Genetic Ancestry-specific Molecular and Survival Differences in Admixed Patients With Breast Cancer.

OBJECTIVE: We aim to determine whether incremental changes in genetic ancestry percentages influence molecular and clinical outcome characteristics of breast cancer in an admixed population. BACKGROUND: Patients with breast cancer are predominantly characterized as "Black" or "White" based on self-identified race/ethnicity or arbitrary genetic ancestry cutoffs. This limits scientific discovery in populations that are admixed or of mixed race/ethnicity as they cannot be classified based on historical race/ethnicity boxes or genetic ancestry cutoffs. METHODS: We used The Cancer Genome Atlas cohort and focused on genetically admixed patients that had less than 90% European, African, Asian, or Native American ancestry. RESULTS: Genetically admixed patients with breast cancer exhibited improved 10-year overall survival relative to those with >90% European ancestry. Within the luminal A subtype, patients with lower African ancestry had longer 10-year overall survival compared to those with higher African ancestry. The correlation of genetic ancestry with gene expression and DNA methylation in the admixed cohort revealed novel ancestry-specific intrinsic PAM50 subtype patterns. In luminal A tumors, genetic ancestry was correlated with both the expression and methylation of signaling genes, while in basal-like tumors, genetic ancestry was correlated with stemness genes. In addition, we took a machine-learning approach to estimate genetic ancestry from gene expression or DNA methylation and were able to accurately calculate ancestry values from a reduced set of 10 genes or 50 methylation sites that were specific for each molecular subtype. CONCLUSIONS: Our results suggest that incremental changes in genetic ancestry percentages result in ancestry-specific molecular differences even between well-established PAM50 subtypes which may influence disparities in breast cancer survival outcomes. Accounting for incremental changes in ancestry will be important in future research, prognostication, and risk stratification, particularly in ancestrally diverse populations.

Uncovering physical activity trade-offs in transportation policy: A spatial agent-based model of Bogotá, Colombia.

BACKGROUND: Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. METHODS: The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. RESULTS: Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a 'free-fare' scenario, largely through reductions in walking trips. 'Free fare' policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. CONCLUSIONS: Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.

Research Translation to Promote Urban Health in Latin America: The SALURBAL Experience.

In highly urbanized and unequal Latin America, urban health and health equity research are essential to effective policymaking. To ensure the application of relevant and context-specific evidence to efforts to reduce urban health inequities, urban health research in Latin America must incorporate strategic research translation efforts. Beginning in 2017, the Urban Health in Latin America (SALURBAL) project implemented policy-relevant research and engaged policymakers and the public to support the translation of research findings. Over 6 years, more than 200 researchers across eight countries contributed to SALURBAL's interdisciplinary network. This network allowed SALURBAL to adapt research and engagement activities to local contexts and priorities, thereby maximizing the policy relevance of research findings and their application to promote policy action, inform urban interventions, and drive societal change. SALURBAL achieved significant visibility and credibility among academic and nonacademic urban health stakeholders, resulting in the development of evidence and tools to support urban policymakers, planners, and policy development processes across the region. These efforts and their outcomes reveal important lessons regarding maintaining flexibility and accounting for local context in research, ensuring that resources are dedicated to policy engagement and dissemination activities, and recognizing that assessing policy impact requires a nuanced understanding of complex policymaking processes. These reflections are relevant for promoting urban health and health equity research translation across the global south and worldwide. This paper presents SALURBAL's strategy for dissemination and policy translation, highlights innovative initiatives and their outcomes, discusses lessons learned, and shares recommendations for future efforts to promote effective translation of research findings.

Recent greening may curb urban warming in Latin American cities of better economic conditions.

