Discrepancies between two long-term dietary datasets in the United Kingdom (UK)

Background: Studying dietary trends can help monitor progress towards healthier and more sustainable diets but longitudinal data are often confounded by lack of standardized methods. Two main data sources are used for longitudinal analysis of diets: food balance sheets on food supply (FBS) and household budget surveys on food purchased (HBS). Methods: We used UK longitudinal dietary data on food supply, provided by the Food and Agriculture Organisation (FAO) (FAO-FBS, 1961-2018), and food purchases, provided by the Department for Environment, Food and Rural Affairs (Defra) (Defra-HBS, 1942-2018). We assessed how trends in dietary change per capita compared between FAO-FBS and Defra-HBS for calories, meat and fish, nuts and pulses, and dairy, and how disparities have changed over time. Results: Estimates made by FAO-FBS were significantly higher (p<0.001) than Defra-HBS for calorie intake and all food types, except nuts and pulses which were significantly lower (p<0.001). These differences are partly due to inclusion of retail waste in FAO-FBS data and under-reporting in Defra- HBS data. The disparities between the two datasets increased over time for calories, meat and dairy; did not change for fish; and decreased for nuts and pulses. Between 1961 and 2018, both FAO-FBS and Defra-FBS showed an increase in meat intake (+23.4% and +1.4%, respectively) and a decrease in fish (-7.1% and -3.2%, respectively). Temporal trends did not agree between the two datasets for dairy, calories, and nuts and pulses. Conclusions: Our finding raises questions over the robustness of both data sources for monitoring UK dietary change, especially when used for evidence-based decision making around health, climate change and sustainability.


Introduction
Monitoring dietary trends is important for measuring progress towards healthier and more sustainable diets. While several longitudinal monitoring databases exist, a number of challenges limit their usefulness for analysis including scarcity of standardized methods (De Keyzer et al., 2015;Perignon et al., 2017), lack of waste monitoring (Whybrow et al., 2017) and variation in the stages of food production being measured (Bandy et al., 2019;Serra-Majem et al., 2003). Both food balance sheets (FBS) (published by Food and Agriculture Organisation (FAO), hereafter referred to as FAO-FBS) and household budget surveys (HBS) (published by the Department for Environment, Food and Rural Affairs (Defra) in the United Kingdom (UK), hereafter referred to as Defra-HBS) have been used to approximate trends in consumption over time (for example Grünberger, 2014 andPeng et al., 2015).
Food balance sheets measure food consumption from a food supply perspective and considers domestic production, imports and exports. The advantage of FBS over HBS is that they are produced in a standardised format, which facilitates comparison between countries, and the combination of food data with associated statistics on trade and agricultural practices (Balanza et al., 2007;Del Gobbo et al., 2015). However, despite adjustments, FAO (2017) report that these FBS can be incomplete or unreliable due to gaps and inaccuracies in underlying data, and complexities in transforming data from a diverse range of sources into a standardised format. HBS measure food consumption from a food purchase perspective (FAO, 2001). Alongside the HBS published by Defra since 1942, Public Health England and the UK Food Standards Agency have conducted the National Diet and Nutrition Survey since 2008-09, which measures food consumption using dietary recall (Public Health England, 2020). Here we use the HBS surveys produced by Defra due to the long time period of their operation (81 years compared to the 13 years of the National Diet and Nutrition Survey), permitting the analysis of long-term temporal trends. The strength of HBS is that data are gathered alongside demographic information, which enables the study of consumption characteristics. FBS and HBS measure food consumption at a different stage of the food supply chain: FBS record the quantity of food that reaches shops and other food outlets, while HBS record the quantity of food that is bought. Because of this, FBS include retail waste in quantity of food supply, whereas HBS do not. Both FBS and HBS estimates include waste at the household level, so overestimate the quantity of food actually eaten. In the UK, 70% of post-farm-gate waste occurs in households (WRAP, 2021). When conducting HBS, reported food purchases are often less than the actual quantity of food bought due to participants ' under-reporting (Mendez et al., 2004; Office for National Statistics, 2016) ( Figure 1).
To our knowledge, the discrepancies between FBS and HBS for monitoring dietary change have never been quantified for the UK. However, as both data sources play a pivotal role in providing evidence for decision-making, it is important that these discrepancies are mapped, and their implications for evidence generation are known. Findings from studies outside the UK indicate that using only one of these methodologies to assess dietary trends can be highly problematic (Del Gobbo et al., 2015;Serra-Majem et al., 2003), and hinders food policy planning, which requires accurate knowledge of food consumption patterns (Serra-Majem et al., 2003). Investigating the reasons behind data discrepancies improves understanding of the limitations of these datasets (Benthem de Grave et al., 2020). In this study, we compared time-series FBS data produced by the FAO (FAOSTAT, 1961-2018 on UK food supply to HBS data produced by Defra (National Food Survey, 1942-2000and Family Food Module, 2000-2018, Defra-HBS) on UK food purchases to determine to what extent the data sources agree, both on overall calorie intake and specific food groups. We assessed how agreement between FAO-FBS and Defra-HBS has changed between 1961 and 2018 (the most up to date data currently available) and the relevance of differences between FAO-FBS and Defra-HBS for evidence-based decision making.

