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Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com PEER REVIEW HISTORY BMJ Open publishes all reviews undertaken for accepted manuscripts. Reviewers are asked to complete a checklist review form (http://bmjopen.bmj.com/site/about/resources/checklist.pdf) and are provided with free text boxes to elaborate on their assessment. These free text comments are reproduced below. 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com (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. Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com (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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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. Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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). Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 Cogswell M, Mugavero K, Bowman B, Frieden T. Dietary sodium and cardiovascular disease risk – 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, 2006;38:82-90. 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, 2002;132:3764-3771. Ello-Martin J, Ledikwe J, Rolls B. The influence of food portion size and energy density on energy intake: implications for weight management. American Journal of Clinical Nutrition, 2005;82:236S241S. He FJ, Li J, MacGregor GA. Effect of longer term modest salt reduction on blood pressure: Cochrane systematic review and meta-analysis of randomised trials. BMJ, 2013;346:f1325 Hurrell R, Egli I. Iron bioavailability and dietary reference values. American Journal of Clinical Nutrition, 2010;91:1461S-1467S. Maillot M, Vieux F, Amiot M-J, Darmon N. Individual diet modeling translates nutrient 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 acceptability of the diet? A modelling study to guide sustainable food choices. Public Health Nutrition, 2016;doi:10.1017/S1368980016000653 Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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_ whats_changed_and_why.pdf Scientific Advisory Committee on Nutrition. Carbohydrates and health. The Stationery Office: London, 2015. 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. Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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. Downloaded from http://bmjopen.bmj.com/ on May 11, 2017 - Published by group.bmj.com 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 This article cites 25 articles, 10 of which you can access for free at: http://bmjopen.bmj.com/content/6/12/e013182#BIBL Open Access This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. 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