as well as the epigenetic legacy of enslavement and ongoing cultural loss [21], which are all factors that are structural in nature. Furthermore, significant correlations of LBW found with other selected health status indicators, such as being negatively correlated with life expectancy, and positively with frequent physical distress, HIV prevalence and food insecurity at the county level in both states could indicate their respective association embedded as factors mediating structural racism, similar to those of community-level mental stress and reduced health care access reported [27].
Allostatic load. In the recent scoping review, it was surmised [13] that Black Americans suffered from chronic stresses on an ongoing basis, bearing a higher allostatic load as compared to White individuals. The concept of allostatic load, first introduced by McEwen and Stellar [37], is the physio-pathological impact of wear and tear resulting from chronic stresses on a number of organs and tissues that can predispose the organism to disease. It is crucial in understanding health inequalities, particularly in the context of our study on LBW among non-Hispanic Black women compared to their non-Hispanic White counterparts. It refers to the physiological cost of chronic exposure to fluctuating or heightened neural and neuroendocrine responses due to repeated or chronic environmental stressors [38]. Ethnicity has been associated with varying levels of allostatic load, with Black Americans generally exhibiting higher levels than the White population [38], while everyday racial discrimination, as well as institution-specific structural discrimination, differentially affect allostatic load among Black women, with higher levels reported in those experiencing greater perceived racial or social adversities throughout their lives [38]. While general population studies consistently show that low socio-economic status, impoverished neighborhoods, and low educational attainment increase allostatic load through the mechanism of neuronal and hormonal responses to the chronic stresses caused by those factors, the evidence of specific impact of allostatic load on birth outcomes is limited, warranting further investigation to establish a clear understanding of the associated multidimensional factors.
Finally, state- or county-level policies, as reported in our literature review, that have a salutary impact against structural racism including aid to needy families, housing assistance, Medicaid, minimum wage, earned income tax credits [17], political representation of racialized minorities [19], the Safe Babies, Safe Moms initiative [18], paid parental leave [33], community building as well as culturally centered care [21] could have reparative impacts on health disparity measured by the indicator such as LBW. On the other hand, implementation of these policies has the potential to not only positively impact but at the same time reinforce structural racism, such as the case of racialized police use of force [16], reductive racial bias by the state [15], exploitative revenue generating county-level fees and fines (Davis et al., 2023), county-level housing eviction rates [36]. As such, policy implementation could have reductive association leading to a higher LBW rate in counties with a higher proportion of racialized populations.
In the backdrop of the pictorial model (Figure 1) derived from our literature review and visualization of ecological scatter plot charts (Figure 2) from our data analysis, we found that while some determinants such as higher rates of high school completion/graduation, median household income, homeownership, and life expectancy are positively (i.e., favorably) correlated with lower LBW rates, other determinants such as school segregation, income inequality, child poverty, unemployment, severe housing problems, frequent physical distress, diseases (e.g., diabetes and HIV), and food insecurity emerge as significant deterrents to healthier LBW outcomes. The consistency of these associations across counties in both US states (Table 3) underscores their embodiment of structural racism. This provides visualization of the ecological impacts of structural racism on LBW disparities, particularly among non-Hispanic Black populations, compared to their non-Hispanic White counterparts, presenting compelling evidence of the area-level impacts of structural racism.
To address the multifactorial nature of structural racism including discrimination embedded in labor markets, residential segregation, income inequality, and challenges to fair political representation, we require multifaceted policy interventions, community-level changes, and systemic reforms targeting the various dimensions of structural racism. Effective solutions must also consider the historical context and cumulative stressors affecting marginalized communities through intergenerational trauma leading to allostatic load. The background literature review and ecological analysis of LBW in our two-state case study generally corroborated each other: extant health disparities between non-Hispanic White and non-Hispanic Black populations are associated with area-level structural racism-related socio-economic determinants and mediating factors. The racially disproportionate county-level distribution of LBW along with various influencing determinants and mediating factors elucidate the nature of health disparity structurally embedded in US society. The racially disproportionate ecological concentration of the rates of residential segregation, incarceration, inequities in education, income and employment, some measurable birthing mother traits, and racially biased policies at the state or county level constitute the components of structural racism that lead to disparity in health such as LBW and need policy change considerations. Future research should further examine the intersectional (i.e., interlocking) relationships by which structural racism and other structural forces (e.g., sexism) jointly exacerbate reproductive health inequities [39].

