E-Mail Alert

Add your e-mail address to receive forthcoming issues of this journal:

Journal Browser

Journal Browser

Special Issue "Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Health".

Deadline for manuscript submissions: closed (30 November 2018)

Special Issue Editor

Guest Editor
Prof. Dr. Mei-Po Kwan

Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Website | E-Mail
Interests: environmental health; human mobility; sustainable cities; GIScience; ICT

Special Issue Information

Dear Colleagues,

Environmental health researchers have long recognized the importance of geographic context for understanding the effects of different environmental factors on human health. While geographic context and neighborhood effects are fundamental constructs for assessing people’s exposure to contextual or environmental influences, they still tend to be conceptualized largely in static spatial terms, which ignores that people move around in their daily lives and come under the influence of many different neighborhood contexts outside their residential neighborhoods. Past studies also tend to ignore the role of human mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) in various health issues. They tend to ignore the temporality of exposures that shapes people’s exposure to environmental influences and subjective wellbeing such as the duration, frequency, and recency of exposure, as well as residential history and cumulative exposure over the life-course.

Recent studies, however, have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have also emerged. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of various forms of human mobility, non-residential contexts, and the temporality of exposures on human health behaviors and outcomes. Studies that illustrate the use of these new methods and data to address questions concerning a wide range of health behaviors and outcomes are welcome. These include but are not limited to individual exposure to air pollution, access to green/blue spaces and subjective wellbeing, environmental influences on physical activity, food environmental and diet behavior, psychosocial stress and drug use behavior, socio-environmental factors that affect sleep patterns and sleep hygiene, risk factors that influence mental health and suicide mortality, exposure to noise and stress, and broader social issues such as environmental justice, health disparities, and racial/ethnic segregation.

Prof. Dr. Mei-Po Kwan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

1. If you are a potential author of this Special Issue; or 2. If you are interested in this Special Issue, but cannot submit a paper at this time; We encourage you to join our reviewer database at: https://susy.mdpi.com/volunteer_reviewer/step/1 When you help to review other manuscripts in this Special Issue, you will be offered a voucher reduction from the APC for each valid review, which can be used immediately for your current submission, or for your future submissions to any MDPI journal.

Keywords

  • human mobility
  • environmental exposures
  • geographic context
  • temporality of context
  • neighborhood effects
  • the uncertain geographic context problem
  • the modifiable areal and/or temporal unit problem
  • life-course perspectives
  • GPS data
  • accelerometer data

Published Papers (20 papers)

View options order results:
result details:
Displaying articles 1-20
Export citation of selected articles as:

Research

Open AccessArticle Roles of Different Transport Modes in the Spatial Spread of the 2009 Influenza A(H1N1) Pandemic in Mainland China
Int. J. Environ. Res. Public Health 2019, 16(2), 222; https://doi.org/10.3390/ijerph16020222
Received: 29 November 2018 / Revised: 4 January 2019 / Accepted: 9 January 2019 / Published: 14 January 2019
PDF Full-text (4750 KB) | HTML Full-text | XML Full-text
Abstract
There is increasing concern about another influenza pandemic in China. However, the understanding of the roles of transport modes in the 2009 influenza A(H1N1) pandemic spread across mainland China is limited. Herein, we collected 127,797 laboratory-confirmed cases of influenza A(H1N1)pdm09 in mainland China
[...] Read more.
There is increasing concern about another influenza pandemic in China. However, the understanding of the roles of transport modes in the 2009 influenza A(H1N1) pandemic spread across mainland China is limited. Herein, we collected 127,797 laboratory-confirmed cases of influenza A(H1N1)pdm09 in mainland China from May 2009 to April 2010. Arrival days and peak days were calculated for all 340 prefectures to characterize the dissemination patterns of the pandemic. We first evaluated the effects of airports and railway stations on arrival days and peak days, and then we applied quantile regressions to quantify the relationships between arrival days and air, rail, and road travel. Our results showed that early arrival of the virus was not associated with an early incidence peak. Airports and railway stations in prefectures significantly advanced arrival days but had no significant impact on peak days. The pandemic spread across mainland China from the southeast to the northwest in two phases that were split at approximately 1 August 2009. Both air and road travel played a significant role in accelerating the spread during phases I and II, but rail travel was only significant during phase II. In conclusion, in addition to air and road travel, rail travel also played a significant role in accelerating influenza A(H1N1)pdm09 spread between prefectures. Establishing a multiscale mobility network that considers the competitive advantage of rail travel for mid to long distances is essential for understanding the influenza pandemic transmission in China. Full article
Figures

