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Summary: Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP, taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from five ancestry groups. In the combined meta-analyses of stages 1 and 2, we identified 59 loci (p value < 5e−8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (PLCL2), synaptic function and neurotransmission (LIN7A and PFIA2), as well as genes previously implicated in neuropsychiatric or stress-related disorders (FSTL5 and CHODL). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.

Cross-impact balance (CIB) analysis leverages expert knowledge pertaining to the nature and strength of relationships between components of a system to identify the most plausible future ‘scenarios’ of the system. These scenarios, also referred to as ‘storylines’, provide qualitative insights into how the state of one factor can either promote or restrict the future state of one or multiple other factors in the system. This paper presents a novel, visually oriented questionnaire developed to elicit expert knowledge about the relationships between key factors in a system, for the purpose of CIB analysis. The questionnaire requires experts to make selections from a series of standardized cause-effect graphical profiles that depict a range of linear and non-linear relationships between factor pairs. The questionnaire and the process of translating the graphical selections into data that can be used for CIB analysis is described using an applied example which focuses on urban health in Latin American cities. • A questionnaire featuring a set of standardized cause-effect profiles was developed. • Cause-effect profiles were used to elicit information about the strength of linear and non-linear bivariate relationships. • The questionnaire represents an intuitive visual means for collecting data required for the conduct of CIB analysis.

The built environment of cities is complex and influences social and environmental determinants of health. In this study we, 1) identified city profiles based on the built landscape and street design characteristics of cities in Latin America and 2) evaluated the associations of city profiles with social determinants of health and air pollution. Landscape and street design profiles of 370 cities were identified using finite mixture modeling. For landscape, we measured fragmentation, isolation, and shape. For street design, we measured street connectivity, street length, and directness. We fitted a two-level linear mixed model to assess the association of social and environmental determinants of health with the profiles. We identified four profiles for landscape and four for the street design domain. The most common landscape profile was the “proximate stones” characterized by moderate fragmentation, isolation and patch size, and irregular shape. The most common street design profile was the “semi-hyperbolic grid” characterized by moderate connectivity, street length, and directness. The “semi-hyperbolic grid”, “spiderweb” and “hyperbolic grid” profiles were positively associated with higher access to piped water and less overcrowding. The “semi-hyperbolic grid” and “spiderweb” profiles were associated with higher air pollution. The “proximate stones” and “proximate inkblots” profiles were associated with higher congestion. In conclusion, there is substantial heterogeneity in the urban landscape and street design profiles of Latin American cities. While we did not find a specific built environment profile that was consistently associated with lower air pollution and better social conditions, the different configurations of the built environments of cities should be considered when planning healthy and sustainable cities in Latin America.

Pollen from trees, grasses, and weeds can trigger asthma exacerbation in sensitized individuals. However, there are gaps in knowledge about the effects, such as the relative risks from different plant taxa and threshold levels of effect. We aimed to describe the local association between pollen and asthma exacerbation among children in the City of Philadelphia, and to evaluate whether effects are modified by children’s characteristics and clinical factors (e.g., child’s age, race/ethnicity, comorbidities). We conducted a time-stratified case-crossover study of pediatric (age

