We investigated historical redlining, a government-sanctioned discriminatory policy, in relation to cardiovascular health (CVH) and whether associations were modified by present-day neighborhood physical and social environments. Data included 4,779 participants (mean age 62 y; SD = 10) from the baseline sample of the Multi-Ethnic Study of Atherosclerosis (MESA; 2000 to 2002). Ideal CVH was a summary measure of ideal levels of seven CVH risk factors based on established criteria (blood pressure, fasting glucose, cholesterol, body mass index, diet, physical activity, and smoking). We assigned MESA participants' neighborhoods to one of four grades (A: best, B: still desirable, C: declining, and D: hazardous) using the 1930s federal Home Owners' Loan Corporation (HOLC) maps, which guided decisions regarding mortgage financing. Two-level hierarchical linear and logistic models, with a random intercept to account for participants nested within neighborhoods (i.e., census tracts) were used to assess associations within racial/ethnic subgroups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Chinese). We found that Black adults who lived in historically redlined areas had a 0.82 (95% CI -1.54, -0.10) lower CVH score compared to those residing in grade A (best) neighborhoods, in a given neighborhood and adjusting for confounders. We also found that as the current neighborhood social environment improved the association between HOLC score and ideal CVH weakened (P < 0.10). There were no associations between HOLC grade and CVH measures or effect modification by current neighborhood conditions for any other racial/ethnic group. Results suggest that historical redlining has an enduring impact on cardiovascular risk among Black adults in the United States.

Introduction

Research examining the influence of neighborhood healthy food environment on diet has been mostly cross-sectional and has lacked robust characterization of the food environment. We examined longitudinal associations between features of the local food environment and healthy diet, and whether associations were modified by race/ethnicity.

Methods

Data on 3634 adults aged 45-84 followed for 10 years were obtained from the Multi-Ethnic Study of Atherosclerosis. Diet quality was assessed using the Alternative Healthy Eating Index at Exam 1 (2000-2002) and Exam 5 (2010-2012). We assessed four measures of the local food environment using survey-based measures (e.g. perceptions of healthier food availability) and geographic information system (GIS)-based measures (e.g. distance to and density of healthier food stores) at Exam 1 and Exam 5. Random effects models adjusted for age, sex, education, moving status, per capita adjusted income, and neighborhood socioeconomic status, and used interaction terms to assess effect measure modification by race/ethnicity.

Results

Net of confounders, one standard z-score higher average composite local food environment was associated with higher average AHEI diet score (β=1.39, 95% CI: 1.05, 1.73) over the follow-up period from Exam 1 to 5. This pattern of association was consistent across both GIS-based and survey-based measures of local food environment and was more pronounced among minoritized racial/ethnic groups. There was no association between changes in neighborhood environment and change in AHEI score, or effect measure modification by race/ethnicity.

Conclusion

Our findings suggest that neighborhood-level food environment is associated with better diet quality, especially among racially/ethnically minoritized populations.

Preliminary evidence suggests that the experience of the novel coronavirus is not shared equally across geographic areas. Findings in the United States suggest that the burden of COVID-19 morbidity and mortality may be hardest felt in disadvantaged and racially segregated places. Deprived neighborhoods are disproportionately populated by people of color, the same populations that are becoming sicker and dying more often from COVID-19. This commentary examines how structurally vulnerable neighborhoods contribute to racial/ethnic inequities in SARS-COV-2 exposure and COVID-19 morbidity and mortality and considers opportunities to intervene through place-based initiatives and the implementation of a Health in All Policies strategy.

Recent archaeological discoveries suggest that both archaic Denisovans and Homo sapiens occupied the Tibetan Plateau earlier than expected. Genetic studies show that a pulse of Denisovan introgression was involved in the adaptation of Tibetan populations to high-altitude hypoxia. These findings challenge the traditional view that the plateau was one of the last places on earth colonized by H. sapiens and warrant a reappraisal of the population history of this highland. Here, we integrate archaeological and genomic evidence relevant to human dispersal, settlement, and adaptation in the region. We propose two testable models to address the peopling of the plateau in the broader context of H. sapiens dispersal and their encounters with Denisovans in Asia.

