The role of neighborhoods in the development of obesity has received much research attention. Being able to identify those social and environmental variables that predict healthier weights can assist health promotion at community-level. This competing renewal of the Seattle Obesity Study (SOS) seeks to explain why obesity prevalence was closely linked to individual- and area-based socioeconomic status (SES), whereas 12 mo. weight change was not. The SOS III will recruit a longitudinal cohort of 1,000 adult residents of King, Snohomish, Pierce, and Yakima counties in WA State. The 4 counties are diverse in race/ethnicity, education, incomes, population density, patterns of development, and obesity rates. An address-based sampling scheme, stratified by SES, will yield a population sample that is >40% obese, while assuring geographic diversity. A 20-min Health Behaviors Survey will be administered by phone by Battelle Survey Research Center. Measured heights and weights will be obtained in-person at local sites at baseline, 12, and 24 mo. Participants will complete food frequency questionnaires (FFQs) at baseline, 12, and 24 mo. Prevailing supermarket prices for 384 FFQ foods in each county will be used to estimate individual diet costs at 3 points in time. GIS/GPS methods will track 3- day travel patterns and the time and location of all food events at baseline, 12, and 24 mo. Accelerometers worn over 3-days will track physical activity at baseline, 12, and 24 mo. Two follow-up Health Behaviors Surveys will be administered at 12 and 24 mo in-person visits. An environmental scan of the food environment using Info USA will be performed at baseline, 12mo and 24 mo. The SOS is one of few observational studies that combine longitudinal survey research with geo-localized metrics of environmental exposure, GPS tracking, accelerometers, and nutrition economics. SOS III will explore the impact of these variables on body weight trajectories over 24 mo. The first aim is to determine whether baseline SES and environmental variables predict subsequent changes in energy intakes, diet quality and cost, physical activity, and body weight. The second aim is to determine whether changes in social and environmental variables and in diet and physical activity behaviors can predict body weight trajectories over 24 mo. The third aim is to develop a new model explaining how changing exposure to socio-economic, environmental, dietary, and psychosocial variables can predict the dynamics of weight change. The SOS III will update and refine our metrics of the built environment and examine the relative impact of SES and the built environment on weight trajectories, using a mixed model framework.