Drop-And-Spin Virtual Neighborhood Auditing: Assessing Built Environment for Linkage to Health Studies

Associations between observed neighborhood physical disorder and health behaviors, New Jersey behavioral risk factor Surveillance System 2011-2016

This study tested associations between observed neighborhood physical disorder and tobacco use, alcohol binging, and sugar-sweetened beverage consumption among a large population-based sample from an urban area of the United States. Individual-level data of this cross-sectional study were from adult respondents of the New Jersey Behavioral Risk Factor Surveillance System, 2011-2016 (n = 62,476). Zip code tabulation area-level observed neighborhood physical disorder were from virtual audits of 23,276 locations. Tobacco use (current cigarette smoking or chewing tobacco, snuff, or snus use), monthly binge drinking occasions (5+/4+ drinks per occasion among males/females), and monthly sugar-sweetened beverages consumed were self-reported. Logistic and negative binomial regression models were used to generate odds ratios, prevalence rate ratios (PRR), 95 % confidence intervals (CI) by levels of physical disorder. Compared to the lowest quartile, residence in the second (PRR: 1.16; 95 % CI: 1.03, 1.13), third (PRR: 1.24; 95 % CI: 1.10, 1.40), and fourth (highest) quartile of physical disorder (PRR: 1.24; 95 % CI: 1.10, 1.40) was associated with higher monthly sugar-sweetened beverage consumption. Associations involving tobacco use and alcohol binging were mixed. Observed neighborhood disorder might be associated with unhealthy behaviors, especially sugar-sweetened beverage consumption.

Lessons Learned from a Citywide Abandoned Housing Experiment

Problem research strategy and findings

The negative impact of vacant and abandoned housing in city neighborhoods is extreme, affecting health and quality of life, promoting violence, and leading to further abandonment. One approach to addressing abandoned housing is to intervene with low-cost interventions that provide a visual sense of ownership. We tested whether a low-cost remediation of abandoned and vacant houses or a trash cleanup intervention would make a noticeable difference in the levels of nearby disrepair, disorder, and public safety. The abandoned housing remediation and trash cleanup interventions were a test of compliance with municipal ordinances. We used an experimental design to test the causal effects of the ordinances, and because the scale of abandonment was too large to provide treatment to all abandoned houses in the city. We used systematic social observation methods to rate changes in disrepair, disorder, and litter at housing sites and on the city blocks they were located, and police reported data on gun violence and illegal substance uses. Our experimental design allowed us to see if observed disrepair, disorder, and public safety improved after working windows and doors were installed on abandoned houses compared with a trash cleanup around properties or a no-intervention control condition. Our results showed significant changes in observed disrepair, disorder, and gun violence and illustrate the benefits of experimental evaluations of place-based changes to the built environment.

Takeaway for practice

Improving compliance with ordinances to remediate abandoned housing can make a noticeable difference in disrepair in neighborhoods and contribute improved public safety. We illustrate how planners can use field experiments in partnership with city agencies, nonprofit community groups, and local universities to discover novel approaches to advance place-based changes to the built environment that can help economically disadvantaged communities abate problems of physical disorder.

Street View Imagery (SVI) in the Built Environment: A Theoretical and Systematic Review

Street view imagery (SVI) provides efficient access to data that can be used to research spatial quality at the human scale. The previous reviews have mainly focused on specific health findings and neighbourhood environments. There has not been a comprehensive review of this topic. In this paper, we systematically review the literature on the application of SVI in the built environment, following a formal innovation–decision framework. The main findings are as follows: (I) SVI remains an effective tool for automated research assessments. This offers a new research avenue to expand the built environment-measurement methods to include perceptions in addition to physical features. (II) Currently, SVI is functional and valuable for quantifying the built environment, spatial sentiment perception, and spatial semantic speculation. (III) The significant dilemmas concerning the adoption of this technology are related to image acquisition, the image quality, spatial and temporal distribution, and accuracy. (IV) This research provides a rapid assessment and provides researchers with guidance for the adoption and implementation of SVI. Data integration and management, proper image service provider selection, and spatial metrics measurements are the critical success factors. A notable trend is the application of SVI towards a focus on the perceptions of the built environment, which provides a more refined and effective way to depict urban forms in terms of physical and social spaces.

Microscale pedestrian environment surrounding pedestrian injury sites in Washington state, 2015-2020

OBJECTIVE

While microscale pedestrian environment features such as sidewalks and crosswalks can affect pedestrian safety, it is challenging to assess microscale environment associated risk across locations or at scale. Addressing these challenges requires an efficient auditing protocol that can be used to assess frequencies of microscale environment features. For this reason, we developed an eight-item pedestrian environment virtual audit protocol and conducted a descriptive epidemiologic study of pedestrian injury in Washington State, USA.

