Environmental impact and nutritional quality of adult
diet in France based on fruit and vegetable intakes

Nathalie Komati, Florent Vieux, Matthieu Maillot, Nicole Darmon, Johanna

Calvarin, Jean-Michel Lecerf, Marie-Josephe Amiot, Luc Belzunces, Delphine

Tailliez

► To cite this version:

Nathalie Komati, Florent Vieux, Matthieu Maillot, Nicole Darmon, Johanna Calvarin, et al. Envi-
ronmental impact and nutritional quality of adult diet in France based on fruit and vegetable intakes.
European Journal of Nutrition, 2024, 63, pp.195-207. 10.1007/s00394-023-03252-3 . hal-04236604

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# Environmental impact and nutritional quality of adult diet in France based on fruit and vegetable intakes

Nathalie Komati<fnref n="1" /> ⒹD· Florent Vieux<fnref n="2" /> ⒹD· Matthieu Maillot<fnref n="2" /> ⒹD· Nicole Darmon<fnref n="3" /> ⒹD· Johanna Calvarin<fnref n="1" /> ⒹD· Jean-Michel Lecerf<fnref n="4" /> ⒹD· Marie-Josèphe Amiot<fnref n="5" /> ⒹD· Luc Belzunces<fnref n="6" /> ⒹD· Delphine Tailliez<fnref n="1" /> ⒹD

Received: 6 April 2023 / Accepted: 8 September 2023

© The Author(s) 2023

## Abstract

**Purpose** To describe the nutritional quality and environmental impact of self-selected diets of adults in France in relation to their fruit and vegetable (FV) intakes.

**Methods** Estimates of food and nutrient intakes were taken from the national INCA3 Survey on food intakes carried out in France in 2014–2015. The population (n = 2121 adults) was split into five quintiles of FV intakes, in g/d (Q1 representing the lowest intake, and Q5 the highest). The nutritional quality of diets was assessed through 4 indicators: mean adequacy ratio (MAR), solid energy density, mean excess ratio (MER) and Programme National Nutrition Santé guideline score 2 (PNNS-GS2). The environmental impacts were measured with environmental footprint (EF) scores and 4 additional indicators: climate change, ozone depletion, fine particulate matter and water use. Indicators were compared between quintiles. Analysis was conducted on diets adjusted to 2000 kcal.

**Results** MAR and PNNS-GS2 increased with increased FV quintiles, while solid energy density decreased. Fibre, potassium, vitamin B9 and vitamin C densities increased with increasing FV intakes. Climate change, ozone depletion and fine particulate matter impacts of diets decreased with increasing quintiles of FV consumption. Conversely, water use impact increased.

**Conclusion** Higher intake of FV is associated with higher nutritional quality of diets and lower environmental impact, except for water use. Given the benefits of fruit and vegetables for human health and the environment, their negative impact on water use could be improved by working on the agricultural upstream, rather than by changing individuals’ food choices and reducing their consumption.

**Keywords** Diet · Fruit and vegetables · Nutritional quality · Environmental impact · Sustainable footprint

## Introduction

The Food and Agriculture Organization of the United Nations (FAO) has defined sustainable diets as those “diets with low environmental impacts which contribute to food and nutrition security and to healthy life for present and future generations. Sustainable diets are protective and respectful of biodiversity and ecosystems, culturally acceptable, accessible, economically fair and affordable; nutritionally adequate, safe and healthy; while optimizing natural and human resources” [1]. This definition clearly shows that all these goals need to converge to ensure sustainable diets. As a result, it is clear that we need to change our diets to accommodate this transition, which could be achieved by including more healthy plant-based foods in our diets, and by increasing the intake of fruit and vegetables (FV) [2].

<figure><img src="image_2.png" /></figure>

<footnote>Nathalie Komati
n.komati@aprifel.com</footnote>

<footnote n="1">¹ Agency for Research and Information on Fruit and Vegetables (APRIFEL), Paris, France</footnote>

<footnote n="2">² MS-Nutrition, Marseille, France</footnote>

<footnote n="3">³ MoISA, University of Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, Montpellier, France</footnote>

<footnote n="4">⁴ Nutrition & Physical Activity Department, Institut Pasteur de Lille, Lille, France</footnote>

<footnote n="5">⁵ INRAE-National Research Institute for Agriculture, Food and the Environment, Montpellier, France</footnote>

<footnote n="6">⁶ INRAE, Laboratory of Environmental Toxicology, UR 0406 A&E, Avignon, France</footnote>
This transition has been recognised in numerous studies
aimed at improving sustainability [3–5].