Rising temperatures have profound impacts on the well-being of urban residents. However, factors explaining the temporal variability of urban thermal environment, or urban warming, remain insufficiently understood, especially in the Global South. Addressing this gap, we studied the relationship between city-level economic conditions and urban warming, and how urban green space mediated this relationship, focusing on 359 major Latin American cities between 2001 and 2022. While effect sizes varied by economic and temperature measures used, we found that better economic conditions were associated with lower baseline greenness in 2011, which contributed to faster warming. There was modest evidence that this faster warming associated with lower baseline greenness and improved economic conditions was partially offset by cooling from recent greening (2001-2022) in cities of better economic conditions. This offset was more evident in arid cities. Together, these findings provide insights into the urban warming mechanism manifested through the effect of economic conditions on urban green space, for Latin American cities and other high-density cities transforming in a similar context.

Translational Epidemiology: An Integrative Approach to Determine the Interplay Between Genetic Ancestry and Neighborhood Socioeconomic Status on Triple Negative Breast Cancer.

OBJECTIVE: To investigate the impact of global and local genetic ancestry and neighborhood socioeconomic status (nSES), on breast cancer (BC) subtype, and gene expression. BACKGROUND: Higher rates of aggressive BC subtypes [triple negative breast cancer (TNBC)] and worse overall BC survival are seen in black women [Hispanic Black (HB) and non-Hispanic Black (NHB)] and women from low nSES. However, the complex relationship between genetic ancestry, nSES, and BC subtype etiology remains unknown. METHODS: Genomic analysis was performed on the peripheral blood from a cohort of 308 stage I to IV non-Hispanic White (NHW), Hispanic White (HW), HB, and NHB women with BC. Patient and tumor characteristics were collected. Global and local ancestral estimates were calculated. Multinomial logistic regression was performed to determine associations between age, stage, genetic ancestry, and nSES on rates of TNBC compared to estrogen receptor (ER+)/epidermal growth factor receptor 2 (HER2-), ER+/HER2+, and ER-/HER2+ disease. RESULTS: Among 308 women, we identified a significant association between increasing West African (WA) ancestry and odds of TNBC [odds ratio (OR): 1.06, 95% confidence interval (95% CI): 1.001-1.126, P =0.046] as well as an inverse relationship between higher nSES and TNBC (OR: 0.343, 95% CI: 0.151-0.781, P =0.011). WA ancestry remained significantly associated with TNBC when adjusting for patient age and tumor stage, but not when adjusting for nSES (OR: 1.049, 95% CI: -0.987-1.116, P =0.120). Local ancestry analysis, however, still revealed nSES-independent enriched WA ancestral segment centered at χ 2 =42004914 ( p =3.70×10 -5 ) in patients with TNBC. CONCLUSIONS: In this translational epidemiologic study of genetic ancestry and nSES on BC subtype, we discovered associations between increasing WA ancestry, low nSES, and higher rates of TNBC compared to other BC subtypes. Moreover, on admixture mapping, specific chromosomal segments were associated with WA ancestry and TNBC, independent of nSES. However, on multinomial logistic regression adjusting for WA ancestry, women from low nSES were more likely to have TNBC, independent of genetic ancestry. These findings highlight the complex nature of TNBC and the importance of studying potential gene-environment interactions as drivers of TNBC.

Urban Scaling of Health Outcomes: a Scoping Review.

Urban scaling is a framework that describes how city-level characteristics scale with variations in city size. This scoping review mapped the existing evidence on the urban scaling of health outcomes to identify gaps and inform future research. Using a structured search strategy, we identified and reviewed a total of 102 studies, a majority set in high-income countries using diverse city definitions. We found several historical studies that examined the dynamic relationships between city size and mortality occurring during the nineteenth and early twentieth centuries. In more recent years, we documented heterogeneity in the relation between city size and health. Measles and influenza are influenced by city size in conjunction with other factors like geographic proximity, while STIs, HIV, and dengue tend to occur more frequently in larger cities. NCDs showed a heterogeneous pattern that depends on the specific outcome and context. Homicides and other crimes are more common in larger cities, suicides are more common in smaller cities, and traffic-related injuries show a less clear pattern that differs by context and type of injury. Future research should aim to understand the consequences of urban growth on health outcomes in low- and middle-income countries, capitalize on longitudinal designs, systematically adjust for covariates, and examine the implications of using different city definitions.

