Optimising measurement of health-related characteristics of the built environment: Comparing data collected by foot-based street audits, virtual street audits and routine secondary data sources

Comparison of the audit method and secondary data sources for assessing health-related characteristics of the built environment in a Brazilian city

This study compared the audit method and secondary data sources for assessing health-related characteristics of the built environment in a Brazilian city. Study sample included 45 census tracts chosen by systematic random sampling, and 36 homes selected from each, from a population-based study. Each neighborhood was delimited by a 400m buffer around the midpoint of the homes. The built environment was assessed for dietary intake and physical activity categorized, respectively, into commercial establishments and services, food retail establishments for home consumption, food retail establishments for immediate consumption, physical activity establishments and public leisure spaces. An audit was conducted in 45 neighborhoods. Secondary data were obtained from lists of commercial establishments and services provided by the city council. Data were analyzed using ArcGIS. Agreement between the audit and secondary data was tested by the intraclass correlation coefficient. Analysis was performed for all neighborhoods and according to neighborhood income tertiles. Results show that agreement between the audit and secondary data was good or excellent for most of the dietary intake and physical activity categories. However, agreement differed according to neighborhood income level across three of the five categories, with lower income neighborhoods presenting the worse agreements. Hence, secondary data should be used with caution to assess health-related characteristics of the built environment in the poorest areas of Brazilian cities.

What is in a food store name? Leveraging large language models to enhance food environment data

Introduction

It is not uncommon to repurpose administrative food data to create food environment datasets in the health department and research settings; however, the available administrative data are rarely categorized in a way that supports meaningful insight or action, and ground-truthing or manually reviewing an entire city or neighborhood is rate-limiting to essential operations and analysis. We show that such categorizations should be viewed as a classification problem well addressed by recent advances in natural language processing and deep learning-with the advent of large language models (LLMs).

Methods

To demonstrate how to automate the process of categorizing food stores, we use the foundation model BERT to give a first approximation to such categorizations: a best guess by store name. First, 10 food retail classes were developed to comprehensively categorize food store types from a public health perspective.

Results

Based on this rubric, the model was tuned and evaluated (F1micro = 0.710, F1macro = 0.709) on an extensive storefront directory of New York City. Second, the model was applied to infer insights from a large, unlabeled dataset using store names alone, aiming to replicate known temporospatial patterns. Finally, a complimentary application of the model as a data quality enhancement tool was demonstrated on a secondary, pre-labeled restaurant dataset.

Discussion

This novel application of an LLM to the enumeration of the food environment allowed for marked gains in efficiency compared to manual, in-person methods, addressing a known challenge to research and operations in a local health department.

Comprehensive walkability assessment of urban pedestrian environments using big data and deep learning techniques

Assessing street walkability is a critical agenda in urban planning and multidisciplinary research, as it facilitates public health, community cohesion, and urban sustainability. Existing evaluation systems primarily focus on objective measurements, often neglecting subjective assessments and the diverse walking needs influenced by different urban spatial elements. This study addresses these gaps by constructing a comprehensive evaluation framework that integrates both subjective and objective dimensions, combining three neighbourhood indicators: Macro-Scale Index, Micro-Scale Index, and Street Walking Preferences Index. A normalization weighting method synthesizes these indicators into a comprehensive index. We applied this framework to assess the street environment within Beijing's Fifth Ring Road. The empirical results demonstrate that: (1) The framework reliably reflects the distribution of walkability. (2) The three indicators show both similarities and differences, underscoring the need to consider the distinct roles of community and street-level elements and the interaction between subjective and objective dimensions. (3) In high-density cities with ring-road development patterns, the Macro-Scale Index closely aligns with the Comprehensive Index, demonstrating its accuracy in reflecting walkability. The proposed framework and findings offer new insights for street walkability research and theoretical support for developing more inclusive, sustainable and walkable cities.

Meteorological gaps in audits of pedestrian environments: a scoping review

BACKGROUND

Weather and season are determinants of physical activity. Therefore, it is important to ensure built environments are designed to mitigate negative impacts of weather and season on pedestrians to prevent these losses. This scoping review aims to identify built environment audits of pedestrian environments developed for use during a specific weather condition or season. Secondly, this review aims to investigate gaps in the inclusion of relevant weather mitigating built environment features in pedestrian environment audit tools.

