Implications of construction method and spatial scale on measures of the built environment

SEnDAE: A resource for expanding research into social and environmental determinants of health

BACKGROUND AND OBJECTIVE

Social and Environmental Determinants of Health (SEDoH) are of increasing interest to researchers in personal and public health. Collecting SEDoH and associating them with patient medical record can be challenging, especially for environmental variables. We announce here the release of SEnDAE, the Social and Environmental Determinants Address Enhancement toolkit, and open-source resource for ingesting a range of environmental variables and measurements from a variety of sources and associated them with arbitrary addresses.

METHODS

SEnDAE includes optional components for geocoding addresses, in case an organization does not have independent capabilities in that area, and recipes for extending the OMOP CDM and the ontology of an i2b2 instance to display and compute over the SEnDAE variables within i2b2.

RESULTS

On a set of 5000 synthetic addresses, SEnDAE was able to geocode 83%. SEnDAE geocodes addresses to the same Census tract as ESRI 98.1% of the time.

CONCLUSION

Development of SEnDAE is ongoing, but we hope that teams will find it useful to increase their usage of environmental variables and increase the field's general understanding of these important determinants of health.

Assessment of Citizens’ Perception of the Built Environment throughout Digital Platforms: A Scoping Review

(1) Background: To assess the quality of the built environment, it is necessary to study both the physical components and the inhabitants’ perceptions. However, since objective indicators are easily measurable, most studies have centered only on analyzing the physical dimensions of cities. Currently, the massification of information technology and the emergence of digital platforms are offering new participatory channels for studying citizens’ perceptions of the built environment. (2) Objective: considering the scarcity of the theoretical and methodological approaches supporting this new research, the main objective of this article is centered on contributing to the field by developing a scoping review of the publications assessing the perception of the built environment through digital platforms and concluding with a conceptual framework to support future research. (3) Methods: to do so, 98 articles were reviewed and 21 of them were selected and studied in detail after applying a selection criteria identifying papers that analyzed the urban environment (Criteria 1), used participatory processes (Criteria 2), were developed with the support of digital platforms (Criteria 3), and were centered on the study urban places, therefore excluding mobility (Criteria 4), which was done in order to identify the main theoretical and methodological approaches used for studying perception in the built environment. (4) Results: The research identified Audit Tools and Perception Tools to study citizens’ perceptions. Audit Tools are methodologically related to Systematic Social Observation (SSO). Perception Tools rely on transactional person–environment or Public Participation as the main theories, followed by Subjective Wellbeing (SWB), Physical Activity (PA), and Social Sustainability as fields where these studies are being applied. Participatory mapping is identified as a general methodology, considered the basic technical tool of Public Participation Geographic Information Systems (PPGIS). Place-based and Citizens Science are other methodologies supporting perception research. (5) Conclusions: Finally, the proposed framework for assessing the perception of the built environment supports the notion that, in order to study perception, both subjective and objective approaches are necessary. The subjective approach supports the study of the self-reported perceived environment while the objective approach is used to collect urban structure data so as to understand the socio-environmental context conditioning the experience.

Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research

The National Institute of Environmental Health Sciences (NIEHS) Superfund Basic Research and Training Program (SRP) funds a wide range of projects that span biomedical, environmental sciences, and engineering research and generate a wealth of data resulting from hypothesis-driven research projects. Combining or integrating these diverse data offers an opportunity to uncover new scientific connections that can be used to gain a more comprehensive understanding of the interplay between exposures and health. Integrating and reusing data generated from individual research projects within the program requires harmonization of data workflows, ensuring consistent and robust practices in data stewardship, and embracing data sharing from the onset of data collection and analysis. We describe opportunities to leverage data within the SRP and current SRP efforts to advance data sharing and reuse, including by developing an SRP dataset library and fostering data integration through Data Management and Analysis Cores. We also discuss opportunities to improve public health by identifying parallels in the data captured from health and engineering research, layering data streams for a more comprehensive picture of exposures and disease, and using existing SRP research infrastructure to facilitate and foster data sharing. Importantly, we point out that while the SRP is in a unique position to exploit these opportunities, they can be employed across environmental health research. SRP research teams, which comprise cross-disciplinary scientists focused on similar research questions, are well positioned to use data to leverage previous findings and accelerate the pace of research. Incorporating data streams from different disciplines addressing similar questions can provide a broader understanding and uncover the answers to complex and discrete research questions.

Characteristics of the built environment and spatial patterning of type 2 diabetes in the urban core of Durham, North Carolina

BACKGROUND

Few studies examine relationships between built environment (BE) and type 2 diabetes mellitus (T2DM) using spatial models, investigate BE domains apart from food environment or physical activity resources or conduct sensitivity analysis of methodological choices made in measuring BE. We examine geographic heterogeneity of T2DM, describe how heterogeneity in T2DM relates to BE and estimate associations of T2DM with BE.

METHODS

Individual-level electronic health records (n=41 203) from the Duke Medicine Enterprise Data Warehouse (2007-2011) were linked to BE based on census block. Data on housing damage, property disorder, territoriality, vacancy and public nuisances were used to estimate BE based on four different construction methods (CMs). We used race-stratified aspatial and spatial Bayesian models to assess geographic heterogeneity in T2DM and associations of T2DM with BE.

RESULTS

Among whites, a 1 SD increase in poor quality BE was associated with a 1.03 (95% credible interval 1.01 to 1.06) and 1.06 (95 % credible interval 1.02 to 1.11) increased risk of T2DM for poor quality BE CM1 and CM2, respectively. Among blacks/African Americans, associations between T2DM and BE overlapped with the null for all CMs. The addition of BE to white models reduced residual geographic heterogeneity in T2DM by 4%-15%, depending on CM. In black/African-American models, BE did not affect residual heterogeneity.

CONCLUSION

Associations of T2DM with BE were sensitive to CM and geographic heterogeneity in T2DM differed by race/ethnicity. Findings underscore the need to consider multiple methods of estimating BE and consider differences in relationships by race/ethnicity.

A direct observation method for auditing large urban centers using stratified sampling, mobile GIS technology and virtual environments

BACKGROUND

With the expansion and growth of research on neighbourhood characteristics, there is an increased need for direct observational field audits. Herein, we introduce a novel direct observational audit method and systematic social observation instrument (SSOI) for efficiently assessing neighbourhood aesthetics over large urban areas.

METHODS

Our audit method uses spatial random sampling stratified by residential zoning and incorporates both mobile geographic information systems technology and virtual environments. The reliability of our method was tested in two ways: first, in 15 Ottawa neighbourhoods, we compared results at audited locations over two subsequent years, and second; we audited every residential block (167 blocks) in one neighbourhood and compared the distribution of SSOI aesthetics index scores with results from the randomly audited locations. Finally, we present interrater reliability and consistency results on all observed items.

RESULTS

The observed neighbourhood average aesthetics index score estimated from four or five stratified random audit locations is sufficient to characterize the average neighbourhood aesthetics. The SSOI was internally consistent and demonstrated good to excellent interrater reliability. At the neighbourhood level, aesthetics is positively related to SES and physical activity and negatively correlated with BMI.

CONCLUSION

The proposed approach to direct neighbourhood auditing performs sufficiently and has the advantage of financial and temporal efficiency when auditing a large city.