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The Growing Price Gap between More and Less Healthy Foods: Analysis of a Novel Longitudinal UK Dataset


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Objectives The UK government has noted the public health importance of food prices and the affordability of a healthy diet. Yet, methods for tracking change over time have not been established. We aimed to investigate the prices of more and less healthy foods over time using existing government data on national food prices and nutrition content. Methods We linked economic data for 94 foods and beverages in the UK Consumer Price Index to food and nutrient data from the UK Department of Health's National Diet and Nutrition Survey, producing a novel dataset across the period 2002–2012. Each item was assigned to a food group and also categorised as either “more healthy” or “less healthy” using a nutrient profiling model developed by the Food Standards Agency. We tested statistical significance using a t-test and repeated measures ANOVA. Results The mean (standard deviation) 2012 price/1000 kcal was £2.50 (0.29) for less healthy items and £7.49 (1.27) for more healthy items. The ANOVA results confirmed that all prices had risen over the period 2002–2012, but more healthy items rose faster than less healthy ones in absolute terms:£0.17 compared to £0.07/1000 kcal per year on average for more and less healthy items, respectively (p<0.001). Conclusions Since 2002, more healthy foods and beverages have been consistently more expensive than less healthy ones, with a growing gap between them. This trend is likely to make healthier diets less affordable over time, which may have implications for individual food security and population health, and it may exacerbate social inequalities in health. The novel data linkage employed here could be used as the basis for routine food price monitoring to inform public health policy.
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The Growing Price Gap between More and Less Healthy
Foods: Analysis of a Novel Longitudinal UK Dataset
Nicholas R. V. Jones
, Annalijn I. Conklin
, Marc Suhrcke
, Pablo Monsivais
1UK Clinical Research Collaboration (UKCRC) Centre for Diet and Activity Research, Department of MRC Epidemiology, University of Cambridge School of Clinical
Medicine, Addenbrooke’s Treatment Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom, 2Faculty of Medicine and Health Sciences, University of East
Anglia, Norwich, United Kingdom
The UK government has noted the public health importance of food prices and the affordability of a healthy
diet. Yet, methods for tracking change over time have not been established. We aimed to investigate the prices of more and
less healthy foods over time using existing government data on national food prices and nutrition content.
We linked economic data for 94 foods and beverages in the UK Consumer Price Index to food and nutrient data
from the UK Department of Health’s National Diet and Nutrition Survey, producing a novel dataset across the period 2002–
2012. Each item was assigned to a food group and also categorised as either ‘‘more healthy’’ or ‘‘less healthy’’ using a
nutrient profiling model developed by the Food Standards Agency. We tested statistical significance using a t-test and
repeated measures ANOVA.
The mean (standard deviation) 2012 price/1000 kcal was £2.50 (0.29) for less healthy items and £7.49 (1.27) for
more healthy items. The ANOVA results confirmed that all prices had risen over the period 2002–2012, but more healthy
items rose faster than less healthy ones in absolute terms:£0.17 compared to £0.07/1000 kcal per year on average for more
and less healthy items, respectively (p,0.001).
Since 2002, more healthy foods and beverages have been consistently more expensive than less healthy ones,
with a growing gap between them. This trend is likely to make healthier diets less affordable over time, which may have
implications for individual food security and population health, and it may exacerbate social inequalities in health. The novel
data linkage employed here could be used as the basis for routine food price monitoring to inform public health policy.
Citation: Jones NRV, Conklin AI, Suhrcke M, Monsivais P (2014) The Growing Price Gap between More and Less Healthy Foods: Analysis of a Novel Longitudinal
UK Dataset. PLoS ONE 9(10): e109343. doi:10.1371/journal.pone.0109343
Editor: Harry Zhang, Old Dominion University, United States of America
Received April 30, 2014; Accepted September 5, 2014; Published October 8, 2014
Copyright: ß2014 Jones et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The present study was undertaken by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. The
authors gratefully acknowledge the funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research
Council, the National Institute for Health Research, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration. AIC was fully supported
by the Gates Cambridge Trust. The funding sources had no role in the design and conduct of the study or in the collection, management, analysis, and
interpretation of the data.
Competing Interests: The authors have declared that no competing interests exist.
* Email:
The association between foods, nutrients and diets and certain
health outcomes is well established, [1] with the World Health
Organization identifying energy-dense, nutrient-poor foods that
are high in fat, sugar and salt as contributing to excess risk of
chronic disease. [2] Accordingly, dietary recommendations,
including those from the UK Department of Health (DH),
discourage the consumption of such foods and emphasise
vegetables and fruits, whole grains, low fat dairy foods and lean
sources of protein. [3] However, on average the UK population
consumes an excess of saturated fat and non-milk extrinsic sugars,
and fails to consume enough oily fish or fruit and vegetables,
falling short of government recommendations. [4] These patterns
have a marked effect on public health: the 2010 Global Burden of
Disease Study found that unhealthy diets accounted for 14.3% of
the UK’s disease burden (measured in disability-adjusted life
years). [5] The burden on the healthcare system is also
considerable with diet-related ill health estimated to be responsible
5.8 billion of National Health Service expenditure annually,
more than either smoking, alcohol consumption or physical
inactivity (based upon data from 2006–7). [6].
