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Ultra-processed foods and added sugars in the
Chilean diet (2010)
Gustavo Cediel
1,2
, Marcela Reyes
3,
*, Maria Laura da Costa Louzada
1,2
,
Euridice Martinez Steele
1,2
, Carlos A Monteiro
1,2
, Camila Corvalán
3
and Ricardo Uauy
3,4
1
Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil:
2
Center for
Epidemiological Studies in Health and Nutrition, University of São Paulo, São Paulo, Brazil:
3
Institute of Nutrition and
Food Technology (INTA), University of Chile, El Líbano 5524, Macul, Santiago, Chile:
4
Department of Nutrition and
Public Health Intervention Research, Faculty of Epidemiology and Population Health, London School of Hygiene
and Tropical Medicine, London, UK
Submitted 30 October 2016: Final revision received 10 April 2017: Accepted 8 May 2017
Abstract
Objective: To assess the consumption of ultra-processed foods and analyse its
association with the content of added sugars in the Chilean diet.
Design: Cross-sectional study of national dietary data obtained through 24 h recalls
and classified into food groups according to the extent and purpose of food
processing (NOVA classification).
Setting: Chile.
Subjects: A probabilistic sample of 4920 individuals (aged 2 years or above)
studied in 2010 by a national dietary survey (Encuesta Nacional de Consumo
Alimentario).
Results: Ultra-processed foods represented 28·6(
SE 0·5) % of total energy intake
and 58·6(
SE 0·9) % of added sugars intake. The mean percentage of energy from
added sugars increased from 7·7(
SE 0·3) to 19·7(SE 0·5) % across quintiles of the
dietary share of ultra-processed foods. After adjusting for several potential
sociodemographic confounders, a 5 percentage point increase in the dietary share
of ultra-processed foods determined a 1 percentage point increase in the dietary
content of added sugars. Individuals in the highest quintile were three times more
likely (OR =2·9; 95 % CI 2·4, 3·4) to exceed the 10 % upper limit for added sugars
recommended by the WHO compared with those in the lowest quintile, after
adjusting for sociodemographic variables. This association was strongest among
individuals aged 2–19 years (OR =3·9; 95 % CI 2·7, 5·9).
Conclusions: In Chile, ultra-processed foods are important contributors to total
energy intake and to the consumption of added sugars. Actions aimed at limiting
consumption of ultra-processed foods are being implemented as effective ways to
achieve WHO dietary recommendations to limit added sugars and processed
foods, especially for children and adolescents.
Keywords
Chile
Food processing
Ultra-processed foods
Energy intake
Added sugars
Ultra-processed foods are rapidly dominating the global
food system
(1)
. These products are formulated and man-
ufactured industrially employing processes and ingre-
dients not commonly used in traditional culinary
preparations
(2)
. Studies from Canada, Brazil and the USA
describe these products as being high in energy density
and high in free/added sugars content, with low fibre and
micronutrient densities, compared with unprocessed or
minimally processed foods (even when the latter are
combined with salt, sugar or fat used as culinary ingre-
dients)
(3–6)
. Cross-sectional and cohort studies have shown
significant positive associations between ultra-processed
food consumption and obesity
(7–9)
and other diet-related
non-communicable diseases
(10–13)
.
