Relationship between Neighborhood-Level Social Risk Factor Measures and Presenting Glaucoma Severity Utilizing Multilevel Modeling.

Purpose: The neighborhood and built environment social determinant of health domain has several social risk factors (SRFs) that are modifiable through policy efforts. We investigated the impact of neighborhood-level SRFs on presenting glaucoma severity at a tertiary eye care center. Design: A cross-sectional study from August 2012 to May 2022 in the University of Michigan electronic health record (EHR). Participants: Patients with a diagnosis of any open-angle glaucoma with ≥1 eye care visit at the University of Michigan Kellogg Eye Center and ≥1 reliable visual field (VF). Methods: Participants who met inclusion criteria were identified by International Classification of Diseases ninth and tenth revision codes (365.x/H40.x). Data extracted from the EHR included patient demographics, address, presenting mean deviation (MD), and VF reliability. Addresses were mapped to SRF measures at the census tract, block group, and county levels. Multilevel linear regression models were used to estimate the fixed effects of each SRF on MD, after adjusting for patient-level demographic factors and a random effect for neighborhood. Interactions between each SRF measure with patient-level race and Medicaid status were tested for an additive effect on MD. Main Outcome Measures: The main outcome measure was the effect of SRF on presenting MD. Results: In total, 4428 patients were included in the analysis who were, on average, 70.3 years old (standard deviation = 11.9), 52.6% self-identified as female, 75.8% self-identified as White race, and 8.9% had Medicaid. The median value of presenting MD was -4.94 decibels (dB) (interquartile range = -11.45 to -2.07 dB). Neighborhood differences accounted for 4.4% of the variability in presenting MD. Neighborhood-level measures, including worse area deprivation (estimate, ß = -0.31 per 1-unit increase; P < 0.001), increased segregation (ß = -0.92 per 0.1-unit increase in Theil's H index; P < 0.001), and increased neighborhood Medicaid (ß = -0.68; P < 0.001) were associated with worse presenting MD. Significant interaction effects with race and Medicaid status were found in several neighborhood-level SRF measures. Conclusions: Although patients' neighborhood SRF measures accounted for a minority of the variability in presenting MD, most neighborhood-level SRFs are modifiable and were associated with clinically meaningful differences in presenting MD. Policies that aim to reduce neighborhood inequities by addressing allocation of resources could have lasting impacts on vision outcomes. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Depression risk and resilience in a diverse sample of older adults in the United States.

Living in poor and physically deteriorating neighborhoods is associated with heightened likelihood of experiencing depression. At the same time, not all people experience their neighborhoods in the same way. We predicted and tested the possibility that variability in this association can be explained by the social support that people derive both from their personal networks and other people residing in the same neighborhood, and that this moderation varies by race/ethnicity. Health and Retirement Study data (2018/2020 waves) were used to evaluate the role of individual-level and contextual risk and resilience factors in association with depression among US older non-Hispanic white adults (n = 4,986, mean age 67 years), non-Hispanic black adults (n = 1,342, mean age 65 years), and Hispanic adults (n = 937, mean age 64 years). Four notable findings emerged. First, perceived neighborhood disorder was related to increased depression risk for non-Hispanic white and black participants, but not Hispanic participants. Second, participants residing in census tracts with higher poverty rates were more likely to report depression. Third, non-Hispanic white participants residing in census tracts with greater Hispanic resident density had reduced depression risk. This same pattern was not observed among non-Hispanic black participants. Finally, perceived support from family was associated with reduced depression risk among all participants. These data suggest both individual- and contextual-level sources of risk and resiliency for depression. The implications for theories that seek to explain the relative resilience to neighborhood disorder observed among US Hispanic residents are discussed.

Neighborhood ethnoracial diversity and positive psychotic symptoms among youth at high-risk and healthy comparisons.

