Download Eatwell Guide: modelling the dietary and cost

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PEER REVIEW HISTORY
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ARTICLE DETAILS
TITLE (PROVISIONAL)
AUTHORS
The Eatwell Guide: modelling the dietary and cost implications of
incorporating new sugar and fibre guidelines.
Scarborough, Peter; Kaur, Asha; Cobiac, Linda J.; Owens, Paul;
Parlesak, Alexandr; Sweeney, Kate; Rayner, Mike
VERSION 1 - REVIEW
REVIEWER
REVIEW RETURNED
Annie S. Anderson
University of Dundee, UK
Member of Public Health England SACN subgroup (maternal and
child nutrition)
22-Jul-2016
GENERAL COMMENTS
Abstract – “reduction in consumption of beans and pulses” does not
sound appropriate
Methods – please clarify that “old recommendations” equate to
“Eatwellplate”… slightly confusing to read
Results- the fibre requirements could be assisted with an increase in
pulses (may also be desirable in sustainability terms) and I am
disappointed not to see some modelling of this.
Discussion -Why quote changes in consumption during 1974 and
2007?
What if portions sizes were the main change approach – how useful
would this be (as opposed to frequency of consumption)
REVIEWER
Nicole Darmon
INRA France
24-Jul-2016
REVIEW RETURNED
GENERAL COMMENTS
The aim is to model food group consumption and price of diet
associated with achieving UK dietary recommendations in order to
“to support the redevelopment” of the UK Eatwell Guide, starting
from the mean diet observed in UK adults based on data from the
National Diet and Nutrition Survey (NDNS) .
The conclusion is that “To achieve the UK dietary recommendations
would require large changes to the average diet of UK adults”
My main concern is that the provision of food based dietary
guidelines for a population has important political, social and
economic consequences. It is weird that such an important decision
could be made on the sole basis of a so simplistic diet modeling
exercise.
The objective of this study is not clear: is this an a posteriori
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validation of guidelines that have already been officially endorsed. If
they were endorsed, on the basis on what was it decided?
The authors state that their model is aimed at designing a diet which
deviates “as little as possible from the current UK diet”. However:
- the choice of the specific objective function implemented is not
justified in the paper. What are the underlining assumptions? How
does it compare with other possible decisions regarding the
objective function? The reader would want to know whether the
choice of objective function influenced the results.
- “the current UK diet” does not exist. It is rather a myriad of very
diverse individual diets. Using population modeling rather that
individual diet modeling is a strong limitation of this study that have
to be acknowledged.
- A first limitation of population modeling is that the mean population
diet is totally theoretical as it assumes that all food categories are
consumed, each in relatively small amounts, which is exactly the
contrary of what is actually observed: in the true life, people have a
limited food repertoire and they consume each repertoire‟s food in
relatively high amount.
- Another limitation of population modeling is that it is impossible to
perform statistical analyses, and therefore it is impossible to
guarantee the validity and the robustness of the results obtained.
(NB:this paper does not requires statistical review as no statistical
analysis can be performed)
- As it is seems so difficult to generalize results from population diet
modeling, this type of modeling it is clearly not adapted to the design
of official dietary recommendations.
The assumptions at the basis of model specifications are not
explicitly stated:
- It is not clear why the author include food-based guidelines as
constraints? If they want to derive FBDGs as the main output of their
model, why do they include them as constraints? It looks like circular
reasoning.
- It is not clear why the authors did not include acceptability
constraints, at least realistic maximal expected amounts of each
food variable (based on the distribution of their consumption in the
target population). Again, it does not seem acceptable to deliver
official dietary recommendations for a population without taking into
account the food habits of individuals in this population (except that
of sticking to the “mean” diet, that nobody eats). The risk in missing
food acceptability constraints is to recommend diets which
individuals will never take.
Specific comments:
Abstract:
Indicate in the abstract which data were used, and which models
were run. The sentence “The optimised diet (which by design will
meet recommendations for carbohydrates, free sugars, fat,
saturated fat, protein, salt, fibre, fruit and vegetables, fish, and red /
processed meat consumption)” is not a result.
Result: in absence of statistics, how do you decide whether some
increases or decreases are “marginal” and other are not?
In particular, the conclusion is that “To achieve the UK dietary
recommendations would require large changes to the average diet
of UK adults,” is this significant? Is this acceptable? Don‟t you think
that this likely to call into question the relevance of the nutritional
constraints used in the model? This should be discussed, at least in
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the discussion section of the paper.
Page 12:
To have an idea of the relative strength of the constraints, and to
know which are the most stringent, the best way is to calculate
normalized shadow costs. Please, provide them.
“Table 3 shows the impact of the scenarios on food category
consumption”: (in all the manuscript) avoidt using the word
“consumption” when commenting results obtained in modeled diets,
that will never been “consumed”.
The modeling suggests that a decrease of dairy products and meats
is needed. This means that animal sources of calcium and iron are
replaced by plant-based one. Please discuss this in the limitation
section (bioavailability not taken into account…).
Page 17
It is not true that only macronutrient and salt constraint were
introduced in the models. Constraints on foods were also included
(see my commentary on the circularity of the argument)
Ref 37 is cited but this paper was a secondary analysis of the results
from individual diet modeling in a representative sample of French
adults. In addition to the country differences in food habits and the
difference in the number of nutritional constraints (essential fatty
acids were included in the “French modeling exercise”), other
important differences were the inclusion of acceptability constraints
in the “French modeling exercise” and the fact that it was based on
individual diet modeling (as described by Maillot AJCN 2010), not on
population modeling.
Table 2: Some comments on the low energy levels of the 3 diets, the
very low content of n-3 fatty acids, and on the very low sodium level
of the Eatwell guide are needed. We also have physiological needs
for Na. If 2070 mg is the mean Na content of a population diet,
would this imply that many individual diets would fall below that
level?
Table 3: please remove SE for cost data, as it is confusing and
some readers may think that this refers to food weights.