The health benefits of FV consumption for humans have
been widely explored, with many studies confirming their
role in the prevention of several chronic diseases, such as
cardiovascular diseases [6] and certain types of cancer [7],
as well as premature mortality [6]. These benefits are mainly
associated with their low energy density and high nutrient
densities in fibre, minerals, bioactive substances like vita-
mins and polyphenols, and other phytonutrients that are
beneficial for the body. Moreover, insufficient intake of FV
is one of the top five risk factors for health. According to
the Global Burden of Disease, in 2017, about 3.9 million
deaths were caused by low FV consumption [8]. There-
fore, the World Health Organization (WHO) recommends
a minimum daily intake of 400 g of FV to prevent the risk
of chronic disease and ensure an adequate daily intake of
dietary fibre [9]. However, the consumption of FV is still
insufficient worldwide. In 2019, it was reported that 33% of
the European population (≥ 15 years of age) did not consume
any fruit or vegetables daily, and only 12% consumed the
recommended minimum of 5 servings daily [10]. In France,
the WHO guideline translates at the national level to a rec-
ommended consumption of at least 5 daily servings of FV
(1 serving = 80–100 g) [11], but only 19.5% of the popu-
lation (≥ 15 years of age) meet this recommendation [10].
According to the third French Individual and National Food
Consumption Survey (INCA3) for the years 2014–2015,
approximately 60% of adults in France have an average con-
sumption below the international and national recommenda-
tion (minimum daily intake of 400 g of FV).

Beyond the benefits of FV to human health, the FAO
stated in a recent report that meeting dietary guidelines (e.g.,
at least 400 g/d of FV) is not sufficient to reach environ-
mental targets, and recommended reduced consumption of
animal products while increasing amounts of plant-based
foods to limit greenhouse gas emissions (GHGE), compared
to the current diet [12]. The findings of this report are sup-
ported by a recent review showing that transitioning to plant-
based diets, that focus on plant-derived foods and exclude or
limit most or all animal products, could potentially reduce
diet-related land use by 76%, diet-related GHGE by 49%,
eutrophication by 49%, and green and blue water use by 21%
and 14%, respectively [13].

All dietary patterns proposed for combined nutritional
and environmental qualities (EAT-Lancet, Mediterranean
diet, The New Nordic Diet, and Atlantic Diet) share the
common characteristic of having a high proportion of plant-
based foods, in particular significant quantities of FV [5,
13–17].

However, FV consumption, like most agricultural prod-
ucts, is also associated with environmental impacts. In par-
ticular, when expressed per 100 kcal instead of 100 g, FV

have the highest impact of plant-based products in terms of
GHGE, with impact levels similar to dairy products: 0.29 kg
CO₂ eq/100 kcal of FV versus 0.28 kg CO₂ eq/100 kcal of
dairy [18].

The aim of this study was to explore the nutritional qual-
ity and environmental impacts of self-selected diets of adults
in France in relation to FV intakes. Nutritional quality was
assessed using four general indicators, while environmen-
tal impact was measured using the single environmental
footprint score (EF score) and four additional indicators.
All indicators were compared by quintiles of daily FV
consumption.

**Materials and methods**

Databases

Estimates of food and nutrient intakes were taken from the
third French Individual and National Food Consumption
Survey (INCA3) for 2014–2015, a cross-sectional survey
carried out by the French Agency for Food, Environmen-
tal and Occupational Health & Safety (ANSES) between
February 2014 and September 2015 among a representa-
tive sample of individuals living in mainland France [19].
Briefly, dietary data were self-reported through 3 non-con-
secutive 24-h dietary recalls consisting of 2 weekdays and
1 weekend day spread over 3 weeks. After excluding chil-
dren (<18 years of age), the final sample was composed of
2121 adults. Socio-demographic information was collected
for each individual, including age class, socio-professional
category (SPC), level of education, income per consump-
tion unit (CU), physical activity level and body mass index
(BMI). Three age classes were provided by INCA3 [18, 45,
65] and ≥ 65. Following the International Standard Classi-
fication of Occupations [20], SPC was divided into “low”
(mainly office and manual workers), “medium” (mainly
craftspeople, company directors/owners and other inter-
mediate professions) and “high” (mainly executives and
self-employed professionals) and a fourth class, labelled as
“not working”, including retired, used to work, students and
housewives/househusbands. Level of education was divided
into 4 classes: “primary & middle school”, “high school”,
“1 to 3 years of post-secondary education” and “4 or more
years of post-secondary education”. Income per CU was
divided into 4 classes: “<900 €/month/CU”, “[900–1340[
€/month/CU”, “[1340–1850[ €/month/CU” and “> = 1850
€/month/CU”. Physical activity level was estimated through
an adapted version of the Recent Physical Activity Ques-
tionnaire [21] and considered into 3 classes: “low”, “mod-
erate” and “high”. BMI classes (“underweight”, “normal”,
“overweight” and “obese”) were derived following the WHO
definition [22]. For each mixed dish reported as consumed in
the dietary survey, an average recipe was estimated, based on
an existing recipe database [19], and on recipes sourced from
the most popular cooking website in France (i.e., marmiton.
org). Based on average recipes, the amount of each specific
FV was collected, and amounts of all FV within each mixed
dish were summed up to estimate the proportion of FV in
each mixed dish. The nutrient contents of all foods and bev-
erages consumed were extracted from the 2016 food com-
position database from the French Information Centre on
Food Quality [23] and matched to INCA3 dietary data for
individual nutrient intake estimations. Free sugar contents
of foods were estimated using a previously published pro-
cedure [24]. Foods consumed in INCA3 were categorised
into 44 food categories, which were assembled into 10 major
food groups for the present analysis (Supplemental Table 1).
Environmental impacts of foods were extracted from Agrib-
alyse V3.1, a life cycle assessment (LCA) database of 2520
food items published by the French Agency for Ecological
Transition [25]. Details of the methodology are available
elsewhere [26]. Briefly, all transportation (except from retail
to consumer) and waste (except for that generated at the
consumer's place of consumption) were taken into account.
The origin of the main raw materials was defined by cross-
ing data from technical institutes and experts' knowledge.
Agribalyse was matched to dietary data at the food item
level for individual environmental impact estimations. For
this purpose, automated matching based on the food label
was applied and verified manually. Additional information
regarding cooking method, physical characteristics (e.g.,
"reconstituted from powder" for coffee), etc., were taken
into account to further improve the matching. Consumed
foods that were not sufficiently described in Agribalyse were
matched to average values (e.g., a consumed "potato" was
matched to a weighted average item of different potatoes).
Remaining unmatched foods were manually matched to their
best alternative (e.g., consumed food "daikon" was matched
to the environmental impacts of "black radish").

