Neighborhood walkability: field validation of geographic information system measures

Impacts of commute mode on body mass index: A longitudinal analysis before and during the COVID-19 pandemic

Introduction

COVID-19 has impacted millions of commuters by decreasing their mobility and transport patterns. While these changes in travel have been studied, less is known about how commute changes may have impacted individuals' body mass index (BMI). The present longitudinal study explores the relationship between commute mode and BMI of employed individuals in Montréal, Canada.

Methods

This study uses panel data drawn from two waves of the Montréal Mobility Survey (MMS) conducted before and during the COVID-19 pandemic (n = 458). BMI was modeled separately for women and men as a function of commuting mode, WalkScore©, sociodemographic, and behavioral covariates using a multilevel regression modeling approach.

Results

For women, BMI significantly increased during the COVID-19 pandemic, but telecommuting frequency, and more specifically telecommuting as a replacement of driving, led to a statistically significant decrease in BMI. For men, higher levels of residential local accessibility decreased BMI, while telecommuting did not have a statistically significant effect on BMI.

Conclusions

This study's findings confirm previously observed gendered differences in the relations between the built environment, transport behaviors, and BMI, while offering new insights regarding the impacts of the changes in commute patterns linked to the COVID-19 pandemic. Since some of the COVID-19 impacts on commute are expected to be lasting, findings from this research can be of use by health and transport practitioners as they work towards generating policies that improve population health.

Spatial Pattern of the Walkability Index, Walk Score and Walk Score Modification for Elderly

Contemporary cities require excellent walking conditions to support human physical activity, increase humans’ well-being, reduce traffic, and create a healthy urban environment. Various indicators and metrics exist to evaluate walking conditions. To evaluate the spatial pattern of objective-based indicators, two popular indices were selected—the Walkability Index (WAI), representing environmental-based indicators, and Walk Score (WS), which applies an accessibility-based approach. Both indicators were evaluated using adequate spatial units (circle buffers with radii from 400 m to 2414 m) in two Czech cities. A new software tool was developed for the calculation of WS using OSM data and freely available network services. The new variant of WS was specifically designed for the elderly. Differing gait speeds, and variable settings of targets and their weights enabled the adaptation of WS to local conditions and personal needs. WAI and WS demonstrated different spatial pattern where WAI is better used for smaller radii (up to approx. 800 m) and WS for larger radii (starting from 800 m). The assessment of WS for both cities indicates that approx. 40% of inhabitants live in unsatisfactory walking conditions. A sensitivity analysis discovered the major influences of gait speed and the β coefficient on the walkability assessment.

Chronic disease and where you live: Built and natural environment relationships with physical activity, obesity, and diabetes

BACKGROUND

Diabetes is among the most prevalent non-communicable diseases causing significant morbidity and mortality globally. The aetiology and disease development of diabetes are influenced by genetic, lifestyle, and environmental factors. Due to an increasing number of cases each year, it is imperative to improve the understanding of modifiable environmental risk and protective factors. In this study we aimed to analyse associations between built and natural environment features and diabetes prevalence; and two major risk factors: physical activity and obesity and their mediation effects.

METHODS

We analysed relationships between walkability and park availability with physical activity, obesity, and diabetes, using self-reported data from a large cross-sectional survey in British Columbia, Canada (n = 22,418). We validated results with an independent cohort (n = 11,972) in a subset of the analyses. The outcome measures included walking, moderate to vigorous physical activity (MVPA), body mass index (BMI), and diabetes. Built and natural environment features within a 1 km road network buffer around residential postal code centroids were assessed using validated indicators of walkability and park availability. We used general linear multivariable models (GLM) to examine the direct relationship between environmental features, physical activity, obesity, and diabetes respectively. Path models were developed to analyse mediation effects of physical activity and obesity on the association between environmental indicators and diabetes. The relative contribution of direct versus indirect effects was assessed. All models were adjusted for age, gender, income. ethnicity, years lived in neighbourhood and regional accessibility.

RESULTS

Walkable neighbourhoods and areas with greater park availability were associated with lower rates of diabetes. There was a direct association of walkability and park availability on physical activity (highest vs. lowest quintile OR = 1.15; 95% CI: 1.00, 1.33 and OR = 1.28, 95% CI: 1.13, 1.45 respectively), obesity (highest vs. lowest quintile OR = 0.58, 95% CI: 0.49, 0.70 and OR = 0.57, 95% CI: 0.48, 0.68 respectively) and diabetes (highest vs. lowest quintile OR = 0.62, 95% CI: 0.45, 0.85, and OR = 0.63, 95% CI: 0.47, 0.84 respectively). Results were similar in the independent cohort. The associations between diabetes and walkability and park availability respectively were partly mediated by obesity (41% of total association for walkability and 53% of total association for park availability). The mediating effect of physical activity was negligible.