Background: Cable cars provide urban mobility benefits for vulnerable populations. However, no evaluation has assessed cable cars' impact from a health perspective. TransMiCable in Bogotá, Colombia, provides a unique opportunity to (1) assess the effects of its implementation on the environmental and social determinants of health (microenvironment pollution, transport accessibility, physical environment, employment, social capital, and leisure time), physical activity, and health outcomes (health-related quality of life, respiratory diseases, and homicides); and (2) use citizen science methods to identify, prioritize, and communicate the most salient negative and positive features impacting health and quality of life in TransMiCable's area, as well as facilitate a consensus and advocacy-building change process among community members, policymakers, and academic researchers.Methods: TrUST (In Spanish: Transformaciones Urbanas y Salud: el caso de TransMiCable en Bogotá) is a quasi-experimental study using a mixed-methods approach. The intervention group includes adults from Ciudad Bolívar, the area of influence of TransMiCable. The control group includes adults from San Cristóbal, an area of future expansion for TransMiCable. A conceptual framework was developed through group-model building. Outcomes related to environmental and social determinants of health as well as health outcomes are assessed using questionnaires (health outcomes, physical activity, and perceptions), secondary data (crime and respiratory outcomes) use of portable devices (air pollution exposure and accelerometry), mobility tracking apps (for transport trajectories), and direct observation (parks). The Stanford Healthy Neighborhood Discovery Tool is being used to capture residents' perceptions of their physical and social environments as part of the citizen science component of the investigation.Discussion: TrUST is innovative in its use of a mixed-methods, and interdisciplinary research approach, and in its systematic engagement of citizens and policymakers throughout the design and evaluation process. This study will help to understand better how to maximize health benefits and minimize unintended negative consequences of TransMiCable.

Abstract Introduction Most interventions aiming to promote leisure-time physical activity (LTPA) at population level showed small or null effects. Approaching the problem from a systems science perspective may shed light on the reasons for these results. We developed an agent-based model to explore how the interactions between psychological attributes and built and social environments may lead to the emergence and evolution of LTPA patterns among adults. Methods The modeling process consisted of four stages: (1) conceptual model development, (2) formulation of the agent-based model, (3) parametrization and calibration, and (4) consistency and sensitivity analyses. The model represents a stylized community containing two types of agents: persons and LTPA sites. Persons interact with each other (proximal network and perceived community) and with the built environment (LTPA sites) over time. Decision-making is based on the person’s intention to practice LTPA, conditioned to the perceived environment. Each iteration is equivalent to one week and we assessed a period of 10 years. Results The model was able to reproduce population temporal trends of intention and LTPA reported in the literature. Sensitivity analyses indicated that population patterns and trends of intention and LTPA were highly influenced by the relationship between a person’s behavior in the preceding week and his current intention, the person’s access to built and social environment, and the density of LTPA sites. Conclusions The proposed agent-based model is suitable to explore the emergence and evolution of LTPA patterns among adults, considering the dynamic interaction between individuals’ psychological attributes and the built and social environments in which they live. The model is available at https://doi.org/10.17605/OSF.IO/J2KAS.

Abstract Background Urbanization and ageing have important implications for public mental health and well-being. Cities pose major challenges for older citizens, but also offer opportunities to develop, test, and implement policies, services, infrastructure, and interventions that promote mental well-being. The MINDMAP project aims to identify the opportunities and challenges posed by urban environmental characteristics for the promotion and management of mental well-being and cognitive function of older individuals. Methods MINDMAP aims to achieve its research objectives by bringing together longitudinal studies from 11 countries covering over 35 cities linked to databases of area-level environmental exposures and social and urban policy indicators. The infrastructure supporting integration of this data will allow multiple MINDMAP investigators to safely and remotely co-analyse individual-level and area-level data. Individual-level data is derived from baseline and follow-up measurements of ten participating cohort studies and provides information on mental well-being outcomes, sociodemographic variables, health behaviour characteristics, social factors, measures of frailty, physical function indicators, and chronic conditions, as well as blood derived clinical biochemistry-based biomarkers and genetic biomarkers. Area-level information on physical environment characteristics (e.g. green spaces, transportation), socioeconomic and sociodemographic characteristics (e.g. neighbourhood income, residential segregation, residential density), and social environment characteristics (e.g. social cohesion, criminality) and national and urban social policies is derived from publically available sources such as geoportals and administrative databases. The linkage, harmonization, and analysis of data from different sources are being carried out using piloted tools to optimize the validity of the research results and transparency of the methodology. Discussion MINDMAP is a novel research collaboration that is combining population-based cohort data with publicly available datasets not typically used for ageing and mental well-being research. Integration of various data sources and observational units into a single platform will help to explain the differences in ageing-related mental and cognitive disorders both within as well as between cities in Europe, the US, Canada, and Russia and to assess the causal pathways and interactions between the urban environment and the individual determinants of mental well-being and cognitive ageing in older adults.