Indicators of nutritional quality

The nutritional quality of individual diets was assessed
through 4 indicators: mean adequacy ratio (MAR), solid
energy density, mean excess ratio (MER) and Programme
National Nutrition Santé—guideline score 2 (PNNS-
GS2). The MAR was calculated as the mean of 23 nutri-
ent adequacy ratios, each corresponding to the percentage
of the daily recommended intake for one of the 23 nutri-
ents [27–29] (see Supplemental Table 2). Each nutrient
adequacy ratio was truncated at 100 so that a high intake
of one nutrient could not compensate for a low intake of
another. MAR ranged from 0 (no nutrient intake) to 100
(coverage of all 23 recommended intakes). Solid energy

density was calculated for each diet by dividing energy
intake by ingested weight for solid food only. Diets with
a low energy density are associated with high diet quality
[30]. The MER was calculated as the mean percentage of
excess sodium, saturated fatty acids (SFA) and free sugars
[18]. Upper limits were taken from ANSES [28, 29] and
WHO guidelines [33] for free sugars. The PNNS-GS2 was
used to estimate adherence of diets to the French Nutrition
and Health Programme recommendations, by allocating
points when the diet is in accordance with the recommen-
dation [34]. Higher PNNS-GS2 is associated with higher
adherence to 2017 dietary guidelines.

Environmental indicators

The single environmental footprint (EF) score [35], also
called the product environmental footprint (PEF) score, (in
mPt) was considered a general measure of the environmen-
tal impact of diet and was calculated for each individual. It
is a weighted mean of 16 environmental impacts and was
calculated following the environmental footprint (EF) 3.0
life cycle impact assessment method [36], as well as the
adaptations proposed for Agribalyse 3.1 for four impact
categories (i.e., climate change, ecotoxicity, human tox-
icity cancer and human toxicity non-cancer) [37]. Three
additional environmental indicators that are considered the
most robust and with the best level of consensus were also
included in our study: a) climate change (in kg CO₂ eq); b)
ozone depletion (in E-06 kg CFC 11 eq), which increases
exposure to harmful ultraviolet radiation; and c) fine par-
ticulate matter (E-06 disease incidence) that has an effect
on human health via air exposure. A fourth indicator with
a lower level of consensus was retained: blue water (fresh
surface and groundwater used for irrigation), called here
water use (in m³). Data from Agribalyse 3.1 are the result
of over 10 years of research and expertise, aiming to pro-
vide the most accurate possible representation of the envi-
ronmental impact of agricultural and food products; how-
ever, this work is constantly evolving and being improved.
The limitations of the environmental impact indicators are
those of the Agribalyse methodology and include a lack
of representation of all biodiversity-friendly pressures and
practices, a lack of description of transformation processes
and the use of co-products in the food industry, as well
as a spatialisation of certain impact categories, coupling
impact indicators with eco-system service indicators. This
means that when life cycle analysis is used to compare
the environmental impacts of different production systems
(organic versus conventional farming, intensive/extensive
livestock rearing, etc.) and processing, these limitations
must be explicitly highlighted.
## Statistical analysis

FV consumption was estimated for each individual (n=2121). To estimate the daily quantity of FV, all fruit (including dried fruits, but not nuts) and vegetables consumed, including those in mixed dishes, were counted. In accordance with French national guidelines, fruit juices (100% pure juice) were counted only up to one glass (125 g). Individuals were split into quintiles according to their daily FV consumption, in g/day (Q1 the lowest, Q5 the highest). Associations between socio-demographic characteristics and FV consumption quintiles were tested using Chi² tests, and energy intakes were compared between quintiles of FV consumption using analysis of variance (ANOVA). As energy intakes could be different from one quintile to another, each diet was proportionally adjusted to a theoretical average adult daily energy intake of 2000 kcal to control for inter-individual differences in energy intakes and compare quintiles of FV consumption independently of energy intake levels. The contributions of the 10 major food groups to 2000 kcal diets were estimated and compared between quintiles of FV consumption.

