Commercial nutrition data focus on packaged and processed foods, which list the information on their nutrition facts panels (NFP). Food and Drug Administration (FDA) rules require serving size (in household measure and metric amounts), total calories, calories from fat, total fat, saturated fat, trans fat, total sugars, total carbohydrate, protein, dietary fiber, sodium, cholesterol, vitamin A, vitamin C, calcium, and iron. The Gladson Database includes more items than public FCTs, and subsets of these (around 2,000 barcodes) are updated weekly. We found 170,000+ barcodes with NFP label data in the 2010 Gladson database compared to the 7,600+ foods available in the 2010 FNDDS (version 4.1). In addition, Product Launch Analytics (Datamonitor) and Mintel Global New Product Database (GNPD) contains NFP and barcode data for new products entering the marketplace. Thus, commercial NFP label data may provide a more complete and updated picture of the nutrients in the US food supply, at least for calories, macronutrients, and a few key micronutrients.
However, commercial data also have limitations. First, although NFP labeling is required for most packaged foods, labeling for raw produce (fruits and vegetables) and fish is voluntary, while delicatessen foods, bakery products and confections sold directly to consumers from preparation locale, and self-service bulk foods have no such requirements. Second, there is a 20% labeling measurement allowance between what is on the NFP and what is found during enforcement analyses (33
) and reporting rules (e.g., foods with <5 calories or <0.5 gram of fat per serving meet the definition of “calorie free” and “fat free”, respectively). Third, barcodes in commercial NFP label data are not updated equally, and its proprietary nature limits researchers’ abilities to determine the comprehensiveness and frequency of collection and updating.
People eat food, but it is the composition of these foods that affects health. Given what is known about these data sources, how can the measures of the foods bought or eaten and the measures of nutritional content of these foods be brought together? provides an example of how the four types of data can be integrated.
Example for linking food sales, purchase, consumption, food composition and nutrition facts panel data
Congruent years of the household (or store) food purchase (sales) data can be linked to the NFP label data by barcodes. However, these commercial data are expensive, and their proprietary nature creates challenges in research collaboration and transparency. Our preliminary work shows that in 2008, there were 600,000+ unique barcodes in the food purchase data, and 170,000+ unique barcodes in the NFP label data, of which 150,000+ matched to Homescan (household purchase) and Scantrack (store sales) data. For most of the other 450,000 barcodes, it is possible to derive basic nutrition information (calories, total fat, saturated fat, sugars) for different sized items of the same product, or apply USDA FCT data for fresh or raw produce, seafood, meats, and some dairy and eggs. In our preliminary work to date, about 90% of US dollar and volume sales have basic nutrition information.
Meanwhile, there are established methods for linking the individual food intake and FCT data based on existing food code and recipe files, but these FCTs do not keep up with changes in the marketplace. Consequently, our team is developing a new nutrient database that aims to better reflect the rapidly changing nutrient profiles (including calories, fats, sugars, sodium, cholesterol, and fiber) of foods people consume for each 2-year period that corresponds with NHANES. We plan to estimate a composite nutrient profile for each USDA food code based on weighted averages (weighted by calories purchased) of nutrient profiles of all matched commercial data over the same time period. A critical step is the creation of a cross-walk between USDA food codes and commercial nutrient data sources (barcode level data from Gladson, Product Launch Analytics, or Mintel and commercial food item level data from the NCC Food and Nutrient Database). We will document our steps and assumptions, including validation procedures (e.g., comparing means and variance of NFP label data for branded products with branded food items in the NCC Food and Nutrient Database; comparing NFP label data to NFP data for a subset of products from food manufacturing companies and based on field data collection efforts). We will involve the scientific community in reviewing our efforts.
By making the links across these four types of data, two forms of data can result:
- An average per day individual level dataset on consumption with extensive nutrition composition information for each food as reported, and
- Daily, weekly, monthly, or annual household level datasets on purchases and prices linked with basic nutrition information for each barcode.
These datasets together can help us identify methodological challenges, sampling, and measurement errors in both public and commercial data sources, and provide guidance on improvements to federally funded monitoring efforts to better capture the rapidly changing nutrition contents of foods.
Commercial data can supplement public data in other ways. For example, Gladson data includes the full ingredients lists, allowing researchers to identify ready-to-eat cereals, bars, and cookies reported in NHANES 2007/08 that contain fruit juice concentrate as an added sweetener (2
), something the USDA FCTs cannot do. Of course, to maintain the relevance of such data, these linkages will have to be updated annually in order to properly capture the changes in foods in the marketplace.
In conclusion, our measurement and understanding of the US food and nutrient supply has not kept up with the modern food landscape. Existing data sources miss important distinctions about the nutritional makeup of food products available across the country and purchased by certain socio-demographic subpopulations. Complex and overlapping sets of measurements exist from commercial vendors capturing many of the rapid shifts in the packaged food sector at the market, household, and individual levels, as well as in major federal surveys capturing raw, packaged, and prepared foods. Yet, such measures miss reformulated, new, and even many old products. While expensive and labor intensive, it is possible to create systematic and meaningful linkages across data on food purchase/sales, food intake, food composition, and nutrition facts panel. Researchers and nutrition professionals’ ability to properly integrate these data sources and fully capitalize on the opportunities that lie behind them is at its infancy.
There is no specific or sustained funding for critical methodological challenges that the USDA and CDC face in monitoring food and nutrient intake of US residents. Cross-governmental groups concerned with methods of reducing caloric intake, sodium, added sugars, and saturated fats in the US diet should create initiatives to support the use of all of these existing data collection systems to validate and improve each system. At the same time, market- and consumer-research companies should recognize their potential contributions to public health and nutrition and collaborate to develop strong relationships with researchers and federal agencies to explore options for researchers to gain access to these commercial data via lower cost contracts with academic libraries or the creation of data repositories.
Integrated data that better reflects the nutritional profile of foods purchase and consumed will allow researchers and policy makers to answer questions like:
- To what extent are voluntary industry initiatives to enhance the quality of food products (e.g., reduce sodium and added sugars) occurring?
- To what extent do prices and income affect consumers’ dietary choices concurrently with any changes in the nutritional profiles of foods?
The answers to these and many other research questions that inform policy-making and national nutrition guidance can emerge from a data system that better captures the dynamics of the actual US food supply and the nutrient intakes of individuals. We can only change what we can measure. In order to advance our understanding of how changes in the food supply affect how and what Americans eat, then we must address the challenge of ensuring that we utilize comprehensive and appropriate data sources and that our measures are valid and reliable. Only then can we truly assess the effectiveness of our collective efforts toward helping improve our nation’s overall health and well-being.