Gentrification, a racialized and profit-driven process in which historically disinvested neighborhoods experience an influx of development that contributes to the improvement of physical amenities, increasing housing costs, and the dispossession and displacement of existing communities, may influence the risk of severe maternal morbidity (SMM). Leveraging a racially diverse population-based sample of all live hospital births in California between 2006 and 2017, we examined associations between neighborhood-level gentrification and SMM. SMM was defined as having one of 21 procedures and diagnoses, as described in the SMM index developed by Centers for Disease Control and Prevention. We compared three gentrification measures to determine which operationalization best captures aspects of gentrification most salient to SMM: Freeman, Landis 3-D, and Urban Displacement Project Gentrification and Displacement Typology. Descriptive analysis assessed bivariate associations between gentrification and birthing peoples characteristics. Overall and race and ethnicity-stratified mixed-effects logistic models assessed associations between gentrification and SMM, adjusting for individual sociodemographic and pregnancy factors while accounting for clustering by census tract. The study sample included 5,256,905 births, with 72,718 cases of SMM (1.4%). The percentage of individuals living in a gentrifying neighborhood ranged from 5.7% to 11.7% across exposure assessment methods. Net of individual and pregnancy-related factors, neighborhood-level gentrification, as measured by the Freeman method, was protective against SMM (OR = 0.89, 95% CI: 0.86-0.93); in comparison, gentrification, as measured by the Gentrification and Displacement Typology, was associated with greater risk of SMM (OR = 1.18, 95% CI: 1.14-1.23). These associations were significant among non-Hispanic White, non-Hispanic Black, and Hispanic individuals. Findings demonstrate that gentrification plays a role in shaping the risk of SMM among birthing people in California. Differences in how gentrification is conceptualized and measured, such as an emphasis on housing affordability compared to a broader characterization of gentrifications multiple aspects, may explain the heterogeneity in the directions of observed associations.

Neighborhood environments significantly influence the development of diabetes risk factors, morbidity, and mortality throughout an individuals life. The social, economic, and physical environments of a neighborhood all affect the health risks of individuals and communities and also affect population health inequities. Factors such as access to healthy food, green spaces, safe housing, and transportation options can impact the health outcomes of residents. Social factors, including social cohesion and neighborhood safety, also play an important role in shaping neighborhood environments and can influence the development of diabetes. Therefore, understanding the complex relationships between neighborhood environments and diabetes is crucial for developing effective strategies to address health disparities and promote health equity. This review presents landmark findings from studies that examined associations between neighborhood socioeconomic, built and physical, and social environmental factors and diabetes-related risk and outcomes. Our framework emphasizes the historical context and structural and institutional racism as the key drivers of neighborhood environments that ultimately shape diabetes risk and outcomes. To address health inequities in diabetes, we propose future research areas that incorporate health equity principles and place-based interventions.

BACKGROUND: Historical mortgage redlining, a racially discriminatory policy designed to uphold structural racism, may have played a role in producing the persistently elevated rate of severe maternal morbidity (SMM) among racialised birthing people. OBJECTIVE: This study examined associations between Home-Owner Loan Corporation (HOLC) redlining grades and SMM in a racially and ethnically diverse birth cohort in California. METHODS: We leveraged a population-based cohort of all live hospital births at ≥20 weeks of gestation between 1997 and 2017 in California. SMM was defined as having one of 21 procedures and diagnoses, per an index developed by Centers for Disease Control and Prevention. We characterised census tract-level redlining using HOLCs security maps for eight California cities. We assessed bivariate associations between HOLC grades and participant characteristics. Race and ethnicity-stratified mixed effects logistic regression models assessed the risk of SMM associated with HOLC grades within non-Hispanic Black, Asian/Pacific Islander, American Indian/Alaskan Native and Hispanic groups, adjusting for sociodemographic information, pregnancy-related factors, co-morbidities and neighbourhood deprivation index. RESULTS: The study sample included 2,020,194 births, with 24,579 cases of SMM (1.2%). Living in a census tract that was graded as Hazardous, compared to census tracts graded Best and Still Desirable, was associated with 1.15 (95% confidence interval [CI] 1.03, 1.29) and 1.17 (95% CI 1.09, 1.25) times the risk of SMM among Black and Hispanic birthing people, respectively, independent of sociodemographic factors. These associations persisted after adjusting for pregnancy-related factors and neighbourhood deprivation index. CONCLUSIONS: Historical redlining, a tool of structural racism that influenced the trajectory of neighbourhood social and material conditions, is associated with increased risk of experiencing SMM among Black and Hispanic birthing people in California. These findings demonstrate that addressing the enduring impact of macro-level and systemic mechanisms that uphold structural racism is a vital step in achieving racial and ethnic equity in birthing peoples health.

