A novel methodology for identifying environmental exposures using GPS data

Aim: While studies using global positioning systems (GPS) have the potential to refine measures of exposure to the neighbourhood environment in health research, one limitation is that they do not typically identify time spent undertaking journeys in motorised vehicles when contact with the environment is reduced. This paper presents and tests a novel methodology to explore the impact of this concern. Methods: Using a case study of exposure assessment to food environments, an unsupervised computational algorithm is employed in order to infer two travel modes: motorised and non-motorised, on the basis of which trips were extracted. Additional criteria are imposed in order to improve robustness of the algorithm. Results: After removing noise in the GPS data and motorised vehicle journeys, 82.43% of the initial GPS points remained. In addition, after comparing a sub-sample of trips classified visually of motorised, non-motorised and mixed mode trips with the algorithm classifications, it was found that there was an agreement of 88%. The measures of exposure to the food environment calculated before and after algorithm classification were strongly correlated. Conclusion: Identifying non-motorised exposures to the food environment makes little difference to exposure estimates in urban children but might be important for adults or rural populations who spend more time in motorised vehicles.APJ was partially supported by the Centre for Diet and Activity Research (CEDAR), a UK Clinical Research Collaboration Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, National Institute for Health Research and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged

Exposure to food environments, diet and weight status in children

There is a growing interest in understanding how the built food environment influences health behaviours. Whilst policy interest in the influence of food environments on diet and body weight is growing, the evidence base is limited, particularly for environments beyond the home neighbourhood. Research in children is of particular importance, as it is known that dietary behaviours and weight tend to track into adulthood. This thesis addresses the gap in knowledge surrounding the influence of exposure to the food environment on weight and diet in children. It also takes into consideration the interactions with socio-economic status. Existing research exploring the environmental influences on diet and weight in children is reviewed, and a conceptual framework of key determinants identified is presented. Three studies are presented which investigate associations between different measures of exposure to the food environment and diet and weight. A systematic review investigating the use of GPS in studies of the food environment is also conducted. Additionally, a novel method for assessing environmental exposure is presented. The results from this research suggest that unhealthy food environments measured at an area level are generally conducive to weight gain and poorer diet, while the opposite is true for healthier food environments. Furthermore, this thesis supports the hypothesis that diet, weight and access to food are patterned by social class, and that the food environment partially mediates the well-known association between socio-economic status and weight status. However, findings were equivocal when using measuring exposure to the food environment at an individual level. This suggests that correctly measuring the characteristics of the food environment is important in order to disentangle their effects on health outcomes, and calls for efforts to attempt to reduce the heterogeneity in measures of the food environment employed

Social and spatial heterogeneity in psychosis proneness in a multilevel case-prodrome-control study

To test whether spatial and social neighbourhood patterning of people at ultra-high risk (UHR) of psychosis differs from first-episode psychosis (FEP) participants or controls and to determine whether exposure to different social environments is evident before disorder onset

Longitudinal cohort of HIV-negative transgender women of colour in New York City: protocol for the TURNNT ('Trying to Understand Relationships, Networks and Neighbourhoods among Transgender women of colour') study.

IntroductionIn the USA, transgender women are among the most vulnerable to HIV. In particular, transgender women of colour face high rates of infection and low uptake of important HIV prevention tools, including pre-exposure prophylaxis (PrEP). This paper describes the design, sampling methods, data collection and analyses of the TURNNT ('Trying to Understand Relationships, Networks and Neighbourhoods among Transgender women of colour') study. In collaboration with communities of transgender women of colour, TURNNT aims to explore the complex social and environmental (ie, neighbourhood) structures that affect HIV prevention and other aspects of health in order to identify avenues for intervention.Methods and analysesTURNNT is a prospective cohort study, which will recruit 300 transgender women of colour (150 Black/African American, 100 Latina and 50 Asian/Pacific Islander participants) in New York City. There will be three waves of data collection separated by 6 months. At each wave, participants will provide information on their relationships, social and sexual networks, and neighbourhoods. Global position system technology will be used to generate individual daily path areas in order to estimate neighbourhood-level exposures. Multivariate analyses will be conducted to assess cross-sectional and longitudinal, independent and synergistic associations of personal relationships (notably individual social capital), social and sexual networks, and neighbourhood factors (notably neighbourhood-level social cohesion) with PrEP uptake and discontinuation.Ethics and disseminationThe TURNNT protocol was approved by the Columbia University Institutional Review Board (reference no. AAAS8164). This study will provide novel insights into the relationship, network and neighbourhood factors that influence HIV prevention behaviours among transgender women of colour and facilitate exploration of this population's health and well-being more broadly. Through community-based dissemination events and consultation with policy makers, this foundational work will be used to guide the development and implementation of future interventions with and for transgender women of colour

A Scalable Field Study Protocol and Rationale for Passive Ambient Air Sampling: A Spatial Phytosampling for Leaf Data Collection

