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UID:20260729T034733EDT-5702UTmulS@132.216.98.100
DTSTAMP:20260729T074733Z
DESCRIPTION:Hiroshi Mamiya\, PhD\n\nPostdoctoral Fellow\n	Department of Comm
 unity Health and Epidemiology\n	University of Saskatchewan\n\nWHERE: In-Per
 son | 2001 McGill College\, Rm 1201 | Zoom\n\nAbstract\n\nHealth-related b
 ehaviours\, such as dietary choices and physical activity\, exhibit inequa
 lities across neighbourhoods and social determinants of health. Large-scal
 e measurements of these behavioural risk factors will provide the followin
 g novel research and surveillance capacities: 1) constructing geographical
 ly detailed maps of behavioural risk factors to uncover neighbourhood disp
 arities of health\; 2) examining the daily or hourly interaction of human 
 behaviours and modifiable environmental factors (e.g.\, green space and bi
 ke infrastructure)\; and 3) investigating potential drivers of these behav
 iours\, such as food marketing. In this talk\, I will demonstrate the util
 ities of location-coded and high-frequency digital data provided by wearab
 le devices and grocery scanners to achieve these capacities. Examples will
  be drawn from my research projects targeting four Canadian cities. I will
  also highlight the importance of epidemiologic and biostatistical princip
 les in guiding data science approaches toward evidence-based healthy city 
 initiatives.\n\nSpeaker Bio\n\nHiroshi is an epidemiologist whose goal is 
 to develop urban environments that sustainably promote healthy lifestyles 
 across neighbourhoods. His research converts large-scale digital data into
  longitudinal and geographic measures of human activities through statisti
 cal modelling and machine learning. He subsequently links these behavioura
 l measures with environmental and health data through Geographic Informati
 on System and Global Positioning System\, aiming to generate novel insight
 s about the mechanisms in which health disparities arise across urban comm
 unities. His collaborators include transportation researchers\, kinesiolog
 ists\, computer scientists\, health geographers\, marketing and management
  scientists\, and nutrition researchers.\n\n \n\n \n
DTSTART:20230424T141500Z
DTEND:20230424T151500Z
SUMMARY:Data Science Approaches to Advance Equitable Healthy Cities Researc
 h
URL:https://www.mcgill.ca/epi-biostat-occh/channels/event/data-science-appr
 oaches-advance-equitable-healthy-cities-research-347701
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