Human mobility networks reveal increased segregation in large cities.

A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1-6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city's hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.

The cellular composition of the human immune system is shaped by age and cohabitation.

Detailed population-level description of the human immune system has recently become achievable. We used a 'systems-level' approach to establish a resource of cellular immune profiles of 670 healthy individuals. We report a high level of interindividual variation, with low longitudinal variation, at the level of cellular subset composition of the immune system. Despite the profound effects of antigen exposure on individual antigen-specific clones, the cellular subset structure proved highly elastic, with transient vaccination-induced changes followed by a return to the individual's unique baseline. Notably, the largest influence on immunological variation identified was cohabitation, with 50% less immunological variation between individuals who share an environment (as parents) than between people in the wider population. These results identify local environmental conditions as a key factor in shaping the human immune system.

Knowledge about others reduces one's own sense of anonymity.

Social ties often seem symmetric, but they need not be1-5. For example, a person might know a stranger better than the stranger knows them. We explored whether people overlook these asymmetries and what consequences that might have for people's perceptions and actions. Here we show that when people know more about others, they think others know more about them. Across nine laboratory experiments, when participants learned more about a stranger, they felt as if the stranger also knew them better, and they acted as if the stranger was more attuned to their actions. As a result, participants were more honest around known strangers. We tested this further with a field experiment in New York City, in which we provided residents with mundane information about neighbourhood police officers. We found that the intervention shifted residents' perceptions of officers' knowledge of illegal activity, and it may even have reduced crime. It appears that our sense of anonymity depends not only on what people know about us but also on what we know about them.

Quantifying social organization and political polarization in online platforms.

Mass selection into groups of like-minded individuals may be fragmenting and polarizing online society, particularly with respect to partisan differences1-4. However, our ability to measure the social makeup of online communities and in turn, to understand the social organization of online platforms, is limited by the pseudonymous, unstructured and large-scale nature of digital discussion. Here we develop a neural-embedding methodology to quantify the positioning of online communities along social dimensions by leveraging large-scale patterns of aggregate behaviour. Applying our methodology to 5.1 billion comments made in 10,000 communities over 14 years on Reddit, we measure how the macroscale community structure is organized with respect to age, gender and US political partisanship. Examining political content, we find that Reddit underwent a significant polarization event around the 2016 US presidential election. Contrary to conventional wisdom, however, individual-level polarization is rare; the system-level shift in 2016 was disproportionately driven by the arrival of new users. Political polarization on Reddit is unrelated to previous activity on the platform and is instead temporally aligned with external events. We also observe a stark ideological asymmetry, with the sharp increase in polarization in 2016 being entirely attributable to changes in right-wing activity. This methodology is broadly applicable to the study of online interaction, and our findings have implications for the design of online platforms, understanding the social contexts of online behaviour, and quantifying the dynamics and mechanisms of online polarization.

Social bond dynamics and the evolution of helping.

Empiricists often struggle to apply game theory models to real-life cases of animal cooperation. One reason is that many examples of cooperation occur in stable groups, where individuals form social bonds that influence exchanges of help in ways that are not well described by previous models, including the extent of reciprocity and how relationships are initiated. We present a game theory model exploring the conditions under which social bonds between group members promote cooperation. In the model, bonds build up from exchanges of help in a similar way as the strength of association increases in learning, as in the Rescorla-Wagner rule. The bonds in turn affect partner choice and influence helping amounts. The model has a mechanism of reciprocity for bonded pairs, which can evolve toward either loose or strict reciprocation. Several aspects of the model are inspired by observations of food sharing in vampire bats. We find that small social neighborhoods are required for the evolutionary stability of helping, either as small group sizes, or if bonded members of larger groups can form temporary (daily) smaller groupings. The costs of helping need to be fairly low, while the benefits can be substantial. The form of reciprocity that evolves is neither immediate nor very strict. Individuals in need request help based on bond strength, but there is also an evolved preference for initiating bonds with new group members. In contrast, if different groups come into temporary contact, the evolved tendency is to avoid forming bonds between groups.

Homophily, selection, and choice in segregation models.

Schelling's 1971 work on the dynamics of segregation showed that even a small degree of homophily, the desire to live among like neighbors, can lead to a starkly segregated population. One of the driving factors for this result is that the notion of homophily used is based on group identities that are exogenous and immutable. In contrast, we consider a homophily that arises from the desire to be with neighbors who are behaviorally similar, not necessarily those who have the same group identity. The distinction matters because behaviors are neither exogenous nor immutable but choices that can change as individuals adapt to their neighborhoods. We show that in such an environment, integration rather than segregation is the typical outcome. However, the tendency toward adaptation and integration can be impeded when economic frictions in the form of income inequality and housing cost are present.