One factor that might limit the uptake of healthier diets is the
cost of healthier foods, which has not been recognised by the
majority of UK public health policy outside of the context of
national food security. [7,8] The notion that healthier foods are
more expensive and that this expense contributes to the
consumption of unhealthy diets is not new, and has a strong
evidence base and conceptual framework to support it. [9] In a
2013 survey, price was rated by UK consumers as the most
important factor influencing their choices of food products, with
39% stating it was the factor of greatest importance and 91%
listing it in their top five criteria. [10] In contrast, just 9% of UK
consumers considered a food’s healthiness to be the most
important factor and only 49% placed it in the top five. [10]
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These findings suggest that cost considerations may override
health concerns in consumer dietary choices.
Both researchers and policymakers have recognised that the
price of healthy diets and foods ought to be monitored to inform
public health nutrition policy but no monitoring system has
hitherto been established in the UK. [8,11] Here we outline a
method for examining the cost of foods in relation to nutrient
content by linking existing UK government economic and
nutrition surveillance data. Using the resulting dataset, we then
examine changes in the price of food between 2002 and 2012, by
Eatwell food group and by category of healthfulness as determined
by a widely used nutrient profiling score. Our approach to linking
such existing data could provide the basis for routine monitoring of
the affordability of healthy foods and diets, thereby allowing for a
better understanding of how price differs between more or less
healthy foods.
Ethics Statement
NDNS was conducted according to the guidelines laid down in
the Declaration of Helsinki and all procedures involving human
subjects were approved by the Oxfordshire A Research Ethics
Committee. Written informed consent was obtained from all
participants [12].
Methods summary
We obtained food price and nutrition data from two separate
and publicly available sources and linked the two together to
create a novel dataset. We then converted prices to a price-per-
unit-of-energy value and classified food items according to their
nutritional content and by food group. Finally, we compared the
mean prices of these categories in 2012 and examined the change
in price since 2002.
Food price data
We selected the foods and beverages in our sample from the list
of goods and services used to calculate the Consumer Price Index
(CPI), a tool used to measure inflation in the UK based upon a
basket of goods for which prices are measured across the nation
each quarter. [13] In 2012, this basket included 157 foods and
beverages which did not include an element of service, for
example, a hot meal in a pub. We excluded such items because the
cost of the service could not be separated from the cost of the food.
However, to ensure that a meaningful comparison was being made
over time, we restricted the contents of the basket analysed to
include only those goods that remained in the basket during our
study period between 2002 and 2012. Research in the USA has
indicated that market baskets that change over time can contribute
to apparent differences in the rate of change in the price of food
groups. [14] We further excluded an additional four items in the
basket as they contained no nutrients meaningful to the research
questions (Instant Coffee, Filter Coffee, Tea Bags, Bottled Mineral
Water), leaving a final list of 94 foods and beverages for
comparison across 10 years.
We took the median price for each good in a given quarter and
produced a mean value for the year, using data taken from the
Office for National Statistics. [15] These data were per-unit prices,
with no separate field for unit weight. To establish the price per
100 g, we used information on the purchased weight where it was
included in the food name (e.g. ‘‘Grapes per kg’’), or inferred the
purchased mass using information on similar items available for
purchase on an online supermarket aggregator, mySupermarket.
[16] We chose items from the site when the price was closest to the
2012 price taken from the CPI data. For items with variable
weights, e.g. peaches, we assigned the weight recorded for that
type of item in the USDA National Nutrient Database for
Standard Reference. [17] Using this combined method we
established a price per 100 g for all 94 items in our list.
Nutrition data
We obtained nutrition data from survey years 1–3 of the rolling
programme of the nationally-representative National Diet and
Nutrition Survey (NDNS), which was available from the Economic
and Social Data Service. [18] Foods consumed by 1,491 adult
survey respondents have their nutrient content reported in detail,
with the content of 60 nutrients and 27 disaggregated foods (e.g.
mass of dried fruit) per portion and total portion mass reported.
We removed non-nutrient information from the Food Level
Dietary Data file, removed duplicate entries, and converted the
values to a 100 g scale, thus creating a database of 3790 unique
foods and beverages.
Linkage process
We used a qualitative process to determine the most appropriate
NDNS items for each of the 94 items from the CPI list. Where
multiple NDNS items were deemed a suitable match for a CPI
item we calculated mean nutrition data, weighted by the frequency
of consumption for each NDNS item. We adopted this approach
to account for the fact that some CPI items were only described in
very broad terms and could cover a range of different foods (e.g.
‘‘frozen ready meal, cooked – serves 1’’), and also to account for
the range of different methods of preparation (for instance, a
potato could be boiled, baked or fried) which were associated with
NDNS food items and would alter the nutrient content. The most
NDNS items matched to any one item was 14 and the least was 1,
with a median of 2 NDNS items match for a given CPI item.
Once matches had been made, the nutrition data needed to be
adjusted to account for the fact that the NDNS data concern foods
as consumed and the CPI data foods as purchased. The
incongruence in the data occurs because there are either losses
or gains associated with preparation and cooking of many of the
listed foods. To remedy this we adjusted the CPI food price data so
that they expressed price in terms of price per 100 g edible
portion, using edible portion figures from the United States
Department of Agriculture’s Handbook 102 where necessary. [19].
Following this adjustment, we converted prices per 100 g into
price per 1000 kcal using the data on energy content provided by
the NDNS. We produced a dataset with detailed nutrient content
per 100 g and 11 years of data on price per 1000 kcal which
would allow us to analyse price changes over time in relation to
nutrient content.
