Comparing Location Data From Smartphone and Dedicated Global Positioning System Devices: Implications for Epidemiologic Research.

In this study, we compared location data from a dedicated Global Positioning System (GPS) device with location data from smartphones. Data from the Interventions, Equity, and Action in Cities Team (INTERACT) Study, a study examining the impact of urban-form changes on health in 4 Canadian cities (Victoria, Vancouver, Saskatoon, and Montreal), were used. A total of 337 participants contributed data collected for about 6 months from the Ethica Data smartphone application (Ethica Data Inc., Toronto, Ontario, Canada) and the SenseDoc dedicated GPS (MobySens Technologies Inc., Montreal, Quebec, Canada) during the period 2017-2019. Participants recorded an average total of 14,781 Ethica locations (standard deviation, 19,353) and 197,167 SenseDoc locations (standard deviation, 111,868). Dynamic time warping and cross-correlation were used to examine the spatial and temporal similarity of GPS points. Four activity-space measures derived from the smartphone app and the dedicated GPS device were compared. Analysis showed that cross-correlations were above 0.8 at the 125-m resolution for the survey and day levels and increased as cell size increased. At the day or survey level, there were only small differences between the activity-space measures. Based on our findings, we recommend dedicated GPS devices for studies where the exposure and the outcome are both measured at high frequency and when the analysis will not be aggregate. When the exposure and outcome are measured or will be aggregated to the day level, the dedicated GPS device and the smartphone app provide similar results.

HealthyPlan.City: A Web Tool to Support Urban Environmental Equity and Public Health in Canadian Communities.

Urban environmental factors such as air quality, heat islands, and access to greenspaces and community amenities impact public health. Some vulnerable populations such as low-income groups, children, older adults, new immigrants, and visible minorities live in areas with fewer beneficial conditions, and therefore, face greater health risks. Planning and advocating for equitable healthy urban environments requires systematic analysis of reliable spatial data to identify where vulnerable populations intersect with positive or negative urban/environmental characteristics. To facilitate this effort in Canada, we developed HealthyPlan.City ( https://healthyplan.city/ ), a freely available web mapping platform for users to visualize the spatial patterns of built environment indicators, vulnerable populations, and environmental inequity within over 125 Canadian cities. This tool helps users identify areas within Canadian cities where relatively higher proportions of vulnerable populations experience lower than average levels of beneficial environmental conditions, which we refer to as Equity priority areas. Using nationally standardized environmental data from satellite imagery and other large geospatial databases and demographic data from the Canadian Census, HealthyPlan.City provides a block-by-block snapshot of environmental inequities in Canadian cities. The tool aims to support urban planners, public health professionals, policy makers, and community organizers to identify neighborhoods where targeted investments and improvements to the local environment would simultaneously help communities address environmental inequities, promote public health, and adapt to climate change. In this paper, we report on the key considerations that informed our approach to developing this tool and describe the current web-based application.

A Systematic Review of Qualitative Studies on Factors Associated With Smoking Cessation Among Adolescents and Young Adults.

