Examining Associations of Environmental Characteristics with Recreational Cycling Behaviour by Street-Level Strava Data

Association between passively collected walking and bicycling data and purposefully collected active commuting survey data—United States, 2019

Commercially-available location-based services (LBS) data derived primarily from mobile devices may provide an alternative to surveys for monitoring physically-active transportation. Using Spearman correlation, we compared county-level metrics of walking and bicycling from StreetLight with metrics of physically-active commuting among U.S. workers from the American Community Survey. Our strongest pair of metrics ranked counties (n = 298) similarly for walking (rho = 0.53 [95% CI: 0.44-0.61]) and bicycling (rho = 0.61 [0.53-0.67]). Correlations were higher for denser and more urban counties. LBS data may offer public health and transportation professionals timely information on walking and bicycling behavior at finer geographic scales than some existing surveys.

The role of neighbourhood design in cycling activity during COVID-19: An exploration of the Melbourne experience

COVID-19 restrictions imposed significant changes on human mobility patterns, with some studies finding significant increases or decreases in cycling. However, to date there is little understanding on how the neighbourhood-level built environment influenced cycling behaviour during the COVID-19 restrictions. As different neighbourhood have different built environment characteristics, it is possible that cycling trends varied across different built environment settings. We aimed to answer this question by examining recreational cycling during different stages of lockdown in Melbourne, Australia. We compared self-reported recreational cycling frequency (weekly) data from 1344 respondents between pre-COVID and two different stages in lockdown. We tested whether the built environment of their residential neighbourhood and different sociodemographic characteristics influenced leisure cycling rates and whether the effect of these factors varied between different stages of COVID-19 restriction. We found that cycling declined significantly during the two stages of COVID-19 lockdown. Cycling infrastructure density and connectivity are two built environment factors that had a significant effect on limiting the decline in leisure cycling during the pandemic. Furthermore, men and younger people had higher cycling rates in comparison to other groups, suggesting that restrictions on indoor activities and travel limits were not enough to encourage women or older people to cycle more during the pandemic.

Supplementing Environmental Assessments with Cumulative Effects Scenario Modeling for Grizzly Bear Connectivity in the Bow Valley, Alberta, Canada

Persistence of sensitive wildlife in populated regions requires conservation strategies that address gradual expansion of development footprint and human activity. The project-based environmental assessment regime for municipal development is poorly suited to provide necessary strategic perspective, given its focus on local and short-term impacts. We used the ALCES cumulative effects model to strategically assess impacts to grizzly bears (Ursus arctos) in the Bow Valley of Alberta, Canada. Landscape simulation mapped expansion of past and potential future development footprint in the region over multiple decades. Consequences to movement connectivity for grizzly bears were estimated by applying a least cost path analysis to the landscape simulation. An index of recreational activity was derived from fitness tracking data and integrated with the landscape simulation to model change in recreational activity through time. Maps of grizzly bear connectivity and recreational activity were combined to calculate human-bear conflict risk. The analysis suggests that connectivity has been altered through displacement to upslope areas by settlement expansion, such that surrounding natural areas have become important for grizzly bear connectivity. These areas are also popular for outdoor recreation, resulting in elevated human-bear conflict risk which can be expected to increase if development and human activity continue to expand in high connectivity areas. Conservation of wildlife in populated regions will be supported by broadening the scope of environmental assessment to address cumulative effects of development footprint and human activity over large spatial and temporal scales.

Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework

Background

Objective measures of built environment and physical activity provide the opportunity to directly compare their relationship across different populations and spatial contexts. This systematic review synthesises the current body of knowledge and knowledge gaps around the impact of objectively measured built environment metrics on physical activity levels in adults (≥ 18 years). Additionally, this review aims to address the need for improved quality of methodological reporting to evaluate studies and improve inter-study comparability though the creation of a reporting framework.