METHODS

We used data from police reports at pedestrian-automotive collision sites where the pedestrian was seriously injured or died. At each collision site, high school students participating in an online summer internship program virtually audited Google Street View imagery to assess the presence of microscale pedestrian environment features such as crosswalks and streetlighting. We assessed inter-rater reliability using Cohen's kappa and explored prevalence of eight microscale environment features in relation to injury severity and municipal boundaries.

RESULTS

There were 2248 motor vehicle crashes eliciting police response and resulting in death or serious injury of a pedestrian in Washington State between January 1, 2015 and May 8, 2020. Of the crashes resulting in serious injury or death, 498 (22%) resulted in fatalities and 1840 (82%) occurred within municipal boundaries. Cohen's kappa scores for the eight pedestrian features that were audited ranged from 0.52 to 0.86. Audit results confirmed that features such as sidewalks and crosswalks were more common at collision sites within city limits.

CONCLUSIONS

High school student volunteers with minimal training can reliably audit microscale pedestrian environments using limited resources.

Pathways between objective and perceived neighborhood factors among Black breast cancer survivors

BACKGROUND

Mounting evidence supports associations between objective neighborhood disorder, perceived neighborhood disorder, and health, yet alternative explanations involving socioeconomic and neighborhood social cohesion have been understudied. We tested pathways between objective and perceived neighborhood disorder, perceived neighborhood social cohesion, and socioeconomic factors within a longitudinal cohort.

METHODS

Demographic and socioeconomic information before diagnosis was obtained at interviews conducted approximately 10 months post-diagnosis from participants in the Women's Circle of Health Follow-up Study - a cohort of breast cancer survivors self-identifying as African American or Black women (n = 310). Neighborhood perceptions were obtained during follow-up interviews conducted approximately 24 months after diagnosis. Objective neighborhood disorder was from 9 items audited across 23,276 locations using Google Street View and scored to estimate disorder values at each participant's residential address at diagnosis. Census tract socioeconomic and demographic composition covariates were from the 2010 U.S. Census and American Community Survey. Pathways to perceived neighborhood disorder were built using structural equation modelling. Model fit was assessed from the comparative fit index and root mean square error approximation and associations were reported as standardized coefficients and 95% confidence intervals.

RESULTS

Higher perceived neighborhood disorder was associated with higher objective neighborhood disorder (β = 0.20, 95% CI: 0.06, 0.33), lower neighborhood social cohesion, and lower individual-level socioeconomic factors (final model root mean square error approximation 0.043 (90% CI: 0.013, 0.068)). Perceived neighborhood social cohesion was associated with individual-level socioeconomic factors and objective neighborhood disorder (β = - 0.11, 95% CI: - 0.24, 0.02).

CONCLUSION

Objective neighborhood disorder might be related to perceived disorder directly and indirectly through perceptions of neighborhood social cohesion.

Associations between neighborhood disinvestment and breast cancer outcomes within a populous state registry

BACKGROUND

Breast cancer (BrCa) outcomes vary by social environmental factors, but the role of built-environment factors is understudied. The authors investigated associations between environmental physical disorder-indicators of residential disrepair and disinvestment-and BrCa tumor prognostic factors (stage at diagnosis, tumor grade, triple-negative [negative for estrogen receptor, progesterone receptor, and HER2 receptor] BrCa) and survival within a large state cancer registry linkage.

METHODS

Data on sociodemographic, tumor, and vital status were derived from adult women who had invasive BrCa diagnosed from 2008 to 2017 ascertained from the New Jersey State Cancer Registry. Physical disorder was assessed through virtual neighborhood audits of 23,276 locations across New Jersey, and a personalized measure for the residential address of each woman with BrCa was estimated using universal kriging. Continuous covariates were z scored (mean ± standard deviation [SD], 0 ± 1) to reduce collinearity. Logistic regression models of tumor factors and accelerated failure time models of survival time to BrCa-specific death were built to investigate associations with physical disorder adjusted for covariates (with follow-up through 2019).

RESULTS

There were 3637 BrCa-specific deaths among 40,963 women with a median follow-up of 5.3 years. In adjusted models, a 1-SD increase in physical disorder was associated with higher odds of late-stage BrCa (odds ratio, 1.09; 95% confidence interval, 1.02-1.15). Physical disorder was not associated with tumor grade or triple-negative tumors. A 1-SD increase in physical disorder was associated with a 10.5% shorter survival time (95% confidence interval, 6.1%-14.6%) only among women who had early stage BrCa.