Sections

"[{\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B1-ijerph-22-00715\", \"B2-ijerph-22-00715\", \"B3-ijerph-22-00715\", \"B4-ijerph-22-00715\", \"B5-ijerph-22-00715\", \"B6-ijerph-22-00715\", \"B7-ijerph-22-00715\", \"B8-ijerph-22-00715\", \"B9-ijerph-22-00715\", \"B10-ijerph-22-00715\", \"B11-ijerph-22-00715\", \"B12-ijerph-22-00715\", \"B10-ijerph-22-00715\", \"B13-ijerph-22-00715\"], \"section\": \"1. Background\", \"text\": \"Health inequities, the differences in health outcomes between populations, are avoidable and preventable, and are therefore unjust [1]. The evidence of extant disparities in health indicators, including morbidity and mortality among populations across geographic regions, demographic groups and socio-economic factors as determinants of health, has been officially reported in the United States (US) [2] and Canada [3,4] in the North American context. While both countries are grappling with extant structural racism, research on the various determinants associated with health disparities in Canada [5,6] and particularly in US life expectancy at the county level [7] among racial-ethnic groups has been reported. More specifically, several studies have reported racial discrimination against Black and African American people leading to health disparities that are structurally embedded in the US society [8,9,10,11,12]. Structural racism refers to the totality of ways in which societies embody racial discrimination through mutually reinforcing systems of housing, education, employment, earnings, benefits, credit, media, health care and criminal justice, while these patterns and practices in vogue at the system level, in turn, reinforce discriminatory beliefs, values and the distribution of resources [10]. A recent cross-disciplinary scoping review of the literature has comprehensively presented theoretical underpinnings and impacts of structural racism that are associated with health disparities across populations [13]. Yet, limited evidence visualizes ecological indicators of structural racism to health disparities among multiple racialized populations.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B14-ijerph-22-00715\", \"B15-ijerph-22-00715\", \"B16-ijerph-22-00715\", \"B14-ijerph-22-00715\", \"B15-ijerph-22-00715\", \"B17-ijerph-22-00715\", \"B18-ijerph-22-00715\"], \"section\": \"1. Background\", \"text\": \"Birth outcomes such as low birthweight (LBW) serve as barometers of health system performance [14] and are generally reported as indicators of overall health and well-being of populations. Birth outcomes are significant risk factors for infant mortality, reflecting a serious public health concern that could have severe lifelong health impacts in terms of quality of life and costly societal burden [15,16]. In high-income North America, the US ranked the highest prevalence of LBW, 8.26% (95% UI, 8.15\\u20138.36), as reported [14]. It is well documented in the US that racial disparities in birth outcomes are attributed to interpersonal and structural racism, but not due to other causes such as discrete genetic differences [15,17,18]; yet, the visualization of such disparities at the area-based ecological level has not been evidently demonstrated in the literature to inform the local-area-level policy planning for reparative changes.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B10-ijerph-22-00715\", \"B19-ijerph-22-00715\", \"B20-ijerph-22-00715\", \"B19-ijerph-22-00715\", \"B15-ijerph-22-00715\", \"B17-ijerph-22-00715\", \"B21-ijerph-22-00715\"], \"section\": \"1. Background\", \"text\": \"An overwhelming body of empirical evidence shows that there exists an association of local-area (neighborhood) adversity factors such as poverty, segregation, crime, and eviction rates with poor infant outcomes [10,19]. Pervasive socio-economic differences occurring across race/ethnic subgroups are associated with resulting measures of disadvantage in birth outcomes, which continue from childhood to adulthood [20]. The physical, social, and political environments which are currently characterized through the contemporary social determinants of health are fundamentally rooted in structural racism [19]. For example, Black mothers are reported typically twice as likely to give birth to a LBW infant than their White counterparts; this Black\\u2013White disparity is due to impact of interpersonal or structural racism along with other risk factors such as mother\\u2019s age, education, smoking, and access to prenatal care [15,17,21].\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B16-ijerph-22-00715\", \"B15-ijerph-22-00715\", \"B22-ijerph-22-00715\", \"B22-ijerph-22-00715\"], \"section\": \"1. Background\", \"text\": \"One of the challenges of studying effects of structural racism on health is identifying appropriate geographical units for aggregation of the data to demonstrate its area-based impacts [16]. Thus, research to confirm the role of racism and to evaluate trends in the impact of racism on health outcomes by geographical areas has been hampered by the challenge of measuring racism [15]. In the empirical measurement of structural racism with its complex, insidious, and ecologic nature, residential segregation has been used as a key exposure factor and is highly predictive of a range of adverse birth outcomes [22], whereby three area-based measures of racial/ethnic