Neighborhood Characteristics Research Articles

State variation in neighborhood COVID-19 burden across the United States

BackgroundA lack of fine, spatially-resolute case data for the U.S. has prevented the examination of how COVID-19 infection burden has been distributed across neighborhoods, a key determinant of both risk and resilience. Without more spatially resolute data, efforts to identify and mitigate the long-term fallout from COVID-19 in vulnerable communities will remain difficult to quantify and intervene on.MethodsWe leveraged spatially-referenced data from 21 states collated through the COVID Neighborhood Project to examine the distribution of COVID-19 cases across neighborhoods and states in the U.S. We also linked the COVID-19 case data with data on the neighborhood social environment from the National Neighborhood Data Archive. We then estimated correlations between neighborhood COVID-19 burden and features of the neighborhood social environment.ResultsWe find that the distribution of COVID-19 at the neighborhood-level varies within and between states. The median case count per neighborhood (coefficient of variation (CV)) in Wisconsin is 3078.52 (0.17) per 10,000 population, indicating a more homogenous distribution of COVID-19 burden, whereas in Vermont the median case count per neighborhood (CV) is 810.98 (0.84) per 10,000 population. We also find that correlations between features of the neighborhood social environment and burden vary in magnitude and direction by state.ConclusionsOur findings underscore the importance that local contexts may play when addressing the long-term social and economic fallout communities will face from COVID-19.

Exploring the Impact of Multimodal Access on Property and Land Economies in Shanghai’s Inner Ring Districts: Leveraging Advanced Spatial Analysis Techniques

This study explores the impact of accessibility on property pricing and land economies by advanced spatial analysis techniques, focusing on Shanghai as a representative metropolis. Despite the impact of metro systems on residential property values, which has been frequently assessed, a research gap exists in understanding this phenomenon in Asian, particularly Chinese, urban contexts. Addressing this gap is crucial for shaping effective urban land use policy and improving the land economy rationally in China and similar settings facing urban challenges. To assess the impact of metro station accessibility on property prices in Shanghai, with extensive rail transit, and to deeply explore the overall impact of land value varieties driven by metro on urban development, we conducted a comprehensive analysis, with discussion about future aspirations for land planning and management along with landscape and facility design, and measures to improve land economy. The procedures involved creating neighborhood centroids to represent accessibility and using the Euclidean distance analysis to determine the shortest paths to metro stations. Our evaluation incorporated a hedonic pricing model, considering variables like neighborhood characteristics, housing attributes, and socio-economic factors. Advanced spatial analysis encompassing Ordinary Least Squares (OLS) regression and XGBoost analysis were employed to explore spatial effects, and Geographically Weighted Regression (GWR) helped examine spatial patterns and address autocorrelation challenges. Results revealed a negative association between distance to metro station and property prices, indicating a non-linear and spatially clustered relationship and heterogeneous spatial pattern. We dissected the non-linear results in detail, which complemented the conclusion in existing research. This study provides valuable insights into the dynamic interplay between metro accessibility and housing market behaviors in a significant Asian urban context, offering targeted suggestions for urban planners and governors to decide on more reasonable land use planning and management strategies, along with landscape and infrastructure design, to promote not only the healthy growth of the real estate market but also the sustainable urban development in China and similar regions.

Personal exposure to ultrafine particles in multiple microenvironments among adolescents.

Experimental studies suggest ultrafine particles (UFPs), the smallest size fraction of particulate matter, may be more toxic than larger particles, however personal sampling studies in children are lacking. The objective of this analysis was to examine individual, housing, and neighborhood characteristics associated with personal UFP concentrations as well as the differences in exposures that occur within varying microenvironments. We measured weekly personal UFP concentrations and GPS coordinates in 117 adolescents ages 13-17 to describe exposures across multiple microenvironments. Individual, home, and neighborhood characteristics were collected by caregiver completed questionnaires. Participants regularly exposed to secondhand tobacco smoke had significantly higher indoor concentrations of UFPs compared to participants who were not. We observed that the 'home' microenvironment dominated the relative contribution of overall UFP concentrations and sampling time, however, relative proportion of integrated UFP exposure were higher in 'other' environments. In this study, we employed a novel panel study design, involving real-time measurement of UFP exposure within the multiple microenvironments of adolescents. We found a combination of personal sampling and detailed activity patterns should be used in future studies to accurately describe exposure-behavior relationships.

Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium

Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Early-life exposures to PM2.5 and NO2 according to participants' birth address. Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

Evaluation of the Impact of Informal Settlements on the Physical and Mental Health of Residents—Case Study Santa Marta—Bogotá, Colombia

The growth of the informal city in Latin America has caused its own dynamics related to urban unsustainability due to the disorderly occupation of the territory. The precarious characteristics of informal neighborhoods have increased the mortality processes in their inhabitants, increasing the poverty and marginality indexes in Latin American urban settlements. This work was developed within the international research project “Modeling informality in Latin America based on indicators of sustainable urban development. Case study Yomasa, Bogotá-Colombia”. This work was developed under the mixed research approach which allowed focusing on a nested concurrent design of dominant model (DIAC), which was carried out in the Santa Marta sector of the locality of Ciudad Bolivar, in Bogotá Colombia, with the participation of 20 people from the studied community and supported by 16 students of Civil Engineering of the Catholic University of Colombia. The work resulted in a total of 31 indicators related to neighborhood informality, 17 impacts on the territory, and 8 pathologies, establishing the intrinsic relationship between informality, poverty, and public health of the inhabitant at the urban level.

The role of neighborhood characteristics in explaining political party residential segregation

High levels of neighborhood political residential segregation have recently been documented for the U.S. This has raised concerns, based on the argument that more politically homogeneous neighborhoods promote extremism and ideological intensity, resulting in this same extremism displayed by elected politicians. Using tens of thousands of single-family home sales from South Florida, our purpose is to examine the extent to which neighborhood observable descriptors can explain party segregation. Our results reveal significant differences between Democrat and Republican home buyers in the types of neighborhoods they choose. In comparison to Democrats, Republicans more frequently chose neighborhoods where a larger percentage of workers have short commutes, homes are on average larger in size, there are fewer restaurants and shops, population density is lower, and Hispanics are a smaller percentage of residents. These differences are found to be important in explaining neighborhood party segregation.

Evaluating Sustainable Mobility: Motorized and Non-motorized Modes in Suburban Areas of Thailand.

The impact of sustainable mobility may be considered through the mode of non-motorization, which may vary by spatial environmental conditions, especially accessibility by active mobility in a necessarily safe, comfortable, and pleasant atmosphere. Sustainable mobility comprises willingness to allow commuting behaviors on non-motorized travel for safety and green ethics. These chiefly participate to create livable places, improve health and well-being, and promote quality of life and economic growth. By contrast, an impoverished street environment decreases the possibility of active mobility and relies on motorization. It is essential to explore the perception of road users through diverse environmental features of street networks and sidewalks directly affecting road user behavior and preferences about motorization and non-motorization. This study evaluated multi-indicators of sustainable urban mobility (SUM) for a group of road users, with data gathered by questionnaire-based survey. 1,998 Pathum Thani Province inhabitants in Thailand were asked to evaluate their neighborhood characteristics by SUM indicators. In addition to different social dimensions and socioeconomic backgrounds, transportation characteristics among diverse trip makers and different perceptions of mobility indicators were classified by factor analysis using principal components and spatial visualization. Results were that traffic management, including intersection controls and signage, as well as information, sidewalk, management, and personal mobility choices, is a key strategy to improve sustainable mobility. This is achieved by tailoring solutions to achieve a modal shift prioritized over other supportive facilities.

Too Privileged to Move? Neighbourhood Perception and Relocation Intention in China's Gated Communities

AbstractThe association between neighbourhood characteristics and residential relocation is a classic topic in urban studies. In China, where gated communities (GCs) have become a highly popular residential form, how and to what extent residents’ perceptions of GCs affect their relocation intention has not been quantitatively examined. Drawing on a large‐scale household survey conducted in Shanghai, we use multi‐level logistic regression models to examine the impact of the perceptions of neighbourhood environment, attachment and gatedness on relocation intention. Our findings are threefold: (1) the greater the perceived improvement of the neighbourhood environment, the lower the likelihood of relocation intention; (2) respondents with higher levels of neighbourhood attachment tend to have lower relocation intention and (3) respondents living in neighbourhoods with higher levels of gatedness are less likely to have relocation intention. This research contributes to the literature of neighbourhood studies and GCs by quantifying the ramification of entrenched ‘gated mindset’ in urban China.

