ArticlePDF Available

Purchases of ready-to-eat cereals vary across US household sociodemographic categories according to nutritional value and advertising targets

Authors:

Abstract and Figures

To describe ready-to-eat (RTE) cereal purchases in 2008 in the USA according to cereal nutritional quality and marketing strategy and household sociodemographic characteristics. Cross-sectional study of purchases in one year. Each type of cereal was assigned to one of four nutrition quality categories (based on Nutrient Profile Index, NPI) and one of four advertising categories based on television exposure and analysis of packaging (child-targeted, family-targeted, adult-targeted and no television advertising). Medians and distributions of purchase indicators were calculated for the cereal categories and the distributions were compared across sociodemographic groups. RTE cereals (n 249) with complete label and nutritional content. RTE cereal purchases according to household sociodemographic characteristics obtained from Nielsen Homescan, a nationally representative panel of households. Purchases of RTE cereals were highest in households with one or more child and lowest in African-American and Asian households, as well as those earning <$US 30 000 per annum. The lowest-quality products were purchased by four times as many households as the highest-quality cereals, but loyalty to these products was lower. Purchases of cereals by households with children and in African-American and Hispanic households increased as cereal nutritional quality declined. Compared with non-advertised products, advertised child-targeted cereals were purchased thirteen times more frequently; family-targeted brand purchases were ten times higher; and adult-targeted cereals were purchased four times more frequently. Our findings suggest that improving the nutritional quality of RTE cereals with advertising targeted to children could also lead to increased consumption of healthier products by young people.
Content may be subject to copyright.
Public Health Nutrition: page 1 of 10 doi:10.1017/S1368980011003065
Purchases of ready-to-eat cereals vary across US household
sociodemographic categories according to nutritional value
and advertising targets
Katia Castetbon
1,2,
*, Jennifer L Harris
2
and Marlene B Schwartz
2
1
Usen, Institut de veille sanitaire/Universite
´Paris 13, 74 rue Marcel Cachin, F-93017 Bobigny Cedex, France:
2
Rudd Center for Food Policy and Obesity, Yale University, New Haven, CT, USA
Submitted 18 February 2011: Accepted 25 October 2011
Abstract
Objective: To describe ready-to-eat (RTE) cereal purchases in 2008 in the USA
according to cereal nutritional quality and marketing strategy and household
sociodemographic characteristics.
Design: Cross-sectional study of purchases in one year. Each type of cereal was
assigned to one of four nutrition quality categories (based on Nutrient Profile
Index, NPI) and one of four advertising categories based on television exposure
and analysis of packaging (child-targeted, family-targeted, adult-targeted and no
television advertising). Medians and distributions of purchase indicators were
calculated for the cereal categories and the distributions were compared across
sociodemographic groups.
Setting: RTE cereals (n249) with complete label and nutritional content.
Subjects: RTE cereal purchases according to household sociodemographic
characteristics obtained from Nielsen Homescan, a nationally representative panel
of households.
Results: Purchases of RTE cereals were highest in households with one or more
child and lowest in African-American and Asian households, as well as those
earning ,$US 30 000 per annum. The lowest-quality products were purchased by
four times as many households as the highest-quality cereals, but loyalty to these
products was lower. Purchases of cereals by households with children and in
African-American and Hispanic households increased as cereal nutritional quality
declined. Compared with non-advertised products, advertised child-targeted
cereals were purchased thirteen times more frequently; family-targeted brand
purchases were ten times higher; and adult-targeted cereals were purchased four
times more frequently.
Conclusions: Our findings suggest that improving the nutritional quality of
RTE cereals with advertising targeted to children could also lead to increased
consumption of healthier products by young people.
Keywords
Food advertising
Nutritional values
Purchases
Ready-to-eat cereals
Sociodemographic categories
Breakfast is an important part of a healthful diet, because it
facilitates energy balance over the day and typically supplies
major nutrients
(1)
. Consuming breakfast (compared with
skipping breakfast) has been associated with weight gain
prevention
(2)
and positive health status in general
(1)
.Young
people, especially teenagers, are at high risk of skipping
breakfast
(3–5)
, with one out of five 9–13-year-olds and a
third of 14–17-year-olds regularly skipping breakfast in the
USA in 1999–2006
(5)
.
Ready-to-eat (RTE) cereals are one common choice for
breakfast. RTE cereal consumption increased through the
mid-1990s in the USA
(4)
; a third of children (9–13 years
of age) and a quarter of adolescents (14–18 years) ate
RTE cereals for breakfast in the first half of the 2000s
(5)
.
RTE cereals provide carbohydrates including fibre and
micronutrients (due to enrichment widely practised since
the 1970s), but low fat content
(1)
. They have therefore
been recommended as components of a healthful
breakfast, together with dairy products (milk is usually
consumed with RTE cereals) and fruit (fresh or juice)
(6)
.
The research documenting the health benefits of RTE
cereals typically compares this choice with skipping
breakfast altogether
(7)
or with high-fat breakfast options
such as those including fried eggs, cheese, bacon or
sausage
(8)
. As shown in a controlled study
(9)
, the benefit
of RTE cereal consumption was sizeable only when
accompanied by nutritional education, suggesting that the
positive impact is probably due more to other healthy
SPublic Health Nutrition
*Corresponding author: Email katia.castetbon@univ-paris13.fr rThe Authors 2011
behaviours associated with such food choices than to the
nutritional quality of the products consumed.
One feature of RTE cereals is their wide variation in
nutritional composition across brands; specifically, some
products contain sizeable amounts of added sugars and
salt
(10)
. Child-targeted RTE cereals are of special concern
(11)
because they are more energy-dense and contain higher
amounts of sugars compared with their adult-targeted
counterparts. Previous studies have found that RTE cereals
of low nutritional quality continue to be advertised exten-
sively to children
(10)
despite cereal companies’ pledges to
reduce marketing of unhealthy products to children
(12)
.
Importantly, during the 2003–2007 period, exposure to RTE
cereal advertising decreased among 2–5-year-old children
(223 %), but remained relatively constant among older
children (23%) and adolescents (20?8%)
(13)
. Different
advertising exposure trends were also observed by cereal
manufacturer. For example, both General Mills and Kellogg
participate in the children’s food marketing pledges, but
older children’s exposure to General Mills advertising went
down by 10 % during that period whereas exposure to
Kellogg advertising went up by 7 %. Similarly, exposure
to advertising by younger children went down by 30 %
for General Mills products, but by just 11 % for Kellogg
products. Manufacturers also committed to reduce the
sugar and Na contents of cereals marketed to children
(10)
.
However, as of early 2009, the average nutritional quality of
children’s cereals improved by only 2–5 % v. formulations
in 2007
(10)
. In addition, how these small improvements
influence RTE cereal purchases and intake, especially in
children and adolescents, remains to be understood
(14)
.
Recent observations on RTE cereals intake are also needed.
Studying RTE cereal purchases can contribute to our
understanding of the relationship between nutritional
quality, marketing and product intake
(15)
. Databases of
individual dietary intake assessments (such as 24 h
recalls) contain little or no information about brands
of manufactured products consumed, and generic foods
do not take into account variations in nutritional content
from one brand to another. Therefore, such surveys
do not enable analyses of specific nutrient variations
based on the exact products eaten
(16)
. Despite their
limitations
(17)
, databases designed to provide economic
information can be used to conduct detailed analyses of
purchase behaviours by finely classifying each RTE cereal
product according to its specific nutritional content and
comparing product purchases with advertising exposure.
Knowing how RTE cereal purchases vary according to
their nutritional content and advertising exposure could
lead to public health actions aimed at improving the
quality of products actually chosen by the population.
In addition, it is hypothesized that purchases vary across
sociodemographic categories of the population in relation
to the nutritional content and/or the advertising volume
and that different population categories may be prone to
‘respond’ differently to these factors. Improving access to
good-quality RTE cereals for subgroups of the population
so identified would also further public health action.
The objective of the present study was to describe
purchases of RTE cereal products in the US population
overall and across sociodemographic categories according
to (i) cereal nutritional content and (ii) product advertising,
including target market (child, family and adult) and
whether the product was advertised on television.
Methods
The Nielsen Homescan data (now ‘National
Consumer Panel’)
Panel recruitment and data collection
Nielsen recruits panel members, 18 years and older, living
in all US states and interested in participating in the
collection of data on their product purchases through its
dedicated website complementary to a random recruit-
ment. Participants are further selected on the basis of
sociodemographic characteristics they provide. Each time
they shop, they register the date, store name and location
of their purchases. They use a hand-held scanner to
register the barcode of all goods purchased along with
the quantity and whether the purchase was made with a
promotion or manufacturer’s coupons (specifying its
amount). They send the data once weekly through the
dedicated and secured website.
Based on the barcodes, Nielsen identifies the detailed
product and brand information, as well as weekly average
price when purchases are made at stores registered in the
store-level data (‘Scan Track’). Otherwise, volunteers
manually enter the price paid using a hand-held scanner.