composition serve as an indicator for residential segregation: the proportion of residents who are non-Hispanic Black, the proportion of residents of color, and the Index of Concentrations at the Extreme (ICE). The ICE measure captures geographical social polarization by looking at extremes of privilege and deprivation within a given neighborhood or census tract. In addition, exploitative revenue generation (the practice of using excessive municipal fines and fees) has a disproportionate impact on residents of color and is associated with preterm and LBW [22]. The discrete residential segregation in certain areas over time could potentially turn into area-based ecological diffusion of its impacts across a geographic jurisdiction. Therefore, we hypothesized that a measurable indicator can be identified at the county level for visualizing ecological impacts of structural racism in health outcomes such as LBW such that the ecological evidence can be used in local-level planning for reparative policy changes.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B22-ijerph-22-00715\", \"B23-ijerph-22-00715\"], \"section\": \"2.2. Ecological Health Disparity Analysis of County-Level Data\", \"text\": \"Using publicly available US County Health Ranking data for the year 2021 extracted from the 2023 Annual Report of the Wisconsin University Population Health Initiative (URL Link for 2023 County Health Rankings National Findings Report\\u2014County Health Rankings & Roadmaps: https://www.countyhealthrankings.org/findings-and-insights/2023-county-health-rankings-national-findings-report, accessed on 17 November 2023), an ecological health disparity visualization analysis was carried out for area-based case studies of two selected states, one state in the deep South and another in the North, respectively, Tennessee and Ohio. The two states represent two different paths in the history of racial slavery in the US\\u2014Tennessee as a slave state deeply embedded in the Southern plantation system and Ohio as a free state with abolitionist influences. However, both states grappled with racial discrimination long after slavery was formally abolished. The two states provide appropriate representative samples for structural racism in the US. While the first author explored and conducted this research when stationed in Tennessee as a visiting scholar to the US, he also had the opportunity to visit Ohio, providing him a first-hand sense of the current geography and populations of both states during the time of this study in the fall 2023. The charts on the LBW data reported for all counties of the two states, measured in proportion of livebirths, were plotted against the proportions of non-Hispanic Black, Hispanic and non-Hispanic White populations by county to examine trends associated across the two variables. Correlation analyses using SPSS Version 25 software were conducted between LBW and the proportion of three racial-ethnic groups and selected other indicators that were hypothesized to have some link with the structural racism. Low birthweight is considered as a racism-sensitive health indicator, with its socio-economic and politico\\u2013legal policy inequities and mediating factors (e.g., race/ethnicity, income, education, and employment) and environmental factors (e.g., severe housing problems). We used the theoretical framework of structural racism with respect to measuring its area-based ecological impact on LWB across counties, whereas the area-based racial segregation as reviewed in the literature [22,23] would be localized within certain parts of the county. Thus, we were able to visualize disparity in the prevalence of LBW among non-Hispanic Black, Hispanic, non-Hispanic White populations across whole counties in the state. Finally, we have drawn potential policy implications for reparative change based on our findings for addressing the impacts of structural racism.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"ijerph-22-00715-t001\"], \"section\": \"3.1. Literature Review for Contextual Background of Low Birthweight as Pathway for Structural Racism\", \"text\": \"We identified influencing determinants and mediating factors as having an effect on LBW and resulting from structural racism. We tabulated these factors into a summary table (Table 1). The included studies highlight the pervasive impact of structural racism on low birthweight and other adverse birth outcomes, particularly among Black populations in the US.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B15-ijerph-22-00715\", \"B17-ijerph-22-00715\", \"B18-ijerph-22-00715\", \"B19-ijerph-22-00715\", \"B22-ijerph-22-00715\", \"B29-ijerph-22-00715\", \"B33-ijerph-22-00715\", \"B18-ijerph-22-00715\", \"B33-ijerph-22-00715\", \"B21-ijerph-22-00715\", \"B36-ijerph-22-00715\", \"B24-ijerph-22-00715\", \"B25-ijerph-22-00715\", \"B26-ijerph-22-00715\", \"B23-ijerph-22-00715\", \"B36-ijerph-22-00715\", \"B16-ijerph-22-00715\", \"B24-ijerph-22-00715\", \"B26-ijerph-22-00715\", \"B27-ijerph-22-00715\", \"B28-ijerph-22-00715\", \"B30-ijerph-22-00715\", \"B27-ijerph-22-00715\", \"B34-ijerph-22-00715\", \"B31-ijerph-22-00715\", \"B34-ijerph-22-00715\", \"B31-ijerph-22-00715\", \"B32-ijerph-22-00715\", \"B32-ijerph-22-00715\"], \"section\": \"3.1. Literature Review for Contextual Background of Low Birthweight as Pathway for Structural Racism\", \"text\": \"A