How people are exposed to neighborhoods racially different from their own.

In US cities, neighborhoods have long been racially segregated. However, people do not spend all their time in their neighborhoods, and the consequences of residential segregation may be tempered by the contact people have with other racial groups as they traverse the city daily. We examine the extent to which people's regular travel throughout the city is to places "beyond their comfort zone" (BCZ), i.e., to neighborhoods of racial composition different from their own-and why. Based on travel patterns observed in more than 7.2 million devices in the 100 largest US cities, we find that the average trip is to a neighborhood less than half as racially different from the home neighborhood as it could have been given the city. Travel to grocery stores is least likely to be BCZ; travel to gyms and parks, most likely; however, differences are greatest across cities. For the first ~10 km people travel from home, neighborhoods become increasingly more BCZ for every km traveled; beyond that point, whether neighborhoods do so depends strongly on the city. Patterns are substantively similar before and after COVID-19. Our findings suggest that policies encouraging more 15-min travel-that is, to amenities closer to the home-may inadvertently discourage BCZ movement. In addition, promoting use of certain "third places" such as restaurants, bars, and gyms, may help temper the effects of residential segregation, though how much it might do so depends on city-specific conditions.

Greenspaces And Cardiovascular Health.

Accumulating evidence suggests that living in areas of high surrounding greenness or even brief exposures to areas of high greenery is conducive to cardiovascular health, which may be related to the environmental, social, psychological, and physiological benefits of greenspaces. Recent data from multiple cross-sectional, longitudinal, and cohort studies suggest that living in areas of high surrounding greenness is associated with a lower risk of all-cause and cardiovascular mortality. High levels of neighborhood greenery have been linked also to a decrease in the burden of cardiovascular disease risk factors as reflected by lower rates of hypertension, dyslipidemia, and diabetes. Those who live in greener environments report better mental health and more frequent social interactions, which can benefit cardiovascular health as well. In this narrative review, we discuss evidence linking greenspaces to cardiovascular health as well as the potential mechanisms underlying the beneficial effects of greenspaces, including the impact of vegetation on air, noise and light pollution, ambient temperature, physical activity, mental health, and biodiversity. We review literature on the beneficial effects of acute and chronic exposure to nature on cardiovascular disease risk factors, inflammation and immune function, and we highlight the potential cardiovascular effects of biogenic volatile organic compounds that are emitted by trees and shrubs. We identify current knowledge gaps in this area and underscore the need for additional population studies to understand more clearly and precisely the link between greenness and health. Such understanding is urgently needed to fully redeem the promise of greenspaces in preventing adverse environmental exposures, mitigating the effects of climate change, and creating healthier living environments.

Host variables confound gut microbiota studies of human disease.

Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false positives is exacerbated by wide interindividual heterogeneity in microbiota composition1, probably due to population-wide differences in human lifestyle and physiological variables2 that exert differential effects on the microbiota. Here we infer the greatest, generalized sources of heterogeneity in human gut microbiota profiles and also identify human lifestyle and physiological characteristics that, if not evenly matched between cases and controls, confound microbiota analyses to produce spurious microbial associations with human diseases. We identify alcohol consumption frequency and bowel movement quality as unexpectedly strong sources of gut microbiota variance that differ in distribution between healthy participants and participants with a disease and that can confound study designs. We demonstrate that for numerous prevalent, high-burden human diseases, matching cases and controls for confounding variables reduces observed differences in the microbiota and the incidence of spurious associations. On this basis, we present a list of host variables that we recommend should be captured in human microbiota studies for the purpose of matching comparison groups, which we anticipate will increase robustness and reproducibility in resolving the members of the gut microbiota that are truly associated with human disease.

Signatures of cross-modal alignment in children's early concepts.

Whether supervised or unsupervised, human and machine learning is usually characterized as event-based. However, learning may also proceed by systems alignment in which mappings are inferred between entire systems, such as visual and linguistic systems. Systems alignment is possible because items that share similar visual contexts, such as a car and a truck, will also tend to share similar linguistic contexts. Because of the mirrored similarity relationships across systems, the visual and linguistic systems can be aligned at some later time absent either input. In a series of simulation studies, we considered whether children's early concepts support systems alignment. We found that children's early concepts are close to optimal for inferring novel concepts through systems alignment, enabling agents to correctly infer more than 85% of visual-word mappings absent supervision. One possible explanation for why children's early concepts support systems alignment is that they are distinguished structurally by their dense semantic neighborhoods. Artificial agents using these structural features to select concepts proved highly effective, both in environments mirroring children's conceptual world and those that exclude the concepts that children commonly acquire. For children, systems alignment and event-based learning likely complement one another. Likewise, artificial systems can benefit from incorporating these developmental principles.

