Objective Neighborhood Research Articles

What Makes a Liveable Neighborhood? Role of Socio-Demographic, Dwelling, and Environmental Factors and Participation in Finnish Urban and Suburban Areas.

Quality of residential area, or neighborhood, is one determinant of overall quality of life and associated with health and health behavior. Ensuring that urban and suburban neighborhoods remain liveable and comfortable to reside in is a challenge amidst growing urbanization. Neighborhood quality has been associated with socio-demographic, dwelling-related, and subjective and objective neighborhood factors. However, only a few studies have additionally included participation in neighborhood decision-making and examined whether these associations are stronger among residents who are more settled in the neighborhood. We examined whether subjectively and objectively measured environmental factors and participation are associated with perception of neighborhood liveability and possible effect moderators. We analyzed survey data collected in 2021 among adults (aged 18-97) living in suburbs and urban centers in five Finnish cities (n = 2057; response rate 34%) with logistic regression models. Almost 80% of the respondents perceived their neighborhood as liveable or very liveable. The following factors were most strongly associated with perceiving the neighborhood as liveable: low area-level socioeconomic deprivation; central urban zone; green view from home; satisfaction with neighborhood safety, green areas, blue areas, and maintenance of traffic routes; and good or very good possibilities to influence decisions regarding the neighborhood. Only a few interactions between indicators of being more settled in the neighborhood (e.g., age group and dwelling ownership) modified these associations. In all, our study suggests that to maintain liveability, urban or community planning should consider local residents' favorable perceptions of safety, recreational areas, and engagement in decision-making.

What characteristics modify the relation of neighborhood walkability and walking behavior in older adults?

Abstract Background and Objective Neighborhood walkability can influence walking behaviors in older adults. However, its associations of walkability with walking may differ by demographic, socioeconomic, health, social, and residential characteristics due to factors such as increased vulnerability to environmental factors or to increased resilience. Research Design and Methods In a sample of older adults (n = 493, median age=82 (range 78-89), 56% female, 31% Black), a walkability index was derived from audits of Google Street View images of participants’ immediate neighborhoods. Walking was self-reported in the past week. Effect modifiers by demographic (age, race, gender, marital status), socioeconomic (education, income), health (gait speed, falls, knee pain, depressive symptoms, cognitive status, perceived energy), social (driving status, social engagement), and residential/neighborhood (residence type, neighborhood socioeconomic status, population density) characteristics were assessed by interaction terms in logistic regression models, adjusted for gender, race, gait speed, prior falls, high depressive symptoms, currently driving, and cognitive status. When effect modification was suggested (p for interaction <0.1), adjusted analyses of walkability with walking stratified on the effect modifier were conducted. Results In this sample, 59% walked in the past week and greater walkability was associated with greater odds of walking (OR = 1.16, 95% CI: 1.01-1.34). This association (p for interaction range 0.002-0.07) was present for those who were not currently married (OR = 1.35, 95% CI: 1.17-1.56), who reported knee pain (OR = 1.40, 95% CI: 1.14-1.72)) or high depressive symptoms (OR = 1.30, 95% CI: 1.06-1.60), or who had declining cognitive function (OR = 1.30, 95% CI: 1.09-1.55). Discussion and Implications High walkability may influence physical activity, particularly for those with vulnerabilities related to social, pain, and brain health characteristics. These results should inform neighborhood planning and targeted interventions for vulnerable older adults.

