Habitual polyphenol intake of foods according to NOVA classification: implications of ultra-processed foods intake (CUME study)

Abstract

We aimed to evaluate the intake of dietary total polyphenols and their classes according to NOVA classification among adults of a Brazilian cohort study. This is a cross-sectional study, in which food consumption was assessed using an Food Frequency Questionnaire (FFQ) and polyphenol content (total and their classes) was estimated at Phenol-Explorer for each food category and presented as mean and 95% confidence interval. Adjusted linear regression was used to describe the trend of the association between the quintiles of polyphenols intake (dependent variable) and NOVA group of food consumption (independent variable). The higher consumption of fresh/minimally processed foods is accompanied by a higher intake of total polyphenols and all their classes, while the higher consumption of ultra-processed foods represented the lower intake of total polyphenols and their classes. Fresh foods are the greatest sources of polyphenols, and their daily consumption should be encouraged, while ultra-processed foods are deficient in such bioactive compounds.

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Habitual polyphenol intake of foods according
to NOVA classification: implications of ultra-
processed foods intake (CUME study)
Hillary Nascimento Coletro, Josefina Bressan, Amanda Popolino Diniz, Helen
Hermana Miranda Hermsdorff, Adriano Marçal Pimenta, Adriana Lúcia
Meireles, Raquel de Deus Mendonça & Júlia Cristina Cardoso Carraro
To cite this article: Hillary Nascimento Coletro, Josefina Bressan, Amanda Popolino
Diniz, Helen Hermana Miranda Hermsdorff, Adriano Marçal Pimenta, Adriana Lúcia
Meireles, Raquel de Deus Mendonça & Júlia Cristina Cardoso Carraro (2023): Habitual
polyphenol intake of foods according to NOVA classification: implications of ultra-processed
foods intake (CUME study), International Journal of Food Sciences and Nutrition, DOI:
10.1080/09637486.2023.2190058
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RESEARCH ARTICLE
INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION
Habitual polyphenol intake of foods according to NOVA classification:
implications of ultra-processed foods intake (CUME study)
Hillary Nascimento Coletroa , Josefina Bressanb , Amanda Popolino Diniza , Helen Hermana
Miranda Hermsdorffb , Adriano Marçal Pimentac , Adriana Lúcia Meirelesd , Raquel de Deus
Mendonçad and Júlia Cristina Cardoso Carrarod
aPostgraduate Program in Health and Nutrition, School of Nutrition, Universidade Federal de Ouro Preto, Ouro Preto, Brazil; bDepartment
of Nutrition and Health, Universidade Federal de Viçosa, Vicosa, Brazil; cNursing Department, Universidade Federal do Paraná, Curitiba,
Brazil; dDepartment of Clinical and Social Nutrition, School of Nutrition, Universidade Federal de Ouro Preto, Ouro Preto, Brazil
ABSTRACT
We aimed to evaluate the intake of dietary total polyphenols and their classes according
to NOVA classification among adults of a Brazilian cohort study. This is a cross-sectional
study, in which food consumption was assessed using an Food Frequency Questionnaire
(FFQ) and polyphenol content (total and their classes) was estimated at Phenol-Explorer for
each food category and presented as mean and 95% confidence interval. Adjusted linear
regression was used to describe the trend of the association between the quintiles of
polyphenols intake (dependent variable) and NOVA group of food consumption (independent
variable). The higher consumption of fresh/minimally processed foods is accompanied by
a higher intake of total polyphenols and all their classes, while the higher consumption of
ultra-processed foods represented the lower intake of total polyphenols and their classes.
Fresh foods are the greatest sources of polyphenols, and their daily consumption should
be encouraged, while ultra-processed foods are deficient in such bioactive compounds.
Introduction
The prevalence and absolute burden of chronic
non-communicable disease (NCD) are increasing
globally and remains a significant public health prob-
lem (Benziger et al. 2016). The growing increase of
NCD is mainly explained by changes in lifestyle and
nutritional transition (Nasreddine et al. 2018), char-
acterised by the reversal of eating habits, previously
marked by the consumption of fresh foods and now
being characterised by increased consumption of
ultra-processed foods (Sartorelli and Franco 2003;
Monteiro et al. 2013). This is because urbanisation
and technological evolution of production and work
have brought changes in various aspects of human
life, including food habits (Popkin and Ng 2022).
Food processing is an important milestone in the
industrialisation and modernisation of the industry.
The food processing technique has always been
employed to prolong food storage and involves prepa-
ration and preservation steps ranging from the
removal of inedible parts of food to more complex
procedures. However, since the 1980s, there has been
a revolutionary movement in the food industry, which
has allowed the invention of new recipes and new
products made from a minimum portion of natural
ingredients and with the addition of new ingredients
that are palatable, inexpensive and synthesised in the
laboratory (Monteiro et al. 2013; Ministério da
Saúde 2014).