Figure 1

Open AccessArticle Spatial Accessibility to Primary Healthcare Services by Multimodal Means of Travel: Synthesis and Case Study in the City of Calgary
Int. J. Environ. Res. Public Health 2019, 16(2), 170; https://doi.org/10.3390/ijerph16020170
Received: 28 November 2018 / Revised: 25 December 2018 / Accepted: 3 January 2019 / Published: 9 January 2019
PDF Full-text (7449 KB) | HTML Full-text | XML Full-text
Abstract
Universal access to primary healthcare facilities is a driving goal of healthcare organizations. Despite Canada’s universal access to primary healthcare status, spatial accessibility to healthcare facilities is still an issue of concern due to the non-uniform distribution of primary healthcare facilities and population
[...] Read more.
Universal access to primary healthcare facilities is a driving goal of healthcare organizations. Despite Canada’s universal access to primary healthcare status, spatial accessibility to healthcare facilities is still an issue of concern due to the non-uniform distribution of primary healthcare facilities and population over space—leading to spatial inequity in the healthcare sector. Spatial inequity is further magnified when health-related accessibility studies are analyzed on the assumption of universal car access. To overcome car-centric studies of healthcare access, this study compares different travel modes—driving, public transit, and walking—to simulate the multi-modal access to primary healthcare services in the City of Calgary, Canada. Improving on floating catchment area methods, spatial accessibility was calculated based on the Spatial Access Ratio method, which takes into consideration the provider-to-population status of the region. The analysis revealed that, in the City of Calgary, spatial accessibility to the primary healthcare services is the highest for the people with an access to a car, and is significantly lower with multimodal (bus transit and train) means despite being a large urban centre. The social inequity issue raised from this analysis can be resolved by improving the city’s pedestrian infrastructure, public transportation, and construction of new clinics in regions of low accessibility. Full article
Figures

Figure 1

Open AccessArticle Environmental, Individual and Personal Goal Influences on Older Adults’ Walking in the Helsinki Metropolitan Area
Int. J. Environ. Res. Public Health 2019, 16(1), 58; https://doi.org/10.3390/ijerph16010058
Received: 13 November 2018 / Revised: 20 December 2018 / Accepted: 21 December 2018 / Published: 26 December 2018
PDF Full-text (1814 KB) | HTML Full-text | XML Full-text
Abstract
Physical activity is a fundamental factor in healthy ageing, and the built environment has been linked to individual health outcomes. Understanding the linkages between older adult’s walking and the built environment are key to designing supportive environments for active ageing. However, the variety
[...] Read more.
Physical activity is a fundamental factor in healthy ageing, and the built environment has been linked to individual health outcomes. Understanding the linkages between older adult’s walking and the built environment are key to designing supportive environments for active ageing. However, the variety of different spatial scales of human mobility has been largely overlooked in the environmental health research. This study used an online participatory mapping method and a novel modelling of individual activity spaces to study the associations between both the environmental and the individual features and older adults’ walking in the environments where older adult’s actually move around. Study participants (n = 844) aged 55+ who live in Helsinki Metropolitan Area, Finland reported their everyday errand points on a map and indicated which transport mode they used and how frequently they accessed the places. Respondents walking trips were drawn from the data and the direct and indirect effects of the personal, psychological as well as environmental features on older adults walking were examined. Respondents marked on average, six everyday errand points and walked for transport an average of 20 km per month. Residential density and the density of walkways, public transit stops, intersections and recreational sports places were significantly and positively associated with older adult’s walking for transport. Transit stop density was found having the largest direct effect to older adults walking. Built environment had an independent effect on older adults walking regardless of individual demographic or psychological features. Education and personal goals related to physical activities had a direct positive, and income a direct negative, effect on walking. Gender and perceived health had an indirect effect on walking, which was realized through individuals’ physical activity goals. Full article
Figures