Psychosocial Risks and Adolescent Mental Health: The Moderating Role of Objective Neighborhood Characteristics

PurposeAlthough previous studies have examined the association between youth psychosocial risks and their perceptions of their neighborhood, it is unclear how objective neighborhood characteristics are associated with psychosocial risks and mental health symptoms among adolescents. We investigated how neighborhood characteristics moderate the relationship between youth psychosocial characteristics and mental health symptoms. MethodsThis cross-sectional study examined 13,837 emergency department visits by 14–18-year-olds who completed a standardized Behavioral Health Screening in a tertiary pediatric hospital in Philadelphia from 2013 to 2020. Psychosocial risk factors and mental health symptoms were assessed based on self-reported survey responses. We characterized neighborhoods as low-, moderate-, and high-stress based on gun violence incidence from 2013 to 2020 and the census tract–level Child Opportunity Index. Mixed effects logistic regression and Poisson models were used to examine moderation effects. ResultsThe 9,814 included patients were 64% female and 64% non-Hispanic Black. The following psychosocial risk factors were associated with two to eight times higher odds of depressive symptoms and suicide risk: exposure to trauma, bullying at school, at-risk substance use, fighting, and retaliation. Adolescents living in high-stress neighborhoods were twice as likely to report fighting and retaliation and reported more psychosocial risk factors than those in low-stress neighborhoods. Odds of mental health symptoms increased with the number of psychosocial risk factors, particularly in youth from low-stress neighborhoods. DiscussionObjective neighborhood characteristics had a significant interaction effect on the relationship between psychosocial risks and depression and suicide risk among adolescents seeking care in a pediatric emergency department.

Perceived but not objective measures of neighborhood safety and food environments are associated with longitudinal changes in processing speed among urban older adults

BackgroundAlthough a growing body of literature documents the importance of neighborhood effects on late-life cognition, little is known about the relative strength of objective and subjective neighborhood measures on late-life cognitive changes. This study examined effects of objective and subjective neighborhood measures in three neighborhood domains (neighborhood safety, physical disorder, food environments) on longitudinal changes in processing speed, an early marker of cognitive aging and impairment.MethodsThe analysis sample included 306 community-dwelling older adults enrolled in the Einstein Aging Study (mean age = 77, age range = 70 to 91; female = 67.7%; non-Hispanic White: 45.1%, non-Hispanic Black: 40.9%). Objective and subjective measures of neighborhood included three neighborhood domains (i.e., neighborhood safety, physical disorder, food environments). Processing speed was assessed using a brief Symbol Match task (unit: second), administered on a smartphone device six times a day for 16 days and repeated annually for up to five years. Years from baseline was used as the within-person time index.ResultsResults from mixed effects models showed that subjective neighborhood safety (β= -0.028) and subjective availability of healthy foods (β= -0.028) were significantly associated with less cognitive slowing over time. When objective and subjective neighborhood measures were simultaneously examined, subjective availability of healthy foods remained significant (β= -0.028) after controlling for objective availability of healthy foods. Associations of objective neighborhood crime and physical disorder with processing speed seemed to be confounded by individual-level race and socioeconomic status; after controlling for these confounders, none of objective neighborhood measures showed significant associations with processing speed.ConclusionSubjective neighborhood safety and subjective availability of healthy foods, rather than objective measures, were associated with less cognitive slowing over time over a five-year period. Perception of one’s neighborhood may be a more proximal predictor of cognitive health outcomes as it may reflect one’s experiences in the environment. It would be important to improve our understanding of both objective and subjective neighborhood factors to improve cognitive health among older adults.

Examining the nonlinear relationship between neighborhood environment and residents' health

Although numerous studies have revealed linear associations between the urban environment and health, the nonlinear effects of subjective and objective neighborhood environment on health have been under-researched. Using Beijing as a case study, this study employs the random forest method to investigate the nonlinear relationship between subjective/objective neighborhood environment and physical/mental health, respectively. The findings indicate that the subjective environment is the most important for both physical and mental health, and subjective air and noise pollution are the key factors. Neighborhood environmental variables have nonlinear correlations with health. Improved perception of facility accessibility is positively associated with physical health, whereas extremely high levels of accessibility may inversely decrease the probability of reporting good health. Road connectivity and bus stop density exhibit inverted U-shaped patterns with physical health and mental health, separately. Furthermore, the study highlights different dimensions of green space affect residents' health in diverse ways.

