Neighborhood Socioeconomic Characteristics Research Articles

Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada.

Psoriasis is a major global health burden affecting ~ 60 million people worldwide. Existing studies on psoriasis focused on individual-level health behaviors (e.g. diet, alcohol consumption, smoking, exercise) and characteristics as drivers of psoriasis risk. However, it is increasingly recognized that health behavior arises in the context of larger social, cultural, economic and environmental determinants of health. We aimed to identify the top risk factors that significantly impact the incidence of psoriasis at the neighborhood level using populational data from the province of Quebec (Canada) and advanced tree-based machine learning (ML) techniques. Adult psoriasis patients were identified using International Classification of Disease (ICD)-9/10 codes from Quebec (Canada) populational databases for years 1997-2015. Data on environmental and socioeconomic factors 1year prior to psoriasis onset were obtained from the Canadian Urban Environment Health Consortium (CANUE) and Statistics Canada (StatCan) and were input as predictors into the gradient boosting ML. Model performance was evaluated using the area under the curve (AUC). Parsimonious models and partial dependence plots were determined to assess directionality of the relationship. The incidence of psoriasis varied geographically from 1.6 to 325.6/100,000 person-years in Quebec. The parsimonious model (top 9 predictors) had an AUC of 0.77 to predict high psoriasis incidence. Amongst top predictors, ultraviolet (UV) radiation, maximum daily temperature, proportion of females, soil moisture, urbanization, and distance to expressways had a negative association with psoriasis incidence. Nighttime light brightness had a positive association, whereas social and material deprivation indices suggested a higher psoriasis incidence in the middle socioeconomic class neighborhoods. This is the first study to highlight highly variable psoriasis incidence rates on a jurisdictional level and suggests that living environment, notably climate, vegetation, urbanization and neighborhood socioeconomic characteristics may have an association with psoriasis incidence.

Abstract WMP41: Neighborhood Social Vulnerability is Associated With Lower Frequency of Stroke Scale Assessment Among Patients With Suspected Stroke

Introduction: High-quality prehospital care during initial assessment by EMS providers can affect downstream care for acute stroke patients. Prehospital guidelines strongly recommend assessing suspected stroke patients with a validated stroke scale and obtaining a blood glucose level, but EMS adherence varies widely. Neighborhood socioeconomic characteristics are associated with stroke incidence and outcomes, but there is little research evaluating their relationship to quality metrics in prehospital stroke care. Hypothesis: Greater neighborhood-level social vulnerability is associated with lower frequency of stroke scale assessment and blood glucose check by EMS for patients with suspected stroke. Methods: We conducted a cross-sectional evaluation of EMS activations for suspected stroke patients in the 2019 ESO Data Collaborative. We included 911 responses where EMS documented a field impression of stroke and excluded activations from an acute health care facility. Neighborhood-level social vulnerability, using CDC’s Social Vulnerability Index (SVI), was assigned to each encounter based on pick-up location. Descriptive statistics were calculated, and mixed effects logistic regression models were fit to assess any relationship between SVI and documentation of stroke scale and blood glucose assessments, controlling for patient and event characteristics and clustering by EMS agency. Results: Among 84,411 patients with suspected stroke, 46% were male, with an average age of 71 years. Stroke scale assessment was documented in 78% of cases, and blood glucose in 88%. Compared to patients in the least vulnerable SVI quartile, those in the most vulnerable SVI quartile had lower odds of documented stroke scale assessment (OR 0.91, 95% CI 0.82, 1.00, p=0.04), but similar odds of documented blood glucose (OR 0.97, 95% CI 0.89, 1.06, p=0.48). High agency-level variation was present for stroke scale (ICC 70%, 95% CI 69, 73). Conclusions: Higher social vulnerability areas may be associated with less frequent stroke scale assessment; however, high agency-level variation indicates that the best targets to improve EMS systems’ compliance with evidence-based guidelines for acute stroke care may be low-performing agencies, regardless of setting.