Neighborhood ethnoracial composition has been associated with schizophrenia, but mechanisms are unclear. This study investigates the moderators and mediators of the association between neighborhood ethnoracial diversity and positive symptoms among youth at clinical high-risk for psychosis (CHR-P) and healthy comparisons (HC). Data were collected as part of The North American Prodrome Longitudinal Study and included 492 youth at CHR-P and 136 HCs. Neighborhood ethnoracial diversity measures the probability that two people chosen at random will be from different ethnoracial groups. Attenuated positive symptoms were derived from the Scale of Prodromal Symptoms. Peer victimization and discriminatory experiences were constructed as latent variables. Using structural equation modeling, this study tested the relationship of these variables and included the following covariates: age, sex, neighborhood poverty, and depressive symptoms. Greater neighborhood ethnoracial diversity was associated with reduced positive symptoms among ethnoracial minorities at CHR-P (ß=-3.78; 95 % CI [-6.61, -0.84]). Fewer life events of peer victimization (ß=-0.13; 95 % CI [-0.24, -0.03]) leading to perceived ethnoracial discrimination (ß=0.56; 95 % CI [0.45, 0.67]) mediated 15.06 % of this association. These findings deepen our understanding of the social determinants of psychosis and may help develop effective interventions to prevent psychosis, especially among ethnoracial minority youth at high risk.

The Role of Multiple Mediation with Contextual Neighborhood Measures in Ovarian Cancer Survival..

BACKGROUND: Mediation by multiple agents can affect the relation between neighborhood deprivation and segregation indices and ovarian cancer survival. In this paper, we examine a variety of potential clinical mediators in the association between deprivation indices (DIs) and segregation indices (SIs) with all-cause survival among women with ovarian cancer in the African American Cancer Epidemiology Study (AACES). METHODS: We use novel Bayesian multiple mediation structural models to assess the joint role of mediators (stage at diagnosis, histology, diagnostic delay) combined with the DIs and SIs (Yost, ADI, Kolak's URB, ICE-income) and a set of confounders with survival. The confounder set is selected in a preliminary step, and each DI or SI is included in separate model fits. RESULTS: When multiple mediators are included, the total impact of DIs and SIs on survival is much reduced. Unlike the single mediator examples previously reported, the Yost, ADI and ICE-income indices do not display significant direct effects. This suggests that when important clinical mediators are included, the impact of neighborhood SES indices is significantly attenuated. It is also clear that certain behavioral and demographic measures such as physical activity, smoking, or adjusted family income do not have a significant role in survival when mediated by clinical factors. CONCLUSION: Multiple mediation via clinical and diagnostic-related measures reduces the contextual effects of neighborhood measures on ovarian cancer survival. The robust association of the Kolak URB index on survival may be due to its relevance to access to care, unlike SES-based indices whose impact was significantly reduced when important clinical mediators were included.

Built environment and childhood obesity.

Childhood obesity, an escalating global health challenge, is intricately linked to the built environment in which children live, learn, and play. This review and perspective examined the multifaceted relationship between the built environment and childhood obesity, offering insights into potential interventions for prevention. Factors such as urbanization, access to unhealthy food options, sedentary behaviors, and socioeconomic disparities are critical contributors to this complex epidemic. Built environment encompasses the human-modified spaces such as homes, schools, workplaces, and urban areas. These settings can influence children's physical activity levels, dietary habits, and overall health. The built environment can be modified to prevent childhood obesity by enhancing active transportation through the development of safe walking and cycling routes, creating accessible and inviting green spaces and play areas, and promoting healthy food environments by regulating fast-food outlet density. School design is another area for intervention, with a focus on integrating outdoor spaces and facilities that promote physical activity and healthy eating. Community engagement and education in reinforcing healthy behaviors is necessary, alongside the potential of technology and innovation in encouraging physical activity among children. Policy and legislative support are crucial for sustaining these efforts. In conclusion, addressing the built environment in the fight against childhood obesity requires the need for a comprehensive, multipronged approach that leverages the built environment as a tool for promoting healthier lifestyles among children, ultimately paving the way for a healthier, more active future generation.

Atacama Large Aperture Submillimeter Telescope (AtLAST) science: Our Galaxy.