CONCLUSION

Results support investments in walkability through active transportation and transit infrastructure. Changes in zoning and subdivision regulations governing land use actions are required to enable compact mixed-use environments with access to parks and high quality transit service. Future studies including cost-benefit analyses of health-related economic impacts of such investments can contribute to evidence-based decisions for healthier cities.

Walkability measures to predict the likelihood of walking in a place: A classification and regression tree analysis

Walkability is a popular and ubiquitous term at the intersection of urban planning and public health. As the number of potential walkability measures grows in the literature, there is a need to compare their relative importance for specific research objectives. This study demonstrates a classification and regression tree (CART) model to compare five familiar measures of walkability from the literature for their relative ability to predict whether or not walking occurs in a dataset of objectively measured locations. When analyzed together, the measures had moderate-to-high accuracy (87.8% agreement: 65.6% of true walking GPS-measured points classified as walking and 93.4% of non-walking points as non-walking). On its own, the most well-known composite measure, Walk Score, performed only slightly better than measures of the built environment composed of a single variable (transit ridership, employment density, and residential density).Thus there may be contexts where transparent and longitudinally available measures of urban form are worth a marginal tradeoff in prediction accuracy. This comparison of walkability measures using CART highlights the importance for public health and urban design researchers to think carefully about how and why particular walkability measures are used.

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.

School Walkability Index: Application of Environmental Audit Tool and GIS

INTRODUCTION

Active school travel is an important way to promote children's physical activity, but it requires supportive environments that can safely and comfortably accommodate children's walking and biking. Few existing indices explicitly consider school neighborhood environmental factors related to children's walking to school. In this study, we used a street audit tool and Geographic Information System (GIS) to evaluate walkability near low-income elementary schools in Seattle, WA.

METHODS

The audit-based school walkability index was developed based on all street segments (n=841) within a 0.4km network buffer from each study school (n=18). The GIS-based school walkability, a combination of road connectivity, vehicular traffic exposure, and residential density, was also measured in a 2km network buffer around each school. The participants were individuals aged 8-11 years (n=315) who participated in the Walking School Bus randomized controlled trial project. Mixed-effects logistic and linear models were used to examine the association of the index's representations of the built environment with children's school travel mode (walking or biking to school 1+ times per week) and with objectively measured moderate-to-vigorous physical activity (MVPA, average weekday minutes during the 90-min before-school period). These associations were tested with the total sample as well as the subsample of children living within 1.5km from their schools.

RESULTS

The audit-based school walkability index (WI) was positively associated with both active commuting to school among the subsample living within 1.5km from their schools and with children's before-school MVPA among the subsample and the total sample. The GIS-based school WI showed significant associations with children's before-school MVPA but no relationships with active school travel among the subsample and the total sample.

CONCLUSION

The audit-based school walkability index can be used as a complementary tool for measuring walkability near low-income elementary schools along with existing GIS-based school walkability index.

Associations between body mass index, physical activity and the built environment in disadvantaged, minority neighborhoods: Predictive validity of GigaPan® imagery

BACKGROUND

The built environment has been shown to influence health in studies of disadvantaged populations using different measurement methods. This study determined whether environmental exposures derived from GigaPan® images could serve as valid predictors of body mass index (BMI), walking and moderate to vigorous physical activity (MVPA) in a longitudinal study of low-income adults living in two primarily African American neighborhoods in Pittsburgh, Pennsylvania, USA. GigaPan® is a robotic system used to obtain high-resolution, panoramic images of environments.

METHODS

Microscale environmental features along 481 streets were audited in 2015-2016 using an audit form. Environmental exposures were estimated for 731 adult participants, using a sample of street segments within a 0.4 km (0.25 mile) network distance from each participant's residential address. Summary environmental exposures were constructed using factor analysis. We tested associations between participant-level environmental exposures and objectively measured BMI, self-reported walking and objectively measured MVPA in regression models controlling for baseline health and demographic variables.

RESULTS

Three factors representing participants' environmental exposures were constructed: pedestrian bicycle-amenities; hilly-vacant-boarded; physical activity-recreation/low housing density. Environments with infrastructure and amenities supportive of walking and bicycling were associated with lower BMI (Coef. = ‒0.47, p = 0.02). Frequent walking was less likely in environments with more physical activity and recreation venues/low housing density (OR = 0.81, 95% CI [0.67, 0.96]). MVPA was not associated with any of the environmental measures and the hilly-vacant-boarded factor was not associated with any of the outcomes.