OBJECTIVE: To summarize findings from qualitative studies on factors associated with smoking cessation among adolescents and young adults. DATA SOURCES: We searched Pubmed, Psychinfo, CINAHL, Embase, Web of Science, and SCOPUS databases, as well as reference lists, for peer-reviewed articles published in English or French between January 1, 2000, and November 18, 2020. We used keywords such as adolescents, determinants, cessation, smoking, and qualitative methods. STUDY SELECTION: Of 1724 records identified, we included 39 articles that used qualitative or mixed methods, targeted adolescents and young adults aged 10-24, and aimed to identify factors associated with smoking cessation or smoking reduction. DATA EXTRACTION: Two authors independently extracted the data using a standardized form. We assessed study quality using the National Institute for Health and Care Excellence checklist for qualitative studies. DATA SYNTHESIS: We used an aggregative meta-synthesis approach and identified 39 conceptually distinct factors associated with smoking cessation. We grouped them into two categories: (1) environmental factors [tobacco control policies, pro-smoking norms, smoking cessation services and interventions, influence of friends and family], and (2) individual attributes (psychological characteristics, attitudes, pre-quitting smoking behavior, nicotine dependence symptoms, and other substances use). We developed a synthetic framework that captured the factors identified, the links that connect them, and their associations with smoking cessation. CONCLUSIONS: This qualitative synthesis offers new insights on factors related to smoking cessation services, interventions, and attitudes about cessation (embarrassment when using cessation services) not reported in quantitative reviews, supplementing limited evidence for developing cessation programs for young persons who smoke. IMPLICATIONS: Using an aggregative meta-synthesis approach, this study identified 39 conceptually distinct factors grouped into two categories: Environmental factors and individual attributes. These findings highlight the importance of considering both environmental and individual factors when developing smoking cessation programs for young persons who smoke. The study also sheds light on self-conscious emotions towards cessation, such as embarrassment when using cessation services, which are often overlooked in quantitative reviews. Overall, this study has important implications for developing effective smoking cessation interventions and policies that address the complex factors influencing smoking behavior among young persons.

Neighbourhood social deprivation and risk of prostate cancer.

BACKGROUND: Striking geographic variations in prostate cancer incidence suggest an aetiological role for spatially-distributed factors. We assessed whether neighbourhood social deprivation, which can reflect limited social contacts, unfavourable lifestyle and environmental exposures, is associated with prostate cancer risk. METHODS: In 2005-2012, we recruited 1931 incident prostate cancer cases and 1994 controls in a case-control study in Montreal, Canada. Lifetime residential addresses were linked to an area-based social deprivation index around recruitment (2006) and about 10 years earlier (1996). Logistic regression estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Men residing in areas characterised by greater social deprivation had elevated prostate cancer risks (ORs of 1.54 and 1.60 for recent and past exposures, respectively; highest vs lowest quintiles), independently from area- and individual-level confounders and screening patterns. The increase in risk with recent high social deprivation was particularly elevated for high-grade prostate cancer at diagnosis (OR 1.87, 95% CI 1.32-2.64). Associations were more pronounced for neighbourhoods with higher proportions of separated/divorced or widowed individuals in the past, and with higher percentages of residents living alone recently. CONCLUSIONS: These novel findings, suggesting that neighbourhood-level social deprivation increases the risk of prostate cancer, point out to potential targeted public health interventions.

How is the COVID-19 pandemic impacting our life, mental health, and well-being? Design and preliminary findings of the pan-Canadian longitudinal COHESION study.

BACKGROUND: With the advent of the COVID-19 pandemic, in-person social interactions and opportunities for accessing resources that sustain health and well-being have drastically reduced. We therefore designed the pan-Canadian prospective COVID-19: HEalth and Social Inequities across Neighbourhoods (COHESION) cohort to provide a deeper understanding of how the COVID-19 pandemic context affects mental health and well-being, key determinants of health, and health inequities. METHODS: This paper presents the design of the two-phase COHESION Study, and descriptive results from the first phase conducted between May 2020 and September 2021. During that period, the COHESION research platform collected monthly data linked to COVID-19 such as infection and vaccination status, perceptions and attitudes regarding pandemic-related measures, and information on participants' physical and mental health, well-being, sleep, loneliness, resilience, substances use, living conditions, social interactions, activities, and mobility. RESULTS: The 1,268 people enrolled in the Phase 1 COHESION Study are for the most part from Ontario (47%) and Quebec (33%), aged 48 ± 16 years [mean ± standard deviation (SD)], and mainly women (78%), White (85%), with a university degree (63%), and living in large urban centers (70%). According to the 298 ± 68 (mean ± SD) prospective questionnaires completed each month on average, the first year of follow-up reveals significant temporal variations in standardized indexes of well-being, loneliness, anxiety, depression, and psychological distress. CONCLUSIONS: The COHESION Study will allow identifying trajectories of mental health and well-being while investigating their determinants and how these may vary by subgroup, over time, and across different provinces in Canada, in varying context including the pandemic recovery period. Our findings will contribute valuable insights to the urban health field and inform future public health interventions.