Associations of Urban Blue and Green Spaces With Coronary Artery Calcification in Black Individuals and Disadvantaged Neighborhoods.

BACKGROUND: Proximity to urban blue and green spaces has been associated with improved cardiovascular health; however, few studies have examined the role of race and socioeconomic status in these associations. METHODS: Data were from the CARDIA study (Coronary Artery Risk Development in Young Adults). We included longitudinal measurements (1985-1986 to 2010-2011) of blue and green spaces, including percentage of blue space cover, distance to the nearest river, green space cover, and distance to the nearest major park. Presence of coronary artery calcification (CAC) was measured with noncontrast cardiac computed tomography in 2010 to 2011. The associations of blue and green spaces with CAC were assessed with generalized estimating equation regression with adjustment for demographics, individual and neighborhood socioeconomic status, health-related behaviors, and other health conditions. We conducted stratified analyses by race and neighborhood deprivation score to investigate whether the association varied according to social determinants of health. RESULTS: The analytic sample included 1365 Black and 1555 White participants with a mean±SD age of 50.1±3.6 years. Among Black participants, shorter distance to a river and greater green space cover were associated with lower odds of CAC (per interquartile range decrease [1.45 km] to the river: odds ratio [OR], 0.90 [95% CI, 0.84-0.96]; per 10 percentage-point increase of green space cover: OR, 0.85 [95% CI, 0.75-0.95]). Among participants in deprived neighborhoods, greater green space cover was associated with lower odds of CAC (per a 10 percentage-point increase: OR, 0.89 [95% CI, 0.80-0.99]), whereas shorter distance to the park was associated with higher odds of CAC (per an interquartile range decrease [5.3 km]: OR, 1.07 [95% CI, 1.00-1.15]). Black participants in deprived neighborhoods had lower odds of CAC with shorter distance to a river (per an interquartile range decrease: OR, 0.90 [95% CI, 0.82-0.98]) and greater green space cover (per a 10 percentage-point increase: OR, 0.85 [95% CI, 0.75-0.97]). There was no statistical interaction between the blue and green spaces and race or neighborhood characteristics in association with CAC. CONCLUSIONS: Longitudinally, shorter distance to a river and greater green space cover were associated with less CAC among Black participants and those in deprived neighborhoods. Shorter distance to a park was associated with increased odds of CAC among participants in deprived neighborhoods. Black participants residing in more deprived neighborhoods showed lower odds of CAC in association with greater exposure to river and green space cover.

Racial and Ethnic Differences in Bystander CPR for Witnessed Cardiac Arrest.

BACKGROUND: Differences in the incidence of cardiopulmonary resuscitation (CPR) provided by bystanders contribute to survival disparities among persons with out-of-hospital cardiac arrest. It is critical to understand whether the incidence of bystander CPR in witnessed out-of-hospital cardiac arrests at home and in public settings differs according to the race or ethnic group of the person with cardiac arrest in order to inform interventions. METHODS: Within a large U.S. registry, we identified 110,054 witnessed out-of-hospital cardiac arrests during the period from 2013 through 2019. We used a hierarchical logistic regression model to analyze the incidence of bystander CPR in Black or Hispanic persons as compared with White persons with witnessed cardiac arrests at home and in public locations. We analyzed the overall incidence as well as the incidence according to neighborhood racial or ethnic makeup and income strata. Neighborhoods were classified as predominantly White (>80% of residents), majority Black or Hispanic (>50% of residents), or integrated, and as high income (an annual median household income of >$80,000), middle income ($40,000-$80,000), or low income (<$40,000). RESULTS: Overall, 35,469 of the witnessed out-of-hospital cardiac arrests (32.2%) occurred in Black or Hispanic persons. Black and Hispanic persons were less likely to receive bystander CPR at home (38.5%) than White persons (47.4%) (adjusted odds ratio, 0.74; 95% confidence interval [CI], 0.72 to 0.76) and less likely to receive bystander CPR in public locations than White persons (45.6% vs. 60.0%) (adjusted odds ratio, 0.63; 95% CI, 0.60 to 0.66). The incidence of bystander CPR among Black and Hispanic persons was less than that among White persons not only in predominantly White neighborhoods at home (adjusted odds ratio, 0.82; 95% CI, 0.74 to 0.90) and in public locations (adjusted odds ratio, 0.68; 95% CI, 0.60 to 0.75) but also in majority Black or Hispanic neighborhoods at home (adjusted odds ratio, 0.79; 95% CI, 0.75 to 0.83) and in public locations (adjusted odds ratio, 0.63; 95% CI, 0.59 to 0.68) and in integrated neighborhoods at home (adjusted odds ratio, 0.78; 95% CI, 0.74 to 0.81) and in public locations (adjusted odds ratio, 0.73; 95% CI, 0.68 to 0.77). Similarly, across all neighborhood income strata, the frequency of bystander CPR at home and in public locations was lower among Black and Hispanic persons with out-of-hospital cardiac arrest than among White persons. CONCLUSIONS: In witnessed out-of-hospital cardiac arrest, Black and Hispanic persons were less likely than White persons to receive potentially lifesaving bystander CPR at home and in public locations, regardless of the racial or ethnic makeup or income level of the neighborhood where the cardiac arrest occurred. (Funded by the National Heart, Lung, and Blood Institute.).