Environmental noise is positively associated with socioeconomically less privileged neighborhoods in the Netherlands

BackgroundEnvironmental noise has detrimental effects on various health outcomes. Although disparities in some environmental exposures (e.g., air pollution) are well-documented, there is still a limited and uncertain understanding of the extent to which specific populations are disproportionately burdened by noise. AimTo assess whether environmental noise levels are associated with demographic and socioeconomic neighborhood compositions. MethodsWe cross-sectionally examined long-term noise levels for 9,372 neighborhoods in the Netherlands. We linked these noise levels with administrative data on neighborhood characteristics for the year 2021. Linear and non-linear spatial regression models were fitted to explore the associations between noise, demographic, and socioeconomic neighborhood characteristics. ResultsOur results showed that 46 % of the neighborhoods exhibited noise levels surpassing the recommended threshold of 53 dB to prevent adverse health effects. The regressions uncovered positive and partially non-linear neighborhood-level associations between noise and non-Western migrants, employment rates, low-incomers, and address density. Conversely, we found negative associations with higher-educated neighborhoods and those with a greater proportion of younger residents. Neighborhoods with older populations displayed a U-shaped association. ConclusionsThis national study showed an inequality in the noise burden, adversely affecting vulnerable, marginalized, and less privileged neighborhoods. Addressing the uneven distribution of noise and its root causes is an urgent policy imperative for sustainable Dutch cities.

Banking on the Neighborhood? Inequalities in Older Adults' Access to Local Banking and Neighborhood Perceptions.

Access to local banking represents an understudied dimension of neighborhood-based inequalities that could significantly influence older adults' perceptions of their neighborhood spaces in ways that matter for disparities in well-being. We evaluate disparities in banking access and then examine how local banking access informs older adults' perceptions of neighborhood collective efficacy and danger, above and beyond other neighborhood socioeconomic characteristics. We use nationally representative data from older adults in the United States who were interviewed at Round 3 of the National Social Life, Health, and Aging Project, linked with data on banks in respondents' residential and surrounding census tracts from the National Establishment Time-Series database, in a series of bivariate and multivariable regression analyses. White older adults and those with higher levels of education have significantly greater local banking access than Black and Hispanic older adults and those with lower levels of education. Higher rates of local banking institutions are associated with significantly lower perceptions of neighborhood danger, but not with perceived collective efficacy. This finding emerges when accounting for neighborhood concentrated disadvantage and physical disorder. Local banks may represent neighborhood investment and the broader economic vitality of a community, as well as the ability of communities to meet older adults' everyday needs in ways that enhance older residents' feelings of safety. Increasing access to local financial institutions may help attenuate neighborhood-based contributors to inequalities in health and well-being among the older adult population.

A Patient-Centered Intervention Reduces Disparities in Remote Monitoring in Patients With Implanted Cardiac Devices

BackgroundRemote monitoring (RM) is recommended for patients with cardiovascular implantable electronic devices, yet many individuals, especially those living in underserved communities, fail to receive this guideline-directed care. Multilevel interventions that target patient and clinic-level barriers to RM care may be beneficial. ObjectivesThis study sought to evaluate a remotely delivered, patient-centered intervention to improve RM activation and adherence and reduce disparities in RM care. MethodsThe intervention provides home delivery of remote monitor, phone-based education, monitor setup, and facilitation of first transmission. A retrospective cohort analysis was performed using RM data from 190,643 patients (71.6 ± 12.7 years of age, 40.5% female) implanted with a pacemaker or defibrillator at 4,195 U.S. clinics between October 2015 and October 2019. Outcomes included RM activation (12 weeks and 1-year postimplantation) and adherence to clinic-scheduled transmissions. Patients receiving a cardiovascular implantable electronic deviceimplant 0 to 730 days before (control group, n = 95,861) and after (intervention group, n = 94,782) intervention launch were compared using logistic regression and generalized estimating equations. Multivariable models included patient, clinic, and neighborhood socioeconomic characteristics. ResultsThe odds of achieving guideline-recommended activation were significantly higher in the intervention group at 12 weeks (OR: 2.99; 76.7% vs 60.9%; P < 0.001) and 1 year (OR: 3.05; 88.2% vs 79.3%; P < 0.001). Adherence to scheduled transmissions was also higher in the intervention group compared with the control group (OR: 2.18; 89.1% vs 81.9%; P < 0.001). Preintervention disparities in RM activation and adherence were reduced in underserved groups following the intervention. ConclusionsA remotely delivered patient-centered intervention was associated with earlier activation and improved adherence to RM while reducing disparities in RM care.