Several reports have concluded that a high intake of
added sugars increases the risk of weight gain
(14–17)
,
excess body weight
(16)
, obesity
(16–18)
, type 2 diabetes
mellitus
(16,18)
, higher serum TAG
(15–17,19)
, dyslipidae-
mia
(17)
, high blood cholesterol
(18)
, higher blood pres-
sure
(15,17–19)
, hypertension
(16)
, stroke
(16,18)
, CHD
(16,18)
,
cancer
(16)
and dental caries
(14–16,18)
. In fact, the WHO
guidelines recommend limiting free sugars intake to less
than 10 % of total energy intake to prevent excess body
weight and dental caries, and to less than 5 % for
Public Health Nutrition
Public Health Nutrition: page 1 of 9 doi:10.1017/S1368980017001161
*Corresponding author: Email mreyes@inta.uchile.cl © The Authors 2017
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additional health benefits
(14)
. Free sugars include sugars
added to foods by the manufacturer, cook and consumer,
plus sugars naturally present in honey, syrups and fruit
juices
(20)
. A recent report using nationally representative
dietary data from the USA (population aged >1 year)
showed a strong association between the consumption of
ultra-processed foods and the intake of added sugars,
suggesting the need to limit consumption of ultra-
processed foods as an effective way of reducing exces-
sive intake of added sugars
(21)
. Yet, these estimates are a
‘conservative’way to assess compliance with WHO dietary
goals as added sugars include sugars added to foods or
beverages during processing, preparation or at the table,
but exclude naturally occurring sugars in fruit juices
(22)
.
In Chile, a study based on data collected by a national
household food budget survey undertaken in 2006–2007
showed that ultra-processed foods and free sugars repre-
sented 52·8 and 16·1 % of total purchased energy,
respectively, but no analyses of the association between
these two variables were performed
(23)
. Information on
the intake of ultra-processed foods and added sugars and
on the association between these two variables is parti-
cularly relevant in Chile, given the large-scale food poli-
cies being implemented in this country such as an increase
in taxation of sugar-sweetened beverages and the law
regulating food labelling and advertising
(24)
. To address
this gap, we used intake data from the most recent
national dietary survey undertaken in Chile to assess the
consumption of ultra-processed foods and to analyse its
association with the dietary content of added sugars.
Methods
Data source and sampling
The data were obtained from the National Dietary Survey
(Encuesta Nacional de Consumo Alimentario, ENCA)
performed between November 2010 and January 2011.
The survey used probability sampling by clusters, with
stratification and multiple lottery stages, allowing it to
represent the Chilean population aged 2 years or above in
urban and rural areas of every geographic region: North,
Center, South, South (Austral) and Metropolitan. The sur-
vey response rate was 85·5 % for a total of 5753 individuals
excluding pregnant women and individuals who showed
signs of altered mental status. A final sample of 4920
individuals was studied
(25)
.
Dietary intake
All individuals were eligible for one 24 h dietary recall
interview, conducted using the US Department of
Agriculture (USDA) Automated Multiple-Pass Method
(26)
.
For children under 12 years of age, an adult caregiver
responded the interview. Adolescents aged between
13 and 18 years answered in the presence of the
caregiver. Individuals provided information on quantities
(using home measurements) and preparation methods of
each consumed food item, assisted by a photographic
‘atlas’of typical Chilean foods and recipes specifically
designed for this survey. Each home measurement was
converted to grams or millilitres using a standardized
conversion table. All reported values (n150 156) were
double checked and inconsistencies were verified by
telephone, resulting in no missing values
(25)
.
Food classification according to processing
Every reported food item was classified according to the
extent and purpose of food processing, following the
NOVA procedure
(2)
. Food items were sorted into mutually
exclusive food subgroups within: (i) unprocessed or
minimally processed foods (eleven subgroups: e.g. fresh
meat, roots and tubers, cereals, vegetables, legumes,
fruits); (ii) processed culinary ingredients (four subgroups:
e.g. plant oils, table sugar, animal fats); (iii) processed
foods (five subgroups: e.g. unpackaged fresh bread,
cheese, ham and salted meat, vegetables and fruits pre-
served in brine or sugar syrup); and (iv) ultra-processed
foods (seventeen subgroups: e.g. carbonated soft drinks,
sweet or savoury snacks, confectionery, industrial des-
serts, reconstituted meat products, shelf-stable or frozen
meals, industrial packaged bread)
(2)
. Details are displayed
in Table 1.