Neighborhood built environment typologies and adiposity in children and adolescents.

BACKGROUND/OBJECTIVES: Neighborhoods are complex, multidimensional systems. However, the interrelation between multiple neighborhood dimensions is seldom considered in relation to youth adiposity. We created a neighborhood typology using a range of built environment features and examined its association with adiposity in youth. SUBJECTS/METHODS: Analyses are based on data from the QUALITY cohort, an ongoing study on the natural history of obesity in Quebec youth with a history of parental obesity. Adiposity was measured at baseline (8-10 years) and follow up, ~8 years later. Neighborhood features were measured at baseline through in-person neighborhood assessments and geocoded administrative data and were summarized using principal components analysis. Neighborhood types were identified using cluster analysis. Associations between neighborhood types and adiposity were examined using multivariable linear regressions. RESULTS: Five distinct neighborhood types characterized by levels of walkability and traffic-related safety were identified. At ages 8-10 years, children in moderate walkability/low safety neighborhoods had higher BMI Z-scores [ß: 0.41 (0.12; 0.71), p = 0.007], fat mass index [ß: 1.22 (0.29; 2.16), p = 0.010], waist circumference [ß: 4.92 (1.63; 8.21), p = 0.003], and central fat mass percentage [ß: 1.60 (0.04; 3.16), p = 0.045] than those residing in moderate walkability/high safety neighborhoods. Attenuated associations were observed between neighborhood types and adiposity 8 years later. Specifically, residents of moderate walkability/low safety neighborhoods had a higher FMI [ß: 1.42 (-0.07; 2.90), p = 0.062], and waist circumference [ß: 5.04 (-0.26; 10.34), p = 0.062]. CONCLUSIONS: Neighborhoods characterized by lower traffic safety appear to be the most obesogenic to children, regardless of other walkability-related features. Policies targeting neighborhood walkability for children may need to prioritize vehicular traffic safety.

Using combined Global Position System and accelerometer data points to examine how built environments and gentrification are associated with physical activity in four Canadian cities.

BACKGROUND: Built and social environments are associated with physical activity. Global Positioning Systems (GPS) and accelerometer data can capture how people move through their environments and provide promising tools to better understand associations between environmental characteristics and physical activity. The purpose of this study is to examine the associations between GPS-derived exposure to built environment and gentrification characteristics and accelerometer-measured physical activity in a sample of adults across four cities. METHODS: We used wave 1 data from the Interventions, Research, and Action in Cities Team, a cohort of adults living in the Canadian cities of Victoria, Vancouver, Saskatoon, and Montreal. A subsample of participants wore a SenseDoc device for 10 days during May 2017-January 2019 to record GPS and accelerometry data. Two physical activity outcomes were derived from SenseDoc data: time spent in light, moderate, and vigorous physical activity; and time spent in moderate or vigorous physical activity. Using corresponding GPS coordinates, we summarized physical activity outcomes by dissemination area-a Canadian census geography that represents areas where 400 to 700 people live- and joined to built (active living space, proximity to amenities, and urban compactness) and gentrification measures. We examined the associations between environmental measures and physical activity outcomes using multi-level negative binomial regression models that were stratified by city and adjusted for covariates (weekday/weekend), home dissemination area, precipitation, temperature) and participant-level characteristics obtained from a survey (age, gender, income, race). RESULTS: We found that adults spent more time being physically active near their homes, and in environments that were more walkable and near parks and less time in urban compact areas, regardless of where participants lived. Our analysis also highlighted how proximity to different amenities was linked to physical activity across different cities. CONCLUSIONS: Our study provides insights into how built environment and gentrification characteristics are associated with the amount of time adults spend being physically active in four Canadian cities. These findings enhance our understanding of the influence that environments have on physical activity over time and space, and can support policies to increase physical activity.