Nielsen verifies this information according to the median
of prices in the area and corrects outlier entries (i.e. those
outside 99 % thresholds of acceptable actual prices). It
typically uses the median price that is most appropriate
for the store where the purchase has been made. The data
set used in the present analysis included RTE cereal
purchases made in 2008 by households in the Homescan
panel that provided any purchase registration for at
least 10 months during the year and purchased any RTE
cereal (n57 171).
Nielsen purchase indicators
Calibration based on the national census for household
size, household income, female head age, race, Hispanic
origin, male and female head education, head of house
occupation, presence of children and Nielsen county
size is carried out to provide national estimations for
sociodemographic characteristics and product purchases.
Based on the sociodemographic characteristics of
Homescan panel households, Nielsen provides estimates
for a nationally representative sample of households
and by sociodemographic category. The data set includes
the following measures for each RTE cereal in their
SPublic Health Nutrition
2 K Castetbon et al.
database: ‘Total spending’, the total dollars spent during
the year by the entire estimated population group; ‘Item
buyers’, the estimated total number of households who
bought the product during the year; ‘Buying rates’, the
mean annual spending per household on the cereal (in
dollars); ‘Purchase frequency’, the mean number of times
the product was bought during the year per household;
‘Purchase size’, the average amount spent per purchase
(in dollars); ‘Purchase cycle’, the average number of days
between two purchases; ‘Loyalty’, the average share of
spending for a given RTE cereal as a percentage of all
spending for RTE cereals during the year by households;
‘Dollars purchased on deal’, the share of total spending
when the product was on promotion at the store (in %);
and ‘Dollars with manufacturer coupon’, the share of total
spending using coupons supplied by manufacturers (in %).
Nielsen also computes an aggregated ‘volume index’
by sociodemographic category. The volume index
describes the extent to which the share of purchases of
a given RTE cereal, by households in a specific socio-
demographic category, compare with those that would
be expected given that category’s share of the total
population. The volume index is calculated by dividing
the percentage of RTE cereal spending in the socio-
demographic group by the percentage of the group in the
national population according to the US Census. A
volume index greater than 100 indicates that the group
purchases a higher-than-average amount of a given cereal;
whereas an index below 100 indicates that it purchases a
lower-than-average amount.
Nutrient content database and nutrient profiling
index model score computation
The detailed list of RTE cereals in the Homescan data set
included products purchased by a minimum of seventy-
five households during 2008, other products being
grouped into a summarizing category. This RTE cereal
list was then merged with a database of RTE cereals,
including nutrient content and advertising, developed for
a comprehensive analysis of the RTE cereal industry in
2008
(10)
. When the nutrient content was missing for a
given RTE cereal, it was completed by using manufacturer
websites and checking the nutrition facts on packaging in
the supermarket. This step was required for very few
cereals (,5 %), therefore it is unlikely to have biased the
final estimations. The nutrient data set included serving
size supplied by manufacturers and the content of energy
(kcal/serving), saturated fat (g/serving), sugar (g/serving),
fibre (g/serving) and Na (mg/serving). The nutrient content
database contained 573 registered RTE cereals.
The Nutrient Profile Index (NPI) score
(18)
was calcu-
lated for each product. The NPI is based on a model
developed for the Food Standards Agency (FSA) in the
UK and validated to reflect food quality assessments
by nutritionists
(19,20)
. The model takes into account both
‘positive’ (i.e. to encourage) and ‘negative’ (i.e. to limit)
nutrients together. Thus it provides a more nuanced
evaluation of foods’ nutritional quality based on their
entire nutrient composition. The original model was
launched to identify products that are healthy and can be
advertised to children on television in the UK; other
applications, with modified calculations, are currently
being evaluated for labelling products, for instance in
Australia and New Zealand (http://www.foodstandards.
gov.au/). Briefly, the model provides one score for indi-
vidual products based on points for components that
should be limited in the diet (energy, saturated fat, simple
sugars and Na; ‘A’ points) relative to points for components
considered favourable for a healthy diet (fruits, vegetables
and nuts, NSP fibre or AOAC (Association of Official
Analytical Chemists) fibre and protein; ‘C’ points). Points
are assigned based on nutrients in 100g of the product.
The overall score is then calculated by subtracting the
C points (from 0 to 15 points maximum) from the A points
(from 0 to 35 points maximum)
(18)
. In the original model, a
solid food is considered as ‘less healthy if it scores 4 or
more points. The initial model is difficult to interpret as
higher scores indicate lower nutritional quality, and the
range of scores falls between 215 and 35. Therefore, we
modified the original model calculation as follows
(10)
.
>The score was transformed as ‘(223NP score) 170’.
The new NP index (NPI) therefore falls between 0
[(22335 points) 170] and 100 [(223215 points) 1
70], with a higher NPI indicating better nutritional
content. An initial NP score lower than 4 points is
considered by FSA as a threshold for identifying
‘healthful products’. The corresponding threshold for
the NPI is therefore higher than 62 points.
>Since no information about AOAC and NSP fibre was
available separately, only the calculation for AOAC
fibre was used
(18)
.
Targeted advertising exposure
The present study categorized RTE cereals using the
same method as the previous analysis that also examined
advertising and packaging for 277 RTE cereals and
classified them as ‘child-targeted’, ‘family-targeted’ or ‘adult-
targeted’
(10)
. Cereals were classified as child-targeted if
they advertised directly to children in 2008. Cereals were
classified as family-targeted if their packaging or marketing
copy indicated that they were appropriate to feed children
and/or families, but the researchers found no evidence
of marketing directed to children. All other cereals were
classified as adult-targeted. Products not advertised on
television at all in 2008 were categorized separately as ‘no
advertising’ in our analyses.
Statistical analyses
Based on the NPI describing the nutrient content of RTE
cereals, four categories of nutrient quality were created:
(i) very poor (,40 points); (ii) poor (40–49 points);
SPublic Health Nutrition
Ready-to-eat cereal purchases and advertising 3
(iii) fair (50–62 points); and (iv) good (.62 points). Given
that individual data at the household level were not
available for the Homescan panel, distributions (median
and 25th–75th percentiles) are used to describe purchase
indicators (number of buyers, purchase frequency, etc.)
and volume indices across the NPI advertising target
categories. Medians were preferred due to small sample
sizes in some subgroups. For volume indices, box-and-
whisker plots are also used to illustrate distributions across
target-advertising categories for some sociodemographic
groups. Nielsen recommends that a volume index less than
80 indicates ‘under-purchasing’ of the product by a given
sociodemographic group, and that a volume index higher
than 120 indicates that the RTE cereal is purchased in
amounts sizeably higher than expected given the share
of the group in the overall population. Indeed, Nielsen
considers a difference of 20 % as meaningful given the
standard errors usually observed for panel volume esti-
mates. Sociodemographic characteristics analysed here
were presence of any child at home (and if yes, the age
category of the child), household size, race/ethnicity,
female head-of-household education, income and geo-
graphic region. Statistical comparisons across categories
were carried out using ANOVA and trend tests when
appropriate. Statistical analyses were conducted using the
STATA statistical software package version 10?0(2007;Stata
Corporation, College Station, TX, USA).
Results
The Homescan data set included purchases of 290 different
RTE cereals. Of these cereals, five consisted of ‘Ralston
Food products (comprised of thirty-five various store
brands) and one observation summarized private label
product (‘CTL-BR’) purchases for which nutrition data
were not available; in 2008, these two categories repre-
sented 10?4 % of total purchases in dollars. In addition,
thirteen items consisted of RTE cereal in mixed cereal
packs (1?1% of the total purchases), nutritional content
was not available for an additional eighteen cereals (mostly
because they had been discontinued; 0?9 % of the total
purchases) and four items were excluded because they
were not RTE cereals (cereal straws or wheat germ; 0?5%
of the total purchases in 2008). The 249 RTE cereals
included in the final analysis represented 87?1 % of total
purchases in US dollars in 2008.
Ready-to-eat cereal purchases across household
sociodemographic categories
Based on medians (25th–75th percentiles) of volume
index (‘All’ column, Table 1), purchases of RTE cereals
were lower than average (volume index median ,80) in
households with one member, African-American and
Asian households, and households earning ,$US 30 000
per annum. Purchases were also low (volume index
median ,90) in households in which the female head of
household was not a high-school graduate and those
without children in the home. In contrast, RTE cereal
purchases were higher than average (volume index
median .120) in households with five or more members
and those with at least one child of any age. In addition,
median volume indices increased regularly with the
number of household members, female head-of-household
education and income (Table 1).
Purchase indicators according to ready-to-eat
cereals’ nutrient quality
RTE cereals were distributed across NPI categories as
follows: very poor (,40), n46 (18?5 %); poor (40–49),
n69 (27?8 %); fair (50–62), n89 (35?7 %); and good
(.62), n45 (18?1 %). Most RTE cereals contain little or no
saturated fat, protein or vegetables/fruits/nuts per 100 g;
the variation between cereal NPI scores is mostly due to
differences in sugar, fibre and Na content. Indeed, the
higher the NPI range, the lower the sugar content and the
higher the fibre content (Table 2). Variations in Na are not
sizeable in the lowest three NPI categories, but the Na
median is much lower in the ‘good’ quality products. In
addition, slightly higher energy content was observed as
the NPI score decreased.
