Neighborhood Socioeconomic Characteristics Research Articles

Neighborhood socioeconomic factors and characteristics correlated with avoidable emergency department visits: A spatial analysis of a Canadian academic hospital.

The influence of neighborhood characteristics and socioeconomic status (SES) factors on avoidable emergency department (ED) utilization is not well understood in a universal healthcare system. We examined correlations between these factors and avoidable ED visits at a Canadian academic hospital. We conducted a retrospective cohort study using administrative ED data from a hospital in Hamilton, Canada from April 1, 2018 to August 31, 2023, and neighborhood data from the Statistics Canada Census of Population 2021. Avoidable visits were classified using the Emergency Department Avoidability Classification (EDAC), and mapped to neighborhoods using Canadian postal codes. SES was defined primarily based on education attained, household income, employment and housing security. The top 20 postal codes with the highest avoidable ED visits were categorized into quartiles and analyzed for trends using chi-squared tests of spatial association and Spearman rank correlations. A consistent ordinal trend across quartiles was observed throughout the study period, with quartile 1 representing the lowest avoidable ED visits and quartile 4 the highest. The quartiles were unevenly distributed spatially, though there was a significant association between close proximity to the ED and avoidable visits (X2 = 7.07, p <0.05). The quartile with the highest avoidable ED visits (quartile 4) had the greatest proportion of one-person households (35.5%) and one-parent families (37.8%), and showed statistically significant positive correlations with male sex, living alone and having an indigenous identity. Quartile 4 had the highest rates of individuals not completing high school (18.6%, p < 0.05), unemployment (13.7%), households spending greater than 30% of their income on shelter (26.5%), and households earning less than $30,000 annually (16.6%, compared to 8.7% in quartile 1 with the lowest avoidable ED visits). In a universal healthcare setting, lower SES neighborhoods were correlated with higher rates of avoidable ED visits. Targeted interventions that address social determinants of health disparities in neighborhoods with lower SES could reduce the burden of avoidable ED visits, and promote more equitable healthcare utilization.

Association of urban infrastructure and physical activity in Santiago and its modifications by neighborhood and municipality level socio-economic characteristics (SES).

Association of urban infrastructure and physical activity in Santiago and its modifications by neighborhood and municipality level socio-economic characteristics (SES).

C. auris and neighborhood socioeconomic vulnerability in the state of Maryland from 2019 to 2022.

Candida auris is an emerging fungal pathogen increasingly recognized as a cause of healthcare-associated infections including outbreaks. We performed a mixed-methods study to characterize the emergence of C. auris in the state of Maryland from 2019 to 2022, with a focus on socioeconomic vulnerability and infection prevention opportunities. We describe all case-patients of C. auris among Maryland residents from June 2019 to December 2021 detected by Maryland Department of Health. We compared neighborhood socioeconomic characteristics of skilled nursing facilities (SNFs) with and without C. auris transmission outbreaks using both the social vulnerability index (SVI) and the area deprivation index (ADI). The SVI and the ADI were obtained at the state level, with an SVI ≥ 75th percentile or an ADI ≥ 80th percentile considered severely disadvantaged. We summarized infection control assessments at SNFs with outbreaks using a qualitative analysis. A total of 140 individuals tested positive for C. auris in the study period in Maryland; 46 (33%) had a positive clinical culture. Sixty (43%) were associated with a SNF, 37 (26%) were ventilated, and 87 (62%) had a documented wound. Separate facility-level neighborhood analysis showed SNFs with likely C. auris transmission were disproportionately located in neighborhoods in the top quartile of deprivation by the SVI, characterized by low socioeconomic status and high proportion of racial/ethnic minorities. Multiple infection control deficiencies were noted at these SNFs. Neighborhood socioeconomic vulnerability may contribute to the emergence and transmission of C. auris in a community.

Evaluating the relationship between health-related social needs, patient demographics, and access to biologics in patients with moderate-to-severe asthma in Bronx, NY

Objectives This study assesses the relationship between patient age, gender, race, socioeconomic status, social determinants of health (SDoH), and access to biologics (products isolated from natural sources that target specific molecules, proteins, and cells) in patients with moderate-to-severe asthma in Bronx, NY. Methods Cohort of 289 patients with moderate-to-severe asthma treated at Montefiore Medical Center (MMC) from 2018 to 2020 was used. Patient demographics, self-reported social needs, and neighborhood socioeconomic characteristics were analyzed. Neighborhood socioeconomic status was estimated by determining median income in patients’ residential zip codes using 2020 Census data and grouping patients based on whether neighborhood median income was above or below New York State (NYS) median ($71,117/year). Area Deprivation Index tool (ADI) was used as an additional measure of neighborhood socioeconomic status. Results Patients living in regions with incomes below NYS median found to have longer wait times between biologic approval to administration than patients living in regions above median income (p = 0.012). Mean time from insurance approval to biologic administration was significantly different between Black and Latinx patients (p = 0.009). No significant difference found for patient regional income status and time from biologic prescription to approval. No significant differences in access to biologics were found for age, gender, number of health-related social needs, or patient ADI quartile. Conclusions Patients who live in areas of NYC where median income is below NYS median are more likely to experience delays in access to biologics, specifically due to time between approval and administration of medication.

Development of Neighborhood Trajectories Employing Historic Redlining and the Area Deprivation Index.

The role of historic residential redlining on health inequities is intertwined with policy changes made before and after the 1930s that influence current neighborhood characteristics and shape ongoing structural racism in the United States (U.S.). We developed Neighborhood Trajectories which combine historic redlining data and the current neighborhood socioeconomic characteristics as a novel approach to studying structural racism. Home Owners' Loan Corporation (HOLC) neighborhoods for the entire U.S. were used to map the HOLC grades to the 2020 U.S. Census block group polygons based on the percentage of HOLC areas in each block group. Each block group was also assigned an Area Deprivation Index (ADI) from the Neighborhood Atlas®. To evaluate changes in neighborhoods from historic HOLC grades to present degree of deprivation, we aggregated block groups into "Neighborhood Trajectories" using historic HOLC grades and current ADI. The Neighborhood Trajectories are "Advantage Stable"; "Advantage Reduced"; "Disadvantage Reduced"; and "Disadvantage Stable." Neighborhood Trajectories were established for 13.3% (32,152) of the block groups in the U.S., encompassing 38,005,799 people. Overall, the Disadvantage-Reduced trajectory had the largest population (16,307,217 people). However, the largest percentage of non-Hispanic/Latino Black residents (34%) fell in the Advantage-Reduced trajectory, while the largest percentage of Non-Hispanic/Latino White residents (60%) fell in the Advantage-Stable trajectory. The development of the Neighborhood Trajectories affords a more nuanced mechanism to investigate dynamic processes from historic policy, socioeconomic development, and ongoing marginalization. This adaptable methodology may enable investigation of ongoing sociopolitical processes including gentrification of neighborhoods (Disadvantage-Reduced trajectory) and "White flight" (Advantage Reduced trajectory).

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.