Figure 1

Open AccessFeature PaperArticle Geographic Imputation of Missing Activity Space Data from Ecological Momentary Assessment (EMA) GPS Positions
Int. J. Environ. Res. Public Health 2018, 15(12), 2740; https://doi.org/10.3390/ijerph15122740
Received: 25 October 2018 / Revised: 28 November 2018 / Accepted: 30 November 2018 / Published: 4 December 2018
PDF Full-text (3268 KB) | HTML Full-text | XML Full-text
Abstract
This research presents a pilot study to develop and compare methods of geographic imputation for estimating the location of missing activity space data collected using geographic ecological momentary assessment (GEMA). As a demonstration, we use data from a previously published analysis of the
[...] Read more.
This research presents a pilot study to develop and compare methods of geographic imputation for estimating the location of missing activity space data collected using geographic ecological momentary assessment (GEMA). As a demonstration, we use data from a previously published analysis of the effect of neighborhood disadvantage, captured at the U.S. Census Bureau tract level, on momentary psychological stress among a sample of 137 urban adolescents. We investigate the impact of listwise deletion on model results and test two geographic imputation techniques adapted for activity space data from hot deck and centroid imputation approaches. Our results indicate that listwise deletion can bias estimates of place effects on health, and that these impacts are mitigated by the use of geographic imputation, particularly regarding inflation of the standard errors. These geographic imputation techniques may be extended in future research by incorporating approaches from the non-spatial imputation literature as well as from conventional geographic imputation and spatial interpolation research that focus on non-activity space data. Full article
Figures

Figure 1

Open AccessArticle Perceived Environmental, Individual and Social Factors of Long-Distance Collective Walking in Cities
Int. J. Environ. Res. Public Health 2018, 15(11), 2458; https://doi.org/10.3390/ijerph15112458
Received: 11 September 2018 / Revised: 31 October 2018 / Accepted: 1 November 2018 / Published: 4 November 2018
PDF Full-text (1937 KB) | HTML Full-text | XML Full-text
Abstract
Long-distance collective walking is a popular activity in cities across China. However, related research is limited, creating a research gap to explore participants’ dynamic experience and related influential factors. Therapeutic mobilities theory explores the relationships among walking, health, and well-being from a qualitative
[...] Read more.
Long-distance collective walking is a popular activity in cities across China. However, related research is limited, creating a research gap to explore participants’ dynamic experience and related influential factors. Therapeutic mobilities theory explores the relationships among walking, health, and well-being from a qualitative perspective. Based on therapeutic mobilities theory, following a systematic process, this study develops a scale to quantitatively estimate the perceived environmental, personal, and social factors that may influence health and well-being. By applying construal level theory, this paper further hypothesizes that personality traits and familiarity moderate environmental, personal, and social perceptions. Data were collected with a paper survey (n = 926) from the “Shenzhen 100 km Walking” event. The findings highlight that long-distance collective walkers have comparatively greater experiences of health and well-being in three aspects: positive social interaction, individual development, and environmental understanding. Personality traits, familiarity, and gender moderate this well-being experience. Theoretical and managerial implications are discussed. Full article
Figures

Figure 1

Open AccessArticle An Improved Healthcare Accessibility Measure Considering the Temporal Dimension and Population Demand of Different Ages
Int. J. Environ. Res. Public Health 2018, 15(11), 2421; https://doi.org/10.3390/ijerph15112421
Received: 10 September 2018 / Revised: 25 October 2018 / Accepted: 29 October 2018 / Published: 31 October 2018
Cited by 1 | PDF Full-text (10652 KB) | HTML Full-text | XML Full-text
Abstract
Healthcare accessibility has become an issue of social equity. An accurate estimation of existing healthcare accessibility is vital to plan and allocate health resources. Healthcare capacity, population demand, and geographic impedance are three essential factors to measure spatial accessibility. Additionally, geographic impedance is
[...] Read more.
Healthcare accessibility has become an issue of social equity. An accurate estimation of existing healthcare accessibility is vital to plan and allocate health resources. Healthcare capacity, population demand, and geographic impedance are three essential factors to measure spatial accessibility. Additionally, geographic impedance is usually represented with a function of travel time. In this paper, the three-step floating catchment area (3SFCA) method is improved from the perspectives of the temporal dimension and population demand. Specifically, the travel time from the population location to the service site is precisely calculated by introducing real-time traffic conditions instead of utilizing empirical speed in previous studies. Additionally, with the utilization of real-time traffic, a dynamic result of healthcare accessibility is derived during different time periods. In addition, since the medical needs of the elderly are higher than that of the young, a demand weight index of demand is introduced to adjust the population demand. A case study of healthcare accessibility in Wuhan shows that the proposed method is effective to measure healthcare accessibility during different time periods. The spatial accessibility disparities of communities and crowdedness of hospitals are identified as an important reference for the balance between the supply and demand of medical resources. Full article
Figures