CONCLUSIONS

Physical disorder is associated with worse tumor prognostic factors and survival among women who have BrCa diagnosed at an early stage.

Panoramic Street-Level Imagery in Data-Driven Urban Research: A Comprehensive Global Review of Applications, Techniques, and Practical Considerations

The release of Google Street View in 2007 inspired several new panoramic street-level imagery platforms including Apple Look Around, Bing StreetSide, Baidu Total View, Tencent Street View, Naver Street View, and Yandex Panorama. The ever-increasing global capture of cities in 360° provides considerable new opportunities for data-driven urban research. This paper provides the first comprehensive, state-of-the-art review on the use of street-level imagery for urban analysis in five research areas: built environment and land use; health and wellbeing; natural environment; urban modelling and demographic surveillance; and area quality and reputation. Panoramic street-level imagery provides advantages in comparison to remotely sensed imagery and conventional urban data sources, whether manual, automated, or machine learning data extraction techniques are applied. Key advantages include low-cost, rapid, high-resolution, and wide-scale data capture, enhanced safety through remote presence, and a unique pedestrian/vehicle point of view for analyzing cities at the scale and perspective in which they are experienced. However, several limitations are evident, including limited ability to capture attribute information, unreliability for temporal analyses, limited use for depth and distance analyses, and the role of corporations as image-data gatekeepers. Findings provide detailed insight for those interested in using panoramic street-level imagery for urban research.

Association of Socioeconomic Disadvantage With Mortality and Readmissions Among Older Adults Hospitalized for Pulmonary Embolism in the United States

Background In the United States, hospitalizations for pulmonary embolism (PE) are increasing among older adults insured by Medicare. Although efforts to reduce health disparities have intensified, it remains unclear whether clinical outcomes differ between socioeconomically disadvantaged and nondisadvantaged Medicare beneficiaries hospitalized with PE. Methods and Results In this study, there were 53 386 Medicare fee-for-service beneficiaries age ≥65 years hospitalized for PE between October 2015 and January 2017. Of these, 5494 (10.3%) were socioeconomically disadvantaged and 47 892 (89.7%) were nondisadvantaged. Socioeconomically disadvantaged adults were of similar age as nondisadvantaged adults (77.1 versus 77.0), more likely to be female (68.5% versus 54.2%), and less likely to receive advanced therapies (11.0% versus 12.1%). After adjustment for demographics, 90-day all-cause mortality rates were similar between disadvantaged and nondisadvantaged adults. In contrast, 1-year mortality rates were higher among socioeconomically disadvantaged adults (hazard ratio [HR], 1.16; 95% CI, 1.10-1.22), although these differences were partially attenuated after additional adjustments for comorbidities and PE severity (HR, 1.09; 95% CI, 1.02-1.16). Risk-adjusted 30-day and 90-day all-cause readmission rates were substantially higher among socioeconomically disadvantaged patients (30-day HR, 1.14 [95% CI, 1.06-1.22]; 90-day HR, 1.18 [95% CI, 1.12-1.25]). In addition, 90-day readmissions attributed to PE, deep vein thrombosis, and/or bleeding were higher among socioeconomically disadvantaged patients (HR, 1.16; 95% CI, 1.02-1.32). Conclusions Socioeconomically disadvantaged older adults hospitalized with PE have higher 1-year mortality rates compared with their nondisadvantaged counterparts. Nearly 1 in 3 socioeconomically disadvantaged older adults was readmitted within 90 days of a hospitalization for PE. Targeted strategies are needed to improve transitional and ambulatory care for this vulnerable population.

Measuring Neighborhood Landscapes: Associations between a Neighborhood's Landscape Characteristics and Colon Cancer Survival

Landscape characteristics have been shown to influence health outcomes, but few studies have examined their relationship with cancer survival. We used data from the National Land Cover Database to examine associations between regional-stage colon cancer survival and 27 different landscape metrics. The study population included all adult New Jersey residents diagnosed between 2006 and 2011. Cases were followed until 31 December 2016 (N = 3949). Patient data were derived from the New Jersey State Cancer Registry and were linked to LexisNexis to obtain residential histories. Cox proportional hazard regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI95) for the different landscape metrics. An increasing proportion of high-intensity developed lands with 80–100% impervious surfaces per cell/pixel was significantly associated with the risk of colon cancer death (HR = 1.006; CI95 = 1.002–1.01) after controlling for neighborhood poverty and other individual-level factors. In contrast, an increase in the aggregation and connectivity of vegetation-dominated low-intensity developed lands with 20–<40% impervious surfaces per cell/pixel was significantly associated with the decrease in risk of death from colon cancer (HR = 0.996; CI95 = 0.992–0.999). Reducing impervious surfaces in residential areas may increase the aesthetic value and provide conditions more advantageous to a healthy lifestyle, such as walking. Further research is needed to understand how these landscape characteristics impact survival.