Methods

A systematic search of the literature was conducted following the PRISMA guidelines. After abstract and full-text screening, 94 studies were included in the final review. Results were synthesised using an association matrix to show overall association between built environment and physical activity variables. Finally, the new PERFORM (’Physical and Environmental Reporting Framework for Objectively Recorded Measures’) checklist was created and applied to the included studies rating them on their reporting quality across four key areas: study design and characteristics, built environment exposures, physical activity metrics, and the association between built environment and physical activity.

Results

Studies came from 21 countries and ranged from two days to six years in duration. Accelerometers and using geographic information system (GIS) to define the spatial extent of exposure around a pre-defined geocoded location were the most popular tools to capture physical activity and built environment respectively. Ethnicity and socio-economic status of participants were generally poorly reported. Moderate-to-vigorous physical activity (MVPA) was the most common metric of physical activity used followed by walking. Commonly investigated elements of the built environment included walkability, access to parks and green space. Areas where there was a strong body of evidence for a positive or negative association between the built environment and physical activity were identified. The new PERFORM checklist was devised and poorly reported areas identified, included poor reporting of built environment data sources and poor justification of method choice.

Conclusions

This systematic review highlights key gaps in studies objectively measuring the built environment and physical activity both in terms of the breadth and quality of reporting. Broadening the variety measures of the built environment and physical activity across different demographic groups and spatial areas will grow the body and quality of evidence around built environment effect on activity behaviour. Whilst following the PERFORM reporting guidance will ensure the high quality, reproducibility, and comparability of future research.

Smartphone app reveals that lynx avoid human recreationists on local scale, but not home range scale

Outdoor recreation is increasing and affects habitat use and selection by wildlife. These effects are challenging to study, especially for elusive species with large spatial requirements, as it is hard to obtain reliable proxies of recreational intensity over extensive areas. Commonly used proxies, such as the density of, or distance to, hiking paths, ignore outdoor recreation occurring on other linear feature types. Here we utilized crowdsourced data from the Strava training app to obtain a large-scale proxy for pedestrian outdoor recreation intensity in southeast Norway. We used the proxy and GPS-tracking data from collared Eurasian lynx (Lynx lynx) to investigate how recreation affects habitat selection at the home range scale and local scale by lynx during summer. We fitted resource selection functions at the two scales using conditional logistic regression. Our analysis revealed that lynx avoided areas of recreational activity at the local scale, but not at home range scale. Nonetheless, lynx frequently used areas associated with recreation, and to a greater degree at night than during the day. Our results suggest that local-scale avoidance of recreation and temporal adjustments of habitat use by lynx mitigate the need for a home range-scale response towards recreation. Scale-dependent responses and temporal adjustments in habitat use may facilitate coexistence between humans and large carnivores.

Volunteered Geographical Information and Recreational Uses within Metropolitan and Rural Contexts

Data obtained through Volunteered Geographical Information (VGI) have gradually been used to monitor and support planning mainly in urban contexts. Regarding recreational activities in peri-urban green and natural areas, VGI has been used to map, measure use intensity, profile users, and evaluate their preferences and motivations. Given their extensive use, it is now worthwhile to assess the value of VGI data to (1) compare recreational uses, profile users and map recreational activities in different contexts (metropolitan vs. rural areas), and (2) evaluate outdoor and adventure tourist products such as Grand Routes (GR). Data from former GPSies (AllTrails nowadays), one of the most popular web-share services, were used to assess recreational uses in Lisbon Metropolitan Area (LMA) and southwest Portugal (SWPT). A set of 22,031 tracks of “on foot” and “on wheels” activities, submitted by 3297 national and foreign users, covering 12 years, was analysed within a GIS modelling environment. Results indicate that, although there are many more submissions in the LMA, the influence of foreigners in the SWPT is higher (11% vs. 19%). The existing GR in SWPT concentrates the foreign use for hiking (71% of foreign vs. 28% of national users), demonstrating its attractiveness. For the favourite activity in both areas—Mountain biking—results show a higher spatial dispersion, yet part of the activity in SWPT still conforms to the GR (16% of foreign and 20% of national use). This study proves other applications for VGI, showing its usefulness for assessing recreational uses in both metropolitan and rural areas. Spatial knowledge about recreational uses is a valuable tool to evaluate and monitor such activities, and to know what users like to do, and where, and is also useful information when designing recreational products considering their tourist potential, thus adding value to these offers.

Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach

The increasing ubiquity of smartphone data, with greater spatial and temporal coverage than achieved by traditional study designs, have the potential to provide insight into habitual physical activity patterns. This study implements and evaluates the utility of both K-means clustering and agglomerative hierarchical clustering methods in identifying weekly and yearlong physical activity behaviour trends. Characterising the demographics and choice of activity type within the identified clusters of behaviour. Across all seven clusters of seasonal activity behaviour identified, daylight saving was shown to play a key role in influencing behaviour, with increased activity in summer months. Investigation into weekly behaviours identified six clusters with varied roles, of weekday versus weekend, on the likelihood of meeting physical activity guidelines. Preferred type of physical activity likewise varied between clusters, with gender and age strongly associated with cluster membership. Key relationships are identified between weekly clusters and seasonal activity behaviour clusters, demonstrating how short-term behaviours contribute to longer-term activity patterns. Utilising unsupervised machine learning, this study demonstrates how the volume and richness of secondary app data can allow us to move away from aggregate measures of physical activity to better understand temporal variations in habitual physical activity behaviour.

Spatial Integration of Non-Motorized Transport and Urban Public Transport Infrastructure: A Case of Johannesburg

Sustainability of transport infrastructure integration begins with involving an all-inclusive transportation chain instead of only focusing on one part of the journey. This is achieved by facilitating spatial integration between diverse transport modalities to allow for a multiplicity of travel opportunities. This paper unpacks the extent of the spatial integration of non-motorized transport and urban public transport infrastructure within the city of Johannesburg in South Africa. Cycling activity datasets derived from Strava Metro and the spatial data of urban public transport infrastructures were collected to demonstrate existing spatial patterns and infrastructure connectivity. Exploratory spatial data analysis and focal statistics analysis were central in the data processing. The findings reveal that cycling activities are separated from urban public transport infrastructure, and the city of Johannesburg’s transport system is characterized by spatially fragmented commuting and cycling operations, with limited to no sharing of infrastructure. Most public transport stations are not easily accessible for non-motorized transport and are characterized by inadequate cycling facilities. In conclusion, the identification of an urban public transportation catchment area becomes essential for developing cities such as Johannesburg. This can be used as tool for planning infrastructural upgrades and forecasting potential public transport ridership while also assessing the impacts of investments in transit planning. There is thus a need to integrate motorized urban public transport and cycling infrastructural developments toward promoting multi-mobility and infrastructure sharing.

Socio-demographic determinants of physical activity and app usage from smartphone data

The increasing ubiquity of smartphones provides a potential new data source to capture physical activity behaviours. Though not designed as a research tool, these secondary data have the potential to capture a large population over a more extensive spatial area and with longer temporality than current methods afford. This paper uses one such secondary data source from a commercial app designed to incentivise activity. We explore the new insights these data provide, alongside the sociodemographic profile of those using physical activity apps, to gain insight into both physical activity behaviour and determinants of app usage in order to evaluate the suitability of the app in providing insights into the physical activity of the population. We find app usage to be higher in females, those aged 25-50, and users more likely to live in areas where a higher proportion of the population are of a lower socioeconomic status. We ascertain longer-term patterns of app usage with increasing age and more male users reaching physical activity guideline recommendations despite longer daily activity duration recorded by female users. Additionally, we identify key weekly and seasonal trends in physical activity. This is one of the first studies to utilise a large volume of secondary physical activity app data to co-investigate usage alongside activity behaviour captured.