METHODS

Following a standard protocol, a systematic search was executed in CINAHL, Medline and Web of Science to identify built environment audit tools of pedestrian spaces. These databases were chosen since they are well-known to comprehensively cover health as well as multi-disciplinary research publications relevant to health. Studies were screened, and data were extracted from selected documents by two independent reviewers (e.g., psychometric properties and audit items included). Audit items were screened for the inclusion of weather mitigating built environment features, and the tool's capacity to measure temperature, precipitation, seasonal and sustainability impacts on pedestrians was calculated.

RESULTS

The search returned 2823 documents. After screening and full text review, 27 articles were included. No tool was found that was developed specifically for use during a specific weather condition or season. Additionally, gaps in the inclusion of weather mitigating items were found for all review dimensions (thermal comfort, precipitation, seasonal, and sustainability items). Poorly covered items were: (1) thermal comfort related (arctic entry presence, materials, textures, and colours of buildings, roads, sidewalk and furniture, and green design features); (2) precipitation related (drain presence, ditch presence, hazards, and snow removal features); (3) seasonal features (amenities, pedestrian scale lighting, and winter destinations and aesthetics); and (4) sustainability features (electric vehicle charging stations, renewable energy, car share, and bike share facilities).

CONCLUSIONS

Current built environment audit tools do not adequately include weather / season mitigating items. This is a limitation as it is important to investigate if the inclusion of these items in pedestrian spaces can promote physical activity during adverse weather conditions. Because climate change is causing increased extreme weather events, a need exists for the development of a new built environment audit tool that includes relevant weather mitigating features.

GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies

The industrial revolution and urbanization fundamentally restructured populations' living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies.

Agreement between a web collaborative dataset and an administrative dataset to assess the retail food environment in Mexico

BACKGROUND

Latin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation.

METHODS

In this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland-Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa.

RESULTS

The CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42).

CONCLUSIONS

Google could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.

Measuring Greenspace in Rural Areas for Studies of Birth Outcomes: A Comparison of Street View Data and Satellite Data

Using street view data, in replace of remotely sensed (RS) data, to study the health impact of greenspace has become popular. However, direct comparisons of these two methods of measuring greenspace are still limited, and their findings are inconsistent. On the other hand, almost all studies of greenspace focus on urban areas. The effectiveness of greenspace in rural areas remains to be investigated. In this study, we compared measures of greenspace based on the Google Street View data with those based on RS data by calculating the correlation between the two and evaluating their associations with birth outcomes. Besides the direct measures of greenness, we also compared the measures of environmental diversity, calculated with the two types of data. Our study area consists of the States of New Hampshire and Vermont, USA, which are largely rural. Our results show that the correlations between the two types of greenness measures were weak to moderate, and the greenness at an eye-level view largely reflects the immediate surroundings. Neither the street view data- nor the RS data-based measures identify the influence of greenspace on birth outcomes in our rural study area. Interestingly, the environmental diversity was largely negatively associated with birth outcomes, particularly gestational age. Our study revealed that in rural areas, the effectiveness of greenspace and environmental diversity may be considerably different from that in urban areas.

Scientific research on food environments in Brazil: a scoping review

OBJECTIVE

To map the scientific research on food environments in Brazil, based on the following questions: How many studies have addressed food environments?; What study designs and methodological approaches were applied?; What is the geographic scope of the studies?; What scenarios and dimensions of food environments were studied?; Which population groups were studied?; How were food environments conceptualised?; What are the main limitations of the studies?

DESIGN

Scoping review conducted in four databases, from January 2005 to December 2022, using different food environment-related terms to cover the main types and dimensions proposed in the literature. The studies were independently selected by two authors. A narrative synthesis was used to summarise the findings.

SETTING

Brazil.

PARTICIPANTS

130 articles.

RESULTS

Scientific research on Brazilian food environments has been increasing. The analytical quantitative approach and the cross-sectional design were the most frequently used. Most articles were published in English. The majority of studies evaluated the community food environment, addressed aspects of the physical dimension, sampled the adult population, had food consumption as an outcome, used primary data, and were carried out in capital cities in the Southeast region. Furthermore, in most articles, no conceptual model was explicitly adopted.

CONCLUSIONS

Gaps in literature are related to the need for conducting studies in the Brazilian countryside, the support for the formulation of research questions based on conceptual models, the use of valid and reliable instruments to collect primary data, in addition to the need for a greater number of longitudinal, intervention and qualitative studies.