Local neighborhood encodings for imbalanced data classification

This paper aims to propose Local Neighborhood Encodings (LNE)-a hybrid data preprocessing method dedicated to skewed class distribution balancing. The proposed LNE algorithm uses both over- and undersampling methods. The intensity of the methods is chosen separately for each fraction of minority and majority class objects. It is selected depending on the type of neighborhoods of objects of a given class, understood as the number of neighbors from the same class closest to a given object. The process of selecting the over- and undersampling intensities is treated as an optimization problem for which an evolutionary algorithm is used. The quality of the proposed method was evaluated through computer experiments. Compared with SOTA resampling strategies, LNE shows very good results. In addition, an experimental analysis of the algorithms behavior was performed, i.e., the determination of data preprocessing parameters depending on the selected characteristics of the decision problem, as well as the type of classifier used. An ablation study was also performed to evaluate the influence of components on the quality of the obtained classifiers. The evaluation of how the quality of classification is influenced by the evaluation of the objective function in an evolutionary algorithm is presented. In the considered task, the objective function is not de facto deterministic and its value is subject to estimation. Hence, it was important from the point of view of computational efficiency to investigate the possibility of using for quality assessment the so-called proxy classifier, i.e., a classifier of low computational complexity, although the final model was learned using a different model. The proposed data preprocessing method has high quality compared to SOTA, however, it should be noted that it requires significantly more computational effort. Nevertheless, it can be successfully applied to the case as no very restrictive model building time constraints are imposed.

NRENet: Neighborhood removal-and-emphasis network for ship detection in SAR Images

In recent years, object detection in Synthetic-Aperture Radar (SAR) images still faces many challenges, especially for ship detection. Small or dense ships are vulnerable to the interference of complex scenes such as ports and land. In feature extraction, a large amount of redundant information on the feature map will further reduce the network’s attention to small-sized ships. Therefore, in this paper, we propose a network called neighborhood removal-and-emphasis network (NRE-Net), including an object neighborhood removal (ONR) strategy and a neighborhood feature emphasis (NFE) module. Among them, the ONR strategy directly removes the complex background information around the ship before feature extraction, only retaining effective contextual neighborhoods conducive to ship detection and avoiding the interference of complex background information on the network. The NFE module is based on ONR to extract features and form a weight map of small-sized ships or complex images. This module can adaptively recognize the detection neighborhood of each ship and highlight the detection ship on the feature map. Our network has validated the effectiveness of the method on multiple SAR ship datasets and improved the object AP for each size. Our code is available at: https://github.com/Xidian-AIGroup190726/NRENet.

Contour Extraction of UAV Point Cloud Based on Neighborhood Geometric Features of Multi-Level Growth Plane

The extraction of UAV building point cloud contour points is the basis for the expression of a three-dimensional lightweight building outline. Previous unmanned aerial vehicle (UAV) building point cloud contour extraction methods have mainly focused on the expression of the roof contour, but did not extract the wall contour. In view of this, an algorithm based on the geometric features of the neighborhood points of the region-growing clustering fusion surface is proposed to extract the boundary points of the UAV building point cloud. Firstly, the region growth plane is fused to obtain a more accurate segmentation plane. Then, the neighboring points are projected onto the neighborhood plane and a vector between the object point and neighborhood point is constructed. Finally, the azimuth of each vector is calculated, and the boundary points of each segmented plane are extracted according to the difference in adjacent azimuths. Experiment results show that the best boundary points can be extracted when the number of adjacent points is 24 and the difference in adjacent azimuths is 120. The proposed method is superior to other methods in the contour extraction of UAV buildings point clouds. Moreover, it can extract not only the building roof contour points, but also the wall contour points, including the window contour points.