Maternal Characteristics and Infant Outcomes by Hispanic Subgroup and Nativity:United States, 2021.

Objectives-This report presents comparisons of maternal characteristics and infant outcomes of Hispanic women and their infants by nativity (whether they were born in or outside the United States) for all Hispanic women and for the six largest Hispanic subgroups by nativity.

The Role of Neighborhood Air Pollution in Disparate Racial and Ethnic Asthma Acute Care Use.

Rationale: The share of Black or Latinx residents in a census tract remains associated with asthma-related emergency department (ED) visit rates after controlling for socioeconomic factors. The extent to which evident disparities relate to the within-city heterogeneity of long-term air pollution exposure remains unclear. Objectives: To investigate the role of intraurban spatial variability of air pollution in asthma acute care use disparity. Methods: An administrative database was used to define census tract population-based incidence rates of asthma-related ED visits. We estimate the associations between census tract incidence rates and 1) average fine and coarse particulate matter, nitrogen dioxide (NO2), and sulfur dioxide (SO2), and 2) racial and ethnic composition using generalized linear models controlling for socioeconomic and housing covariates. We also examine for the attenuation of incidence risk ratios (IRRs) associated with race/ethnicity when controlling for air pollution exposure. Measurements and Main Results: Fine and coarse particulate matter and SO2 are all associated with census tract-level incidence rates of asthma-related ED visits, and multipollutant models show evidence of independent risk associated with coarse particulate matter and SO2. The association between census tract incidence rate and Black resident share (IRR, 1.51 [credible interval (CI), 1.48-1.54]) is attenuated by 24% when accounting for air pollution (IRR, 1.39 [CI, 1.35-1.42]), and the association with Latinx resident share (IRR, 1.11 [CI, 1.09-1.13]) is attenuated by 32% (IRR, 1.08 [CI, 1.06-1.10]). Conclusions: Neighborhood-level rates of asthma acute care use are associated with local air pollution. Controlling for air pollution attenuates associations with census tract racial/ethnic composition, suggesting that intracity variability in air pollution could contribute to neighborhood-to-neighborhood asthma morbidity disparities.

A social perspective on perceived distances reveals deep community structure.

Community structure, including relationships between and within groups, is foundational to our understanding of the world around us. For dissimilarity-based data, leveraging social concepts of conflict and alignment, we provide an approach for capturing meaningful structural information resulting from induced local comparisons. In particular, a measure of local (community) depth is introduced that leads directly to a probabilistic partitioning conveying locally interpreted closeness (or cohesion). A universal choice of threshold for distinguishing strongly and weakly cohesive pairs permits consideration of both local and global structure. Cases in which one might benefit from use of the approach include data with varying density such as that arising as snapshots of complex processes in which differing mechanisms drive evolution locally. The inherent recalibrating in response to density allows one to sidestep the need for localizing parameters, common to many existing methods. Mathematical results together with applications in linguistics, cultural psychology, and genetics, as well as to benchmark clustering data have been included. Together, these demonstrate how meaningful community structure can be identified without additional inputs (e.g., number of clusters or neighborhood size), optimization criteria, iterative procedures, or distributional assumptions.

Environmental inequality in the neighborhood networks of urban mobility in US cities.