Secondary datasets
Food balance sheets (FAO-FBS) consist of compiled, cleaned and standardised data from national statistics on food supply -the quantity of food available to buy per person. Data for food balance sheets are gathered from a number of sources, including industrial production surveys, estimates based on expert observations and household and expenditure surveys (FAO, 2001). The basic data are adjusted by the FAO to account for biases and inaccuracies in data reporting and estimate missing data. The methodology of FAO-FBS was updated in 2014. The primary change was the shift from using 2015 United Nations Development Programme (UNDP) population data (used before 2014) to using updated 2019 UNDP population

Amendments from Version 2
The methodology of FAO data was updated in 2014. Previously we handled data between 1961 and 2018 as a continuous time series, without adjusting for this change in methodology. However, it is necessary to adjust for the methodology change to provide accurate estimates of changes in food supply over time. Peter Alexander drew our attention to this and has been included as a co-author due to his contributions. The 2014 to 2018 values have been adjusted to give values consistent with the older methodology. A mean offset ratio between old and new methodology values was calculated for each food category using the four overlapping years (2010 to 2013) where data was published under both methodologies. Food category values for 2014 to 2018 were adjusted by multiplying them by the associated offset ratio. The FAO has also published updated data for 2018 since the time of publishing, so we have updated the paper to include the updated data values. These updates affect the reported change in food supply between 1961 and 2018 (and between 2008 and 2018) for most food groups, and trends in the differences between Defra-HBS and FAO-FBS values, but do not affect the conclusions of the paper.
An error in the "Total Meat" row of Table 2 has been corrected. This error did not affect underlying data or results presented in figures or in text. data (FAO, 2020). As some of the revised population numbers are higher than those used previously this can affect per capita values. To account for this, the 2014 to 2018 values were adjusted to give values consistent with the older methodology. A mean offset ratio between old and new methodology values was calculated for each food category using the four overlapping years (2010 to 2013) where data was published under both methodologies. Food category values for 2014 to 2018 were adjusted by multiplying them by the associated offset ratio. Figure 1a summarises the overall method of data collection and processing in FAO-FBS (FAO, 2001;FAO, 2017;Ritchie & Roser, 2020). As data are produced in a standardised format on nearly all food products FAO-FBS allows comparison between countries.