Food group-based classification of foods
We classified food items in our new dataset according to five
distinct food groups, defined by the Eatwell Plate—a tool for
nutrition communication developed by the DH to define a healthy
diet. [3] The five groups analysed were: (i) bread, rice potatoes and
pasta; (ii) fruit and vegetables; (iii) milk and dairy foods; (iv) meat,
fish, eggs, beans and other sources of protein; and (v) food and
drinks high in fat and/or sugar. We assigned foods to food groups
using a reference table in the Livewell Report which matched
NDNS food categories to Eatwell food groups. [20] When NDNS
items corresponding to a CPI item included more than one food
group, we applied only one food group based on the item most
frequently consumed according to the NDNS survey data.
UK Food Price Trends and Nutrition 2002-2012
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Nutrient-based classification of foods
Food items were also classified as ‘‘more healthy’’ or ‘‘less
healthy’’ based upon nutrient profiling, a technique which
accounts for a food or drink’s overall nutritional characteristics.
We used the WXYfm model detailed in the DH’s Nutritional
Profiling Technical Guide, hereafter referred to as the ‘‘FSA
score’’ due to its historical usage by the Food Standards Agency
(FSA), because this score provides a categorical distinction
between more and less healthy foods. [21] This model assigns
an overall numeric score according to per 100 g levels of: energy,
saturated fat, total sugar, sodium, fibre, protein, and fruit,
vegetable and nut content. This particular model was originally
developed to highlight foods which should not be advertised to
children and consequently gives a definition of less healthy foods,
allowing for objective classification of the items in our sample. [21]
When used to classify foods this score has been shown to have
good agreement with the subjective opinions of nutrition
professionals. [22].
Statistical analyses
Descriptive statistics were used to characterise the mean
economic cost and change in cost over time, according to food
group and FSA score healthfulness categories. The distributions of
the nutrient profile score for each Eatwell food group were tested
with ANOVA using the data for 2012. The difference in price in
2012 between the categories ‘‘less healthy’’ and ‘‘more healthy’’
was tested using a t-test and between the Eatwell groups with
ANOVA. Repeated measures ANOVA were used to determine
whether (a) there was a statistically significant change in price over
the period 2002–2012 for all foods and (b) the prices changed
differently between Eatwell food group and FSA categories over
this period.
Analyses were conducted using Stata (version SE 12.1). [23]
Figures were produced using R(version 2.15.1 for Windows) and
the ggplot2 package. [24,25].
Sensitivity Analyses
We conducted two sensitivity analyses: we analysed the
difference in price between more and less healthy foods with fruit
and vegetables removed from the healthy foods category, to test
whether any price difference was due only to this group. We also
tested for the possibility of bias caused by excluding items which
did not appear in all years, by looking at the difference in price
between more and less healthy foods when all items in 2012 were
included, not just those which appeared in the CPI basket across
the entire 2002–12 period.
Table 1 shows the 2012 mean price and changes in price for
2002–2012, 2002–2007 and 2007–2012, in both absolute and
relative terms, for all foods and by Eatwell and FSA score
categories. Between 2002 and 2012 the mean price of all foods in
our sample rose 35%, from
3.87/1000 kcal to
5.21/1000 kcal.
This increase was not constant, with the prices rising at a greater
rate after 2007 than before, with the absolute change for the
period 2002–07 being
0.27/1000 kcal compared to
1000 kcal for the period 2007–12. This increase in the rate of
change after 2007 applied to all food groups and nutrient
composition categories.
Price differences by Eatwell food group
The mean prices per 1000 kcal for each of the Eatwell food
groups for the period 2002–2012 are shown in Figure 1. The
Table 1. 2012 mean, absolute and relative changes in price for all foods, by Eatwell group and by FSA score category.
All foods
Bread, rice,
potatoes, pasta Fruit and vegetables
Milk and
dairy foods
Meat, fish, eggs,
beans, other sources
of protein
Food & drinks
high in fat
and/or sugar More healthy Less healthy
2012 mean price (£/1000 kcal) 5.21 1.26 9.13 4.75 4.93 3.11 7.49 2.50
Relative change in price (%) 200212 35 12 23 29 54 49 33 41
200207 7 -9 4 9 11 11 7 8
200712 26 22 18 18 39 33 24 31
Absolute change in price (£/
1000 kcal)
2002–12 1.34 0.13 1.73 1.07 1.73 1.02 1.84 0.73
2002–07 0.27 20.10 0.32 0.34 0.34 0.24 0.37 0.14
2007–12 1.07 0.23 1.41 0.73 1.39 0.78 1.47 0.59
UK Food Price Trends and Nutrition 2002-2012
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figure shows that there is a clear hierarchy of prices across the
period in which fruit and vegetables are always the most expensive
foods and starchy carbohydrates the least expensive. All food
groups saw price increases over the observation period, except for
starchy foods, whose average price remained broadly constant
throughout. The difference between groups was significant across
all years (p,0.001).
Comparison of food groups’ nutrient composition
Figure 2 shows the distribution of nutritional value for each
Eatwell group according to the FSA score. We found that only the
fruits and vegetables group showed a distinct, healthier nutrient
profile, while all other groups contained food items overlapping
the Ofcom categories of more and less healthy (for visual clarity,
this plot excludes the sample’s six beverages sample because the
score uses different cut-offs for foods and beverages. All other
analyses include all 94 foods and beverages). When tested with an
ANOVA, there was a significant difference between FSA scores by
groups (p,0.001) but this was not the case when the ‘‘Fruit and
Vegetables’’ category was removed (p = 0.267). This result
indicates that with the exception of this category, a food’s Eatwell
group cannot be used to determine whether a food is more or less
healthy. This plot excludes the six beverages in the sample because
the score uses a separate cut-off for foods and beverages. The
beverages are included for all other analyses.