Green infrastructure and socioeconomic dynamics in London low-income neighbourhoods: A 120-year perspective

Green infrastructure (GI) and nature-based solutions (NBS) are increasingly adopted as urban planning and development solutions to enable sustainable and healthy urban transitions. However, urban green(ing) has featured as an instrument of urban planning for several centuries. The extent and causal effect of these instruments in delivering environmental and social sustainability outcomes are, however, often unclear, but raise concerns of green gentrification. This paper presents a 120-year analysis of GI in London low-income neighbourhoods drawing on below (soils) and above (urban greenery) components of GI. Three testable relationships are analysed in a long-term perspective (1881–2001): soils, geology and initial socio-spatial structures; impact of urban greenery in comparable low-income neighbourhoods; and the impact of urban greenery in low-income neighbourhoods set in their wider urban systems adjustments. The results suggest that new greenery in comparable low-income neighbourhoods had little independent effect on neighbourhood socioeconomic characteristics. Where gentrification does occur, wider processes of social, economic, and technological adjustment, rather than urban greening, is likely causal. The non-random distribution of soils is found to anchor socio-spatial structures. Future productivity of GI and NBS, e.g., sponginess or mass of green that can be sustained, will likely also vary spatially, and continue to anchor socio-spatial structures.

The association of neighborhood socioeconomic characteristics with cardiovascular health: A quasi-experimental study of refugees to Denmark

Neighborhood socioeconomic disadvantage is associated with cardiovascular health, although it is unclear which specific aspects of neighborhoods matter most. We leveraged a natural experiment in which refugees to Denmark were quasi-randomly assigned to neighborhoods across the country during 1986–1998, creating variation in exposure to various aspects of neighborhood disadvantage. The cohort was followed through December 2018. Exposures included neighborhood-level family income, educational attainment, unemployment, and welfare transfers measured in the first neighborhood after arrival to Denmark. Outcomes included cardiovascular risk factors (hyperlipidemia, hypertension, diabetes and anxiety/depression) and cardiovascular disease (acute myocardial infarction and ischemic heart disease). Neighborhood-level income and education were most consistently associated with cardiovascular risk factors, whereas welfare transfers were most consistently associated with cardiovascular disease. Addressing these specific aspects of neighborhood disadvantage could therefore lower the risk of poor cardiovascular health among refugees. Future research is warranted to examine if results are generalizable to other immigrant groups, countries or time periods.

Measuring the impact of COVID-19 policies on local commute traffic: Evidence from mobile data in Northern California

The COVID-19 pandemic upended the world economy and significantly altered how people work by imposing limits on in-person interactions. The policy response in places like California illustrate a range of scenarios that are applicable more broadly, from stringent restrictions on travel to flexible directives. This study focuses on the impact of various policy instruments the State of California implemented on morning peak hour and home-based work traffic volume in the San Francisco Bay Area and California’s Central Valley. Previous studies have not been able to measure COVID-19′s impact on commute traffic at a sufficiently local level, nor have they tested the impact of policy instruments on local commute traffic. We fill this gap by using mobile-derived morning peak hour traffic volume data from StreetLight Insights along with census-based neighborhood socioeconomic characteristics to model neighborhood-level variation in morning traffic volume and distance traveled. Remote work, a policy the private sector initiated, had a more significant and lasting effect than state policy. Morning traffic volume did not recover in response to policies aiming to provide businesses and people greater flexibility and predictability, and while vaccination was associated with a recovery of morning peak hour and home-based traffic, that recovery was short of pre-COVID levels. The effect of remote work undergirds inequities in commute burden. Economic sectors deemed essential and lower-income workers saw the lowest decreases in commute traffic and fastest recovery. Policymakers and planners ought to consider the occupation mix as a key ingredient in understanding the impact of telework ability and takeup on future transportation infrastructure improvements across various regions.

Zoning for character: Contextual rezoning and socioeconomic change in New York City neighborhoods, 1986–2019

Empirical research is increasingly evaluating how municipal rezonings may affect the racial and socioeconomic characteristics of neighborhoods over time. There are also some zoning types that are not intended to affect development capacity and are based on the policy rationale of protecting urban character. Contextual rezonings are one such type and apply a layer of mandatory regulation on building height, setbacks from the street line, and yard requirements to create more restrictive but visually interesting building envelopes. In the American context, bundled with the notion of urban character are also discriminatory biases about the demographic characteristics of who should be allowed to live in urban neighborhoods and whose presence adds economic value. There is a need for additional studies that examine how character-based zoning controls may also be implicated in forms of neighborhood change, particularly exclusionary practices. This paper contributes to the literature by examining the neighborhood socioeconomic impacts of contextual rezonings implemented in New York City between 1986 and 2019 using a difference-in-difference method. The findings indicate that after implementation, contextually zoned neighborhoods tend to increase in socioeconomic status and become more predominately white and affluent. These changes represent a further entrenchment of white isolation that solidifies related privileges.

