Use of emerging technologies to assess differences in outdoor physical activity in st. Louis, missouri

Assessing the Impact of a New Urban Greenway Using Mobile, Wearable Technology-Elicited Walk- and Bike-Along Interviews

Physical inactivity is the fourth leading risk factor for global mortality, causing an estimated 3.3 million deaths worldwide. Characteristics of the built environment, including buildings, public spaces, pedestrian and cycling infrastructure, transportation networks, parks, trails and green spaces can facilitate or constrain physical activity. However, objective study of built environment interventions on physical activity remains challenging due to methodological limitations and research gaps. Existing methods such as direct observations or surveys are time and labour intensive, and only provide a static, cross-sectional view of physical activity at a specific point in time. The aim of this study was to develop a novel method for objectively and inexpensively assessing how built environment changes may influence physical activity. We used a novel, unobtrusive method to capture real-time, in situ data from a convenience sample of 25 adults along a newly constructed urban greenway in an area of high deprivation in Belfast, UK. Walk/bike-along interviews were conducted with participants using a body-worn or bicycle-mounted portable digital video camera (GoPro HERO 3+ camera) to record their self-determined journeys along the greenway. This is the first study to demonstrate the feasibility of using wearable sensors to capture participants’ responses to the built environment in real-time during their walking and cycling journeys. These findings contribute to our understanding of the impact of real-world environmental interventions on physical activity and the importance of precise, accurate and objective measurements of environments where the activity occurs.

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.

Perceptions of Important Characteristics of Physical Activity Facilities: Implications for Engagement in Walking, Moderate and Vigorous Physical Activity

Background

Although few United States adults meet physical activity recommendations, those that do are more likely to access to physical activity facilities. Additionally, vigorous exercisers may be more likely to utilize a nearby physical activity facility, while light-to-moderate exercisers are less likely to do so. However, it is unclear what characteristics of those facilities are most important as well as how those characteristics are related to activity intensity.

Purpose

This study examined relationships between self-reported leisure-time physical activities and the use of and perceived characteristics of physical activity facilities.

Methods

Data were from a cross-sectional study in a major metropolitan area. Participants (N = 582; ages 18–74, mean age = 45 ± 14.7 years) were more likely to be female (69.9%), Caucasian (65.6%), married (51.7%), and have some college education (72.8%). Household surveys queried leisure-time physical activity, regular physical activity facility use, and importance ratings for key facility characteristics.

Results

Leisure-time physical activity recommendations were met by 41.0% of participants and 50.9% regularly used a physical activity facility. Regular facility use was positively associated with meeting walking (p = 0.036), moderate (p < 0.001), and vigorous (p < 0.001) recommendations. Vigorous exercisers were more likely to use a gym/fitness center (p = 0.006) and to place higher importance on facility quality (p = 0.022), variety of physical activity options offered (p = 0.003), and availability of special equipment and resources (p = 0.01). The facility characteristics of low or free cost (p = 0.02) and offering childcare (p = 0.028) were barriers for walking, and being where friends and family like to go were barriers for moderate leisure-time physical activity (p = 0.013).

Conclusion

Findings offer insights for structuring interventions using the social ecological model as well as for improving existing physical activity facilities.

Urban Green Space Perception and Its Contribution to Well-Being

Individual perceptions are essential when evaluating the well-being benefits from urban green spaces. This study predicted the influence of perceived green space characteristics in the city of Szeged, Hungary, on two well-being variables: the green space visitors’ level of satisfaction and the self-reported quality of life. The applied logistic regression analysis used nine predictors: seven perceived green space characteristics from a questionnaire survey among visitors of five urban green spaces of Szeged; and the frequency of green space visitors’ crowd-sourced recreational running paths and photographs picturing green space aesthetics. Results revealed that perceived green space characteristics with direct well-being benefits were strong predictors of both dependent variables. Perceived green space characteristics with indirect, yet fundamental, well-being benefits, namely, regulating ecosystem services had minor influence on the dependent variables. The crowd-sourced geo-tagged data predicted only the perceived quality of life contributions; but revealed spatial patterns of recreational green space use and aesthetics. This study recommends that regulating ecosystem services should be planned with a focus on residents’ aesthetic and recreational needs. Further research on the combination of green space visitors´ perceptions and crowd-sourced geo-tagged data is suggested to promote planning for well-being and health benefits of urban green spaces.