A Spatial Regression Model for Predicting Prices of Short-Term Rentals in Athens, Greece

Short-term house rentals constitute a growing component of tourist accommodation in several countries and the determination of factors affecting rents is an important consideration in relevant studies. Short-term rentals have shown increasing trends in the city of Athens, Greece; however, this activity has not been adequately studied. In this paper, spatial data of Airbnb rentals in Athens are analyzed in order to indicate the factors which are important for the spatial variation of rents. Factors such as property capacity, host attributes and review characteristics are considered. In addition, several locational attributes are examined. Regression analysis techniques are used to predict the cost per night, according to various explanatory factors, while the results of two models are presented: ordinary least squares (OLS) and geographically weighted regression (GWR). The results of the OLS model indicate several factors determining the rent, including capacity and host characteristics, as well as locational attributes. The GWR model produces more accurate results with a smaller number of independent variables. For the residuals analysis several additional amenities were examined that resulted in a small impact on rents. The unexplained spatial variation of rents may be attributed to neighborhood characteristics, socioeconomic conditions and special characteristics of the rentals.

Somali refugees in urban neighborhoods: an eco-social study of mental health and wellbeing.

Impact of pre-migration trauma and post-migration settlement on refugee mental health and wellbeing is well-documented. However, little research has focused on the specific places where refugees settle and spend their daily lives within the post-migration context. This study adopts an eco-social perspective to explore the relationship between urban neighborhoods and refugee mental health and wellbeing. We conducted twenty-six qualitative interviews with Somali refugees in London and Bristol in the UK. The transcripts were coded using an inductive approach and analyzed through thematic analysis. Somali refugees navigate a complex urban environment comprising various neighborhood features which include important places near home, interactions with neighbors, and community spaces. While these features afford them resources to improve mental health and wellbeing, they also present challenges such as high urban density, exposure to violence or discrimination, and neighborhood disorder. The societal and physical features of urban neighborhoods intersect with refugee experiences of adversity, trauma and stress over time. As eco-social niches, urban neighborhoods are both accommodating, safe and familiar, as well as alien, threatening and unwelcoming. To support mental health and wellbeing and ensure successful settlement, it is essential to recognize the agency of refugees and provide continuous support throughout the entire asylum process and after, ensuring stable and safe living conditions.

Social contacts, neighborhoods and individual unemployment risk

PurposeThe aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.Design/methodology/approachWe use 2006–2017 data from the Household Income and Labour Dynamics in Australia (HILDA) survey and a dynamic random-effects model to describe the evolution of individual unemployment status over time.FindingsOnce controlled for the local context where individuals live and create friendships, we find that above-average social contacts reduce unemployment persistence. However, social contacts seem to be slightly less effective in deprived neighborhoods. These findings are consistent with the idea that individuals obtain information about job opportunities through a network of social contacts, and unemployment may lead to a decay of social capital, making it more difficult to find employment in future periods. Our results also show that neighborhood deprivation increases individual unemployment risk, while above-average neighborhood cohesion reduces the probability of unemployment in deprived neighborhoods.Originality/valueAlthough many studies have been published on unemployment persistence, to the best of the author's knowledge, this is the first study quantifying the impact of social contacts on unemployment persistence. The study also offers fresh empirical evidence on the impact of neighborhood characteristics on unemployment risk.

The Role of the Perceived Neighborhood Social Environment on Adolescent Sedentary Behavior and Physical Activity: Findings from Add Health.

