Background COVID-19 has had differential impacts on health and mobility patterns.

Data Health survey variables collected in 2020 in Saskatoon, Montreal, and Vancouver

Methods

• Operationalize use, frequency of use and perception of urban form interventions
• Operationalize differences in behavior by COVID phase (most locked down phase, vs current context (fall 2020))
• Analyze use in relation to gender and age

Expertise required GISc, strong methodological background

Background Measuring and understanding exposure to and changes in the urban environment is crucial for public health intervention research. Features of the urban environment like green space, park access, land use mix, transit access, and bike infrastructure relate to population health outcomes. Researchers can use a range of methods to track changes, such as continuous updates to open data GIS layers, GSV image segmentation, and crowd-sourcing initiatives.

Based on the lead author’s interests, this paper could be conceptual, or describe a case study and demonstrate the potential of these methods.

Objectives of the paper

• Document methods for tracking urban form changes over time
• Discuss challenges and opportunities for methodological advancements / Demonstrate the application of these methods for public health intervention research
• Detail exposure measures based on urban form change data
• Discuss how researchers can detect meaningful change

Expertise required Social network analysis

Background While population health is influenced both by social networks and the built environment in people’s activity space, little research has considered spatial and social contexts simultaneously. The VERITAS survey combines map-based questionnaire with a name generator tool. Network analysis provides a useful framework for studying connections between social and spatial contexts.

Data Health Survey, VERITAS, GPS (optional)

Methods

• Create a typology of social network types using VERITAS data
• Operationalize daily mobility using survey data, or GPS data from smartphone
• Operationalize use of urban form interventions using survey variables
• Analyze how social network relates to daily mobility and usage of urban form

Expertise required Analysis of repeated measures

Background The types of environments in which we spent time can impact how we feel during the day. As cities are increasingly interested in indicators of well-being, better understanding the impact of environment on mood can help design happier cities.

Data Health Survey, GPS, EMA

Methods

• Characterize urban environments (considering one, some, or all of the following: greenness, active transportation infrastructure, land use, walkability, transit accessibility)
• Assess exposure to urban environments
• Operationalize mood and well-being
• Analyze effect of environment on mood and well-being

Expertise required Qualitative Data Analysis

Data Semi-structured interviews, Health survey variables

Background People’s experiences and perceptions are a function of the person, the environment, and interaction of the person with the environment, and these can inform how environments relate to health outcomes.

Methods

• Code interview data from different project sites.
• Integrate interview data with other project data (survey
  data, GPS/accelerometry data, ecological momentary assessment data, spatial data)
• Identify themes surrounding participants experience of place

Background Mobility patterns were disrupted during the pandemic. Understanding how changes to mobility patterns may relate to various health outcomes can help public health intervention researchers predict how mobility interventions may impact health.

Data Health Survey Data

Methods

• Calculate trip frequency per phase of COVID lockdown
• Relate trip frequency with self-perception variables and socio-demographic variables
• Discuss cross-tabulated results and potential of mobility interventions on health

Background To better understand the implementation and impact of built environment interventions, it is important to understand the policy context in which these changes are made. We are recruiting a student to join us in investigating how policy and implementation decisions are made with respect to built environment interventions, and whether/how health and equity are considered.

Data Urban policy documents

Methods

• Conduct a policy document analysis to identify language related to health and equity. In each city, we will include recent and historically relevant policies and plans concerning transportation, sustainability, and healthy cities. After initial review of policy documents, the student will develop a policy code book specific for each city.
• Set up key informant interviews to evaluate how and why decisions around the built environment interventions were made, and who was considered in these decisions. In each city, the student will interview 5-8 intersectoral participants (e.g. city staff, elected officials, advocates). They will contribute to the preparation of a semi-structured interview guide.
• Prepare summary reports to city partners to share findings from analysis: the student will contribute to the production of lay material for stakeholders.
• Lead a manuscript to be submitted for publication to a peer-reviewed scientific journal