Figure 1

Open AccessArticle Impacts of Individual Daily Greenspace Exposure on Health Based on Individual Activity Space and Structural Equation Modeling
Int. J. Environ. Res. Public Health 2018, 15(10), 2323; https://doi.org/10.3390/ijerph15102323
Received: 30 September 2018 / Revised: 12 October 2018 / Accepted: 16 October 2018 / Published: 22 October 2018
PDF Full-text (1351 KB) | HTML Full-text | XML Full-text
Abstract
Previous studies on the effects of greenspace exposure on health are largely based on static contextual units, such as residential neighborhoods, and other administrative units. They tend to ignore the spatiotemporal dynamics of individual daily greenspace exposure and the mediating effects of specific
[...] Read more.
Previous studies on the effects of greenspace exposure on health are largely based on static contextual units, such as residential neighborhoods, and other administrative units. They tend to ignore the spatiotemporal dynamics of individual daily greenspace exposure and the mediating effects of specific activity type (such as physical activity). Therefore, this study examines individual daily greenspace exposure while taking into account people’s daily mobility and the mediating role of physical activity between greenspace exposure and health. Specifically, using survey data collected in Guangzhou, China, and high-resolution remote sensing images, individual activity space for a weekday is delineated and used to measure participants’ daily greenspace exposure. Structural equation modeling is then applied to analyze the direct effects of individual daily greenspace exposure on health and its indirect effects through the mediating variable of physical activity. The results show that daily greenspace exposure directly influences individual health and also indirectly affects participants’ health status through physical activity. With respect to the total effects, daily greenspace exposure helps improve participants’ mental health and contributes to promoting their social health. It also helps improve participants’ physical health, although to a lesser extent. In general, the higher the daily greenspace exposure, the higher the physical activity level and the better the overall health (including physical, mental, and social health). Full article
Figures

Figure 1

Open AccessArticle Evaluating the Accessibility of Healthcare Facilities Using an Integrated Catchment Area Approach
Int. J. Environ. Res. Public Health 2018, 15(9), 2051; https://doi.org/10.3390/ijerph15092051
Received: 23 July 2018 / Revised: 15 September 2018 / Accepted: 16 September 2018 / Published: 19 September 2018
Cited by 1 | PDF Full-text (7121 KB) | HTML Full-text | XML Full-text
Abstract
Accessibility is a major method for evaluating the distribution of service facilities and identifying areas in shortage of service. Traditional accessibility methods, however, are largely model-based and do not consider the actual utilization of services, which may lead to results that are different
[...] Read more.
Accessibility is a major method for evaluating the distribution of service facilities and identifying areas in shortage of service. Traditional accessibility methods, however, are largely model-based and do not consider the actual utilization of services, which may lead to results that are different from those obtained when people’s actual behaviors are taken into account. Based on taxi GPS trajectory data, this paper proposed a novel integrated catchment area (ICA) that integrates actual human travel behavior to evaluate the accessibility to healthcare facilities in Shenzhen, China, using the enhanced two-step floating catchment area (E2SFCA) method. This method is called the E2SFCA-ICA method. First, access probability is proposed to depict the probability of visiting a healthcare facility. Then, integrated access probability (IAP), which integrates model-based access probability (MAP) and data-based access probability (DAP), is presented. Under the constraint of IAP, ICA is generated and divided into distinct subzones. Finally, the ICA and subzones are incorporated into the E2SFCA method to evaluate the accessibility of the top-tier hospitals in Shenzhen, China. The results show that the ICA not only reduces the differences between model-based catchment areas and data-based catchment areas, but also distinguishes the core catchment area, stable catchment area, uncertain catchment area and remote catchment area of healthcare facilities. The study also found that the accessibility of Shenzhen’s top-tier hospitals obtained with traditional catchment areas tends to be overestimated and more unequally distributed in space when compared to the accessibility obtained with integrated catchment areas. Full article
Figures

Figure 1

Open AccessArticle An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposures and Body Weight
Int. J. Environ. Res. Public Health 2018, 15(9), 2022; https://doi.org/10.3390/ijerph15092022
Received: 31 August 2018 / Revised: 11 September 2018 / Accepted: 13 September 2018 / Published: 15 September 2018
Cited by 1 | PDF Full-text (4510 KB) | HTML Full-text | XML Full-text
Abstract
In past studies, individual environmental exposures were largely measured in a static manner. In this study, we develop and implement an analytical framework that dynamically represents environmental context (the environmental context cube) and effectively integrates individual daily movement (individual space-time tunnel) for accurately
[...] Read more.
In past studies, individual environmental exposures were largely measured in a static manner. In this study, we develop and implement an analytical framework that dynamically represents environmental context (the environmental context cube) and effectively integrates individual daily movement (individual space-time tunnel) for accurately deriving individual environmental exposures (the environmental context exposure index). The framework is applied to examine the relationship between food environment exposures and the overweight status of 46 participants using data collected with global positioning systems (GPS) in Columbus, Ohio, and binary logistic regression models. The results indicate that the proposed framework generates more reliable measurements of individual food environment exposures when compared to other widely used methods. Taking into account the complex spatial and temporal dynamics of individual environmental exposures, the proposed framework also helps to mitigate the uncertain geographic context problem (UGCoP). It can be used in other environmental health studies concerning environmental influences on a wide range of health behaviors and outcomes. Full article
Figures

