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dc.contributor.authorKwan, Mei-Po*
dc.date.accessioned2021-02-11T15:37:27Z
dc.date.available2021-02-11T15:37:27Z
dc.date.issued2019*
dc.date.submitted2019-08-28 11:21:27*
dc.identifier35899*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/49631
dc.description.abstractEnvironmental health researchers have long used concepts like the neighborhood effect to assessing people’s exposure to environmental influences and the associated health impact. However, these are static notions that ignore people’s daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies 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 been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.*
dc.languageEnglish*
dc.subjectR5-920*
dc.subject.classificationthema EDItEUR::M Medicine and Nursingen_US
dc.subject.otherthe elderly*
dc.subject.otherregression analysis*
dc.subject.otherwalking event*
dc.subject.othergreen space*
dc.subject.othermissing data*
dc.subject.othercrop residue burning*
dc.subject.othercorrelation analysis*
dc.subject.otherimputation*
dc.subject.otherphysical environment*
dc.subject.othercrowdedness*
dc.subject.otherGuangzhou*
dc.subject.othermobile phone data*
dc.subject.otherGPS trace*
dc.subject.othernoise pollution*
dc.subject.othermental disorders*
dc.subject.otherBeijing*
dc.subject.otherurban leisure*
dc.subject.otherenvironmental exposure*
dc.subject.otherenvironmental context cube*
dc.subject.othersubway stations*
dc.subject.otherair pollution exposure*
dc.subject.otherlong-distance walking*
dc.subject.othercar ownership*
dc.subject.othermultilevel model*
dc.subject.otherCHAS*
dc.subject.otherecological momentary assessment*
dc.subject.othercycling for transportation*
dc.subject.othercognitive aging*
dc.subject.other3SFCA*
dc.subject.otherinterannual and seasonal variations*
dc.subject.otherwell-being experience*
dc.subject.otherpersonal projects*
dc.subject.otherspatial spread*
dc.subject.otherE2SFCA*
dc.subject.otheractivity space*
dc.subject.othercatchment areas*
dc.subject.otherstructural equation modeling*
dc.subject.othertransport modes*
dc.subject.othergreenspace exposure*
dc.subject.otherhealth*
dc.subject.othertrain stations*
dc.subject.otherhuman mobility*
dc.subject.otherquantile regression*
dc.subject.otherthe neighborhood effect averaging problem (NEAP)*
dc.subject.otheremissions estimation*
dc.subject.othertaxi GPS trajectories*
dc.subject.otherreal-time traffic*
dc.subject.otherprimary healthcare*
dc.subject.otherrail travel*
dc.subject.otherspatial accessibility*
dc.subject.othercommuting route*
dc.subject.otherGPS*
dc.subject.otherurban planning*
dc.subject.otherenvironmental health*
dc.subject.otherBrazil*
dc.subject.otherEMA*
dc.subject.othergeographical accessibility*
dc.subject.otherbig data*
dc.subject.otherdynamic assessment*
dc.subject.otherobesity*
dc.subject.otherhealthcare accessibility*
dc.subject.otherpopulation demand*
dc.subject.otherthe uncertain geographic context problem (UGCoP)*
dc.subject.othergeographic impedance*
dc.subject.othercollective leisure activity*
dc.subject.othermultimodal network*
dc.subject.otherGIS*
dc.subject.other2009 influenza A(H1N1) pandemic*
dc.subject.otherUGCoP*
dc.subject.otherenvironmental exposures*
dc.subject.otherspatial data*
dc.subject.otherthe uncertain geographic context problem*
dc.subject.otherSingapore*
dc.subject.otherbuilt environment*
dc.subject.otheradults*
dc.subject.othertime-weighted exposure*
dc.subject.othergeographic imputation*
dc.subject.otherPublic Participatory GIS (PPGIS)*
dc.subject.otheraccess probability*
dc.subject.otherlife-course perspectives*
dc.subject.otherChina*
dc.subject.otherwalking*
dc.subject.otheractive travel*
dc.subject.otherfoodscape exposure*
dc.subject.othercar use*
dc.subject.otherfood environment*
dc.subject.otherfuel consumption*
dc.subject.otherageing*
dc.subject.otherHealthcare services*
dc.subject.otherroad traffic accidents*
dc.subject.otherspace-time kernel density estimation*
dc.subject.othermultilevel Bayesian model*
dc.subject.otherenvironmental context exposure index*
dc.subject.otherspatial autocorrelation*
dc.subject.otherPM concentrations*
dc.subject.otherphysical activity*
dc.subject.otherbike paths*
dc.titleHuman Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods*
dc.typebook
oapen.identifier.doi10.3390/books978-3-03921-184-5*
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0*
oapen.relation.isbn9783039211838*
oapen.relation.isbn9783039211845*
oapen.pages382*
oapen.edition1st*


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