Food composition databases in the era of Big Data: Vegetable oils as a case study

Abstract

Understanding the population's dietary patterns and their impacts on health requires many different sources of information. The development of reliable food composition databases is a key step in this pursuit. With them, nutrition and health care professionals can provide better public health advice and guide society toward achieving a better and healthier life. Unfortunately, these databases are full of caveats. Focusing on the specific case of vegetable oils, we analyzed the possible obsolescence of the information and the differences or inconsistencies among databases. We show that in many cases, the information is limited, incompletely documented, old or unreliable. More importantly, despite the many efforts carried out in the last decades, there is still much work to be done. As such, institutions should develop long-standing programs that can ensure the quality of the information on what we eat in the long term. In the face of climate change and complex societal challenges in an interconnected world, the full diversity of the food system needs to be recognized and more efforts should be put toward achieving a data-driven food system.

Keywords: food composition; food composition database; food guidelines; food nutrient; healthy nutrition; vegetable oils.

Figure 1

Number of compounds and nutrients reported for each vegetable oil in the selected databases (EuroFIR not included). (A) The total number of nutrients for which the database provides some information, while (B) contains only those nutrients with a quantity larger than 0. In both panels, the bar plots represent the sum of the values of the same line, and the rows and columns of the matrix are ordered in decreasing order from left to right and from top to bottom.

Figure 2

Date associated with each compound or nutrient in the selected databases that provide said information. For each vegetable oil, the length of the bar indicates the number of compounds, while the color represents the amount of them that have an associated date within a decade. Palm kernel is not included as it is only reported in FRIDA and USDA. (A) The information for all elements present in the database, regardless of their actual value, while (B) shows the information only for those with a reported quantity larger than 0.

Figure 3

Comparison of fatty acids among different oils in the USDA database. The values are shown as the percentage out of 100 g of the product. MUFA, PUFA, and SFA represent monounsaturated, polyunsaturated, and saturated fatty acids, respectively. Other compounds denote elements that were not described in the database and that would be necessary to reach 100%.

Figure 4

Comparison of fatty acids in palm oil among different FCDBs. The values are shown as the percentage out of 100 g of the product. MUFA, PUFA, and SFA represent monounsaturated, polyunsaturated, and saturated fatty acids, respectively. Other compounds denote elements that were not described in the database and that would be necessary to reach 100%.

Figure 5

Visualization of the palm oil citation network. Scientific records that cite each other can form communities, signaling that they contain similar information. Each color represents a community detected in the network and the labels are the keywords that determine the contents present in the community. Communities are ordered according to their size, with A being the largest. This network was plotted using the software implemented in Silva et al. (82).