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Transport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts. METHODS: We performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers. RESULTS: Simulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers. CONCLUSION: This study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

Female Prostate Development: Morphological Analysis of the Budding Dynamic.

The presence of the prostate in female mammals has long been known. However, pieces of information related to its development are still lacking. The aim of this study was to explore the budding dynamic during the initial prostate development in female gerbils. Pregnant females were timed, the fetuses were euthanized, and the urogenital sinus was dissected out between the embryonic days 20 and 24 (E20-E24 groups). Newborn pups (1-day-old; P1 group) underwent the same procedures. The female prostate development was based on epithelial buds which arose far from the paraurethral mesenchyme (PAM). The epithelial buds reached the PAM at prenatal day 24, crossing a small gap in the smooth muscle layer between the periurethral mesenchyme (PEM) and the PAM. Steroid nuclear receptors such as the androgen receptor and estrogen receptor alpha were localized in the PEM through the urethral wall, although some epithelial labeling was also present in the urogenital sinus epithelium (UGE). P63-positive cells were found only in the UGE, becoming restricted to the basal compartment after the 23rd prenatal day. The results showed that the gerbil female prostate exhibits a distinct budding pattern as compared to the male prostate development.

Is self-reported park proximity associated with perceived social disorder? Findings from eleven cities in Latin America.

Parks and greenspaces can enhance personal health in various ways, including among others, through psychological restoration and improved well-being. However, under certain circumstances, parks may also have adverse effects by providing isolated and hidden spaces for non-normative and crime-related activities. This study uses a survey conducted by the Development Bank of Latin America in a cross-sectional representative sample of 7,110 respondents in eleven Latin-American cities. We examine associations between self-reported park proximity with perceived social disorder (drug use/sales, gangs, prostitution and assault and/or crime), and whether these associations are modified by neighborhood characteristics (informal neighborhoods, poor street-lighting, abandoned buildings, illegal dumping). High self-reported park proximity was associated with lower perceptions of social disorder, but these associations were no longer significant following adjustment for neighborhood characteristics. Significant interactions were observed between park proximity and neighborhood characteristics suggesting that the likelihood of perceiving social disorder increases with high park proximity in informal neighborhoods and in the presence of certain neighborhood characteristics, such as poor street-lighting, abandoned buildings, and illegal dumping in residential streets. The differential associations between reported park proximity and perceived social disorder in different living environments highlight the importance of supportive social and physical infrastructure to maximize the restorative benefits of parks in all urban areas.

Is city-level travel time by car associated with individual obesity or diabetes in Latin American cities? Evidence from 178 cities in the SALURBAL project.

There is growing evidence that longer travel time by private car poses physical and mental risks. Individual-level obesity and diabetes, two of the main public health challenges in low- and middle-income contexts, could be associated to city-level travel times by car. We used individual obesity and diabetes data from national health surveys from individuals in 178 Latin American cities, compiled and harmonized by the SALURBAL project. We calculated city-level travel times by car using the Google Maps Distance Matrix API. We estimated associations between peak hour city-level travel time by car and obesity and diabetes using multilevel logistic regression models, while adjusting for individual characteristics and other city-level covariates. In our study we did not observe a relationship between city-level peak-hour travel time by car and individual obesity and diabetes, as reported in previous research for individual time spent in vehicles in high-income settings. Our results suggest that this relationship may be more complex in Latin America compared to other settings, especially considering that cities in the region are characterized by high degrees of population density and compactness and by a higher prevalence of walking and public transportation use.

Uphyloplot2: visualizing phylogenetic trees from single-cell RNA-seq data.

