Place-based Measures Research Articles

Dynamic changes in place-based measures of structural racism and preterm birth in the USA

BackgroundStructurally racist systems, ideologies and processes generate and reinforce inequities among minoritised racial/ethnic groups. Prior cross-sectional literature finds that place-based structural racism, such as the Index of Concentration at the...

Place-Based Measures of Inequity and Vision Difficulty and Blindness

Known social risk factors associated with poor visual and systemic health in the US include segregation, income inequality, and persistent poverty. To investigate the association of vision difficulty, including blindness, in neighborhoods with measures of inequity (Theil H index, Gini index, and persistent poverty). This cross-sectional study used data from the 2012-2016 American Community Survey and 2010 US census tracts as well as Theil H index, Gini index, and persistent poverty measures from PolicyMap. Data analysis was completed in July 2023. The main outcome was the number of census tract residents reporting vision difficulty and blindness (VDB) and the association with the Theil H index, Gini index, or persistent poverty, assessed using logistic regression. In total, 73 198 census tracts were analyzed. For every 0.1-unit increase in Theil H index and Gini index, there was an increased odds of VDB after controlling for census tract-level median age, the percentage of the population that identified as female sex, the percentage of the population that identified as a member of a racial or ethnic minority group, state, and population size (Theil H index: odds ratio [OR], 1.14 [95% CI, 1.14-1.14; P < .001]; Gini index: OR, 1.15 [95% CI, 1.15-1.15; P < .001]). Persistent poverty was associated with an increased odds of VDB after controlling for census tract-level median age, the percentage of the population that identified as female sex, the percentage of the population that identified as a member of a racial or ethnic minority group, state, and population size compared with nonpersistent poverty (OR, 1.36; 95% CI, 1.35-1.36; P < .001). In this cross-sectional study, residential measures of inequity through segregation, income inequality, or persistent poverty were associated with a greater number of residents living with VDB. It is essential to understand and address how neighborhood characteristics can impact rates of VDB.

Place-Based Climate-Proofing of Commercial and Industrial Areas: Inventory and Guidelines From a Regional Planning Perspective

In spite of all efforts to reduce greenhouse gases, climate change has become a new reality that requires regional planning to provide effective solutions. This article focuses on commercial and industrial areas (&lt;em&gt;Gewerbegebiete&lt;/em&gt;), which are important but often overlooked spaces, by means of examples in the Berlin-Brandenburg region. The article investigates whether and how regional planning can help these areas adapt to climate change. Three commercial and industrial areas in different spatial settings are examined, using an inventory of place-based measures, general standards, and regional networking of planning actors. This inventory is based on a backcasting analysis that compares normative future images of climate-adapted commercial and industrial areas with their current local situation. Spatially differentiated guidelines for the adaptation of commercial and industrial areas are then developed from a regional planning perspective by “climate-proofing” regional plans. These guidelines provide both place-based and general solutions for integrating and governing climate adaptation measures and standards into existing frameworks using a hands-on regional planning approach.

Redlining-associated methylation in breast tumors: the impact of contemporary structural racism on the tumor epigenome.

Place-based measures of structural racism have been associated with breast cancer mortality, which may be driven, in part, by epigenetic perturbations. We examined the association between contemporary redlining, a measure of structural racism at the neighborhood level, and DNA methylation in breast tumor tissue. We identified 80 Black and White women diagnosed and treated for a first-primary breast cancer at Emory University Hospitals (2008-2017). Contemporary redlining was derived for census tracts using the Home Mortgage Disclosure Act database. Linear regression models were used to calculate the association between contemporary redlining and methylation in breast tumor tissue. We also examined epigenetic age acceleration for two different metrics, regressing β values for each cytosine-phosphate-guanine dinucleotide (CpG) site on redlining while adjusting for covariates. We employed multivariable Cox-proportional hazards models and 95% confidence intervals (CI) to estimate the association between aberrant methylation and mortality. Contemporary redlining was associated with 5 CpG sites after adjustment for multiple comparisons (FDR<0.10). All genes were implicated in breast carcinogenesis, including genes related to inflammation, immune function and stress response (ANGPT1, PRG4 and PRG4). Further exploration of the top 25 CpG sites, identified interaction of 2 sites (MRPS28 and cg11092048) by ER status and 1 site (GDP1) was associated with all-cause mortality. Contemporary redlining was associated with epigenetic age acceleration by the Hannum metric (β=5.35; CI 95%=0.30,10.4) and showed positive but non-significant correlation with the other clock. We identified novel associations between neighborhood contemporary redlining and the breast tumor DNA methylome, suggesting that racist policies leading to inequitable social and environmental exposures, may impact the breast tumor epigenome. Additional research on the potential implications for prognosis is needed.

