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.

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.

Inclusion Criteria:

• 35 - 80 years
• live in the same residence selected for the study for at least one year
• are able to walk without human assistance
• are able to read and write fluently in English or Spanish
• have a stable phone
• leave their home at least 3 or more times per week
• have a stable weight over the past 3 months (+/- 5 lbs)
• spend most of their time within San Diego County
• will be in San Diego County for the study period (i.e. not travel or border crossing)
• are able to give informed consent and comply with the protocol
• are willing to complete all assessments and wear all devices for 14 days.

Exclusion Criteria:

• are younger than 435 or older than 80 years of age
• are pregnant or nursing
• have a mental state that would preclude complete understanding of the protocol or compliance
• have a chronic illness that may be associated with weight change
• are participating in another clinical trial
• have type 1 diabetes
• have an autoimmune disorder such as lupus, rheumatoid arthritis, or multiple sclerosis
• have an intestinal disease such as celiac disease, Crohn's disease, or inflammatory bowel disease (IBD) or sensitivities or allergies to gluten
• have psoriasis
• have a history of or a current eating disorder
• have had previous weight loss surgery
• plan to travel into Mexico during the two-week study period or have a history of travel to Mexico
• are taking second generation or "atypical" antipsychotics
• live with someone else who is participating in this study
• are currently taking weight loss supplements and unwilling to stop for a predetermined "wash-out" period

700 35 - 80 year old adults living in San Diego County