© 2017 American Chemical Society. Stable, bioreactive, radicals known as environmentally persistent free radicals (EPFRs) have been found to exist on the surface of airborne PM2.5. These EPFRs have been found to form during many combustion processes, are present in vehicular exhaust, and persist in the environment for weeks and biological systems for up to 12 h. To measure EPFRs in PM samples, high volume samplers are required and measurements are less representative of community exposure; therefore, we developed a novel spatial phytosampling methodology to study the spatial patterns of EPFR concentrations using plants. Leaf samples for laboratory PM analysis were collected from 188 randomly drawn sampling sites within a 500-m buffer zone of pollution sources across a sampling grid measuring 32.9 × 28.4 km in Memphis, Tennessee. PM was isolated from the intact leaves and size fractionated, and EPFRs on PM quantified by electron paramagnetic resonance spectroscopy. The radical concentration was found to positively correlate with the EPFR g-value, thus indicating cumulative content of oxygen centered radicals in PM with higher EPFR load. Our spatial phytosampling approach reveals spatial variations and potential hotspots risk due to EPFR exposure across Memphis and provides valuable insights for identifying exposure and demographic differences for health studies

Comparing self-identified and census-defined neighborhoods among adolescents using GPS and accelerometer

Background: Numerous definitions of neighborhood exist, yet few studies have considered youth’s perceptions of neighborhood boundaries. This study compared youth-identified neighborhood (YIN) boundaries to census-defined neighborhood (CDN) boundaries, and determined how the amount of time spent and moderate-to-vigorous physical activity (MVPA) levels compared within both boundary types. Methods: Adolescents aged 11–14 years were asked to identify their neighborhood boundaries using a map. Objective location and physical activity data collected using Global Positioning System (GPS) devices and accelerometers were used to calculate the amount of time spent and MVPA within youth-identified and census-defined neighborhood boundaries. Paired bivariate analyses compared mean area (meters squared), percent of total time, daily MVPA (minutes), time density (minutes/m2) and MVPA density (minutes/m2) for both boundary types. Results: Youth-identified neighborhoods (1,821,705 m2) and census-defined neighborhoods (1,277,181 m2) were not significantly different in area, p = 0.30. However, subjects spent more time in youth-identified neighborhoods (80.3%) than census-defined neighborhoods (58.4%), p < 0.0001, and engaged in more daily MVPA within youth-identified neighborhoods (14.7 minutes) than census-defined neighborhoods (9.5 minutes), p < 0.0001. After adjusting for boundary area, MVPA density (minutes of MVPA per squared meter of area) remained significantly greater for youth-identified neighborhoods (2.4 × 10-4 minutes/m2) than census-defined neighborhoods (1.4 × 10-4 minutes/m2), p = 0.02. Conclusions: Adolescents perceive their neighborhoods to be similar in size to census-defined neighborhoods. However, youth-identified neighborhoods better capture the locations in which adolescents spend time and engage in physical activity. Asking adolescents to identify their neighborhood boundaries is a feasible and valuable method for identifying the spaces that adolescents are exposed to and use to be physically active

“Exposure Track”—The Impact of Mobile-Device-Based Mobility Patterns on Quantifying Population Exposure to Air Pollution

Air pollution is now recognized as the world’s single largest environmental and human health threat. Indeed, a large number of environmental epidemiological studies have quantified the health impacts of population exposure to pollution. In previous studies, exposure estimates at the population level have not considered spatially- and temporally varying populations present in study regions. Therefore, in the first study of it is kind, we use measured population activity patterns representing several million people to evaluate population-weighted exposure to air pollution on a city-wide scale. Mobile and wireless devices yield information about where and when people are present, thus collective activity patterns were determined using counts of connections to the cellular network. Population-weighted exposure to PM2.5 in New York City (NYC), herein termed “Active Population Exposure” was evaluated using population activity patterns and spatiotemporal PM2.5 concentration levels, and compared to “Home Population Exposure”, which assumed a static population distribution as per Census data. Areas of relatively higher population-weighted exposures were concentrated in different districts within NYC in both scenarios. These were more centralized for the “Active Population Exposure” scenario. Population-weighted exposure computed in each district of NYC for the “Active” scenario were found to be statistically significantly (p < 0.05) different to the “Home” scenario for most districts. In investigating the temporal variability of the “Active” population-weighted exposures determined in districts, these were found to be significantly different (p < 0.05) during the daytime and the nighttime. Evaluating population exposure to air pollution using spatiotemporal population mobility patterns warrants consideration in future environmental epidemiological studies linking air quality and human health

How can GPS technology help us better understand exposure to the food environment? A systematic review.

PURPOSE: Global Positioning Systems (GPS) are increasingly being used to objectively assess movement patterns of people related to health behaviours. However research detailing their application to the food environment is scarce. This systematic review examines the application of GPS in studies of exposure to food environments and their potential influences on health. METHODS: Based on an initial scoping exercise, published articles to be included in the systematic review were identified from four electronic databases and reference lists and were appraised and analysed, the final cut-off date for inclusion being January 2015. Included studies used GPS to identify location of individuals in relation to food outlets and link that to health or diet outcomes. They were appraised against a set of quality criteria. RESULTS: Six studies met the inclusion criteria, which were appraised to be of moderate quality. Newer studies had a higher quality score. Associations between observed mobility patterns in the food environment and diet related outcomes were equivocal. Findings agreed that traditional food exposure measures overestimate the importance of the home food environment. CONCLUSIONS: The use of GPS to measure exposure to the food environment is still in its infancy yet holds much potential. There are considerable variations and challenges in developing and standardising the methods used to assess exposure.AC was funded by the Lord Zuckerman PhD scholarship. APJ was partially supported by the Centre for Diet and Activity Research, a UK Clinical Research Collaboration Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Department of Health, Economic and Social Research Council, Medical Research Council, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ssmph.2016.04.00