REVIEWER
REVIEW RETURNED
Sigrid Gibson
Sig-Nurture Ltd.
11 Woodway
Guildford
Surrey
GU1 2TF
UK
My company Sig-Nurture Ltd., has received research funding,
/honoraria/expenses from food manufacturers and trade
organisations.
27-Jul-2016
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GENERAL COMMENTS
Reviewers Comments
The Eatwell Guide: modelling the dietary and cost implications
of incorporating new sugar and fibre guidelines.
1. The paper provides a very interesting evaluation of the
dietary and cost implications of meeting current DRVS and
food based guidelines, as illustrated in the Eatwell guide.
This is a much-needed analysis to support Public Health
recommendations.
2. I would prefer to see slightly more emphasis on the
nutritional results (which are after all the focus of Eatwell)
and less on the economics, which will be dependent on the
pricing assumptions and selection of items. The
sustainability assessments are also highly uncertain, and
this should be mentioned. My comments are restricted to the
dietary aspects as this is my area of expertise.
3. I have some concerns about the method, or at least how it is
framed in terms of the Eatwell Guide. The stated aim was
quantifying the angles in the EWG (page 6). However, it is
ambiguous whether the food groupings were based on the
Eatwell Guide (oils and fats only in section, high sugar foods
outside the plate) or the Eatwell Plate (section for foods high
in sugars and fat), or a hybrid. For example, the introduction
on page6 lines 38-42 describe the 5 sections of the new
EWG as the basis of the model, but in the methods on page
9 the researchers appear to have used the Plate for noncomposite foods,(i) the Guide for composite foods (ii), while
condiments/unclassified items (iii) refers to “Eatwell groups“
which is unclear. On page 10 is it explained that the
categories used for modelling differ from the EWG – this
should be mentioned earlier. I can see why the researchers
needed to do this – how else to show the effect of the
sugars target? However, the paragraph on page 6 may need
to be revised; unless I am mistaken, what the study appears
to have done is to calculate the impact of old and new
recommendations, using the illustration of the Old Eatwell
plate. Referring to this as the Eatwell Guide is confusing
when surely what is meant is the “modelled diet scenario”
4. For example, figure 1 shows the changes resulting from the
old and new recommendations compared to the current diet
very well- but is this in terms of the Plate categories, not the
Guide categories. The footnote should make it clear what
the purple category represents for each bar- currently it
merely describes the EWG and implies that for the right
hand bar (EWG) purple represents only oils and fats. From
Table 3 it looks like this looks like both high sugar high fat
foods and oils and spreads, i.e. the old Plate classification.
5. Authors could also discuss the implications of leaving
alcoholic drinks out of the model, as this represents a nontrivial source of energy for many people. Omission may
have overconstrained the energy intake.
6. Given that the optimisation modelling was designed to
produce a solution with the smallest total change to existing
habits, this “best” result involves drastic changes, which as
they point out are unprecedented in recent history. Although
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it is true that the model itself cannot take account of
behaviour, the authors should discuss the outcome and
what it means in greater depth.
 For example, the Eatwell scenario diet is higher in
carbohydrate than SACN recommended and low in
fat, (as no upper limit was set for CHO or lower limit
for fat). The fibre target is possibly the driver for the
huge increase in starchy foods and higher CHO
intake, the sugar target the driver for the big
decrease in sugary foods. Possibly, saturated fat
and salt were drivers for the lower meat and dairy
consumption as well as calorie displacement from
the food groups that need to increase.
7. The comparison with other similar modelling studies should
be expanded. For example, reference 29 is mentioned only
in the context of sustainability but is highly relevant. Their
model was designed with acceptability as a constraint and
they discounted an option that increased breakfast cereal
but provided less milk to go with it (as in the current
scenario). Incidentally the amount of milk quoted in Table 3
is barely enough for 3 cups of tea.
8. Page 14 Lines 18-46 discusses historic precedents for
changes in consumption, including large declines in some
dairy products since the 1980s; the tone is optimistic.
However, the changes in dairy referred to in Line 45 mainly
involved switching to low fat versions within the product
category. Reversal of current trends such as doubling the
amount of bread and potatoes or fruit and vegetables, are
likely to be much harder.
9. It would be helpful if the authors could provide more or
different references as examples of successful dietary
interventions, if possible. 21 was a review on portion control
and 22 is NICE recommendations (perhaps a more specific
reference in the report would be helpful). There are probably
few examples of successful interventions of this magnitude,
the Finnish example of SFA reduction comes to mind.
10. The comparison with previous studies is in 2 places in the
discussion and could be reorganised. Page 17 lines 13 to
46 highlight important differences between the findings of
this study and others in US and France, both of which
suggested an increase in dairy.
11. Slightly more could be said about micronutrients, for
example likely lower bioavailability of iron, zinc, calcium.
12. Further work that is clearly needed is to devise meal plans
based on these recommendations under same assumptions
about supermarket foods. The meal plans by BNF could be
referred to but include very few pre-prepared meals. More
realistic scenarios are needed to see if the diet is workable
for time-poor or resource-poor groups.
13. Further modelling could look at acceptability constraints and
scenarios with more leeway, for example, the energy
constraint: a higher energy allowance to replace kcals from
alcoholic drinks could allow more oils and fats.
14. I presume you used NDNS data on NMES as proxy for free
sugars, although the definitions are slightly different
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(although that for free sugars has not yet been finalised).
This should be mentioned in limitations (NMES slightly overestimates free sugars intake). More dried fruit would be
allowed in the model scenario without pushing up free
sugars.
Other comments:
Abstract



The important detail of which dietary recommendations are
included is inserted halfway through the results. It would be
better to mention it earlier (perhaps under Design)
Abstract Line 19 aged 19 and above. Should this be “aged
19y and above”?
Results line 32: “Reductions in consumption of beans… etc
“ Although this is how the Eatwell guide describes the
category, perhaps say reduction in “meat and alternatives” ?
