Global Positioning System (GPS) Exposure to Environments & Relations With Biomarkers of Cancer Risk
Condition: Physical Activity; Sedentary Lifestyle
Study type: Observational

Summary: 
      The prevalence of overweight and obesity are increasing worldwide. In the U.S., approximately
      85,000 new cancer cases per year are related to obesity. Understanding lifestyle behaviors,
      their causes, and relations to cancer are critical. Where people spend their time during the
      day may be related to their risk of getting cancer. This project will assess behaviors in
      different locations across the day and relate exposure to different environments to
      biological outcomes.
    

Detailed description: 
      The purpose of this study is to advance methods of cancer risk exposure assessment by
      measuring both neighborhood access and total environment exposure to healthy environments by
      dynamically integrating Global Positioning System (GPS) data with Geographical Information
      System (GIS) data. We hypothesize that dynamic GPS based measures of environmental exposure
      will be more strongly related to behavior and insulin and inflammation biomarkers than static
      address based GIS measures of access.

      Primary Aim:

      To compare Dynamic vs Static GIS measures of physical activity (PA) supportivity and their
      associations with PA behaviors, body mass index (BMI), and biological markers.

      Secondary Aim:

      To compare Dynamic vs Static GIS measures of access to healthy food and their associations
      with dietary intake, BMI, and biological markers.

      Exploratory aim:

      Social environment (e.g. eating with others) has been identified as an important determinant
      of health, but assessment of this has been limited to self-report through surveys or text
      prompts. Images from a person worn camera (the SenseCam) provide an objective and continuous
      assessment of social environment e.g. number of social interactions per day, eating alone or
      with others. In a subsample of participants (N=30), we propose to explore whether portable
      SenseCam measures of social interactions & social behaviors from person view images are more
      strongly related to breast and colon cancer risk factors than self-reported social
      environment measures. Behaviors and built environments (especially food locations) can also
      be coded to validate the accuracy of the GIS measures and the machine learned behavior
      categories employed in the full sample.
    

Observational model: Case-Control
Time perspective: Cross-Sectional
Sampling method: Non-Probability Sample
Study population: 
        700 35 - 80 year old adults living in San Diego County
      
Biospecimen description: 
      DNA and RNA will be collected from your blood. This may be used to look at genetic components
      important to your health. DNA may be analyzed for important genetic determinants that
      indicate unhealthy environment exposure and risk of obesity, cancer, and cardiometabolic
      disease. Data from such analyses could guide and may help us learn more about genetic markers
      of therapeutic or prevention effectiveness and risk of chronic disease associated with
      obesity and unhealthy environment exposure, including cancer.