Any further responses from the reviewers can be found at
We compared these FAO-FBS with Defra-HBS, which consists of three household datasets: The National Food Survey, the adjusted National Food Survey and the Family Food Module.
All are HBS that record purchases over time of the quantity of food and drink bought by a household. The National Food Survey and Family Food Module use a stratified random sample (with clustering) of UK households (Defra, 2012). In 2011, 5692 households were sampled. Surveys are spread out throughout the year to ensure seasonal effects are accounted for. Both include a voluntary survey in which purchases of food and drink (after 1992) are recorded over a two-week period. Adjustments are made by Defra to account for sampling bias and non-response bias. We made no further adjustments to account for data inaccuracies and biases, and used the data as provided by Defra. To account for differences between the National Food Survey and the Family Food Module methodology, adjusted quantities of the National Food Survey were produced by Defra for 1974to 2000(Defra, 2011. Data collection methodologies of Defra-HBS are summarised in Figure 1b and c (Defra, 2011;Defra, 2012). The difference between Defra-HBS methodologies was deemed small enough to treat all three Mutton & Goat Meat datasets as continuous. All data on supply and purchases are expressed in grams/capita/day other than calorie intake which is expressed in kcal/capita/day.
As this study did not involve human subjects and used open-source secondary data which did not include any personal information, an independent ethical review was not required.
The datasets used in this study can be found in the Data availability section (Smith et al., 2022).

Data analysis
Data analysis was carried out in Excel Version 2108 and R version 3.6.1 (R Core Team, 2020). Data were converted from kg/capita/year to g/capita/day then aggregated according to food types (Table 1). We calculated mean daily per capita supply and production of meat and fish, dairy, nuts and pulses, and calories for each year covered by each data source (Table 1).
No data were removed during the analysis.
For Defra-HBS, cheese was converted to milk equivalent by multiplying mass (g) by 10 (the extraction rate from milk to cheese is 10% in the United Kingdom [FAO, 2000]). Milk and products in Defra-HBS were converted from millilitres to grams (using the density of cow's milk reported by Cziszter et al., 2012 [1.03g/cm 3 ]). The food types analysed were chosen as they are produced in categories which are comparable between the two data sources, and provide an indication of changes in total consumption (calorie intake) and protein intake (meat, fish, dairy, nuts and pulses represent the majority of total protein intake in the UK [British Nutrition Foundation, 2018]). Differences in aggregation of food categories between FAO-FBS and Defra-HBS makes comparison between some food types challenging. For example, Defra-HBS report purchases of bread, whereas FAO-FBS report supply of wheat and products. As many food groups are produced in aggregated categories, converting to nutritional intake can be difficult (Serra-Majem et al., 2003). Whilst data on supply and purchases of selected macronutrients are provided by FAO-FBS and Defra-HBS, here we have compared data on food groups between the two data sources, as data on food supply and purchases have been used to assess how diets (Serra-Majem et al., 2003;Thar et al., 2020), and their associated health (Aiello et al., 2019) and environmental impacts (Lucas et al., 2021) have changed.
We fitted a linear model for FAO-FBS food supply against time  for all food types and calorie provision to analyse long term trends in the UK diet. We repeated this for Defra-HBS food purchases against time .
Ruminant supply and purchases were calculated by summing supply and purchases of beef and mutton (lamb). Gradient of slope was compared between FAO-FBS and Defra-HBS (mean change, g/capita/day per year).
For each year (1961-2018) we calculated the difference between FAO-FBS food supply and Defra-HBS food purchases (as a percentage of Defra-HBS purchases) for each food type in turn. We explored whether this difference changed over time using correlation tests: Pearson's product-moment for normally distributed data, Spearman's rank for non-normally distributed data, after assessing for normality using Shapiro-Wilk. Finally, we estimated the mean difference between FAO-FBS food supply and Defra-HBS food purchases across all years for each food category.
Temporal trends: food type intake Long-term trends in UK consumption differ between FAO-FBS and Defra-HBS (Table 2). Between 1961 and 2018, both data sources do show increasing intake of meat (FAO-FBS, +23.4%; Defra-HBS, +1.4%) and decreasing intake of fish (FAO-FBS, -7.1%; Defra-HBS, -13.9%) though the magnitude of change generally differs substantially. However, FAO-FBS shows an increase in calorie consumption (1961-2018, +3.4) while Defra-HBS records a decrease (1961-2018, -17.3%). There was no significant trend in dairy consumption when based on FAO-FBS but there was a significant decrease over time when based on Defra-HBS ( Figure 2 and Table 3). Per capita supply of nuts and pulses show a clear increasing trend when based on FAO-FBS, while the purchase data from Defra-HBS show a stable per capita purchase pattern.
Disaggregating total meat and fish by individual meat type, gives further detail on the different trends in supply and purchases. Both datasets show a sharp decrease in ruminant intake and a steep increase in poultry consumption ( Figure 3, Table 2 and Table 3). Between 1961 and 2018, Defra-HBS estimated steeper falls in ruminant consumption than FAO-FBS (FAO-FBS -38.4%, Defra-HBS -67.4%) and a smaller increase in poultry consumption (FAO-FBS, +465.5%; Defra-HBS +277.8%, Table 2). Pork showed more stable consumption over time, but the direction of change differed between with datasets   with FAO-FBS showing a slight increase in consumption and Defra-HBS showing a slight decrease in consumption (FAO-FBS 5.0%, Defra-HBS -11.2%). However, these results for ruminants, pork and poultry should be interpreted cautiously, as the Defra-HBS categorisations did not allow the total intake of these meat types to be calculated (for example, takeaways and meat pies could not be assigned), unlike FAO-FBS data (Table 1).
Long-term trends in consumption were not always representative of short-term trends (Figure 3, Table 2 and Table 4). Between 2008 and 2018, Defra-HBS estimated significant declines in meat consumption (-3.0%), in contrast to the significant increase estimated between 1961 and 2018 (Table 3).