Methods


Page 7 line 30 “average consumption” - better to say “mean”
Page 8 line 33. Portion sizes for NDNS were not just taken
from the portion size handbook but estimated using
household measures, pack sizes, photos as well.
Results




Page 11 Line 38 Figure 1 shows breakdown by Eatwell
guide categories or Eatwell Plate (see above)?
There are some discrepancies between the “5 a day”
allowances and the modelling, in regard to Fruit Juice and
Smoothies. The NHS choices website ( 5 a day) states „One
150ml glass of unsweetened 100% fruit/vegetable juice or
smoothie combined can count as maximum one portion”,
whereas the modelling appears to allow 1 portion of fruit
juice (150ml) and 2 portions (300ml) of smoothies per day.
The Fruit juice advice has recently been “clarified” but the
authors should mention this difference under limitations and
whether it would have affected the estimates (probably by
very little).
Table 2: AER should be EAR. RNI for Vitamin D is now
10ug/day.
Fig 1 is duplicated pg. 27?
Finally I would like to congratulate the authors on tackling this
complex and important task and writing a very absorbing paper. I
hope the comments will be helpful.
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VERSION 1 – AUTHOR RESPONSE
Reviewer: 1
Reviewer Name: Annie S. Anderson
Abstract – “reduction in consumption of beans and pulses” does not sound appropriate
Response: We have added a line to the abstract to clarify that there is variety in results within broad
food groups. The results in the paper clearly show increases in consumption of beans and pulses and
reductions in consumption of meat.
Methods – please clarify that “old recommendations” equate to “Eatwellplate”… slightly confusing to
read
Response: The „old recommendations‟ does not equate with the eatwell plate, as the eatwell plate
was not constructed on the basis of optimisation modelling. We have added sections to the methods
that clarify the difference between the eatwell plate food categories and the Eatwell Guide food
categories, and the categories used in this manuscript (see response to reviewer 3).
Results- the fibre requirements could be assisted with an increase in pulses (may also be desirable in
sustainability terms) and I am disappointed not to see some modelling of this.
Response: The optimisation modelling in the paper results in an increase in beans, pulses and
legumes from 14g/d to 26g/d (nearly doubling in quantity). We have added a line in the results to
highlight this. We could have introduced a constraint to require that pulses increase in consumption
even further, but that would have been arbitrary and contrary to the rationale for the other constraints
that were used for the modelling (i.e. that they should be based only on official food and nutrientbased recommendations). We think there may be some confusion here due to the category names
used in the paper which we have tried to clarify by including the Eatwell Guide category names in
quotations throughout the manuscript in order to show clearly when we are referring to changes in
broad food categories rather than individual foods within categories.
Discussion -Why quote changes in consumption during 1974 and 2007?
Response: Our intention was to demonstrate the size of the challenge faced by the large changes in
the average UK diet that would be needed to meet the food and nutrient recommendations. We do
this by placing them in the context of how food habits have evolved over time, to show the magnitude
of food consumption changes that have previously been observed in the UK. 1974 was the first year
when data were available for the trend in fruit and vegetables that we were considering, and 2007
was when the increases in fruit and vegetables levelled out.
What if portions sizes were the main change approach – how useful would this be (as opposed to
frequency of consumption)
Response: For the purposes of our optimisation modelling, these two approaches are identical. The
optimisation modelling estimates the optimum amount of food that should be consumed for 125 food
groups and compares this to current consumption of these 125 food groups (as measured in the
NDNS). Consumption of the food groups is measured in g/d. Movement from the baseline
consumption to the modelled consumption could be achieved by changes in portion size or changes
in frequency of consumption or both.
Reviewer: 2
Reviewer Name: Nicole Darmon
The aim is to model food group consumption and price of diet associated with achieving UK dietary
recommendations in order to “to support the redevelopment” of the UK Eatwell Guide, starting from
the mean diet observed in UK adults based on data from the National Diet and Nutrition Survey
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(NDNS) . The conclusion is that “To achieve the UK dietary recommendations would require large
changes to the average diet of UK adults”. My main concern is that the provision of food based dietary
guidelines for a population has important political, social and economic consequences. It is weird that
such an important decision could be made on the sole basis of a so simplistic diet modeling exercise.
Response: The modelling exercise conducted for this paper was only one element of the
redevelopment of the UK Eatwell Guide. The first stage was the development of new population
targets for consumption of free sugars and fibre, which was conducted by the Scientific Advisory
Committee on Nutrition (SACN). These new targets were based on a comprehensive review of the
scientific literature (SACN, 2015). The next stage was for Public Health England (PHE) to re-evaluate
the design of the UK food guide (previously the eatwell plate) to address criticisms of the previous
food guide, such as the presence within the food guide of carbonated sugary drinks and other
unhealthy foods. At this stage, PHE conducted consumer research that informed the redesign of the
food guide, including changes in the name of the guide, the images used for the guide and the names
of the food group segments (PHE, 2016). Only the redesign of the angles of the Eatwell Guide was
informed by the analyses reported in this paper. We have added further details of this process to the
introduction to make this clear.
The objective of this study is not clear: is this an a posteriori validation of guidelines that have already
been officially endorsed. If they were endorsed, on the basis on what was it decided?
Response: The objective was not an a posteriori validation of food-based guidelines. The output of
this project that has been used for the Eatwell Guide (namely the angles of the segments in the
Eatwell Guide) was not known prior to our analyses. We have changed the text in the introduction to
make this clear.
The authors state that their model is aimed at designing a diet which deviates “as little as possible
from the current UK diet”. However:
- the choice of the specific objective function implemented is not justified in the paper. What are the
underlining assumptions? How does it compare with other possible decisions regarding the objective
function? The reader would want to know whether the choice of objective function influenced the
results.