Purchase indicators varied significantly across nutrient
content categories, with the exception of purchase fre-
quency (P50?10; Table 3). With improvement in NPI,
the number of buyers decreased (P50?01) but loyalty
increased dramatically (P,0?001). Buying rates per annum
andpurchasesize(P50?002) increased with nutritional
quality; whereas the purchase cycle (i.e. time between
two purchases) decreased (P,0?001). Finally, share of
purchases using coupons or promotions was lowest in the
extreme nutrient profile categories (NPI ,40 and NPI .62)
and highest in the two intermediate categories (Table 3).
In each household sociodemographic group, volume
index varied across nutrient content categories (Table 1).
The RTE cereal volume index decreased when nutritional
quality increased in households with at least one child,
while the opposite occurred in households without
children. A similar pattern was also observed for household
size (volume index increased in households with one or
two members and decreased in households with three
or more members) and according to female head-of-
household education level (volume index decreased with
nutritional quality in the first three education categories, but
increased for households with a college graduate female
head of household). Moreover, variations across nutritional
content categories differed according to race/ethnicity:
the volume index increased with nutritional quality in
Caucasian households, but decreased in Hispanic and
African-American households. Asian households showed a
different pattern with an increasing volume index up to the
fair (50–62) NPI category and then a decrease. RTE cereal
volume indices also increased significantly with nutritional
SPublic Health Nutrition
4 K Castetbon et al.
quality in the highest household income category ($$US
100 000 per annum) and in the East and West regions. By
contrast, volume indices decreased significantly with NPI
category in households earning $US 30 000–39 999 and
$US 50 000–59 999 per annum, as well as in the South
and Central regions.
SPublic Health Nutrition
Table 2 Energy and nutrient contents (median and 25th–75th percentiles) of ready-to-eat (RTE) cereals according to nutritional quality (NPI
category)-and target-advertising category-
-
, Homescan data, Nielsen, 2008
Energy (kJ/100 g) Energy (kcal/100 g) Sugar (g/100 g) Na (mg/100 g) Fibre (g/100 g)
nMedian 25th–75th Median 25th–75th Median 25th–75th Median 25th–75th Median 25th–75th
Nutritional quality (NPI range)-
Very poor (,40) 46 7004 6883–7234 1674 1645–1705 41?435?5–44?4 180 150–220 3?3 0–3?6
Poor (40–49) 69 6732 6485–7004 1609 1550–1674 32?117?0–25?0 180 150–230 3?73?3–7?1
Fair (50–62) 89 6485 6046–6686 1550 1445–1598 20?717?0–25?0 200 150–230 8?66?7–12?8
Good (.62) 45 6058 5933–6418 1448 1418–1534 13?31?5–19?3 10 0–120 10?99?1–13?6
Target-advertising category-
-
Child-targeted 17 6732 6565–7234 1609 1569–1705 37?532?3–41?4 180 140–180 3?73?4–6?7
Family-targeted 17 6494 6251–6778 1552 1494–1620 20?717?6–30?0 190 140–200 7?46?2–10?2
Adult-targeted 13 6276 5385–6565 1500 1287–1569 19?412?9–24?5 180 120–230 9?46?9–25?0
No advertising 202 6602 6301–7004 1578 1506–1674 23?716?7–33?3 170 130–220 6?73?3–10?9
NPI, Nutrient Profiling Index.
-For definition of NPI, see the Methods section and Rayner et al.
(18)
.
-
-
For definition of target-advertising categories, see the Methods section.
Table 1 Ready-to-eat (RTE) cereal volume index-(median and 25th–75th percentiles) according to nutritional quality (NPI category)-
-
,
Homescan data, Nielsen, 2008y
Nutrient quality (NPI range)
Very poor (,40) Poor (40–49) Fair (50–62) Good (.62) All
Median 25th–75th Median 25th–75th Median 25th–75th Median 25th–75th Median 25th–75th
Children at home
None ,18 years*** 43 38–57 76 47–92 97 80–112 111 93–127 85 56–106
Any ,6 years*** 192 165–216 152 113–204 100 66–162 77 53–132 136 80–186
Any of 6–12 years*** 239 202–279 152 116–224 99 72–133 63 40–126 132 81–206
Any of 13–17 years*** 229 202–262 141 111–199 101 77–127 71 43–125 125 86–196
Household size
1 member*** 27 19–36 45 30–63 68 54–84 90 67–105 56 33–79
2 members*** 50 41–64 84 60–110 109 86–130 127 96–139 94 63–123
3–4 members*** 151 135–158 129 107–144 106 89–128 89 65–110 117 92–142
$5 members*** 282 231–315 209 141–284 113 73–156 87 41–130 151 91–246
Race/ethnicity
Caucasian*** 101 96–106 105 99–110 108 100–111 113 107–118 106 99–112
African American*** 74 53–118 73 51–101 52 35–84 36 21–48 56 37–89
Asian 67 26–103 74 41–101 88 53–147 50 27–94 72 39–113
Hispanic** 122 98–139 100 72–125 97 66–128 74 49–106 98 69–129
Female head education
No high-school graduate** 111 73–161 94 68–122 69 37–99 80 55–102 83 52–114
High-school graduate*** 111 106–121 108 95–121 91 64–104 99 76–121 103 85–116
Some college*** 124 118–135 108 94–122 101 81–120 87 67–101 107 85–123
College graduate*** 103 76–119 117 94–131 129 107–159 121 93–141 118 94–140
Income ($US per annum)
,20 000 80 64–101 72 54–90 66 44–84 68 44–113 71 51–91
20 000–29 999 83 71–106 79 69–89 79 49–93 79 54–105 79 60–97
30 000–39 999* 107 85–131 103 88–116 86 65–105 87 61–109 94 72–114
40 000–49 999 112 95–126 100 83–111 89 74–116 93 74–121 100 82–119
50 000–69 999* 116 105–133 113 100–125 103 86–123 100 70–113 108 92–124
70 000–99 999 109 92–121 109 99–123 113 86–135 107 81–126 111 91–125
$100 000*** 86 55–114 107 85–125 123 103–149 126 87–167 112 86–139
Regionjj
East** 98 58–110 101 81–122 113 83–138 107 81–136 105 78–124
Central** 105 95–125 109 99–124 97 76–114 92 73–117 104 85–121
South 96 81–114 93 84–103 84 68–100 85 73–110 91 74–106
West* 107 85–127 101 78–112 104 79–141 111 80–125 104 79–125
NPI, Nutrient Profiling Index.
-Volume index 5ratio of RTE cereal spending in the sociodemographic group divided by percentage of the sociodemographic group in the US population.
-
-
For definition of NPI, see the Methods section and Rayner et al.
(18)
.
yComparison tests across NPI categories: *P,0?05, **P,0?01, ***P,0?001.
jjCensus definition.
Ready-to-eat cereal purchases and advertising 5
Purchase indicators according to whether the
product was advertised on television and by
target audience
Of the RTE cereals in the final analysis, forty-seven were
advertised on television in 2008. All child-targeted RTE
cereals with television advertising (n17) had an NPI score
in the very poor to poor range (,50). By contrast, eleven
of thirteen adult-targeted advertised cereals and twelve of
seventeen family-targeted cereals exhibited an NPI score
.50 (four and two cereals, respectively, scored .62).
RTE cereals that were not advertised on television in 2008
(n202) had the following distribution by NPI score:
17?4 % were very poor (,40), 27?7 % were poor (40–49),
35?6 % were fair (50–62) and 19?3 % were good (.62).
Nutrient content variations were observed by advertising
category (Table 2). Whereas the nutrient content of
no-advertised products fell between the three other
categories, the highest energy and sugar contents were
observed in child-targeted RTE cereals and the lowest
in the adult-targeted products. The Na content was
comparable across advertising categories.
Purchase indicators varied greatly by advertising target
(Table 4). Compared with cereals not advertised in 2008,
the median number of buyers for advertised child-
targeted RTE cereals was more than thirteen times higher,
buyers for advertised family-targeted products were ten
times higher and those for advertised adult-targeted
cereals were nearly four times higher. Purchase frequency
and dollar share using promotions or coupons were
also higher across the board for advertised compared
with not-advertised RTE cereals. Additionally, advertised
child-targeted RTE cereals exhibited unique purchase
SPublic Health Nutrition
Table 3 Ready-to-eat (RTE) cereal purchase indicators (median and 25th–75th percentiles) according to nutritional quality (NPI category)-,
Homescan data, Nielsen, 2008
Nutrient quality (NPI category)
Very poor (,40) Poor (40–49) Fair (50–62) Good (.62)
(n4–6) (n69) (n89) (n45)
Median 25th–75th Median 25th–75th Median 25th–75th Median 25th–75th
Number of buyers (31000) 2170 867–6093 1627 586–4967 731 333–2239 526 211–2029
Buying rates ($US)-
-
6?04?9–6?95?54?4–7?47?14?7–9?26?85?2–9?8
Purchase frequency (per annum) 1?81?5–2?11?71?4–2?01?71?4–2?11?91?4–2?3
Purchase size ($US) 3?25 3?03–3?69 3?36 3?0–3?75 3?88 3?54–4?26 3?83 3?24–4?21
Purchase cycle (d)y54 44–59 52 45–61 46 38–52 41 36–47
Loyaltyjj 5?34?2–5?95?13?6–7?26?74?4–8?66?95
?3–9?2
% on dealz18?46?9–32?329?416?6–35?629?220?4–36?620?911?8–29?8
% with coupons-- 2?50?7–7?24?01?8–10?46?11?3–11?31?70?4–5?4
NPI, Nutrient Profiling Index.