Summary: Background: Latin America is one of the most unequal regions in the world, but evidence is lacking on the magnitude of health inequalities in urban areas of the region. Our objective was to examine inequalities in life expectancy in six large Latin American cities and its association with a measure of area-level socioeconomic status. Methods: In this ecological analysis, we used data from the Salud Urbana en America Latina (SALURBAL) study on six large cities in Latin America (Buenos Aires, Argentina; Belo Horizonte, Brazil; Santiago, Chile; San José, Costa Rica; Mexico City, Mexico; and Panama City, Panama), comprising 266 subcity units, for the period 2011–15 (expect for Panama city, which was for 2012–16). We calculated average life expectancy at birth by sex and subcity unit with life tables using age-specific mortality rates estimated from a Bayesian model, and calculated the difference between the ninth and first decile of life expectancy at birth (P90–P10 gap) across subcity units in cities. We also analysed the association between life expectancy at birth and socioeconomic status at the subcity-unit level, using education as a proxy for socioeconomic status, and whether any geographical patterns existed in cities between subcity units. Findings: We found large spatial differences in average life expectancy at birth in Latin American cities, with the largest P90–P10 gaps observed in Panama City (15·0 years for men and 14·7 years for women), Santiago (8·9 years for men and 17·7 years for women), and Mexico City (10·9 years for men and 9·4 years for women), and the narrowest in Buenos Aires (4·4 years for men and 5·8 years for women), Belo Horizonte (4·0 years for men and 6·5 years for women), and San José (3·9 years for men and 3·0 years for women). Higher area-level socioeconomic status was associated with higher life expectancy, especially in Santiago (change in life expectancy per P90–P10 change unit-level of educational attainment 8·0 years [95% CI 5·8–10·3] for men and 11·8 years [7·1–16·4] for women) and Panama City (7·3 years [2·6–12·1] for men and 9·0 years [2·4–15·5] for women). We saw an increase in life expectancy at birth from east to west in Panama City and from north to south in core Mexico City, and a core-periphery divide in Buenos Aires and Santiago. Whereas for San José the central part of the city had the lowest life expectancy and in Belo Horizonte the central part of the city had the highest life expectancy. Interpretation: Large spatial differences in life expectancy in Latin American cities and their association with social factors highlight the importance of area-based approaches and policies that address social inequalities in improving health in cities of the region. Funding: Wellcome Trust.

Background Current literature examining the prospective relationship between depression and other measures of negative affect with atrial fibrillation (AF) are limited. We determined the relationships of depression, anger, anxiety, and chronic stress with incident AF in a multiethnic cohort of middle‐ and older‐aged adults. Methods and Results This analysis included 6644 MESA (Multi‐Ethnic Study of Atherosclerosis) study participants who were free of AF at baseline. Depressive symptoms were assessed at baseline and defined as either a 20‐item Center for Epidemiologic Studies Depression Scale score ≥16 or use of antidepressant medications. The Spielberger Trait Anger Scale, Spielberger Trait Anxiety Scale, and Chronic Burden Scale were also administered at baseline to assess anger, anxiety, and chronic stress, respectively. The primary outcome was incident AF, identified by follow‐up study visit ECGs, hospital discharge diagnoses, or Medicare claims data. A total of 875 (13%) incident AF cases were detected over a median follow‐up of nearly 13 years. A Center for Epidemiologic Studies Depression Scale score ≥16 (referent, Center for Epidemiologic Studies Depression Scale score