In this scenario, in which we are facing a change
in the profile of disease in the population, with an
increase in the incidence of food-related illnesses and
a pandemic of obesity and malnutrition, the NOVA
classification was created (Monteiro et al. 2010),
which evaluates foods according to their degree of
industrial processing. The NOVA classification allo-
cates foods into four groups: fresh and minimally
processed foods, culinary ingredients, processed foods
and ultra-processed foods (Moubarac et al. 2014).
Despite the importance and usefulness of NOVA clas-
sification, the criteria used in these types of classifi-
cation are often ambiguous and generalist, grouping
© 2023 Taylor & Francis Group, LLC
CONTACT Júlia Cristina Cardoso Carraro julia.carraro@ufop.edu.br Universidade Federal de Ouro Preto, Morro do Cruzeiro, Bauxita, Ouro Preto,
Minas Gerais 35400-000, Brazil.
https://doi.org/10.1080/09637486.2023.2190058
ARTICLE HISTORY
Received 3 October 2022
Revised 28 February 2023
Accepted 7 March 2023
KEYWORDS
Food consumption;
phenolic compounds;
NOVA classication;
fresh/minimally processed
foods;
processed foods;
ultra-processed foods

2 H. N. COLETRO ETAL.
in the same group foods with different properties and
nutritional composition (Marino et al. 2021).
The consumption of ultra-processed foods has been
studied worldwide and it is observed that the countries
with the highest consumption of these foods are devel-
oped and western countries, especially the United States
of America and the United Kingdom (Rauber etal. 2018;
Marino etal. 2021), with the highest percentage of con-
tribution of ultra-processed foods in daily energy con-
sumption (>50%), followed by France (35.9%) (Julia etal.
2018) and Mexico (29.8%) (Marrón-Ponce et al. 2018).
In recent years, the literature has emphasised the effects
of high consumption of ultra-processed foods, docu-
menting solid scientific evidence that such foods are
harmful to health and may increase the risk for several
diseases (Louzada et al. 2015; de Deus Mendonça et al.
2017; Fiolet et al. 2018; Juul et al. 2018; Louzada et al.
2018; Rauber etal. 2018; Adjibade etal. 2019; Blanco-Rojo
etal. 2019; Martínez Steele et al. 2019; Rico-Campà etal.
2019; Gómez-Donoso etal. 2020; Passos etal. 2020; Juul
etal. 2021; Levy et al. 2021; Moradi etal. 2021; Nardocci
et al. 2021; Pagliai etal. 2021; Coletro et al. 2022). This
is because such foods are energy-dense, high in sodium,
sugar, fat and other unnatural ingredients (Ministério da
Saúde 2014). Thus, such foods are not only a source of
ingredients and substances related to diseases, but they
can be also deficient in several nutrients and bioactive
compounds, due to the lack of natural ingredients
(Monteiro etal. 2018), so there are no recommendations
for the consumption of foods that belong to this group
(Ministério da Saúde 2014).
On the other hand, fresh/minimally processed foods,
that are natural sources of several nutrients and bioactive
compounds such as polyphenols, should be the basis of
daily nutrition (Wang et al. 2014; Barabási et al. 2019;
Koch 2019; Wang etal. 2021; Coletro et al. 2022; Khan
et al. 2022; Nguyen et al. 2022). The polyphenols, sec-
ondary metabolites produced by plant interactions with
the environment, have been studied and associated with
human health for their antioxidant capacity, its ability
to control the redox environment, metabolic homeostasis,
anti-inflammatory property and ability to induce vaso-
dilation (Manach et al. 2004; Leri et al. 2020; Marino
etal. 2020). Polyphenols are only available in plant-based
foods and ingredients and are associated with lower risk
of metabolic syndrome, hypertension and cardiovascular
disease (Hügel etal. 2016; Grosso etal. 2017; Mendonça
et al. 2019; Coletro et al. 2021).
Although the high intake of ultra-processed foods
has been related to the deficient intake of several nutri-
ents (Monteiro et al. 2018), to the best of all knowl-
edge, there are few studies conducted on the relation
between ultra-processed foods and polyphenols intake
(Conceição Santos etal. 2021). For this reason, studies
are necessary to extend the knowledge on the effects
of food consumption according to the degree of pro-
cessing in terms of its nutritional composition, mainly
polyphenols intake through the diet. Thus, the aim of
this work was to evaluate the dietary intake of total
polyphenols and their classes according to each of the
three groups of the NOVA classification among adults
who participated in a Brazilian cohort study.
Materials and methods
CUME study
The Cohort of Universities of Minas Gerais (CUME)
is an open cohort conducted in Brazil since 2016 that
aims to assess the impacts of the Brazilian dietary
pattern on non-communicable chronic diseases. As
an open cohort, the recruitment of participants is
continuous, and follow-up happens every 2 years, as
described by Domingos et al. (2018).