-For definition of NPI, see the Methods section and Rayner et al.
(18)
.
-
-
Mean annual spending per household on the cereal (in $US).
yAverage number of days between two purchases.
jjAverage share of spending for a given RTE cereal as a percentage of all spending for RTE cereals during the year by households.
zShare of total spending when the product was on promotion at the store.
--Share of total spending using coupons supplied by manufacturers.
Table 4 Ready-to-eat cereal (RTE) purchase indicators (median and 25th–75th percentiles) according to target-advertising category-,
Homescan data, Nielsen, 2008
Target-advertising category
Child-targeted Family-targeted Adult-targeted No advertising
(n17) (n17) (n13) (n202)
Median 25th–75th Median 25th–75th Median 25th–75th Median 25th–75th
Number of buyers ($1000) 11 165 8684–19 059 8646 1783–16 627 3354 2033–5779 869 331–2236
Buying rates ($US)-
-
6?45?2–7?97?75?6–10?17?95?8–9?86?34?6–8?2
Purchase frequency (per annum) 2?01?8–2?32?11?7–2?32?01?6–2?31?71?4–2?1
Purchase size ($US) 3?23?0–3?53?93?6–4?14?13?6–4?33?63?1–4?0
Purchase cycle (d)y60 54–63 49 44–56 44 42–47 46 38–54
Loyaltyjj 5?54?3–6?57?85?1–8?67?85?2–9?85?44
?0–7?6
% on dealz35?931?9–38?935?828?6–40?334?329?0–40?322?412?2–32?2
% with coupons-- 9?24?1–11?84?53?7–12?99?06?4–19?22?80?8–7?8
-For definition of target-advertising categories, see the Methods section.
-
-
Mean annual spending per household on the cereal (in $US).
yAverage number of days between two purchases.
jjAverage share of spending for a given RTE cereal as a percentage of all spending for RTE cereals during the year by households.
zShare of total spending when the product was on promotion at the store.
--Share of total spending using coupons supplied by manufacturers.
6 K Castetbon et al.
behaviours: their median purchase size was the lowest and
median purchase cycle was the highest of the advertised
categories. Finally, median loyalty for RTE advertised
cereals targeted to children was comparable to that of
not-advertised cereals, while advertised family- and adult-
targeted RTE cereals showed the highest loyalty.
In several population subgroups, RTE cereal volume
indices also varied according to whether products were
advertised or not and across target-advertising categories.
As would be expected, in households with at least
one child (Fig. 1a), volume indices were higher for child-
targeted advertised RTE cereals than for advertised cereals
targeted to families and adults (P,0?001). In contrast,
households without children purchased family- and
adult-targeted advertised RTE cereals more often (Fig. 1b).
Variations according to the number of household members
followed the same patterns (data not shown). Additionally,
Caucasian households (Fig. 2a) were less likely to purchase
child-targeted RTE cereals compared with family- and adult-
targeted RTE cereals (P,0?001), while African-American
households exhibited the opposite pattern (P,0?001;
Fig. 2b). Finally, in households in which the female head
of household had some college (P50?047), the volume
index (median (25th–75th percentile)) was higher for
advertised child-targeted RTE cereals (123 (116–128))
than for family-targeted (104 (96–117)), adult-targeted (90
(82–101)) and not-advertised RTE cereals (106 (84–124)).
For households in the remaining sociodemographic
categories, the volume index of RTE cereals did not
vary significantly according to whether the product was
advertised or the advertising target.
Discussion
Analyses of various aggregated indicators of RTE cereal
purchases highlight interesting variations across socio-
demographic categories in US households. RTE cereal
purchases varied according to nutritional value, television
advertising and target market. Nevertheless, the extent of
such variations was not the same across household
categories. Overall, these results illustrate the need for
improvement in the nutritional content of RTE cereals
advertised on television and targeted to children.
To our knowledge, such a detailed description of RTE
cereal-buying patterns across sociodemographic categories
has not been previously published. One study conducted in
1996 in Canada
(21)
showedthat,overall,RTEcerealswere
bought by fewer than half of households, and purchased
moreoftenwithincreasingeducationandincomeandwith
the presence of youth aged ,15 years at the dwelling. Our
observations based on purchase volume index are similar to
previous studies of US individual intake data. For adults
(22)
and children
(5)
, consumption of RTE cereals was lower in
African-American, Hispanic and low socio-economic status
households (based on education for adults and poverty-to-
income ratio for children in these studies) compared with
non-Hispanic white and high socio-economic status house-
holds. Lower purchases of RTE cereals could be markers of
low breakfast intake in these subgroups of the population as
RTE cereals are commonly consumed at breakfast. Given the
consequences of skipping breakfast on health
(1)
, this can be
considered a public health issue for which surveillance of
individual diet behaviours is necessary.
In the present study of 2008 purchases, US households
with at least one child bought relatively more RTE cereals,
which would be expected as many RTE cereals are
marketed as ‘kid products’. Nevertheless, households
with at least one child exhibited particularly elevated
purchases of RTE cereals of poor nutritional quality. This
can be related to the fact that while product advertising
was closely associated with buying patterns (purchases of
child-targeted advertised products were thirteen times
higher than not-advertised products), child-targeted pro-
ducts were also those with the poorest nutritional content
(i.e. in 2008 all child-targeted advertised products had
SPublic Health Nutrition
0
20
40
60
80
100
120
140
160
180
200
220
240
Child-
targeted
Family-
targeted
Adult-
targeted
No
advertising
Advertising category
Volume index
0
20
40
60
80
100
120
140
160
180
200
220
240
Child-
targeted
Family-
targeted
Adult-
targeted
No
advertising
Advertising category
Volume index
(a)
(b)
Fig. 1 Ready-to-eat (RTE) cereal volume index according to
target-advertising category in: (a) households including at least
one child; and (b) households without children (Homescan data,
Nielsen, 2008). Volume index 5ratio of RTE cereal spending
in the sociodemographic group divided by percentage of the
sociodemographic group in the US population; for definition of
target-advertising categories, see the Methods section
Ready-to-eat cereal purchases and advertising 7
an NPI ,50). Our observations together with previous
analyses
(23)
underline the potential impact of television
advertising on food-buying behaviours, especially for
advertising directed at children. Nevertheless, indicators
analysed here such as purchase frequency, time between
purchases and resulting loyalty suggest that buying beha-
viours for healthier products could increase with increased
advertising (adult-targeted products were bought four
times as often as products not advertised in 2008) and
potentially the use of promotions and coupons
(24)
.
Sociodemographic characteristics were also associated
with RTE cereal-buying patterns, in particular household
race/ethnicity and education of the female head of house-
hold. RTE cereal purchases made by white households were
rather homogeneous for all products (based on volume
index medians and 25th–75th percentiles). African-American
and Hispanic households under-purchased RTE cereals
overall, but they purchased more of the cereals with poorest
nutritional quality, especially the child-targeted advertised
RTE cereals. Similar buying patterns were found with
lower female head-of-household education, lower income
and southern region, and indicates that sociodemographic
groups for whom RTE cereal consumption is not the
norm in adults
(22)
maybemoresusceptibletoadvertising
directed towards their children and adolescents. Again,
these observations support the need to promote healthier
RTE cereals among population subgroups in which advertis-
ing seems to have a direct impact.