WalkRollMap.org: Crowdsourcing barriers to mobility

Walking is a simple way to improve health through physical activity. Yet many people experience barriers to walking from a variety of physical, social, and psychological factors that impact their mobility. A challenge for managing and studying pedestrian environments is that barriers often occur at local scales (e.g., sidewalk features), yet such fine scale data on pedestrian facilities and experiences are often lacking or out of date. In response, our team developed WalkRollMap.org an online mapping tool that empowers communities by providing them with tools for crowdsourcing their own open data source. In this manuscript we highlight key functions of the tool, discuss initial approaches to community outreach, and share trends in reporting from the first nine months of operation. As of July 27, 2022, there have been 897 reports, of which 53% served to identify hazards, 34% missing amenities, and 14% incidents. The most frequently reported issues were related to sidewalks (15%), driver behavior (19%), and marked crosswalks (7%). The most common suggested amenities were sidewalks, marked crosswalks, connections (i.e., pathways between streets), and curb cuts. The most common types of incidents all included conflicts with vehicles. Data compiled through WalkRollMap.org offer unique potential for local and timely information on microscale barriers to mobility and are available for use by anyone as data are open and downloadable.

Can imaginary mobilities be conducive to mental health?

Despite the growing interest in the relationship between physical mobility and mental health in health geography, there has been less attention to mobility in the non-physical imaginary realm and its effects on health. This study attempts to explore whether and how 'imaginary mobilities' can be conducive to mental health. It conceptualised imaginary mobilities and designed 'Imaginary Travels' as a type of imaginary mobility. To verify the research questions, 50 young unemployed people living in Seoul, South Korea, were examined (experimental group: n = 25; control group: n = 25). The results demonstrate the immediate and long-term therapeutic effects of Imaginary Travels as imaginary mobility using three psychological questionnaires in the quantitative analysis and data derived from interviews and diary entries in the qualitative analysis. The quantitative statistical analysis revealed significant effects in the experimental group in contrast to the control group. The qualitative analysis indicated that imaginary mobilities are conducive to mental health through immersing, exploring, and practising inner geographies. These findings have implications for understanding mobilities and their associated therapeutic qualities in the imaginary realm beyond the physical realm.

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.

Measuring the Built Environment in Studies of Child Health-A Meta-Narrative Review of Associations

Although the built environment (BE) is important for children’s health, there is little consensus about which features are most important due to differences in measurement and outcomes across disciplines. This meta-narrative review was undertaken by a multi-disciplinary team of researchers to summarise ways in which the BE is measured, and how this links to children’s health. A structured search of four databases across the relevant disciplines retrieved 108 relevant references. The most commonly addressed health-related outcomes were active travel, physical activity and play, and obesity. Many studies used objective (GIS and street audits) or standardised subjective (perceived) measurements of the BE. However, there was a wide variety, and sometimes inconsistency, in their definition and use. There were clear associations between the BE and children’s health. Objective physical activity and self-reported active travel, or obesity, were positively associated with higher street connectivity or walkability measures, while self-reported physical activity and play had the strongest association with reduced street connectivity, indicated by quieter, one-way streets. Despite the high heterogeneity found in BE measures and health outcomes, the meta-narrative approach enabled us to identify ten BE categories that are likely to support children’s health and be protective against some non-communicable disease risk factors. Future research should implement consistent BE measures to ensure key features are explored. A systems approach will be particularly relevant for addressing place-based health inequalities, given potential unintended health consequences of making changes to the BE.

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.

International evaluation of the Microscale Audit of Pedestrian Streetscapes (MAPS) Global instrument: comparative assessment between local and remote online observers

OBJECTIVES

The use of online imagery by non-local observers to conduct remote, centralized collection of streetscape audit data in international studies has the potential to enhance efficiency of collection and comparability of such data for research on built environments and health. The objectives of the study were to measure (1) the consistency in responses between local in-field observers and non-local remote online observers and (2) the reliability between in-country online observers and non-local remote online observers using the Microscale Audit of Pedestrian Streetscapes Global tool to characterize pedestrian-related features along streets in five countries.

METHODS

Consistency and inter-rater reliability were analyzed between local and non-local observers on a pooled database of 200 routes in five study regions (Melbourne, Australia; Ghent, Belgium; Curitiba, Brazil; Hong Kong, China; and Valencia, Spain) for microscale environmental feature subscales and item-level variables using the intraclass correlation coefficient (ICC).

RESULTS

A local in-field versus remote online comparison had an ICC of 0.75 (95 % CI: 0.68-0.80) for the grand total score. An ICC of 0.91 (95 % CI: 0.88-0.93) was found for the local online versus remote online comparison. Positive subscales yielded stronger results in comparison to negative subscales, except for the similarly poor-performing positive aesthetics/social characteristics.