Price differences by nutrient profile category
We found an absolute difference in price between the nutrient
profile categories in 2012, with more healthy foods approximately
three times more expensive than less healthy foods (p,0.001). The
mean price was
2.50 (standard deviation = 0.29) for less healthy
items and
7.49 (1.27) for more healthy items. The mean prices
per 1000 kcal for foods categorised as less healthy and foods
categorised as more healthy for the period 2002–2012 are shown
in Figure 3. Across the study period, we found that there was a
consistent difference in price between these groups (p,0.001) and
that there was a difference in the change over time by group
(p = 0.008).
Sensitivity Analyses
When we included all foods and beverages in the CPI in 2012
rather than only those which has been included in the CPI basket
since 2002, the difference in mean price between more and less
healthy foods was
6.57/1000 kcal and
2.96/1000 kcal respec-
tively (p,0.001). We also tested for a difference between more and
less healthy foods over time when fruit and vegetables were
removed from the analysis, finding that the difference between
groups remained (p,0.001) and that they showed different time
trends (p = 0.004), with the price of more healthy foods rising by
1.95/1000 kcal over the period in comparison to
1000 kcal for less healthy foods. With fruit and vegetables
excluded, the mean price for more healthy foods in 2012 was
5.78/1000 kcal whereas the mean price of less healthy foods did
not change.
Our results show that the price of more healthy foods was
consistently greater than that of less healthy foods over the period
2002–2012, and that the absolute price gap between healthy and
less healthy foods has grown over this period. This finding
strengthens the case for monitoring the affordability of healthy
foods and diets in order to inform potential economic policy
This study is the first to use UK data to examine price trends by
the nutrient composition of foods. Our results tally with the
general trend of increasing food prices observed in similar high
income nations, as reported in a review, [26] where studies have
found that in recent years healthy foods had increased more in
price than foods which were less healthy, [27–30] and that
healthier versions of particular foods were more expensive. [31,32]
Another recent review has again found that within given food
groups, the healthier option was typically more expensive for
meats/protein, snacks/sweets, grains, and fats/oils, whilst health-
ier dairy foods were found to be less expensive. [33].
The broadly consistent observation of disparities in food prices
across countries is likely to have multiple causes. In the UK it may
be the case that food prices are heavily influenced by certain
features of the Common Agricultural Policy (CAP) which
intervenes in food markets to subsidise the production of certain
goods, including grains, dairy products, oils and sugar. [34] Such
subsidies have the potential to affect public health by influencing
the availability and price of foods, with modelling studies showing
that the CAP’s presence may reduce the quantity of fruit and
vegetables consumed and increase cardiovascular mortality
through encouraging the consumption of saturated fats. [35,36]
If public health policy is required to address the issue of the higher
price of more healthy foods, it is likely to be necessary to engage
with supply-side issues such as CAP reform to achieve long-term
Figure 1. Mean price of foods by Eatwell food group, 2002–
2012. Mean price (£/1000 kcal) by Eatwell food group of foods and
beverages remaining in the UK Consumer Price Index basket across the
entirety of the period 2002–2012 (n = 94).
UK Food Price Trends and Nutrition 2002-2012
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In recent years the issue of food poverty has been of increasing
concern in the UK and the rising use of food banks has been
recognised as an issue of public health importance. [37,38] Our
results suggest that we should consider not only the issue of people
being able to afford to eat enough food to avoid hunger but also
being able to eat enough food which is healthy. The standard
definition of food security is that people should have physical and
economic access to ‘‘sufficient, nutritionally adequate and safe
food’’, [39,40] meaning that if economic constraints are gradually
forcing people to replace more healthy foods with less healthy
ones, they are becoming increasingly exposed to the risk of food
insecurity. Analyses of UK food spending data by the Institute for
Fiscal Studies has shown that, in recent years, all SES groups have
changed their purchasing habits to both spend less on food and
purchase calories which are both cheaper and less healthy, for
example purchasing less fruit but more grains, cheese and
prepared dishes. [41] Our findings help to explain this observation
by uncovering the magnitude of the price difference between more
and less healthy foods, which is a factor that drives increasing food
insecurity and could contribute to a deterioration in population
In addition to our main finding we also observed that, with the
exception of ‘‘fruit and vegetables’’, the Eatwell food groups were
not distinct in terms of the FSA scores of their constituent foods.
This finding is consistent with earlier work in the US showing that
food groups have limited value in classifying healthy and less
healthy foods. [42] If monitoring of food prices is to start in the
UK, we would echo these authors in arguing for the development
of a monitoring tool that merges nutritional profiling techniques
Figure 2. Box plots of nutrient density by Eatwell food group. Box plots of nutrient density as defined by the Food Standards Agency nutrient
profiling score for foods (and not beverages) remaining in the UK Consumer Price Index basket across the entirety of the period 2002–2012 (n= 88),
by Eatwell food group.
Figure 3. Mean price of foods by Food Standards Agency
nutrient profiling score category, 2002–2012. Mean price (£/
1000 kcal) by Food Standards Agency nutrient profiling score category
of foods and beverages remaining in the UK Consumer Price Index
basket across the entirety of the period 2002-2012 (n = 94).
UK Food Price Trends and Nutrition 2002-2012
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with current guidance for eating a balanced diet rather than
relying on monitoring prices by food group alone.