CONCLUSIONS

Predictive validity was demonstrated for an environmental exposure factor that captured features supportive of walking and cycling in a model predicting BMI, using built environment audit data from GigaPan® imagery. A complementary analysis found lower odds of frequent walking in the neighborhood among participants with exposure to more physical activity and recreational features, but fewer types and lower density of housing.

Planning and Design Support Tools for Walkability: A Guide for Urban Analysts

We present a survey of operational methods for walkability analysis and evaluation, which we hold show promise as decision-support tools for sustainability-oriented planning and urban design. An initial overview of the literature revealed a subdivision of walkability studies into three main lines of research: transport and land use, urban health, and livable cities. A further selection of articles from the Scopus and Web of Science databases focused on scientific papers that deal with walkability evaluation methods and their suitability as planning and decision-support tools. This led to the definition of a taxonomy to systematize and compare the methods with regard to factors of walkability, scale of analysis, attention on profiling, aggregation methods, spatialization and sources of data used for calibration and validation. The proposed systematization aspires to offer to non-specialist but competent urban analysts a guide and an orienteering, to help them integrate walkability analysis and evaluation into their research and practice.

How Does Walkability Change Behavior? A Comparison between Different Age Groups in the Netherlands

Empirical research provides evidence that, in neighborhoods with higher walkability, individuals make more walking trips. However, it is not clear what the exact nature is of the relationships between neighborhood walkability and walking trips, since a higher walking frequency can be explained in different ways. This study examined whether the extra walking trips in better walkable neighborhoods are related primarily to trip generation, destination choice, or transport mode choice and whether this is the same for different age groups. A neighborhood fixed effects regression analysis was conducted in a first step to obtain a walkability measure for each neighborhood in the Netherlands including systematic as well as unobserved effects. Subsequently, the estimated fixed effects were used as walkability data for a path analysis based on a causal model to test the hypotheses stated. The results of the path analysis show direct relationships of neighborhood walkability with trip generation, destination choice, and transport mode choice, after controlling for the mutual relationships between the activity and trip variables. Comparing different age groups (i.e., children, adults, and elderly), the differences found mostly concerned the relationship between neighborhood walkability and trip generation. We concluded therefore that conditions for walkability are not the same for all age groups.

Does Residents' Satisfaction with the Neighbourhood Environment Relate to Residents' Self-Rated Health? Evidence from Beijing

Objective: The aim of this study is to examine the association between satisfaction with two types of green space and residents’ self-rated health by comparing neighbourhood green space (NGS) and community green space (CGS) across spatial dimensions. Method: This study was based on 4291 workers from a large-scale individual survey of inhabitants of Beijing city in 2013. Multilevel ordered logistic regression analysis was used to examine the associations between residents’ satisfaction with the two types of green spaces and residents’ self-rated health. Results: Residents who are more satisfied with NGS and CGS have higher odds of reporting good self-rated health outcomes. Such effects are more pronounced for residents living close to NGS and tend to decline non-linearly over space. Conclusion: Additional results quantify the differentiated effects on self-rated health between urban and suburban residents. The findings of this study suggest that the effects of residents’ satisfaction with different types of green space on health benefits should be taken into account in the land-use design of green space preservation and development policies.

Perception of parks and trails as mobility facilitators and transportation walking in older adults: a study using digital geographical maps

BACKGROUND

Transportation walking represents a promising target for physical activity promotion in older adults. Perceived characteristics of the neighbourhood physical environment may affect older adults' choice of transportation mode for a routine activity such as walking to the grocery store.

AIMS

To (1) evaluate associations between older adults' perception of parks and trails as outdoor mobility facilitators and transportation walking, specifically to the grocery store; and (2) explore whether the spatial relationship between people's home, perceived facilitator and store was relevant for their transportation choice.

METHODS

Cross-sectional data were collected in a subsample of the 'Life-space mobility in old age' cohort. Multivariable logistic regression analysis on the binary outcome 'transportation walking' (vs. 'motorized transportation') was used to evaluate the association with perceived mobility facilitators in the neighborhood; in step (1) without and in step (2) with taking spatial relationships into account.

RESULTS

Perceiving a park as facilitator increased the odds of walking (N = 179; Odds Ratio 9.89; 95% Confidence interval 3.11-31.50). Spatial relationships did not affect transportation choice. Reporting a trail as facilitator was not significantly associated with walking.