As we learn more about the multi-scale interstellar medium (ISM) of our Galaxy, we develop a greater understanding for the complex relationships between the large-scale diffuse gas and dust in Giant Molecular Clouds (GMCs), how it moves, how it is affected by the nearby massive stars, and which portions of those GMCs eventually collapse into star forming regions. The complex interactions of those gas, dust and stellar populations form what has come to be known as the ecology of our Galaxy. Because we are deeply embedded in the plane of our Galaxy, it takes up a significant fraction of the sky, with complex dust lanes scattered throughout the optically recognizable bands of the Milky Way. These bands become bright at (sub-)millimetre wavelengths, where we can study dust thermal emission and the chemical and kinematic signatures of the gas. To properly study such large-scale environments, requires deep, large area surveys that are not possible with current facilities. Moreover, where stars form, so too do planetary systems, growing from the dust and gas in circumstellar discs, to planets and planetesimal belts. Understanding the evolution of these belts requires deep imaging capable of studying belts around young stellar objects to Kuiper belt analogues around the nearest stars. Here we present a plan for observing the Galactic Plane and circumstellar environments to quantify the physical structure, the magnetic fields, the dynamics, chemistry, star formation, and planetary system evolution of the galaxy in which we live with AtLAST; a concept for a new, 50m single-dish sub-mm telescope with a large field of view which is the only type of facility that will allow us to observe our Galaxy deeply and widely enough to make a leap forward in our understanding of our local ecology.

There are many individual components contributing to the overall evolution of our Galaxy, the Milky Way. Through understanding the physics and chemistry of the Galaxy around us, we better understand our origins, our environment, and where we're going. Here we outline a number of observational surveys of our Galaxy that would produce a step change in our understanding of the evolution of the Galaxy around us, both as a template for others, and as the only way of understanding our place in the larger Universe. We present surveys of the Galactic Plane focusing on the dust and magnetic fields, chemistry, and dynamics of the gas. We then suggest surveys of local stars and star forming regions to uncover the origins of stars, planets and how those planetary systems evolve over the course of their lives, helping to put our Sun and Solar System in context. These types of observations require simultaneously sensitive, long wavelength (between 0.3 and 3 millimetre) observations as well as a large coverage of the sky, and cannot be done with current observatories operating at these wavelengths. Future leaps in understanding these systems will require a new telescope; a large telescope at a good observing location with a large field of view. This telescope, the Atacama Large Sub-mm Telescope (AtLAST; http://atlast-telescope.org/) is being developed, and here we are presenting the science cases for this new telescope from the point of view of our Galaxy. Together, these studies will revolutionise our understanding of the history and evolution of our Galaxy and bring us yet another step closer to understanding our place in, and the evolution of, our Universe.

Identifying priority populations for lung cancer screening intervention using neighborhood-level factors and cancer registry data.

To evaluate the association of neighborhood level economic, environmental, and social indicators with lung cancer (LC) incidence and mortality. Data for adult incident LC cases in Allegheny County, Pennsylvania, diagnosed between 2015-2019 were obtained from Pennsylvania cancer registry. Cases were summarized at census-tract level. Publicly available data on neighborhood deprivation index (NDI), built environment, and racial isolation at census-tracts were linked to cases. Poisson regression was used to compute relative risk (RR) for LC incidence and mortality, adjusting for covariates. A total of 3256 LC cases were included in the analyses. About 68% were ≥65 years, 54% female, 14% Black or African American, and 63% deceased. Results of the multivariable model found that increasing quintiles (Q) of NDI were significantly associated with increasing risk of LC incidence and mortality. The RRs (95% confidence interval) of LC incidence for Q2, Q3, Q4 and Q5 were 1.36 (1.21-1.52), 1.55 (1.40-1.72), 1.68 (1.51-1.87), 2.08 (1.82-2.38), respectively, compared with Q1 (P trend <0.01). The corresponding RRs for LC mortality were 1.46 (1.27-1.68), 1.63 (1.42-1.88), 1.74 (1.51-2.01), 2.04 (2.02-2.88) (P trend <0.01). Targeted interventions for LC prevention and early detection in high NDI neighborhoods may be more effective to reduce LC health disparities.

Perception of one's social environment and loneliness: results of the nationally representative "Old age in Germany (D80+)" study.

OBJECTIVES: To examine the association between perception of one's social environment (in terms of residential attachment and neighborhood trust) and loneliness among the oldest old and whether these associations differ by living arrangement. METHODS: We used data from the nationally representative "Old Age in Germany (D80+)" study that included individuals residing in private households and institutionalized settings. The analytic sample was 9,621 individuals (average age: 85.5 years, SD: 4.1 years; 62% female). Data collection took place from November 2020 to April 2021. Multiple linear regressions were conducted with adjustment for relevant covariates. RESULTS: Higher residential attachment (ß=-0.02, p < .05) and higher neighborhood trust (ß=-0.12, p < .001) were associated with less loneliness. The latter association was moderated by living arrangement (ß=-0.09, p = .04) such that the association between neighborhood trust and loneliness was stronger among individuals living in institutionalized settings compared to individuals in private households. CONCLUSION: Greater residential attachment and neighborhood trust, particularly among individuals living in institutionalized settings, are associated with less loneliness among the oldest old. Finding ways to improve perceived attachment and trust may assist in avoiding loneliness among older individuals.