Methodological considerations and limitations
A key weakness to acknowledge is that the number of foods and
beverages included in this study is small and only reflects those
foods included in the CPI rather than a full range of available
foods. Nevertheless, the items included for analysis should reflect
those most commonly purchased by UK consumers, given the
CPI’s role as a measure of consumer inflation. Our study also does
not account for variation in price by region or outlet, which is
likely to affect the absolute and relative difference in price between
food types in given instances. Another potential weakness is the use
of price per unit energy rather than price per unit mass or any
other price denominator, given that one of the factors determining
a food’s health categorisation is its energy content, an issue which
has been raised by others. [33,43] We analysed price per unit of
energy in line with the approach used by international organisa-
tions to assess food poverty. [44,45] Moreover, price per unit
energy is more consistent with dietary guidance than price per unit
weight and with observed household purchasing behaviour which
shows that energy consumption is broadly consistent in the UK,
even across differing SES groups. [46,47].
The main strength of our study is that we demonstrate the utility
of existing government datasets on the prices and nutrition content
of foods purchased and consumed in the UK, addressing the
recent call by the International Network for Food and Obesity/
Non-communicable Diseases Research, Monitoring and Action
Support (INFORMAS) for a cost-effective and simple tool for
monitoring the price of healthy foods. [11] The study also provides
information on recent price trends pertinent to the health of the
UK population, using an objective and nutritionally relevant tool
to categorise the foods and beverages examined.
Unanswered questions and future research
In conjunction with other work in the area of food prices, food
poverty and food security, our findings highlight the need for the
routine monitoring of food prices in relation to the food’s nutrient
composition. For greater relevance these prices should also be
considered in the context of income and other unavoidable
expenditure, such a rent or utilities, making it possible to consider
the affordability of a healthy diet. Future research in this area
ought to build on our findings and examine the cost of observed
diets in relation to their quality, since the quality and cost of the
overall diet is not simply a function of the price of certain healthy
foods being more expensive. Future research should also seek to go
beyond a descriptive analysis of the price trends by themselves and
try to assess the cause of the observed link between the price and
healthiness of foods, and also to examine the link between food
purchases, actual consumption and health outcomes.
We have demonstrated a novel linkage of existing economic and
nutrition surveillance data to assess trends in the prices of foods in
relation to their nutritional value. The growing gap in the price of
more healthy and less healthy foods revealed by our analysis leads
us to suggest that ongoing monitoring of food prices for public
health is warranted. The data linkage we describe could underpin
such food price monitoring and provide evidence to inform policy
responses to the problem of rising food prices.
Author Contributions
Conceived and designed the experiments: NRVJ AIC MS PM. Analyzed
the data: NRVJ. Wrote the paper: NRVJ AIC MS PM.
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... Processes and ingredients that are used to manufacture UPF make them highly convenient for consumers and highly profitable for manufacturers [4]. Over the past years, it has been argued that unhealthy foods are less expensive compared with healthy foods while the price gap between them is growing [8]. Considering that food prices are an important determinant of food choices and nutritious diets, affordability of ultra-processed foods seems inevitably linked to its consumption, which may have implications for public health, health inequalities and food security, among others [9]. ...
... In Belgium, MPFD contributed most to daily dietary costs (30-42%) compared with UPFD (22-30%) [40]. Higher food costs for unprocessed, healthier foods and diets, might have implications for population health, especially among the lower educated individuals [8,9]. ...
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Objective This study investigates nutritional quality, environmental impact and costs of foods and drinks and their consumption in daily diets according to the degree of processing across the Dutch population. Design The NOVA classification was used to classify the degree of processing (ultra-processed foods (UPF) and ultra-processed drinks (UPD)). Food consumption data were derived from the Dutch National Food Consumption Survey 2012–2016. Indicators assessed were nutritional quality (saturated fatty acids (SFA), sodium, mono and disaccharides (sugar), fibre and protein), environmental impact (greenhouse gas (GHG) emissions and blue water use) and food costs. Setting The Netherlands. Participants Four thousand three hundred thirteen Dutch participants aged 1 to 79 years. Results Per 100 g, UPF were more energy-dense and less healthy than unprocessed or minimally processed foods (MPF); UPF were associated with higher GHG emissions and lower blue water use, and were cheaper. The energy and sugar content of UPD were similar to those of unprocessed or minimally processed drinks (MPD); associated with similar GHG emissions but blue water use was less, and they were also more expensive. In the average Dutch diet, per 2000 kcal, ultra-processed foods and drinks (UPFD) covered 29% (456 g UPF and 437 g UPD) of daily consumption and 61% of energy intake. UPFD consumption was higher among children than adults, especially for UPD. UPFD consumption determined 45% of GHG emissions, 23% of blue water use and 39% of expenses for daily food consumption. UPFD consumption contributed 54% to 72% to daily sodium, sugar and SFA intake. Conclusions Compared with unprocessed or minimally processed foods and drinks, UPF and UPD were found to be less healthy considering their high energy, SFA, sugar and sodium content. However, UPF were associated higher GHG emissions and with less blue water use and food costs. Therefore daily blue water use and food costs might increase if UPF are replaced by those unprocessed or minimally processed. As nutritional quality, environmental impacts and food costs relate differently to the NOVA classification, the classification is not directly applicable to identify win–win-wins of nutritional quality, environmental impact and costs of diets.