Figure 1

Open AccessArticle Geographical Accessibility of Community Health Assist Scheme General Practitioners for the Elderly Population in Singapore: A Case Study on the Elderly Living in Housing Development Board Flats
Int. J. Environ. Res. Public Health 2018, 15(9), 1988; https://doi.org/10.3390/ijerph15091988
Received: 9 August 2018 / Revised: 3 September 2018 / Accepted: 4 September 2018 / Published: 12 September 2018
PDF Full-text (8023 KB) | HTML Full-text | XML Full-text
Abstract
Accessible primary healthcare is important to national healthcare in general and for older persons in particular, in societies where the population is ageing rapidly, as in Singapore. However, although much policy and research efforts have been put into this area, we hardly find
[...] Read more.
Accessible primary healthcare is important to national healthcare in general and for older persons in particular, in societies where the population is ageing rapidly, as in Singapore. However, although much policy and research efforts have been put into this area, we hardly find any spatial perspective to assess the accessibility of these primary healthcare services. This paper analyzes the geographical accessibility of one major healthcare service in Singapore, namely, General Practitioners (GPs) services under the Community Health Assist Scheme (CHAS) for older persons. A Python script was developed to filter the website data of the Housing Development Board (HDB) of Singapore. The data derived was comprehensively analyzed by an Enhanced 2-Step Floating Catchment Area (E2SFCA) method based on a Gaussian distance-decay function and the GIS technique. This enabled the identification of areas with relatively weak geographical accessibility of CHAS-GPs. The findings are discussed along with suggestions for health practitioners, service planners and policy makers. Despite its initial nature, this study has demonstrated the value of innovative approaches in data collection and processing for the elderly-related studies, and contributed to the field of healthcare services optimization and possibly to other human services. Full article
Figures

Figure 1

Open AccessArticle Exploring the Influence of Built Environment on Car Ownership and Use with a Spatial Multilevel Model: A Case Study of Changchun, China
Int. J. Environ. Res. Public Health 2018, 15(9), 1868; https://doi.org/10.3390/ijerph15091868
Received: 22 July 2018 / Revised: 26 August 2018 / Accepted: 27 August 2018 / Published: 29 August 2018
Cited by 1 | PDF Full-text (1801 KB) | HTML Full-text | XML Full-text
Abstract
Although the impacts of built environment on car ownership and use have been extensively studied, limited evidence has been offered for the role of spatial effects in influencing the interaction between built environment and travel behavior. Ignoring the spatial effects may lead to
[...] Read more.
Although the impacts of built environment on car ownership and use have been extensively studied, limited evidence has been offered for the role of spatial effects in influencing the interaction between built environment and travel behavior. Ignoring the spatial effects may lead to misunderstanding the role of the built environment and providing inconsistent transportation policies. In response to this, we try to employ a two-step modeling approach to investigate the impacts of built environment on car ownership and use by combining multilevel Bayesian model and conditional autocorrelation (CAR) model to control for spatial autocorrelation. In the two-step model, the predicting car ownership status in the first-step model is used as a mediating variable in the second-step car use model. Taking Changchun as a case study, this paper identifies the presence of spatial effects in influencing the effects of built environment on car ownership and use. Meanwhile, the direct and cascading effects of built environment on car ownership and use are revealed. The results show that the spatial autocorrelation exists in influencing the interaction between built environment and car dependency. The results suggest that it is necessary for urban planners to pay attention to the spatial effects and make targeted policy according to local land use characteristics. Full article
Figures