Assessing total energy and added sugars intakes
Energy and total sugars contents of reported food items
were calculated using the US Food Composition Table
(USDA National Nutrient Database for Standard Reference
Release 28)
(27)
. For each reported food item, a USDA food
code was assigned, taking into account the nutritional
information in the Chilean Food Composition Table
(28)
and in the Nutrient Fact Panels obtained from Chilean
packaged foods (80–120 % agreement in macronutrient
and energy contents was required in order to assign a food
code). Data on added sugars per food code were obtained
by merging the USDA database on added sugars (Food
Patterns Equivalents Database 2009–2010)
(22)
. For Chilean
food items not found in the USDA database, added sugars
were calculated using the algorithm proposed by the
nutrient profile model launched by the Pan American
Health Organization
(29)
.
Data analysis
First, we described the contribution of each of the NOVA
groups and subgroups to total energy intake and to total
added sugars intake for the overall sample. Thereafter,
we analysed the average energy contribution of ultra-
processed foods according to sociodemographic variables,
namely sex, age group (2–19, 20–49, 50–46, ≥65 years),
geographic region (North, Center, South, South (Austral)
and Metropolitan), urban or rural setting, family income
(1, 2, 3–5, ≥6 minimum wages) and years of schooling
of the head of the family (≤8, 9–11, ≥12 years),
Public Health Nutrition
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using unadjusted and adjusted Gaussian regression
analyses. For ordinal sociodemographic variables (age
group, family income, years of schooling), tests of linear
trend were performed. For categorical variables (sex,
geographic region, urban or rural) and ordinal variables
with no statistically significant linear trend, Wald tests were
used to identify significant differences between categories.
Gaussian regression analyses were also used to estimate
the association between the dietary contribution of ultra-
processed foods and the dietary content of added sugars
(both as proportions of total energy intake). The dietary
share of ultra-processed foods was transformed using
restricted cubic spline functions with knots at 5th, 27·5th,
50th, 72·5th and 95th percentiles, to allow for non-linearity
(the Wald test was used to assess non-linearity). We used
Poisson regression models to analyse the proportion of
individuals consuming more than 5 % and more than 10 %
of total energy from added sugars
(14,30)
across quintiles of
the dietary share of ultra-processed foods. We also repe-
ated these analyses stratifying by age group. Regression
models evaluating the association between ultra-
processed foods and added sugars were adjusted for
sociodemographic variables associated with dietary intake
of ultra-processed foods. Tests of linear trend were per-
formed to evaluate the effect of quintiles as a single con-
tinuous variable. The ENCA sample weights were used in
all analyses
(25)
. The Taylor series linearization variance
approximation procedure was used for variance estima-
tion in all analyses, in order to account for the complex
sample design and the sample weights. Data were ana-
lysed using the statistical software package Stata
version 14.
Results
Distribution of total energy intake by food group
The mean per capita daily energy intake among Chileans
aged 2 years or above was 7611 kJ (1819 kcal). One-third
(33·8 %) of the total energy intake came from unprocessed
or minimally processed foods and 11·0 % came from
processed culinary ingredients. The remaining energy was
nearly equally distributed between processed foods
(26·6 %) and ultra-processed foods (28·6 %; Table 1).
Within unprocessed or minimally processed foods, meat
was the leading contributor (7·3 % of total energy), fol-
lowed by roots and tubers, cereals, vegetables, legumes
and fruits (each subgroup contributing more than 2 % of
total energy intake). Among processed culinary ingre-
dients, plant oils (6·1 %) and table sugar (4·0 %) were the
most consumed; while within processed foods, fresh
bread provided the largest contribution to total energy
intake (22·0 %). Among ultra-processed foods energy
came from a diverse range of products (seventeen sub-
groups), led by carbonated soft drinks; cakes, cookies and
pies; sauces, dressings and gravies; reconstituted meats;
‘milk’-based drinks; ‘fruit’drinks/sweetened ‘waters’; and
salty snacks, each one contributing more than 2·0% of
total energy.