Response: We have added an explanation of the objective function to the methods section and also
two sensitivity analyses where the objective function is varied. The new text in the methods reads as
follows: “This objective function was selected following previous work that has built objective functions
on the assumption that individuals facing economic constraints will choose a diet as similar as
possible to their current consumption patterns (Darmon et al., 2002; Darmon et al., 2006; Perignon et
al., 2016). We used the square of the distance between the modelled and baseline consumption
levels as this measure discriminates against large changes in single food categories (in favour of
small changes in many food categories), thereby discriminating against solutions with unrealistically
large consumptions of a small number of food groups. We chose to model on the basis of quantity of
food consumed in g/d rather than kcal/d as evidence suggests that individuals regulate food
consumption by volume as well as energy consumed (Ello-Martin et al., 2005). We conducted
sensitivity analyses with two alternative objective functions – one where the difference in consumption
in the modelled and baseline scenarios is based on kcal/d, and one where the difference is calculated
as the absolute standardised percentage change in consumption in g/d (an objective function
previously used elsewhere (Darmon et al., 2002)).” We have added the following to the results
section: “Our results were sensitive to the choice of the objective function for the optimisation
modelling. When the difference in baseline and modelled consumption was measured by kcal/d rather
than g/d, the resultant angles of the Eatwell Guide for the “fruit and vegetables”, “beans, pulses, fish,
eggs, meat and alternatives”, “foods high in fat, salt and sugar”, “dairy and alternatives”, and
“potatoes, bread, rice, pasta and other starchy carbohydrates” categories were 53%, 12%, 5%, 6%,
and 24% respectively. When the objective function was the absolute percentage difference in
consumption, these angles were 50%, 12%, 5%, 7% and 26%.” We have added a reference to the
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sensitivity of the results in the discussion section.
- “the current UK diet” does not exist. It is rather a myriad of very diverse individual diets. Using
population modeling rather that individual diet modeling is a strong limitation of this study that have to
be acknowledged.
- A first limitation of population modeling is that the mean population diet is totally theoretical as it
assumes that all food categories are consumed, each in relatively small amounts, which is exactly the
contrary of what is actually observed: in the true life, people have a limited food repertoire and they
consume each repertoire‟s food in relatively high amount.
- Another limitation of population modeling is that it is impossible to perform statistical analyses, and
therefore it is impossible to guarantee the validity and the robustness of the results obtained. (NB:this
paper does not requires statistical review as no statistical analysis can be performed)
- As it is seems so difficult to generalize results from population diet modeling, this type of modeling it
is clearly not adapted to the design of official dietary recommendations.
Response: We agree with the reviewer that it would be very useful to conduct individual-level
modelling in order to compare the results with those that we present in this paper. It would be
intriguing to assess whether individual-level modelling results would align with population-level results
as a method of cross-validation of the two approaches. If they do agree, then the individual-level
approach has the obvious advantages described above. However, if they do not agree then it would
be necessary to conduct a thorough investigation of the reason for these differences in order to get a
better understanding of which approach is preferable for this analysis. Even after individual evaluation
of each study participant‟s diet one would have to calculate average values in order to make the
results communicable. The authors feel that the comparison of individual modelling with subsequent
averaging vs. an a priori averaging with subsequent modelling is an important topic that deserves
attention. Therefore, this question should be addressed in a separate study.
We have added the following paragraph to the discussion expanding on this point: “The optimisation
modelling conducted in this paper has been done at the population level. An alternative approach
would be to conduct individual diet modelling (Maillot et al., 2010), where a separate optimisation
model is constructed for each of the individuals in the NDNS and the aggregated results are
combined to produce an optimised population model. There are two advantages of the individual diet
modelling approach. First, the final population model is based on an aggregate of results from the
individual-level models and therefore it is possible to calculate the variance (and hence confidence
intervals) around population-level results. This would provide an assessment of the robustness of the
results. A second advantage of individual-level diet modelling is that baseline diets are actual diets
whereas the average population diet used as the baseline for these analyses is a composite diet that
is not actually consumed by anyone in the population. However, the objective of this analysis was to
construct an average diet for the UK population that meets the population goals set out in Table 1.
The majority of these goals are population rather than individual-level goals i.e. they are targets for
the average level of consumption within a population as opposed to targets for individual-level
consumption. Using an individual-level approach would result in an average population diet where
everyone in the population meets the population goals, whereas the population-level approach
produces results where roughly half the population meet the population goals. Conceptually, we
believe that the population-level approach is better suited to optimisation modelling for meeting
population dietary goals. However, because of the advantages described above it would be useful to
cross-validate these results against an individual-diet modelling approach.”
The assumptions at the basis of model specifications are not explicitly stated:
- It is not clear why the author include food-based guidelines as constraints? If they want to derive
FBDGs as the main output of their model, why do they include them as constraints? It looks like
circular reasoning.
Response: We do not see this as circular reasoning. Although three of the constraints were based on
three existing Government food-based guidelines, these three guidelines cover six types of food. In
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the modelling we have done here we cover 125 different food groups. Food based dietary guidelines
come in a variety of formats including simple messages such as eat at least five portions of fruit and
vegetables a day and more complex guidance about the proportions of the diet which ideally should
come from different food categories – the output of our modelling. We see no reason why such
guidance about proportions should not be constrained by more simple food based dietary guidelines.
- It is not clear why the authors did not include acceptability constraints, at least realistic maximal
expected amounts of each food variable (based on the distribution of their consumption in the target
population). Again, it does not seem acceptable to deliver official dietary recommendations for a
population without taking into account the food habits of individuals in this population (except that of
sticking to the “mean” diet, that nobody eats). The risk in missing food acceptability constraints is to
recommend diets which individuals will never take.