BACKGROUND: Recent advances in single cell sequencing technologies allow for greater resolution in assessing tumor clonality using chromosome copy number variations (CNVs). While single cell DNA sequencing technologies are ideal to identify tumor sub-clones, they remain expensive and in contrast to single cell RNA-seq (scRNA-seq) methods are more limited in the data they generate. However, CNV data can be inferred from scRNA-seq and bulk RNA-seq, for which several tools have been developed, including inferCNV, CaSpER, and HoneyBADGER. Inferences regarding tumor clonality from CNV data (and other sources) are frequently visualized using phylogenetic plots, which previously required time-consuming and error-prone, manual analysis. RESULTS: Here, we present Uphyloplot2, a python script that generates phylogenetic plots directly from inferred RNA-seq data, or any Newick formatted dendrogram file. The tool is publicly available at https://github.com/harbourlab/UPhyloplot2/ . CONCLUSIONS: Uphyloplot2 is an easy-to-use tool to generate phylogenetic plots to depict tumor clonality from scRNA-seq data and other sources.

A method for estimating neighborhood characterization in studies of the association with availability of sit-down restaurants and supermarkets.

BACKGROUND: Although neighborhood-level access to food differs by sociodemographic factors, a majority of research on neighborhoods and food access has used a single construct of neighborhood context, such as income or race. Therefore, the many interrelated built environment and sociodemographic characteristics of neighborhoods obscure relationships between neighborhood factors and food access. METHODS: The objective of this study was to account for the many interrelated characteristics of food-related neighborhood environments and examine the association between neighborhood type and relative availability of sit-down restaurants and supermarkets. Using cluster analyses with multiple measures of neighborhood characteristics (e.g., population density, mix of land use, and sociodemographic factors) we identified six neighborhood types in 1993 in the Twin Cities Region, Minnesota. We then used mixed effects regression models to estimate differences in the relative availability of sit-down restaurants and supermarkets in 1993, 2001, and 2011 across the six neighborhood types. RESULTS: We defined six types of neighborhoods that existed in 1993, namely, urban core, inner city, urban, aging suburb, high-income suburb, and suburban edge. Between 1993 and 2011, inner city neighborhoods experienced a greater increase in the percent of sit-down restaurants compared with urban core, urban, and aging suburbs. Differences in the percent of sit-down restaurants between inner city and aging suburbs, high-income suburbs and suburban edge neighborhoods increased between 1993 and 2011. Similarly, aging suburb neighborhoods had a greater percent of supermarkets compared with urban and high-income suburb neighborhoods in 2001 and 2011, but not in 1993, suggesting a more varied distribution of food stores across neighborhoods over time. Thus, the classification of neighborhood type based on sociodemographic and built environment characteristics resulted in a complex and increasingly varied distribution of restaurants and food stores. CONCLUSIONS: The temporal increase in the relative availability of sit-down restaurants in inner cities after accounting for all restaurants might be partly related to a higher proportion of residents who eat-away-from-home, which is associated with higher calorie and fat intake.

Disentangling associations between vegetation greenness and dengue in a Latin American city: Findings and challenges.

Being a Re-Emerging Infectious Disease, dengue causes 390 million cases globally and is prevalent in many urban areas in South America. Understanding the fine-scale relationships between dengue incidence and environmental and socioeconomic factors can guide improved disease prevention strategies. This ecological study examines the association between dengue incidence and satellite-based vegetation greenness in 3826 census tracts nested in 474 neighborhoods in Belo Horizonte, Brazil, during the 2010 dengue epidemic. To reduce potential bias in the estimated dengue-greenness association, we adjusted for socioeconomic vulnerability, population density, building height and density, land cover composition, elevation, weather patterns, and neighborhood random effects. We found that vegetation greenness was negatively associated with dengue incidence in a univariate model, and this association attenuated after controlling for additional covariates. The dengue-greenness association was modified by socioeconomic vulnerability: while a positive association was observed in the least vulnerable census tracts, the association was negative in the most vulnerable areas. Using greenness as a proxy for vegetation quality, our results show the potential of vegetation management in reducing dengue incidence, particularly in socioeconomically vulnerable areas. We also discuss the role of water infrastructure, sanitation services, and tree cover in lowering dengue risk.