Figure 1

Open AccessFeature PaperCommunication The Neighborhood Effect Averaging Problem (NEAP): An Elusive Confounder of the Neighborhood Effect
Int. J. Environ. Res. Public Health 2018, 15(9), 1841; https://doi.org/10.3390/ijerph15091841
Received: 30 July 2018 / Revised: 21 August 2018 / Accepted: 23 August 2018 / Published: 27 August 2018
Cited by 4 | PDF Full-text (244 KB) | HTML Full-text | XML Full-text
Abstract
Ignoring people’s daily mobility and exposures to nonresidential contexts may lead to erroneous results in epidemiological studies of people’s exposures to and the health impact of environmental factors. This paper identifies and describes a phenomenon called neighborhood effect averaging, which may significantly confound
[...] Read more.
Ignoring people’s daily mobility and exposures to nonresidential contexts may lead to erroneous results in epidemiological studies of people’s exposures to and the health impact of environmental factors. This paper identifies and describes a phenomenon called neighborhood effect averaging, which may significantly confound the neighborhood effect as a result of such neglect when examining the health impact of mobility-dependent exposures (e.g., air pollution). Several recent studies that provide strong evidence for the neighborhood effect averaging problem (NEAP) are discussed. The paper concludes that, due to the observed attenuation of the neighborhood effect associated with people’s daily mobility, increasing the mobility of those who live in disadvantaged neighborhoods may be helpful for improving their health outcomes. Full article
Open AccessArticle Understanding the Influence of Crop Residue Burning on PM2.5 and PM10 Concentrations in China from 2013 to 2017 Using MODIS Data
Int. J. Environ. Res. Public Health 2018, 15(7), 1504; https://doi.org/10.3390/ijerph15071504
Received: 5 June 2018 / Revised: 9 July 2018 / Accepted: 14 July 2018 / Published: 17 July 2018
Cited by 1 | PDF Full-text (5488 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, particulate matter (PM) pollution has increasingly affected public life and health. Therefore, crop residue burning, as a significant source of PM pollution in China, should be effectively controlled. This study attempts to understand variations and characteristics of PM10 and
[...] Read more.
In recent years, particulate matter (PM) pollution has increasingly affected public life and health. Therefore, crop residue burning, as a significant source of PM pollution in China, should be effectively controlled. This study attempts to understand variations and characteristics of PM10 and PM2.5 concentrations and discuss correlations between the variation of PM concentrations and crop residue burning using ground observation and Moderate Resolution Imaging Spectroradiometer (MODIS) data. The results revealed that the overall PM concentration in China from 2013 to 2017 was in a downward tendency with regional variations. Correlation analysis demonstrated that the PM10 concentration was more closely related to crop residue burning than the PM2.5 concentration. From a spatial perspective, the strongest correlation between PM concentration and crop residue burning existed in Northeast China (NEC). From a temporal perspective, the strongest correlation usually appeared in autumn for most regions. The total amount of crop residue burning spots in autumn was relatively large, and NEC was the region with the most intense crop residue burning in China. We compared the correlation between PM concentrations and crop residue burning at inter-annual and seasonal scales, and during burning-concentrated periods. We found that correlations between PM concentrations and crop residue burning increased significantly with the narrowing temporal scales and was the strongest during burning-concentrated periods, indicating that intense crop residue burning leads to instant deterioration of PM concentrations. The methodology and findings from this study provide meaningful reference for better understanding the influence of crop residue burning on PM pollution across China. Full article
Figures

Figure 1

Open AccessArticle A Multilevel Analysis of Perceived Noise Pollution, Geographic Contexts and Mental Health in Beijing
Int. J. Environ. Res. Public Health 2018, 15(7), 1479; https://doi.org/10.3390/ijerph15071479
Received: 15 June 2018 / Revised: 7 July 2018 / Accepted: 8 July 2018 / Published: 13 July 2018
Cited by 1 | PDF Full-text (2342 KB) | HTML Full-text | XML Full-text
Abstract
With rapid urbanization and increase in car ownership, ambient noise pollution resulting from diversified sources (e.g., road traffic, railway, commercial services) has become a severe environmental problem in the populated areas in China. However, research on the spatial variation of noise pollution and
[...] Read more.
With rapid urbanization and increase in car ownership, ambient noise pollution resulting from diversified sources (e.g., road traffic, railway, commercial services) has become a severe environmental problem in the populated areas in China. However, research on the spatial variation of noise pollution and its potential effects on urban residents’ mental health has to date been quite scarce in developing countries like China. Using a health survey conducted in Beijing in 2017, we for the first time investigated the spatial distributions of multiple noise pollution perceived by residents in Beijing, including road traffic noise, railway (or subway) noise, commercial noise, and housing renovation (or construction) noise. Our results indicate that there is geographic variability in noise pollution at the neighborhood scale, and road traffic and housing renovation/construction are the principal sources of noise pollution in Beijing. We then employed Bayesian multilevel logistic models to examine the associations between diversified noise pollution and urban residents’ mental health symptoms, including anxiety, stress, fatigue, headache, and sleep disturbance, while controlling for a wide range of confounding factors such as socio-demographics, objective built environment characteristics, social environment and geographic context. The results show that perceived higher noise-pollution exposure is significantly associated with worse mental health, while physical environment variables seem to contribute little to variations in self-reported mental disorders, except for proximity to the main road. Social factors or socio-demographic attributes, such as age and income, are significant covariates of urban residents’ mental health, while the social environment (i.e., community attachment) and housing satisfaction are significantly correlated with anxiety and stress. This study provides empirical evidence on the noise-health relationships in the Chinese context and sheds light on the policy implications for environmental pollution mitigation and healthy city development in China. Full article
Figures