Exploring young people’s views of their local area related to the 20-minute neighbourhood policy: a national cross-sectional study

ABSTRACT This study aimed to examine how young people subjectively perceive their local neighbourhoods and compare these perceptions with objective data regarding access to amenities aligned with features of the 20-minute neighbourhood (20MN) policy. Objective data (n:287 aged 12-18 years) were gathered through an online adaptation of the Place Standard Tool for Young People in Scotland. Subjective data concerning access to ten amenities in line with the 20MN concept, along with crime statistics, area-level deprivation and urbanicity were spatially linked. The association between perceptions of localities and factors such as gender, as well as both subjective and objective neighbourhood assessments were examined. Young people were most satisfied with nature and active travel in their local area. Conversely, their satisfaction was lowest for active travel to school. Rural young people were more dissatisfied with their localities. Agreement was observed between satisfaction with their 20 neighbourhoods and objective data indicating the presence of frequent public transportation, recreational spaces, and access to services. In conclusion, our study highlights the importance of amenities in healthy urban planning, showing a positive impact on young people’s perceptions. Additionally, we uncover a connection between crime perceptions and area-level crime variables, potentially influencing health outcomes.

NEIGHBORHOOD QUALITY AND WEEKLY PATTERNS OF PHYSICAL ACTIVITY AMONG BLACK AND WHITE ADULTS

Abstract Engaging in regular moderate to vigorous physical activity across the week is recommended for maintaining health. This analysis examined whether objective and subjective neighborhood quality was associated with different patterns of weekly physical activity across the week among middle and older Black and white adults. We leveraged data from the National Study of Daily Experiences (NSDE), in which 833 Black and white American adults (Mage = 62.65; n Black = 167) reported their daily moderate to vigorous physical activity across eight consecutive days. The objective and subjective measures of neighborhood quality were the area deprivation index (ADI) and personal belief in the neighborhood, respectively. Hypotheses were tested using the latent class analysis (LCA) framework. Weekly patterns of daily physical activity were classified into four different groups: Active Every Day (group size = 35.75%), Active on Weekdays (26.63%), Active on the Weekend (11.76%), and Less Active (15.85%). Lower ADI rankings, but not personal beliefs about one’s neighborhood, were associated with a higher probability of being in the three more active relative to the Less Active group, an association stronger among white adults. Finally, the three more active groups showed higher self-rated physical health than the Less Active group. Within-race analyses showed that this association was only evident among white adults. Neighborhood deprivation is an important structural context that may strongly limit adults’ engagement in daily physical health.

Understanding complex interactions between neighborhood environment and personal perception in affecting walking behavior of older adults: A random forest approach combined with human-machine adversarial framework

The population aging is a growing problem worldwide. Walking is one of the most important ways of self-management of health for older adults, determined by many factors, such as neighborhood environment (NE) and socio-economic attributes. Although the previous studies have typically predicted elderly walking behavior through NE, they are limited by the methodological system and data collection, resulting in low prediction accuracy. To this end, this study incorporates residents' subjective perceptions of the environment and objective neighborhood environmental attributes into the evaluation system, uses human-machine adversarial framework and machine learning methods to predict elderly walking behavior, and assesses the nonlinear effects of each factor. The results show that (1) combining subjective and objective factors, the prediction accuracy of elderly walking behavior has been effectively improved based on human-machine adversarial framework and machine learning methods. (2) The nonlinear and threshold effects of environmental and perceptual factors on the walking time of the elderly were revealed. (3) The neighborhood attributes were incorporated into the walking behavior prediction, and were found to be of comparable importance to the influence of the NE on the behavior of the elderly. These results provide more reliable qualitative and quantitative auxiliary suggestions for planners.

