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

• Autore: Kwan Mei-Po
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
• Descrizione fisica: 1 electronic resource (382 p.)
• Soggetto non controllato: the elderly; regression analysis; walking event; green space; missing data; crop residue burning; correlation analysis; imputation; physical environment; crowdedness; Guangzhou; mobile phone data; GPS trace; noise pollution; mental disorders; Beijing; urban leisure; environmental exposure; environmental context cube; subway stations; air pollution exposure; long-distance walking; car ownership; multilevel model; CHAS; ecological momentary assessment; cycling for transportation; cognitive aging; 3SFCA; interannual and seasonal variations; well-being experience; personal projects; spatial spread; E2SFCA; activity space; catchment areas; structural equation modeling; transport modes; greenspace exposure; health; train stations; human mobility; quantile regression; the neighborhood effect averaging problem (NEAP); emissions estimation; taxi GPS trajectories; real-time traffic; primary healthcare; rail travel; spatial accessibility; commuting route; GPS; urban planning; environmental health; Brazil; EMA; geographical accessibility; big data; dynamic assessment; obesity; healthcare accessibility; population demand; the uncertain geographic context problem (UGCoP); geographic impedance; collective leisure activity; multimodal network; GIS; 2009 influenza A(H1N1) pandemic; UGCoP; environmental exposures; spatial data; the uncertain geographic context problem; Singapore; built environment; adults; time-weighted exposure; geographic imputation; Public Participatory GIS (PPGIS); access probability; life-course perspectives; China; walking; active travel; foodscape exposure; car use; food environment; fuel consumption; ageing; Healthcare services; road traffic accidents; space-time kernel density estimation; multilevel Bayesian model; environmental context exposure index; spatial autocorrelation; PM concentrations; physical activity; bike paths
• Sommario/riassunto: Environmental 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.
• Altri titoli varianti: Human Mobility, Spatiotemporal Context, and Environmental Health
• Titolo autorizzato: Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods
• ISBN: 3-03921-184-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910346665403321
• Lo trovi qui: Univ. Federico II