The present study has some limitations. First, we chose
to use a standardized nutrition score so that we could
classify products within the RTE cereal group according
to their nutritional quality. This does not tell us how
consuming these cereals influenced the entire diet over
a day
(18)
. Second, the requirements for participating in
the Homescan panel might produce biased estimations
despite the calibration of data on the census
(17)
. House-
holds must regularly register and transmit information
about their grocery store purchases which can be a time-
consuming process. Therefore, retired individuals may be
over-represented among one-member households relative
to young single adults. This potential self-selection bias
could explain why one-member households purchased
more RTE cereals of good nutritional quality. Further
research could examine the buying behaviours of young
SPublic Health Nutrition
0
20
40
60
80
100
120
140
160
180
200
220
240
Advertising category
Volume index
0
20
40
60
80
100
120
140
160
180
200
220
240
Advertising category
Volume index
0
20
40
60
80
100
120
140
160
180
200
220
240
Advertising category
Volume index
0
20
40
60
80
100
120
140
160
180
200
220
240
Advertising category
Volume index
Child-
targeted
Family-
targeted
Adult-
targeted
No
advertising
Child-
targeted
Family-
targeted
Adult-
targeted
No
advertising
Child-
targeted
Family-
targeted
Adult-
targeted
No
advertising
Child-
targeted
Family-
targeted
Adult-
targeted
No
advertising
(a) (b)
(c) (d)
Fig. 2 Ready-to-eat (RTE) cereal volume index according to target-advertising category in various race/ethnic groups: (a)
Caucasian; (b) African American; (c) Asian; and (d) Hispanic (Homescan data, Nielsen, 2008). Volume index 5ratio of RTE cereal
spending in the sociodemographic group divided by percentage of the sociodemographic group in the US population; for definition
of target-advertising categories, see the Methods section
8 K Castetbon et al.
single adults to evaluate whether they continue to pur-
chase the less-healthy cereals consumed when they were
younger and living with their parents. Third, these
aggregated data do not provide information about indi-
vidual household purchasing patterns nor individual
intake within households, especially by gender and age.
We assume that a product targeted to children purchased
by households with children is predominantly eaten
by children; however, parents may also consume these
cereals. Indeed, as previously mentioned, such house-
holds did not also purchase adult- and family-targeted
RTE cereals in higher quantities compared with other
households. Finally, our results are based on a cross-
sectional survey; therefore, we cannot make conclusions
about the direct impact of advertising on behaviours.
Experimental studies, such as naturalistic trials in ‘real
contexts’, are necessary to confirm a causal relationship.
In spite of these limitations, only these kinds of economic
databases enable researchers to attribute a precise nutri-
tional value to each product and to describe purchases
using various complementary indicators.
Conclusions
RTE cereal purchases are an interesting example to
understand the relationship between advertising, nutri-
tional quality and food purchase behaviours. Indeed, RTE
cereal advertising is widely targeted to children, but often
for products with nutritional quality that is far from
optimal. A great variety of products exists in the market
and advertising for high-quality products should be
encouraged given its probable effect on purchases. This is
relevant to improve diet, nutritional status and health
in the population categories which seem particularly
susceptible to food advertising according to our results
(e.g. households with children, African-American and
Hispanic households). Changes in food composition
toward lower contents of sugar and Na and higher fibre
content would be a complementary public health action.
The NPI model could be used to identify new product
formulations that would improve the overall nutritional
quality of different cereals. In addition, cost variance
analyses would help identify strategies to increase pur-
chases of healthy RTE cereals, which tend to be priced
higher than the less-healthy cereals. It would also be
interesting to conduct equivalent analyses for other
manufactured products containing sizeable amounts of
sugar, salt and/or fat.
Acknowledgements
The research was funded by the Robert Wood Johnson
Foundation and the Rudd Foundation. The authors declare
no conflict of interest. K.C. was a visiting researcher at
Rudd Center for Food Policy and Obesity at the time of
the study; she conceived the analysis design, carried out
analyses, interpreted results and drafted the manuscript.
J.L.H. contributed to the analysis design conception,
acquisition of data and interpretation of results, and
revised the manuscript. M.B.S. contributed to interpreta-
tion of results and revision of the paper. All authors
approved the final version of the paper for publication.
The authors are grateful to Vishnudas Sarda (Rudd Center)
for his help on data management.
References
1. Rampersaud GC, Pereira MA, Girard BL et al. (2005)
Breakfast habits, nutritional status, body weight, and
academic performance in children and adolescents. JAm
Diet Assoc 105, 743–760.
2. Timlin MT, Pereira MA, Story M et al. (2008) Breakfast
eating and weight change in a 5-year prospective analysis
of adolescents: Project EAT (Eating Among Teens).
Pediatrics 121, e638–e645.
3. Alexy U, Wicher M & Kersting M (2010) Breakfast trends in
children and adolescents: frequency and quality. Public
Health Nutr 13, 1795–1802.
4. Siega-Riz AM, Popkin BM & Carson T (1998) Trends in
breakfast consumption for children in the United States
from 1965–1991. Am J Clin Nutr 67, issue 4, 748S–756S.
5. Deshmukh-Taskar PR, Nicklas TA, O’Neil CE et al. (2010)
The relationship of breakfast skipping and type of break-
fast consumption with nutrient intake and weight status in
children and adolescents: the National Health and Nutrition
Examination Survey 1999–2006. J Am Diet Assoc 110,
869–878.
6. US Department of Agriculture (2010) MyPyramid for Kids
Web site. http://www.mypyramid.gov (accessed January
2011).
7. Albertson AM, Affenito SG, Bauserman R et al. (2009) The
relationship of ready-to-eat cereal consumption to nutrient
intake, blood lipids, and body mass index of children as they
age through adolescence. JAmDietAssoc109, 1557–1565.
8. Cho S, Dietrich M, Brown CJ et al. (2003) The effect of
breakfast type on total daily energy intake and body mass
index: results from the Third National Health and Nutrition
Examination Survey (NHANES III). J Am Coll Nutr 22,
296–302.
9. Rosado JL, del RA, Montemayor K et al. (2008) An
increase of cereal intake as an approach to weight reduction
in children is effective only when accompanied by nutrition
education: a randomized controlled trial. Nutr J 7,28.
10. Harris JL, Schwartz MB, Brownell KD et al. (2009) Cereal
FACTS: Evaluating the Nutrition Quality and Marketing of
Children’s Cereals. New Haven, CT: Rudd Center for Food
Policy & Obesity, Yale University; available at http://
www.cerealfacts.org/media/Cereal_FACTS_Report.pdf
11. Schwartz MB, Vartanian LR, Wharton CM et al. (2008)
Examining the nutritional quality of breakfast cereals
marketed to children. J Am Diet Assoc 108, 702–705.
12. Schwartz MB, Ross C, Harris JL et al. (2010) Breakfast cereal
industry pledges to self-regulate advertising to youth: will
they improve the marketing landscape? J Public Health
Policy 31, 59–73.
13. Powell LM, Szczypka G & Chaloupka FJ (2010) Trends in
exposure to television food advertisements among children
and adolescents in the United States. Arch Pediatr Adolesc
Med 164, 794–802.
14. World Health Organization (2006) Marketing of Food and
Non-alcoholic Beverages to Children. Report of a WHO
Forum and Technical Meeting, Oslo, Norway, 2–5 May 2006.
SPublic Health Nutrition
Ready-to-eat cereal purchases and advertising 9
Geneva: WHO; available at http://www.who.int/diet
physicalactivity/publications/Oslo%20meeting%20layout
%2027%20NOVEMBER.pdf
15. Larson NI, Story MT & Nelson MC (2009) Neighborhood
environments: disparities in access to healthy foods in the
US. Am J Prev Med 36, 74–81.
16. SlimaniN,DeharvengG,UnwinIet al. (2007) The EPIC
nutrient database project (ENDB): a first attempt to standardize
nutrient databases across the 10 European countries partici-
pating in the EPIC study. Eur J Clin Nutr 61, 1037–1056.
17. Einav L, Leibtag E & Nevo A (2008) On the Accuracy of
Nielsen Homescan Data. Economic Research Report no. 69.
Washington, DC: US Department of Agriculture, Economic
Research Service; available at http://www.ers.usda.gov/
Publications/ERR69/ERR69.pdf
18. Rayner M, Scarborough P, Lobstein T (2009) The UK Ofcom
Nutrient Profiling Model. http://www.dphpc.ox.ac.uk/bhfhprg/
publicationsandreports/publications/bhfhprgpublished/
nutrientprofilemodel (accessed January 2011).
19. Arambepola C, Scarborough P & Rayner M (2008)
Validating a nutrient profile model. Public Health Nutr
11, 371–378.
20. Scarborough P, Arambepola C, Kaur A et al. (2010) Should
nutrient profile models be ‘category specific’ or ‘across-the-
board’? A comparison of the two systems using diets of
British adults. Eur J Clin Nutr 64, 553–560.
21. Ricciuto L, Tarasuk V & Yatchew A (2006) Socio-demographic
influences on food purchasing among Canadian house-
holds. Eur J Clin Nutr 60, 778–790.
22. Siega-Riz AM, Popkin BM & Carson T (2000) Differences in
food patterns at breakfast by sociodemographic characteristics
among a nationally representative sample of adults in the
United States. Prev Med 30, 415–424.
23. Story M & French S (2004) Food advertising and marketing
directed at children and sdolescents in the US. Int J Behav
Nutr Phys Act 1,3.
24. Hawkes C (2009) Sales promotions and food consumption.
Nutr Rev 67, 333–342.
SPublic Health Nutrition
10 K Castetbon et al.
... Longacre et al. (2017) verified that exposure to TV commercials of cereals for children is associated with the family buying the advertised product [38]. According to Castetbon et al. (2012), households are 13 times more likely to buy those cereals aimed at children advertised on TV than unbranded cereals [39]. ...