Research has made clear that neighborhoods impact the health and well-being of their residents. A related strand of research shows that neighborhood disadvantage is geographically clustered. Because the neighborhoods of low-income and minority populations tend to be more disadvantaged, neighborhood conditions help explain racial and socioeconomic inequalities. These strands of research restrict processes of neighborhood influence to operate only within and between geographically contiguous neighbors. However, we are underestimating the role of neighborhood conditions in explaining inequality if disadvantage extends beyond the residential and extralocal environments into a network of neighborhoods spanning the urban landscape based on where residents move within a city. I use anonymized mobile phone data to measure exposure to air pollution among residents of poor and minority neighborhoods in 88 of the most populous US cities. I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. Hispanic neighborhoods exhibit the greatest overall pollution burden, Black/White and Asian/White disparities are greatest at the network than residential scale, and the socioeconomic advantage of lower risk exposure is highest for residents from White neighborhoods. These inequalities are notable given recent declines in segregation and air pollution levels in American cities.

Concentrated incarceration and the public-housing-to-prison pipeline in New York City neighborhoods.

Using public housing developments as a strategic site, our research documents a distinct pathway linking disadvantaged context to incarceration-the public-housing-to-prison pipeline. Focusing on New York City Housing Authority (NYCHA) housing developments as a case study, we find that incarceration rates in NYCHA tracts are 4.6 times higher than those in non-NYCHA tracts. More strikingly, 94% of NYCHA tracts report rates above the median value for non-NYCHA tracts. Moreover, 17% of New York State's incarcerated population originated from just 372 NYCHA tracts. Compared with non-NYCHA tracts, NYCHA tracts had higher shares of Black residents and were significantly more disadvantaged. This NYCHA disadvantage in concentrated incarceration is also robust at different spatial scales. Our findings have implications for policies and programs to disrupt community-based pipelines to prison.

Systemic racism alters wildlife genetic diversity.

In the United States, systemic racism has had lasting effects on the structure of cities, specifically due to government-mandated redlining policies that produced racially segregated neighborhoods that persist today. However, it is not known whether varying habitat structures and natural resource availability associated with racial segregation affect the demographics and evolution of urban wildlife populations. To address this question, we repurposed and reanalyzed publicly archived nuclear genetic data from 7,698 individuals spanning 39 terrestrial vertebrate species sampled in 268 urban locations throughout the United States. We found generally consistent patterns of reduced genetic diversity and decreased connectivity in neighborhoods with fewer White residents, likely because of environmental differences across these neighborhoods. The strength of relationships between the racial composition of neighborhoods, genetic diversity, and differentiation tended to be weak relative to other factors affecting genetic diversity, possibly in part due to the recency of environmental pressures on urban wildlife populations. However, the consistency of the direction of effects across disparate taxa suggest that systemic racism alters the demography of urban wildlife populations in ways that generally limit population sizes and negatively affect their chances of persistence. Our results thus support the idea that limited capacity to support large, well-connected wildlife populations reduces access to nature and builds on existing environmental inequities shouldered by predominantly non-White neighborhoods.

Trajectory analysis of rhinitis in a birth cohort from lower-income New York City neighborhoods.

BACKGROUND: Rhinitis is a prevalent, chronic nasal condition associated with asthma. However, its developmental trajectories remain poorly characterized. OBJECTIVE: We sought to describe the course of rhinitis from infancy to adolescence and the association between identified phenotypes, asthma-related symptoms, and physician-diagnosed asthma. METHODS: We collected rhinitis data from questionnaires repeated across 22 time points among 688 children from infancy to age 11 years and used latent class mixed modeling (LCMM) to identify phenotypes. Once children were between ages 5 and 12, a study physician determined asthma diagnosis. We collected information on the following asthma symptoms: any wheeze, exercise-induced wheeze, nighttime coughing, and emergency department visits. For each, we used LCMM to identify symptom phenotypes. Using logistic regression, we described the association between rhinitis phenotype and asthma diagnosis and each symptom overall and stratified by atopic predisposition and sex. RESULTS: LCMM identified 5 rhinitis trajectory groups: never/infrequent; transient; late onset, infrequent; late onset, frequent; and persistent. LCMM identified 2 trajectories for each symptom, classified as frequent and never/infrequent. Participants with persistent and late onset, frequent phenotypes were more likely to be diagnosed with asthma and to have the frequent phenotype for all symptoms (P < .01). We identified interaction between seroatopy and rhinitis phenotype for physician-diagnosed asthma (P = .04) and exercise-induced wheeze (P = .08). Severe seroatopy was more common among children with late onset, frequent and persistent rhinitis, with nearly 25% of these 2 groups exhibiting sensitivity to 4 or 5 of the 5 allergens tested. CONCLUSIONS: In this prospective, population-based birth cohort, persistent and late onset, frequent rhinitis phenotypes were associated with increased risk of asthma diagnosis and symptoms during adolescence.