Data collection
The CUME Project is conducted with alumni from
seven universities in the state of Minas Gerais, Brazil.
Baseline data were collected using a questionnaire
named Q_0 (available at: https://www.projetocume.com.
br/). The online baseline questionnaire contained ques-
tions about sociodemographic and socioeconomic
aspects, lifestyle, personal and family background dis-
ease, medication use, biochemical data and anthropo-
metric data. The food consumption was informed by
a Food Frequency Questionnaire (FFQ) validated
(Azarias etal. 2021) with 144 food items, also validated
according to the NOVA classification, divided into
eight food groups (dairy, meat and fish, cereals and
legumes, oils and fats, fruits and vegetables, beverages
and other foods including food preparations, sugar,
honey and sweets).
Study population
This is a cross-sectional study with data from the
baseline of participants in the CUME study who had
completed an undergraduate or graduate degree at
one of the seven participating educational institutions.
As inclusion criteria, participants should have
answered the questions about food consumption,
should be Brazilian and reside in Brazil. In addition,
they should have a daily energy intake of >500 kcal
and <6000 kcal (Siqueira et al. 2018; Azarias et al.

INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION 3
2021; Coletro et al. 2021) and women should not be
pregnant at the time they answered the questionnaire
or in the last year.
A total of 7710 individuals participated at baseline,
but at the end of the selection, according to exclusion
criteria, 6892 individuals remained (Figure 1).
Polyphenols intake
Polyphenols intake was measured using the habitual
diet, which was assessed using an FFQ referring to
consumption in the last year. The frequency of con-
sumption was counted daily, weekly, monthly and
annually, besides the number of times each food was
consumed (0–9 or more) and the serving size (small,
medium, large portion or according to household
measures). In order to increase the reliability of the
data, a photo album was provided so that partici-
pants could observe the portion sizes of the foods
that best corresponded to their actual consumption
(Azarias et al. 2021). Daily food consumption was
estimated by multiplying the serving size by the fre-
quency and number of times the consumption of
each FFQ item.
To assess total polyphenols, phenolic acids, flavo-
noids, stilbenes and lignans, we excluded animal
(n = 34) and other foods with only trace amounts of
polyphenols (n = 29), totalling 89 foods for analysis.
For processed foods or preparations, the phenolic con-
tent was calculated based on each ingredient that was
a source of polyphenols as described by Coletro
et al. (2021).
Data on the polyphenol content in foods were
obtained at Phenol-Explorer database (Pérez-Jiménez
et al. 2011) (available at: http://phenol-explorer.eu/),
United States Department of Agriculture (USDA)
(available at: https://www.ars.usda.gov/nutrientdata) and
original articles for specific foods (cassava, mate tea
and chimarrão) (Montagnac et al. 2009; Baeza et al.
2018). The retention factor was applied to raw foods
to compensate for losses or gains in nutrients during
food processing (Rothwell et al. 2015). The intake of
polyphenols (total and classes) was calculated by mul-
tiplying the polyphenol content of each food by its
daily consumption in grams.
To evaluate the phenolic intake in foods according
to the NOVA classification, total polyphenols and
their classes were adjusted by 1000 kcal/day, by mul-
tiplying the polyphenols of the foods of each group
by 1000 and subsequently dividing by the daily energy
intake of the participants. The contribution of each
food to polyphenol intake in the four NOVA groups
was calculated separately by the ratio of the mean
intake of total polyphenols and their classes from a
particular food to the mean sum of total polyphenols
or their classes from all foods.
Food consumption according to NOVA
classication
The 144 foods listed in the FFQ were divided into
the three major food groups covered by the NOVA
classification: fresh/minimally processed foods, pro-
cessed foods and ultra-processed foods and adjusted
by the residual adjustment method proposed by
Willett and Howe (1997) (Figure 2). The culinary
ingredient group was not considered in the final anal-
ysis, because these foods are usually consumed with
fresh/minimally processed foods in the form of culi-
nary preparations, and when their consumption is
evaluated separately, it becomes difficult for the inter-
viewer to accurately estimate this information.
Covariates
The covariates correspond to sociodemographic vari-
ables such as age, sex, self-declared skin colour/race
(white, brown and black, indigenous or yellow), work-
ing status (unemployed, student, stayed home, work-
ing or retired), marital status (married or not
Baseline
7,710 participants
299 Brazilians living abroad 7,411 participants
29 participants from other
nationalities 7,382 participants
220 participants with
extreme values of total
energy
7,162 participants
270 pregnant or women who
had children in the last year 6,892 participants
Final sample
2016 2018 2020
Collection Years
Figure 1. Participant inclusion ow chart in the CUME study,
2016–2020.

