Limitations of the Food Compass Nutrient
Content type: Matters Arising
Authors: Flaminia Ortenzi, Marit Kolby, Mark Lawrence, Frédéric Leroy, Stella Nordhagen,
Stuart M. Phillips, Stephan van Vliet, Ty Beal*
*Corresponding author: Ty Beal
Nutrient Profiling Systems provide algorithms which are designed to assess the
healthfulness of foods based on nutrient composition, and intended as a strategy to improve
diets. Many Nutrient Profiling Systems are founded on a reductionist assumption that the
healthfulness of foods is determined by the sum of their nutrients, with little consideration
for the extent and purpose of processing and its health implications. A novel Nutrient
Profiling System called Food Compass attempted to address existing gaps and provide a
more holistic assessment of the healthfulness of foods. While a conceptually impressive
effort, we propose that the chosen algorithm is not well justified and produces results that
fail to discriminate for common shortfall nutrients, exaggerate the risks associated with
animal-source foods, and underestimate the risks associated with ultra-processed foods. We
caution against the use of Food Compass in its current form to inform consumer choices,
policies, programs, industry reformulations, and investment decisions.
Unhealthy diets are a leading cause of death and disease.1 A common strategy to improve diets is
by using Nutrient Profiling Systems (NPS)—which are designed to assess the healthfulness of
foods based on their nutrient composition—to inform front-of-package labeling, industry
reformulations, company ratings, policies, programs, and investments.2 However, the application
of NPS is limited because health is not determined by the consumption of single foods but rather
by overall diet quality interacting with unique individual and contextual factors.3 Furthermore,
NPS largely depend on a reductionist paradigm that the healthfulness of a given food is
determined by the mere sum of its nutrients, with little consideration for the extent and purpose
of processing, which has important implications on food quality and health.4 This is problematic
because food processing is not invariably benign. While acknowledging there is a large variation
in the health effects of different types of ultra-processed foods (UPF), in general the higher the
share of UPF in the diet the higher the risk of non-communicable diseases (NCD).5 For instance,
a recent randomized controlled trial found that diets high in UPF led to substantial overeating
and weight gain compared to unprocessed food diets, even though meals within both diets were
matched for energy, energy density, macronutrients, sugar, sodium, and fiber.6 This evidence
suggests that how foods are processed significantly impacts their healthfulness, independently of
nutrient profiles. The resulting overconsumption, weight gain, and related NCD risk is likely
attributed, at least partly, to the degradation of the food matrix and increased hyperpalatability.
A novel NPS called Food Compass attempted to address the concerns of an overly reductionist
approach by comprehensively assessing 54 food attributes across nine health-relevant domains,
including additives, processing, and phytochemicals, among others.2 While a conceptually
impressive effort, we propose that the chosen algorithm and weighting of various components is
not well justified and produces results that do not account for shortfall nutrients, exaggerate the
risks associated with animal-source foods (ASF), and underestimate the risks associated with
A key feature of Food Compass is that it applies the same scoring principles to all foods, aiming
to increase objectivity, avoid arbitrary food categories, allow for direct comparison across items,
and facilitate the assessment of mixed dishes. However, since healthy diets can be achieved in
various ways through combining disparate quantities of different food groups, assessing the
healthfulness of all foods based on a single scale may not be appropriate. Impressively, Food
Compass has undergone validation for content, face, and convergent/discriminant validity, and
the authors plan to test it for construct/predictive validity against health outcomes. This is
welcomed; however, most current assessments of construct/predictive validity consist of
modeling approaches, which require significant assumptions with limited certainty, imply a risk
of circularity, and can be heavily influenced by a limited selection of foods and their
combinations. This raises the question of whether it is possible to robustly validate the health
effects of individual foods, as health outcomes are determined by overall diet quality.3
We propose that a primary limitation of Food Compass is that the weighting of attributes and
domains does not represent a balanced reflection of available evidence and sometimes appears
arbitrary and insufficiently transparent. For instance, phytochemicals are assigned the same
weight as protein and fiber, even though evidence shows that health effects from these domains
are not comparable. Similarly, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)
are weighted the same as alpha‐linolenic acid (ALA), despite the inefficient conversion of ALA
to EPA and DHA, and the more convincing evidence on health benefits of EPA and DHA.7
Other nutrients such as iron and vitamin C, whose abundance in the food supply varies
considerably and deficiencies of which have very different public health significance,8 are also
weighted equally. Additionally, the NOVA classification is only one of 54 attributes,
contributing <5% to the overall score, which fails to sufficiently recognize the crucial role of
food processing in health and disease. The type of processing should arguably be attributed
significantly more weight given the substantial evidence linking UPF with negative health
outcomes,4–6 as well as broader societal impacts associated with aggressive marketing and nutri-
washing of UPF.9 Furthermore, we are concerned that Food Compass did not properly apply
NOVA classifications. For example, many vegetables such as fresh kale and spinach prepared in
oil are classified as UPF, when these should be classified as processed foods. Moreover, several
of these foods incorrectly classified as UPF also received the top score of 100, which suggests
they have not been properly penalized according to the Food Compass algorithm.
