Validity of environmental audits using GigaPan® and Google Earth Technology

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.

An audit tool for longitudinal assessment of the health-related characteristics of urban neighborhoods: implementation methods and reliability results

BACKGROUND

Improving the neighborhood environment may help address chronic disease and mortality. To identify neighborhood features that are predictors of health, objective assessments of the environment are used. Multiple studies have reported on cross-sectional assessments of health-related neighborhood features using direct observation. As study designs expand to better understand causation and predictors of change, there is a need to test whether direct observation methods are adequate for longitudinal assessment. To our knowledge, this is the first study to report on the reliability of repeated measurements of the neighborhood environment, and their stability, over time.

METHODS

The Pittsburgh Hill/Homewood Research on Neighborhood Change and Health (PHRESH) study conducted longitudinal assessments in two low-income, African American neighborhoods at three waves (years 2012, 2015, 2017). The PHRESH audit tool is a modification of earlier validated tools, with an emphasis on environment features relevant for physical activity, sleep, and obesogenic behaviors. Trained data-collector pairs conducted direct observations of a 25% sample of street segments in each neighborhood. At each wave, we audited a sub-sample of street segments twice and assessed reliability using percentage inter-observer agreement and krippendorf's alpha statistics. Stability of these items was assessed as exhibiting moderate or high agreement at every time point.

RESULTS

Across waves, a majority (81%) of the items consistently demonstrated moderate to high agreement except for items such as public/communal space, amount of shade, sidewalk features, number of traffic lanes, garden/flower bed/planter, art/statue/monument, amount of trash, and physical disorder. The list of items with poor agreement includes features that are easy to miss (e.g. flower bed/planter), hard to assess from outside (e.g. public/communal space), or may change quickly (e.g. amount of trash).

CONCLUSION

In this paper, we have described implementation methods, reliability results and lessons learned to inform future studies of change. We found the use of consistent methods allowed us to conduct reliable, replicable longitudinal assessments of the environment. Items that did not exhibit stability are less useful for detecting real change over time. Overall, the PHRESH direct observation tool is an effective and practical instrument to detect change in the neighborhood environment.

Virtual audits of the urban streetscape: comparing the inter-rater reliability of GigaPan® to Google Street View

Background

Although previous research has highlighted the association between the built environment and individual health, methodological challenges in assessing the built environment remain. In particular, many researchers have demonstrated the high inter-rater reliability of assessing large or objective built environment features and the low inter-rater reliability of assessing small or subjective built environment features using Google Street View. New methods for auditing the built environment must be evaluated to understand if there are alternative tools through which researchers can assess all types of built environment features with high agreement. This paper investigates measures of inter-rater reliability of GigaPan®, a tool that assists with capturing high-definition panoramic images, relative to Google Street View.

Methods

Street segments (n = 614) in Pittsburgh, Pennsylvania in the United States were randomly selected to audit using GigaPan® and Google Street View. Each audit assessed features related to land use, traffic and safety, and public amenities. Inter-rater reliability statistics, including percent agreement, Cohen’s kappa, and the prevalence-adjusted bias-adjusted kappa (PABAK) were calculated for 106 street segments that were coded by two, different, human auditors.

Results

Most large-scale, objective features (e.g. bus stop presence or stop sign presence) demonstrated at least substantial inter-rater reliability for both methods, but significant differences emerged across finely detailed features (e.g. trash) and features at segment endpoints (e.g. sidewalk continuity). After adjusting for the effects of bias and prevalence, the inter-rater reliability estimates were consistently higher for almost all built environment features across GigaPan® and Google Street View.

Conclusion

GigaPan® is a reliable, alternative audit tool to Google Street View for studying the built environment. GigaPan® may be particularly well-suited for built environment projects with study settings in areas where Google Street View imagery is nonexistent or updated infrequently. The potential for enhanced, detailed imagery using GigaPan® will be most beneficial in studies in which current, time sensitive data are needed or microscale built environment features would be challenging to see in Google Street View. Furthermore, to better understand the effects of prevalence and bias in future reliability studies, researchers should consider using PABAK to supplement or expand upon Cohen’s kappa findings.

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.

From inspiration to translation: Closing the gap between research and control of helminth zoonoses in Southeast Asia

Poverty magnifies limitations resulting from traditional biases and environmental risks in endemic areas. Any approach towards disease control needs to recognise that socially embedded vulnerabilities can be as powerful as externally imposed infections. Important for RNAS was networking across borders, not just on schistosomiasis but on the whole spectrum of endemic helminthiases, and this bore fruit in the form of the expansion of RNAS into the 'Regional Network on Asian Schistosomiasis and other Helminth Zoonoses (RNAS⁺)', which focuses on technical standardization, supporting the growth of research capacity and the further development of networking. Administration is lean and largely virtual with the focus on connecting members via the Internet, providing databases and administrative back-up. The strategy emphasizes ways and means to alleviate the spectre of disease and poverty from the endemic areas through boosting research on target diseases and supporting collaboration between basic and operational research on the one hand and control/elimination activities on the other. RNAS⁺ also benefits from continuing input from outside research institutions in areas outside Southeast Asia. This paper is aiming to identify the priority actions to close the gap between researcher and policy makers.

Reliability and validity of environmental audits using GigaPan® technology in parks

Park quality and features can contribute to more engaging places for play and recreation. However, assessing park characteristics remains a challenge. This study measured the reliability of GigaPan® as a method for assessing park characteristics as well as the validity of GigaPan® compared to Google Street View (GSV) and direct observation (DO). A total of 65 target areas (16 parks total) in Pittsburgh, PA were assessed using GigaPan®, GSV, and DO from July 2015–January 2016. For reliability and validity, 14 and 28 variables were examined, respectively. Cohen's kappa was used to assess inter-rater reliability. Sensitivity and specificity were used to measure validity. Of the 14 variables included in the inter-rater reliability analysis, five variables had almost perfect reliability (kappa > 0.80) and three variables had substantial reliability (kappa > 0.60). Of the 28 variables included in the validity analysis, GigaPan® was able to correctly classify 17 of the 28 variables and GSV was able to correctly classify 15 of the 28 variables with a sensitivity >80%. There were no significant differences between sensitivity and specificity between GSV and GigaPan®. GigaPan® performed similarly to GSV with DO being used as the gold standard. Further, GigaPan overall had high reliability among the features measured. A strength of GigaPan® is the ability to be implemented quickly in the field, making it a viable alternative to GSV particularly when temporality is an important factor.

•

GigaPan®, a robot system for taking panoramic photos, had high reliability among the park attributes measured

•

GigaPan® is a valid method to assess park attributes and offers some advantages over other methods

•

GigaPan® had comparable validity to Google Earth for assessing features, amenities and incivilities

•

GigaPan® should be used in future studies to help identify the association between park attributes and health outcomes