Traveling Together: A Road Map for Researching Neighborhood Effects on Population Health and Health Inequities.

As evidence of the relationship between place and health mounts, more epidemiologists and clinical science researchers are becoming interested in incorporating place-based measures and analyses into their examination of population health and health inequities. Given the extensive literature on place and health, it can be challenging for researchers new to this area to develop neighborhood-effects research questions and apply the appropriate measures and methods. This paper provides a road map for guiding health researchers through the conceptual and methodological stages of incorporating various dimensions of place into their quantitative health research. Synthesizing across reviews, commentaries, and empirical investigations, the road map consists of 4 broad stages for considering place and health: 1) why?: articulating the motivation for assessing place and health and grounding the motivation in theory; 2) what?: identifying the relevant place-based characteristics and specifying their link to health to build a conceptual framework; 3) how?: determining how to operationalize the conceptual framework by defining, measuring, and assessing place-based characteristics and quantifying their effect on health; and 4) now what?: discussing the implications of neighborhood research findings for future research, policy, and practice. This road map supports efforts to develop conceptually and analytically rigorous neighborhood research projects.

The associations between place-based measures of walkability and physical activity across a range of diverse streetscapes

Walkability relates to aspects of a physical environment that have the potential to influence walking in that environment. In 2019, the Environmental Protection Agency developed the National Walkability Index (NWI), an easily accessible, U.S. Census block-group-level indicator of walkability. Although the NWI could be the metric of choice for researchers and urban planners, there is a lack of empirical evidence for its validity. The current study examined the validity of the NWI and Walk Score for predicting physical activity (PA) occurring along urban streetscapes. A wearable video device (Gogloo E7 SMART eyewear) was used to capture videos of streetscapes in 24 U.S. Census block groups in three different sized cities. The block groups varied in walkability, income level, and minority composition. The videos, collected over 10 months during 2019 at different times on weekdays and weekends, were reviewed by experts to obtain counts of walkers/h and individuals performing leisure PA/h (dependent variables). The independent variables were the NWI, its components - transit stop proximity, intersection density, employment/household occupancy mix, and employment mix, and Walk Score. Block group was the level of analysis. Linear regression indicated Walk Score, employment/household occupancy mix, and employment mix were associated with walkers/h (p < .001) while only employment/household occupancy mix, and employment mix were associated with leisure PA/h (p < .001). The NWI did not account for a significant portion of the variance in PA outcomes. A place-based examination of PA and walkability indexes favors the use of Walk Score and a modified version of the NWI.

Abstract C093: Historical redlining is associated with breast cancer subtype, stage at diagnosis and mortality