Operationalising the 20-minute neighbourhood.

BACKGROUND: Recent rapid growth in urban areas and the desire to create liveable neighbourhoods has brought about a renewed interest in planning for compact cities, with concepts like the 20-minute neighbourhood (20MN) becoming more popular. A 20MN broadly reflects a neighbourhood that allows residents to meet their daily (non-work) needs within a short, non-motorised, trip from home. The 20MN concept underpins the key planning strategy of Australia's second largest city, Melbourne, however the 20MN definition has not been operationalised. This study aimed to develop and operationalise a practical definition of the 20MN and apply this to two Australian state capital cities: Melbourne (Victoria) and Adelaide (South Australia). METHODS: Using the metropolitan boundaries for Melbourne and Adelaide, data were sourced for several layers related to five domains: 1) healthy food; 2) recreational resources; 3) community resources; 4) public open space; and 5) public transport. The number of layers and the access measures required for each domain differed. For example, the recreational resources domain only required a sport and fitness centre (gym) within a 1.5-km network path distance, whereas the public open space domain required a public open space within a 400-m distance along a pedestrian network and 8 ha of public open space area within a 1-km radius. Locations that met the access requirements for each of the five domains were defined as 20MNs. RESULTS: In Melbourne 5.5% and in Adelaide 7.6% of the population were considered to reside in a 20MN. Within areas classified as residential, the median number of people per square kilometre with a 20MN in Melbourne was 6429 and the median number of dwellings per square kilometre was 3211. In Adelaide's 20MNs, both population density (3062) and dwelling density (1440) were lower than in Melbourne. CONCLUSIONS: The challenge of operationalising a practical definition of the 20MN has been addressed by this study and applied to two Australian cities. The approach can be adapted to other contexts as a first step to assessing the presence of existing 20MNs and monitoring further implementation of this concept.

Creation and validation of the pictorial ecological momentary well-being instrument (EMOWI) for adolescents.

PURPOSE: Adolescence is characterized by the ongoing maturation of emotion-regulation skills and increased emotional reactivity. There is a need for a measurement tool suitable to the Ecological Momentary Assessment methodology, to better capture within-day variations in well-being, and provide fine-grained data that can help understand how environments, behaviors, and health intersect. This paper presents the development and evaluation of the Ecological MOmentary Well-Being Instrument for adolescents, designed for use in EMA. METHODS: A mixed-methods study was conducted, using both qualitative and quantitative approaches, to develop and assess the EMOWI. A literature review, pictorial production by graphic designers, and qualitative interviews with French and Canadian professionals and adolescents helped design and evaluate the scale face validity. Quantitative evaluation of dimensionality, reliability, and validity was conducted in two samples of French 8th graders. RESULTS: The resulting 8-item EMOWI showed excellent face validity. Confirmatory factor analysis supported a single factor hypothesis (RMSEA = 0.072). Internal consistency (Cronbach's alpha = 0.85) and intraday test-retest reliability (ICC = 0.83) were high. Correlations with existing scales were consistent with preset hypotheses. Ceiling effects were evidenced for all items, yet not on the global score. Quantitative estimations were similar for the verbal and pictorial versions, but qualitative findings argued in favor of the pictorial version. CONCLUSION: The 8-item pictorial EMOWI is a short and innovative instrument to measure momentary well-being in adolescents aged 12 to 17 years. Its strong psychometric properties and its acceptability among adolescents make it an excellent candidate instrument for the Ecological Momentary Assessment of well-being in this population.

Rethinking walkability and developing a conceptual definition of active living environments to guide research and practice.