Distribution of energy intake from added sugars by
food groups
The mean per capita daily intake of energy from added
sugars was 1017 kJ (243·0 kcal) or 13·2 % of total energy
intake (Table 1). The group of ultra-processed foods
contributed more than half of total added sugars con-
sumption (58·6 %) mainly through soft drinks (24·1 %),
fruit and water drinks (8·8 %) and cakes, cookies and pies
(7·3 %). Processed culinary ingredients contributed 33·6%
of the total added sugars intake, mainly through table
sugar consumed as part of home-made drinks, desserts or
other preparations. A further 7·5 % of total added sugars
came from processed foods, mainly from fresh bread
(6·3 %).
Intake of ultra-processed foods according to
sociodemographic variables
As shown in Table 2, individuals who were younger, living
in urban areas, residing in the metropolitan region and
with a higher income presented a significantly higher
intake of ultra-processed foods, in both unadjusted and
adjusted models. A significant inverse linear trend was
observed between age and ultra-processed food con-
sumption, while a significant positive linear trend was
observed between family income and consumption of
ultra-processed foods. Even though an increased intake of
ultra-processed foods was observed among females and
heads of families with higher schooling, differences were
not statistically significant.
Crude and adjusted associations between
dietary share of ultra-processed foods and
added sugars intake
In unadjusted restricted cubic spline Gaussian regression
analysis, a direct linear association was found between the
dietary share of ultra-processed foods and the dietary
content of added sugars (coefficient for linear term =0·22;
95 % CI 0·08, 0·34; Wald test for linear term, P=0·001;
Wald test for all non-linear terms, P=0·07; Fig. 1). The
linear association remained fairly unchanged after adjust-
ing for several potential sociodemographic confounders:
age, urban or rural setting, geographic region and family
income (coefficient for linear term =0·20; 95 % CI 0·07,
0·34). Thus, a 5 percentage point increase in the dietary
share of ultra-processed foods determined a 1 percentage
point increase in the dietary content of added sugars. As
shown in Table 3, the dietary content of added sugars
increased significantly from 7·7 % in the lowest quintile of
the energy contribution of ultra-processed foods to 19·7%
in the highest quintile. After adjusting for potential socio-
demographic confounders, individuals in the highest
quintile of dietary share of ultra-processed foods had 50 %
Public Health Nutrition
Ultra-processed foods and added sugars 3
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Public Health Nutrition
Table 1 Distribution of total energy intake and energy intake from added sugars according to NOVA food group, and mean content of added sugars of each food group, in the diet of the Chilean
population aged 2 years or above (2010)*
Mean energy intake Mean energy intake from added sugars Mean content of added sugars
Absolute
(kcal/d)
Relative
(% of total energy intake)
Absolute
(kcal/d)
Relative (% of total energy
from added sugars)
% of energy from
added sugars
NOVA food group Mean SE Mean SE Mean SE Mean SE Mean SE
