Nutrient composition databases in the age of big data: foodDB, a comprehensive, real-time database infrastructure

Abstract

ObjectivesTraditional methods for creating food composition tables struggle to cope with the large number of products and the rapid pace of change in the food and drink marketplace. This paper introduces foodDB, a big data approach to the analysis of this marketplace, and presents analyses illustrating its research potential.DesignfoodDB has been used to collect data weekly on all foods and drinks available on six major UK supermarket websites since November 2017. As of June 2018, foodDB has 3 193 171 observations of 128 283 distinct food and drink products measured at multiple timepoints.MethodsWeekly extraction of nutrition and availability data of products was extracted from the webpages of the supermarket websites. This process was automated with a codebase written in Python.ResultsAnalyses using a single weekly timepoint of 97 368 total products in March 2018 identified 2699 ready meals and pizzas, and showed that lower price ready meals had significantly lower levels of fat, saturates, sugar and salt (p<0.001). Longitudinal analyses of 903 pizzas revealed that 10.8% changed their nutritional formulation over 6 months, and 29.9% were either discontinued or new market entries.ConclusionsfoodDB is a powerful new tool for monitoring the food and drink marketplace, the comprehensive sampling and granularity of collection provides power for revealing analyses of the relationship between nutritional quality and marketing of branded foods, timely observation of product reformulation and other changes to the food marketplace.

Are food and drink available in online and physical supermarkets the same? A comparison of product availability, price, price promotions and nutritional information

“…Nutrient composition tables on packaging are required by law to be accurate (22) and previous research has suggested that nutritional labels are a reasonably accurate representation of the food contained in the packaging (23) . Our study shows that the nutritional information available online and in physical stores in the UK correlates very highly; therefore, it is viable to use data from online supermarket databases such as foodDB (4) for nutrition studies and interventions.…”

“…Increasingly, online supermarkets are being used as a source of 'big data' for monitoring the food system and developing novel nutrient composition tables to support public health research. In the UK, data collected from six online supermarkets have been used to monitor the healthiness of ready meals and pizzas (4) and to evaluate the impact of the Soft Drink Industry Levy on sugar levels in drinks (5) . In Australia, data collected from two online supermarkets have been used to monitor price promotions on sugar-sweetened beverages (6) and foods (7) .…”

Impact of the announcement and implementation of the UK Soft Drinks Industry Levy on sugar content, price, product size and number of available soft drinks in the UK, 2015-19: A controlled interrupted time series analysis

“…We collected data for this analysis using a webscraping and data-processing software and database platform called foodDB, which has run continuously since November 2017. Full details of the methods of data collection using this tool are provided elsewhere [31]. Briefly, foodDB software collects and processes data automatically on over 99% of all food and drink products available for purchase on supermarket websites each week, including product name, nutritional information, ingredients, product size, price, and whether or not the product is on promotion.…”

Effects of Labelling and Increasing the Proportion of Lower-Energy Density Products on Online Food Shopping: A Randomised Control Trial in High- and Low-Socioeconomic Position Participants

“…The site has all of the essential features of a normal online supermarket: browse and search for products, add products to the basket and check out, and has been used in previous research work [8][9][10]. It contains a grocery product range (FoodDB database [19]) including products names and images, department, aisle and shelf of the products, product size and nutritional information (energy, fat, saturated fat, carbohydrates, sugar, salt, fibre and protein). For the purpose of the present study, drinks were removed from the online supermarket as prior work has suggested it is inappropriate to combine food and drinks when calculating ED [20].…”