Support for market-based and command-and-control congestion relief policies in Latin American cities: Effects of mobility, environmental health, and city-level factors.

Public support for the implementation of congestion relief policies is critical for the policies' technical and political success. To identify the personal, social, and city-level factors associated with higher acceptance towards such policies, this study uses a 2016 survey of 8178 residents from 11 cities across 10 Latin American countries collected by the Development Bank of Latin America (Corporación Andina de Fomento or CAF). We examined support for two demand-side approaches to managing the traffic congestion externality: congestion pricing - a market-based approach, and driving restrictions or bans - a command-and-control approach. Logit regression models show that personal mobility such as owning or using a private vehicle during a respondent's main commute trip are associated with decreased support, while higher congestion delay in one's commute and having a young child recently diagnosed with respiratory problems increases support for either congestion relief policy. In addition, residents of cities with higher levels of median annual particulate matter and with prior experience with traffic bans expressed higher support for either policy. Residents of cities with higher income inequality supported only driving restrictions; while those of cities with higher GDP per capita had lower support only for congestion pricing. To improve the public acceptance of congestion relief policies in Latin America, policy makers could: (1) explicitly seek to mitigate the costs it brings on individuals by investing in substitutes like public transportation; (2) promote the personal and social environmental and health benefits; (3) consider beginning with temporary, pilot programs; and in the case of driving restrictions, (4) take into account city-specific conditions related to income inequality that may influence public support for the policies.

Public transit use in the United States in the era of COVID-19: Transit riders' travel behavior in the COVID-19 impact and recovery period.

COVID-19 has upended travel across the world, disrupting commute patterns, mode choices, and public transit systems. In the United States, changes to transit service and reductions in passenger volume due to COVID-19 are lasting longer than originally anticipated. In this paper we examine the impacts of the COVID-19 pandemic on individual travel behavior across the United States. We analyze mobility data from Janurary to December 2020 from a sample drawn from a nationwide smartphone-based panel curated by a private firm, Embee Mobile. We combine this with a survey that we administered to that sample in August 2020. Our analysis provides insight into travel patterns and the immediate impacts of the COVID-19 pandemic on transit riders. We investigate three questions. First, how do transit riders differ socio-demographically from non-riders? Second, how has the travel behavior of transit riders changed due to the pandemic in comparison to non-riders, controlling for other factors? And third, how has this travel behavior varied across different types of transit riders? The travel patterns of transit riders were more significantly disrupted by the pandemic than the travel of non-riders, as measured by the average weekly number of trips and distance traveled before and after the onset of the pandemic. This was calculated using GPS traces from panel member smartphones. Our survey of the panel revealed that of transit riders, 75% reported taking transit less since the pandemic, likely due to a combination of being affected by transit service changes, concerns about infection risk on transit, and trip reductions due to shelter-in-place rules. Less than 10 percent of transit riders in our sample reported that they were comfortable using transit despite COVID-19 infection risk, and were not affected by transit service reductions. Transit riders were also more likely to have changed their travel behavior in other ways, including reporting an increase in walking. However, lower-income transit riders were different from higher-income riders in that they had a significantly smaller reduction in the number of trips and distance traveled, suggesting that these lower-income households had less discretion over the amount of travel they carried out during the pandemic. These results have significant implications for understanding the way welfare has been affected for transportation-disadvantaged populations during the course of the pandemic, and insight into the recovery of U.S. transit systems. The evidence from this unique dataset helps us understand the future effects of the pandemic on transit riders in the United States, either in further recovery from the pandemic with the anticipated effects of mass vaccination, or in response to additional waves of COVID-19 and other pandemics.

Assessing Google Street View Image Availability in Latin American Cities.