Neighborhood Disadvantage and Neural Correlates of Threat and Reward Processing in Survivors of Recent Trauma

Differences in neighborhood socioeconomic characteristics are important considerations in understanding differences in risk vs resilience in mental health. Neighborhood disadvantage is associated with alterations in the function and structure of threat neurocircuitry. To investigate associations of neighborhood disadvantage with white and gray matter and neural reactivity to positive and negative stimuli in the context of trauma exposure. In this cross-sectional study, survivors of trauma who completed sociodemographic and posttraumatic symptom assessments and neuroimaging were recruited as part of the Advancing Understanding of Recovery After Trauma (AURORA) study between September 2017 and June 2021. Data analysis was performed from October 25, 2022, to February 15, 2023. Neighborhood disadvantage was measured with the Area Deprivation Index (ADI) for each participant home address. Participants completed separate threat and reward tasks during functional magnetic resonance imaging. Diffusion-weighted and high-resolution structural images were also collected. Linear models assessed the association of ADI with reactivity, microstructure, and macrostructure of a priori regions of interest after adjusting for income, lifetime trauma, sex at birth, and age. A moderated-mediation model tested whether ADI was associated with neural activity via microstructural changes and if this was modulated by PTSD symptoms. A total of 280 participants (183 females [65.4%]; mean [SD] age, 35.39 [13.29] years) completed the threat task and 244 participants (156 females [63.9%]; mean [SD] age, 35.10 [13.26] years) completed the reward task. Higher ADI (per 1-unit increase) was associated with greater insula (t274 = 3.20; β = 0.20; corrected P = .008) and anterior cingulate cortex (ACC; t274 = 2.56; β = 0.16; corrected P = .04) threat-related activity after considering covariates, but ADI was not associated with reward reactivity. Greater disadvantage was also associated with altered microstructure of the cingulum bundle (t274 = 3.48; β = 0.21; corrected P = .001) and gray matter morphology of the ACC (cortical thickness: t273 = -2.29; β = -0.13; corrected P = .02; surface area: t273 = 2.53; β = 0.13; corrected P = .02). The moderated-mediation model revealed that ADI was associated with ACC threat reactivity via cingulum microstructural changes (index of moderated mediation = -0.02). However, this mediation was only present in individuals with greater PTSD symptom severity (at the mean: β = -0.17; standard error = 0.06, t= -2.28; P = .007; at 1 SD above the mean: β = -0.28; standard error = 0.08; t = -3.35; P < .001). In this study, neighborhood disadvantage was associated with neurobiology that supports threat processing, revealing associations of neighborhood disadvantage with neural susceptibility for PTSD and suggesting how altered structure-function associations may complicate symptoms. Future work should investigate specific components of neighborhood disadvantage that may be associated with these outcomes.

Association between neighborhood availability of physical activity facilities and cognitive performance in older adults

The existing evidence on the contextual influence of the availability of local facilities for physical activity on the cognitive health of elderly residents is sparse. This study examined the association between neighborhood physical activity facilities and cognitive health in older individuals. A cohort study of community-dwelling older adults was performed using baseline data and follow-up data from the Taiwan Biobank. Cognitive health was measured in 32,396 individuals aged 60–70 years using the Mini-Mental State Examination (MMSE) with follow-up information on 8025 participants. The district was used as the proxy for local neighborhood. To determine neighborhood physical activity facilities, school campuses, parks, activity centers, gyms, swimming pools, and stadiums were included. Multilevel linear regression models were applied to examine the associations of neighborhood physical activity facilities with baseline MMSE and MMSE decline during follow-up, with adjustment for individual factors and neighborhood socioeconomic characteristics. Multilevel analyses revealed that there was a neighborhood-level effect on cognitive health among older adults. After adjusting for compositional and neighborhood socioeconomic characteristics, baseline MMSE was higher in individuals living in the middle- (beta = 0.12, p-value = 0.140) and high-density facility (beta = 0.22, p-value = 0.025) groups than in the low-density group (p-value for trend-test = 0.031). MMSE decline during follow-up was slower in the middle- (beta = 0.15, p-value = 0.114) and high-density facility (beta = 0.27, p-value = 0.052) groups than in the low-density group (p-value for trend-test = 0.032). Greater neighborhood availability of physical activity facilities was associated with better cognitive health among older residents. These findings have implications for designing communities and developing strategies to support cognitive health of an aging population.