Few studies have examined the role of perceived neighborhood characteristics such as neighborhood safety, social cohesion, and contentedness on sedentary behavior (SB) and physical activity (PA) among adolescents. Furthermore, no studies have investigated how these associations are moderated by gender and race. This study aimed to examine the associations of the perceived neighborhood social environment with (SB) and moderate-to-vigorous physical activity (MVPA). Data from 6504 adolescents (aged 15.4 ± 0.03 years) who participated in the National Longitudinal Study of Adolescent Health was used. SB and PA were considered continuously and dichotomously. PNSE variables include safety, social cohesion, and contentedness, where higher values of PNSE indicate a more favorable neighborhood perception. Weighted linear and logistic regression models were used to examine the association of PNSE with continuous total SB (hours/week) and MVPA (bouts/week), and binary excessive SB (14h/week) and meeting MVPA guidelines (≥ 5 bouts/week), respectively. Associations were stratified by gender and race to test moderation effects. Models were adjusted for demographic, health, parental, and neighborhood covariates. This study found that neighborhood safety and contentedness were negatively associated with SB, whereas neighborhood social cohesion and contentedness were positively associated with PA. Gender-specific and race-specific results remained somewhat consistent with overall findings; however, neighborhood safety was not associated with SB among female and non-White adolescents, respectively. Similarly, neighborhood safety and contentedness were not associated with MVPA for non-White adolescents. Findings suggest that an adolescent's neighborhood environment, gender, and race should be considered when implementing strategies to reduce SB and increase PA.

Neighbourhood Health Inequalities between Ethnic Groups in England: An Application of Ecological Inference

Ecological inference has had primarily political science applications, but this study considers an application to assess variations in neighbourhood mental health between population sub-groups. The methodology used has particular utility when neighbourhood health data are available only in aggregate form, without disaggregation (e.g. by ethnic or socioeconomic group). The ecological inference approach is shown to provide insights into contextual effects, where neighbourhood features influence disease variations between sub-groups (e.g. the ethnic density effect on psychosis among non-white groups). The present study also highlights important issues raised by the data’s geographic framework, namely strong spatial clustering in the outcome, and compares spatial error and spatial lag methods to represent this spatial patterning appropriately. The study considers neighbourhood variations in psychosis between four ethnic groups, with a spatial framework provided by 32,844 small areas (Lower Super Output Areas, LSOAs) in England.

The association between neighborhood-level social fragmentation and distressing psychotic-like experiences in early adolescence: the moderating role of close friends.

Early exposure to neighborhood social fragmentation has been shown to be associated with schizophrenia. The impact of social fragmentation and friendships on distressing psychotic-like experiences (PLE) remains unknown. We investigate the relationships between neighborhood social fragmentation, number of friends, and distressing PLE among early adolescents. Data were collected from the Adolescent Brain Cognitive Development Study. Generalized linear mixed models tested associations between social fragmentation and distressing PLE, as well as the moderating role of the number of total and close friends. Participants included 11 133 adolescents aged 9 to 10, with 52.3% being males. Greater neighborhood social fragmentation was associated with higher levels of distressing PLE (adjusted β = 0.05; 95% CI: 0.01-0.09). The number of close but not total friends significantly interacted with social fragmentation to predict distressing PLE (adjusted β = -0.02; 95% CI: -0.04 to <-0.01). Among those with fewer close friends, the association between neighborhood social fragmentation and distressing PLE was significant (adjusted β = 0.07; 95% CI: 0.03-0.11). However, among those with more close friends, the association was non-significant (adjusted β = 0.03; 95% CI: -0.01 to 0.07). Greater neighborhood social fragmentation is associated with higher levels of distressing PLE, particularly among those with fewer close friends. Further research is needed to disentangle aspects of the interaction between neighborhood characteristics and the quality of social interactions that may contribute to psychosis, which would have implications for developing effective interventions at the individual and community levels.

Moderating Role of Neighborhood Environment in the Associations Between Hearing Loss and Cognitive Challenges Among Older Adults: Evidence From US National Study.