BACKGROUND: Walkability is a popular term used to describe aspects of the built and social environment that have important population-level impacts on physical activity, energy balance, and health. Although the term is widely used by researchers, practitioners, and the general public, and multiple operational definitions and walkability measurement tools exist, there are is no agreed-upon conceptual definition of walkability. METHOD: To address this gap, researchers from Memorial University of Newfoundland hosted "The Future of Walkability Measures Workshop" in association with researchers from the Canadian Urban Environmental Health Research Consortium (CANUE) in November 2017. During the workshop, trainees, researchers, and practitioners worked together in small groups to iteratively develop and reach consensus about a conceptual definition and name for walkability. The objective of this paper was to discuss and propose a conceptual definition of walkability and related concepts. RESULTS: In discussions during the workshop, it became clear that the term walkability leads to a narrow conception of the environmental features associated with health as it inherently focuses on walking. As a result, we suggest that the term Active Living Environments, as has been previously proposed in the literature, are more appropriate. We define Active Living Environments (ALEs) as the emergent natural, built, and social properties of neighbourhoods that promote physical activity and health and allow for equitable access to health-enhancing resources. CONCLUSIONS: We believe that this broader conceptualization allows for a more comprehensive understanding of how built, natural, and social environments can contribute to improved health for all members of the population.

Recruiting Participants for Population Health Intervention Research: Effectiveness and Costs of Recruitment Methods for a Cohort Study.

BACKGROUND: Public health research studies often rely on population-based participation and draw on various recruitment methods to establish samples. Increasingly, researchers are turning to web-based recruitment tools. However, few studies detail traditional and web-based recruitment efforts in terms of costs and potential biases. OBJECTIVE: This study aims to report on and evaluate the cost-effectiveness, time effectiveness, and sociodemographic representation of diverse recruitment methods used to enroll participants in 3 cities of the Interventions, Research, and Action in Cities Team (INTERACT) study, a cohort study conducted in Canadian cities. METHODS: Over 2017 and 2018 in Vancouver, Saskatoon, and Montreal, the INTERACT study used the following recruitment methods: mailed letters, social media (including sponsored Facebook advertisements), news media, partner communications, snowball recruitment, in-person recruitment, and posters. Participation in the study involved answering web-based questionnaires (at minimum), activating a smartphone app to share sensor data, and wearing a device for mobility and physical activity monitoring. We describe sociodemographic characteristics by the recruitment method and analyze performance indicators, including cost, completion rate, and time effectiveness. Effectiveness included calculating cost per completer (ie, a participant who completed at least one questionnaire), the completion rate of a health questionnaire, and the delay between completion of eligibility and health questionnaires. Cost included producing materials (ie, printing costs), transmitting recruitment messages (ie, mailing list rental, postage, and sponsored Facebook posts charges), and staff time. In Montreal, the largest INTERACT sample, we modeled the number of daily recruits through generalized linear models accounting for the distributed lagged effects of recruitment campaigns. RESULTS: Overall, 1791 participants were recruited from 3 cities and completed at least one questionnaire: 318 in Vancouver, 315 in Saskatoon, and 1158 in Montreal. In all cities, most participants chose to participate fully (questionnaires, apps, and devices). The costs associated with a completed participant varied across recruitment methods and by city. Facebook advertisements generated the most recruits (n=687), at a cost of CAD $15.04 (US $11.57; including staff time) per completer. Mailed letters were the costliest, at CAD $108.30 (US $83.3) per completer but served to reach older participants. All methods resulted in a gender imbalance, with women participating more, specifically with social media. Partner newsletters resulted in the participation of younger adults and were cost-efficient (CAD $5.16 [US $3.97] per completer). A generalized linear model for daily Montreal recruitment identified 2-day lag effects on most recruitment methods, except for the snowball campaign (4 days), letters (15 days), and reminder cards (5 days). CONCLUSIONS: This study presents comprehensive data on the costs, effectiveness, and bias of population recruitment in a cohort study in 3 Canadian cities. More comprehensive documentation and reporting of recruitment efforts across studies are needed to improve our capacity to conduct inclusive intervention research.

Gentrification, Urban Interventions and Equity (GENUINE): A map-based gentrification tool for Canadian metropolitan areas.