Temporal trends: differences between FAO-FBS and Defra-HBS
While a difference between supply and purchase data is to be expected, the difference between FAO-FBS food supply and Defra-HBS food purchases increased between 1961 and 2018 ( Figure 4) for all food types (other than nuts and pulses), and for calorie intake. For nuts and pulses there was again a positive relationship between the difference between FAO-FBS food supply and Defra-HBS food purchases and time, but as FAO-FBS supply of nuts and pulses was lower than Defra-HBS purchases at the start of the timeseries, FAO-FBS supply and Defra-HBS purchases converged over time. When disaggregated by individual meat types, the difference between FAO-FBS and Defra-HBS increased over time for all meat types (ruminants, pork and poultry), but not for fish, which showed no change over time.

Discussion
The per capita quantities of food supplied in the UK (as reported by FAO-FBS) and purchased (as reported by Defra-HBS) are significantly different for all food types and for calorie consumption. These differences affected the long-term trends in food consumption observed in the UK, as trends in consumption of dairy, nuts and pulses and calorie intake did not agree between FAO-FBS and Defra-HBS, and while the trends in meat and fish consumption did agree, the slope of the trends differed between the two data sources. The difference between FAO-FBS and Defra-HBS was not constant over time, and for all food types and calorie intake (other than nuts and pulses and fish) FAO-FBS and Defra-HBS values diverged between 1961 and 2018.  (1997) showed that overreporting of 'healthy' foods occurs, perhaps partly explaining the overprediction of nuts and pulses by Defra-HBS relative to FAO-FBS.
The differences between reported consumption by FAO-FBS and Defra-HBS could be due to genuine differences in supply and purchases of food, or inaccuracies in data collection. Food supply estimates from FAO-FBS include retail food waste (Poore & Nemecek, 2018), whereas Defra-HBS food purchases do not, so some of the observed differences could be due to retail food waste. If so, we would expect greater discrepancies in food with a short shelf-life (Parfitt et al., 2010). However, while meat, fish and dairy usually have a shorter shelf life than nuts and pulses (Premavalli, 2000), the latter exhibit a greater difference between mean FAO-FBS food supply and mean Defra-HBS food purchases. It seems likely that inaccuracies in data collection, primarily due to under-reporting, are also important. The National Food and Dietary Survey (a HBS similar to Defra's but run by Public Health England and the UK Food Standards Agency; Public Health England, 2020) has been shown to underestimate calorie consumption. Reported energy intake was shown to be 34% less than energy expenditure (measured using doubly labelled water), giving an indication of substantial under-reporting in the National Food and Dietary Survey (Office for National Statistics, 2016). A similar level of under-reporting in Defra surveys would account for most of the difference seen between FAO-FBS and Defra-HBS data.
As well as differences in estimates of overall per capita consumption we found no agreement between long term trends in FAO-FBS food supply and Defra-HBS food purchases of dairy, calories and nuts and pulses. As such, drawing conclusions about changes in the quantity of these foods consumed is challenging. Quantification of under-reporting and household and retail waste might reveal whether the divergence between FAO-FBS and Defra-HBS-based estimates are due to genuine divergences in supply and purchases or inaccuracies in data collection. Retail waste increased by 6% between 2015 and 2018 (WRAP, 2020), yet only represented 2.4% of post farm waste in 2015 (British Retail Consortium, 2016). Data on long-term trends on UK retail waste are limited, but given it's small contribution to total post farm waste, it's unlikely waste is a major factor causing the divergence between FAO-FBS and Defra-HBS. Harper & Hallsworth (2015) suggest that under-reporting