Provision of Home & Community Based Services to Veterans by Race, Rurality, and Neighborhood Deprivation Index.

Home and community-based services (HCBS) enable frail patients to remain at home. We examined whether there were neighborhood-deprivation, racial, or rural disparities in HCBS utilization provided to Veterans by the Department of Veterans Affairs (VA) or Medicare by comparing the adjusted utilization rate of a historically disadvantaged group with the predicted utilization rate had it been treated as the historically dominant group. Among the 2.7 million VA patients over 66 years old in 2019, 11.0% were Black, 39.2% lived in rural settings, 15.3%/29.2%/30.9%/24.7% lived in least/mild/moderate/most-deprived neighborhoods. On average, 11.2% received VA or Medicare HCBS. Veterans residing in more deprived neighborhoods had 0.11-0.95% higher adjusted probability of receiving HCBS than expected had they resided in the least deprived neighborhoods. Veterans residing in rural areas had 0-0.7% lower HCBS rates than expected had they been treated like urban Veterans. Black Veterans were 0.8-1.2% more likely to receive HCBS than expected had they been treated like White Veterans. Findings indicate that VA resources were equitably employed, aligning with probable HCBS needs, suggesting that VA's substantial and long-standing investment in HCBS for care of frail Veterans could serve as a model for other payers and providers in the U.S.

Experimental evidence of inbreeding depression for competitive ability and its population-level consequences in a mixed-mating plant.

Inbreeding depression is a key factor regulating the evolution of self-fertilization in plants. Despite predictions that inbreeding depression should evolve with selfing rates as deleterious alleles are increasingly exposed and removed by selection, evidence of purging the genetic load in wild populations is equivocal at best. This discordance could be explained, in part, if the load underlying inbreeding depression is subject to soft selection, i.e., the fitness of selfed individuals depends on the frequency and density of selfed vs. outcrossed individuals in the population. Somewhat counterintuitively, this means that populations with contrasting mutation load can have similar fitness. Soft selection against selfed individuals may be expected when there is inbreeding depression for competitive ability in density-regulated populations. We tested population-level predictions of inbreeding depression in competitive ability by creating a density series of potted plants consisting of either purely outcrossed, purely selfed, or mixed (50% outcrossed, 50% selfed) seed of the mixed-mating biennial Sabatia angularis (Gentianaceae) representing ecological neighborhoods. Focusing on the growth and survival of juveniles, we show that mean plant size is independent of neighborhood composition when resources are limiting, but greatest in outcrossed neighborhoods at low densities. Across a range of densities, this manifests as stronger density-dependence in outcrossed populations compared to selfed or mixed ones. We also found significantly greater size inequalities among individuals in mixed neighborhoods, even at high densities where mean juvenile size converged, a key signature of asymmetric competition between outcrossed and selfed individuals. Our work illustrates how soft selection could shelter the genetic load underlying inbreeding depression and its demographic consequences.

The association between perceived neighborhood safety and cardiovascular disease risk factors.

Cardiovascular disease (CVD) remains the leading cause of mortality in the U.S. accounting for 1 in 4 deaths each year. Environmental factors, such as neighborhood safety, may increase the risk of CVD. Therefore, the current study assessed perceived neighborhood safety and its association with CVD risk factors (i.e. dyslipidemia, hypertension, type II diabetes) among 663 adults (mean age: 49.97 years, 61.24% female, 78.28% White). Participants completed self-report measures as part of a larger study of environmental influences on cardiac health. Results indicated that individuals reporting low perceived neighborhood safety had greater odds of having at least one CVD risk factor (OR = 2.76, 95% CI: 1.46, 5.22) compared to those with high perceived safety. There was a significant interaction between gender and the presence of at least one CVD risk factor in relation to perceived neighborhood safety. Low perceived neighborhood safety was associated with greater odds of having at least one CVD risk factor among males (OR = 5.48, 95% C.I: 1.82, 16.52) but not females. These findings suggest that low perceived safety is associated with CVD risk factors, especially among males. Future work should seek to better understand the interaction by gender in the relationship between perceived safety and CVD risk factors.