CONCLUSIONS

Our findings suggest that the perception of environmental characteristics in the neighbourhood has an influence on older people's transportation choices. Taking environmental measures or informing older adults on their options in the neighbourhood might be possible ways to increase older adults' transportation walking on a population level.

Sampling Methodology and Reliability of a Representative Walkability Audit

Background

Physical inactivity is a public health concern in the US Virgin Islands (USVI). A contributing factor may be a lack of pedestrian infrastructure and other environmental supports for walking. In this manuscript, we describe the methods used to conduct a walkability audit of environmental features related to physical activity in the USVI.

Methods

In 2016, volunteer auditors conducted the audit using a modified version of the Microscale Audit of Pedestrian Streetscapes tool. A two-stage sampling method was developed using publicly available census data to select a sample of estates (n=46) and street segments (n=1,550; 99.2 km) across the USVI. A subset of segments was audited by two independent auditors, and inter-rater reliability was assessed using Cohen's kappa and percent agreement.

Results

Audits were completed on 1,114 segments (94.6 km), and estimates were weighted to represent accessible public street length in the study area (1,155.9 km). Most items on the audit tool (62.7%) demonstrated good to excellent reliability. We found that it was feasible to conduct a reliable audit of environmental features related to physical activity across a large sample of streets in the USVI.

Conclusions

These methods can be replicated in other settings to collect comprehensive data that can be used to guide strategies to improve the walkability of communities.

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.

Validity of environmental audits using GigaPan® and Google Earth Technology

Background

Health behaviors are shaped by the context in which people live. However, documenting environmental context has remained a challenge. More specifically, direct observation techniques require large investments in time and resources and auditing the environment through web-based platforms has limited stability in spatio-temporal imagery. This study examined the validity of a new methodology, using GigaPan^® imagery, where we took photos locally and, stitched them together using GigaPan^® technology, and quantified environmental attributes from the resulting panoramic photo. For comparison, we examined validity using Google Earth imagery.

Methods

A total of 464 street segments were assessed using three methods: GigaPan^® audits, Google Earth audits, and direct observation audits. Thirty-seven different attributes were captured representing three broad constructs: land use, traffic and safety, and amenities. Sensitivity (i.e. the proportion of true positives) and specificity (i.e. the proportion of true negatives) were used to estimate the validity of GigaPan^® and Google Earth audits using direct observation audits as the gold standard.

Results

Using GigaPan^®, sensitivity was 80% or higher for 6 of 37 items and specificity was 80% or higher for 31 of 37 items. Using Google Earth, sensitivity was 80% or higher for 8 of 37 items and specificity was 80% or higher for 30 of 37 items. The validity of GigaPan^® and Google Earth was similar, with significant differences in sensitivity and specificity for 7 items and 2 items, respectively.

Conclusion

GigaPan^® performed well, especially when identifying features absent from the environment. A major strength of the GigaPan^® technology is its ability to be implemented quickly in the field relative to direct observation. GigaPan^® is a method to consider as an alternative to direct observation when temporality is prioritized or Google Earth imagery is unavailable.

Physical Limitations, Walkability, Perceived Environmental Facilitators and Physical Activity of Older Adults in Finland

The aim was to study objectively assessed walkability of the environment and participant perceived environmental facilitators for outdoor mobility as predictors of physical activity in older adults with and without physical limitations. 75–90-year-old adults living independently in Central Finland were interviewed (n = 839) and reassessed for self-reported physical activity one or two years later (n = 787). Lower-extremity physical limitations were defined as Short Physical Performance Battery score ≤9. Number of perceived environmental facilitators was calculated from a 16-item checklist. Walkability index (land use mix, street connectivity, population density) of the home environment was calculated from geographic information and categorized into tertiles. Accelerometer-based step counts were registered for one week (n = 174). Better walkability was associated with higher numbers of perceived environmental facilitators (p < 0.001) and higher physical activity (self-reported p = 0.021, step count p = 0.010). Especially among those with physical limitations, reporting more environmental facilitators was associated with higher odds for reporting at least moderate physical activity (p < 0.001), but not step counts. Perceived environmental facilitators only predicted self-reported physical activity at follow-up. To conclude, high walkability of the living environment provides opportunities for physical activity in old age, but among those with physical limitations especially, awareness of environmental facilitators may be needed to promote physical activity.

