title: A method for neighborhood-level surveillance of food purchasing.
abstract: Added sugar, particularly in carbonated soft drinks (CSDs), represents a considerable proportion of caloric intake in North America. Interventions to decrease the intake of added sugar have been proposed, but monitoring their effectiveness can be difficult due to the costs and limitations of dietary surveys. We developed, assessed the accuracy of, and took an initial step toward validating an indicator of neighborhood-level purchases of CSDs using automatically captured store scanner data in Montreal, Canada, between 2008 and 2010 and census data describing neighborhood socioeconomic characteristics. Our indicator predicted total monthly neighborhood sales based on historical sales and promotions and characteristics of the stores and neighborhoods. The prediction error for monthly sales in sampled stores was low (2.2%), and we demonstrated a negative association between predicted total sales and median personal income. For each $10,000 decrease in median personal income, we observed a fivefold increase in predicted monthly sales of CSDs. This indicator can be used by public health agencies to implement automated systems for neighborhood-level monitoring of an important upstream determinant of health. Future refinement of this indicator is possible to account for factors such as store catchment areas and to incorporate nutritional information about products.
authors: Surveillance Lab, McGill Clinical and Health Informatics.|Department of Epidemiology, Biostatistics and Occupational Health.
authors: David L
authors: DL
authors: Buckeridge
authors: Surveillance Lab, McGill Clinical and Health Informatics.|Department of Epidemiology, Biostatistics and Occupational Health.
authors: Katia
authors: K
authors: Charland
authors: Desautels Faculty of Management, McGill University, Montréal, Québec, Canada.
authors: Alice
authors: A
authors: Labban
authors: Department of Marketing, Business Economics, and Law, Alberta School of Business, University of Alberta, Edmonton, Alberta, Canada.
authors: Yu
authors: Y
authors: Ma
mesh_terms: D002253:Carbonated Beverages; D003132:Commerce; D003625:Data Collection; D004032:Diet; D005502:Food / Q000191:economics*; D005523:Food Supply / Q000191:economics; D006293:Health Promotion; D006801:Humans; D007182:Income; D018803:Models, Economic; D015233:Models, Statistical; D011203:Poverty; D011237:Predictive Value of Tests; D011792:Quebec; D012044:Regression Analysis; D015203:Reproducibility of Results; D012111:Residence Characteristics; D012923:Social Class; D012959:Socioeconomic Factors
keywords: nutrition; obesity; public health surveillance; statistical methods