has increased over time and is responsible for falling calorie intake. They propose that increasing obesity levels, increase in desire to lose weight, increased eating outside the home and snacking, falling response rates of surveys and growing disparities between reference data and true portion sizes or food energy density, are responsible for the increase in under-reporting. Here we show that increase in under-reporting may not be limited to calorie intake, as trends in calorie intake differences between FAO-FBS and Defra-HBS are comparable to those of meat and fish, and dairy. These results suggest that the composition of the UK diet should be informed by both FAO-FBS and Defra-HBS data, with knowledge of their limitations. Stewart et al. (2021) found that according to the National Diet and Nutrition Survey (NDNS), meat consumption in the UK declined by 17.4% (103.7g to 86.3g) between 2008/9 and 2018/19. This is a smaller quantity of meat and a larger decline than the trend we observed from Defra-HBS (3.0% decline in meat intake (155.5g to 150.9g) between 2008 and 2018). FAO-FBS showed the opposite trend in meat intake than the NDNS, with a 4.9% increase in meat supply between 2008 and 2018 (from 223.3g to 234.2g). Both NDNS and Defra-HBS are likely to be subject to under-reporting, unlike FAO-FBS (Office for National Statistics, 2016). Household waste is included in Defra-HBS (as food purchases are measured) but is not in NDNS (as food consumption is measured). However, if household food waste were the only discrepancy between the two datasets, this would indicate 42.8% of purchased meat in UK households is wasted (2018: (150.9-86.3)/ 150.9 = 42.8%), which is substantially higher than the estimated figure for meat and fish household waste of 21% (13.5% avoidable (for example, not used in time) and 7.4% unavoidable (for example, bones and fish heads)) (Quested et al., 2013;Quested & Murphy, 2014). This suggests methodology discrepancies are also contributing to this difference.
Steeper falls in ruminant consumption were estimated by Defra-HBS than FAO-FBS and Defra-HBS estimate a smaller increase in poultry consumption. It is key to be able to compare consumption of different meat types, given the higher environmental impacts of beef compared to chicken (Poore & Nemecek, 2018) and the increased disease burden from increased red and processed meat consumption (Chung et al., 2021). While this is straightforward for FAO-FBS, it is hard to accurately sum up for the Defra-HBS data due to categories such as meat pies, ready meals and burgers and "takeaway miscellaneous meats".
For all food types except nuts and pulses (where the difference over time decreased), the difference between FAO-FBS and Defra-HBS increased between 1961 and 2018. With limited long-term data on the prevalence of under-reporting and extent of waste (FAO, 2001) identifying reasons for this divergence is challenging. To our knowledge, the increasing difference between FAO-FBS food supply and Defra-HBS food purchases has not been documented before. Due to the problems the divergence between these datasets poses for accurate monitoring of UK dietary change, identifying the reasons for this is an important topic for future research. Nuts and pulses are an exception to the observed divergence, with FAO-FBS supply and Defra-HBS purchases converging overtime. This could be due to an increase in home production of food since 1985 (Defra, 2021), or a decrease in under-reporting (for example due to the rise in awareness of the environmental benefit of switching to plant-based protein (Alae-Carew et al., 2022)).