Neighbourhood Walkability and Daily Steps in Adults with Type 2 Diabetes

Introduction

There is evidence that greater neighbourhood walkability (i.e., neighbourhoods with more amenities and well-connected streets) is associated with higher levels of total walking in Europe and in Asia, but it remains unclear if this association holds in the Canadian context and in chronic disease populations. We examined the relationships of different walkability measures to biosensor-assessed total walking (i.e., steps/day) in adults with type 2 diabetes living in Montreal (QC, Canada).

Materials and Methods

Participants (60.5±10.4 years; 48.1% women) were recruited through McGill University-affiliated clinics (June 2006 to May 2008). Steps/day were assessed once per season for one year with pedometers. Neighbourhood walkability was evaluated through participant reports, in-field audits, Geographic Information Systems (GIS)-derived measures, and the Walk Score^®. Relationships between walkability and daily steps were estimated using Bayesian longitudinal hierarchical linear regression models (n = 131).

Results

Participants who reported living in the most compared to the least walkable neighbourhoods completed 1345 more steps/day (95% Credible Interval: 718, 1976; Quartiles 4 versus 1). Those living in the most compared to the least walkable neighbourhoods (based on GIS-derived walkability) completed 606 more steps per day (95% CrI: 8, 1203). No statistically significant associations with steps were observed for audit-assessed walkability or the Walk Score^®.

Conclusions

Adults with type 2 diabetes who perceived their neighbourhoods as more walkable accumulated more daily steps. This suggests that knowledge of local neighborhood features that enhance walking is a meaningful predictor of higher levels of walking and an important component of neighbourhood walkability.

Neighbourhood walkability, daily steps and utilitarian walking in Canadian adults

OBJECTIVES

To estimate the associations of neighbourhood walkability (based on Geographic Information System (GIS)-derived measures of street connectivity, land use mix, and population density and the Walk Score) with self-reported utilitarian walking and accelerometer-assessed daily steps in Canadian adults.

DESIGN

A cross-sectional analysis of data collected as part of the Canadian Health Measures Survey (2007-2009).

SETTING

Home neighbourhoods (500 m polygonal street network buffers around the centroid of the participant's postal code) located in Atlantic Canada, Québec, Ontario, the Prairies and British Columbia.

PARTICIPANTS

5605 individuals participated in the survey. 3727 adults (≥18 years) completed a computer-assisted interview and attended a mobile clinic assessment. Analyses were based on those who had complete exposure, outcome and covariate data (n=2949).

MAIN EXPOSURE MEASURES

GIS-derived walkability (based on land use mix, street connectivity and population density); Walk Score.

MAIN OUTCOME MEASURES

Self-reported utilitarian walking; accelerometer-assessed daily steps.

RESULTS

No important relationship was observed between neighbourhood walkability and daily steps. Participants who reported more utilitarian walking, however, accumulated more steps (<1 h/week: 6613 steps/day, 95% CI 6251 to 6975; 1 to 5 h/week: 6768 steps/day, 95% CI 6420 to 7117; ≥6 h/week: 7391 steps/day, 95% CI 6972 to 7811). There was a positive graded association between walkability and odds of walking ≥1 h/week for utilitarian purposes (eg, Q4 vs Q1 of GIS-derived walkability: OR=1.66, 95% CI 1.31 to 2.11; Q3 vs Q1: OR=1.41, 95% CI 1.14 to 1.76; Q2 vs Q1: OR=1.13, 95% CI 0.91 to 1.39) independent of age, sex, body mass index, married/common law status, annual household income, having children in the household, immigrant status, mood disorder, perceived health, ever smoker and season.

CONCLUSIONS

Contrary to expectations, living in more walkable Canadian neighbourhoods was not associated with more total walking. Utilitarian walking and daily steps were, however, correlated and walkability demonstrated a positive graded relationship with utilitarian walking.

A call for caution and transparency in the calculation of land use mix: measurement bias in the estimation of associations between land use mix and physical activity

There is evidence that land use mix based on the Shannon (1948) entropy formula may be misspecified in some studies. The aim of this study was to quantify the bias arising from this misspecification. Spatial coordinates were obtained from Statistics Canada for 9348 unique point locations. Five hundred-metre polygon-based network buffers were drawn around each coordinate (ArcGIS 10.1). Land use mix was calculated for each buffer using the true and misspecified land use mix formulas. Linear regression models were used to estimate the associations between a simulated dataset of daily steps and the true and misspecified measures. Misspecification of the land use mix formula resulted in a systematic underestimation of the true association by 26.4% (95% CI 25.8-27.0%). To minimize measurement bias in future studies, researchers are encouraged to use a constant definition of N in the denominator of the Shannon entropy formula.