BACKGROUND: Social determinants of health, including neighborhood context, may be a key driver of severe maternal morbidity and its related racial and ethnic inequities; however, investigations remain limited. OBJECTIVE: This study aimed to examine the associations between neighborhood socioeconomic characteristics and severe maternal morbidity, as well as whether the associations between neighborhood socioeconomic characteristics and severe maternal morbidity were modified by race and ethnicity. STUDY DESIGN: This study leveraged a California statewide data resource on all hospital births at ≥20 weeks of gestation (1997-2018). Severe maternal morbidity was defined as having at least 1 of 21 diagnoses and procedures (eg, blood transfusion or hysterectomy) as outlined by the Centers for Disease Control and Prevention. Neighborhoods were defined as residential census tracts (n=8022; an average of 1295 births per neighborhood), and the neighborhood deprivation index was a summary measure of 8 census indicators (eg, percentage of poverty, unemployment, and public assistance). Mixed-effects logistic regression models (individuals nested within neighborhoods) were used to compare odds of severe maternal morbidity across quartiles (quartile 1 [the least deprived] to quartile 4 [the most deprived]) of the neighborhood deprivation index before and after adjustments for maternal sociodemographic and pregnancy-related factors and comorbidities. Moreover, cross-product terms were created to determine whether associations were modified by race and ethnicity. RESULTS: Of 10,384,976 births, the prevalence of severe maternal morbidity was 1.2% (N=120,487). In fully adjusted mixed-effects models, the odds of severe maternal morbidity increased with increasing neighborhood deprivation index (odds ratios: quartile 1, reference; quartile 4, 1.23 [95% confidence interval, 1.20-1.26]; quartile 3, 1.13 [95% confidence interval, 1.10-1.16]; quartile 2, 1.06 [95% confidence interval, 1.03-1.08]). The associations were modified by race and ethnicity such that associations (quartile 4 vs quartile 1) were the strongest among individuals in the other racial and ethnic category (1.39; 95% confidence interval, 1.03-1.86) and the weakest among Black individuals (1.07; 95% confidence interval, 0.98-1.16). CONCLUSION: Study findings suggest that neighborhood deprivation contributes to an increased risk of severe maternal morbidity. Future research should examine which aspects of neighborhood environments matter most across racial and ethnic groups.

Background Residential segregation, a geospatial manifestation of structural racism, is a fundamental driver of racial and ethnic health inequities, and longitudinal studies examining segregation's influence on cardiovascular health are limited. This study investigates the impact of segregation on hypertension in a multiracial and multiethnic cohort and explores whether neighborhood environment modifies this association. Methods and Results Leveraging data from a diverse cohort of adults recruited from 6 sites in the United States with 2 decades of follow-up, we used race- and ethnicity-stratified Cox models to examine the association between time-varying segregation with incident hypertension in 1937 adults free of hypertension at baseline. Participants were categorized as residing in segregated and nonsegregated neighborhoods using a spatial-weighted measure. We used a robust covariance matrix estimator to account for clustering within neighborhoods and assessed effect measure modification by neighborhood social or physical environment. Over an average follow-up of 7.35 years, 65.5% non-Hispanic Black, 48.1% Chinese, and 53.7% Hispanic participants developed hypertension. Net of confounders, Black and Hispanic residents in segregated neighborhoods were more likely to develop hypertension relative to residents in nonsegregated neighborhoods (Black residents: hazard ratio [HR], 1.33; 95% CI, 1.09-1.62; Hispanic residents: HR, 1.33; 95% CI, 1.04-1.70). Results were similar but not significant among Chinese residents (HR, 1.20; 95% CI, 0.83-1.73). Among Black residents, neighborhood social environment significantly modified this association such that better social environment was associated with less pronounced impact of segregation on hypertension. Conclusions This study underscores the importance of continued investigations of groups affected by the health consequences of racial residential segregation while taking contextual neighborhood factors, such as social environment, into account.

Gentrification may play an important role in influencing health outcomes, but few studies have examined these associations. One major barrier to producing empirical evidence to establish this link is that there is little consensus on how to measure gentrification. To address this barrier, we compared three gentrification classification methodologies in relation to their ability to identify neighborhood gentrification in nine San Francisco Bay Area counties: the Freeman method, the Landis method, and the Urban Displacement Project (UDP) Regional Early Warning System. In the 1580 census tracts, 43% of the population had a bachelor's degree or higher. The average median household income was $79,671 in 2013. A comparison of gentrification methodologies revealed that the Landis and Freeman methodologies characterized the vast majority of census tracts as stable, and only 5.2% and 6.1% of tracts as gentrifying. UDP characterized 46.7% of tracts at risk, undergoing, or experiencing advanced stages of gentrification and displacement. There was substantial variation in the geographic location of tracts identified as gentrifying across methods. Given the variation in characterizations of gentrification across measures, studies evaluating associations between gentrification and health should consider using multiple measures of gentrification to examine the robustness of the study findings across measures.