Analyses of UK dietary trends are impeded by the differences between FAO-FBS and Defra-HBS. One approach, used by Del Gobbo et al. (2015), is to apply calibration models to adjust FAO-FBS to dietary surveys. This assumes that dietary surveys provide an accurate estimation of consumption, which given the observed levels of underreporting in the National Food and Dietary Survey (Office for National Statistics, 2016), may not be the case. To improve understanding of UK dietary trends, monitoring of underreporting across time and food types is necessary. Additionally, data on the proportion of food wasted at each stage of the production chain, disaggregated by food type, would assist in reconciling differences between FAO-FBS and Defra-HBS. If data collection on waste and underreporting were integrated into current data collection processes, and published alongside dietary datasets, this would allow uncertainties to be reduced, whilst retaining consistency in long term temporal monitoring. Improving data availability on waste and underreporting is key for enabling robust analyses of UK dietary change.
With current data quality and availability, we recommend that where possible, both FAO-FBS and Defra-HBS are used in parallel to monitor dietary trends. For specific applications, use of one dataset may be appropriate. For example, when conducting assessments of the environmental impact of food consumption, the presence of underreporting in Defra-HBS risks underestimation of the environmental impact of UK food consumption. In contrast, food balance sheets (FAO-FBS) are not subject to underreporting, and are readily conciliable with major life cycle analyses datasets (Poore & Nemecek, 2018), so are best suited to this application. The inclusion of retail waste in FAO-FBS estimates impedes monitoring of purchasing patterns. Household budget surveys (Defra-HBS) monitor purchases directly, and are published alongside demographic data, so are appropriate for monitoring changes in purchasing patterns, and comparisons between demographic groups. Understanding dataset methodology and limitations supports decision making in UK dietary analyses, when identifying the most suitable dataset or datasets to use.
Studying the temporal aspect of discrepancies between FAO-FBS and Defra-HBS was a strength of this study.
Here we show that the increasing disparity between FBS and HBS in calorie intake found by Harper & Hallsworth (2015) over time is also present for specific food types. A limitation of this study was that we did not quantify the relative contribution of underreporting, retail waste and other differences in data collection methods to the reported discrepancies. This means that the extent to which inconsistencies are attributable to a genuine difference between supply and purchases, or inaccuracies in data collection, processing, and reporting is unknown. Understanding the reasons for discrepancies between FAO-FBS and Defra-HBS reported here, is important for resolving data inaccuracies and improving consistency of dietary monitoring in the UK.
Exploration of whether such inconsistencies are also present for macronutrients such as protein and fat may be informative, and yield implications for monitoring progress towards healthier diets.
Efforts to make food systems healthier and more sustainable rely on routinely collected data such as FAO-FBS and Defra-HBS (Marshall et al., 2021). The inconsistencies between these datasets -and the challenges in directly comparing them -raises concerns for evidence-based policy making. The National Food Strategy (Dimbleby, 2020) recommends creation of a National Food System data programme to monitor and shape progress towards a better food system. While the envisaged collection of data on land use, retail and environmental and health impacts of food outlined in the National Food Strategy will be a vital resource to solve problems in the UK food system, these efforts may be undermined by the inconsistencies between datasets used to monitor UK food supply and purchases, outlined here. High quality surveys are most common in high income countries such as the UK. If these data inconsistencies exist in the UK, they are likely to exist in other countries as well, as exemplified by Del Gobbo et al. (2015), Grünberger (2014) and Serra-Majem et al. (2003). This raises the question as to whether other methods of data collection are needed for monitoring progress of food systems towards health and sustainability goals, and how inconsistencies in long-term dietary datasets can be reconciled.