BackgroundGene expression may be an important biological mediator in associations between social factors and health. However, previous studies were limited by small sample sizes and use of differing cell types with heterogeneous expression patterns. We use a large population-based cohort with gene expression measured solely in monocytes to investigate associations between seven social factors and expression of genes previously found to be sensitive to social factors.MethodsWe employ three methodological approaches: 1) omnibus test for the entire gene set (Global ANCOVA), 2) assessment of each association individually (linear regression), and 3) machine learning method that performs variable selection with correlated predictors (elastic net).ResultsIn global analyses, significant associations with the a priori defined socially sensitive gene set were detected for major or lifetime discrimination and chronic burden (p = 0.019 and p = 0.047, respectively). Marginally significant associations were detected for loneliness and adult socioeconomic status (p = 0.066, p = 0.093, respectively). No associations were significant in linear regression analyses after accounting for multiple testing. However, a small percentage of gene expressions (up to 11%) were associated with at least one social factor using elastic net.ConclusionThe Global ANCOVA and elastic net findings suggest that a small percentage of genes may be "socially sensitive," (i.e. demonstrate differential expression by social factor), yet single gene approaches such as linear regression may be ill powered to capture this relationship. Future research should further investigate the biological mechanisms through which social factors act to influence gene expression and how systemic changes in gene expression affect overall health.

Abstract Obesity prevalence is rapidly increasing in developing countries. Existing research investigating social patterning of obesity and its risk factors in Latin American urban contexts has inconsistent findings. This study analyzed a multistage household survey in adults in Belo Horizonte, Minas Gerais State, Brazil. Marginal models were used to examine the association of education and household and neighborhood income with body mass index (BMI), obesity, physical inactivity, and low fruit and vegetable intake after adjusting for age and ethnicity and stratifying by sex. BMI and obesity were inversely associated with education in women. BMI was positively associated with household and neighborhood income in men. Additionally, physical inactivity and low fruit and vegetable intake were inversely associated with education and household income in both men and women, and physical inactivity was inversely associated with neighborhood income in men. Understanding the drivers of these patterns will allow for development of appropriate policy and interventions to reduce cardiovascular disease risk in large cities in Latin America.

Abstract This paper reviews the potential utility of using the concepts and tools of systems to understand and act on health in cities. The basic elements of systems approaches and the links between cities as systems and population health as emerging from the functioning of a system are reviewed. The paper also discusses implications of systems thinking for urban health including the development of dynamic conceptual models, the use of new tools, the integration of data in new ways and the identification of data gaps, and the formulation of different kinds of questions and identification of new policies. The paper concludes with a review of caveats and challenges.

Abstract This study aimed to estimate the prevalence of leisure-time physical activity and investigate its association with contextual characteristics of the social and physical environment in different socioeconomic statuses, using a household survey in Belo Horizonte, Minas Gerais State, Brazil (2008-2009). Leisure-time physical activity was measured by the International Physical Activity Questionnaire; and the social and physical environment by scales arising from perception of neighborhood attributes. Multilevel logistic regression analysis was performed separately for each socioeconomic status stratum. The overall prevalence of leisure-time physical activity was 30.2%, being 20.2% amongst participants of low socioeconomic status, 25.4% in the medium and 40.6% in the high socioeconomic status group. A greater perception of social cohesion was associated with increased leisure-time physical activity only amongst participants of the lowest socioeconomic status even after adjusting for individual characteristics. The results demonstrate the importance of social cohesion for the promotion of leisure-time physical activity in economically disadvantaged groups, supporting the need to stimulate interventions for enhancing social relationships in this population.

Abstract Neighborhood problems constitute sources of chronic stress that may increase the risk of poor self-rated health. The associations of census tract level income and perceived neighborhood problems with self-rated health were examined in Florianópolis, Santa Catarina State, Brazil (1,720 adults). Odds ratios (OR) and their 95% confidence intervals (95%CI) of poor self-rated health were estimated through multilevel models. Residents in census tracts in the lower and intermediate tertiles of income reported poorer health than those in the highest tertile. OR of reporting poorer health was 2.44 (95%CI: 2.35- 2.54) in the higher tertile of social disorder (adjusting for mental health). The chances of reporting the poorer health with neighborhood problems ranged from 1.07 (95%CI: 1.03-1.11) to 2.02 (95%CI: 1.95-2.10) for the higher tertile of social disorder (physical health) and physical problem (health-related variables). Perceived neighborhood problems were independently associated with poor health. The perception of a neighborhood among its residents should be considered by health policymakers.