4 H. N. COLETRO ETAL.
married), study field (health courses or others) and
family income.
Statistical analyses
Data analysis included descriptive analyses of the
sociodemographic characteristics of the sample. For
that, continuous data are presented as mean and stan-
dard deviation and categorical variables as absolute
and relative frequencies.
The contribution of each group’s daily energy
intake (%/day) according to NOVA classification was
obtained by adding the energies from carbohydrates,
proteins, lipids and ethanol (when present) and divid-
ing the result by total energy intake multiplied by 100.
To estimate the total polyphenols and their classes’
intake in each food category according to the degree
of processing, individuals were classified into five
strata according to their daily consumption of fresh/
minimally processed, processed and ultra-processed
NOVA Classification
Group 1 -
Fresh/minimally
processed foods
Obtained directly from
plants or animals and
consumed without any
alteration after leaving
nature, or undergo only
minimal industrial
processes
Group 3 – Processed
foods
Products manufactured
essentially by adding
salt or sugar or
vegetable oils to a fresh
or minimally processed
food
Group 4 – Ultra –
processed food
Formulated mostly by
substances extracted
from food, derived from
food constituents, or
synthesized in the
laboratory with a
minimum portion of
fresh food.
Food Frequency Questionnaire
Group 1 - Fresh/minimally
processed foods
Soybeans/Oatmeal/Grain/Rice/
Brown rice/Pasta/Gnocchi/Polenta/
Fried Polenta/
Canjiquinha/Cassava flour/Corn
flour/ Beans/Lentils/ Avocado/
Pineapple/Acai/Acerola
Banana/Guava/Kiwi/
Orange/Tangerine/
Apple/Pear/Papaya/Mango/Water-
melon/Melon/Strawberry/Cherry/
Peach/Plum/Nectarine/Grape/Rai-
sin/Fruit salad/Pumpkin/Zucchini/
Chayote/Lettuce/Swiss chard/
Watercress/Rugula/ Spinach/Kale/
Cassava/Yam/Fried
Cassava/Potato/Fried Potato/
Beet/Eggplant/Carrot/
Cauliflower/Cabbage/Corn/Pepper/
Cucumber/Pea/Tomate/Vegetable
soup/Coffee/Black,Green and
White tea/Natural fruit
juice/Soup/Nuts
Group 3 – Processed
foods
Beer/Red Wine/White and
Rosé Wine/Fruit syrup/Fruit
jam/ Peach paste/Guava
paste/Fig paste
Group 4 – Ultra –
processed food
Soy milk/Loaf bread/ Whole-
grain bread/ Sweet
Bread/Light
Bread/Toast/Cheese
bread/Cereal/Cereal bar/
Lasagna/Pizza/Industrial fruit
juice/Industrial juice/Dark
chocolate/Chocolate
candy/Popcorn/ Hot dog/
Sandwich/Sweet
rice/Chocolate milk/Salty
pastry/Cachaça/Liquor
Figure 2. NOVA classication and assessed foods by the Food Frequency Questionnaire, CUME study, 2016–2020.

INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION 5
foods (g/day), adjusted by the residual adjustment
method. According to the NOVA classification, these
strata corresponded to quintiles of the population
distribution according to the daily consumption (in
grams) of the food groups.
Linear regression analyses were used to describe
the trend and the statistical significance of the asso-
ciation between the quintiles of food consumption
according to NOVA classification and dietary poly-
phenol intake, with adjustment for sex, age and family
income. The statistical analyses were performed using
Stata version 15.0 software (StataCorp, College
Station, TX).
Ethical approval
This study was conducted according to the guidelines
of the Declaration of Helsinki and approved by the
Ethics Committee of the seven universities involved
UFV, UFJF, UFOP, UFMG, UFLA, UFVJM, UNIFAL
(protocol no.: (i) 596.741-0; (ii) 2.615.738; (iii)
2565240; (iv) 2491366; (v) 18/2.676.682; (vi) 3.989.443;
(vii) 44483415.5.2002.5148).
Results
A total of 6892 individuals participated in the study,
with a mean age of 35.6 years (±9.5 years); most of
them were female (67.60%), not married (54.34%),
self-declared as white (64.54%), had more than 16years
of schooling with higher education in non-health
courses (74.01%), worked or were retired (75.10%) and
with an average family income of R$/month: 10352.74
(equivalent to USD: 2924.50) (Table 1).
The mean calorie intake was 2411.30 kcal per day
(Table 2), influenced mainly by the consumption of
fresh and minimally processed foods. Regarding the
intake of polyphenols, an average of 860.79 mg/day
was observed, mainly due to the intake of phenolic
acids (638.05 mg/day) (Table 2).