COVID-19 case rates, spatial mobility, and neighbourhood socioeconomic characteristics in Toronto: a spatial-temporal analysis.

This study has two primary research objectives: (1) to investigate the spatial clustering pattern of mobility reductions and COVID-19 cases in Toronto and their relationships with marginalized populations, and (2) to identify the most relevant socioeconomic characteristics that relate to human mobility and COVID-19 case rates in Toronto's neighbourhoods during five distinct time periods of the pandemic. Using a spatial-quantitative approach, we combined hot spot analyses, Pearson correlation analyses, and Wilcoxon two-sample tests to analyze datasets including COVID-19 cases, a mobile device-derived indicator measuring neighbourhood-level time away from home (i.e., mobility), and socioeconomic data from 2016 census and Ontario Marginalization Index. Temporal variations among pandemic phases were examined as well. The paper identified important spatial clustering patterns of mobility reductions and COVID-19 cases in Toronto, as well as their relationships with marginalized populations. COVID-19 hot spots were in more materially deprived neighbourhood clusters that had more essential workers and people who spent more time away from home. While the spatial pattern of clusters of COVID-19 cases and mobility shifted slightly over time, the group socioeconomic characteristics that clusters shared remained similar in all but the first time period. A series of maps and visualizations were created to highlight the dynamic spatiotemporal patterns. Toronto's neighbourhoods have experienced the COVID-19 pandemic in significantly different ways, with hot spots of COVID-19 cases occurring in more materially and racially marginalized communities that are less likely to reduce their mobility. The study provides solid evidence in a Canadian context to enhance policy making and provide a deeper understanding of the social determinants of health in Toronto during the COVID-19 pandemic.

Workplace socioeconomic characteristics and coronary heart disease: a nationwide follow-up study

ObjectivesImportant gaps in previous research include a lack of studies on the association between socioeconomic characteristics of the workplace and coronary heart disease (CHD).We aimed to examine two contextual factors...

Inequalities in urban greenness and epigenetic aging: Different associations by race and neighborhood socioeconomic status.

Slower epigenetic aging is associated with exposure to green space (greenness); however, the longitudinal relationship has not been well studied, particularly in minority groups. We investigated the association between 20-year exposure to greenness [Normalized Difference Vegetation Index (NDVI)] and epigenetic aging in a large, biracial (Black/white), U.S. urban cohort. Using generalized estimating equations adjusted for individual and neighborhood socioeconomic characteristics, greater greenness was associated with slower epigenetic aging. Black participants had less surrounding greenness and an attenuated association between greenness and epigenetic aging [βNDVI5km: -0.80, 95% confidence interval (CI): -4.75, 3.13 versus βNDVI5km: -3.03, 95% CI: -5.63, -0.43 in white participants]. Participants in disadvantaged neighborhoods showed a stronger association between greenness and epigenetic aging (βNDVI5km: -3.36, 95% CI: -6.65, -0.08 versus βNDVI5km: -1.57, 95% CI: -4.12, 0.96 in less disadvantaged). In conclusion, we found a relationship between greenness and slower epigenetic aging, and different associations by social determinants of health such as race and neighborhood socioeconomic status.