Abstract Background: Structurally racist policies have an important impact on health. The etiologic basis of racial disparities in aggressive forms of breast cancer is not well understood. Few studies have investigated the impact of structural racism as a potential driver of etiologic heterogeneity. We sought to estimate the effect of historic redlining on the development of aggressive subtypes and late-stage disease, and examine its role in breast cancer mortality. Methods: Using the Georgia Cancer Registry, we identified 921 non-Hispanic White (NHW) and 878 non-Hispanic Black (NHB) women residing in a Georgia Home Owners' Loan Corporation (HOLC) graded area with a first primary invasive breast cancer diagnosis in 2010–2017. Historic redlining scores for 2010 census tracts were calculated according to the proportion of HOLC grades within the tract. Historic redlining scores were examined continuously and dichotomized at &amp;lt;2.5, which represents areas that were historically considered low for investment risk (Green/“Best” or Blue/“Still Desirable”), vs. ≥2.5, which represents areas that were considered to be high risk (Yellow/“Definitely Declining” or Red/“Hazardous”). We used age-adjusted logistic regression to calculate case-only odds ratios (ORs) and 95% confidence intervals (CIs) associating historically high-risk redlined areas to a diagnosis of Luminal B, HER2, or Triple-Negative breast cancer (TNBC) compared with Luminal A tumors and a diagnosis of Stage II, III, or Stage IV breast cancer compared with Stage I disease. Additionally, we used Cox proportional hazards regression to calculate age-adjusted hazard ratios (HRs) and 95% CIs to associate historically high-risk areas with breast cancer mortality, overall and within each race strata. Results: Overall, 81% of NHB and 19% of NHW women lived in historically redlined census tracts. Women living in redlined areas were diagnosed with more aggressive subtypes (TNBC and HER2) and later stage (Stage III and IV) breast cancers. Compared with Luminal A breast cancer, the ORs for living in historically high-risk vs. low risk investment areas were 2.05 (95%CI=1.44, 2.93) for TNBC and1.49 (95%CI=0.89, 2.48) for HER2 disease. Compared with Stage I breast cancers, the ORs for historically high-risk vs. low risk investment areas were 1.85(95%CI=1.30, 2.63) for Stage III and 2.00 (95%CI=1.32, 3.02) for Stage IV breast cancer. Residing in historically high-risk census tracts was associated with a 1.68-fold increase in breast cancer mortality (95% CI=1.23, 2.30), after adjusting for age. The association was most pronounced among NHW women living in redlined census tracts (HR=1.36; 95%CI=0.99, 1.87); a near-null association was observed among NHB women (HR=0.97; 95% CI=0.78, 1.20). Conclusions: Historic redlining scores were associated with the diagnosis of more aggressive forms of breast cancer and breast cancer mortality. Historic place-based measures of structural racist policies have modern-day implications on health outcomes and may underpin reported disparities in aggressive or advanced tumor types. Citation Format: Jasmine M. Miller-Kleinhenz, Maret L. Maliniak, Micah J. Streiff, Leah Moubadder, Lauren E. Barber, Rebecca Nash, Lindsay J. Collin, Jeffrey M. Switchenko, Kevin C. Ward, Lauren E. McCullough. Historical redlining is associated with breast cancer subtype, stage at diagnosis and mortality [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C093.

Aboveground biomass of marshes in Northeast China: Spatial pattern and annual changes responding to climate change

Examining vegetation aboveground biomass (AGB) changes is important to understanding wetland carbon sequestration. Here, we combined the field-measured AGB data (458 samples) from 2009 to 2021, moderate resolution imaging spectroradiometer reflectance products, and climatic data to reveal the AGB variations of marshes in Northeast China by comparing various models driven by different indicators. The results indicated that random forest model driven by six vegetation indices, land surface temperature, and land surface water index achieved accurate marsh AGB estimation with R2 being 0.78 and relative error being 16.71%. The mean marsh AGB in Northeast China from 2000 to 2021 was 682.89 ± 31.69 g·m−2, which generally increased from north to south in space. Temporally, annual marsh AGB declined slowly at a rate of 3.45 g·m−2·year−1 during the past 21 years driven mainly by the decrease in summer mean temperature that was characterized by a significantly positive correlation between them. Nevertheless, we highlighted that the temporal changes of marsh AGB spatially varied in response to inconsistent climate change, thus place-based measures are required for sustainable management of marshes.

Calculating place-based transit accessibility: Methods, tools and algorithmic dependence

To capture the complex relationships between transportation and land use, researchers and practitioners are increasingly using place-based measures of transportation accessibility to support a broad range of planning goals. This research reviews the state-of-the-art in applied transportation accessibility measurement and performs a comparative evaluation of software tools for calculating accessibility by walking and public transit including ArcGIS Pro, Emme, R5R, and OpenTripPlanner using R and Python, among others. Using a case study of Toronto, we specify both origin-based and regional-scale analysis scenarios and find significant differences in computation time and calculated accessibilities. While the calculated travel time matrices are highly correlated across tools, each tool produces different results for the same origin-destination pair. Comparisons of the estimated accessibilities also reveal evidence of spatial clustering in the ways paths are calculated by some tools relative to others at different locations around the city. With the growing emphasis on accessibility-based planning, analysts should approach the calculation of accessibility with care and recognize the potential for algorithmic dependence in their calculated accessibility results.