Means of environmental impacts (EF, climate change, ozone depletion, fine particulate matter and water use) and nutritional quality (MAR, solid energy density, MER, and PNNS-GS2) indicators, as well as nutrient intakes (expressed in percentage of dietary reference value—DRV), were statistically compared between quintiles of FV consumption. Then, trend tests across quintiles and 2-by-2 comparison tests between quintiles using Bonferroni correction (Supplemental Table 3) were conducted. For environmental indicators, total impacts were expressed as a percentage of the most impacting quintile. Contributions within each quintile were then expressed as a percentage of the total contribution. Statistical analyses were computed using the SURVEYREG (to compare quantitative indicators between quintiles) and SURVEYFREQ (for qualitative socio-demographic variables) procedures of SAS Statistical Software (version 9.4) to ensure national representativeness. I threshold for statistical significance was *p* < 0.05.

## Results

Mean FV consumption ranged from 119 g/d in Q1 (111.3–125.8) to 694 g/d in Q5 (672.6–714.6) (unadjusted amounts, Table 1). Age increased with increasing quintiles of FV intake (74.9% of 45 yo or more in Q5 against 41.4% in Q1), but no clear trend was observed for the gender ratio. Physical activity levels significantly increased across FV

quintiles, but no relation was observed with BMI status. All three socio-economic variables, namely SPC, income per consumption unit and educational level, were significantly and positively associated with the level of FV consumption. The relationship with income was very strong, with 40% of individuals in the lowest FV quintile belonging to the lowest socio-economic class (i.e., living in a household with <900 €/month/CU), and only 15% of individuals in the highest quintile of FV intakes belonging to this class.

As expected, energy intakes increased significantly from Q1 (1894 kcal/d) to Q5 (2277 kcal/d). As indicators of nutritional quality and environmental impact are correlated with energy intakes [18], the subsequent analyses were conducted on diets adjusted to 2000 kcal. However, absolute (i.e., unadjusted) daily quantities and environmental impacts in each quintile are available in Supplemental Table 4.

Figure 1 shows the mean energy provided by the different major food groups to diets adjusted to 2000 kcal in each quintile of FV intake. Increased quantities of FV from Q1 to Q5 were associated with increased energy contribution from FV. This increased energy contribution of FV was associated with increased energy contribution from "dairies" and "fats", and with decreased energy contributions from "sweetened products", "drinks", and "mixed dishes" as well as from "potatoes and pulses". In contrast, the mean energy contributions from "cereals" and from the "Meat, fish, eggs and alternatives" group were not significantly different across quintiles of FV consumption.

Figure 2 shows the indicators of nutritional quality for diets adjusted to 2000 kcal according to quintiles of FV intake. As FV consumption increased, MAR and PNNS-GS2 increased, while solid energy density decreased (*p* < 0.05). MER also decreased (*p* < 0.05), but analysis of the differences quintile by quintile (Supplemental Table 3) showed that none of them were significant.