total of 7 from the above-stated 21 selected US studies identified state- or county-level polices facilitating structural racism [15,17,18,19,22,29,33] that were negatively associated with LBW, while positive impact of policies were also reported [18,33] such as Safe Babes, Safe Mom and Paid Parent Leave supporting the birthing mothers. Other state- and county-level policy-related causes of structural racism negatively impacting birth weights reported in the literature include multiple level structural racism [21] and county-level eviction rates [36]. A Minnesota study showed that the higher risk of LBW for the US-born Black population compared to their White counterparts was explained by multidimensional structural racism of various typologies based on residential, income, education, employment, home ownership and criminal justice inequities [24,25], while inequities in three commonly known determinants of health\\u2014education, income and employment associated with structural racism resulting in LBW as birth outcome\\u2014were also reported [26]. Residential segregation typology of this association was also reported by other studies as well [23,36]. Criminal justice inequity was reported as a typology of structural racism associated with LBW by four studies [16,24,26,27]. Heteropatriarchal structural sexism were identified to explain structural racism associated with LBW in two studies [28,30]. The reported vulnerability factors of birthing mothers subject to impacts of structural racism on the birth outcome of LBW include their mental distress [27,34], life course impact such as Adverse Childhood Experiences (ACEs) and Adverse Adult Experiences (AAEs) [31]. The study that considered the status of prenatal mental health and substance use [34] indicated important implications for pregnant women as well as their developing children, and found positive associations between life course impact such as maternal childhood adversity (i.e., Adverse Childhood Experiences\\u2014ACEs) with prenatal mental health and substance use outcomes (e.g., severe anxiety, mood dysregulation measured by Mood Disorder Questionnaire\\u2014MDQ, and marijuana use) among urban, low-income, mostly minority women such as Black women. Further reports indicated the life course perspective with poorer birthing outcomes among Black people [31]. This originated from heightened exposure to stressors as adverse experiences early in life followed by cumulative exposure to the stressors later in life over time. Experiences of Discriminations (EoDs) at various settings such as school, job hiring, work, housing, medical care, sales and service, banking and mortgage, and in public settings and police or courts could impact on the psychophysiological status of pregnant women, leading to impairment of vasodilation during pregnancy [32]. This study found that impaired vasodilation during pregnancy as a potential mediating factor in the hypertension-related health disparities between African American women and European American women, and exposures to discrimination were associated with higher total peripheral resistance during pregnancy in the former with potential impact on the birth weight of their offspring [32].\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B35-ijerph-22-00715\"], \"section\": \"3.1. Literature Review for Contextual Background of Low Birthweight as Pathway for Structural Racism\", \"text\": \"While the report that Black mothers had dramatically higher rates of very low birthweight (VLBW) than White mothers [35], it was also reported that between 1989 and 2019 the relative odds that first births were VLBW increased by approximately 16 percent (from 0.030 to 0.034) for Black mothers and 13 percent (from 0.010 to 0.012) for White mothers. In addition, they showed that the maternal age-specific rate of VLBW had a widening gap with higher rates with the increasing age of the Black mothers compared to White mothers in 2017\\u20132019. In summary, the most current literature provides the framework for using LBW as a lens for examining health disparities, such that LBW is characterized as a socio-biological pathway of structural racism. The framework necessitates visualization of these health disparities at the ecological level as vivid evidence of the impact of structural racism.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"ijerph-22-00715-f001\"], \"section\": \"3.1. Literature Review for Contextual Background of Low Birthweight as Pathway for Structural Racism\", \"text\": \"A pictorial chart model (Figure 1) was derived, summarizing the indicators of structural racism identified from the literature review, visualizing how it shows up in the characteristics of the population, how it impacts socio-economic and politico\\u2013legal determinants and mediating factors which, in turn, lead to health disparities such as low birthweight. The positive mediating factors are salutary to health equity, whereas negative ones are associated with health disparity. \"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"ijerph-22-00715-t002\", \"ijerph-22-00715-f002\", \"ijerph-22-00715-f001\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"County-level ecological socio-demographic and health characteristics of Tennessee and Ohio are summarized in Table 2. Tennessee in the US South, where slavery was legal, and Ohio in the US North, where