An institutional periphery in discussion. Rethinking the inner areas in Italy

Geographic peripheries in Italy are defined by the government in an institutional document as areas affected by increasing depopulation, high rates of demographic ageing, geographic marginality, and various degrees and forms of inequalities in the provision of services and infrastructure. These so-called ‘inner areas’ are identified based on the level of accessibility to three citizenship rights (mobility, education, and health) and characterized by nonuniform socio-economic and infrastructure conditions, a heterogeneity that raises questions about the criteria used for their definition. This paper therefore proposes an alternative approach to describe the features of marginality related to mobility, demographic, and socio-economic conditions in Italy, discussing the institutional classification of the inner areas. Based on the literature review, we select a set of indicators to identify different geographies of marginality. Combining them in a cluster analysis, we identify the most disadvantaged territories in terms of mobility, demographics, and economics, highlighting different forms of marginality that challenge territorial cohesion policies and address more selective and place-based measures.

Equitable allocation of COVID-19 vaccines in the United States.

Many vaccine rationing guidelines urge planners to recognize, and ideally reduce, inequities. In the United States, allocation frameworks are determined by each of the Centers for Disease Control and Prevention's 64 jurisdictions (50 states, the District of Columbia, five cities and eight territories). In this study, we analyzed vaccine allocation plans published by 8 November 2020, tracking updates through to 30 March 2021. We evaluated whether jurisdictions adopted proposals to reduce inequity using disadvantage indices and related place-based measures. By 30 March 2021, 14 jurisdictions had prioritized specific zip codes in combination with metrics such as COVID-19 incidence, and 37 jurisdictions (including 34 states) had adopted disadvantage indices, compared to 19 jurisdictions in November 2020. Uptake of indices doubled from 7 to 14 among the jurisdictions with the largest shares of disadvantaged communities. Five applications were distinguished: (1) prioritizing disadvantaged groups through increased shares of vaccines or vaccination appointments; (2) defining priority groups or areas; (3) tailoring outreach and communication; (4) planning the location of dispensing sites; and (5) monitoring receipt. To ensure that equity features centrally in allocation plans, policymakers at the federal, state and local levels should universalize the uptake of disadvantage indices and related place-based measures.

Assessing the dynamics of sustainability for social-ecological systems based on the adaptive cycle framework: A case study in the Beijing-Tianjin-Hebei urban agglomeration

Evaluating the dynamics of sustainability for social-ecological systems (SESs) is fundamental for guaranteeing human well-being and achieving sustainable development goals (SDGs). Here, we develop a method to quantify and analyze the dynamics of sustainability for SESs based on the adaptive cycle framework and catastrophe theory. This method can effectively identify the important time points and areas that affect the dynamics of sustainability and is flexible for assessing various SESs. We applied this method to a typical SES, the Beijing-Tianjin-Hebei urban agglomeration (BTHUA). The results showed that the BTHUA experienced an overall rise in sustainability from 2000 to 2017. It has exhibited two adaptive cycles, among which 2006 and 2012 marked the release phases (i.e., the decrease in sustainability). The decline in the environmental subsystem and the increase in pollution from resource-based cities were major factors affecting the dynamics of sustainability in the BTHUA. Therefore, implementing place-based measures is encouraged to promote the sustainability of this urban agglomeration.

Neighborhood-Level Redlining and Lending Bias Are Associated with Breast Cancer Mortality in a Large and Diverse Metropolitan Area.