Table 2 shows the four nutritional quality indicators, nutrient contents (expressed in % of DRV) and environmental impacts of diets adjusted to 2000 kcal in the five quintiles of FV intakes. Increased consumption of FV was characterised by increasing densities in fibre, EPA+DHA, potassium, vitamin A, vitamin E, vitamin B9 and vitamin C (significant 2-by-2 comparisons between all quintiles). Among nutrients to limit (SFA, sodium, free sugars), free sugar intakes were the only one that progressively decreased with increased FV consumption. However, 2-by-2 significances were observed only with Q5 as a reference against Q1, Q2 and Q3, but not Q4. There were no differences in proteins, linoleic acid, alpha-linolenic acid, vitamins B12 and D, iron, magnesium and zinc densities between quintiles. EF impacts of diets adjusted to 2000 kcal reached 0.710, 0.711, 0.690, 0.702 and
<table><caption>**Table 1** Daily FV consumption, daily energy intake and socio-demographics characteristics of individuals among the five quintiles of FV consumption</caption><thead><tr><th></th><th></th><th>Q1</th><th>Q2</th><th>Q3</th><th>Q4</th><th>Q5</th><th>p-value</th></tr></thead><tbody><tr><td rowspan="2">Amounts of FV (g/d) 95% CI</td><td></td><td>118.6</td><td>243.4</td><td>355.9</td><td>465.7</td><td>693.6</td><td rowspan="2">&lt;0.001</td></tr><tr><td></td><td>111.3–125.8</td><td>238.4–248.3</td><td>352.0–359.8</td><td>461.1–470.2</td><td>672.6–714.6</td></tr><tr><td rowspan="2">Energy intakes (kcal/d) 95% CI</td><td></td><td>1894</td><td>2065</td><td>2110</td><td>2167</td><td>2277</td><td rowspan="2">0.0014</td></tr><tr><td></td><td>1739.1–2048.25</td><td>1934.0–2195.5</td><td>2012.1–2207.6</td><td>2065.5–2267.6</td><td>2183.0–2370.2</td></tr><tr><td rowspan="2">Gender</td><td>Men</td><td>44.8</td><td>46.7</td><td>45.7</td><td>50.9</td><td>54.3</td><td rowspan="2">0.3289</td></tr><tr><td>Women</td><td>55.2</td><td>53.3</td><td>54.3</td><td>49.1</td><td>45.7</td></tr><tr><td rowspan="3">Age</td><td>18.0–44.0 year-old</td><td>58.6</td><td>57.1</td><td>50.2</td><td>38.6</td><td>25.2</td><td rowspan="3">&lt;0.001</td></tr><tr><td>45.0–64.0 year-old</td><td>32.7</td><td>28.8</td><td>33.6</td><td>40.1</td><td>47.4</td></tr><tr><td>65.0–79.0 year-old</td><td>8.7</td><td>14.1</td><td>16.2</td><td>21.3</td><td>27.5</td></tr><tr><td rowspan="4">SPC</td><td>Low</td><td>36.1</td><td>36.1</td><td>27.9</td><td>17.2</td><td>20.9</td><td rowspan="4">&lt;0.001</td></tr><tr><td>Medium</td><td>26.1</td><td>21.1</td><td>23.4</td><td>22.0</td><td>18.1</td></tr><tr><td>High</td><td>9.6</td><td>13.5</td><td>16.9</td><td>17.7</td><td>17.6</td></tr><tr><td>Not working</td><td>28.2</td><td>29.2</td><td>31.7</td><td>43.2</td><td>43.4</td></tr><tr><td rowspan="4">Income per consumption unit</td><td>&lt;900 €/month/CU</td><td>40.2</td><td>25.2</td><td>19.8</td><td>23.7</td><td>15.3</td><td rowspan="4">&lt;0.001</td></tr><tr><td>[900–1340] €/month/CU</td><td>23.9</td><td>20.8</td><td>22.6</td><td>23.6</td><td>23.8</td></tr><tr><td>[1340–1850] €/month/CU</td><td>21.5</td><td>23.7</td><td>25.2</td><td>19.6</td><td>27.0</td></tr><tr><td>&gt; = 1850 €/month/CU</td><td>14.4</td><td>30.3</td><td>32.4</td><td>33.1</td><td>34.0</td></tr><tr><td rowspan="4">Educational level</td><td>Primary + middle school</td><td>53.0</td><td>48.0</td><td>45.8</td><td>46.6</td><td>46.6</td><td rowspan="4">0.0075</td></tr><tr><td>High school</td><td>23.2</td><td>21.3</td><td>19.8</td><td>12.6</td><td>15.1</td></tr><tr><td>1 to 3 years of post-secondary education</td><td>13.2</td><td>16.9</td><td>14.0</td><td>22.0</td><td>18.7</td></tr><tr><td>4 or more years of post-secondary education</td><td>10.6</td><td>13.8</td><td>20.5</td><td>18.8</td><td>19.7</td></tr><tr><td rowspan="3">Physical activity level</td><td>Low</td><td>42.4</td><td>45.7</td><td>36.1</td><td>30.5</td><td>31.3</td><td rowspan="3">0.0258</td></tr><tr><td>Moderate</td><td>44.6</td><td>45.5</td><td>51.9</td><td>51.7</td><td>55.2</td></tr><tr><td>High</td><td>13.0</td><td>8.8</td><td>12.0</td><td>17.8</td><td>13.6</td></tr><tr><td rowspan="4">BMI</td><td>Underweight</td><td>3.3</td><td>5.0</td><td>2.7</td><td>2.4</td><td>1.4</td><td rowspan="4">0.6192</td></tr><tr><td>Normal</td><td>42.9</td><td>45.4</td><td>44.9</td><td>49.3</td><td>41.8</td></tr><tr><td>Overweight</td><td>32.9</td><td>32.8</td><td>35.1</td><td>34.9</td><td>39.5</td></tr><tr><td>Obesity</td><td>20.9</td><td>16.8</td><td>17.3</td><td>13.3</td><td>17.3</td></tr></tbody></table>

p-value from ANOVA for quantitative variables and Chi² test for qualitative ones

SPC socio-professional category, CU consumption unit, BMI body mass index

0.681 mPt from Q1 to Q5, respectively. The difference was not significant (p = 0.5302). The effect of quintiles on other environmental impact indicators was significant.

In Fig. 3, Q2 having the highest value of EF impact, has been selected as a reference (i.e., 100), and total EF impacts from other quintiles were expressed as a percentage of this reference. Within each quintile, contributions of food groups were expressed as a percentage of the quintile's total. The food group "Meat, fish, eggs and alternatives" was the major

contributor to the EF impact of diets (between 35 and 41%) in all quintiles.