CONCLUSIONS

This study demonstrated remote audits of microscale built environments using online imagery had good reliability with local in-field audits and excellent reliability with local online audits. Results generally supported remote online environmental audits as comparable to local online audits. This identification of low-cost and efficient data acquisition methods is important for expanding research on microscale built environments and physical activity globally.

Optimization of Walk Score Based on Street Greening-A Case Study of Zhongshan Road in Qingdao

Enhancing the walkability of urban streets is an effective means to improve public health, alleviate traffic congestion, and enhance the living environment. In China, the government has actively encouraged green travel and promoted improvements in the walk system. The walkability of the built environment is affected by many factors. In addition to the configuration of daily life facilities, street greening can have significant effects on walkability. To explore the rationality of street life facilities and understand the impact of the natural attributes of the block space (street-level greening) on the quality of the walking environment, we evaluated the walkability of Zhongshan Road in Qingdao, China and optimized the algorithm of the walk score. In this study, we selected residential areas as the starting point and modified the weight coefficients for facilities to evaluate the walkability of streets. Traditional research methods were combined with street view image capture, and the rate of the attenuation factor was used for the new optimization algorithm. We discussed the rationality of street life facilities and increased the green vision rate using a correction index. By comparing changes in walkability before and after joining, we analyzed the necessity of including new indicators. The results show that the average walking index of Zhongshan Road is 79.74, and the overall performance is good, showing a high trend in the west and a low trend in the east, and a high trend in the south and a low trend in the north. According to the general walking index, western stations and southern coastal areas have higher scores, and living facilities are well equipped; old northern and eastern residential areas have lower scores. Among them, the average weight of bookstores is 0.74, and the average weight of parks is 0.69. To meet residents’ needs for daily leisure activities, adding bookstores or similar facilities in community parks would be necessary to improve daily facilities and services. The average green viewing rate of Zhongshan Road is 20.48%, which is lower than the best visual perception value of 25.00%. Comparing the walking index changes before and after adding the green viewing rate, the high-scoring area shifted from the west to the south, and the west walking index has the most significant decline. Street greening has a certain impact on the quality of the walking environment. The results and conclusions of this study can be used as a reference in developing street walkability indicators and further improving the evaluation system.

Adapting the SPOTLIGHT Virtual Audit Tool to assess food and activity environments relevant for adolescents: a validity and reliability study

Background

Physical inactivity and unhealthy diet are key behavioral determinants underlying obesity. The neighborhood environment represents an important arena for modifying these behaviors, and hence reliable and valid tools to measure it are needed. Most existing virtual audit tools have been designed to assess either food or activity environments deemed relevant for adults. Thus, there is a need for a tool that combines the assessment of food and activity environments, and which focuses on aspects of the environment relevant for youth.

Objective

The aims of the present study were: (a) to adapt the SPOTLIGHT Virtual Audit Tool (S-VAT) developed to assess characteristics of the built environment deemed relevant for adults for use in an adolescent population, (b) to assess the tool’s inter- and intra-rater reliability, and (c) to assess its criterion validity by comparing the virtual audit to a field audit.

Methods

The tool adaptation was based on literature review and on results of a qualitative survey investigating how adolescents perceived the influence of the environment on dietary and physical activity behaviors. Sixty streets (148 street segments) in six neighborhoods were randomly selected as the study sample. Two raters assessed the inter- and intra-rater reliability and criterion validity, comparing the virtual audit tool to a field audit. The results were presented as percentage agreement and Cohen’s kappa (κ).

Results

Intra-rater agreement was found to be moderate to almost perfect (κ = 0.44–0.96) in all categories, except in the category aesthetics (κ = 0.40). Inter-rater agreement between auditors ranged from fair to substantial for all categories (κ = 0.24–0.80). Criterion validity was found to be moderate to almost perfect (κ = 0.56–0.82) for most categories, except aesthetics and grocery stores (κ = 0.26–0.35).

Conclusion

The adapted version of the S-VAT can be used to provide reliable and valid data on built environment characteristics deemed relevant for physical activity and dietary behavior among adolescents.