Spatial Inequities in Life Expectancy in Small Areas of Buenos Aires, Argentina 2015–2017

Studies of life expectancy (LE) in small areas of cities are relatively common in high-income countries but rare in Latin American countries. Small-area estimation methods can help to describe and quantify inequities in LE between neighborhoods and their predictors. Our objective was to analyze the distribution and spatial patterning of LE across small areas of Ciudad Autónoma de Buenos Aires (CABA), Argentina, and its association with socioeconomic characteristics. As part of the SALURBAL project, we used georeferenced death certificates in 2015–2017 for CABA, Argentina. We used a spatial Bayesian Poisson model using the TOPALS method to estimate age- and sex-specific mortality rates. We used life tables to estimate LE at birth. We obtained data on neighborhood socioeconomic characteristics from the 2010 census and analyzed their associations. LE at birth was higher for women (median of across neighborhoods = 81.1 years) compared to men (76.7 years). We found a gap in LE of 9.3 (women) and 14.9 years (men) between areas with the highest and the lowest LE. Better socioeconomic characteristics were associated with higher LE. For example, mean differences in LE at birth in areas with highest versus lowest values of composite SES index were 2.79 years (95% CI: 2.30 to 3.28) in women and 5.61 years (95% CI: 4.98 to 6.24) in men. We found large spatial inequities in LE across neighborhoods of a large city in Latin America, highlighting the importance of place-based policies to address this gap.

Neighborhood Socioeconomic Characteristics Associated with the COVID-19 Incidence in Elementary School Children: An Ecological Study in Osaka City, Japan.

We aimed to determine whether neighborhood socioeconomic characteristics are associated with the coronavirus disease 2019 (COVID-19) incidence in elementary school children and, if so, the associated characteristics. We obtained data on the number of infected children from 282 public elementary schools and the socioeconomic characteristics of each school district in Osaka City, Japan. We examined associations between these variables through negative binomial regression analyses. The proportion of employment in the wholesale and retail trade industry and the college graduation rate were significantly positively and negatively associated, respectively, with the total number of COVID-19-infected children. It was discovered that percentages of employment in the accommodation and food service industries in Wave 2, wholesale and retail trade industries after Wave 3, and healthcare and social assistance industries in Wave 5 were significantly positively associated with the number of infected children; likewise, the college graduation rate in Wave 5 was significantly negatively associated with the number of infected children. Our findings provide insight into the relevant and important areas of focus for public health policymakers and practitioners to ensure reduced disparities in COVID-19 infection rates.

Association of Playground "Playability" With Physical Activity and Energy Expenditure.

Children's physical activity, especially play, is important for healthy physical, social, and psychological development. Playgrounds are public spaces for children, but not all playgrounds are conducive to play and physical activity. We examined "playability," the ability of a space to promote active play, and associations with moderate-to-vigorous physical activity (MVPA) and energy expenditure. This cross-sectional study assessed playground features with the Play Space Audit Tool; we calculated playability scores from audit data, overall and by domain (general amenities, surface, path, and play structure), from playgrounds in 70 parks in Chicago, Illinois, in 2017. We observed 2,712 individuals during the audits and used the System for Observing Play and Recreation in Communities tool to assess MVPA and energy expenditure. We used generalized estimating equation negative binomial regression to calculate incidence rate ratios for MVPA and mixed effects models to calculate energy expenditure (in kcal/kg/min) associated with playability scores. General amenities and play structure scores were associated with 1.28 (95% CI, 1.08-1.52) and 1.15 (95% CI, 1.00-1.31) times as many individuals (any age) engaged in MVPA, respectively. The general amenities score was significantly associated with 0.51 (95% CI, 0.24-0.79) and 0.42 (95% CI, 0.15-0.68) higher energy expenditure in renovated playgrounds and in all playgrounds, respectively. Overall, general amenities and play structure scores were associated with MVPA and were robust to adjustment for weather, neighborhood socioeconomic characteristics, and crime. These playground playability indices may strengthen future evaluations of community infrastructure for children's physical activity.

Socioeconomic disparities in fertility treatments and associated likelihood of livebirth following in vitro fertilization

To determine whether neighborhood-level socioeconomic characteristics are associated with the likelihood of livebirth (LB) following in vitro fertilization (IVF). Specifically, we evaluated neighborhood-level household income, unemployment rate, and educational attainment. A retrospective cross-sectional study was conducted for patients undergoing autologous IVF cycles. Large academic health system. For each patient, ZIP code of residence was used as a proxy for neighborhood. Neighborhood characteristics were compared between patients with and without LB. Generalized estimating model was used to adjust the association between SES factors and likelihood of a live birth with respect to relevant clinical factors. A total of 4942 autologous IVF cycles from 2768 patients were included: 1717 (62.0%) had at least one associated LB. Patients who achieved LB from IVF were younger, had higher anti-Mullerian hormone (AMH) levels, lower body mass index (BMI), and differed by ethnic background, primary language, and neighborhood socioeconomic characteristics. In a multivariable model, language, age, AMH, and BMI were associated with a live birth from IVF. None of the neighborhood-level socioeconomic variables were associated with the total number of IVF cycles or cycles required to achieve first LB. Patients living in neighborhoods with lower annual household income have lower odds of livebirth after IVF compared to those living in more affluent areas, despite undergoing the same number of IVF stimulation cycles.