Figure 4 shows that impacts on climate change, ozone depletion and fine particulate matter from diets adjusted to 2000 kcal decreased with increasing quintiles of FV consumption. Conversely, impacts on water use in diets adjusted to 2000 kcal increased with increasing quintiles of FV consumption, with, in Q5 a contribution to this impact from FV of 54%. Fresh fruit alone accounted for 2.72 m³/2000 kcal in Q5, corresponding to 30% of water use associated with the entire
<figure><img src="image_3.png" /><figcaption>**Fig. 1** Mean energy provided by the different food groups to diet adjusted to 2000 kcal according to quintiles of FV consumption</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>**Fig. 2** Mean (95% CI) nutritional quality of diets adjusted to 2000 kcal according to quintiles of FV consumption*</figcaption></figure>

diet adjusted to 2000 kcal (data not shown). The food group “Meat, fish, eggs and alternatives” was the major contributor to climate change (between 39 and 44%) and fine particulate

matter (between 44 and 49%), while “drinks” was the major contributor to ozone depletion (between 42 and 55%), mainly due to bottled water and cold non-alcoholic beverages (data not shown).
<table><caption>**Table 2** Mean nutritional characteristics and environmental impacts of diets adjusted to 2,000 kcal according to the quintiles of FV consumption</caption><thead><tr><th></th><th>Q1</th><th>Q2</th><th>Q3</th><th>Q4</th><th>Q5</th><th>p-value</th><th>p-trend</th></tr></thead><tbody><tr><td colspan="8"><strong>Nutritional quality indicators</strong></td></tr><tr><td>MAR, % adequacy</td><td>74.6</td><td>77.2</td><td>80.1</td><td>81.24</td><td>82.9</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>MER, % excess</td><td>27.8</td><td>28.7</td><td>28.0</td><td>24.85</td><td>24.7</td><td>0.010</td><td>0.016</td></tr><tr><td>Solid energy density, kcal/100 g</td><td>193.1</td><td>175.8</td><td>165.4</td><td>149.37</td><td>133.7</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>PNNS-GS2</td><td>-2.3</td><td>-2.2</td><td>-0.6</td><td>0.1</td><td>0.8</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td colspan="8"><strong>Nutrients (in % of DRV*)</strong></td></tr><tr><td colspan="8"><strong>Nutrients to favour</strong></td></tr><tr><td>Proteins</td><td>172.2</td><td>172.4</td><td>168.7</td><td>168.3</td><td>165.7</td><td>0.563</td><td>0.126</td></tr><tr><td>Fibres</td><td>51.9</td><td>57.2</td><td>62.4</td><td>70.0</td><td>78.4</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Linoleic acid</td><td>81.3</td><td>78.5</td><td>81.0</td><td>76.6</td><td>78.3</td><td>0.542</td><td>0.259</td></tr><tr><td>Alpha linolenic acid</td><td>41.4</td><td>43.2</td><td>45.6</td><td>45.4</td><td>47.9</td><td>0.094</td><td>0.008</td></tr><tr><td>EPA + DHA</td><td>44.1</td><td>59.2</td><td>60.6</td><td>60.8</td><td>68.5</td><td>0.001</td><td>0.001</td></tr><tr><td>Vitamin A</td><td>85.3</td><td>126.6</td><td>133.0</td><td>141.5</td><td>169.6</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Vitamin B1</td><td>139.3</td><td>151.0</td><td>152.8</td><td>151.0</td><td>157.8</td><td>0.004</td><td>0.013</td></tr><tr><td>Vitamin B2</td><td>103.0</td><td>105.4</td><td>112.9</td><td>109.1</td><td>112.5</td><td>0.033</td><td>0.008</td></tr><tr><td>Vitamin B3</td><td>169.0</td><td>160.8</td><td>151.0</td><td>154.7</td><td>151.8</td><td>0.027</td><td>0.002</td></tr><tr><td>Vitamin B6</td><td>96.1</td><td>96.9</td><td>101.1</td><td>106.0</td><td>110.4</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Vitamin B9</td><td>72.1</td><td>81.4</td><td>92.7</td><td>99.4</td><td>109.4</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Vitamin B12</td><td>133.5</td><td>131.1</td><td>136.8</td><td>129.3</td><td>136.0</td><td>0.970</td><td>0.922</td></tr><tr><td>Vitamin C</td><td>42.5</td><td>62.3</td><td>84.4</td><td>96.8</td><td>126.6</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Vitamin E</td><td>90.4</td><td>92.5</td><td>109.2</td><td>103.5</td><td>116.0</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Vitamin D</td><td>18.8</td><td>20.9</td><td>21.6</td><td>21.8</td><td>21.8</td><td>0.082</td><td>0.010</td></tr><tr><td>Calcium</td><td>87.3</td><td>92.7</td><td>100.9</td><td>97.5</td><td>98.6</td><td>0.001</td><td>&lt;0.001</td></tr><tr><td>Potassium</td><td>76.6</td><td>80.2</td><td>84.3</td><td>89.8</td><td>97.4</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Iron</td><td>72.1</td><td>72.6</td><td>73.1</td><td>74.3</td><td>76.4</td><td>0.383</td><td>0.096</td></tr><tr><td>Magnesium</td><td>98.3</td><td>97.7</td><td>99.4</td><td>101.5</td><td>104.2</td><td>0.172</td><td>0.024</td></tr><tr><td>Phosphorus</td><td>211.1</td><td>212.2</td><td>219.4</td><td>220.4</td><td>220.3</td><td>0.033</td><td>0.003</td></tr><tr><td>Zinc</td><td>92.4</td><td>93.5</td><td>89.0</td><td>88.6</td><td>85.8</td><td>0.187</td><td>0.052</td></tr><tr><td>Copper</td><td>90.3</td><td>93.7</td><td>94.2</td><td>100.6</td><td>108.4</td><td>0.001</td><td>&lt;0.001</td></tr><tr><td>Iodine</td><td>90.2</td><td>90.7</td><td>100.1</td><td>98.9</td><td>104.2</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>Selenium</td><td>176.1</td><td>169.6</td><td>175.9</td><td>182.9</td><td>190.8</td><td>0.012</td><td>0.019</td></tr><tr><td colspan="8"><strong>Nutrients to limit</strong></td></tr><tr><td>Saturated fatty acids</td><td>121.4</td><td>122.4</td><td>121.4</td><td>118.5</td><td>114.1</td><td>0.012</td><td>0.012</td></tr><tr><td>Sodium</td><td>126.2</td><td>133.2</td><td>134.9</td><td>133.6</td><td>140.5</td><td>0.004</td><td>&lt;0.001</td></tr><tr><td>Free sugars</td><td>109.8</td><td>105.5</td><td>100.9</td><td>95.8</td><td>85.2</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td colspan="8"><strong>Environmental impact indicators</strong></td></tr><tr><td>EF Score, mPt</td><td>0.7</td><td>0.7</td><td>0.7</td><td>0.7</td><td>0.7</td><td>0.530</td><td>0.199</td></tr><tr><td>Climate change, kg CO2 eq</td><td>5.6</td><td>5.6</td><td>5.3</td><td>5.3</td><td>5.0</td><td>0.011</td><td>0.003</td></tr><tr><td>Ozone depletion, E-06 kg CFC 11 eq</td><td>0.7</td><td>0.7</td><td>0.7</td><td>0.6</td><td>0.6</td><td>0.008</td><td>&lt;0.001</td></tr><tr><td>Fine particulate matter, E-06 disease incidence</td><td>0.6</td><td>0.6</td><td>0.5</td><td>0.5</td><td>0.5</td><td>0.014</td><td>0.001</td></tr><tr><td>Water use, m³</td><td>6.0</td><td>6.6</td><td>7.8</td><td>8.9</td><td>9.1</td><td>&lt;0.001</td><td>&lt;0.001</td></tr></tbody></table>