Objective scoring of streetscape walkability related to leisure walking: Statistical modeling approach with semantic segmentation of Google Street View images

Although the pedestrian-friendly qualities of streetscapes promote walking, quantitative understanding of streetscape functionality remains insufficient. This study proposed a novel automated method to assess streetscape walkability (SW) using semantic segmentation and statistical modeling on Google Street View images. Using compositions of segmented streetscape elements, such as buildings and street trees, a regression-style model was built to predict SW, scored using a human-based auditing method. Older female active leisure walkers living in Bunkyo Ward, Tokyo, are associated with SW scores estimated by the model (OR = 3.783; 95% CI = 1.459 to 10.409), but male walkers are not.

Assessing Google Street View Image Availability in Latin American Cities

Virtual audits using Google Street View are an increasingly popular method of assessing neighborhood environments for health and urban planning research. However, the validity of these studies may be threatened by issues of image availability, image age, and variance of image age, particularly in the Global South. This study identifies patterns of Street View image availability, image age, and image age variance across cities in Latin America and assesses relationships between these measures and measures of resident socioeconomic conditions. Image availability was assessed at 530,308 near-road points within the boundaries of 371 Latin American cities described by the SALURBAL (Salud Urbana en America Latina) project. At the subcity level, mixed-effect linear and logistic models were used to assess relationships between measures of socioeconomic conditions and image availability, average image age, and the standard deviation of image age. Street View imagery was available at 239,394 points (45.1%) of the total sampled, and rates of image availability varied widely between cities and countries. Subcity units with higher scores on measures of socioeconomic conditions had higher rates of image availability (OR = 1.11 per point increase of combined index, p < 0.001) and the imagery was newer on average (- 1.15 months per point increase of combined index, p < 0.001), but image capture date within these areas varied more (0.59-month increase in standard deviation of image age per point increase of combined index, p < 0.001). All three assessed threats to the validity of Street View virtual audit studies spatially covary with measures of socioeconomic conditions in Latin American cities. Researchers should be attentive to these issues when using Street View imagery.

Google-truthing to assess hot spots of food retail change: A repeat cross-sectional Street View of food environments in the Bronx, New York

Google Street View (GSV) images can be used to "ground-truth" current and historical food retail data from approximately 2007 - when GSV was launched in a few US cities - to the present, facilitating analyses of food environments over time. A review of GSV images of all food retailers listed in a government database of licensed establishments in the Bronx, New York enabled records to be verified, businesses classified, and retail change quantified. The data revealed several trends likely to affect food access and health: increasing overall numbers of food retailers; the growth of dollar stores; and numerous openings, closings, and ownership changes across all food retail segments. Hot spot analysis identified statistically significant clusters of new dollar stores and bodegas, purveyors of less healthy processed foods, in lower-income neighborhoods in the South Bronx that face elevated rates of diet-related diseases. This article demonstrates the benefits and limitations of using GSV to conduct "virtual" food environment research.

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.

Bus Stops Near Schools Advertising Junk Food and Sugary Drinks

Children rarely understand the full extent of the persuasive purpose of advertising on their eating behaviours. Addressing the obesogenic environments in which children live, through a quantification of outdoor advertising, is essential in informing policy changes and enforcing stricter regulations. This research explores the proportion of bus stop advertisements promoting non-core food and beverages within walking distance (500 m) from schools in Auckland, New Zealand while using Google Street View. Information was collected on: school type, decile, address, Walk Score^®, and Transit Score for all 573 schools in the Auckland region. Ground-truthing was conducted on 10% of schools and showed an alignment of 87.8%. The majority of advertisements on bus shelters were for non-food items or services (n = 541, 64.3%). Of the advertisements that were for food and/or beverages, the majority were for non-core foods (n = 108, 50.2%). There was no statistically significant difference between the variables core and non-core food and beverages and School decile (tertiles), Walk Score (quintiles), and Transit Score (quintiles). 12.8% of all bus stop advertisements in this study promoted non-core dietary options; highlighting an opportunity for implementing stricter regulations and policies preventing advertising unhealthy food and drink to children in New Zealand.

The Impact of Street Space Perception Factors on Elderly Health in High-Density Cities in Macau—Analysis Based on Street View Images and Deep Learning Technology

The urban space environment has been proven to be related to the health of the elderly. However, as a high-density city, Macau’s limited urban space must cope with the growing population and the arrival of an aging society. In the existing studies, less attention has been paid to Macau, especially the relationship between Macanese elderly and urban space. This study uses Baidu Street View (BSV) on the Macau Peninsula and conducts field surveys to obtain street view data to evaluate the openness, greenness, interface coverage, and road area ratio of street space and its association with the physical and mental health of the elderly and social health. The results show that the data truly reflect the overall street space conditions on the Macau Peninsula. The street openness, greenery rate, and interface enclosure are all related to the elderly in various evaluations in areas with a higher population dependency index and aging index. Human space perception is related to health gain, and road area ratio is weaker than other indicators. The research results have certain policy implications and have practical significance for city managers and designers.