Quantifying the Modern City: Emerging Technologies and Big Data for Active Living Research

Opportunities and infrastructure for active living are an important aspect of a community's design, livability, and health. Features of the built environment influence active living and population levels of physical activity, but objective study of the built environment influence on active living behaviors is challenging. The use of emerging technologies for active living research affords new and promising means to obtain objective data on physical activity behaviors and improve the precision and accuracy of measurements. This is significant for physical activity promotion because precise measurements can enable detailed examinations of where, when, and how physical activity behaviors actually occur, thus enabling more effective targeting of particular behavior settings and environments. The aim of this focused review is to provide an overview of trends in emerging technologies that can profoundly change our ability to understand environmental determinants of active living. It discusses novel technological approaches and big data applications to measure and track human behaviors that may have broad applications across the fields of urban planning, public health, and spatial epidemiology.

Lifestyle chemistries from phones for individual profiling

Imagine a scenario where personal belongings such as pens, keys, phones, or handbags are found at an investigative site. It is often valuable to the investigative team that is trying to trace back the belongings to an individual to understand their personal habits, even when DNA evidence is also available. Here, we develop an approach to translate chemistries recovered from personal objects such as phones into a lifestyle sketch of the owner, using mass spectrometry and informatics approaches. Our results show that phones' chemistries reflect a personalized lifestyle profile. The collective repertoire of molecules found on these objects provides a sketch of the lifestyle of an individual by highlighting the type of hygiene/beauty products the person uses, diet, medical status, and even the location where this person may have been. These findings introduce an additional form of trace evidence from skin-associated lifestyle chemicals found on personal belongings. Such information could help a criminal investigator narrowing down the owner of an object found at a crime scene, such as a suspect or missing person.

"Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward.

Adaptation and Evaluation of the Neighborhood Environment Walkability Scale in India (NEWS-India)

Physical inactivity is the fourth leading risk factor for global mortality, with most of these deaths occurring in low and middle-income countries (LMICs) like India. Research from developed countries has consistently demonstrated associations between built environment features and physical activity levels of populations. The development of culturally sensitive and reliable measures of the built environment is a necessary first step for accurate analysis of environmental correlates of physical activity in LMICs. This study systematically adapted the Neighborhood Environment Walkability Scale (NEWS) for India and evaluated aspects of test-retest reliability of the adapted version among Indian adults. Cultural adaptation of the NEWS was conducted by Indian and international experts. Semi-structured interviews were conducted with local residents and key informants in the city of Chennai, India. At baseline, participants (N = 370; female = 47.2%) from Chennai completed the adapted NEWS-India surveys on perceived residential density, land use mix-diversity, land use mix-access, street connectivity, infrastructure and safety for walking and cycling, aesthetics, traffic safety, and safety from crime. NEWS-India was administered for a second time to consenting participants (N = 62; female = 53.2%) with a gap of 2-3 weeks between successive administrations. Qualitative findings demonstrated that built environment barriers and constraints to active commuting and physical activity behaviors intersected with social ecological systems. The adapted NEWS subscales had moderate to high test-retest reliability (ICC range 0.48-0.99). The NEWS-India demonstrated acceptable measurement properties among Indian adults and may be a useful tool for evaluation of built environment attributes in India. Further adaptation and evaluation in rural and suburban settings in India is essential to create a version that could be used throughout India.

Dysbiotic drift: mental health, environmental grey space, and microbiota

Advances in research concerning the mental health implications of dietary patterns and select nutrients have been remarkable. At the same time, there have been rapid increases in the understanding of the ways in which non-pathogenic microbes can potentially influence many aspects of human health, including those in the mental realm. Discussions of nutrition and microbiota are often overlapping. A separate, yet equally connected, avenue of research is that related to natural (for example, green space) and built environments, and in particular, how they are connected to human cognition and behaviors. It is argued here that in Western industrial nations a ‘disparity of microbiota’ might be expected among the socioeconomically disadvantaged, those whom face more profound environmental forces. Many of the environmental forces pushing against the vulnerable are at the neighborhood level. Matching the developing microbiome research with existing environmental justice research suggests that grey space may promote dysbiosis by default. In addition, the influence of Westernized lifestyle patterns, and the marketing forces that drive unhealthy behaviors in deprived communities, might allow dysbiosis to be the norm rather than the exception in those already at high risk of depression, subthreshold (subsyndromal) conditions, and subpar mental health. If microbiota are indeed at the intersection of nutrition, environmental health, and lifestyle medicine (as these avenues pertain to mental health), then perhaps the rapidly evolving gut-brain-microbiota conversation needs to operate through a wider lens. In contrast to the more narrowly defined psychobiotic, the term eco-psychotropic is introduced.