Structural inequities have important implications for the health of marginalized groups. Neighborhood-level redlining and lending bias represent state-sponsored systems of segregation, potential drivers of adverse health outcomes. We sought to estimate the effect of redlining and lending bias on breast cancer mortality and explore differences by race. Using Georgia Cancer Registry data, we included 4,943 non-Hispanic White (NHW) and 3,580 non-Hispanic Black (NHB) women with a first primary invasive breast cancer diagnosis in metro-Atlanta (2010-2014). Redlining and lending bias were derived for census tracts using the Home Mortgage Disclosure Act database. We calculated hazard ratios and 95% confidence intervals (CI) for the associations of redlining, lending bias on breast cancer mortality and estimated race-stratified associations. Overall, 20% of NHW and 80% of NHB women lived in redlined census tracts, and 60% of NHW and 26% of NHB women lived in census tracts with pronounced lending bias. Living in redlined census tracts was associated with a nearly 1.60-fold increase in breast cancer mortality (hazard ratio = 1.58; 95% CI, 1.37-1.82) while residing in areas with substantial lending bias reduced the hazard of breast cancer mortality (hazard ratio = 0.86; 95% CI, 0.75-0.99). Among NHB women living in redlined census tracts, we observed a slight increase in breast cancer mortality (hazard ratio = 1.13; 95% CI, 0.90-1.42); among NHW women the association was more pronounced (hazard ratio = 1.39; 95% CI, 1.09-1.78). These findings underscore the role of ecologic measures of structural racism on cancer outcomes. Place-based measures are important contributors to health outcomes, an important unexplored area that offers potential interventions to address disparities.

Social Vulnerability, Disadvantage, and COVID-19 Vaccine Rationing: A Review Characterizing the Construction of Disadvantage Indices Deployed To Promote Equitable Allocation of Resources in the United States

When planners began developing COVID-19 vaccine rationing frameworks in 2020, an additional major challenge arose, as the spread of the virus was exacerbated by major health disparities. In an unprecedented, novel turn, planners added statistical place-based measures of deprivation, known as disadvantage indices, to traditional sequential allocation frameworks. To better understand the construction of these indices and their role in equitable allocation, we reviewed the most commonly used indices with publicly available documentation.We characterized four indices: Area Deprivation Index (ADI), COVID-19 Community Vulnerability Index (CCVI), Healthy Places Index (HPI), and Social Vulnerability Index (SVI).Seventy-eight total variables from the following nine domains were used to construct these indices: population demographics, poverty, education and employment, minority populations, housing, and transportation, high-risk transmission environments, health, healthcare system, and environmental and neighborhood.Geographic units that the indices were applied to range from the block group to census tract, zip code, and county level. U.S. Census Bureau’s American Community Survey was the primary source of data, but indices varied greatly on variables and geography used, weighting schemes, and reporting units.While all indices have comparable goals, their designs differed considerably. Given the clear potential to promote equity in the pandemic setting and, plausibly, outside of it, further analyses should systematically elicit the tradeoffs associated with using different types of indices.

The long-run effects of the 1930s HOLC “redlining” maps on place-based measures of economic opportunity and socioeconomic success

We estimate the long-run effects of the 1930s Home Owners Loan Corporation (HOLC) redlining maps on census tract-level measures of socioeconomic status and economic opportunity from the Opportunity Atlas (Chetty et al., 2018). We use two identification strategies to identify the long-run effects of differential access to credit along HOLC boundaries. The first compares cross-boundary differences along actual HOLC boundaries to a comparison group of boundaries that had similar pre-existing differences as the actual boundaries. A second approach uses a statistical model to identify boundaries that were least likely to have been chosen by the HOLC. We find that the maps had large and statistically significant causal effects on a wide variety of outcomes measured at the census tract level for cohorts born in the late 1970s and early 1980s.