Group 1: Unprocessed or minimally processed foods 579·17·933·80·40·00·00·0
Meat 129·54·07·30·20·00·00·0
Roots and tubers 71·12·34·20·10·00·00·0
Cereals 69·72·84·20·20·00·00·0
Vegetables 65·62·03·80·10·00·00·0
Legumes 38·61·52·30·09 0·00·00·0
Fruits 37·91·72·30·10·00
·00·0
Eggs 29·21·61·60·08 0·00·00·0
Milk and plain yoghurt 25·51·61·60·10·00·00·0
Fish and seafood 9·71·20·50·08 0·00·00·0
Natural fruit juices 1·80·20·10·02 0·00·00·0
Other unprocessed or minimally processed foods†100·54·85·60·20·00·00·0
Group 2: Processed culinary ingredients 192·84·111·00·269·32·433·60·831·70·7
Plant oils 105·02·56·10·10·00·00·0
Table sugar 69·42·44·00·169·12·433·50·899·30·1
Animal fats 17·81·30·90·05 0·00·00·0
Other processed culinary ingredients‡0·70·10·04 0·08 0·20·05 0·10·04 31·54·3
Groups 1 + 2 771·912·044·80·669·32·433·60·89·90·3
Group 3: Processed foods 501·212·726
·60·46·70·37·50·41·30·06
Breads (fresh unpackaged) 405·99·522·00·44·90·16·30·31·10·02
Cheese 48·12·32·60·10·20·20·05 0·0
Ham and other salted, smoked or canned meat or fish 7·91·00·50·05 0·00·00·0
Vegetables, fruits and other plant foods preserved in brine or syrup 3·20·90·20·07 0·80·20·60·229·43·0
Other processed foods§ 36·27·21·30·20·80
·20·40·07 8·20·7
Group 4: Ultra-processed foods 545·512·828·60·5167·56·058·60·930·40·6
Soft drinks, carbonated 88·34·04·50·284·43·824·10·895·50·09
Cakes, cookies and pies 86·65·24·30·223·71·67·30·431·30·4
Sauces, dressings and gravies 55·32·12·90·09 3·30·32·10·112·20·7
Reconstituted meat 55·13·02·70
·11·10·07 0·80·07 2·10·07
‘Milk’-based drink 48·74·42·60·29·21·04·60·319·40·8
‘Fruit ’drinks/sweetened ‘water’44·42·92·50·119·41·58·80·645·11·5
Salty snacks 37·82·62·10·10·00·00·0
Ice cream and ice pops 28·92·51·50·110·50·94·10·341·50·9
Breads (packaged) 28·22·21·50·11·20·10·90·14·30·3
Sweet snacks 16·93·80·70·16·61·31·90·246·31·1
Sandwiches & hamburgers on bun (ready-to-eat/heat) 10·62·00·60·10·05 0·09 0·01·40·02
Breakfast cereals 8·81·00·50·06 2·30·31·10·226·61·5
Desserts 8·71·60·50·09 3·10·61·00·166·93·0
Instant and canned soups 8·03·70·40·20·10·05 0·10·03 10·91·9
Pizza (ready-to-eat/heat) 3·30·50·20·03 0·00·00·0
Frozen and shelf-stable plate meals 3·20·50·20·03 0·20·03 0·09 0·03 5·40·02
Other ultra-processed foods║12·81·30·70·07 2·30·31·70·225·60·9
Total 1819 22·4100·0243·05·7 100·013·20·2
To convert to kJ, multiply kcal value by 4·184.
*National Nutrition Examination Survey 2010, n4920.
†Other unprocessed or minimally processed foods: chilli pepper, garlic, basil, cinnamon, cumin, curry, merken, chamomile, oregano, plain water, coffee, tea, mate, noodles and powdered milk.
‡Other processed culinary ingredients: table salt, honey and vinegar.
§Other processed foods: chilli paste, wine and beer.
║Other ultra-processed foods: dehydrated soup, artificial sweeteners and distilled liqueurs.
4 G Cediel et al.
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greater probability of exceeding the 5 % added sugars
cut-off compared with those individuals in the lowest
quintile (adjusted prevalence ratio =1·5; 95 % CI 1·4, 1·6).
Similarly, those individuals in the highest quintile of
dietary share of ultra-processed foods were three
times more likely to exceed the 10 % cut-off compared
with those individuals in the lowest quintile (adjusted
prevalence ratio =2·9; 95 % CI 2·4, 3·4; Table 3).