Virtual audits using Google Street View are an increasingly popular method of assessing neighborhood environments for health and urban planning research. However, the validity of these studies may be threatened by issues of image availability, image age, and variance of image age, particularly in the Global South. This study identifies patterns of Street View image availability, image age, and image age variance across cities in Latin America and assesses relationships between these measures and measures of resident socioeconomic conditions. Image availability was assessed at 530,308 near-road points within the boundaries of 371 Latin American cities described by the SALURBAL (Salud Urbana en America Latina) project. At the subcity level, mixed-effect linear and logistic models were used to assess relationships between measures of socioeconomic conditions and image availability, average image age, and the standard deviation of image age. Street View imagery was available at 239,394 points (45.1%) of the total sampled, and rates of image availability varied widely between cities and countries. Subcity units with higher scores on measures of socioeconomic conditions had higher rates of image availability (OR = 1.11 per point increase of combined index, p < 0.001) and the imagery was newer on average (- 1.15 months per point increase of combined index, p < 0.001), but image capture date within these areas varied more (0.59-month increase in standard deviation of image age per point increase of combined index, p < 0.001). All three assessed threats to the validity of Street View virtual audit studies spatially covary with measures of socioeconomic conditions in Latin American cities. Researchers should be attentive to these issues when using Street View imagery.

Determinants of Residential Preferences Related to Built and Social Environments and Concordance between Neighborhood Characteristics and Preferences.

We explored associations between residential preferences and sociodemographic characteristics, the concordance between current neighborhood characteristics and residential preferences, and heterogeneity in concordance by income and race/ethnicity. Data came from a cross-sectional phone and mail survey of 3668 residents of New York City, Baltimore, Chicago, Los Angeles, St. Paul, and Winston Salem in 2011-12. Scales characterized residential preferences and neighborhood characteristics. Stronger preferences were associated with being older, female, non-White/non-Hispanic, and lower education. There was significant positive but weak concordance between current neighborhood characteristics and residential preferences (after controlling sociodemographic characteristics). Concordance was stronger for persons with higher income and for Whites, suggesting that residential self-selection effects are strongest for populations that are more advantaged.

GIS-Based Home Neighborhood Food Outlet Counts, Street Connectivity, and Frequency of Use of Neighborhood Restaurants and Food Stores.

Researchers have linked neighborhood food availability to the overall frequency of using food outlets without noting if those outlets were within or outside of participants' neighborhoods. We aimed to examine the association of neighborhood restaurant and food store availability with frequency of use of neighborhood food outlets, and whether such an association was modified by neighborhood street connectivity using a large and diverse population-based cohort of middle-aged U.S. adults. We used self-reported frequency of use of fast food restaurants, sit-down restaurants, and grocery stores in respondents' home neighborhoods using data from the Coronary Artery Risk Development in Young Adults study Year 20 exam in 2005-2006 (n = 2860; Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA) and geographically matched GIS-measured neighborhood-level food resource, street, and U.S. Census data. We used mixed-effects logistic regression to examine the associations of the GIS-measured count of neighborhood fast food restaurants, sit-down restaurants, and grocery stores with self-reported frequency of using neighborhood restaurants and food stores and whether such associations differed by GIS-measured neighborhood street connectivity among those who perceived at least one such food outlet. In multivariate analyses, we observed a positive association between the GIS-measured count of neighborhood sit-down restaurants (OR = 1.02, 95% CI 1.00-1.04) and the self-reported frequency of using neighborhood sit-down restaurants. We observed no statistically significant association between GIS-measured count of neighborhood fast food restaurants and self-reported frequency of using neighborhood fast food restaurants, nor did we observe a statistically significant association between GIS-measured count of neighborhood grocery stores and self-reported frequency of using neighborhood grocery stores. We observed inverse associations between GIS-measured neighborhood street connectivity and the self-reported frequencies of using neighborhood fast food restaurants (OR = 0.42, 95% CI 0.26-0.68) and grocery stores (OR = - 2.26, 95% CI - 4.52 to - 0.01). Neighborhood street connectivity did not modify the association between GIS-measured neighborhood restaurant and food store count and the self-reported frequency of using neighborhood restaurants and food stores. Our findings suggest that, for those who perceived at least one sit-down restaurant in their neighborhood, individuals who have more GIS-measured sit-down restaurants in their neighborhoods reported more frequent use of sit-down restaurants than those whose neighborhoods contain fewer such restaurants. Our results also suggest that, for those who perceived at least one fast food restaurant in their neighborhood, individuals who live in neighborhoods with greater GIS-measured street connectivity reported less use of neighborhood fast food restaurants than those who live in neighborhoods with less street connectivity. The count of neighborhood sit-down restaurants and the connectivity of neighborhood street networks appear important in understanding the use of neighborhood food resources.