Table 3 describes the consumption of total poly-
phenols and their classes across the quintiles of con-
sumption of fresh/minimally processed foods. It is
possible to observe an increase in the intake of total
polyphenols and all the classes studied, mainly from
the phenolic acids, flavonoids and lignans classes, as
there is a greater consumption of fresh and minimally
processed foods.
In Table 4, it is noted that an increase in the con-
sumption of processed foods is proportional to the
increase in total polyphenols intake, phenolic acids
and stilbenes. However, the consumption of this group
of foods is inversely proportional to the intake of
flavonoids and lignans, which means higher consump-
tion of processed foods leads to lower intake of these
polyphenols.
Regarding the consumption of ultra-processed
foods, it can be observed that the increase in daily
consumption of ultra-processed foods is inversely
proportional to the intake of total polyphenols and
their classes. In this sense, the higher the consump-
tion of ultra-processed foods, the lower is the con-
sumption of phenolic compounds (Table 5).
When evaluating the main foods that contribute
to the intake of polyphenols, it is observed that
among the fresh/minimally processed foods, coffee,
peanuts, walnuts, nuts and corn products were the
foods with the highest source of total polyphenols.
The processed beverages, red wine and beer were the
greatest sources of total polyphenols. For
ultra-processed foods, the main contributors to total
Table 1. Sociodemographic characteristics of the participants
(n = 6892), CUME study, 2016–2020.
Characteristics Total
Sexa
Female (n/%) 4659 (67.60)
Ageb (years old) 35.64 (±9.49)
Marital statusa
Married (n/%) 3147 (45.66)
Not married (n/%) 3745 (54.34)
Skin coloura
White (n/%) 4448 (64.54)
Brown and black (n/%) 2359 (34.23)
Indigenous, yellow and others (n/%) 85 (1.23)
Study elda
Health courses (n/%) 1791 (25.99)
Others (n/%) 5101 (74.01)
Professional statusa
Unemployed/stayed home/student (n/%) 1716 (24.90)
Works/retired (n/%) 5176 (75.10)
Family incomeb (R$/month) 10352.74 (±49423.09)
aValues expressed as absolute and relative frequency.
bValues expressed as mean and standard deviation.
Table 2. Calorie contribution of fresh/minimally processed, pro-
cessed and ultra-processed foods and habitual polyphenol intake
of the participants (n = 6892), CUME study, 2016–2020.
Daily energy intake
(kcal/day)a2411.30 (±985.26)
NOVA classication
Daily energy intake
(kcal/day)
Daily energy
contribution (%)
Fresh/minimally processed
foods
1451.04 60.07
Processed foods 234.63 9.87
Ultra-processed foods 584.97 24.08
PolyphenolsaDaily intake (mg/day)
Total polyphenols 860.79 (±448.72)
Phenolic acids 638.05 (±456.87)
Flavonoids 183.61 (±145.49)
Lignans 18.92 (±14.98)
Stilbenes 0.72 (±1.45)
aValues expressed as mean and standard deviation.

6 H. N. COLETRO ETAL.
polyphenol intake were whole grain bread, industrial
fruit juice and chocolate milk, while dark chocolate
was the main contributor to consumption of stilbenes
(Figure 3).
Discussion
To our knowledge, this is one of the first articles that
attempted to evaluate the intake of total polyphenols
and their classes in foods according to their degree
of processing. We observed that the consumption of
fresh and minimally processed foods is the main con-
tributor to the daily calorie intake of the sample
studied, and the higher consumption of fresh/mini-
mally processed foods is accompanied by a higher
intake of total polyphenols and all their classes, while
the higher consumption of ultra-processed foods rep-
resented the lower intake of total polyphenols and
their classes. The foods that mainly contribute to the
intake of total polyphenols were coffee, nuts and corn
products. However, ultra-processed foods account for
24.08% of the daily calorie contribution, similar to
the results reported by Louzada et al. (2018) when
investigating the share of ultra-processed foods’ nutri-
tional quality of diets in Brazil that found an average
consumption of ultra-processed foods in 20.4% of
daily calories. These consumption profiles are a par-
ticular concern because ultra-processed foods are
associated with personal, population and planetary
health problems (Lawrence 2021).
Our results show that ultra-processed foods are a
contributor to a negative nutritional quality of diets,
in concern to their phenolic and antioxidant content.
Higher consumption of ultra-processed foods is neg-
atively associated with the consumption of total poly-
phenols and all their classes in this population and,
as presented by Conceição Santos etal., that evaluated
87 menus in a university restaurant (Conceição Santos
etal. 2021). In comparison, both fresh and minimally
processed foods are positively associated with higher
consumption of total polyphenols and their classes.