... Longacre et al. (2017) verified that exposure to TV commercials of cereals for children is associated with the family buying the advertised product [38]. According to Castetbon et al. (2012), households are 13 times more likely to buy those cereals aimed at children advertised on TV than unbranded cereals [39]. ...
Article
Full-text available
1) Background: Childhood obesity is a public health problem. The purpose of this study was to know if exposure to commercial messages which advertise food products exerts any effect on the short-term consumption preferences of 4-to 6-year-old children. (2) Methods: A double-blind and randomized experimental design. Sample consisted of 421 boys and girls from twelve schools in a city in Spain. (3) Results: In three of the four product pairs shown, the products advertised in the intervention were preferred. In the results of applying the model for the first product pair presented, sugared cereals, the predictive variable which best explains the behavior of the preferences expressed is gender (Odds Ratio 0.285 (0.19-0.42); p < 0.05). For the second pair, chocolate cookies, the family's nationality has a strong weight in the model. As regards the regression model calculated for the last pair (filled rolls), the predictive variable which showed having more influence was gender. Boys had a 1.39 times higher risk of selecting the advertised product than girls. (4) Conclusions: The persuasive effect of commercials has shown to be influential in a general, immediate, and significant way only in the case of products with wide brand awareness. This study reinforces the importance of advertising and emphasizes the need to initiate measures to control the content of TV commercials.
... Children can also have a substantial impact on parental purchases through pester power in response to food marketing (11) . For example, a study conducted in the USA found that over the course of a year, household purchases of child-targeted cereals were thirteen times higher if they were advertised on television, and these purchases were highest in households with one or more children (12) . ...
Article
Full-text available
Objective To assess associations between self-reported advertising exposure to foods high in fats, salt and sugar and household purchases of energy, nutrients and specific product categories. Design A cross-sectional design was used. Advertising exposure data were gathered using a questionnaire administered to the main shopper of each household, and purchase data from supermarkets and other stores for these households were accessed for a 4-week period during February 2019. Setting Households in London and the North of England. Participants Representative households ( N 1289) from the Kantar Fast Moving Consumer Goods Panel. Main shoppers were predominantly female (71 %), with a mean age of 54 years (±13). Results Linear regression models identified that exposure to foods high in fats, salt and sugar advertising through traditional mediums (including broadcast and print), but not digital, transport, recreational or functional mediums, was associated with greater purchases of energy (9779 kcal; 95 % CI 3515, 16 043), protein (416 g; 95 % CI 161, 671), carbohydrate (1164 g; 95 % CI 368, 1886) and sugar (514 g; 95 % CI 187, 841). Generalised linear models showed that individuals who reported exposure to sugary drink advertising were more likely to purchase sugary drinks (1·16; 95 % CI 2·94, 4·99) but did not purchase more energy or nutrients from sugary drinks. There was no evidence of associations between exposure to advertising for sugary cereals or sweet snacks and purchases from these categories. Conclusions There was a strong influence of traditional advertising and sugar-sweetened beverage advertising on household food and drink purchases, thus supporting the need for advertising restrictions across traditional formats and for sugary drinks specifically.
... • Castetbon Harris et al (2012; US; sales data/crosssectional study of purchases in one year): Compared with non-advertised products, child-targeted RTE cereals advertised via TV and on-packet were purchased thirteen times more frequently; family-targeted brand purchases were ten times higher; and adult-targeted cereals were purchased four times more frequently. ...
Technical Report
Full-text available
This work was conducted at the request of the Centre for Population Health at the NSW Ministry of Health, to inform implementation of the relevant strategic direction of the NSW Healthy Eating Active Living (HEAL) Strategy 2013–2018. It is not intended to be an exhaustive review but rather to provide an indication of the rationale for intervening and the potential effectiveness of a broad range of policy options. It is also intended to inform ongoing stakeholder consultation regarding action with respect to the food environment. This consultation will necessarily take account of other evidence of effectiveness including likely reach and population impact, as well as implementation issues such as sustainability of effects, feasibility, acceptability, equity, and other factors affectingplanning and investment decisions. It is noted that no single action contained within this evidence synthesis will in itself be sufficient to affect weight status substantially at the population level. A portfolio of interventions within the food environment, alongside action to increase physical activity and reduce sedentary behaviours, is required to halt the progress of obesity and prevent chronic disease. This sentiment has been expressed many times previously but also recently in the McKinsey paper by Dobbs et al (November 2014) relating to an economic analysis for obesity prevention: “Existing evidence indicates that no single intervention is likely to have a significant overall impact. A systemic, sustained portfolio of initiatives, delivered at scale, is needed to reverse the health burden.” Similarly, no individual sector in society can address obesity acting on its own — neither governments, retailers, consumer-goods companies, restaurants, employers, media organisations, educators, healthcare providers, or individuals.Achieving the full potential impact requires engagement from as many sectors as possible. Ideally such actions would be contained within an overarching National Nutrition Policy in Australia. Finally, we would like to echo another sentiment of the McKinsey Global Institute discussion paper, that “… our analysis is by no means complete. Rather we see our work [on a potential program to address obesity] as the equivalent of the maps used by 16th-century navigators. Some islands were missing and some islands were misshapen in these maps, but they were helpful to the sailors of the era. We are sure that we have missed some interventions and over- or underestimated the impact of others. But we hope our work to be a useful guide….”
... Breakfast cereals are among the foods most often marketed to children (32,33). Products marketed to children, including RTE cereals, have a high number of health-related claims, even though many products with those claims do not meet national dietary guidelines or recommendations (34,35). ...
Article
Full-text available
Background: The use of advertising content strategies that suggest consuming a product will confer nutrient- and health-related benefits influences household food purchasing decisions, which increases consumption of energy-dense, nutrient-poor products. We examined the presence of marketing claims regarding nutrient content, health and nature in ready-to-eat (RTE) cereal packages in relation to the products' nutritional quality. Methods: A cross-sectional content analysis was conducted on 178 RTE cereal packages available in the six largest supermarket chains in four Colombian cities from August to November 2018. The nutritional quality of products was assessed through the nutrient profile model established by the Chilean Law of Food Labeling and Advertising law. Results: All products sampled exceeded the regulation threshold for at least one nutrient of concern (e.g., high-in calories and/or sugar). The majority (66.3%) of packages had claims related to nature, 57.3% had nutrient-content claims, and 15.7% had health benefit or risk avoidance claims. Most products with nature, nutrient-content, and health claims were high in energy (99.2, 98.0, and 92.9%, respectively) and sugar (88.1, 87.3, and 92.9%, respectively). Conclusion: RTE cereal products offered in major Colombian supermarket chains are heavily marketed using nutrition- and nature-related claims. Nearly all products with claims are high in energy and sugar, despite the messages conveyed by the claims to consumers. Results support the implementation of mandatory regulations restricting claims on food and beverage products high in nutrients of concern.
... For each participant, the arithmetic daily energy-weighted mean of the score was then calculated [11,14], ranging from -15 (most favorable diet) to 40 (poorest diet). To facilitate interpretation, the final FSAm-NPS-DI was converted into a scale theoretically ranging from 0 (poorest diet) to 100 (most favorable diet) [34,35]: ...
Article
Full-text available
PurposeTo estimate the 10-year change in the overall nutritional quality of adolescent and young adult’s diet, as measured by the modified Nutrient Profiling System of the British Food Standards Agency individual Dietary Index (FSAm-NPS-DI) which funds the Nutri-Score development, and in different components of this score, overall and according to the individual characteristics.Methods Two 24-h dietary recalls were carried out in 15- to 39-year-old respondents included in the Belgian Food Consumption Surveys in 2004 (n = 1186) and 2014 (n = 952). The weighted mean individual FSAm-NPS-DI was computed from all foods and beverages consumed, converted into a scale from 0 to 100 (from the poorest to the most favorable diet), and compared between survey years. Subject characteristics associated with the score, along with the mean daily intake of food groups, energy, and nutrients were explored in multiple linear regressions stratified by survey year and age group.ResultsThe weighted mean daily FSAm-NPS-DI significantly increased between 2004 and 2014 [2004: 55.3 (SEM: 0.2) vs. 2014: 57.4 (0.5), P < 0.001 in 15- to 18-year olds; 55.0 (0.6) vs. 58.1 (0.4), P < 0.001 in 19- to 25-year olds; 57.1 (0.4) vs. 58.5 (0.3), P < 0.01 in 26- to 39-year olds]. SFA intake decreased in all age groups, and sugar-sweetened beverage, sugar, sodium, and fiber intakes decreased among 15‒18-year olds. The nutritional quality changed unevenly according to sociocultural characteristics, levels of education and regions being the main sources of disparities.Conclusion The quality of diet improved overall between 2004 and 2014 among young people in Belgium, an uneven change that need to be confirmed in future surveys, following the implementation of the Nutri-Score.