Concluding remarks
Data produced on food supply by FAO-FBS and on food purchases by Defra-HBS differ for all food types and for calories, both overall and in terms of temporal trends. Underreporting and retail waste were the main reasons for these differences, with underreporting expected to be the greatest contributor. Further research concerning the reasons for disagreement between FAO-FBS and Defra-HBS is required. Specifically, data collection on temporal trends in underreporting, and food waste at each stage of the production chain, disaggregated by food type, could assist in reconciling the differences between datasets.
We recommend that where possible assessments of dietary trends use both household budget surveys and food balance sheets in parallel, with knowledge of their limitations. For most food groups, the difference between FAO-FBS and Defra-HBS increased over time raising questions about the reliability of both data sources for monitoring dietary change, especially when used as routine data sources for evidence-based decision-making. -National Food Survey data are named 'Household nutrient data from 1940 to 2000 -1940-2000' and 'Household consumption of selected foods from 1942 to 2000 -1942-2000'. Data are available under the terms of the Open Government Licence v3.0.

Data availability
Chung MG, Li Y, Liu J: Global red and processed meat trade and non-

Open Peer Review
In a few places in the paper, other studies are cited that noted that the differences in the databases "can be highly problematic" (Del Gobbo et al. 2015, Sarra-Majem et al. 2003. Did these authors address any of the above ideas related to implications or recommendations? If so, how does your analysis and assessment of implications compare? In other words, provide more detail than "it's problematic."

5.
Minor point: The Excel Version is noted as 2108, which I assume is meant to be 2018.

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes What are ways to improve the data? What recommendations of either future changes in data collection or post processing (but still allow for consistency across the time series)? Could you get closer to the "truth" by adding a third data set, such as national-level sales data for foods like beef? Response 4. We have added the following to the discussion. "Analyses of UK dietary trends are impeded by the differences between FAO-FBS and Defra-HBS. One approach, used by Del Gobbo et al. (2015), is to apply calibration models to adjust FAO-FBS to (FAO-FBS, 1961-2018, and food purchases, provided by the Department for Environment, Food and Rural Affairs (Defra) Defra (Defra-HBS, 1942-2018 Grünberger, 2014 andPeng et al., 2015)." The UK government does not capitalise Defra so we have followed the same formatting.

Comment 3:
There are a couple of 2008-2018 decreasing trends for meat and fish in both databases. It would be good if they are also presented graphically.

Response 3:
We have added trend lines between 2008-2018 (where significant) to figure 2, and added a paragraph to explain these trends in the results. "Long-term trends in consumption were not always representative of short-term trends (Figure 3, Tables 2 and 4). Between 2008 and 2018, both FAO-FBS and Defra-HBS estimated significant declines in meat consumption .2%, Defra-HBS -3.0%), in contrast to the significant increase estimated by both datasets over the whole time period (Table 3). Significant declines in dairy supply between 2008-2018 (-15.0%) were estimated by FAO-FBS despite no significant trend between 1961 and2018. No significant change in supply of nuts and pulses and calorie intake was estimated by FAO-FBS between 2008and 2018, despite significant increases in supply between 1961and 2018."

Comment 4:
The discussion section would benefit from some possible explanations for the discrepancies in nuts and legumes in the case of UK.

Response 4:
While we have provided some explanation for why the difference in estimations between FAO-FBS and Defra-HBS for nuts and pulses might differ from other food groups, we did not provide information on why FAO-FBS and Defra-HBS might be converging for nuts and pulses and not other food groups. As such, we have added the following to the discussion. "Nuts and pulses are an exception to the observed divergence, with FAO-FBS supply and Defra-HBS purchases converging overtime. This could be due to an increase in home production of food since 1985 (Defra, 2021), or a decrease in under-reporting (for example due to the rise in awareness of the environmental benefit of switching to plant-based protein (Alae-Carew et al., 2022))."

Comment 5:
The conclusion section could be expanded to do justice to the study. For example, it is important to emphasise again the issue of waste. Highlights from the findings can also be included.