slavery was illegal, are otherwise fairly comparable states in their demographic composition, though the former has a smaller population size. The former has also a relatively larger proportion of racialized populations, especially the non-Hispanic Black and has relatively lower status in health indicators such as birth outcomes, life expectancy, chronic disease especially diabetes that are generally reported to be linked with the impacts of structural racism. In particular among birth outcomes, LBW, can be considered as a case example indicator of health impact of structural racism in its local-area-based ecological analysis by counties, in both states showing certain distribution patterns as presented in scatter plots (Figure 2). In both states, the rate of LBW was lower in the counties that have lower proportion of non-Hispanic Black populations and increased with the proportion of that population within the county. Also in both states, the reverse pattern of lower LBW rate was observed with the increasing proportion of the non-Hispanic White population, while the Hispanic population did not show any significant pattern. These plots were consistent with Pearson\\u2019s correlations of LBW rate, which were significantly positive with the proportion of the non-Hispanic Black population (p < 0.01) and significantly negative with the proportion of the non-Hispanic White population (p < 0.01), whereas the Hispanic population was statistically non-significant in both states. It must be noted that the non-Hispanic Black population had suffered from extreme racial discrimination with the historical enslavement, followed by a series of racially discriminatory policies as illustrated in Figure 1, and their health outcomes such as LBW had been severely impacted by the socio-economic and politico\\u2013legal policy determinants and associated mediating factors. On the other hand, the Hispanic population might not have been subjected to racial discrimination practices that were of the same type or severity as the former. We suggest that this would help explain the difference in the health outcomes between the two populations.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"ijerph-22-00715-t002\", \"ijerph-22-00715-t003\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Using Pearson\\u2019s correlation analysis, further exploration of selected measurable indicators that have been generally considered examples of mediating factors associated with the impacts of structural racism (Table 2) showed that Education (Highschool completion in TN, Highschool graduation in OH, school segregation), Income (Income inequality, Median household income, Childhood poverty, Unemployment, Food insecurity, and Health (Life expectancy, Frequent physical stress, Diabetes prevalence, HIV prevalence) were all significantly correlated towards disadvantageousness for LBW. The selection of these measurable indicators for correlation analysis as presented in Table 3 was an opportunistic exercise, as the indicators were intuitively selected based on their relevance to the findings of the literature review with respect to impact of structural racism on the selected health outcome, LBW, from the available indicators in the database used. \"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B10-ijerph-22-00715\", \"B23-ijerph-22-00715\", \"B24-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Our case study-based analysis of LBW provides visualized ecological evidence of health disparities, particularly between non-Hispanic White and non-Hispanic Black populations to the disadvantage of the latter. We were able to show the nature of health disparity structurally embedded in the influencing factors measurable at the county level as elucidated by the racially disproportionate ecological distribution of LBW. Particularly, our two-state case study supports the notion that residential segregation is a reflection and reinforcement of structural and institutional racism resulting from racialized and economically segregated neighborhoods [10,23,24].\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B23-ijerph-22-00715\", \"B22-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Mehra et al. introduced five distinct modes of operationalizations of segregation that could explain its impact at the county level [23]. These five modes that could be calculated for indexing cross micro-level spatial units (e.g., neighborhoods) within macro-level spatial units (e.g., regions) are comprised of Exposure\\u2014the degree of neighborhood isolation or interaction of minority with majority groups; Evenness\\u2014the degree to which each neighborhood has the same proportion of minority and majority members for even distribution; Clustering\\u2014the degree to which minority neighborhoods are contiguous and tightly clustered; Concentration\\u2014the degree to which minority members occupy a small proportion of the total area of a region; and Centralization\\u2014the degree to which a minority group is centrally located within a region. These modes of segregation could explain how the proportions of the LBW rate are positively and significantly correlated with the proportion of the non-Hispanic Black population and negatively correlated with the non-Hispanic White population, in both states studied. However, interestingly in our case studies, the Hispanic population did not show these patterns of significant health disparity at the ecological level, even though it could have been subjected to county-level exploitative revenue generation through fees and fines as described by Davies et al. [22]. Yet, it is important to note that Hispanics have not previously been reported to have these five modes of segregation, and the ethnic/racial discrimination against them was not the same in terms of its form and severity as in the non-Hispanic Black population to cause similar impact at the ecological level, and this may be an area for future study.