Identifying possible mechanisms to explain how
the consumption of ultra-processed foods can affect
human health is a complicated and controversial pro-
cess. Numerous scientific evidence report that the
ingredients present in ultra-processed foods, such as
sugar, fat, salt and food additives, ingredients pro-
duced synthetically in laboratories, are harmful to
health (Monteiro etal. 2018; Lawrence 2021; Monteiro
et al. 2021; Schulte and Gearhardt 2021). However,
limited literature studies the content of bioactive
compounds in these foods. Polyphenols are a large
and complex family of phytochemicals and bioactive
compounds produced in metabolic pathways triggered
by plant interactions with the environment
(Velderrain-Rodríguez etal. 2014) and are associated
with health benefits. Thus, it is known that food
affects our health through multiple molecular mech-
anisms, with some chemicals serving as a direct
source of negative intermediates to human health,
largely present as an ingredient of ultra-processed
foods, while others, such as polyphenols, play a ben-
eficial regulatory role (Barabási et al. 2019). The
benefits to vascular health are outstanding. These
compounds have antioxidant properties and the abil-
ity to induce nitric oxide production, with a conse-
quent decrease in blood pressure and improvement
in insulin resistance, lipid profile and inflammatory
markers (Andriantsitohaina et al. 2012; Mendonça
et al. 2019; Coletro et al. 2021). Other benefits of
polyphenols include their ability to modulate cell
signalling pathways to provide neuroprotective effects
and reverse cognitive and behavioural deficits
(Gomez-Pinilla and Nguyen 2012; Lin et al. 2021).
Besides acting to control the redox environment,
proteostatic and metabolic homeostasis, organelle
turnover and inflammatory response, making cells
more resistant to toxic drives (Leri et al. 2020).
However, the sources of polyphenols are limited
to plant-based foods, so they are largely present in
fruits, vegetables, legumes, grains and cereals (Manach
etal. 2004; Tresserra-Rimbau etal. 2013). Thus, fresh/
minimally processed foods are the major sources of
phenolic compounds, and therefore part of the ben-
efits of daily consumption of these foods can be
attributed to the presence of polyphenols. In contrast,
ultra-processed foods, formulated from a minimum
fraction of fresh foods (Ministério da Saúde 2014),
are not great sources of polyphenols. Besides the lack
of natural ingredients, cooking and food processing
alters the chemical composition of food and often
causes losses in polyphenol content, usually caused
by oxidation, enzymatic action, removal of skin or
seeds, and leaching into oil or water, which is then
discarded (Rothwell etal. 2015). In addition, adding
chemicals that are not natural and absent in raw
ingredients and transforming others can alter the
chemical structure and phenolic composition of foods
(Rothwell et al. 2015; Barabási et al. 2019).
Thus, one of the major goals presented here is to
generate more corroborative data to support and
advance public policies capable of regulating the
production and marketing of ultra-processed foods
in order to reverse the harm presented by the regular
consumption of these foods. Synergistic and coherent

INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION 7
Table 3. Habitual dietary polyphenol intake according to quintiles of daily fresh/minimally processed food consumption of the participants (n = 6892), CUME study, 2016–2020.
Quintiles of fresh/minimally processed foodsa
Polyphenols Q1 (1667.17 g/day)bQ2 (2258.65 g/day)bQ3 (2651.97 g/day)bQ4 (3061.79 g/day)bQ5 (3766.54 g/day)b
Adjusted
regression
coecientc
p trend
Total polyphenols
(mg/1000 kcal)
287.41 (279.84–294.97) 338.52 (329.57–347.47) 370.45 (360.91–379.99) 401.37 (390.73–412.02) 458.66 (446.29–471.03) 39.82 <.001
Phenolic acids (mg/1000 kcal) 215.00 (206.90–221.30) 254.91 (246.36–263.45) 278.67 (269.64–287.71) 301.13 (291.05–311.22) 336.08 (324.15–348.02) 28.63 <.001
Flavonoids (mg/1000 kcal) 60.74 (58.56–62.91) 68.46 (66.21–70.71) 74.43 (72.15–76.72) 81.85 (79.09–84.60) 101.22 (97.59–104.84) 9.18 <.001
Lignans (mg/1000 kcal) 5.18 (5.00–5.36) 6.61 (6.41–6.81) 7.83 (7.58–8.08) 8.86 (8.59–9.14) 11.48 (11.13–11.84) 1.44 <.001
Stilbenes (mg/1000 kcal) 0.27 (0.24–0.29) 0.31 (0.28–0.33) 0.31 (0.28–0.34) 0.33 (0.28–0.37) 0.33 (0.30–0.35) 0.01 .038
aValues expressed as means and 95% condence interval.
bValues expressed as means for the daily consumption of the quintile.
cRegression coecient of the polyphenol intake on the daily consumption (g/day) of fresh/minimally processed foods, adjusted for sex, age and family income.
Table 4. Habitual dietary polyphenol intake according to quintiles of daily processed food consumption of the participants (n = 6892), CUME study, 2016–2020.