Using VGI and Social Media Data to Understand Urban Green Space: A Narrative Literature Review

Volunteered Geographical Information (VGI) and social media can provide information about real-time perceptions, attitudes and behaviours in urban green space (UGS). This paper reviews the use of VGI and social media data in research examining UGS. The current state of the art is described through the analysis of 177 papers to (1) summarise the characteristics and usage of data from different platforms, (2) provide an overview of the research topics using such data sources, and (3) characterise the research approaches based on data pre-processing, data quality assessment and improvement, data analysis and modelling. A number of important limitations and priorities for future research are identified. The limitations include issues of data acquisition and representativeness, data quality, as well as differences across social media platforms in different study areas such as urban and rural areas. The research priorities include a focus on investigating factors related to physical activities in UGS areas, urban park use and accessibility, the use of data from multiple sources and, where appropriate, making more effective use of personal information. In addition, analysis approaches can be extended to examine the network suggested by social media posts that are shared, re-posted or reacted to and by being combined with textual, image and geographical data to extract more representative information for UGS analysis.

The Flows of Nature to People, and of People to Nature: Applying Movement Concepts to Ecosystem Services

To date, the provision of ecosystem services has largely been estimated based on spatial patterns of land cover alone, using benefit transfer analysis. Although it is increasingly being recognised that the distribution of the human population affects whether a potential service translates into a realised service, this misses key steps in the process and assumes that everyone accesses ecosystem services in the same way. Here we describe a conceptual approach to ecosystem services in terms of movement and flows. We highlight that ecosystem service flows can be broken down into ‘nature to people’ (the movement of nature towards beneficiaries) and ‘people to nature’ (the movement of beneficiaries towards nature). The former has been relatively well described. Here, we explore the latter by reviewing research on human migration, animal foraging and landscape connectivity. We assess if and how existing theories might be useful in describing how people seek out ecosystem services. We consider some of the ways in which flows of people to nature can be measured. Such measurements may reveal which movement theories best represent how people seek out and access ecosystem services. Overall, our review aims to improve the future modelling of ecosystem services by more explicitly considering how people access potential services and therefore realise them.

How Is Urban Greenness Spatially Associated with Dockless Bike Sharing Usage on Weekdays, Weekends, and Holidays?

Dockless bike sharing plays an important role in residents’ daily travel, traffic congestion, and air pollution. Recently, urban greenness has been proven to be associated with bike sharing usage around metro stations using a global model. However, their spatial associations and bike sharing usage on public holidays have seldom been explored in previous studies. In this study, urban greenness was obtained objectively using eye-level greenness with street-view images by deep learning segmentation and overhead view greenness from the normalized difference vegetation index (NDVI). Geographically weighted regression (GWR) was applied to fill the research gap by exploring the spatially varying association between dockless bike sharing usage on weekdays, weekends, and holidays, and urban greenness indicators as well as other built environment factors. The results showed that eye-level greenness was positively associated with bike sharing usage on weekdays, weekends, and holidays. Overhead-view greenness was found to be negatively related to bike usage on weekends and holidays, and insignificant on weekdays. Therefore, to promote bike sharing usage and build a cycling-friendly environment, the study suggests that the relevant urban planner should pay more attention to eye-level greenness exposure along secondary roads rather than the NDVI. Most importantly, planning implications varying across the study area during different days were proposed based on GWR results. For example, the improvement of eye-level greenness might effectively promote bike usage in northeastern and southern Futian districts and western Nanshan on weekdays. It also helps promote bike usage in Futian and Luohu districts on weekends, and in southern Futian and southeastern Nanshan districts on holidays.