... 20 NPI was chosen over other measures of nutritional quality because (1) the MenuStat data set had all the necessary measures to calculate NPI and (2) NPI has been validated previously and has been used to quantify the nutrition quality of chain restaurant menu items and packaged food items in the U.S. and United Kingdom. 21,[25][26][27][28][29] The NPI score is based on the United Kingdom Ofcom nutrient profiling model 30 and provides a single score based on the amount of positive and negative nutrients per 100 grams of a given food item. Detailed instructions for the NPI scoring system are available elsewhere. ...
Article
Introduction Fast food restaurants, including top burger chains, have reduced calorie content of some menu items in recent years. However, the extent to which the nutrition profile of restaurant menus is changing over time is unknown. Methods Data from 2,472 food items on the menus of 14 top-earning burger fast food chain restaurants in the U.S., available from 2012 to 2016, were obtained from the MenuStat project and analyzed in 2019. Nutrition Profile Index scores were estimated and used to categorize foods as healthy (≥64 of 100). Generalized linear models examined mean scores and the proportion of healthy menu items among items offered in all years (2012–2016) and items offered in 2012 only compared with items newly introduced in subsequent years. Results Overall, <20% of menu items were classified as healthy with no change from 2012 to 2016 (p=0.91). Mean Nutrition Profile Index score was relatively constant across the study period among all food items (≈50 points, p=0.58) and children's menu items (≈56 points, p=0.73). The only notable change in Nutrition Profile Index score or in proportion of healthy items was in the direction of menu items becoming less healthy. Conclusions At large chain burger restaurants, most items were unhealthy, and the overall nutrition profile of menus remained unchanged from 2012 to 2016. Future research should examine the nutrition profile of restaurant menus in a larger, more diverse sample of restaurants over a longer timeframe and examine whether results are robust when other measures of nutritional quality are used.
Article
Full-text available
Importance: There is widespread interest in the effect of food marketing on children; however, the comprehensive global evidence reviews are now dated. Objective: To quantify the association of food and nonalcoholic beverage marketing with behavioral and health outcomes in children and adolescents to inform updated World Health Organization guidelines. Data sources: Twenty-two databases were searched (including MEDLINE, CINAHL, Web of Science, Embase, and The Cochrane Library) with a publication date limit from January 2009 through March 2020. Study selection: Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines were followed. Inclusion criteria were primary studies assessing the association of food marketing with specified outcomes in children and adolescents (aged 0-19 years). Exclusion criteria were qualitative studies or those on advertising of infant formula. Of 31 063 articles identified, 96 articles were eligible for inclusion in the systematic review, and 80 articles in the meta-analysis (19 372 participants). Data extraction and synthesis: Two reviewers independently extracted data. Random-effects models were used for meta-analyses; meta-regressions, sensitivity analyses, and P curve analyses were also performed. Where appropriate, pooling was conducted using combining P values and vote counting by direction of effect. Grading of Recommendations Assessment, Development, and Evaluation was used to judge certainty of evidence. Main outcomes and measures: Critical outcomes were intake, choice, preference, and purchasing. Important outcomes were purchase requests, dental caries, body weight, and diet-related noncommunicable diseases. Results: Participants totaled 19 372 from 80 included articles. Food marketing was associated with significant increases in intake (standardized mean difference [SMD], 0.25; 95% CI, 0.15-0.35; P < .001), choice (odds ratio, 1.77; 95% CI, 1.26-2.50; P < .001), and preference (SMD, 0.30; 95% CI, 0.12-0.49; P = .001). Substantial heterogeneity (all >76%) was unexplained by sensitivity or moderator analyses. The combination of P values for purchase requests was significant but no clear evidence was found for an association of marketing with purchasing. Data on dental health and body weight outcomes were scarce. The certainty of evidence was graded as very low to moderate for intake and choice, and very low for preference and purchasing. Conclusions and relevance: In this systematic review and meta-analysis, food marketing was associated with increased intake, choice, preference, and purchase requests in children and adolescents. Implementation of policies to restrict children's exposure is expected to benefit child health.
Article
Introduction Sugar-sweetened beverages contribute a large proportion of added sugar in young children's diets; yet, companies market sugar-sweetened children's drinks extensively to children and parents. This study examines the changes in children's drink purchases by U.S. households with young children and the associations with marketing practices. Methods Longitudinal Nielsen U.S. household panel data provided monthly volume purchases by children's drink category (sugar-sweetened fruit drinks and flavored water and unsweetened juices) among households with young children (aged 1–5 years) from 2006 to 2017. Differences by household race/ethnicity and income were assessed. The 2-part models examined the associations between household purchases and marketing (including price and brand TV advertising) for each category, controlling for sociodemographics. Data were collected and analyzed in 2019–2020. Results Households’ volume purchases of children's fruit drinks and unsweetened juices declined from 2006 to 2017, whereas flavored water purchases increased. Non-Hispanic Black households purchased significantly more fruit drinks (351.23 fluid ounces/month, 95% CI=342.63, 359.82) than non-Hispanic White (204.43 fluid ounces/month, 95% CI=201.81, 207.05) and Hispanic (222.63 fluid ounces/month, 95% CI=217.11, 228.15) households. Low-income households purchased more fruit drinks and fewer unsweetened juices than higher-income households (p<0.001). TV brand advertising was positively associated with purchases across all categories, and this relationship was stronger for low-income households (p<0.05). Conclusions Despite expert recommendations that young children do not consume Sugar-sweetened beverages, households with young children purchase more sweetened fruit drinks than unsweetened juices. Extensive TV advertising for children's drink brands may exacerbate the racial and income disparities in sugar-sweetened beverage purchases. Public health initiatives to address sugar-sweetened beverage consumption by young children and restrictions on marketing sugar-sweetened beverages to children are necessary.
Article
Full-text available
We examined breakfast consumption patterns and trends between 1965 and 1991 for children (1-10 y old) and adolescents (11-18 y old) in the United States. The analysis was undertaken by pooling nationally representative samples obtained from the Nationwide Food Consumption Surveys of 1965 and 1977-1978 and the 1989-1991 Continuing Survey of Food Intakes by Individuals. Breakfast consumption, defined as the consumption of food, beverage, or both between 0500 and 1000, was the focus of the trends analysis. Descriptive results indicated a decline in breakfast consumption between 1965 and 1991, particularly for older adolescents aged 15-18 y; the rates for boys and girls declined from 89.7% and 84.4%, respectively, in 1965 to 74.9% and 64.7%, respectively, in 1991. Multivariate results indicated that breakfast consumption declined predominantly because of behavioral changes and not the population's changing sociodemographic patterns. The nutritional quality of foods consumed at breakfast has improved since 1965, with significant shifts toward consumption of lower-fat milk and smaller changes in other food groups. The improvement over time in the quality of food consumed at breakfast, however, is offset by the large percentage of persons aged > or = 11 y who do not presently consume breakfast. Given the association of obesity with less frequent breakfast consumption and the rise in obesity among persons of this age group, a renewed emphasis on the importance of breakfast is warranted.
Article
Full-text available
Researchers use Nielsen Homescan data, which provide detailed food-purchase information from a panel of U.S. households, to address a variety of important research topics. However, some question the credibility of the data since the data are self-recorded and the recording process is time-consuming. Matching purchase records from 2004 Homescan data with data obtained from a large grocery retailer, it is evident that quantities purchased are reported more accurately in Homescan than are prices. Many of the price differences may be driven by the way Nielsen imputes prices: when available, Nielsen uses store-level prices instead of the actual price paid by the household. There are also differences by household type in the tendency to make mistakes that are correlated with demographic variables. However, the fraction of variance explained by the documented recording errors is in line with other research data sets for which cross-validation studies have been conducted.
Article
Full-text available
Although breakfast is important for obesity prevention and dietary quality, breakfast skipping is a common behaviour. Knowledge of changes in breakfast habits may provide potential behaviour targets for intervention programmes. The present study describes the actual data on trends in breakfast habits and composition. A total of 7800 3 d dietary records of 1081 participants aged 2-18 years collected between 1986 and 2007 in the DONALD (Dortmund Nutritional and Anthropometric Longitudinally Designed) Study were analysed using mixed linear models. Breakfast was eaten at 78 % of all record days; regular breakfast (breakfast was eaten on all three recorded weekdays) was eaten in 75 % of records. During the study period, the number of records with regular breakfast decreased significantly in 6-12- and 13-18-year-olds (P = 0·0084 and 0·0350, respectively). Of all breakfast meals, 62 % were bread meals and 21 % were ready-to-eat cereal (RTEC) meals. RTEC meals nearly doubled from the youngest to the oldest age group (P < 0·0001). During the study period, the percentage of bread meals decreased, whereas the percentage of RTEC meals increased (P < 0·0001). A higher percentage of RTEC meals than the bread meals was in accordance with the food-based guidelines (36 % v. 20 %, P < 0·0001), i.e. a breakfast including grain, dairy and fruit/vegetables. In the DONALD Study sample, a negative age and time trend in breakfast consumption was verified. Interventions regarding breakfast habits should be aimed at adolescents and should focus on fruit/vegetables.