Discussion

To our knowledge, this is the first study to simultaneously assess the nutritional quality and environmental impacts of self-selected diets in relation to levels of FV consumption. Diets were adjusted to 2000 kcal (theoretical average

adult energy intake), which allows for standardisation and to have a homogeneous functional unit [39].

Our results revealed that the lowest consumers of FV (Q1) have an average intake of 119 g/d, which corresponds to less than 2 daily servings of FV. These low consumers are more likely to be young and to have a lower socio-economic level

<footnote>*Dietary references values [27–29, 38]</footnote>
<figure><img src="image_5.png" /><figcaption>**Fig. 3** Mean contribution of food groups to single EF score of 2000 kcal adjusted diets according to quintiles of FV consumption</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 4** Mean contribution of food groups to impacts on climate change, ozone depletion, fine particulate matter and water use of diets adjusted to 2000 kcal according to quintiles of FV consumption</figcaption></figure>
than the highest-level consumers. The most recent National Diet and Nutrition Survey in the United Kingdom (NDNS, 2020) showed comparable results, with 67% of adults surveyed reporting consumption of less than the quantities recommended in guidelines [40]. These observations are consistent with the situation observed in 2019 in Europe, with 88% of the population aged 15 years and over not meeting the recommendation [41].

We observed that nutritional quality increased systematically with increasing intakes of FV. Hence, high FV intakes were characterised by lower energy density and higher densities of vitamins C (126.6% in Q5 vs 42.5% in Q1), B9 (109.4% in Q5 vs 72.0% in Q1), potassium (97.4% in Q5 vs 76.6% in Q1) and fibre (78.5% of DRVs in Q5 vs 52.0% of DRVs in Q1), contributing to a higher MAR, and lower amounts of free sugars compared to groups consuming less FV. This finding is supported by data from the literature showing that FV contains high amounts of a wide range of beneficial nutrients including fibre, vitamins (A, B9 and C), and minerals such as potassium [42, 43]. In addition, higher consumption of FV was associated, in our study, with higher densities of nutrients that are not found in FV, such as nutrients that are specific to fish products (iodine and EPA + DHA) and to dairies (calcium), without reducing densities of nutrients specific to meat products (iron, vitamin B12), showing that an increased consumption of FV is associated with a more balanced diet.