The Universal Neighborhood Effect Averaging in Mobility-Dependent Environmental Exposures.

The neighborhood effect averaging problem (NEAP) is a fundamental statistical phenomenon in mobility-dependent environmental exposures. It suggests that individual environmental exposures tend toward the average exposure in the study area when considering human mobility. However, the universality of the NEAP across various environmental exposures and the mechanisms underlying its occurrence remain unclear. Here, using a large human mobility data set of more than 27 000 individuals in the Chicago Metropolitan Area, we provide robust evidence of the existence of the NEAP in a range of individual environmental exposures, including green spaces, air pollution, healthy food environments, transit accessibility, and crime rates. We also unveil the social and spatial disparities in the NEAP's influence on individual environmental exposure estimates. To further reveal the mechanisms behind the NEAP, we perform multiscenario analyses based on environmental variation and human mobility simulations. The results reveal that the NEAP is a statistical phenomenon of regression to the mean (RTM) under the constraints of spatial autocorrelation in environmental data. Increasing travel distances and out-of-home durations can intensify and promote the NEAP's impact, particularly for highly dynamic environmental factors like air pollution. These findings illuminate the complex interplay between human mobility and environmental factors, guiding more effective public health interventions.

Daily Diversity Flows: Racial and Ethnic Context Between Home and Work.

The racial and ethnic diversification of the U.S. population has transformed the demographic makeup of communities and rapidly increased exposure to diversity in American neighborhoods. Although diversity exposure occurs throughout people's daily lives, the conventional approach to describing diversity only at places of residence potentially understates the full extent of this phenomenon. In this study, we explore short-term, within-day changes in the diversity of different neighborhoods by considering U.S. workers' work and residential locations. Using estimates for daytime and nighttime populations among metropolitan census tracts, our empirical analyses investigate the extent to which the process of daytime mobility for work relates to changes in the racial and ethnic diversity of different spaces. Our results indicate widespread daily shifts toward diversity for most neighborhood types, especially those with residential (nighttime) populations that are predominantly Black, Latino, or Asian. We find that patterns of intraday diversification experienced minor declines across recent decades but are present in most metropolitan areas. Our findings also show that intraday changes in racial and ethnic diversity overlap with nonracial forms of daily diversity change. Further, average within-day changes in diversity are more pronounced in areas with greater residential segregation.

Perceptions of neighborhood disorder and gun carrying during adolescence: The indirect effect of exposure to violence.

OBJECTIVE: As society strives to curb gun violence among adolescents, understanding the risk factors associated with gun carrying is of critical importance. The current study seeks to examine the relationship between perceived neighborhood disorder and adolescents' susceptibility to carrying a gun to school. More specifically, the aim of the current study was threefold: (1) to examine the direct relationship between perceived neighborhood disorder and exposure to violence, (2) to investigate the association between perceived neighborhood disorder and gun carrying, and (3) to test the mediating effect of exposure to violence on the relationship between perceived neighborhood disorder and gun carrying. METHODS: Data from waves I and II (1994-1996) of the National Longitudinal Study of Adolescent to Adult Health was analyzed (N = 11,887). Due to the binary nature of the mediating and dependent variables (i.e., exposure to violence and gun carrying) a series of logistic regression models were estimated. RESULTS: Our analyses revealed that perceived neighborhood disorder is positive and significantly associated with, both, exposure to violence and gun carrying. The relationship between perceived neighborhood disorder and gun carrying was fully mediated by exposure to violence. CONCLUSIONS: While neighborhood disorder is a risk factor for gun carrying among youth, exposure to violence explains the relationship between perceived neighborhood disorder and carrying a gun to school. To reduce the prevalence of gun carrying and gun violence among the adolescent population, mental health resources should be provided to those who reside in communities with high levels of disorder and violence.

Examining the importance of neighborhood natural, and built environment factors in predicting older adults' mental well-being: An XGBoost-SHAP approach.