Article
Full-text available
Nutrient profile models have the potential to help promote healthier diets. Some models treat all foods equally (across-the-board), some consider different categories of foods separately (category specific). This paper assesses whether across-the-board or category-specific nutrient profile models are more appropriate tools for improving diets. Adult respondents to a British dietary survey were split into four groups using a diet quality index. Fifteen food categories were identified. A nutrient profile model provided a measure of the healthiness of all foods consumed. The four diet quality groups were compared for differences in (a) the calories consumed from each food category and (b) the healthiness of foods consumed in each category. Evidence of healthier diet quality groups consuming more of healthy food categories than unhealthy diet quality groups supported the adoption of across-the-board nutrient profile models. Evidence of healthier diet quality groups consuming healthier versions of foods within food categories supported adoption of category-specific nutrient profile models. A significantly greater percentage of the healthiest diet quality group's diet consisted of fruit and vegetables (21 vs 16%), fish (3 vs 2%) and breakfast cereals (7 vs 2%), and significantly less meat and meat products (7 vs 14%) than the least healthy diet quality group. The foods from the meat, dairy and cereals categories consumed by the healthy diet quality groups were healthier versions than those consumed by the unhealthy diet quality groups. All other things being equal, nutrient profile models designed to promote an achievable healthy diet should be category specific but with a limited number of categories. However models which use a large number of categories are unhelpful for promoting a healthy diet.
Article
Full-text available
In 2007, the Council of Better Business Bureaus created the Children's Food and Beverage Advertising Initiative to improve the nutritional profile of products marketed to children in the United States. We provide quantitative baseline data describing (a) the amount of child-directed breakfast cereal advertising in 2007; (b) an assessment of the nutritional value for all cereals advertised on television; and (c) the relationship between nutrition quality and child exposure to television advertising for major cereal brands. In 2007, the average American child viewed 757 cereal ads, and 98 per cent of these ads promoted unhealthy cereals that would be prohibited from advertising to children in the United Kingdom. Healthy cereals were advertised in 2007 in the United States, but adults, not children, were predominantly exposed to these ads. These quantitative methods can be used in the future to evaluate the impact of industry self-regulation efforts to improve the marketing landscape.
Article
Background Poor dietary patterns and obesity, established risk factors for chronic disease, have been linked to neighborhood deprivation, neighborhood minority composition, and low area population density. Neighborhood differences in access to food may have an important influence on these relationships and health disparities in the U.S. This article reviews research relating to the presence, nature, and implications of neighborhood differences in access to food. Methods A snowball strategy was used to identify relevant research studies (n=54) completed in the U.S. and published between 1985 and April 2008. Results Research suggests that neighborhood residents who have better access to supermarkets and limited access to convenience stores tend to have healthier diets and lower levels of obesity. Results from studies examining the accessibility of restaurants are less consistent, but there is some evidence to suggest that residents with limited access to fast-food restaurants have healthier diets and lower levels of obesity. National and local studies across the U.S. suggest that residents of low-income, minority, and rural neighborhoods are most often affected by poor access to supermarkets and healthful food. In contrast, the availability of fast-food restaurants and energy-dense foods has been found to be greater in lower-income and minority neighborhoods. Conclusions Neighborhood disparities in access to food are of great concern because of their potential to influence dietary intake and obesity. Additional research is needed to address various limitations of current studies, identify effective policy actions, and evaluate intervention strategies designed to promote more equitable access to healthy foods.
Article
To examine the trends in food advertising seen by American children and adolescents. Trend analysis of children's and adolescents' exposure to food advertising in 2003, 2005, and 2007, including separate analyses by race. Children aged 2 to 5 years and 6 to 11 years and adolescents aged 12 to 17 years. Television ratings. Exposure to total food advertising and advertising by food category. Between 2003 and 2007 daily average exposure to food ads fell by 13.7% and 3.7% among young children aged 2 to 5 and 6 to 11 years, respectively, but increased by 3.7% among adolescents aged 12 to 17 years. Exposure to sweets ads fell 41%, 29.3%, and 12.1%, respectively, for 2- to 5-, 6- to 11-, and 12- to 17-year-olds and beverage ads were down by about 27% to 30% across these age groups, with substantial decreases in exposure to ads for the most heavily advertised sugar-sweetened beverages-fruit drinks and regular soft drinks. Exposure to fast food ads increased by 4.7%, 12.2%, and 20.4% among children aged 2 to 5, 6 to 11, and 12 to 17 years, respectively, between 2003 and 2007. The racial gap in exposure to food advertising grew between 2003 and 2007, particularly for fast food ads. A number of positive changes have occurred in children's exposure to food advertising. Continued monitoring of food advertising exposure along with nutritional analyses is needed to further assess self-regulatory pledges.
Article
National data comparing nutrient intakes and anthropometric measures in children/adolescents in the United States who skip breakfast or consume different types of breakfasts are limited. To examine the relationship between breakfast skipping and type of breakfast consumed with nutrient intake, nutrient adequacy, and adiposity status. Children aged 9 to 13 years (n=4,320) and adolescents aged 14 to 18 years (n=5,339). Cross-sectional data from the National Health and Nutrition Examination Survey 1999-2006. Breakfast consumption was self-reported. A 24-hour dietary recall was used to assess nutrient intakes. Mean adequacy ratio (MAR) for micronutrients and anthropometric indexes were evaluated. Covariate-adjusted sample-weighted means were compared using analysis of variance and Bonferroni's correction for multiple comparisons among breakfast skippers (breakfast skippers), ready-to-eat (RTE) cereal consumers, and other breakfast (other breakfast) consumers. Twenty percent of children and 31.5% of adolescents were breakfast skippers; 35.9% of children and 25.4% of adolescents consumed RTE cereal. In children/adolescents, RTE cereal consumers had lower intakes of total fat and cholesterol and higher intakes of total carbohydrate, dietary fiber, and several micronutrients (P<0.05 for all) than breakfast skippers and other breakfast consumers. RTE cereal consumers had the highest MAR for micronutrients, and MAR was the lowest for breakfast skippers (P<0.05). In children/adolescents, breakfast skippers had higher body mass index-for-age z scores (P<0.05) and a higher waist circumference (P<0.05) than RTE cereal and other breakfast consumers. Prevalence of obesity (body mass index > or = 95th percentile) was higher in breakfast skippers than RTE cereal consumers (P<0.05) in children/adolescents and was higher in other breakfast consumers than RTE cereal consumers only in adolescents (P<0.05). RTE cereal consumers had more favorable nutrient intake profiles and adiposity indexes than breakfast skippers or other breakfast consumers in US children/adolescents.
Article
To examine sex differences and longitudinal changes in ready-to-eat (RTE) cereal and breakfast consumption in the Dietary Intervention Study in Children, and the relationship between RTE cereal intake with nutrient intake, blood lipids, and body mass index (BMI). Secondary analyses based on data from Dietary Intervention Study in Children, a randomized, controlled, multicenter, clinical trial with five sets of three 24-hour recalls. Children (n=660) from six clinics aged 8 to 10 years at study entry. Participants had serum low-density lipoprotein cholesterol levels between the 80th and 98th percentiles for age, and were followed for a mean of 7.5 years. Children were randomized to a total fat- and saturated fat-modified dietary intervention or usual care. Frequency of RTE cereal and breakfast consumption was examined by sex and age. Mixed models by sex were used to examine the relationship of RTE cereal consumption to average daily intake of nutrients, blood lipids, and BMI. For all children, RTE cereal and breakfast consumption declined with age. Boys consumed RTE cereal more often compared with girls. Except for energy, RTE cereal consumption was positively associated with all measures of nutrients for both sexes. In boys, higher RTE cereal consumption was associated with lower total and low-density lipoprotein cholesterol levels and lower BMI. Food and nutrition professionals should continue to educate youth and their parents on the nutritional benefits of routinely eating RTE cereal.
Article
Sales promotions are widely used to market food to adults, children, and youth. Yet, in contrast to advertising, practically no attention has been paid to their impacts on dietary behaviors, or to how they may be used more effectively to promote healthy eating. This review explores the available literature on the subject. The objective is to identify if and what literature exists, examine the nature of this literature, and analyze what can be learned from it about the effects of sales promotions on food consumption. The review finds that while sales promotions lead to significant sales increases over the short-term, this does not necessarily lead to changes in food-consumption patterns. Nevertheless, there is evidence from econometric modeling studies indicating that sales promotions can influence consumption patterns by influencing the purchasing choices of consumers and encouraging them to eat more. These effects depend on the characteristics of the food product, sales promotion, and consumer. The complexity of the effects means that sales promotions aiming to encourage consumption of nutritious foods need to be carefully designed. These conclusions are based on studies that use mainly sales data as a proxy for dietary intake. The nutrition (and economics) research communities should add to this existing body of research to provide evidence on the impact of sales promotions on dietary intake and related behaviors. This would help support the development of a sales promotion environment conducive to healthy eating.