Response: We did not include acceptability constraints for two reasons. First, we did not want to
introduce arbitrary thresholds as constraints. Second, the objective function that we employed was
developed in such a way as to discriminate against large (and hence unacceptable) changes in
consumption in any one category, thereby protecting against modelled diets with large consumption of
a small number of food categories. This explanation has been added to our description of the
objective function. For our modelled diet we note that modelled consumption of the 125 food
categories never exceed 25% of the maximum consumption level shown in the NDNS dataset (which
is due to the average levels of consumption in the baseline diets diluting consumption of each of the
food categories compared to individual dietary behaviour, as the reviewer has already noted).
Therefore, acceptability constraints to restrict consumption of food groups based on high thresholds of
observed consumption would not make any difference to our analyses.
Specific comments:
Abstract: Indicate in the abstract which data were used, and which models were run. The sentence
“The optimised diet (which by design will meet recommendations for carbohydrates, free sugars, fat,
saturated fat, protein, salt, fibre, fruit and vegetables, fish, and red / processed meat consumption)” is
not a result.
Response: We have altered the abstract accordingly.
Result: in absence of statistics, how do you decide whether some increases or decreases are
“marginal” and other are not?
Response: We accept that this is a limitation that is common to all population based optimisation
modelling studies (e.g. Perignon et al., 2016) and have discussed this limitation in depth in the
discussion (see above). In the abstract we have changed the word „marginal‟ to „small‟.
In particular, the conclusion is that “To achieve the UK dietary recommendations would require large
changes to the average diet of UK adults,” is this significant? Is this acceptable? Don‟t you think that
this likely to call into question the relevance of the nutritional constraints used in the model? This
should be discussed, at least in the discussion section of the paper.
Response: As discussed above, we have now included a section in the discussion that describes the
limitation of the lack of statistics for population diet modelling. The nutritional constraints used in the
model are current UK food and nutrient recommendations and so are highly relevant to this analysis.
We have discussed why we did not include acceptability constraints above. We are not sure what the
reviewer means about the results being „acceptable‟.
Page 12: To have an idea of the relative strength of the constraints, and to know which are the most
stringent, the best way is to calculate normalized shadow costs. Please, provide them.
Response: We have updated the paper to include this analysis and added results under the new
„sensitivity analysis‟ section of the manuscript. We followed the dual value approach described in
Perignon et al., 2016 for the analysis and found that the most stringent constraints were for free
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sugars, fibre and salt.
“Table 3 shows the impact of the scenarios on food category consumption”: (in all the manuscript)
avoid using the word “consumption” when commenting results obtained in modeled diets, that will
never been “consumed”.
Response: We have updated the manuscript throughout to use the term „modelled consumption‟ to
distinguish between the modelled results (which as the reviewer points out have not been consumed)
and the baseline diet, which is based on observed consumption patterns.
The modeling suggests that a decrease of dairy products and meats is needed. This means that
animal sources of calcium and iron are replaced by plant-based one. Please discuss this in the
limitation section (bioavailability not taken into account…).
Response: We have added the following to the limitation section: “Our results on micronutrient quality
of the diet do not account for differences in the bioavailability of nutrients consumed from different
foods. For example, it has been estimated that bioavailability of iron in a mixed diet is approximately
14-18% but only 5-12% for vegetarian diets with no iron stores (Hurrel and Egli, 2010). Reductions in
bioavailability of this magnitude could impact on the nutritional adequacy of the diet for population
subgroups. Further work with individual diet modelling could explore this possibility further.”
Page 17: It is not true that only macronutrient and salt constraint were introduced in the models.
Constraints on foods were also included (see my commentary on the circularity of the argument)
Response: We thank the reviewer for spotting this oversight. We have corrected this in the revised
manuscript.
Ref 37 is cited but this paper was a secondary analysis of the results from individual diet modeling in
a representative sample of French adults. In addition to the country differences in food habits and the
difference in the number of nutritional constraints (essential fatty acids were included in the “French
modeling exercise”), other important differences were the inclusion of acceptability constraints in the
“French modeling exercise” and the fact that it was based on individual diet modeling (as described by
Maillot AJCN 2010), not on population modeling.
Response: We have added the following to this section of the discussion: “Additionally, the French
study used individual diet modelling, used a different objective function based on the absolute
difference in the modelled and baseline diet (our sensitivity analyses show that our results are
sensitive to the choice of objective function) and used “acceptability constraints” where consumption
of individual food groups was constrained to high levels of consumption observed in the baseline
dataset. Our choice of objective function mitigated against the need for acceptability constraints – in
our main results modelled consumption of each of the 125 food groups was never higher than 25% of
the maximum consumption observed in the NDNS dataset.”
Table 2: Some comments on the low energy levels of the 3 diets, the very low content of n-3 fatty
acids, and on the very low sodium level of the Eatwell guide are needed. We also have physiological
needs for Na. If 2070 mg is the mean Na content of a population diet, would this imply that many
individual diets would fall below that level?
Response: We have not added a discussion of the low n-3 fatty acids consumption as we do not think
that baseline consumption levels of this nutrient warrant special attention in this paper. We have
addressed the other comments in the limitations section of the discussion with the following addition:
“The NDNS which provided the data for these analyses is subject to under-reporting (NatCen, 2015),
which explains why the energy levels of the baseline and modelled diets are fairly low. It is likely that
baseline levels of specific foods are also under-reported which could exaggerate or underplay the
changes in diet that are needed to meet the constraints depending on whether the constraints
encourage greater consumption (e.g. fruit and vegetables) or less consumption (e.g. free sugars). The
reductions in average sodium intake in our modelled diets result from the constraint to reduce
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average salt consumption to 6g per day (Table 1) and may mean that some individual diets fall well
below this level. Whether this would lead to adverse health consequences for some people is a
subject of debate (Cogswell et al 2016 NEJM).”
Table 3: please remove SE for cost data, as it is confusing and some readers may think that this
refers to food weights.
Response: We think it is important to provide the SE for the cost data in this table. However, we agree
that the table is misleading so we have reformatted and added a footnote to make it clear that the SE
refers to the cost data and not the consumption data.