A systematic review of empirical and simulation studies evaluating the health impact of transportation interventions.

Urban transportation is an important determinant of health and environmental outcomes, and therefore essential to achieving the United Nation's Sustainable Development Goals. To better understand the health impacts of transportation initiatives, we conducted a systematic review of longitudinal health evaluations involving: a) bus rapid transit (BRT); b) bicycle lanes; c) Open Streets programs; and d) aerial trams/cable cars. We also synthesized systems-based simulation studies of the health-related consequences of walking, bicycling, aerial tram, bus and BRT use. Two reviewers screened 3302 unique titles and abstracts identified through a systematic search of MEDLINE (Ovid), Scopus, TRID and LILACS databases. We included 39 studies: 29 longitudinal evaluations and 10 simulation studies. Five studies focused on low- and middle-income contexts. Of the 29 evaluation studies, 19 focused on single component bicycle lane interventions; the rest evaluated multi-component interventions involving: bicycle lanes (n = 5), aerial trams (n = 1), and combined bicycle lane/BRT systems (n = 4). Bicycle lanes and BRT systems appeared effective at increasing bicycle and BRT mode share, active transport duration, and number of trips using these modes. Of the 10 simulation studies, there were 9 agent-based models and one system dynamics model. Five studies focused on bus/BRT expansions and incentives, three on interventions for active travel, and the rest investigated combinations of public transport and active travel policies. Synergistic effects were observed when multiple policies were implemented, with several studies showing that sizable interventions are required to significantly shift travel mode choices. Our review indicates that bicycle lanes and BRT systems represent promising initiatives for promoting population health. There is also evidence to suggest that synergistic effects might be achieved through the combined implementation of multiple transportation policies. However, more rigorous evaluation and simulation studies focusing on low- and middle-income countries, aerial trams and Open Streets programs, and a more diverse set of health and health equity outcomes is required.

Neighborhood characteristics and transport walking: Exploring multiple pathways of influence using a structural equation modeling approach.

In studies of neighborhood effects on transport walking, residential preferences along with other personal characteristics (walking attitude, factors that affect decision to walk for transport) are important factors to consider. However, few studies have examined relationships between neighborhood characteristics and transport walking accounting for a complex suite of personal factors. This study employed a structural equation modeling approach to examine associations between neighborhood characteristics and transport walking behaviors by accounting for residential preferences, self-assessed factors that affect decision to walk for transportation, and socio-demographics; and to examine whether neighborhood effects were modified by walking attitude and residential preferences. Based on a cross-sectional phone and mail survey of 2,848 residents of New York City, Baltimore, Chicago, Los Angeles, St. Paul, and Winston Salem in 2011-12, we found neighborhood characteristics had significant independent associations with transport walking, even after adjusting for residential preferences and other personal factors. Neighborhood effects on transport walking did not differ significantly by walking attitude or residential preferences. Our findings highlight the importance of neighborhood effects in promoting transport walking, and suggest that while residential preferences are important factors, they do not obviate the neighborhood effects on transport walking.