Using neighborhood characteristics to predict vacancy types: Comparing multi-scale conditions surrounding existing vacant lots.

Vacant and abandoned land can be public eyesores that can potentially result in neighborhood distress in the long term. In some cases, the contextual conditions of a neighborhood have been shown to have more of a negative effect on communities than the vacant property itself. Maximum opportunities to actually reuse vacant and abandoned land is known to primarily exist in cases where the surrounding area has locational benefits or when local economic conditions are hopeful. This study examines and compares neighborhood socioeconomic characteristics around vacant lots in Minneapolis, Minnesota, USA, to identify spatial heterogeneity within vacancy types and neighborhood characteristics. Specifically, we examine 1) if the socioeconomic characteristics of a neighborhood can predict existing vacant lots and 2) what neighborhood characteristics are associated with certain vacant lot types. Three logistic regressions were tested with different buffers around each vacant lot, and a total of eighteen regressions were performed to capture the effects on six vacancy types. Results suggest that there are various types of vacancies interacting differently at the neighborhood scale, and that a large-scale neighborhood context matters when predicting vacancy types. The results also indicate three salient points. First, minority populations are a strong predictor of residential and commercial vacancies. Second, high-income areas tend to predict vacancies with potential investment opportunities or vacancies as a part of an existing park or recreational system. Third, vacant properties designated for institutional land uses tend to be found in lower-income areas, yet, not necessarily in areas with high minority populations. Managing and repurposing vacant and abandoned land should be handled more progressively with a better understanding of the socioeconomic characteristics of neighborhoods. Further, examining vacancy types by community can be a way to diagnose potential neighborhood risks associated with vacant and abandoned land.

Neighborhood disinvestment and severe maternal morbidity in the state of California

Social determinants of health, including neighborhood context, may be a key driver of severe maternal morbidity and its related racial and ethnic inequities; however, investigations remain limited. This study aimed to examine the associations between neighborhood socioeconomic characteristics and severe maternal morbidity, as well as whether the associations between neighborhood socioeconomic characteristics and severe maternal morbidity were modified by race and ethnicity. This study leveraged a California statewide data resource on all hospital births at ≥20 weeks of gestation (1997-2018). Severe maternal morbidity was defined as having at least 1 of 21 diagnoses and procedures (eg, blood transfusion or hysterectomy) as outlined by the Centers for Disease Control and Prevention. Neighborhoods were defined as residential census tracts (n=8022; an average of 1295 births per neighborhood), and the neighborhood deprivation index was a summary measure of 8 census indicators (eg, percentage of poverty, unemployment, and public assistance). Mixed-effects logistic regression models (individuals nested within neighborhoods) were used to compare odds of severe maternal morbidity across quartiles (quartile 1 [the least deprived] to quartile 4 [the most deprived]) of the neighborhood deprivation index before and after adjustments for maternal sociodemographic and pregnancy-related factors and comorbidities. Moreover, cross-product terms were created to determine whether associations were modified by race and ethnicity. Of 10,384,976 births, the prevalence of severe maternal morbidity was 1.2% (N=120,487). In fully adjusted mixed-effects models, the odds of severe maternal morbidity increased with increasing neighborhood deprivation index (odds ratios: quartile 1, reference; quartile 4, 1.23 [95% confidence interval, 1.20-1.26]; quartile 3, 1.13 [95% confidence interval, 1.10-1.16]; quartile 2, 1.06 [95% confidence interval, 1.03-1.08]). The associations were modified by race and ethnicity such that associations (quartile 4 vs quartile 1) were the strongest among individuals in the "other" racial and ethnic category (1.39; 95% confidence interval, 1.03-1.86) and the weakest among Black individuals (1.07; 95% confidence interval, 0.98-1.16). Study findings suggest that neighborhood deprivation contributes to an increased risk of severe maternal morbidity. Future research should examine which aspects of neighborhood environments matter most across racial and ethnic groups.