Reviewer: 3
Reviewer Name: Sigrid Gibson
1. The paper provides a very interesting evaluation of the dietary and cost implications of meeting
current DRVS and food based guidelines, as illustrated in the Eatwell guide. This is a much-needed
analysis to support Public Health recommendations.
Response: We thank the reviewer for this comment.
2. I would prefer to see slightly more emphasis on the nutritional results (which are after all the focus
of Eatwell) and less on the economics, which will be dependent on the pricing assumptions and
selection of items. The sustainability assessments are also highly uncertain, and this should be
mentioned. My comments are restricted to the dietary aspects as this is my area of expertise.
Response: In response to other comments we have increased the emphasis on the nutritional results
(e.g. running sensitivity analyses on the objective function; assessing the relative strength of the
constraints; discussing bioavailability etc.) We do not agree with the reviewer that the sustainability
assessments are highly uncertain. It is accepted that animal-based products have a higher
greenhouse gas intensity than vegetable based products (three references are provided in the paper),
and the Carbon Trust has assessed the impact of the modelled diet on greenhouse gas emissions,
land use and water use, all with positive results (also referenced in the paper).
3. I have some concerns about the method, or at least how it is framed in terms of the Eatwell Guide.
The stated aim was quantifying the angles in the EWG (page 6). However, it is ambiguous whether
the food groupings were based on the Eatwell Guide (oils and fats only in section, high sugar foods
outside the plate) or the Eatwell Plate (section for foods high in sugars and fat), or a hybrid. For
example, the introduction on page6 lines 38-42 describe the 5 sections of the new EWG as the basis
of the model, but in the methods on page 9 the researchers appear to have used the Plate for noncomposite foods,(i) the Guide for composite foods (ii), while condiments/unclassified items (iii) refers
to “Eatwell groups“ which is unclear. On page 10 is it explained that the categories used for modelling
differ from the EWG – this should be mentioned earlier. I can see why the researchers needed to do
this – how else to show the effect of the sugars target? However, the paragraph on page 6 may need
to be revised; unless I am mistaken, what the study appears to have done is to calculate the impact of
old and new recommendations, using the illustration of the Old Eatwell plate. Referring to this as the
Eatwell Guide is confusing when surely what is meant is the “modelled diet scenario”
Response: We agree that the description of the Eatwell Guide categories could have been clearer
and we have revised the manuscript throughout to clarify this. In response to the reviewer‟s specific
points:
• The analysis was conducted using the five food categories used for the eatwell plate. Public Health
England (PHE) used the results of the optimisation modelling to define the angles of the new Eatwell
Guide, but due to the results of consumer research the names of the food groups were changed for
the Eatwell Guide. For four of the groups, only the name was changed – the foods that were included
in these categories remained the same. For the „foods high in fat and sugar‟ category, PHE decided to
move all foods from this category to the bottom left hand corner of the Eatwell Guide with the
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exception of „oils and spreads‟ (PHE, 2016). In the published Eastwell Guide the angle for the new
„oils and spreads‟ segment is 1%, which is the amount of the „foods high in fat and sugar‟ category
made up of oils and spreads from our analyses (see https://www.gov.uk/government/publications/theeatwell-guide/the-eatwell-guide-how-to-use-in-promotional-material ). In this paper we have retained
all the types of foods included in the former „foods high in fat and sugar‟ category and Table 1 shows
that this is 3.8 % in the modelled diet. For these reasons, we have used, in this paper, the new
Eatwell Guide names for all of the food categories with the exception of „foods high in fat and sugar‟
category where we used the old name as it was a more appropriate description of the modelled
category. We have added a description of this in the methods.
• Both the eatwell plate and the Eatwell Guide treat composite foods and condiments, etc. in the same
way. We have updated the manuscript so this ambiguity is removed.
4. For example, figure 1 shows the changes resulting from the old and new recommendations
compared to the current diet very well- but is this in terms of the Plate categories, not the Guide
categories. The footnote should make it clear what the purple category represents for each barcurrently it merely describes the EWG and implies that for the right hand bar (EWG) purple represents
only oils and fats. From Table 3 it looks like this looks like both high sugar high fat foods and oils and
spreads, i.e. the old Plate classification.
Response: We have added the following to the methods section to clarify this: “Note that after
consumer research, the names of four of the eatwell plate food categories were changed in order to
emphasise sustainable choices within those categories (PHE, 2015). In this paper we use the new
Eatwell Guide names of these food categories. For the remaining category („foods high in fat and
sugar‟) we use the older name from the eatwell plate. This is because the Eatwell Guide uses the
name „oils and spreads‟ and moves many of the foods from this category to the bottom left hand
corner of the guide (PHE, 2015). However, our analyses include these foods so we retain the older
(more descriptive) name. For clarity, the angle of the „oils and spreads‟ segment of the published
Eatwell Guide is 1% and represents merely the fats and oils of „foods high in fat and sugar‟.
5. Authors could also discuss the implications of leaving alcoholic drinks out of the model, as this
represents a non-trivial source of energy for many people. Omission may have over constrained the
energy intake.
Response: We agree that the inclusion of alcohol in our model could have changed the results. It
would allow, for example, for a reduction in calories from alcohol to be replaced by calories from fruit
and vegetables. However, it also could have unexpected consequences. If we include alcohol then it
would make sense to change the macronutrient constraints to percentages of total energy (as
opposed to percentages of food energy). Then the model would find that increasing alcohol
consumption would be a beneficial means of reducing the relative contribution of saturated fat in the
model! On theoretical grounds we do not think it is appropriate to include alcohol in the modelling
process as alcohol consumption is a different behaviour to food consumption and it is not clear that
food and alcohol are substitutes in the way that different food groups are. We have not added a
discussion of this in the paper as we have very limited space due to other extensive revisions.