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

INTRODUCTION

Various built environment factors might influence certain health behaviors and outcomes. Reliable, resource-efficient methods that are feasible for assessing built environment characteristics across large geographies are needed for larger, more robust studies. This paper reports the item response prevalence, reliability, and rating time of a new virtual neighborhood audit protocol, drop-and-spin auditing, developed for assessment of walkability and physical disorder characteristics across large geographic areas.

METHODS

Drop-and-spin auditing, a method where a Google Street View scene was rated by spinning 360° around a point location, was developed using a modified version of the virtual audit tool Computer Assisted Neighborhood Visual Assessment System. Approximately 8,000 locations within Essex County, New Jersey were assessed by 11 trained auditors. Using a standardized protocol, 32 built environment items per a location within Google Street View were audited. Test-retest and inter-rater κ statistics were from a 5% subsample of locations. Data were collected in 2017-2018 and analyzed in 2018.

RESULTS

Roughly 70% of Google Street View scenes had sidewalks. Among those, two thirds were in good condition. At least 5 obvious items of garbage or litter were present in 41% of Google Street View scenes. Maximum test-retest reliability indicated substantial agreement (κ ≥0.61) for all items. Inter-rater reliability of each item, generally, was lower than test-retest reliability. The median time to rate each item was 7.3 seconds.

CONCLUSIONS

Compared with segment-based protocols, drop-and-spin virtual neighborhood auditing is quicker and similarly reliable for assessing built environment characteristics. Assessment of large geographies may be more feasible using drop-and-spin virtual auditing.

Characterizing the Rural Opioid Use Environment in Kentucky Using Google Earth: Virtual Audit

Background

The opioid epidemic has ravaged rural communities in the United States. Despite extensive literature relating the physical environment to substance use in urban areas, little is known about the role of physical environment on the opioid epidemic in rural areas.

Objective

This study aimed to examine the reliability of Google Earth to collect data on the physical environment related to substance use in rural areas.

Methods

Systematic virtual audits were performed in 5 rural Kentucky counties using Google Earth between 2017 and 2018 to capture land use, health care facilities, entertainment venues, and businesses. In-person audits were performed for a subset of the census blocks.

Results

We captured 533 features, most of which were images taken before 2015 (71.8%, 383/533). Reliability between the virtual audits and the gold standard was high for health care facilities (>83%), entertainment venues (>95%), and businesses (>61%) but was poor for land use features (>18%). Reliability between the virtual audit and in-person audit was high for health care facilities (83%) and entertainment venues (62%) but was poor for land use (0%) and businesses (12.5%).

Conclusions

Poor reliability for land use features may reflect difficulty characterizing features that require judgment or natural changes in the environment that are not reflective of the Google Earth imagery because it was captured several years before the audit was performed. Virtual Google Earth audits were an efficient way to collect rich neighborhood data that are generally not available from other sources. However, these audits should use caution when the images in the observation area are dated.

Virtual audits of streetscapes by crowdworkers

Audits have been used to provide objective ratings of neighborhood environments. Physical audits, however, are time- and resource-intensive. This study examines the efficiency and reliability of virtual auditing using Google Street View and crowdsourcing to conduct walkability audits of streets in Japan. Overall, 830 street segments were physically and virtually audited by two trained auditors; 300 untrained crowdworkers also virtually audited 3 street segments. Statistical analysis found good inter-source and inter-rater reliability. This study helps establish crowdsourced virtual auditing as a valuable method of measuring neighborhood walkability, reducing audit costs as well as enabling large-scale auditor recruitment while maintaining reliability.

Nature and mental health: An ecosystem service perspective

A growing body of empirical evidence is revealing the value of nature experience for mental health. With rapid urbanization and declines in human contact with nature globally, crucial decisions must be made about how to preserve and enhance opportunities for nature experience. Here, we first provide points of consensus across the natural, social, and health sciences on the impacts of nature experience on cognitive functioning, emotional well-being, and other dimensions of mental health. We then show how ecosystem service assessments can be expanded to include mental health, and provide a heuristic, conceptual model for doing so.