This study examined the associations between hearing loss and cognitive challenges among community-dwelling older adults and whether neighborhood characteristics (physical disorder and low social cohesion) moderated the associations. Cross-sectional national data from Round 11 of the National Health and Aging Trends Study were adopted (N = 2,515). Multinomial logistic regressions were used to examine associations among variables and interactive analyses were conducted to examine moderating effects. Results indicated significant relationships between the experience of hearing loss and possible dementia and between severe or profound hearing loss and probable dementia. Interactive models suggested that residing in neighborhoods with physical disorder and low social cohesion were negatively associated with possible dementia among older adults with moderate and severe or profound hearing loss, respectively, compared to those without hearing loss. Findings underscore the necessity of environmental and social interventions to enhance cognitive health among older adults with varying degrees of hearing challenges.

Multiscale dilated denoising convolution with channel attention mechanism for micro-seismic signal denoising

Denoising micro-seismic signals is paramount for ensuring reliable data for localizing mining-related seismic events and analyzing the state of rock masses during mining operations. However, micro-seismic signals are commonly contaminated by various types of complex noise, which can hinder micro-seismic accurate P-wave pickup and analysis. In this study, we propose the Multiscale Dilated Convolutional Attention denoising method, referred to as MSDCAN, to eliminate complex noise interference. The MSDCAN denoising model consists of an encoder, an improved attention mechanism, and a decoder. To effectively capture the neighborhood features and multiscale features of the micro-seismic signal, we construct an initial dilated convolution block and a multiscale dilated convolution block in the encoder, and the encoder focuses on extracting the relevant feature information, thus eliminating the noise interference and improving the signal-to-noise ratio (SNR). In addition, the attention mechanism is improved and introduced between the encoder and decoder to emphasize the key features of the micro-seismic signal, thus removing the complex noise and further improving the denoising performance. The MSDCAN denoising model is trained and evaluated using micro-seismic data from Stanford University. Experimental results demonstrate an impressive increase in SNR by 11.237 dB and a reduction in root mean square error (RMSE) by 0.802. Compared to the denoising results of the DeepDenoiser, CNN-denoiser and Neighbor2Neighbor methods, the MSDCAN denoising model outperforms them by enhancing the SNR by 2.589 dB, 1.584 dB and 2dB, respectively, and reducing the RMSE by 0.219, 0.050 and 0.188, respectively. The MSDCAN denoising model presented in this study effectively improves the SNR of micro-seismic signals, offering fresh insights into micro-seismic signal denoising methodologies.

Neighborhood characteristics and HIV treatment outcomes: A scoping review.

Recognizing challenges faced by people living with HIV is vital for improving their HIV treatment outcomes. While individual-level interventions play a crucial role, community factors can shape the impact of individual interventions on treatment outcomes. Understanding neighborhood characteristics' association with HIV treatment outcomes is crucial for optimizing effectiveness. This review aims to summarize the research scope on the association between neighborhood characteristics and HIV treatment outcomes. The databases PubMed, CINAHL (EBSCOhost), Embase (Elsevier), and PsychINFO (EBSCOhost) were searched from the start of each database to Nov 21, 2022. Screening was performed by three independent reviewers. Full-text publications of all study design meeting inclusion criteria were included in the review. There were no language or geographical limitations. Conference proceedings, abstract only, and opinion reports were excluded from the review. The search yielded 7,822 publications, 35 of which met the criteria for inclusion in the review. Studies assessed the relationship between neighborhood-level disadvantage (n = 24), composition and interaction (n = 17), social-economic status (n = 18), deprivation (n = 16), disorder (n = 8), and rural-urban status (n = 7) and HIV treatment outcomes. The relationship between all neighborhood characteristics and HIV treatment outcomes was not consistent across studies. Only 7 studies found deprivation had a negative association with HIV treatment outcomes; 6 found that areas with specific racial/ethnic densities were associated with poor HIV treatment outcomes, and 5 showed that disorder was associated with poor HIV treatment outcomes. Three studies showed that rural residence was associated with improved HIV treatment outcomes. There were inconsistent findings regarding the association between neighborhood characteristics and HIV treatment outcomes. While the impact of neighborhood characteristics on disease outcomes is highly recognized, there is a paucity of standardized definitions and metrics for community characteristics to support a robust assessment of this hypothesis. Comparative studies that define and assess how specific neighborhood indicators independently or jointly affect HIV treatment outcomes are highly needed.