6. Given that the optimisation modelling was designed to produce a solution with the smallest total
change to existing habits, this “best” result involves drastic changes, which as they point out are
unprecedented in recent history. Although it is true that the model itself cannot take account of
behaviour, the authors should discuss the outcome and what it means in greater depth. For example,
the Eatwell scenario diet is higher in carbohydrate than SACN recommended and low in fat, (as no
upper limit was set for CHO or lower limit for fat). The fibre target is possibly the driver for the huge
increase in starchy foods and higher CHO intake, the sugar target the driver for the big decrease in
sugary foods. Possibly, saturated fat and salt were drivers for the lower meat and dairy consumption
as well as calorie displacement from the food groups that need to increase.
Response: We have now conducted a sensitivity analysis to assess which of the constraints are the
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most difficult to achieve (and hence are having the biggest impact on the makeup of the modelled
diet) and found them to be the free sugars, sodium and fibre constraints. We have added these
results to the paper (see earlier comment). We have added the changes in carbohydrate and fat in the
modelled diet scenario to the discussion.
7. The comparison with other similar modelling studies should be expanded. For example, reference
29 is mentioned only in the context of sustainability but is highly relevant. Their model was designed
with acceptability as a constraint and they discounted an option that increased breakfast cereal but
provided less milk to go with it (as in the current scenario). Incidentally the amount of milk quoted in
Table 3 is barely enough for 3 cups of tea.
Response: We have moved the discussion of the two optimisation modelling studies that included
sustainability constraints to the „comparison with other literature‟ section and included a discussion of
acceptability constraints in this section.
8. Page 14 Lines 18-46 discusses historic precedents for changes in consumption, including large
declines in some dairy products since the 1980s; the tone is optimistic. However, the changes in dairy
referred to in Line 45 mainly involved switching to low fat versions within the product category.
Reversal of current trends such as doubling the amount of bread and potatoes or fruit and vegetables,
are likely to be much harder.
Response: We agree that the comparison to changes in milk consumption and butter and spreads
were unwarranted as these switches were due to changes within category and the Eatwell Guide
would require changes between food categories. We have removed that line from the revised
manuscript.
9. It would be helpful if the authors could provide more or different references as examples of
successful dietary interventions, if possible. 21 was a review on portion control and 22 is NICE
recommendations (perhaps a more specific reference in the report would be helpful). There are
probably few examples of successful interventions of this magnitude, the Finnish example of SFA
reduction comes to mind.
Response: We have added a reference to the North Karelia project which is clearly relevant to the
discussion of large scale public health action to change diets. We acknowledge in the discussion that
the scale of change needed to meet the recommended diet is unprecedented and would require a
combination of many successful public health interventions (hence the reference to NICE which
identifies a range of potential interventions).
10. The comparison with previous studies is in 2 places in the discussion and could be reorganised.
Page 17 lines 13 to 46 highlight important differences between the findings of this study and others in
US and France, both of which suggested an increase in dairy.
Response: We have reordered the discussion so that all the comparisons with other literature are in
one place.
11. Slightly more could be said about micronutrients, for example likely lower bioavailability of iron,
zinc, calcium.
Response: We have added a paragraph about bioavailability to the limitations section of the
discussion (see response to earlier reviewer).
12. Further work that is clearly needed is to devise meal plans based on these recommendations
under same assumptions about supermarket foods. The meal plans by BNF could be referred to but
include very few pre-prepared meals. More realistic scenarios are needed to see if the diet is
workable for time-poor or resource-poor groups.
Response: We have added a sentence about the development of meal plans to the future work
section and referenced the BNF meal plans.
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13. Further modelling could look at acceptability constraints and scenarios with more leeway, for
example, the energy constraint: a higher energy allowance to replace kcals from alcoholic drinks
could allow more oils and fats.
Response: We have conducted sensitivity analyses around the objective function and looked at
varying each constraint in turn to assess its impact on the modelled diet. We have also described in
the paper how our objective function mitigates against the need for acceptability constraints (in our
modelled diet, none of the 125 food groups are consumed at a level greater than 25% of the
maximum level of consumption found in the NDNS). We have not conducted sensitivity analyses
around including alcohol in the modelling (see earlier response).
14. I presume you used NDNS data on NMES as proxy for free sugars, although the definitions are
slightly different (although that for free sugars has not yet been finalised). This should be mentioned in
limitations (NMES slightly over-estimates free sugars intake). More dried fruit would be allowed in the
model scenario without pushing up free sugars.
Response: We have altered the NDNS dataset in order to use free sugars (using the definition
provided in the manuscript) for our analyses. We did not use NMES as a proxy for free sugars.
Other comments:
Abstract
• The important detail of which dietary recommendations are included is inserted halfway through the
results. It would be better to mention it earlier (perhaps under Design)
Response: This has now been moved to the „design‟ section.
• Abstract Line 19 aged 19 and above. Should this be “aged 19y and above”?
Response: We have made this change.
• Results line 32: “Reductions in consumption of beans… etc “ Although this is how the Eatwell guide
describes the category, perhaps say reduction in “meat and alternatives” ?
Response: We agree the names are very cumbersome, but we think it is important to use the full
names to reduce the possibility of confusion.
Methods
• Page 7 line 30 “average consumption” - better to say “mean”
Response: We have made this change.
• Page 8 line 33. Portion sizes for NDNS were not just taken from the portion size handbook but
estimated using household measures, pack sizes, photos as well.
Response: We have added this information.
Results
• Page 11 Line 38 Figure 1 shows breakdown by Eatwell guide categories or Eatwell Plate (see
above)?
Response: We have made adjustments throughout the paper to ensure clarity.
• There are some discrepancies between the “5 a day” allowances and the modelling, in regard to
Fruit Juice and Smoothies. The NHS choices website ( 5 a day) states „One 150ml glass of
unsweetened 100% fruit/vegetable juice or smoothie combined can count as maximum one portion”,
whereas the modelling appears to allow 1 portion of fruit juice (150ml) and 2 portions (300ml) of
smoothies per day. The Fruit juice advice has recently been “clarified” but the authors should mention
this difference under limitations and whether it would have affected the estimates (probably by very
little).
