Population density, distance to public transportation, and health of women in low-income neighborhoods

Scientometric Analysis of The Relationship between a Built Environment and Cardiovascular Disease

The prevention and treatment of cardiovascular disease (CVD) are necessary to improve patient quality of life and to reduce the burden of medical and other social problems. Reducing the impact of CVD through environmental intervention was hailed as the most economical approach and research into such interventions is becoming key. The purpose of this article is to summarize the research topics and developments in the field of the built environment and CVD between 2000 and 2021 using scientometric analysis. In total, 1304 records retrieved from the Web of Science core database were analyzed using CiteSpace software, and the results were displayed using knowledge mapping. The number of publications and conferences relating to the built environment and CVD showed an upward trend over the study period, with the United States taking the lead. Physical activity and the food environment were used as mediators and entry points to map the relationship between the built environment and CVD. Walkability, residence characteristics, the food environment, and greenness were key research topics. Research shifted over the period to incorporate quantitative analyses of subjective feelings while focusing on decreasing sedentary behavior. Understanding the variability in the built environment is critical to improving the generalizability of the findings presented in the individual studies. Inter-disciplinary and multi-disciplinary research is conducive to innovation and ensuring the integration of real environmental elements. This study provides an overview and valuable guidance for researchers relating to how the built environment impacts CVD.

Use of Geographic Information Systems to Explore Associations between Neighborhood Attributes and Mental Health Outcomes in Adults: A Systematic Review

Background: Neighborhood attributes are increasingly recognized as factors shaping mental health in adults. Geographic information systems (GIS) offer an innovative approach for quantifying neighborhood attributes and studying their influence on mental health outcomes. Our aim was to describe GIS applications used in neighborhood-related mental health research and how neighborhood attributes are related to depressive symptoms or psychological distress in community-residing adults. Methods: We conducted a systematic review of studies published in English that included GIS techniques and a validated questionnaire of depressive symptoms or psychological distress. Medline, PsycInfo, Embase, Scopus, CINAHL, GEOBASE, and Compedex were searched to June 2020. Study quality was assessed by a modification of the Joanna Briggs Institute’s Checklist for Analytical Cross-sectional Studies. Results: Thirty-two studies met the inclusion criteria. Studies varied in definitions of neighborhood and GIS-derived measurements of neighborhood attributes. Neighborhood attributes were significantly associated with mental health outcomes, although findings were not consistent. Moderating factors (e.g., gender, living conditions) significantly influenced depressive symptoms or psychological distress. Conclusion: Neighborhood attributes are important factors influencing mental health in adults. Consensus may be needed on how to standardize the neighborhood unit or GIS-derived measures of neighborhoods in order to explain depression or psychological distress in diverse adult populations.

The Spatial and Social Patterning of Property and Violent Crime in Toronto Neighbourhoods: A Spatial-Quantitative Approach

Criminal activities are often unevenly distributed over space. The literature shows that the occurrence of crime is frequently concentrated in particular neighbourhoods and is related to a variety of socioeconomic and crime opportunity factors. This study explores the broad patterning of property and violent crime among different socio-economic stratums and across space by examining the neighbourhood socioeconomic conditions and individual characteristics of offenders associated with crime in the city of Toronto, which consists of 140 neighbourhoods. Despite being the largest urban centre in Canada, with a fast-growing population, Toronto is under-studied in crime analysis from a spatial perspective. In this study, both property and violent crime data sets from the years 2014 to 2016 and census-based Ontario-Marginalisation index are analysed using spatial and quantitative methods. Spatial techniques such as Local Moran’s I are applied to analyse the spatial distribution of criminal activity while accounting for spatial autocorrelation. Distance-to-crime is measured to explore the spatial behaviour of criminal activity. Ordinary Least Squares (OLS) linear regression is conducted to explore the ways in which individual and neighbourhood demographic characteristics relate to crime rates at the neighbourhood level. Geographically Weighted Regression (GWR) is used to further our understanding of the spatially varying relationships between crime and the independent variables included in the OLS model. Property and violent crime across the three years of the study show a similar distribution of significant crime hot spots in the core, northwest, and east end of the city. The OLS model indicates offender-related demographics (i.e., age, marital status) to be a significant predictor of both types of crime, but in different ways. Neighbourhood contextual variables are measured by the four dimensions of the Ontario-Marginalisation Index. They are significantly associated with violent and property crime in different ways. The GWR is a more suitable model to explain the variations in observed property crime rates across different neighbourhoods. It also identifies spatial non-stationarity in relationships. The study provides implications for crime prevention and security through an enhanced understanding of crime patterns and factors. It points to the need for safe neighbourhoods, to be built not only by the law enforcement sector but by a wide range of social and economic sectors and services.

Modeling Health Disparities and Outcomes in Disenfranchised Populations

The Health Disparities and Outcomes (HDO) model originally created to explain the complexity of obtaining healthcare in rural settings has been revised and updated using emerging theoretical models of adversity and inequity and two decades of empirical work by the authors. With a strong orientation to explaining population-based health inequities, the HDO is applied to individuals with Serious Mental Illness (SMI), to explain their high rates of morbidity and mortality compared to the general population. Individual-, community-, and system-level factors that reflect an understanding of life-long risk, accrued hazards associated with multiple and intersecting disadvantages, and difficulty obtaining healthcare that meets accepted standards are described. The revised HDO can be applied to populations with disproportionate health challenges to identify multi-level factors that affect illness trajectory and overall health outcomes.

Urban Green Space and the Pursuit of Health Equity in Parts of the United States

Research has demonstrated that inequitable access to green space can relate to health disparities or inequalities. This commentary aims to shift the dialogue to initiatives that have integrated green spaces in projects that may promote health equity in the United States. Specifically, we connect this topic to factors such as community revitalization, affordable housing, neighborhood walkability, food security, job creation, and youth engagement. We provide a synopsis of locations and initiatives in different phases of development along with characteristics to support effectiveness and strategies to overcome challenges. The projects cover locations such as Atlanta (GA), Los Angeles (CA), the District of Columbia (Washington D.C.), South Bronx (NY), and Utica (NY). Such insight can develop our understanding of green space projects that support health equity and inform the dialogue on this topic in ways that advance research and advocacy.