Associations of objective and subjective neighborhood measures with cognitive change in a repeated measurement burst design

AbstractBackgroundPrior studies have reported associations between neighborhood characteristics and late‐life cognition. These studies assessed neighborhood using either objective (e.g., area‐level data from public database) or subjective (individual‐level perception) measures. However, little research has been done to examine effects of objective and subjective measures simultaneously. The present study aims to investigate the independent associations of objective and subjective neighborhood characteristics with cognitive change in older adults.MethodParticipants include 316 individuals in the Einstein Aging Study (mean age = 77; 67% females; 45% non‐Hispanic Whites, 40% non‐Hispanic Blacks). Subjective neighborhood measures included perceived neighborhood safety, aesthetic quality, social cohesion, and availability of healthy foods (range = 1 poor to 5 excellent). Objective neighborhood measures included violent crime, neighborhood deprivation, volunteering rates, percentage of healthy food retailers, and low access to healthy food. Processing speed was assessed using the brief, smartphone‐administered Symbol Search Test, and was completed 6x/day over two weeks; this was repeated annually from 2017 to 2022. To account for non‐linear retest/practice effects, double negative exponential models were used to estimate the relation of neighborhood measures to asymptotic performance (i.e., fastest response time) at baseline and to change in asymptotic performance over time.ResultMost subjective and objective neighborhood measures were significantly correlated with each other (Table 1). In models containing both objective and subjective neighborhood measures, better perceived safety was associated with greater annual improvement in asymptotic performance (40 milliseconds/year for one point increase in safety) while the objective measure of violent crime was not. Perceived availability of healthy foods was independently associated with a faster baseline asymptotic processing speed (estimate = 160 milliseconds) and with greater annual improvement rate (estimate = 54 milliseconds/year) while the objective measures of food environment were not (Table 2).ConclusionSubjective rather than objective neighborhood characteristics were strongly associated with annual rates of change in processing speed over five years in community‐dwelling older adults. Perception of one’s neighborhood may be a more proximal predictor of cognitive health as it may reflect an individual’s lived experiences and determine one’s psychological states and health‐related behaviors. Alternatively, more fine‐grained objective neighborhood measures (e.g., individual‐level) would be necessary to better characterize objective neighborhood environments.

An examination of the relationships between the neighborhood social environment, adiposity, and cardiometabolic disease risk in adolescence: a cross-sectional study

BackgroundDisadvantaged neighborhood environments are a source of chronic stress which undermines optimal adolescent health. This study investigated relationships between the neighborhood social environment, specifically, chronic stress exposures, adiposity, and cardiometabolic disease risk factors among 288 Louisiana adolescents aged 10 to 16 years.MethodsThis cross-sectional study utilized baseline data from the Translational Investigation of Growth and Everyday Routines in Kids (TIGER Kids) study. Adolescent data were obtained using self-reported questionnaires (demographics and perceived neighborhood disorder), anthropometry, body imaging, and a blood draw while objective neighborhood data for the concentrated disadvantage index were acquired from the 2016 American Community Survey five-year block group estimates, 2012–2016. Multilevel linear regression models were used to examine whether neighborhood concentrated disadvantage index and perceived neighborhood disorder were associated with body mass index, waist circumference, body fat, adipose tissue, blood pressure, and lipids. We performed multilevel logistic regression to determine the odds of elevated adiposity and cardiometabolic disease risk for adolescents living in neighborhoods with varying levels of neighborhood concentrated disadvantage and disorder.ResultsAdolescents living in neighborhoods with higher disadvantage or disorder had greater waist circumference and total percent body fat compared to those in less disadvantaged and disordered neighborhoods (p for trend < 0.05). Neighborhood disadvantage was also positively associated with percentage of the 95th Body Mass Index percentile and visceral abdominal adipose tissue mass while greater perceived neighborhood disorder was related to higher trunk fat mass and diastolic blood pressure (p for trend < 0.05). Living in the most disadvantaged was associated with greater odds of obesity (OR: 2.9, 95% CI:1.3, 6.5) and being in the top tertile of body fat mass (OR: 3.0, 95% CI: 1.4, 6.6). Similar results were found with neighborhood disorder for odds of obesity (OR: 2.1, 95% CI:1.1, 4.2) and top tertile of body fat mass (OR: 2.1, 95% CI:1.04, 4.1).ConclusionsNeighborhood social environment measures of chronic stress exposure were associated with excess adiposity during adolescence, and relationships were most consistently identified among adolescents living in the most disadvantaged and disordered neighborhoods. Future studies should account for the influences of the neighborhood environment to stimulate equitable improvements in adolescent health.Clinical Trials Registration# NCT02784509.