Public Health Nutrition
Table 2 Dietary share of ultra-processed foods according to sociodemographic variables in the diet of the Chilean
population aged 2 years or above (2010)*
% of total energy intake from ultra-processed foods
Variable nMean 95 % CI Adjusted mean†95 % CI
Sex
Women 2988 29·127·9, 30·429·428·1, 30·6
Men 1932 28·126·6, 29·627·826·5, 29·2
Age group (years)
2–19 1374 37·635·7, 39·438·636·7, 40·6
20–49 1668 27·726·2, 29·126·725·2, 28·2
50–64 948 21·519·5, 23·621·819·7, 24·0
≥65 930 17·4‡15·9, 18·918·3‡16·8, 19·8
Residential area
Rural 610 22·5
a
20·7, 24·323·7
a
21·9, 25·5
Urban 4310 29·5
b
28·4, 30·629·3
b
28·3, 30·4
Geographic region
North 531 27·7
c
24·7, 30·727·5
c
24·4, 30·6
Center 1001 27·8
c
26·0, 29·628·5
c
26·8, 30·3
South 901 25·7
c
23·7, 27·726·7
c,d
24·8, 28·6
South (Austral) 535 26·6
c
23·6, 29·527·3
c
24·2, 30·4
Metropolitan 1952 31·1
d
29·4, 32·830·2
c,e
28·6, 31·8
Family income
1 minimum wage 1019 24·222·4, 26·125·824·0, 27·6
2 minimum wages 1319 28·827·2, 30·428·727·2, 30·3
3–5 minimum wages 871 30·828·5, 33·230·027·8, 32·2
≥6 minimum wages 922 30·8‡28·9, 32·730·1‡28·3, 31·9
Years of schooling of head of family
≤8 years 2420 28·527·0, 30·128·727·3, 30·1
9–11 years 1340 27·625·8, 29·327·425·7, 29·1
≥12 years 1160 29·928·2, 31·729·828·0, 31·6
Total 4920 28·627·7, 29·628·627·7, 29·6
a,b
Mean values within the residential area (a, b) or geographic region (c–e) column with unlike superscript letters were significantl y
different (P<0·05).
*National Nutrition Examination Survey 2010, n4920.
†Performed with a multiple linear regression model, averaging or otherwise integrating over the covariates (remaining variables in the table).
‡P≤0·001 for linear trend.
30
25
20
15
10
5
0
% of total energy intake from added sugars
0 20406080100
% of total energy intake from ultra-processed foods
40
Fig. 1 Association between the dietary share of ultra-processed foods and the dietary content of added sugars in the diet of the
Chilean population aged 2 years or above (2010)* determined by unadjusted restricted cubic spline Gaussian regression analysis
(, predicted value; , 95 % CI). *National Nutrition Examination Survey 2010, n4920
Ultra-processed foods and added sugars 5
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Similar associations between the dietary contribution of
ultra-processed foods and the dietary content of added
sugars were seen in all age groups, being more pro-
nounced among children and adolescents (see online
supplementary material, Supplemental Tables 1 to 3). For
instance, children and adolescents in the highest quintile
of ultra-processed food consumption were four times
more likely to exceed the 10 % added sugars cut-off than
those in the lowest quintile (adjusted prevalence ratio =
3·9; 95 % CI 2·7, 5·9). The same prevalence ratios were 2·7
(95 % CI 2·2, 3·3) among adults and 2·3 (95 % CI 1·8, 3·0)
among the elderly.
Discussion
In the Chilean diet, ultra-processed foods provided 28·6%
of total energy intake and contributed more than half of
total added sugars intake. A strong association was found
between the consumption of these products and the
dietary content of added sugars. After adjusting for several
potential sociodemographic confounders, a 5 percentage
point increase in the dietary share of ultra-processed foods
determined a 1 percentage point increase in the dietary
content of added sugars. The association between ultra-
processed food consumption and the dietary content of
added sugars was present in every age group, being more
pronounced among children and adolescents.
The estimated dietary share of ultra-processed foods in
Chile in 2010 was similar to that found in Mexico in 2012
(29·8 % of total energy intake; JA Marron, T Sánchez, ML
et al., unpublished results), lower than those found in
national surveys of industrialized countries such as the
USA (57·9%)
(21)
and Canada (47·7%)
(3)
, but greater than in
Brazil (21·5%)
(4)
. A higher share of ultra-processed foods
in Chile (52·8 % of total energy) was estimated for 2006–
2007 by Crovetto et al.