Virtual Reality Representations of Nature to Improve Well-Being amongst Older Adults: a Rapid Review

Poor well-being amongst older adults poses a serious health concern. Simultaneously, research shows that contact with nature can improve various facets of well-being, including physical, social, and mental well-being. However, nature is not always accessible for older adults due to mobility restrictions and related care needs that come with age. A promising strategy aims at bringing nature inside through pervasive technologies. However, so far, there is little academic understanding of essential nature characteristics, psychological processes involved, and means for implementation in practice. The current study used a three-folded rapid review to assess current understanding and strategies used for improving well-being for older adults through virtual reality representations of nature. Searches were performed across three databases, followed-up by content-based evaluation of abstracts. In total, a set of 25 relevant articles was identified. Only three studies specifically focus on digital nature as an intervention strategy for improving well-being amongst older adults. Although these studies provide useful starting points for the design and (technological) development of such environments, they do not generate understanding of how specific characteristics of virtual nature representations impact social well-being measures in particular, and of the underlying psychological processes involved. We conclude that follow-up research is warranted to close the gap between insights and findings from nature research, gerontology, health research, and human-technology interaction.

Technological innovations in the recreational fishing sector: implications for fisheries management and policy

Technology that is developed for or adopted by the recreational fisheries sector (e.g., anglers and the recreational fishing industry) has led to rapid and dramatic changes in how recreational anglers interact with fisheries resources. From improvements in finding and catching fish to emulating their natural prey and accessing previously inaccessible waters, to anglers sharing their exploits with others, technology is completely changing all aspects of recreational fishing. These innovations would superficially be viewed as positive from the perspective of the angler (aside from the financial cost of purchasing some technologies), yet for the fisheries manager and policy maker, technology may create unintended challenges that lead to reactionary or even ill-defined approaches as they attempt to keep up with these changes. The goal of this paper is to consider how innovations in recreational fishing are changing the way that anglers interact with fish, and thus how recreational fisheries management is undertaken. We use a combination of structured reviews and expert analyses combined with descriptive case studies to highlight the many ways that technology is influencing recreational fishing practice, and, relatedly, what it means for changing how fisheries and/or these technologies need to be managed-from changes in fish capture, to fish handling, to how anglers share information with each other and with managers. Given that technology is continually evolving, we hope that the examples provided here lead to more and better monitoring of technological innovations and engagement by the management and policy authorities with the recreational fishing sector. Doing so will ensure that management actions related to emerging and evolving recreational fishing technology are more proactive than reactive.

Technological innovations in the recreational fishing sector: implications for fisheries management and policy

Technology that is developed for or adopted by the recreational fisheries sector (e.g., anglers and the recreational fishing industry) has led to rapid and dramatic changes in how recreational anglers interact with fisheries resources. From improvements in finding and catching fish to emulating their natural prey and accessing previously inaccessible waters, to anglers sharing their exploits with others, technology is completely changing all aspects of recreational fishing. These innovations would superficially be viewed as positive from the perspective of the angler (aside from the financial cost of purchasing some technologies), yet for the fisheries manager and policy maker, technology may create unintended challenges that lead to reactionary or even ill-defined approaches as they attempt to keep up with these changes. The goal of this paper is to consider how innovations in recreational fishing are changing the way that anglers interact with fish, and thus how recreational fisheries management is undertaken. We use a combination of structured reviews and expert analyses combined with descriptive case studies to highlight the many ways that technology is influencing recreational fishing practice, and, relatedly, what it means for changing how fisheries and/or these technologies need to be managed-from changes in fish capture, to fish handling, to how anglers share information with each other and with managers. Given that technology is continually evolving, we hope that the examples provided here lead to more and better monitoring of technological innovations and engagement by the management and policy authorities with the recreational fishing sector. Doing so will ensure that management actions related to emerging and evolving recreational fishing technology are more proactive than reactive.