Nature and mental health: An ecosystem service perspective

A growing body of empirical evidence is revealing the value of nature experience for mental health. With rapid urbanization and declines in human contact with nature globally, crucial decisions must be made about how to preserve and enhance opportunities for nature experience. Here, we first provide points of consensus across the natural, social, and health sciences on the impacts of nature experience on cognitive functioning, emotional well-being, and other dimensions of mental health. We then show how ecosystem service assessments can be expanded to include mental health, and provide a heuristic, conceptual model for doing so.

Examining the Relationship between Urban Design Qualities and Walking Behavior: Empirical Evidence from Dallas, TX

This study examines the relationship between street-level urban design perceptual qualities and walking behavior in the City of Dallas. While the city has the potential to experience growth in pedestrian activities, it exhibits a very low level of walking activity, placing it as one of the least walkable cities in the nation. To assess the impact of urban design qualities on walkability, we collected data on 23 features related to urban design, 11 built environment variables characterized as D variables comprising diversity, density, design, distance to transit, and destination accessibility. The sample included 402 street block faces in Dallas Downtown Improvement District. Accounting for spatial autocorrelation, we found that two urban design qualities, among five, including image-ability—such as a memorable quality of a place, and transparency—as to what degree people can see beyond the street’s edge—significantly influence pedestrian volume in downtown streets. These findings are in agreement with the two previous studies that used the same methodology in different cities (New York City, NYC and Salt Lake City, UT). According to the findings of these three studies, the other urban design qualities including human scale, complexity, as well as enclosure, are not playing a significant role in walkability, despite the theoretical justification and the extensive operationalization efforts. The findings of this study draw policy makers’ attention to creating more appealing and walkable places through the implementation of these urban design qualities.

Examining the relationships between walkability and physical activity among older persons: what about stairs?

BACKGROUND

Walkability is considered an important dimension of healthy communities. However, variable associations between measures of walkability and physical activity have been observed, particularly among older persons. Given the challenges older persons may have navigating stairs on walking routes, the presence of stairs may be an explanatory factor for these mixed associations. The purposes of this scoping review were to determine whether studies examining the relationship between walkability and physical activity included items that assessed stairs and what relationships were found.

METHODS

Systematic reviews were identified by entering search terms into five database search engines. Eligibility criteria were: a) published between 2008 and 2017, b) examined the relationship between walkability and physical activity, c) included a focus on persons aged 65 years and older, and d) written in English. The full articles for all primary studies included in eligible systematic reviews were then retrieved. Duplicates were removed. Information about where the study took place, walkability measures used, types of walkability data obtained (objective and/or subjective) and questions asked about stairs were extracted from the full text articles.

RESULTS

Eleven systematic reviews were identified; seven were eligible. After removing duplicates, 289 primary studies remained for review. Measures of neighborhood walkability were present in 205 studies; a minority (n = 5, 2.4%) included items about stairs. No information was obtained on the structural features of the stairs.

CONCLUSIONS

The presence of stairs may deter older persons (and others) from walking outdoors. Standard measures to document the presence and characteristics of stairs, and sampling approaches to select stairs for assessment are needed. The inclusion of these measures would augment the utility and comparability of studies examining relationships between walkability and physical activity and better inform planning and policy decisions.

Systematic review of the use of Google Street View in health research: Major themes, strengths, weaknesses and possibilities for future research

We systematically reviewed the current use of Google Street View (GSV) in health research and characterized major themes, strengths and weaknesses in order to highlight possibilities for future research. Of 54 qualifying studies, we found that most used GSV to assess the neighborhood built environment, followed by health policy compliance, study site selection, and disaster preparedness. Most studies were conducted in urban areas of North America, Europe, or New Zealand, with few studies from South America or Asia and none from Africa or rural areas. Health behaviors and outcomes of interest in these studies included injury, alcohol and tobacco use, physical activity and mental health. Major strengths of using GSV imagery included low cost, ease of use, and time saved. Identified weaknesses were image resolution and spatial and temporal availability, largely in developing regions of the world. Despite important limitations, GSV is a promising tool for automated environmental assessment for health research. Currently untapped areas of health research using GSV include identification of sources of air, soil or water pollution, park design and usage, amenity design and longitudinal research on neighborhood conditions.

Nature as a facilitator for physical activity: Defining relationships between the objective and perceived environment and physical activity among community-dwelling older people

The aim was to study the correspondence between the objective and perceived environment and to assess their associations with physical activity (PA) in older people. 848 community-dwelling older people aged 75-90 were interviewed on their difficulties in walking 500m, perceiving nature as a facilitator for outdoor mobility, and PA. The presence of water and landscape diversity were objectively assessed inside 500m and 1000m circular buffers around participants' homes. Using logistic regression, participant data were analyzed together with the objectively assessed environmental features. Our results indicate that higher habitat diversity within natural areas correlates with higher PA among older people without walking difficulties and the presence of water correlates with higher PA among those with walking difficulties.