The practice of physical activity is an important factor in the prevention of health problems. However, a small portion of the population is physically active. Recent reviews show that physical activity classes in community settings have the potential to increase population levels of physical activity and reduce health inequalities.To evaluate the effect of the Academias da Cidade Program in Belo Horizonte on the practice of physical activity in leisure time (PALT) by non-users living near the program centers.We conducted a home-based health survey in Belo Horizonte (2008-2009) with 1,581 adults who were non-users of the program and who lived within a 1,500-meter radius of one active program center (exposed group) and two nonoperational centers with sites reserved for their construction (unexposed group). We collected data on PALT levels (≥150 minutes/week), which was measured with the Physical Activity International Questionnaire and analyzed with binary logistic regression using the Generalized Estimating Equations method. The propensity score was used as an adjustment variable to control the potential confusion in the measures of effect of exposure studied.The overall prevalence of the PALT was 26.5% in the exposed group and 22.7% in the unexposed group. The exposed group was more likely to be active in leisure time (OR = 1.05; CI 95%: 1.01-1.10). When considering the interaction between exposed group and distance, individuals in the exposed group who lived less than 500 meters from the program center were more likely to be active in leisure time (OR = 1.18, CI 95%: 1.03-1.35) compared to their counterparts.Promoting physical activity in the community can favorably affect PALT levels among residents, especially those living closest to intervention centers. We believe the Academias da Cidade Program is a promising strategy to facilitate the access to appropriate spaces for the practice of physical activity and contribute to increase the levels physical activity within populations.

The objective of this research was to examine the association between income inequality and high blood pressure in Colombia. Using a nationally representative Colombian sample of adults, and data from departments and municipalities, we fit sex-stratified linear and logistic multilevel models with blood pressure as a continuous and binary variable, respectively. In adjusted models, women living in departments with the highest quintile of income inequality in 1997 had higher systolic blood pressure than their counterparts living in the lowest quintile of income inequality (mean difference 4.42mmHg; 95%CI: 1.46, 7.39). Women living in departments that were at the fourth and fifth quintile of income inequality in 1994 were more likely to have hypertension than those living in departments at the first quintile in the same year (OR: 1.56 and 1.48, respectively). For men, no associations of income inequality with either systolic blood pressure or hypertension were observed. Our findings are consistent with the hypothesis that income inequality is associated with increased risk of high blood pressure for women. Future studies to analyze pathways linking income inequality to high blood pressure in Colombia are needed.

Epigenetic changes are a potential mechanism contributing to race/ethnic and socioeconomic disparities in health. However, there is scant evidence of the race/ethnic and socioeconomic patterning of epigenetic marks. We used data from the Multi-Ethnic Study of Atherosclerosis Stress Study (N = 988) to describe age- and gender-independent associations of race/ethnicity and socioeconomic status (SES) with methylation of Alu and LINE-1 repetitive elements in leukocyte DNA. Mean Alu and Line 1 methylation in the full sample were 24% and 81% respectively. In multivariable linear regression models, African-Americans had 0.27% (p

Recent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood.We used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25(th) to 75(th) percentile) predicted inter-exam reduction in BMI of 0.09 kg/m(2) [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m(2) in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m(2) in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.Findings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.

Using ~60,000 SNPs selected for minimal linkage disequilibrium, we perform population structure analysis of 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By projection of principal components (PCs) of ancestry to samples from the HapMap phase III and the Human Genome Diversity Panel (HGDP), we show the first two PCs quantify the Caucasian, African, and Native American origins, while the third and fourth PCs bring out an axis that aligns with known South-to-North geographic location of HGDP Native American samples and further separates MESA Mexican versus Central/South American samples along the same axis. Using k-means clustering computed from the first four PCs, we define four subgroups of the MESA Hispanic cohort that show close agreement with self-identification, labeling the clusters as primarily Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. To demonstrate our recommendations for genetic analysis in the MESA Hispanic cohort, we present pooled and stratified association analysis of triglycerides for selected SNPs in the LPL and TRIB1 gene regions, previously reported in GWAS of triglycerides in Caucasians but as yet unconfirmed in Hispanic populations. We report statistically significant evidence for genetic association in both genes, and we further demonstrate the importance of considering population substructure and genetic heterogeneity in genetic association studies performed in the United States Hispanic population.