A dual-method approach toward measuring the built environment - sampling optimization, validity, and efficiency of using GIS and virtual auditing

In recent years, GIS and virtual auditing have been widely used to measure the built environment, and each method carries its strengths and weaknesses. To generate higher quality, more cost-effective, and less time-consuming measures, it is necessary to explore dual- or multi-method strategy toward sampling optimization, improvement of measurement, and enhancement of efficiency. To justify the proposed dual-method approach, the study has three major objectives. First, it examines the uncertainties associated with different sample sizes by using GIS to generate scenarios that contrast the validity of measurements to aid sampling optimization in auditing. Second, it compares the validity of GIS measures with those generated through Google Street View Auditing (GSVA) by human raters. Third, it further examines the efficiency of the proposed dual-method approach in comparison to the two individual methods. Such investigation generates several novel findings. First, the study presents important evidence to support that GIS measures can offer sampling guidance applicable to the GSVA method. It leads to a recommendation of sampling sizes (5%-20%) for cases in settings with a mixture of affluent and disadvantaged neighborhoods. Results further indicate that different communities and certain individual features and characteristics may demand different sampling practices. Second, the study found that while GSVA is trustworthy for most characteristic variables, especially those that required subjective input, GIS provides well-validated measures for certain objective environmental attributes. Furthermore, the study reports that a dual-method approach of GIS and GSVA had a lower financial and time burden than using GSVA alone and is thus recommended as a comprehensive solution for optimal measurement of an objective built environment in mixed urban neighborhoods.

Visual cues of the built environment and perceived stress among a cohort of black breast cancer survivors

We investigated relationships between independently observed, visual cues of residential environments and subsequent participant-reported stress within a population-based cohort of Black breast cancer survivors (n = 476). Greater visual cues of engagement - presence of team sports, yard decorations, outdoor seating - (compared to less engagement) was marginally associated with lower perceived stress in univariate models, but attenuated towards null with adjustment for socio-demographic, behavioral, and health-related covariates. Similarly, physical disorder and perceived stress were not associated in adjusted models. Relationships between observed built environment characteristics and perceived stress might be influenced by socioeconomic and health behavior factors, which longitudinal studies should investigate.

Spatial predictive properties of built environment characteristics assessed by drop-and-spin virtual neighborhood auditing

Background

Virtual neighborhood audits have been used to visually assess characteristics of the built environment for health research. Few studies have investigated spatial predictive properties of audit item responses patterns, which are important for sampling efficiency and audit item selection. We investigated the spatial properties, with a focus on predictive accuracy, of 31 individual audit items related to built environment in a major Metropolitan region of the Northeast United States.

Methods

Approximately 8000 Google Street View (GSV) scenes were assessed using the CANVAS virtual audit tool. Eleven trained raters audited the 360^° view of each GSV scene for 10 sidewalk-, 10 intersection-, and 11 neighborhood physical disorder-related characteristics. Nested semivariograms and regression Kriging were used to investigate the presence and influence of both large- and small-spatial scale relationships as well as the role of rater variability on audit item spatial properties (measurement error, spatial autocorrelation, prediction accuracy). Receiver Operator Curve (ROC) Area Under the Curve (AUC) based on cross-validated spatial models summarized overall predictive accuracy. Correlations between predicted audit item responses and select demographic, economic, and housing characteristics were investigated.

Results

Prediction accuracy was better within spatial models of all items accounting for both small-scale and large- spatial scale variation (vs large-scale only), and further improved with additional adjustment for rater in a majority of modeled items. Spatial predictive accuracy was considered ‘Excellent’ (0.8 ≤ ROC AUC < 0.9) for full models of all but four items. Predictive accuracy was highest and improved the most with rater adjustment for neighborhood physical disorder-related items. The largest gains in predictive accuracy comparing large- + small-scale to large-scale only models were among intersection- and sidewalk-items. Predicted responses to neighborhood physical disorder-related items correlated strongly with one another and were also strongly correlated with racial-ethnic composition, socioeconomic indicators, and residential mobility.

Conclusions

Audits of sidewalk and intersection characteristics exhibit pronounced variability, requiring more spatially dense samples than neighborhood physical disorder audits do for equivalent accuracy. Incorporating rater effects into spatial models improves predictive accuracy especially among neighborhood physical disorder-related items.