BACKGROUND: Researchers, policy makers, and urban planners require tools to better understand the complex relationship between gentrification and health. The Gentrification, Urban Interventions and Equity (GENUINE) tool is an open-access, map-based tool that allows users to explore measures of gentrification for Canadian cities and incorporate them into their work. DATA AND METHODS: The phenomenon of gentrification has manifested differently across cities. The GENUINE tool was developed to include four distinct gentrification measures that have been used in the United States and Canada and that rely on different combinations of change in census indicators related to income, housing, occupation, education and age. The measures were computed for all census tracts within the 36 Canadian census metropolitan areas to identify gentrifiable areas in 2006 and those that gentrified between 2006 and 2016. RESULTS: Depending on the measure, by 2016, 2% to 20% of census tracts had experienced gentrification, corresponding to between 2% (418,065 people) and 17% (4,266,434) of the Canadian population living in gentrified areas. Generally, metropolitan areas with populations over 1 million people had a greater proportion of their population living in gentrified areas (2% to 18%) compared with metropolitan areas with fewer than 250,000 residents (1% to 14%). DISCUSSION: With attention on healthy cities only expanding, GENUINE provides pan-Canadian indicators of gentrification, which can be an integral part of solution-oriented research and advancing cities toward designing healthy and equitable communities.

Is Smoking Cessation in Young Adults Associated With Tobacco Retailer Availability in Their Activity Space?

INTRODUCTION: The presence of tobacco retailers in residential neighborhoods has been inversely associated with residents' likelihood of quitting smoking. Few studies have yet explored whether this association holds when accounting for tobacco retailers found in the multiple environments where people conduct their daily activities, that is, their activity space. METHODS: We analyzed cross-sectional data from 921 young adults (18- to 25-years old) participating in the Interdisciplinary Study of Inequalities in Smoking (Montreal, Canada). Respondents self-reported sociodemographic, smoking, and activity location data. Log-binomial regression was used to estimate prevalence ratios (PRs) for the association between smoking cessation and (1) the number of tobacco retailers (counts), and (2) the distance to the closest retailer (proximity) in participants' residential neighborhood and activity space. RESULTS: Smoking cessation was positively associated with low and intermediate tertile levels of tobacco retailer counts in both the residential neighborhood and activity space, and with the furthest distance level in the activity space [PR (95% CI) = 1.21 (1.02 to 1.43)]. CONCLUSIONS: Individuals encounter resources in the course of their regular daily activities that may hamper smoking cessation. This study highlights the relevance of considering the tobacco retail environment of both individuals' residential neighborhood and activity space to understand its association with smoking cessation. IMPLICATIONS: This article contributes to the literature on the association between the tobacco retail environment and smoking cessation in young adults by moving beyond the residential neighborhood to also assess individuals' access to tobacco retailers in the multiple areas where they regularly spend time, that is, their activity space. Findings suggest that lower numbers of tobacco retailers in both the residential neighborhood and activity space, and further distance to tobacco retailers in the activity space are associated with increased smoking cessation.

Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking.

BACKGROUND: Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes. METHODS: We used data of 285 participants (RECORD MultiSensor Study, 2013-2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken. RESULTS: Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city. CONCLUSIONS: Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity.

INTERACT: A comprehensive approach to assess urban form interventions through natural experiments.