En países de altos ingresos el efecto de las inequidades sociales en los riesgos de enfermedades cardiovasculares (ECV) se encuentra bien documentado. En Latinoamérica se ha realizado amplias discusiones teóricas y conceptuales sobre el efecto de las inequidades sociales en salud, sin embargo, la investigación empírica ha sido limitada. En el presente artículo, se resumen los trabajos empíricos recientes sobre las inequidades sociales y el riesgo de ECV en Latinoamérica y se resalta las principales necesidades en materia de investigación, al igual que las implicaciones para su prevención. Aunque mucho se desconoce acerca de los patrones sociales de las ECV en Latinoamérica, los pocos estudios disponibles hasta la fecha indican que las inequidades sociales en los riesgos de ECV varían de acuerdo a la población, a los indicadores de nivel socioeconómico, al igual que a los indicadores de riesgo de enfermedad. Las mayores inequidades sociales se observan entre mujeres en áreas urbanas y se relacionan con obesidad, diabetes y dieta. Pocos estudios se han realizado en algunas partes de Latinoamérica y en países de Centroamérica y del norte de Suramérica. Los sistemas de registro civil, estadísticas vitales y las encuestas representativas a nivel nacional sobre factores de riesgo pueden constituirse en fuentes importantes de datos, mientras se recoge información sobre los indicadores socioeconómicos. Los estudios longitudinales también son importantes para investigar los factores que conducen a las inequidades sociales. En la medida en que se implementen políticas y estrategias de prevención para reducir las ECV en Latinoamérica, también se deben investigar los factores que generan inequidades sociales en el riesgo de ECV.

Paid sick leave provides workers with paid time off to receive COVID-19 vaccines and to recover from potential vaccine adverse effects. We hypothesized that US cities with paid sick leave would have higher COVID-19 vaccination coverage and narrower coverage disparities than those without such policies. Using county-level vaccination data and paid sick leave data from thirty-seven large US cities in 2021, we estimated the association between city-level paid sick leave policies and vaccination coverage in the working-age population and repeated the analysis using coverage in the population ages sixty-five and older as a negative control. We also examined associations by neighborhood social vulnerability. Cities with a paid sick leave policy had 17 percent higher vaccination coverage than cities without such a policy. We found stronger associations between paid sick leave and vaccination in the most socially vulnerable neighborhoods compared with the least socially vulnerable ones, and no association in the population ages sixty-five and older. Paid sick leave policies are associated with higher COVID-19 vaccination coverage and narrower coverage disparities. Increasing access to these policies may help increase vaccination and reduce inequities in coverage.

Objectives. To examine racial/ethnic disparities in COVID-19 outcomes between Hispanics and Whites across 27 US jurisdictions whose health departments are members of the Big Cities Health Coalition (BCHC). Methods. Using surveillance data from the BCHC COVID-19 dashboard as of mid-June 2021, we computed crude incidence, age-adjusted hospitalization and mortality, and full vaccination coverage rates for Hispanics and Whites by city. We estimated relative and absolute disparities cumulatively and for 2020 and 2021 and explored associations between city-level social vulnerability and the magnitude of disparities. Results. In most of the cities with available COVID-19 incidence data, rates among Hispanics were 2.2 to 6.7 times higher than those among Whites. In all cities, Hispanics had higher age-adjusted hospitalization (1.5-8.6 times as high) and mortality (1.4-6.2 times as high) rates. Hispanics had lower vaccination coverage in all but 1 city. Disparities in incidence and hospitalizations narrowed in 2021, whereas disparities in mortality remained similar. Disparities in incidence, hospitalization, mortality, and vaccination rates were wider in cities with lower social vulnerability. Conclusions. A deeper exploration of racial/ethnic disparities in COVID-19 outcomes is essential to understand and prevent disparities among marginalized communities. ( Am J Public Health . 2022;112(7): 1034-1044. https://doi.org/10.2105/AJPH.2022.306809).