Socioeconomic variations and disparity in space–time accessibility in suburban China: A case study of Guangzhou

The concept of conventional place-based accessibility, despite being well researched, tends to ignore people’s space–time constraints arising from mandatory activities (e.g. work and household duties), which confine people’s potential movement and delimit the accessible opportunities. As people with different socioeconomic statuses may have different space–time constraints even while living in similar locations, using the place-based measures could lead to an underestimation of accessibility inequality. This study applies a space–time measure to unravel the disparities in service accessibility in suburban China. Since the late 1970s, suburbanisation in Chinese cities has fostered income inequality and has elevated other dimensions (e.g. institutional status and gender) of disparity within each income class. Within this context, we conduct a case study of suburban neighbourhoods in Guangzhou, based on the activity diary data derived from a home-based questionnaire survey. Findings indicate that the use of a space–time measure effectively captures the disparities in service accessibility among residents in suburban Guangzhou. On the basis of structural equation modelling, we further identify that certain socioeconomic groups (e.g. high-income residents, public sector workers, local hukou holders, male household heads and welfare housing residents) tend to experience fewer space–time constraints from rigid activities, such as work, commuting and household duties, and are thus more advantaged in accessing service facilities. These findings imply that urban planning should address the space–time perspective to promote equal service access for the highly heterogeneous social groups in suburban China and to incorporate time-sensitive policies (e.g. flexitime policies).

The Long-Run Effects of the 1930s HOLC 'Redlining' Maps on Place-Based Measures of Economic Opportunity and Socioeconomic Success

We estimate the long-run effects of the 1930s Home Owners Loan Corporation (HOLC) redlining maps on census tract-level measures of socioeconomic status and economic opportunity from the Opportunity Atlas (Chetty et al. 2018). We use two identification strategies to identify the long-run effects of differential access to credit along HOLC boundaries. The first compares cross-boundary differences along actual HOLC boundaries to a comparison group of boundaries that had similar pre-existing differences as the actual boundaries. A second approach uses a statistical model to identify boundaries that were least likely to have been chosen by the HOLC. We find that the maps had large and statistically significant causal effects on a wide variety of outcomes measured at the census tract level for cohorts born in the late 1970s and early 1980s.

Counting early deaths due to socioeconomic inequality

Counting early deaths due to socioeconomic inequality

Adding a Vital Sign: Considering the Utility of Place-Based Measures in Health Care Settings.

During rounds, you prepare to enter the room of a child who was hospitalized overnight for an asthma exacerbation. You review the chart, taking careful notice of the documented history and the physical examination. You also quickly glance at the child’s zip code. This may not be a routine aspect of your care, but this particular zip code stands out. You know that it includes blocks with dilapidated housing conditions, limited access to pharmacies, and unreliable bus routes. You wonder whether this is the reality faced by your patient. This prompts you to more deeply consider your management plans for this child’s hospitalization and for their eventual transition to home. How could or should you think about this child’s zip code in relation to their medical and social needs? Is it a proxy for their own risks or a reflection of their surroundings? Or is it both? With studies in which measures of a child’s neighborhood are linked to adverse postdischarge outcomes1 and to patient-level social and financial risks themselves,2 it is becoming increasingly relevant to consider how to interpret and then use such measures during clinical care. As hospitalists grapple with such scenarios and questions, they may begin by considering the extent to which place-based measures, or “geomarkers,”3 may or may not serve as proxies for patient-level social, economic, and environmental risks. Geomarkers can approximate risks related to critical social determinants of health (SDH) that are known to be associated with poor health outcomes for conditions like pediatric asthma (eg, readmission).2,4,5 Still, such place-based measures are not commonly used during clinical encounters. This is despite …

An information theory approach to hypothesis testing in criminological research

BackgroundThis research demonstrates how the Akaike information criterion (AIC) can be an alternative to null hypothesis significance testing in selecting best fitting models. It presents an example to illustrate how AIC can be used in this way.MethodsUsing data from Milwaukee, Wisconsin, we test models of place-based predictor variables on street robbery and commercial robbery. We build models to balance explanatory power and parsimony. Measures include the presence of different kinds of businesses, together with selected age groups and social disadvantage.ResultsModels including place-based measures of land use emerged as the best models among the set of tested models. These were superior to models that included measures of age and socioeconomic status. The best models for commercial and street robbery include three measures of ordinary businesses, liquor stores, and spatial lag.ConclusionsModels based on information theory offer a useful alternative to significance testing when a strong theoretical framework guides the selection of model sets. Theoretically relevant ‘ordinary businesses’ have a greater influence on robbery than socioeconomic variables and most measures of discretionary businesses.