Other aspects of Food Compass illustrate its limited consideration of the food matrix. For
instance, while UPF are assigned negative points, unprocessed foods do not receive any positive
points, which does not valorize food matrix quality. Moreover, no distinction is made between
minimally processed and reconstituted whole grains, or between fortified and naturally occurring
nutrients. However, reconstitution and fortification cannot fully replicate the potential benefits of
the food matrix in unprocessed and minimally processed foods, which go beyond their individual
Another limitation is lack of adjustment for differences in bioavailability of iron and zinc, which
varies widely across foods depending on factors such as the proportion of heme to non-heme
iron, phytate, and vitamin C content.11 Also, anti-nutrients (for example, phytate and oxalate) are
not incorporated into the scoring, despite their important role in nutrient absorption. Finally, little
consideration is given to total protein, contributing <4% of the overall score, while protein
quality of foods is omitted.
Several elements in the scoring algorithm are unfavorable towards ASF, regardless of their
processing level. First, no distinction is made between red and processed meat, although
available evidence shows that the consumption-associated risk differs substantially between the
two.12 Second, red meat is always attributed negative scores, even when minimally processed,
despite being a top source of high-quality protein and bioavailable micronutrients commonly
lacking in diets globally, including iron, zinc, and vitamin B12.13 Third, dietary cholesterol is
always scored negatively despite its limited influence on plasma cholesterol,14 inevitably
penalizing ASF. Finally, seafood and yogurt are the only two ASF in the list of healthful food-
based ingredients, while other nutrient-dense ASF that make a significant contribution to diet
quality (for example, eggs and milk) are not included. The excessive penalization of ASF could
have implications on nutrient adequacy in all contexts, but especially in low- and middle-income
countries, where ASF intake is generally low, and the burden of nutrient inadequacies is high,
particularly for iron, zinc, folate, calcium, vitamins A, B12, and D, and essential amino acids and
While there are many justified scores, the above-mentioned limitations of Food Compass result
in numerous unjustified scores. For example, kale receives the same score as watermelon, despite
the large difference in nutrient density and fiber between the two foods (Figure). Surprisingly,
Frosted Mini Wheats, Honey Nut Cheerios, nonfat frozen yogurt, calcium-fortified orange juice,
and chocolate-covered almonds all receive top scores (≥70, “to be encouraged”). In contrast,
foods such as millet, whole wheat bread, skinless chicken breast, boiled eggs, and whole milk,
are assigned lower scores (31–69, “to be moderated”), which are comparable to those of sweet
potato fries, Lucky Charms, canned pineapple in sugar syrup, almond M&M’s, and ice cream
cones with nuts. Moreover, all of the aforementioned items score higher than ground beef,
cheddar cheese, and whole eggs fried in butter (≤30, “to be minimized”).
Figure. Illustrative examples of limitations of Food Compass scores (non-exhaustive list).
Although a variety of NPS have been developed, currently there is no universally accepted gold
standard, as all existing NPS face technical and conceptual limitations. Food Compass represents
an impressive effort to develop a more comprehensive and objective NPS; nonetheless, we
propose that its overall algorithm and structure needs to be redesigned. If used as intended to
inform consumer choice, policies, programs, reformulations, and investment decisions, Food
Compass scores could result in certain dietary improvements such as increased consumption of
minimally processed plant-source foods, but may have negative implications on nutrient
adequacy in essential commonly lacking nutrients (for example, iron) and, to some extent,
reinforce the consumption of UPF.
Competing Interests statement
TB, SN, MK, and FO have nothing to disclose. SMP reports grants from US National Dairy
Council, Roquette Freres, and Dairy Farmers of Canada during the conduct of the study; non-
financial support from Enhanced Recovery, outside the submitted work. In addition, SMP has a
patent Canadian 3052324 issued to Exerkine, and a patent US 20200230197 pending to Exerkine
but reports no financial gains. SvV reports grant support from USDA (2020-38640-31521; 2021-
67034-35118), the North Dakota Beef Commission, the Turner Institute of Ecoagriculture, and
the Greenacres Foundation during the conduct of the study. SvV reports financial remuneration
for academic talks, but does not accept honoraria, consulting fees, or other personal income from
food industry groups/companies. ML is a Board member of Food Standards Australia New
Zealand (FSANZ) and the views he expresses in this commentary are his alone and not
necessarily those of FSANZ. FL reports financial support of the Research Council of the Vrije
Universiteit Brussel, including the SRP7, IOF3017 and IRP11 projects. FL is a board member of
various academic non-profit organizations including the Belgian Association for Meat Science
and Technology (president), the Belgian Society for Food Microbiology (secretary), and the
Belgian Nutrition Society. On a non-remunerated basis, he also has a seat in the scientific
committee of the Institute Danone Belgium and the Scientific Board of the World Farmers’
Organization. The views he expresses in this commentary are his alone and not necessarily those
of the aforementioned organizations. All authors consume omnivorous diets.
FO and TB prepared the initial manuscript. All authors critically reviewed and approved the final
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