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B10-ijerph-22-00715\", \"B27-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"The disproportionate representation of Black people in the US penal system demonstrates longstanding mechanisms underlying inequities in incarceration (dating back to colonialism) and health at the population level [10]. The ecological concentration of incarceration measured as county-level prison rates has been reported to be associated with racial disparities in adverse birth outcome such as LBW mediated through two pathways\\u2014community-level mental stress and reduced health care access [27].\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B24-ijerph-22-00715\", \"B26-ijerph-22-00715\", \"B24-ijerph-22-00715\", \"ijerph-22-00715-t002\", \"B24-ijerph-22-00715\", \"B25-ijerph-22-00715\", \"B26-ijerph-22-00715\", \"B29-ijerph-22-00715\", \"ijerph-22-00715-t002\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Inequity in education has been identified in the literature [24,26], and constitutes one determinant of the multidimensional structural racism typology which could be a factor explaining birth inequities leading to a higher risk of LBW for the US-born Black population [24]. This further resonates with our county-level results showing significant correlations of LBW with a degree of High School completion in Tennessee, High School graduation in Ohio and a degree of school segregation in both states as valid indicators of education (Table 2). Likewise, our background literature review indicated income, poverty and employment as three other determinants of the multidimensional structural racism typology, explaining the higher risk of LBW among the Black population [24,25,26,29]. These findings were consistent with significantly positive correlations of LWB with income inequality (negative correlation with median household income), child poverty and unemployment at the county level in both the states (Table 2).\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B9-ijerph-22-00715\", \"B19-ijerph-22-00715\", \"B25-ijerph-22-00715\", \"B26-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Closely related with the residential segregation, homeownership has been well documented as one of the major components embedded in the structural racism in the US leading to health disparity such as impacting negatively on birth outcomes in the Black population [9,19,25,26]. This pattern of relationships has been consistently elucidated by the significant correlations of LBW negatively with homeownership and positively with severe housing problems at the county level in both the states.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B31-ijerph-22-00715\", \"B34-ijerph-22-00715\", \"B34-ijerph-22-00715\", \"B35-ijerph-22-00715\", \"B21-ijerph-22-00715\", \"B27-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Some of the factors intrinsic to the birthing Black mothers reported in the literature influencing their disproportionate rate of LWB include life course impacts of Adverse Childhood Experiences (ACEs) and Adverse Adult Experiences [31,34], prenatal mental health and substance use [34], maternal age at first births [35], as well as the epigenetic legacy of enslavement and ongoing cultural loss [21], which are all factors that are structural in nature. Furthermore, significant correlations of LBW found with other selected health status indicators, such as being negatively correlated with life expectancy, and positively with frequent physical distress, HIV prevalence and food insecurity at the county level in both states could indicate their respective association embedded as factors mediating structural racism, similar to those of community-level mental stress and reduced health care access reported [27].\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B13-ijerph-22-00715\", \"B37-ijerph-22-00715\", \"B38-ijerph-22-00715\", \"B38-ijerph-22-00715\", \"B38-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Allostatic load. In the recent scoping review, it was surmised [13] that Black Americans suffered from chronic stresses on an ongoing basis, bearing a higher allostatic load as compared to White individuals. The concept of allostatic load, first introduced by McEwen and Stellar [37], is the physio-pathological impact of wear and tear resulting from chronic stresses on a number of organs and tissues that can predispose the organism to disease. It is crucial in understanding health inequalities, particularly in the context of our study on LBW among non-Hispanic Black women compared to their non-Hispanic White counterparts. It refers to the physiological cost of chronic exposure to fluctuating or heightened neural and neuroendocrine responses due to repeated or chronic environmental