Association Of Perceived And Objective Neighborhood Walkability With Accelerometer Measured Physical Activity And Sedentary Time

Association Of Perceived And Objective Neighborhood Walkability With Accelerometer Measured Physical Activity And Sedentary Time

The damages of stigma, the benefits of prestige: Examining the consequences of perceived residential reputations on neighbourhood attachment

This study examines how perceived residential reputations – that is, how people think non-residents assess the reputation of their neighbourhood – affect neighbourhood attachment, including residents’ sense of belonging, local civic membership, social relationships and compliance with social rules and norms in the neighbourhood. We focus on Santiago, the capital city of Chile: a highly segregated context. We use data from the Chilean Longitudinal Social Survey (ELSOC, 2016–2019) and information on neighbourhood characteristics. Results show that perceived residential reputations affect neighbourhood attachment, even after adjusting for time-invariant individual heterogeneity and lagged dependent variables. Specifically, perceived stigma reduces residents’ neighbourhood identification, physical rootedness, trust and sociability with neighbours, while positive perceived reputations improve these components of neighbourhood attachment, although to a lesser extent. However, perceived residential reputations do not affect the formation of strong ties between neighbours or local participation, suggesting that residential reputations mainly influence affective components of neighbourhood attachment. We conclude that perceived residential reputations reinforce the influence of individual characteristics and objective neighbourhood conditions in producing diverging patterns of neighbourhood attachment, with broader implications for social inequality in the city.

Association of perceived and objective neighborhood walkability with accelerometer-measured physical activity and sedentary time in the Maastricht Study.

We investigated the association of neighborhood walkability with accelerometer-measured physical activity (PA) and sedentary behavior (SB) and examined whether objective and subjective measures of walkability resulted in similar findings. PA and SB from the first 7689 Maastricht Study participants ages 40-75 from 2010 to 2017 were measured using accelerometers for 7 days. Mean daily step count, light-intensity PA, moderate- to vigorous- intensity PA (MVPA), and SB were calculated. Objective walkability was measured by the 7-component Dutch Walkability Index within 500 m Euclidean buffers around residential addresses of participants. Subjective walkability was obtained from the Abbreviated Neighborhood Environment Walkability Scale. Linear regression models analyzed the associations of walkability with PA and SB, controlling for potential confounders. Objective walkability was negatively associated with light intensity PA in the most walkable quartile (b = -14.58, 95% CI = -20.94, -8.23). Compared to participants living in the least walkable neighborhoods, those in the most walkable quartile had statistically significantly higher SB levels (b = 11.64, 95% CI = 4.95, 18.32). For subjective walkability, mean daily step count was significantly higher in the most walkable quartile (b = 509.60, 95% CI = 243.38, 775.81). Higher subjective walkability was positively associated with MVPA (b = 4.40, 95% CI = 2.56, 6.23). Living in a neighborhood with higher objective walkability was associated with lower levels of PA and higher SB levels while higher subjective walkability was associated with higher levels of PA. These results show discordant findings and thus, the effect of walkability on participant PA and SB within our sample is to be determined.

Associations of Perceived and Objective Neighborhood Environment Attributes with Walking in Older Adults: A Cross-Sectional Study

Associations of Perceived and Objective Neighborhood Environment Attributes with Walking in Older Adults: A Cross-Sectional Study

Neighborhood Social Cohesion and Loneliness in Mid- and Later Life: Are Benefits Contingent on Race/Ethnicity or Neighborhood Disorder?