... There is a clear price disparity between healthy and unhealthy food products, with one UK study reporting that (at 2012 prices) healthy options cost £7.49 per 1000 calories compared with £2.50 per 1000 calories of unhealthy products (Jones 2014). The Broken Plate report from the Food Foundation is their annual review of the state of the UK's food system. ...
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Food insecurity occurs when an individual lacks the financial resources to ensure reliable access to sufficient food to meet their dietary, nutritional and social needs. Adults living with mental ill health, particularly severe mental illness, are more likely to experience food insecurity than the general adult population. Despite this, most interventions and policy reforms in recent years have been aimed at children and families, with little regard for other vulnerable groups. Initiating a conversation about access to food can be tricky and assessing for food insecurity does not happen in mental health settings. This article provides an overview of food insecurity and how it relates to mental ill health. With reference to research evidence, the reader will gain an understanding of food insecurity, how it can be assessed and how food-insecure individuals with severe mental illness can be supported. Finally, we make policy recommendations to truly address this driver of health inequality.
... 'One of the clearest and most immediate impacts of being in poverty is an inability to buy nutritious food' and those living on low incomes are more likely to have poorer diets (Marmot, Allen, Boyce, Goldblatt, & Morrison, 2020, p. 84). In the UK, more nutritious food tends to be significantly more expensive than less nutritious food, meaning it is difficult for low-income families to eat healthily and/or meet government nutritional guidelines, such as the 'Eatwell' guide (Jones, Conklin, Suhrcke, & Monsivais, 2014;Pechey et al., 2013;Pechey & Monsivais, 2015;Scott, Sutherland, & Taylor, 2018). ...
Technical Report
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Currently, we know little about the role or reach of localised services supporting households experiencing food poverty across Hertfordshire. Nor do we know if or what gaps in provision exist or households’ experiences of accessing these support services. This research aims to address these issues and feed into the HCC food poverty needs assessment in order to inform policy and practice in relation to supporting households experiencing food poverty in Hertfordshire.
... ↓, significant decrease; DM, diabetes mellitus; CHD, cardiovascular heart diseases. (22), the lower cost of unhealthy food acquisition (23) and cultural behaviors barriers (24) allied to unfavorable educational programs impact negatively on healthy food acquisition (25). ...
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Obesity is associated with the leading causes of death in the worldwide. On the other hand, the intake of vegetables, fruits and fish is related to the reduction of obesity and other metabolic syndromes. This review aims to highlight the role of ingestion of polyphenols and omega-3 polyunsaturated fatty acids (ω-3 PUFAs) in reducing obesity and related metabolic diseases (RMDs). The consumption of vegetables, fish and by-products rich in polyphenols and α-linolenic acid (ALA), as well as oils rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are associated with a decrease in obesity and its RMDs in consumers. Furthermore, we discussed the adequate amount of extracts, powder, polyphenols, ω-3 PUFAs administrated in animal models and human subjects, and the relevant outcomes obtained. Thus, we appeal to the research institutions and departments of the Ministries of Health in each country to develop a food education joint project to help schools, businesses and families with the aim of reducing obesity and other metabolic diseases.
... When Lee and Kane [9] compared healthy (modelled on the five AGHE food groups and foundation diet) with unhealthy (based on intake of Australians from the Australian Health Survey and inclusion of discretionary choices) diets in Queensland for five different household structures, the cost of the 'healthy' diet was more affordable for all households, likely due to the removal of alcoholic beverages, take-away foods and sugar-sweetened beverages. But, international data displays conflicting results as 'healthy food' in the UK has been reported to be consistently more expensive compared to less healthy foods, by up to £5 ($9AUD) [14]. In addition, Ni Mhurchu and Ogra [15] found that a healthy food basket based on core foods in New Zealand was slightly more expensive compared to the cost of a 'regular' shopping basket reflective of the population ($6AUD). ...
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Background Weight loss diets continue to rise in popularity; however, the associated costs are seldom reported. Certain weight loss diets may be unaffordable and differ from their traditional nutrition composition to include non-conventional premium products. In contrast, healthy eating principles such as the Australian Guide to Healthy Eating (AGHE) and the Mediterranean Diet (MedDiet) place an emphasis on fresh produce and staple foods but are sometimes thought to be unaffordable. A new methodology was piloted to assess the cost of weight loss diets using seven meal plans. Methods Seven meal plans were analysed to quantify the absolute grams required of all ingredients across seven days and multiplied by the cost of the ingredient per gram to determine the total cost of each ingredient based on unit size and price. The weekly grocery shopping cost was determined through summation of all ingredients and their entire unit size to compare weekly costs. Results Weekly meal plans (absolute grams) cost between $93-193AUD. The AGHE meal plan was the least expensive and 8 Weeks to Wow was the most expensive. Weekly grocery shopping of entire units cost between $345-$625AUD, over $100AUD greater than the spending of an average Australian ($237AUD/week). Conclusions The financial feasibility for long-term sustainment of weight loss diets may be questionable for groups including low-income earners and low socioeconomic status. Further, when dietary patterns are adapted for weight loss, or followed by consumers, deviations from foundational principles tend to occur which may influence overall cost.