Objectives. To describe the creation of an interactive dashboard to advance the understanding of the COVID-19 pandemic from an equity and urban health perspective across 30 large US cities that are members of the Big Cities Health Coalition (BCHC). Methods. We leveraged the Drexel‒BCHC partnership to define the objectives and audience for the dashboard and developed an equity framework to conceptualize COVID-19 inequities across social groups, neighborhoods, and cities. We compiled data on COVID-19 trends and inequities by race/ethnicity, neighborhood, and city, along with neighborhood- and city-level demographic and socioeconomic characteristics, and built an interactive dashboard and Web platform to allow interactive comparisons of these inequities across cities. Results. We launched the dashboard on January 21, 2021, and conducted several dissemination activities. As of September 2021, the dashboard included data on COVID-19 trends for the 30 cities, on inequities by race/ethnicity in 21 cities, and on inequities by neighborhood in 15 cities. Conclusions. This dashboard allows public health practitioners to contextualize racial/ethnic and spatial inequities in COVID-19 across large US cities, providing valuable insights for policymakers. ( Am J Public Health . 2022;112(6):904-912. https://doi.org/10.2105/AJPH.2021.306708).

Understanding health disparity causes is an important first step toward developing policies or interventions to eliminate disparities, but their nature makes identifying and addressing their causes challenging. Potential causal factors are often correlated, making it difficult to distinguish their effects. These factors may exist at different organizational levels (e.g., individual, family, neighborhood), each of which needs to be appropriately conceptualized and measured. The processes that generate health disparities may include complex relationships with feedback loops and dynamic properties that traditional statistical models represent poorly. Because of this complexity, identifying disparities' causes and remedies requires integrating findings from multiple methodologies. We highlight analytic methods and designs, multilevel approaches, complex systems modeling techniques, and qualitative methods that should be more broadly employed and adapted to advance health disparities research and identify approaches to mitigate them.

Objectives: To examine the impact of neighborhood conditions resulting from racial residential segregation on cardiovascular disease (CVD) risk in a socioeconomically diverse African American sample., Methods: The study included 4096 African American women (n = 2652) and men (n = 1444) aged 21 to 93 years from the Jackson Heart Study (Jackson, Mississippi; 2000-2011). We assessed neighborhood disadvantage with a composite measure of 8 indicators from the 2000 US Census. We assessed neighborhood-level social conditions, including social cohesion, violence, and disorder, with self-reported, validated scales., Results: Among African American women, each standard deviation increase in neighborhood disadvantage was associated with a 25% increased risk of CVD after covariate adjustment (hazard ratio = 1.25; 95% confidence interval = 1.05, 1.49). Risk also increased as levels of neighborhood violence and physical disorder increased after covariate adjustment. We observed no statistically significant associations among African American men in adjusted models., Conclusions: Worse neighborhood economic and social conditions may contribute to increased risk of CVD among African American women. Policies directly addressing these issues may alleviate the burden of CVD in this group.