Figure 1

Open AccessArticle An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago
Int. J. Environ. Res. Public Health 2018, 15(4), 703; https://doi.org/10.3390/ijerph15040703
Received: 9 March 2018 / Revised: 1 April 2018 / Accepted: 3 April 2018 / Published: 9 April 2018
Cited by 5 | PDF Full-text (10604 KB) | HTML Full-text | XML Full-text
Abstract
Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an
[...] Read more.
Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an indicator of where and how people have contact with their social and physical environments. Conventionally, standard deviational ellipses, road network buffers, minimum convex polygons, and kernel density surfaces have been used to represent people’s activity space, but they all have shortcomings. Inconsistent findings of the effects of environmental exposures on health behaviors/outcomes suggest that the reliability of existing studies may be affected by the uncertain geographic context problem (UGCoP). This paper proposes the context-based crystal-growth activity space as an innovative method for generating individual activity space based on both GPS trajectories and the environmental context. This method not only considers people’s actual daily activity patterns based on GPS tracks but also takes into account the environmental context which either constrains or encourages people’s daily activity. Using GPS trajectory data collected in Chicago, the results indicate that the proposed new method generates more reasonable activity space when compared to other existing methods. This can help mitigate the UGCoP in environmental health studies. Full article
Figures

Figure 1

Open AccessArticle Real-Time Estimation of Population Exposure to PM2.5 Using Mobile- and Station-Based Big Data
Int. J. Environ. Res. Public Health 2018, 15(4), 573; https://doi.org/10.3390/ijerph15040573
Received: 5 March 2018 / Revised: 16 March 2018 / Accepted: 16 March 2018 / Published: 23 March 2018
Cited by 3 | PDF Full-text (2196 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Extremely high fine particulate matter (PM2.5) concentration has been a topic of special concern in recent years because of its important and sensitive relation with health risks. However, many previous PM2.5 exposure assessments have practical limitations, due to the assumption
[...] Read more.
Extremely high fine particulate matter (PM2.5) concentration has been a topic of special concern in recent years because of its important and sensitive relation with health risks. However, many previous PM2.5 exposure assessments have practical limitations, due to the assumption that population distribution or air pollution levels are spatially stationary and temporally constant and people move within regions of generally the same air quality throughout a day or other time periods. To deal with this challenge, we propose a novel method to achieve the real-time estimation of population exposure to PM2.5 in China by integrating mobile-phone locating-request (MPL) big data and station-based PM2.5 observations. Nationwide experiments show that the proposed method can yield the estimation of population exposure to PM2.5 concentrations and cumulative inhaled PM2.5 masses with a 3-h updating frequency. Compared with the census-based method, it introduced the dynamics of population distribution into the exposure estimation, thereby providing an improved way to better assess the population exposure to PM2.5 at different temporal scales. Additionally, the proposed method and dataset can be easily extended to estimate other ambient pollutant exposures such as PM10, O3, SO2, and NO2, and may hold potential utilities in supporting the environmental exposure assessment and related policy-driven environmental actions. Full article
Figures

Figure 1

Open AccessArticle Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data
Int. J. Environ. Res. Public Health 2018, 15(4), 566; https://doi.org/10.3390/ijerph15040566
Received: 14 February 2018 / Revised: 12 March 2018 / Accepted: 20 March 2018 / Published: 21 March 2018
Cited by 3 | PDF Full-text (6779 KB) | HTML Full-text | XML Full-text
Abstract
The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions
[...] Read more.
The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles’ mobile activities (MA) and stationary activities (SA). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA, SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles’ activities in road networks. Full article
Figures