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Response: We have added a line in the limitations about this change in definition, which does not
affect our results.
• Table 2: AER should be EAR. RNI for Vitamin D is now 10ug/day.
Response: We have updated this table accordingly.
• Fig 1 is duplicated pg. 27?
Response: We do not know what the reviewer means.
Finally I would like to congratulate the authors on tackling this complex and important task and writing
a very absorbing paper. I hope the comments will be helpful.
Response: We thank the reviewer for their comments which were very helpful.
References
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measurement matters. New England Journal of Medicine, 2016;375(6):580-586.
Darmon N, Ferguson E, Briend A. Impact of a cost constraint on nutritionally adequate food choices
for French women: an analysis by linear programming. Journal of Nutrition Education and Behaviour,
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Darmon N, Ferguson E, Briend A. A cost constraint alone has adverse effects on food selection and
nutrient density: an analysis of human diets by linear programming. Journal of Nutrition,
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Ello-Martin J, Ledikwe J, Rolls B. The influence of food portion size and energy density on energy
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Hurrell R, Egli I. Iron bioavailability and dietary reference values. American Journal of Clinical
Nutrition, 2010;91:1461S-1467S.
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recommendations into realistic and individual-specific food choices. American Journal of Clinical
Nutrition, 2010;91:421-430.
Mente A, O‟Donnell M, Rangarajan S, Dagenais G, Lear S, McQueen M, et al. Associations of urinary
sodium excretion with cardiovascular events in individuals with and without hypertension: a pooled
analysis of data from four studies. Lancet, 2016;388(10043):465-475.
NatCen Social Research, MRC Human Nutrition Research, University College London Medical
School. National Diet and Nutrition Survey Years 1-4, 2008/09-2011/12. Public Health England and
Food Standards Agency: London, 2015.
Perignon M, Masset G, Ferrari G, Barre T, Vieux F, Maillot M, Amiot M-J, Darmon N. How low can
dietary greenhouse gas emissions be reduced without impairing nutritional adequacy, affordability and
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Public Health England. The Eatwell Guide: How does it differ to the eatwell plate and why? PHE:
London, 2016. Available at
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/528201/Eatwell_guide_
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VERSION 2 – REVIEW
REVIEWER
REVIEW RETURNED
GENERAL COMMENTS
Sigrid Gibson
Sig-Nurture Ltd
26-Sep-2016
The authors have improved the paper by better discussion and
sensitivity checks. A few minor points could clarify some aspects
further.
1. Abstract should mention the date of the NDNS data used (20082011)
2. It should be made clear earlier on that the modelling is based on
the population average amounts, not individuals.For example
inserting 'population' in the abstract before average in line 11
3. Where average is used, "mean" would be more appropriate in
most instances eg page 9 lines 11-22.
4. The keywords include "linear programming". Is this correct as the
methods mention non-linear algorithm?
5. The discussion of underreporting Page 17 para line 28-45 says
that underreporting may have exaggerated or underplayed the
changes required depending on whether a higher or lower amount is
recommended. I agree that under-reporting "across the board"
would have this effect when comparing absolute amounts consumed
vs guidelines, but free sugar change would not be underestimated
by this type of under-reporting because the guideline is based on %
energy. Only macronutrient-specific under-reporting of sugar,
relative to fat, protein etc would do this. If possible this should be
clarified, but it is a minor point.
6. More important perhaps is to mention that sodium is certainly
underrestimated in the model because NDNS excludes salt added in
cooking or at the table (hence urine analysis is used). This means
that the sodium target of <6g is even more of a problem to reach.
Limitation of the sodium intake assessment in NDNS should be
mentioned somewhere.
VERSION 2 – AUTHOR RESPONSE
Responses to reviewers‟ comments
Reviewer 3 comments
1. Abstract should mention the date of the NDNS data used (2008-2011)
Response: This has been added.
2. It should be made clear earlier on that the modelling is based on the population average amounts,
not individuals. For example inserting 'population' in the abstract before average in line 11
Response: We have added this to the abstract to make it clearer. We have also amended the
introduction of the paper to make it clear that we are modelling population averages rather than
individual diets.
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3. Where average is used, "mean" would be more appropriate in most instances eg page 9 lines 1122.
Response: We agree with the reviewers and have gone through the manuscript to replace „average‟
with „mean‟ where we think that this is a better description.
4. The keywords include "linear programming". Is this correct as the methods mention non-linear
algorithm?
Response: Thank you for spotting this. We have amended this to „non-linear programming‟.
5. The discussion of underreporting Page 17 para line 28-45 says that underreporting may have
exaggerated or underplayed the changes required depending on whether a higher or lower amount is
recommended. I agree that under-reporting "across the board" would have this effect when comparing
absolute amounts consumed vs guidelines, but free sugar change would not be underestimated by
this type of under-reporting because the guideline is based on % energy. Only macronutrient-specific
under-reporting of sugar, relative to fat, protein etc would do this. If possible this should be clarified,
but it is a minor point.
Response: We agree with the reviewer and have altered the discussion of this point accordingly.
6. More important perhaps is to mention that sodium is certainly underrestimated in the model
because NDNS excludes salt added in cooking or at the table (hence urine analysis is used). This
means that the sodium target of <6g is even more of a problem to reach. Limitation of the sodium
intake assessment in NDNS should be mentioned somewhere.
Response: We agree with the reviewer and have added this limitation to the discussion.
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Eatwell Guide: modelling the dietary and cost
implications of incorporating new sugar and
fibre guidelines
Peter Scarborough, Asha Kaur, Linda Cobiac, Paul Owens, Alexandr
Parlesak, Kate Sweeney and Mike Rayner
BMJ Open 2016 6:
doi: 10.1136/bmjopen-2016-013182
Updated information and services can be found at:
http://bmjopen.bmj.com/content/6/12/e013182
These include:
References
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