Fruits and vegetable (FVs) consumption is an essential determinant of health, and intake is strongly patterned by socioeconomic status (SES). Inside grocery store interventions have increasingly been explored to promote healthier diets, especially for people with lower SES. This study describes how the supermarket chain Kiwi used a combination of in-store interventions to increase annual sales of FVs between 2012 and 2020. In particular, this study examined how sales developed in counties with different demographic characteristics (e.g., education, income, overweight and obesity, and self-reported FVs consumption level) in order to evaluate whether the effect differs between different populations. The primary outcome measurement was annual volume sales, adjusted for new stores opening and closing during the study period, also called like-for-like sales. The study has used a descriptive study design. The chain used interventions such as better placement, promoting healthy foods, giving out discounts, and placing “on the go” FVs and cups with portioned FVs at the cash registry. Results show that like-for-like volume sales of FVs grew by 34.1% during the study period. The increase was especially strong for vegetables, which increased by 41.8%, compared to fruits and berries, which increased by 25%. Sales increased for all eleven counties in Norway. Using the Spearman correlation, a moderately positive association was found between the number of overweight or obese people in counties and the development in FVs sales. To conclude, in-store interventions positively impacted FVs sales. More research in an experimental context is needed to determine if interventions may reduce the socioeconomic gap in FVs consumption.
Sustainable diets are those diets with low environmental impacts that contribute to food and nutrition security and to healthy lives for present and future generations. Sustainable diets are protective and respectful of biodiversity and ecosystems, culturally acceptable, accessible, economically fair and affordable, are nutritionally adequate, safe, and healthy, and optimize natural and human resources. (FAO, 2010). This book takes a transdisciplinary approach and considers multisectoral actions, integrating health, agriculture and environmental sector issues to comprehensively explore the topic of sustainable diets. The team of international authors informs readers with arguments, challenges, perspectives, policies, actions and solutions on global topics that must be properly understood in order to be effectively addressed. They position issues of sustainable diets as central to the Earth’s future. Presenting the latest findings, they: • Explore the transition to sustainable diets within the context of sustainable food systems, addressing the right to food, and linking food security and nutrition to sustainability. • Convey the urgency of coordinated action, and consider how to engage multiple sectors in dialogue and joint research to tackle the pressing problems that have taken us to the edge, and beyond, of the planet’s limits to growth. • Review tools, methods and indicators for assessing sustainable diets. • Describe lessons learned from case studies on both traditional food systems and current dietary challenges. As an affiliated project of the One Planet Sustainable Food Systems Programme, this book provides a way forward for achieving global and local targets, including the Sustainable Development Goals and the United Nations Decade of Action on Nutrition commitments. This resource is essential reading for scientists, practitioners, and students in the fields of nutrition science, food science, environmental sciences, agricultural sciences, development studies, food studies, public health and food policy
Background: Research indicates that food parcels provided by foodbanks are nutritionally-poor. Food insecurity and foodbank use are rising, with detrimental effects on the dietary intake and health of users. This mixed-method systematic review aims to investigate the current nutritional adequacy of pre-packaged food parcels and whether using foodbanks reduces the food insecurity and improves the dietary intake of their users. Methodology: A mixed-method systematic literature review, restricted to articles published from 2015, was conducted using 8 electronic databases, 4 grey literature databases and 8 relevant websites. Quantitative findings, investigating the nutritional quality of food parcels and/or their impact on dietary intake or food insecurity, were presented narratively. Qualitative findings, reporting views of foodbank users regarding foodbank food, underwent thematic synthesis. These independent syntheses were integrated using configurative analysis and presented narratively. Results: Of 2,189 articles, 11 quantitative and 10 qualitative were included. Food parcels were inconsistent at meeting nutritional requirements and often failed to meet individual needs, including cultural and health preferences. Using foodbanks improved food security and dietary quality of users, allowing otherwise unachievable access to food. However, food insecurity remained, explained by limited food variety, quality and choice. The mixed-method findings support interventions to ensure consistent, adequate nutrition at foodbanks, including catering for individual needs. Conclusions: Foodbanks are a lifeline when severely food insecure. However alone, foodbanks struggle to eliminate the heightened food insecurity of their users. Efforts to improve the nutritional quality of food parcels could improve the experiences and diet-related outcomes of those requiring foodbanks. This article is protected by copyright. All rights reserved.
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Nutrition is a major modifiable determinant of health. National nutrition surveys are essential tools to monitor the population nutritional status and guide nutrition policies. Switzerland conducted its first national survey, menuCH, in 2014-2015. A total of 2 086 Swiss residents aged 18 to 75 years old were interviewed and their diet assessed using two 24-hour dietary recalls. This thesis aimed at 1) describing dietary intake of Swiss adult population using menuCH data, and 2) developing recommendations for the next national nutrition surveys and future nutrition policies. menuCH data indicated that the vast majority of the Swiss adult population poorly adhered to the national dietary guidelines. The population consumed insufficient plant-based products, and excessive ultra-processed and/or animal-based foods. Moreover, food consumption patterns substantially differed between the German, French and Italian-speaking parts of Switzerland. Finally, we showed that regularly consuming a breakfast rich in fruit, unsweetened cereal flakes, nuts and yogurt was associated with reduced abdominal obesity. Since menuCH did not survey children nor collect bio-samples, we tested child-specific dietary assessment methods and evaluated acceptability of bio-sample collection in a feasibility study to prepare the next national nutrition survey. We recruited a population-based sample of 53 children aged 3 to 17 years in Lausanne. The developed dietary assessment tools (e.g., 24-hour food diary, food questionnaire) were well accepted by participants and their caregiver(s). Compliance with the collection of spot urine, venous and capillary blood, and toenails was high in the different age groups. As shown above, dietary behaviours in Switzerland are not optimal. Classically, public health can propose two types of interventions to improve the situation: 1) provide information to encourage behavioural modifications (individual level), or 2) change the environment to reduce exposition (population level). I wrote an essay about a novel instrument designed to improve diet, i.e., precision nutrition. I concluded that providing personalized advice at a large scale via smartphones (individual level) might have a limited effect on dietary behaviours and obesity, if environments promoting unhealthy food are not modified in parallel (population level). We have shown that Switzerland needs public health interventions to improve dietary behaviours. We suggest that these interventions target in priority the food environments to facilitate access to healthy foods. Furthermore, the next national nutrition surveys should include children, strengthen dietary assessment methods, and collect bio-samples for relying on objective nutritional biomarkers. We believe that this will improve the assessment of dietary intake and nutritional status at both individual and population levels to further fine-tune national dietary guidelines and guide future nutrition policies.