Assessing Crime History as a Predictor: Exploring Hotspots of Violent and Property Crime in Malmö, Sweden

Objectives: Assessing the predictive accuracy of using prior crime, place attributes, ambient population, community structural, and social characteristics, in isolation and combined when forecasting different violent and property crimes. Method: Using multilevel negative binomial regression, crime is forecasted into the subsequent year, in 50-m grid-cells. Incidence rate ratio (IRR), Prediction Accuracy Index (PAI), and Prediction Efficacy Index (PEI*) are interpreted for all combined crime generators and community characteristics. This study is partially a test of a crude version of the Risk Terrain Modeling technique. Results: Where crime has been in the past, the risk for future crime is higher. Where characteristics conducive to crime congregate, the risk for crime is higher. Community structural characteristics and ambient population are important for some crime types. Combining variables increases the accuracy for most crime types, looking at the IRR. Taking the geographical area into account, crime history in combination with both place- and neighborhood characteristics reaches similar accuracy as crime history alone for most crime types and most hotspot cutoffs. Conclusions: Crime history, place-, and neighborhood-level attributes are all important when trying to accurately forecast crime, long-term at the micro-place. Only counting past crimes, however, still does a really good job.

The Association of Alcohol Outlet Density With Alcohol Intake: The Multiethnic Cohort.

Neighborhood characteristics have been shown to influence lifestyle behaviors. Here we characterized alcohol outlet density in Los Angeles County, CA, and Hawaii and assessed the association of alcohol outlet density with self-reported alcohol intake in the Multiethnic Cohort. Participants (n = 178,977) had their addresses geocoded at cohort entry (1993-1996) and appended to block group-level alcohol outlet densities (on- and off-premises). Multinomial logistic regression was performed to assess the association between self-reported alcohol intake and on- and off-premise alcohol outlet densities by each state. Stratified analysis was conducted by sex, race, and ethnicity. Overall, we did not find associations between alcohol outlet density and self-reported alcohol intake in Los Angeles County, but we found that on-premise alcohol outlets were associated with 59% (odds ratio [OR] = 1.59, 95% CI [1.29, 1.96]) increased odds of consuming more than two drinks per day in Hawaii. Women living in neighborhoods with a high density of on-premise alcohol outlets (Los Angeles County: OR = 1.15, 95% CI [0.95, 1.40]; Hawaii: OR = 2.07, 95% CI [1.43, 3.01]) had an increased odds of more than two drinks per day. This study suggests that neighborhood factors are associated with individual-level behaviors and that multilevel interventions may be needed.

Association of Neighborhood Opportunity with Infant Brain Activity and Cognitive Development.

Neighborhood socioeconomic disadvantage is associated with lower neurocognitive scores and differences in brain structure among school-age children. Associations between positive neighborhood characteristics, infant brain activity, and cognitive development are underexplored. We examined direct and indirect associations between neighborhood opportunity, brain activity, and cognitive development. This longitudinal cohort study included infants from 2 primary care clinics in Boston and Los Angeles. Using a sample of 65 infants, we estimated path models to examine associations between neighborhood opportunity (measured by the Child Opportunity Index), infant electroencephalography (EEG) at 6 months, and infant cognitive development (measured using the Mullen Scales of Early Learning) at 12 months. A mediation model tested whether EEG power explained associations between neighborhood opportunity and infant cognition. Neighborhood opportunity positively predicted infant absolute EEG power across multiple frequency bands: low ( b = 0.12, 95% CI 0.01-0.24, p = 0.04, = 0.21); high ( b = 0.11, 95% CI 0.01-0.21, p = 0.03, = 0.23); ( b = 0.10, 95% CI 0.00-0.19, p = 0.04, = 0.20); and ( b = 0.12, 95% CI 0.02-0.22, p = 0.02, = 0.24). The results remained statistically significant after applying a Benjamini-Hochberg false discovery rate of 0.10 to adjust for multiple comparisons. No significant associations emerged between neighborhood opportunity, relative EEG power, and infant cognition. Mediation was not significant. Neighborhood opportunity is positively associated with some forms of infant brain activity, suggesting that positive neighborhood characteristics may play a salient role in early development.