BACKGROUND: Previous studies have shown that urban neighborhood environmental factors significantly influence the health outcomes of urban older adults. However, most cross-sectional studies exploring the health effects of these factors have failed to quantify the relative importance of each factor. METHODS: We use XGBoost machine learning techniques and SHAPley Additive Interpretation (SHAP) to rank the importance of urban neighborhood environmental factors in shaping the mental health of urban older adults. To address self-selection bias in housing choice, we distinguish older adults living in private housing from those living in public as residents in private housing have more freedom to choose where to live. RESULTS: The results show that both natural and built environmental factors in urban neighborhoods are important predictors of mental well-being scores. Five natural environmental factors (blue space, perceived greenery quantity, NDVI, street view greenness, aesthetic quality) and three built environmental factors (physical activity facilities quality, physical activity facilities quantity, neighborhood disorder) had considerable predictive power for mental well-being scores in two groups. Among them, blue space, perceived greenery quantity and street view greenness quantity became less important after controlling for self-selection bias, possibly because of the unequal distribution of quantity and quality, and the performance of neighborhood disorder, aesthetic quality and physical activity facilities quality was more sensitive in public housing. CONCLUSIONS: These results highlight the nuanced and differential effects of neighborhood environmental exposures on mental well-being outcomes, depending on housing preferences. The results of this study can provide support for decision makers in urban planning, landscape design and environmental management in order to improve the mental well-being status of urban older adults.

Population-based estimates of major forms of housing insecurity among community-living older Americans.

OBJECTIVES: The number of older adults struggling to maintain adequate housing is growing. Prior studies have used various criteria to measure housing insecurity; however, no standardized definition exists to date. Using a multidimensional approach, our study sought to calculate population-based estimates of various forms of housing insecurity among community-living older Americans and determine how these estimates differ across key characteristics. METHODS: This study utilized data from the 2011 round of the National Health and Aging Trends Study (NHATS), a prospective longitudinal study of Medicare beneficiaries aged 65 years or older. Three key forms of housing insecurity were operationalized: poor housing affordability (PHA), poor housing quality (PHQ), and poor neighborhood quality (PNQ). Population-based estimates of these forms of housing insecurity were calculated using analytic sampling weights and stratified by age, gender, race and ethnicity, frailty status, and dementia status. RESULTS: Totally 6466 participants were included in the analysis, representing 29,848,119 community-living older Americans. The mean (standard deviation) age was 77.3 (7.7) years; by weighted percentages, 56.0% identified as female, 81.3% as White, 8.2% Black, and 7.1% Hispanic. At least one form of housing insecurity was identified in 38.5% of older Americans. Individually, the prevalence of PHA was 14.8%, PHQ 24%, and PNQ 12.5%. The prevalence of at least one form of housing insecurity was higher among persons of color (62.9% Black and 66% Hispanic vs White; p < 0.001), those with frailty (40.9% pre-frail and 49.4% frail vs robust; p < 0.001), and those with cognitive impairment (48.1% possible and 51% probable dementia vs no dementia; p < 0.001). DISCUSSION: Nearly one in three community-living older Americans experience at least one form of housing insecurity. This was most common among vulnerable subgroups. Our multidimensional approach to defining various forms of housing insecurity can be used for future studies focused on improving social determinants of health among high-risk older adults.

Neighborhood Racial and Ethnic Predominance, Child Opportunity, and Violence-Related Mortality among Children and Adolescents in Chicago.

Our objective was to determine whether Child Opportunity Index (COI), a measure of neighborhood socioeconomic and built environment specific to children, mediated the relationship of census tract Black or Hispanic predominance with increased rates of census tract violence-related mortality. The hypothesis was that COI would partially mediate the relationship. This cross-sectional study combined data from the American Community Survey 5-year estimates, the COI 2.0, and the Illinois Violent Death Reporting System 2015-2019 for the City of Chicago. Individuals ages 0-19 years were included. The primary exposure was census tract Black, Hispanic, White, and other race predominance (> 50% of population). The primary outcome was census tract violence-related mortality. A mediation analysis was performed to evaluate the role of COI as a potential mediator. Multivariable logistic regression modeling census tract violence-related mortality demonstrated a direct effect of census tract Black predominance (adjusted odds ratio [aOR] 2.59, 95% confidence interval [CI] 1.30-5.14) on violence-related mortality compared to White predominance. There was no association of census tract Hispanic predominance with violence-related mortality compared to White predominance (aOR 1.57, 95% CI 0.88-2.84). Approximately 64.9% (95% CI 60.2-80.0%) of the effect of census tract Black predominance and 67.9% (95% CI 61.2-200%) of the effect of census tract Hispanic predominance on violence-related mortality was indirect via COI. COI partially mediated the effect of census tract Black and Hispanic predominance on census tract violence-related mortality. Interventions that target neighborhood social and economic factors should be considered to reduce violence-related mortality among children and adolescents.