(23)
. Two differences may explain
this discrepancy relative to our study: the origin of their
estimate was based on household food purchasing data
and the fact that all bread was classified as ultra-processed.
As in our study, recent evidence from the USA showed
that a 5 percentage point increase in the dietary share of
ultra-processed foods determined a 1 percentage point
increase in the dietary content of added sugars
(21)
. The US
data also showed that the mean percentage of total energy
intake from added sugars rose from 7·5 % in the lowest to
19·5 % in the highest quintiles of dietary share of ultra-
processed foods
(21)
. Similar results to our own were
obtained by two studies quantifying free sugars. In
Brazil
(4)
, the mean percentage of total energy intake from
free sugars increased from 10·9 % in the lowest to 20·2%in
the highest quintiles of dietary share of ultra-processed
foods; while in Canada
(3)
, free sugars increased from 7·7to
19·4 % across these quintiles.
Our study showed that the content of added sugars in
the Chilean diet (a total of 81·2 and 57·0 % of all individuals
Public Health Nutrition
Table 3 Indicators of the dietary content of added sugars according to the dietary contribution of ultra-processed foods in the diet of the Chilean population aged 2 years or above (2010)*
Indicators of the dietary content in added sugars
Dietary contribution of ultra-processed foods
(% of total energy intake) % of total energy from added sugars
Individuals with ≥5 % of total energy
from added sugars†
Individuals with ≥10 % of total energy
from added sugars†
Quintile Mean Range Mean SE %PR‡95 % CI PR
adj
§95%CI % PR‡95 % CI PR
adj
§95%CI
1st (n1095) 3·80–9·37·70·360·31·0–1·0–27·51·0–1·0–
2nd (n979) 14·49·3–19·910·20·377·41·31·2, 1·41·31·2, 1·445·01·61·4, 2·01·61·3, 2·0
3rd (n989) 25·719·9–31·713·60·487·61·41·3, 1·61·41
·3, 1·664·02·32·0, 2·72·31·9, 2·7
4th (n981) 39·231·7–47·414·90·588·01·41·3, 1·51·41·3, 1·566·92·42·1, 2·92·42·0, 2·8
5th (n876) 60·147·5–100 19·7║0·592·81·5║1·4, 1·71·5║1·4, 1·681·73·0║2·6, 3·52·9║2·4, 3·4
Total (n4920) 28·60–100 13·20·281·2–– – –57·0––––
PR, prevalence ratio; PR
adj
, adjusted prevalence ratio.
*National Nutrition Examination Survey 2010 (n4920).
†Cut-offs recommended for total energy intake from added sugars by WHO
(14)
.
‡PR estimated using Poisson regression.
§PR adjusted for age group (2–19, 20–49, 50–64, ≥65 years), residential area (urban and rural), geographic region (North, Center, South, South (Austral) and Metropolitan) and family income
(1, 2, 3–5, ≥6 minimum wages).
║P≤0·001 for linear trend.
6 G Cediel et al.
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exceeded the 5 and 10 % WHO cut-offs, respectively) was
closely associated with the consumption of ultra-
processed food. Indeed, individuals with the highest
consumption of ultra-processed foods (>47·5 % of energy
intake) were three times more likely to exceed the 10 %
cut-off compared with those having the lowest consump-
tion (<9·3 % of energy intake). Even though ultra-
processed food consumption was lower in Chile than in
the USA for all quintiles, this prevalence ratio was exactly
the same in both countries. Considering the evidence
relating consumption of added sugars to risk of chronic
diseases
(14–19)
and the current high prevalence of chronic
disease-related risk factors in the Chilean population
(31,32)
,
these results have important implications for the public
health agenda. This is especially true if we consider the
rapid increase in the consumption of selected ultra-
processed foods according to annual national food and
drink sales data collected between 1999 and 2013
(8)
and
according to household food expenditure data collected in
the Santiago metropolitan area between 1986 and 2007
(33)
.
Furthermore, our results support the regulations recently
implemented by the Chilean Government to improve
dietary quality, especially those targeting children and
adolescents
(24,34)
.
