The Kunming CalFit Study: Modeling Dietary Behavioral Patterns Using Smartphone Data

Details

• Personal Author:
  Bestick A ; Eom S ; Han J ; Hua J ; Li Y ; Seto E ; Shia V ; Wang M ; Wu L
• Description:
  Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can facilitate various forms of user feedback for intervention studies. We describe our findings from a smartphone-based study, in which an Android-based application we developed called CalFit was used to collect information related to young adults' dietary behaviors. In addition to monitoring dietary patterns, we were interested in understanding contextual factors related to when and where an individual eats, as well as how their dietary intake relates to physical activity (which creates energy demand) and psychosocial stress. 12 participants were asked to use CalFit to record videos of their meals over two 1-week periods, which were translated into nutrient intake by trained dietitians. During this same period, triaxial accelerometry was used to assess each subject's energy expenditure, and GPS was used to record time-location patterns. Ecological momentary assessment was also used to prompt subjects to respond to questions on their phone about their psychological state. The GPS data were processed through a web service we developed called Foodscoremap that is based on the Google Places API to characterize food environments that subjects were exposed to, which may explain and influence dietary patterns. Furthermore, we describe a modeling framework that incorporates all of these information to dynamically infer behavioral patterns that may be used for future intervention studies. [Description provided by NIOSH]
• Subjects:
  Behavior Diet Occupational Health Safety
• Keywords:
  Behavior Patterns Cell Phones Physical Exercise Psychological Stress Sensors Wearable Technologies
• ISBN:
  9781424479290
• ISSN:
  1557-170X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Proceedings
• Place as Subject:
  California ; OSHA Region 10 ; OSHA Region 9 ; Washington
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  2014
• NIOSHTIC Number:
  nn:20054825
• Citation:
  Conf Proc IEEE Eng Med Biol Soc 2014 Aug; 2014:6884-6887
• Contact Point Address:
  Mark J. Nieuwenhuijsen, Centre for Research in Environmental Epidemiology (CREAL), 08003 Barcelona, Catalonia, Spain
• Email:
  mnieuwenhuijsen@creal.cat
• CAS Registry Number:
  Carbon black (CAS RN 1333-86-4)
• Federal Fiscal Year:
  2014
• Performing Organization:
  University of Washington
• Peer Reviewed:
  False
• Start Date:
  20050701
• Source Full Name:
  Conference Proceedings of the IEEE Engineering in Medicine and Biology Society
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:c7f127d603bf101e8a6bab3d57388d5fdd977a43723194038efca81e3b6a89df4567460febafb7493daa980381bfd37be1bddbb87c3915693fb80cb7d22e2655
• Download URL:
  https://stacks.cdc.gov/view/cdc/217247/cdc_217247_DS1.pdf
• File Type:
  [PDF - 491.66 KB ]