stressors [38]. Ethnicity has been associated with varying levels of allostatic load, with Black Americans generally exhibiting higher levels than the White population [38], while everyday racial discrimination, as well as institution-specific structural discrimination, differentially affect allostatic load among Black women, with higher levels reported in those experiencing greater perceived racial or social adversities throughout their lives [38]. While general population studies consistently show that low socio-economic status, impoverished neighborhoods, and low educational attainment increase allostatic load through the mechanism of neuronal and hormonal responses to the chronic stresses caused by those factors, the evidence of specific impact of allostatic load on birth outcomes is limited, warranting further investigation to establish a clear understanding of the associated multidimensional factors.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B17-ijerph-22-00715\", \"B19-ijerph-22-00715\", \"B18-ijerph-22-00715\", \"B33-ijerph-22-00715\", \"B21-ijerph-22-00715\", \"B16-ijerph-22-00715\", \"B15-ijerph-22-00715\", \"B36-ijerph-22-00715\"], \"section\": \"3.2. Ecological Case Study of Two US Counties\", \"text\": \"Finally, state- or county-level policies, as reported in our literature review, that have a salutary impact against structural racism including aid to needy families, housing assistance, Medicaid, minimum wage, earned income tax credits [17], political representation of racialized minorities [19], the Safe Babies, Safe Moms initiative [18], paid parental leave [33], community building as well as culturally centered care [21] could have reparative impacts on health disparity measured by the indicator such as LBW. On the other hand, implementation of these policies has the potential to not only positively impact but at the same time reinforce structural racism, such as the case of racialized police use of force [16], reductive racial bias by the state [15], exploitative revenue generating county-level fees and fines (Davis et al., 2023), county-level housing eviction rates [36]. As such, policy implementation could have reductive association leading to a higher LBW rate in counties with a higher proportion of racialized populations.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"ijerph-22-00715-f001\", \"ijerph-22-00715-f002\", \"ijerph-22-00715-t003\"], \"section\": \"4. Conclusions\", \"text\": \"In the backdrop of the pictorial model (Figure 1) derived from our literature review and visualization of ecological scatter plot charts (Figure 2) from our data analysis, we found that while some determinants such as higher rates of high school completion/graduation, median household income, homeownership, and life expectancy are positively (i.e., favorably) correlated with lower LBW rates, other determinants such as school segregation, income inequality, child poverty, unemployment, severe housing problems, frequent physical distress, diseases (e.g., diabetes and HIV), and food insecurity emerge as significant deterrents to healthier LBW outcomes. The consistency of these associations across counties in both US states (Table 3) underscores their embodiment of structural racism. This provides visualization of the ecological impacts of structural racism on LBW disparities, particularly among non-Hispanic Black populations, compared to their non-Hispanic White counterparts, presenting compelling evidence of the area-level impacts of structural racism.\"}, {\"pmc\": \"PMC12111462\", \"pmid\": \"\", \"reference_ids\": [\"B39-ijerph-22-00715\"], \"section\": \"4. Conclusions\", \"text\": \"To address the multifactorial nature of structural racism including discrimination embedded in labor markets, residential segregation, income inequality, and challenges to fair political representation, we require multifaceted policy interventions, community-level changes, and systemic reforms targeting the various dimensions of structural racism. Effective solutions must also consider the historical context and cumulative stressors affecting marginalized communities through intergenerational trauma leading to allostatic load. The background literature review and ecological analysis of LBW in our two-state case study generally corroborated each other: extant health disparities between non-Hispanic White and non-Hispanic Black populations are associated with area-level structural racism-related socio-economic determinants and mediating factors. The racially disproportionate county-level distribution of LBW along with various influencing determinants and mediating factors elucidate the nature of health disparity structurally embedded in US society. The racially disproportionate ecological concentration of the rates of residential segregation, incarceration, inequities in education, income and employment, some measurable birthing mother traits, and racially biased policies at the state or county level constitute the components of structural racism that lead to disparity in health such as LBW and need policy change considerations. Future research should further examine the intersectional (i.e., interlocking) relationships by which structural racism and other structural forces (e.g., sexism) jointly exacerbate reproductive health inequities [39].\"}]"

Metadata

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