According to our study, almost 70 % of individuals in the
lowest quintile of dietary share of ultra-processed foods
met the <10 % cut-off for added sugars, even when the
intake of table sugar as culinary ingredient in the Chilean
population was comparatively high (33·5 % of total added
sugars intake v.8·7 % in the US population). This suggests
that in Chile, promoting diets based on unprocessed or
minimal processed foods, complemented with small
amounts of processed culinary ingredients and processed
foods (e.g. fresh bread), as recommended by recently
launched food-based dietary guidelines in Brazil
(35)
and
Uruguay
(36)
, would help achieve the WHO added sugars
recommendations
(14)
and the FAO advice for food secur-
ity
(37)
. Despite the cultural differences, this is also true in
countries such as the USA where more than 70 % of
individuals in the lowest quintile of dietary share of
ultra-processed foods met the <10 % cut-off for added
sugars
(21)
.
The present study is not without limitations. Even
though dietary data obtained by 24 h recalls are imperfect,
electronic surveys and the multiple-pass method were
used to prevent the interviewer from forgetting items fre-
quently omitted by interviewees
(26)
. In addition, although
information indicative of food processing such as place of
meals or product brands was collected, these data were
missing for some food items and thus may have led to
errors in food classification. Since Chile does not have an
updated Food Composition Table
(28)
, the intakes of
energy and total sugars were calculated using information
from the US Food Composition Table (USDA National
Nutrient Database for Standard Reference Release 28)
(27)
.
For foods lacking information on added sugars, the
algorithm proposed in the nutrient profile model launched
by the Pan American Health Organization
(29)
was used.
Therefore, the consumption of ultra-processed foods or
added sugars could be slightly under- or overestimated.
Evidence suggests that some people may under-report
consumption of foods with caloric sweeteners
(38–40)
. If so,
this bias may lead to underestimation of the overall intake
of added sugars or the dietary contribution of ultra-
processed foods, but may less likely affect the association
between these variables.
The present study has several strengths. It is based on a
large, nationally representative sample of the Chilean
population with data on individual consumption rather
than on market or household purchases, which do not
account for the fraction of wasted food. It is also the first
study to examine the contribution of ultra-processed foods
to total energy and added sugars intakes in the Chilean
diet, providing updated and relevant results for informing
the public health agenda. These may also serve as baseline
results to measure the impact of a set of regulations being
implemented by the Chilean Government aimed at
improving diets
(24,34)
.
Conclusions
We have documented that ultra-processed foods represent
close to one-third of total energy intake and contribute
more than half of total added sugars in the Chilean diet.
Developing strategies to limit and decrease the con-
sumption of ultra-processed foods is a potentially effective
way to achieve WHO dietary recommendations on added
sugars and to promote eating in accordance with food-
based dietary guidance in Chile, especially for young
children and adolescents.
Acknowledgements
Acknowledgements: The authors thank the Ministry of
Health of Chile for supplying the database (Chilean National
Dietary Survey, 2010) and the International Development
Research Center for its support in obtaining information from
Nutrient Fact Panels from packaged foods in 2015. Financial
support: The analyses were supported by the Fundaçâo de
Amparo à Pesquisa do Estado de São Paulo (FAPESP). G.C. is
abeneficiary of a Postdoctoral Fellowship from FAPESP
(grant number 2016/13522-3). FAPESP had no role in the
design, analysis or writing of this article. Conflict of interest:
The authors declare no conflict of interest. Authorship:
C.A.M., M.R. and G.C. designed the research. G.C., M.L.d.C.L.
and E.M.S. took care of data management and analyses.
G.C., M.R., C.C. and R.U. interpreted the data. G.C. and M.R.
wrote the first draft of the manuscript. All authors read,
edited and approved the final manuscript. Ethics of human
subject participation: Verbal consent was formally recorded.
Public Health Nutrition
Ultra-processed foods and added sugars 7
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