Investigating associations between the built environment and physical activity among older people in 20 UK towns

Background

Policy initiatives such as WHO Age Friendly Cities recognise the importance of the urban environment for improving health of older people, who have both low physical activity (PA) levels and greater dependence on local neighbourhoods. Previous research in this age group is limited and rarely uses objective measures of either PA or the environment.

Methods

We investigated the association between objectively measured PA (Actigraph GT3x accelerometers) and multiple dimensions of the built environment, using a cross-sectional multilevel linear regression analysis. Exposures were captured by a novel foot-based audit tool that recorded fine-detail neighbourhood features relevant to PA in older adults, and routine data.

Results

795 men and 638 women aged 69–92 years from two national cohorts, covering 20 British towns, were included in the analysis. Median time in moderate to vigorous PA (MVPA) was 27.9 (lower quartile: 13.8, upper quartile: 50.4) minutes per day. There was little evidence of associations between any of the physical environmental domains (eg, road and path quality defined by latent class analysis; number of bus stops; area aesthetics; density of shops and services; amount of green space) and MVPA. However, analysis of area-level income deprivation suggests that the social environment may be associated with PA in this age group.

Conclusions

Although small effect sizes cannot be discounted, this study suggests that older individuals are less affected by their local physical environment and more by social environmental factors, reflecting both the functional heterogeneity of this age group and the varying nature of their activity spaces.

Investigating the importance of the local food environment for fruit and vegetable intake in older men and women in 20 UK towns: a cross-sectional analysis of two national cohorts using novel methods

BACKGROUND

Local neighbourhood environments can influence dietary behavior. There is limited evidence focused on older people who are likely to have greater dependence on local areas and may suffer functional limitations that amplify any neighbourhood impact.

METHODS

Using multi-level ordinal regression analysis we investigated the association between multiple dimensions of neighbourhood food environments (captured by fine-detail, foot-based environmental audits and secondary data) and self-reported frequency of fruit and vegetable intake. The study was a cross-sectional analysis nested within two nationally representative cohorts in the UK: the British Regional Heart Study and the British Women's Heart and Health Study. Main exposures of interest were density of food retail outlets selling fruits and vegetables, the density of fast food outlets and a novel measure of diversity of the food retail environment.

RESULTS

A total of 1124 men and 883 women, aged 69 - 92 years, living in 20 British towns were included in the analysis. There was strong evidence of an association between area income deprivation and fruit and vegetable consumption, with study members in the most deprived areas estimated to have 27% (95% CI: 7, 42) lower odds of being in a higher fruit and vegetable consumption category relative to those in the least deprived areas. We found no consistent evidence for an association between fruit and vegetable consumption and a range of other food environment domains, including density of shops selling fruits and vegetables, density of premises selling fast food, the area food retail diversity, area walkability, transport accessibility, or the local food marketing environment. For example, individuals living in areas with greatest fruit and vegetable outlet density had 2% (95% CI: -22, 21) lower odds of being in a higher fruit and vegetable consumption category relative to those in areas with no shops.

CONCLUSIONS

Although small effect sizes in environment-diet relationships cannot be discounted, this study suggests that older people are less influenced by physical characteristics of neighbourhood food environments than is suggested in the literature. The association between area income deprivation and diet may be capturing an important social aspect of neighbourhoods that influence food intake in older adults and warrants further research.

Nature Contact and Human Health: A Research Agenda

BACKGROUND

At a time of increasing disconnectedness from nature, scientific interest in the potential health benefits of nature contact has grown. Research in recent decades has yielded substantial evidence, but large gaps remain in our understanding.

OBJECTIVES

We propose a research agenda on nature contact and health, identifying principal domains of research and key questions that, if answered, would provide the basis for evidence-based public health interventions.

DISCUSSION

We identify research questions in seven domains: a) mechanistic biomedical studies; b) exposure science; c) epidemiology of health benefits; d) diversity and equity considerations; e) technological nature; f) economic and policy studies; and g) implementation science.

CONCLUSIONS

Nature contact may offer a range of human health benefits. Although much evidence is already available, much remains unknown. A robust research effort, guided by a focus on key unanswered questions, has the potential to yield high-impact, consequential public health insights. https://doi.org/10.1289/EHP1663.