Neighborhood Safety Concerns and the Onset of Depressive Symptoms Among Women: A Population-based Prospective Cohort Study in South Korea.

Neighborhood safety is crucial for the well-being of residents; however, longitudinal evidence is scarce. This study explored the association between neighborhood safety concerns and depressive symptoms among women. A nationally representative sample of 10,008 women was surveyed in 2016. Six dimensions of neighborhood safety concerns were assessed: crime, food, safety at night, traffic accidents, building and facility, and general safety. The total score for neighborhood safety concerns ranged from 6 to 24, with higher scores indicating greater concerns. Depressive symptoms were assessed using the 10-item version of the Center for Epidemiologic Studies Depression. For cross-sectional analyses, we explored how neighborhood safety concerns were associated with concurrent depressive symptoms at baseline. For the longitudinal analyses, we explored how they were associated with depressive symptom onset at the 2-year follow-up (2018) among women without depressive symptoms at baseline (n = 7,643). Logistic regressions were employed. The mean (standard deviation [SD]) of the neighborhood safety concern score was 12.7 (3.3). In the cross-sectional analysis, a 1-SD increase in neighborhood safety concern score was associated with 1.23-fold (95% CI: 1.13-1.35) increase in the odds of concurrent depressive symptoms at the baseline year. In the longitudinal analysis, a 1-SD increase in neighborhood safety concern score was associated with 1.15-fold (95% CI: 1.03-1.29) increase in the odds of experiencing the onset of depressive symptoms at the follow-up year. This study suggests that neighborhood safety concerns are risk factors for the development of depressive symptoms of female residents. Policy efforts are necessary to ensure community safety.

DCWPSO: particle swarm optimization with dynamic inertia weight updating and enhanced learning strategies.

Particle swarm optimization (PSO) stands as a prominent and robust meta-heuristic algorithm within swarm intelligence (SI). It originated in 1995 by simulating the foraging behavior of bird flocks. In recent years, numerous PSO variants have been proposed to address various optimization applications. However, the overall performance of these variants has not been deemed satisfactory. This article introduces a novel PSO variant, presenting three key contributions: First, a novel dynamic oscillation inertia weight is introduced to strike a balance between exploration and exploitation; Second, the utilization of cosine similarity and dynamic neighborhood strategy enhances both the quality of solution and the diversity of particle populations; Third, a unique worst-best example learning strategy is proposed to enhance the quality of the least favorable solution and consequently improving the overall population. The algorithm's validation is conducted using a test suite comprised of benchmarks from the CEC2014 and CEC2022 test suites on real-parameter single-objective optimization. The experimental results demonstrate the competitiveness of our algorithm against recently proposed state-of-the-art PSO variants and well-known algorithms.

The association between neighborhood disadvantage and patient-reported outcomes in burn survivors.

BACKGROUND: Burns can cause long-term complications including pain and poor physical function. While neighborhood disadvantage is associated with burn severity, its effect on long-term complications has not been investigated. We hypothesized that patients from areas of higher area of deprivation index (ADI) will report poorer long-term outcomes. METHODS: We linked patient data from the Burn Model System with ADI state decile (1 = least, 10 = most disadvantaged) using year and residence at time of injury. We performed bivariate analyses to identify associations between ADI and patient and burn characteristics and multivariate regressions to determine whether ADI was associated with PROMIS-29 pain and physical function 6- and 24-months post-burn. RESULTS: We included 780 patients; 69 % male, median age = 46 years, median ADI = 6, and median TBSA = 8 %. Multivariate regressions adjusting for TBSA, race, age, sex, anxiety, depression, and pain interference demonstrated that higher ADI was a significant predictor of higher pain intensity 6- (p = 0.001) and 24-months (p = 0.037) post-burn but not worse physical function 24-months post-burn (p = 0.089). CONCLUSIONS: Higher neighborhood disadvantage was associated with higher long-term pain intensity post-burn. This study highlights the importance of socioeconomic factors that may impact long-term outcomes and the use of aggregate markers to identify patients at risk for worse outcomes.