Quintiles of processed foodsa
Polyphenols Q1 (28.61 g/day)bQ2 (89.31 g/day)bQ3 (130.43 g/day)bQ4 (195.70 g/day)bQ5 (383.55 g/day)b
Adjusted regression
coecientcp trend
Total polyphenols (mg/1000 kcal) 346.31 (336.58–356.03) 366.58 (356.08–377.08) 384.20 (372.79–395.61) 370.79 (361.13–380.46) 388.47 (378.01 − 398.93) 8.78 <.001
Phenolic acids (mg/1000 kcal) 247.92 (238.97–256.86) 270.34 (260.51–280.17) 289.64 (278.77–300.51) 279.88 (270.89–288.88) 297.09 (287.37–306.81) 9.80 <.001
Flavonoids (mg/1000 kcal) 81.78 (78.46–85.11) 78.48 (75.85–81.10) 77.02 (74.41–79.62) 74.29 (71.71–76.87) 75.11 (72.47–77.74) –0.95 .042
Lignans (mg/1000 kcal) 8.73 (8.42–9.04) 8.60 (8.31–8.90) 8.27 (7.98–8.57) 7.49 (7.25–7.73) 6.86 (6.61–7.11) –0.44 <.001
Stilbenes (mg/1000 kcal) 0.11 (0.10–0.12) 0.16 (0.14–0.17) 0.25 (0.23–0.26) 0.41 (0.38–0.44) 0.61 (0.56–0.67) 0.13 <.001
aValues expressed as mean and 95% condence interval.
bValues expressed as means for the daily consumption of the quintile.
cRegression coecient of the polyphenol intake on the daily consumption (g/day) of processed foods, adjusted for sex, age and family income.

8 H. N. COLETRO ETAL.
Table 5. Habitual dietary polyphenol intake according to quintiles of daily ultra-processed food consumption of the participants (n = 6892), CUME study, 2016–2020.
Quintiles of ultra-processed foodsa
Polyphenols Q1 (92.93 g/day)bQ2 (211.06 g/day)bQ3 (279.46 g/day)bQ4 (364.98 g/day)bQ5 (618.42 g/day)b
Adjusted regression
coecientcp trend
Total polyphenols (mg/1000 kcal) 398.30 (387.43–409.17) 400.74 (389.52–411.95) 383.10 (373.28–392.92) 356.23 (345.95–366.51) 317.94 (308.91–326.97) –18.50 <.001
Phenolic acids (mg/1000 kcal) 294.51 (284.44–304.57) 304.74 (294.11–315.37) 287.03 (277.85–296.22) 265.20 (255.48–287.92) 233.36 (224.86–241.87) –14.64 <.001
Flavonoids (mg/1000 kcal) 87.42 (84.12–90.71) 78.63 (76.04–81.22) 78.13 (75.32–80.93) 73.44 (70.94–75.94) 69.06 (66.58–71.55) –3.87 <.001
Lignans (mg/1000 kcal) 9.54 (9.21–9.88) 8.43 (8.16–8.71) 8.06 (7.78–8.34) 7.35 (7.10–7.60) 6.58 (6.34–6.81) –0.61 <.001
Stilbenes (mg/1000 kcal) 0.35 (0.31–0.40) 0.34 (0.31–0.37) 0.32 (0.29–0.34) 0.28 (0.25–0.30) 0.25 (0.29–0.27) –0.02 <.001
aValues expressed as mean and 95% condence interval.
bValues expressed as means for the daily consumption of the quintile.
cRegression coecient of the polyphenol intake in the diet on the daily consumption (g/day) of ultra-processed foods, adjusted for sex, age and family income.
actions are needed between the government and the
industry to implement fiscal policies aiming at
increasing taxes on such products and restricting
their availability in stores, as well as legal and other
regulations for the labelling, promotion and adver-
tising of ultra-processed products (Organização
Pan-Americana da Saúde 2018). Furthermore, it is
necessary to reinforce the importance of healthy eat-
ing to promote and protect good health and overall
well-being through policies that can reverse the
increase in consumption of ultra-processed foods
and promote increased consumption of fresh and
minimally processed foods (Ministério da Saúde
2014; Ministerio de Salud 2016) to restore an ade-
quate intake of nutrients and phenolic compounds
beneficial to overall health. Legal regulations are
needed to encourage farming and trade of fresh
foods, coupled with educational campaigns to protect
and promote family farming (Ministério da Saúde
2014; Organização Pan-Americana da Saúde 2018).
However, this article must be interpreted in light of
some limitations. The methodology and research for
quantifying the phenolic content of foods are still new.
The polyphenol content of processed and ultra-processed
foods is based on an estimate from their ingredients,
and therefore the phenolic content of these foods is
possibly over estimated because it is not known what
fraction of the ingredients remains in the food after
the industrial processes (Rothwell et al. 2015).