Connections between social integration and health throughout the life span are well established, including at the neighborhood level and among older adults. Less explored is how pathways between neighborhood social cohesion and well-being may differ by race/ethnicity or by neighborhood disorder. This study investigates whether perceived neighborhood social cohesion is associated with loneliness in adults aged 50 and older, and whether this association is moderated by race/ethnicity or perceived neighborhood disorder. We used pooled cross-sectional data from the 2016 and 2018 waves of the Health and Retirement Study and respondents to the Leave-behind Questionnaire age 50 and older, living in the community (N = 10,713). Data were analyzed using multivariate ordinary least squares regression. Perceived social cohesion was negatively associated with loneliness (B = -0.13, p < .001); however, this effect was strongest among White respondents, and significantly weaker for respondents who were Black (B = 0.02, p < .05), Hispanic (B = 0.03, p < .05), or of another race/ethnicity (B = 0.03, p < .05). Further, neighborhood disorder moderated the association between social cohesion and loneliness (B = 0.02, p < .001), reducing the strength of relationship for those in areas of high disorder. Inclusion of this interaction also attenuated the interaction between neighborhood cohesion and race for Black older adults. Findings show that neighborhood social cohesion matters for midlife and older adults' loneliness, but that this relationship varies by race/ethnicity and neighborhood disorder. As such, neighborhood racial/ethnic makeup and both social and objective neighborhood characteristics should be considered when designing interventions to reduce loneliness.

Neighborhood and Depressive Symptoms in Older Adults Living in Rural and Urban Regions in South Korea

Neighborhoods have a significant impact on depressive symptoms in older adults. In response to the increasing depression of older adults in Korea, this study aims to identify the relationship between perceived and objective neighborhood characteristics in depressive symptoms and find differences between rural and urban areas. We used a National survey collected in 2020 of 10,097 Korean older adults aged 65 and older. We also utilized Korean administration data for identifying the objective neighborhood characteristics. Multilevel modeling results indicated that depressive symptoms decreased when older adults perceived their housing condition (b = -0.04, p < 0.001), their interaction with neighbors (b = -0.02, p < 0.001), and overall neighborhood environment (b = -0.02, p < 0.001) positively. Among the objective neighborhood characteristics, only nursing homes (b = 0.09, p < 0.05) were related to depressive symptoms of older adults living in urban areas. For older adults living in rural areas, the number of social workers (b = -0.03, p < 0.001), the number of senior centers (b = -0.45, p < 0.001), and nursing home (b = -3.30, p < 0.001) in the neighborhood were negatively associated with depressive symptoms. This study found that rural and urban areas have different neighborhood characteristics related to older adults' depressive symptoms in South Korea. This study encourages policymakers to consider neighborhood characteristics to improve the mental health of older adults.

The associations of objective and perceived neighborhood disadvantage with stress among pregnant black women.

Neighborhood disadvantage may impact risk of preterm birth through stress. Few studies have examined how neighborhood disadvantage relates to stress during pregnancy, especially for Black women. Secondary data analysis of 572 women in a prospective cohort in Detroit, MI and Columbus, OH. Participants completed questionnaires including the ROSS Neighborhood Disorder Scale, the crime subscale of the Perceived Neighborhood Scale (PNS), and the Perceived Stress Scale. An objective neighborhood disadvantage index (NDI) was created using principal components analysis after geocoding residential addresses and linking to Census data. All models used logistic regression. Adjusted for maternal age and annual household income, perceived stress was positively associated with perceived neighborhood disorder (p<.01). In a separate model, perceived neighborhood crime was positively associated with perceived neighborhood disorder (p=.005). In a joint model adjusted for age and income, the association of disorder with stress was similar in magnitude (p<.01) but the association between crime and stress weakened. The NDI was not associated with perceived stress before or after adjustment for confounders. Perceived neighborhood disadvantage may capture a different dimension than objective neighborhood disadvantage. Future studies should test stress as a pathway by which neighborhood environment increases risk of preterm birth.