BACKGROUND: Urban form interventions can result in positive and negative impacts on physical activity, social participation, and well-being, and inequities in these outcomes. Natural experiment studies can advance our understanding of causal effects and processes related to urban form interventions. The INTErventions, Research, and Action in Cities Team (INTERACT) is a pan-Canadian collaboration of interdisciplinary scientists, urban planners, and public health decision makers advancing research on the design of healthy and sustainable cities for all. Our objectives are to use natural experiment studies to deliver timely evidence about how urban form interventions influence health, and to develop methods and tools to facilitate such studies going forward. METHODS: INTERACT will evaluate natural experiments in four Canadian cities: the Arbutus Greenway in Vancouver, British Columbia; the All Ages and Abilities Cycling Network in Victoria, BC; a new Bus Rapid Transit system in Saskatoon, Saskatchewan; and components of the Sustainable Development Plan 2016-2020 in Montreal, Quebec, a plan that includes urban form changes initiated by the city and approximately 230 partnering organizations. We will recruit a cohort of between 300 and 3000 adult participants, age 18 or older, in each city and collect data at three time points. Participants will complete health and activity space surveys and provide sensor-based location and physical activity data. We will conduct qualitative interviews with a subsample of participants in each city. Our analysis methods will combine machine learning methods for detecting transportation mode use and physical activity, use temporal Geographic Information Systems to quantify changes to urban intervention exposure, and apply analytic methods for natural experiment studies including interrupted time series analysis. DISCUSSION: INTERACT aims to advance the evidence base on population health intervention research and address challenges related to big data, knowledge mobilization and engagement, ethics, and causality. We will collect ~ 100 TB of sensor data from participants over 5 years. We will address these challenges using interdisciplinary partnerships, training of highly qualified personnel, and modern methodologies for using sensor-based data.

A pan-Canadian measure of active living environments using open data.

BACKGROUND: Neighbourhood environments that support active living, such as walking or cycling for transportation, may decrease the burden of chronic conditions related to sedentary behaviour. Many measures exist to summarize features of communities that support active living, but few are pan-Canadian and none use open data sources that can be widely shared. This study reports the development and validation of a novel set of indicators of active living environments using open data that can be linked to national health surveys and can be used by local, regional or national governments for public health surveillance. DATA AND METHODS: A Geographic Information System (GIS) was used to calculate a variety of measures of the connectivity, density and proximity to destinations for 56,589 dissemination areas (DAs) across Canada (2016 data). Pearson correlation coefficients were calculated to assess the association between each measure and the rates of walking to work and taking active transportation to work (a combination of walking, cycling and using public transportation) from census data. The active living environment measures selected for the final database were used to classify the DAs by the favourability of their active living environment into groups by k-medians clustering. RESULTS: All measures were correlated with walking-to-work and active-transportation-to-work rates at the DA level, whether they were derived using proprietary or open data sources. Coverage of open data was consistent across Canadian regions. Three measures were selected for the Canadian Active Living Environments (Can-ALE) dataset based on the correlation analysis, but also on the principles of suitability for a variety of community sizes and openly available data: (1) three-way intersection density of roads and footpaths derived from OpenStreetMap (OSM), (2) weighted dwelling density derived from Statistics Canada dwelling counts and (3) points of interest derived from OSM. A measure of access to public transportation was added for the subset of DAs in larger urban areas and was strongly related to active-transportation-to-work rates. Active-transportation-to-work rates were graded, in steps, by the five Can-ALE groups derived from the cluster analysis, although walking-to-work rates exceeded the national average only in the most favourable active living environments. DISCUSSION: Open data may be used to derive measures that characterize the active living environments of Canadian communities.

Spatial modeling of daily concentrations of ground-level ozone in Montreal, Canada: A comparison of geostatistical approaches.

Ground-level ozone (O3) is a powerful oxidizing agent and a harmful pollutant affecting human health, forests and crops. Estimating O3 exposure is a challenge because it exhibits complex spatiotemporal patterns. The aim in this study was to provide high-resolution maps (100 × 100 m) of O3 for the metropolitan area of Montreal, Canada. We assessed the kriging with external drift (KED) model to estimate O3 concentration by synoptic weather classes for 2010. We compared these results with ordinary kriging (OK), and a simple average of 12 monitoring stations. We also compared the estimates obtained for the 2010 summer with those from a Bayesian maximum entropy (BME) model reported in the literature (Adam-Poupart et al., 2014). The KED model with road and vegetation density as covariates showed good performance for all six synoptic classes (daily R2 estimates ranging from 0.77 to 0.92 and RMSE from 2.79 to 3.37 ppb). For the summer of 2010, the model using KED demonstrated the best results (R2 = 0.92; RMSE = 3.14 ppb), followed by the OK model (R2 = 0.85, RMSE = 4 ppb). Our results showed that errors appear to be substantially reduced with the KED model. This may increase our capacity of linking O3 levels to health problems by means of improved assessments of ambient exposures. However, future work integrating the temporal dependency in the data is needed to not overstate the performance of the KED model.