Objectives: We described the associations of ambient air pollution exposure with race/ethnicity and racial residential segregation., Methods: We studied 5921 White, Black, Hispanic, and Chinese adults across 6 US cities between 2000 and 2002. Household-level fine particulate matter (PM2.5) and nitrogen oxides (NOX) were estimated for 2000. Neighborhood racial composition and residential segregation were estimated using US census tract data for 2000., Results: Participants in neighborhoods with more than 60% Hispanic populations were exposed to 8% higher PM2.5 and 31% higher NOX concentrations compared with those in neighborhoods with less than 25% Hispanic populations. Participants in neighborhoods with more than 60% White populations were exposed to 5% lower PM2.5 and 18% lower NOX concentrations compared with those in neighborhoods with less than 25% of the population identifying as White. Neighborhoods with Whites underrepresented or with Hispanics overrepresented were exposed to higher PM2.5 and NOX concentrations. No differences were observed for other racial/ethnic groups., Conclusions: Living in majority White neighborhoods was associated with lower air pollution exposures, and living in majority Hispanic neighborhoods was associated with higher air pollution exposures. This new information highlighted the importance of measuring neighborhood-level segregation in the environmental justice literature.

Objectives: We investigated relations between changes in neighborhood ethnic composition and changes in body mass index (BMI) and waist circumference among Chinese and Hispanic immigrants in the United States., Methods: We used Multi-Ethnic Study of Atherosclerosis data over a median 9-year follow-up (2000-2002 to 2010-2012) among Chinese (n = 642) and Hispanic (n = 784) immigrants aged 45 to 84 years at baseline. We incorporated information about residential moves and used econometric fixed-effects models to control for confounding by time-invariant characteristics. We characterized neighborhood racial/ethnic composition with census tract-level percentage Asian for Chinese participants and percentage Hispanic for Hispanic participants (neighborhood coethnic concentration)., Results: In covariate-adjusted longitudinal fixed-effects models, results suggested associations between decreasing neighborhood coethnic concentration and increasing weight, although results were imprecise: within-person BMI increases associated with an interquartile range decrease in coethnic concentration were 0.15 kilograms per meters squared (95% confidence interval [CI] = 0.00, 0.30) among Chinese and 0.17 kilograms per meters squared (95% CI = -0.17, 0.51) among Hispanic participants. Results did not differ between those who did and did not move during follow-up., Conclusions: Residential neighborhoods may help shape chronic disease risk among immigrants.

Objectives: We examined the association of childhood and adult socioeconomic status with longitudinal change in allostatic load (AL), a measure of biological dysfunction., Methods: The study sample included 6135 participants from the Multi-Ethnic Study of Atherosclerosis, aged 45 to 84 years, recruited in 2000 from 6 US counties; 3 follow-up examinations took place through September 2011. We calculated standardized scores for several metabolic and cardiovascular components relative to accepted clinical cut points for "higher risk" and then summed them to create an overall index of AL. We used mixed effects growth curve models to assess the relationship between socioeconomic status and AL as a linear function of time passed since the baseline examination; we included random effects for the intercept and slope., Results: Among those with lower baseline AL (< median), high adult education was associated with a significantly slower increase in AL over time, whereas there was no significant association among those with higher baseline AL., Conclusions: The relationship between socioeconomic status and patterns of change in health parameters may vary over time and with the accumulation of biological risk.

Objectives: We investigated whether moving to neighborhoods with closer proximity of destinations and greater street connectivity was associated with more walking, a greater probability of meeting the "Every Body Walk!" campaign goals (≥ 150 minutes/week of walking), and reductions in body mass index (BMI)., Methods: We linked longitudinal data from 701 participants, who moved between 2 waves of the Multi-Ethnic Study of Atherosclerosis (2004-2012), to a neighborhood walkability measure (Street Smart Walk Score) for each residential location. We used fixed-effects models to estimate if changes in walkability resulting from relocation were associated with simultaneous changes in walking behaviors and BMI., Results: Moving to a location with a 10-point higher Walk Score was associated with a 16.04 minutes per week (95% confidence interval [CI] = 5.13, 29.96) increase in transport walking, 11% higher odds of meeting Every Body Walk! goals through transport walking (adjusted odds ratio = 1.11; 95% CI = 1.02, 1.21), and a 0.06 kilogram per meters squared (95% CI = -0.12, -0.01) reduction in BMI. Change in walkability was not associated with change in leisure walking., Conclusions: Our findings illustrated the potential for neighborhood infrastructure to support health-enhancing behaviors and overall health of people in the United States.