Furthermore, the scientific evidence on the absorption
of polyphenols outside the cellular matrix of foods is
scarce (Manach et al. 2004; D’Archivio et al. 2010;
Marín etal. 2015; Stevens and Maier 2016). Nevertheless,
it is important to highlight that the present study is
one of the first to evaluate the intake of polyphenols
of foods according to the NOVA classification of 6892
adults participating in a cohort. In addition, a validated
FFQ (Azarias et al. 2021) was used regarding food
intake in the last year, allowing the knowledge of the
usual food consumption of such individuals.
We conclude that habitual consumption of
ultra-processed foods provides not only a high amount
of calories, sodium, fat and sugar, as already described
in the scientific literature, but also a deficient amount
of bioactive compounds such as total polyphenols and
their classes, since the higher the daily consumption
of such foods (g/day), the lower the quantity of poly-
phenols consumed. On the contrary, fresh and min-
imally processed foods are the most significant
sources of polyphenols, and their daily consumption
should be encouraged, as reinforced by the Food
Guide for the Brazilian Population, which dictates the

INTERNATIONAL JOURNAL OF FOOD SCIENCES AND NUTRITION 9
recommendations for a healthy diet based on the
degree of food processing.
Acknowledgements
The authors thank the Cohort of Universities of Minas
Gerais and the Grupo de Pesquisa e Ensino em Nutrição
e Saúde Coletiva for their support and encouragement.
Author contributions
Hillary Nascimento Coletro – analysis and interpretation of
data, and writing and review of the paper; Josena Bressan
– coordination of cohort CUME, management of nancial
resources, data interpretation and review of the paper;
Amanda Popolino Diniz – analysis of data and review of
the paper; Helen Hermana Miranda Hermsdor – coordi-
nation of cohort CUME, management of nancial resources,
data interpretation and review of the paper; Adriano Marçal
Pimenta – coordination of cohort CUME, management of
nancial resources, data interpretation and review of the
paper; Adriana Lúcia Meireles – analysis of data and review
of the paper; Raquel de Deus Mendonça – coordination of
the present study, design study, data analysis and interpre-
tation, and review of the paper; Júlia Cristina Cardoso
Carraro – coordination of the present study, design study,
data analysis and interpretation, and review of the paper.
Disclosure statement
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that
could be construed as a potential conict of interest.
Data availability statement
e authors declare that all data are available upon previous
request.
Funding
e authors are thankful for the funding by Universidade
Federal de Ouro Preto, Coordenação de Aperfeiçoamento
de Pessoal de Nível Superior, Brazil (CAPES) and Fundação
de Amparo à Pesquisa do estado de Minas Gerais
(FAPEMIG (CDS-APQ-00571/13, CDS-APQ-02407/16,
CDS-APQ-00424/17 and CDS-APQ-03008/18)).
0
20
40
60
80
100
Total
Polyphenols
Phenolic AcidsFlavonoidsLignansStilbenes
C- Major ultra - processed foods that contribute to the
intake of polyphenols
Whole-grain breadIndustrial fruit juiceChocolate milk
PizzaLoaf breadDark chocolate
So
y
milk Popcorn Chocolate cand
y
0%
20%
40%
60%
80%
100%
Total
Polyphenols
Phenolic Acids Flavonoids LignansStilbenes
A -Major fresh/minimally processed foods that contribute
to the intake of polyphenols
Coffee Nuts
Canjiquinha/Polenta/Fried Polenta/Corn Canjiquinha/Polenta/Fried Polenta
Orange/Tangerine Grape
Beans/Lentil Apple/ Pear
Peach/Plum/Nectarine Strawberry/Cherry
0%
20%
40%
60%
80%
100%
Total
Polyphenols
Phenolic AcidsFlavonoidsLignans Stilbenes
B -Major processed foods that contribute to the intake of
polyphenols
Red Wine Beer Fruit JamPeach/Guava/Fig jamWhite/Rosé wine
%
%
%
%
%
%
Figure 3. Main foods, according to NOVA classication, that contribute to the intake of polyphenols of the participants (n = 6892),
CUME study, 2016–2020.

10 H. N. COLETRO ETAL.
ORCID
Hillary Nascimento Coletro http://orcid.
org/0000-0002-9142-6079
Josena Bressan http://orcid.org/0000-0002-4993-9436
Amanda Popolino Diniz http://orcid.
org/0000-0002-3300-0440
Helen Hermana Miranda Hermsdor http://orcid.
org/0000-0002-4441-6572
Adriano Marçal Pimenta http://orcid.
org/0000-0001-7049-7575
Adriana Lúcia Meireles http://orcid.
org/0000-0002-1447-953X
Raquel de Deus Mendonça http://orcid.
org/0000-0001-7599-8715
Júlia Cristina Cardoso Carraro http://orcid.
org/0000-0003-0027-2690
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