Assessing conflicts between winter recreational activities and grouse species

Mountain environments provide habitats for many wild animal species and are of great importance to recreational activities. In the European Alps, winter recreation activities such as ski mountaineering are becoming increasingly popular, which may lead more often to disturbance of Alpine wildlife. Assessment of ski mountaineering activities and related potential conflict zones is needed to implement protection measures and to guide skiers towards nature-friendly behaviour in sensitive locations. Yet basic data regarding frequencies of ski mountaineers is still missing at regional scale. For the Region of the Tyrol (Austria), this study therefore aimed to advance methods of assessing ski mountaineering activities for use in the spatial analysis of conflict zones with grouse species. We overlaid high-resolution information on the spatial and temporal distribution of ski mountaineers from crowd-sourced data (Strava) with distribution maps of capercaillie (Tetrao urogallus L.) and black grouse (Tetrao tetrix L.). Our results indicate that ski mountaineering activities affected 10.3% of the distribution area of black grouse and 8.6% of the distribution area of capercaillie. The raw crowd-sourced data was pre-processed with local information on skiing resorts, cross-country trails and infrastructure and use of the tested method was validated, with good spatial resolution (0.076 km² per minimum mapping unit) for large study areas. We identified four intensity classes of ski mountaineering activity, which were randomly distributed in the study area. The spatial distribution of ski mountaineering activities showed an accumulation of activities in the south of the Inn valley. Our results could provide a valuable basis for developing mitigation measures and strategies in order to reduce the disturbance of Alpine wildlife by ski mountaineering.

Eye-Level Street Greenery and Walking Behaviors of Older Adults

Evidence suggests that built environment characteristics affect older adults' travel activity behaviors, e.g., walking and cycling, which have well-established health benefits. However, the relationship between urban greenery and walking behaviors remains unclear, partly due to methodological limitation. Previous studies often measured urban greenery from a bird's eye perspective, which may mismatch with the pedestrian's perception from the street. In this study, we measured greenery view index from eye-level streetscape photos retrieved from Baidu Street View, an online mapping service provider. Walking behaviors of 180 older adults in six neighborhoods were collected from questionnaires. We also measured land use diversity, pedestrian-oriented design (street connectivity), and population density-the three Ds of the built environment. Results show that street greenery view index contributes to walking time of older adults, suggesting street greenery should be taken into design consideration to promote walking behaviors of older adults.

Social media captures demographic and regional physical activity

Objectives

We examined the use of data from social media for surveillance of physical activity prevalence in the USA.

Methods

We obtained data from the social media site Twitter from April 2015 to March 2016. The data consisted of 1 382 284 geotagged physical activity tweets from 481 146 users (55.7% men and 44.3% women) in more than 2900 counties. We applied machine learning and statistical modelling to demonstrate sex and regional variations in preferred exercises, and assessed the association between reports of physical activity on Twitter and population-level inactivity prevalence from the US Centers for Disease Control and Prevention.

Results

The association between physical inactivity tweet patterns and physical activity prevalence varied by sex and region. Walking was the most popular physical activity for both men and women across all regions (15.94% (95% CI 15.85% to 16.02%) and 18.74% (95% CI 18.64% to 18.88%) of tweets, respectively). Men and women mentioned performing gym-based activities at approximately the same rates (4.68% (95% CI 4.63% to 4.72%) and 4.13% (95% CI 4.08% to 4.18%) of tweets, respectively). CrossFit was most popular among men (14.91% (95% CI 14.52% to 15.31%)) among gym-based tweets, whereas yoga was most popular among women (26.66% (95% CI 26.03% to 27.19%)). Men mentioned engaging in higher intensity activities than women. Overall, counties with higher physical activity tweets also had lower leisure-time physical inactivity prevalence for both sexes.

Conclusions

The regional-specific and sex-specific activity patterns captured on Twitter may allow public health officials to identify changes in health behaviours at small geographical scales and to design interventions best suited for specific populations.