Promoting access to fresh fruits and vegetables through a local market intervention at a subway station.

OBJECTIVE: Alternative food sources (AFS) such as local markets in disadvantaged areas are promising strategies for preventing chronic disease and reducing health inequalities. The present study assessed how sociodemographic characteristics, physical access and fruit and vegetable (F&V) consumption are associated with market use in a newly opened F&V market next to a subway station in a disadvantaged neighbourhood. DESIGN: Two cross-sectional surveys were conducted among adults: (i) on-site, among shoppers who had just bought F&V and (ii) a telephone-based population survey among residents living within 1 km distance from the market. SETTING: One neighbourhood in Montreal (Canada) with previously limited F&V offerings. SUBJECTS: Respectively, 218 shoppers and 335 residents completed the on-site and telephone-based population surveys. RESULTS: Among shoppers, 23 % were low-income, 56 % did not consume enough F&V and 54 % did not have access to a car. Among all participants living 1 km from the market (n 472), market usage was associated (OR; 95 % CI) with adequate F&V consumption (1·86; 1·10, 3·16), living closer to the market (for distance: 0·86; 0·76, 0·97), having the market on the commute route (2·77; 1·61, 4·75) and not having access to a car (2·96; 1·67, 5·26). CONCLUSIONS: When implemented in strategic locations such as transport hubs, AFS like F&V markets offer a promising strategy to improve F&V access among populations that may be constrained in their food acquisition practices, including low-income populations and those relying on public transportation.

The "Residential" Effect Fallacy in Neighborhood and Health Studies: Formal Definition, Empirical Identification, and Correction.

BACKGROUND: Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this "residential" effect fallacy bias applicable to a large fraction of neighborhood and health studies. METHODS: Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naïve intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions). RESULTS: There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naïve model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naïve estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8. CONCLUSIONS: Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.

An evaluation of transport mode shift policies on transport-related physical activity through simulations based on random forests.

BACKGROUND: Physical inactivity is widely recognized as one of the leading causes of mortality, and transport accounts for a large part of people's daily physical activity. This study develops a simulation approach to evaluate the impact of the Ile-de-France Urban Mobility Plan (2010-2020) on physical activity, under the hypothesis that the intended transport mode shifts are realized. METHODS: Based on the Global Transport Survey (2010, n = 21,332) and on the RECORD GPS Study (2012-2013, n = 229) from the French capital region of Paris (Ile-de-France), a simulation method was designed and tested. The simulation method used accelerometer data and random forest models to predict the impact of the transport mode shifts anticipated in the Mobility Plan on transport-related moderate-to-vigorous physical activity (T-MVPA). The transport mode shifts include less private motorized trips in favor of more public transport, walking, and biking trips. RESULTS: The simulation model indicated a mean predicted increase of 2 min per day of T-MVPA, in case the intended transport mode shifts in the Ile-de-France Urban Mobility Plan were realized. The positive effect of the transport mode shifts on T-MVPA would, however, be larger for people with a higher level of education. This heterogeneity in the positive effect would further increase the existing inequality in transport-related physical activity by educational level. CONCLUSIONS: The method presented in this paper showed a significant increase in transport-related physical activity in case the intended mode shifts in the Ile-de-France Urban Mobility Plan were realized. This simulation method could be applied on other important health outcomes, such as exposure to noise or air pollution, making it a useful tool to anticipate the health impact of transport interventions or policies.