Figure 1

Open AccessArticle Cycling for Transportation in Sao Paulo City: Associations with Bike Paths, Train and Subway Stations
Int. J. Environ. Res. Public Health 2018, 15(4), 562; https://doi.org/10.3390/ijerph15040562
Received: 8 December 2017 / Revised: 28 February 2018 / Accepted: 2 March 2018 / Published: 21 March 2018
PDF Full-text (1145 KB) | HTML Full-text | XML Full-text
Abstract
Cities that support cycling for transportation reap many public health benefits. However, the prevalence of this mode of transportation is low in Latin American countries and the association with facilities such as bike paths and train/subway stations have not been clarified. We conducted
[...] Read more.
Cities that support cycling for transportation reap many public health benefits. However, the prevalence of this mode of transportation is low in Latin American countries and the association with facilities such as bike paths and train/subway stations have not been clarified. We conducted a cross-sectional analysis of the relationship between bike paths, train/subway stations and cycling for transportation in adults from the city of Sao Paulo. We used data from the Sao Paulo Health Survey (n = 3145). Cycling for transportation was evaluated by a questionnaire and bike paths and train/subway stations were geocoded using the geographic coordinates of the adults’ residential addresses in 1500-m buffers. We used multilevel logistic regression, taking account of clustering by census tract and households. The prevalence of cycling for transportation was low (5.1%), and was more prevalent in males, singles, those active in leisure time, and in people with bicycle ownership in their family. Cycling for transportation was associated with bike paths up to a distance of 500 m from residences (OR (Odds Ratio) = 2.54, 95% CI (Confidence interval) 1.16–5.54) and with the presence of train/subway stations for distances >500 m from residences (OR = 2.07, 95% CI 1.10–3.86). These results are important to support policies to improve cycling for transportation in megacities such as Sao Paulo. Full article
Figures

Figure 1

Open AccessArticle Using Individual GPS Trajectories to Explore Foodscape Exposure: A Case Study in Beijing Metropolitan Area
Int. J. Environ. Res. Public Health 2018, 15(3), 405; https://doi.org/10.3390/ijerph15030405
Received: 13 January 2018 / Revised: 24 February 2018 / Accepted: 25 February 2018 / Published: 27 February 2018
Cited by 2 | PDF Full-text (10376 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
With the growing interest in studying the characteristics of people’s access to the food environment and its influence upon individual health, there has been a focus on assessing individual food exposure based on GPS trajectories. However, existing studies have largely focused on the
[...] Read more.
With the growing interest in studying the characteristics of people’s access to the food environment and its influence upon individual health, there has been a focus on assessing individual food exposure based on GPS trajectories. However, existing studies have largely focused on the overall activity space using short-period trajectories, which ignores the complexity of human movements and the heterogeneity of the spaces that are experienced by the individual over daily life schedules. In this study, we propose a novel framework to extract the exposure areas consisting of the localized activity spaces around daily life centers and non-motorized commuting routes from long-term GPS trajectories. The newly proposed framework is individual-specific and can incorporate the internal heterogeneity of individual activities (spatial extent, stay duration, and timing) in different places as well as the dynamics of the context. A pilot study of the GeoLife dataset suggests that there are significant variations in the magnitude as well as the composition of the food environment in different parts of the individual exposure area, and residential environment is not representative of the overall foodscape exposure. Full article
Figures

Figure 1

Open AccessArticle The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou
Int. J. Environ. Res. Public Health 2018, 15(2), 308; https://doi.org/10.3390/ijerph15020308
Received: 28 December 2017 / Revised: 3 February 2018 / Accepted: 5 February 2018 / Published: 10 February 2018
Cited by 9 | PDF Full-text (2487 KB) | HTML Full-text | XML Full-text
Abstract
Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated
[...] Read more.
Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals’ activity space. First, a survey was conducted to collect individuals’ daily activity and weight information in Guangzhou in January 2016. Then, the data were used to calculate and compare the values of several built environment variables based on seven activity space delineations, including home buffers, workplace buffers (WPB), fitness place buffers (FPB), the standard deviational ellipse at two standard deviations (SDE2), the weighted standard deviational ellipse at two standard deviations (WSDE2), the minimum convex polygon (MCP), and road network buffers (RNB). Lastly, we conducted comparative analysis and regression analysis based on different activity space measures. The results indicate that significant differences exist between variables obtained with different activity space delineations. Further, regression analyses show that the activity space delineations used in the analysis have a significant influence on the results concerning the relationships between the built environment and obesity. The study sheds light on the UGCoP in analyzing the relationships between obesity and the built environment. Full article
Figures

Figure 1

Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top