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While school food initiatives across England sup­port children’s nutritional intake during school term time, there is no universal state provision dur­ing the school holidays to reduce the risk of chil­dren experiencing food insecurity. In the absence of a national program of holiday provision, com­munity organizations in disadvantaged com­muni­ties have established holiday clubs offering free food and activities to children. This paper exam­ines how these holiday clubs source food and the challenges of procuring food and delivering healthy meals that adhere to UK School Food Standards. Results indicate that holiday clubs adopt a variety of procurement strategies including rely­ing upon donated food. While club leaders have sought opportunities to source food cost-effectively, the findings suggest significant chal­lenges for these clubs to achieve their aim of delivering healthy meals. Findings point to needs for sustainable funding and the developing healthy food procure­ment policies and processes that align with a wider food strategy.
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To conduct a systematic review and meta-analysis of prices of healthier versus less healthy foods/diet patterns while accounting for key sources of heterogeneity. MEDLINE (2000-2011), supplemented with expert consultations and hand reviews of reference lists and related citations. Studies reviewed independently and in duplicate were included if reporting mean retail price of foods or diet patterns stratified by healthfulness. We extracted, in duplicate, mean prices and their uncertainties of healthier and less healthy foods/diet patterns and rated the intensity of health differences for each comparison (range 1-10). Prices were adjusted for inflation and the World Bank purchasing power parity, and standardised to the international dollar (defined as US$1) in 2011. Using random effects models, we quantified price differences of healthier versus less healthy options for specific food types, diet patterns and units of price (serving, day and calorie). Statistical heterogeneity was quantified using I(2) statistics. 27 studies from 10 countries met the inclusion criteria. Among food groups, meats/protein had largest price differences: healthier options cost $0.29/serving (95% CI $0.19 to $0.40) and $0.47/200 kcal ($0.42 to $0.53) more than less healthy options. Price differences per serving for healthier versus less healthy foods were smaller among grains ($0.03), dairy (-$0.004), snacks/sweets ($0.12) and fats/oils ($0.02; p<0.05 each) and not significant for soda/juice ($0.11, p=0.64). Comparing extremes (top vs bottom quantile) of food-based diet patterns, healthier diets cost $1.48/day ($1.01 to $1.95) and $1.54/2000 kcal ($1.15 to $1.94) more. Comparing nutrient-based patterns, price per day was not significantly different (top vs bottom quantile: $0.04; p=0.916), whereas price per 2000 kcal was $1.56 ($0.61 to $2.51) more. Adjustment for intensity of differences in healthfulness yielded similar results. This meta-analysis provides the best evidence until today of price differences of healthier vs less healthy foods/diet patterns, highlighting the challenges and opportunities for reducing financial barriers to healthy eating.
Aim: To undertake a systematic literature review to examine the effect of food cost on diet quality and risk factors for chronic disease, specifically focusing on diet-related lifestyle diseases affecting the Australian population. Methods: A search of six databases resulted in the inclusion of one systematic review, three cohort studies, 41 cross-sectional studies and four modelling studies in this review. Results: Between 2000 and 2006, the price of healthy foods has increased more than the price of less healthy foods. Healthy Food Access Basket surveys show that a healthy diet may often be unaffordable for low- and average-income households. Diets of higher energy density were associated with lower diet cost, whereas diets of higher nutrient density and nutritional quality were associated with higher diet cost. Recent studies report an inverse association between food price and food consumption. Consequently, an increase in food cost was associated with a significant reduction in weight, waist circumference, body mass index, obesity and insulin resistance. Conclusions: Manipulation of food cost may alter food consumption and therefore risk factors for chronic disease. Further longitudinal studies investigating the impact of pricing strategies on diet quality and disease risk are needed.
Food prices and food affordability are important determinants of food choices, obesity and non-communicable diseases. As governments around the world consider policies to promote the consumption of healthier foods, data on the relative price and affordability of foods, with a particular focus on the difference between ‘less healthy’ and ‘healthy’ foods and diets, are urgently needed. This paper briefly reviews past and current approaches to monitoring food prices, and identifies key issues affecting the development of practical tools and methods for food price data collection, analysis and reporting. A step-wise monitoring framework, including measurement indicators, is proposed. ‘Minimal’ data collection will assess the differential price of ‘healthy’ and ‘less healthy’ foods; ‘expanded’ monitoring will assess the differential price of ‘healthy’ and ‘less healthy’ diets; and the ‘optimal’ approach will also monitor food affordability, by taking into account household income. The monitoring of the price and affordability of ‘healthy’ and ‘less healthy’ foods and diets globally will provide robust data and benchmarks to inform economic and fiscal policy responses. Given the range of methodological, cultural and logistical challenges in this area, it is imperative that all aspects of the proposed monitoring framework are tested rigorously before implementation.