Mapping with Stakeholders: An Overview of Public Participatory GIS and VGI in Transport Decision-Making

Transport decision-making problems are typically spatially based and involve a set of feasible alternatives with multiple evaluation criteria. Besides, transport decisions affect citizens’ quality of life, as well as specific interests of general stakeholders (e.g., transport companies), thus needing a participatory approach to decision-making. Geographic Information Systems (GIS) have the ability to visualize spatial data and represent the impact of location based transport alternatives, thus helping experts to conduct robust assessments. Moreover, with the recent diffusion of Volunteered Geographic Information (VGI) and development of Public Participatory GIS (PPGIS) platforms, the process can be enhanced thanks to the collection of a large amount of updated spatial data and the achievement of an active community participation. In this study, we provide an overview based on a structured literature review of the use of VGI and PPGIS in transport studies, exploring the fields of application, role played by GIS, level of public involvement and decision stage at which they are applied. From the overview’s results, we propose a general framework for the evaluation of transport alternatives using GIS from a multiple stakeholder point of view; the main conclusion is the usefulness of the integration between Public Participation, GIS and quantitative evaluation methods, in particular Multi Criteria Decision Analysis, in order to foster technically sound and shared decisions.

Understanding Potential Exposure of Bicyclists on Roadways to Traffic-Related Air Pollution: Findings from El Paso, Texas, Using Strava Metro Data

As bicycling on roadways can cause adverse health effects, there is an urgent need to understand how bicycle routes expose bicyclists to traffic emissions. Limited resources for monitoring reveal that bicycle travel patterns may constrain such understanding at the network level. This study examined the potential exposure of bicyclists to traffic-related air pollution in El Paso, Texas, using Strava Metro data that revealed bicycle patterns across the city networks. An initial spatial mapping analysis was conducted to explore the spatial patterns of bicycling and traffic pollutant emission, followed by exploratory descriptive statistics. A spatial bicycle model was then developed to explore factors influencing bicycling activity in El Paso. Analysis results indicated significant associations between greater bicycle volume and both higher levels of particulate matter (PM2.5) emissions and more frequent bus services, implying adverse health concerns related to traffic-related air pollution. The results also indicated significant effects of various environmental characteristics (e.g., roadway, bicycle infrastructure, topography, and demographics) on bicycling. The findings encourage extending this study to provide guidance to bicyclists whose regular trips take place on heavily trafficked roads and during rush hours in this region and to evaluate the net health impacts of on-road bicycling for the general population.

How has big data contributed to obesity research? A review of the literature

There has been growing interest in the potential of ‘big data’ to enhance our understanding in medicine and public health. Although there is no agreed definition of big data, accepted critical components include greater volume, complexity, coverage and speed of availability. Much of these data are ‘found’ (as opposed to ‘made’), in that they have been collected for non-research purposes, but could include valuable information for research. The aim of this paper is to review the contribution of ‘found’ data to obesity research to date, and describe the benefits and challenges encountered. A narrative review was conducted to identify and collate peer-reviewed research studies. Database searches conducted up to September 2017 found original studies using a variety of data types and sources. These included: retail sales, transport, geospatial, commercial weight management data, social media, and smartphones and wearable technologies. The narrative review highlights the variety of data uses in the literature: describing the built environment, exploring social networks, estimating nutrient purchases or assessing the impact of interventions. The examples demonstrate four significant ways in which ‘found’ data can complement conventional ‘made’ data: firstly, in moving beyond constraints in scope (coverage, size and temporality); secondly, in providing objective, quantitative measures; thirdly, in reaching hard-to-access population groups; and lastly in the potential for evaluating real-world interventions. Alongside these opportunities, ‘found’ data come with distinct challenges, such as: ethical and legal questions around access and ownership; commercial sensitivities; costs; lack of control over data acquisition; validity; representativeness; finding appropriate comparators; and complexities of data processing, management and linkage. Despite widespread recognition of the opportunities, the impact of ‘found’ data on academic obesity research has been limited. The merit of such data lies not in their novelty, but in the benefits they could add over and above, or in combination with, conventionally collected data.