Our results also showed that as FV consumption increased, MER decreased, showing the importance of increasing FV intake. However, this raises the question of substitution when increasing intake. According to our findings, the contribution of cereals and meat/fish/eggs remained similar in the different quintiles, which could allow us to suggest that the FV pattern is independent of the meat/egg/fish and cereal patterns.

Although our results showed an association between higher FV consumption and higher fibre intake, ranging from 51.95% of DRVs for Q1 to 78.45% of DRVs for Q5, the recommended intakes were not met in adults as mean intakes remained below DRVs in all quintiles. A review conducted in 2017 reported comparable results for adults in Europe, showing that fibre intake was below the recommendations. Grain products, especially bread, have been identified as the primary food source of fibre, while vegetables, potatoes and fruits are secondary fibre contributors, providing 12.0% to 21.0%, 6.0% to 19.0% and 8.0% to 23.0% of fibres, respectively [43].

Regarding the environmental impact of the studied diet, there were no significant differences in single EF scores between quintiles of FV consumption, showing that the level of FV consumption is independent of environmental impact when estimated with an aggregate indicator. This finding could be explained by the low contribution of FV to the

single EF score, compared to other food groups. FV intake (excluding that from mixed dishes) contributed between 3% (Q1) to 14.6% (Q5) of the total single EF score, whereas the major contributors were meat products with 35.4% (Q3) to 40.7% (Q1) of the total. This finding is confirmed by EAT-Lancet [14] and World Wildlife Fund [44] studies, according to which meat and dairy food groups are the highest contributors to single EF scores, but also to other environmental impacts such as climate change, ozone depletion or fine particulate matter.

When the environmental indicators were analysed separately, higher FV consumption was associated with higher impact on water use compared to other food groups, but had less impact on climate change, fine particulate matter and ozone depletion, even for the highest consumers of FV (Q5). The low contribution of FV to the total impact (single EF score) compared to other food groups, and the characteristics of the French market (half of FV are produced in France, with a low amount of inputs and fertilisation in production) [45, 46] could explain their low impact on climate change, fine particulate matter and ozone depletion. Our results suggest that increasing the intake of FV at constant energy intake will have little impact on climate change, fine particulate matter and ozone depletion, but may increase water use impact. The contribution of FV should, therefore, be considered for reducing water use, although meat consumption remains the priority to reduce the environmental impacts of diet [16, 47].

A recent study assessed the environmental impact of diets in Sweden for six indicators (GHGE, cropland use, nitrogen (N) and phosphorus (P) application, consumptive water use and extinction rate). In this study, animal-based foods contributed most to the total environmental impact of diet (23.0–83.0%), followed by plant-based foods (8.0–40.0%), and discretionary foods (9.0–37.0%) for all environmental indicators. While animal-based foods contributed mainly to GHGE, cropland use, and N and P application, plant-based and discretionary foods had more significant impacts on consumptive water use and extinction rates (together responsible for 70–77% of the total dietary impact on these indicators) [48]. Comparable results were also observed in a recent population-based study conducted in Israel, where meat was the major contributor to land use, dairy to GHGE, and fruits followed by vegetables to water use; however, the authors highlighted that most FV in this country are grown using treated wastewater, which could reduce pressure on the environment [49].

## Limitations, strengths, and challenges

The main strength of the present study was the matching of Agribalyse, the official national database on environmental impacts, with the INCA3 database, representative
of all individuals residing in metropolitan France (exclud-
ing Corsica) and living in an ordinary household. In addi-
tion, INCA3 respects the methodology recommended by
the European Food Safety Authority (EFSA) [50]. How-
ever, the INCA3 study, like all studies assessing dietary
intakes, is based primarily on self-reporting by participants,
which makes the reliability of the data partly dependent on
the cognitive abilities of the participants, and on possible
biases in reporting. Another limitation is the uncertainty in
extrapolating long-term consumption from short-term cross-
sectional, dietary reports [51]. Also, food consumption data
from INCA3 were last updated in 2014–2015, whereas the
food consumption habits of the French population may have
changed since then, specifically due to the COVID-19 pan-
demic and inflation [52–58].

Our study also has several limitations and challenges that
need to be addressed. It was impossible to dissociate the
impacts of the ingredients of mixed dishes. Recipes indicat-
ing the amounts of ingredients for each meal enabled us to
quantify the total amounts of FV for each individual. How-
ever, nutritional composition or environmental impacts were
only available for the final dish and not for each ingredient,
which made it impossible to assess the nutritional intake or
environmental impacts of total FV consumption (i.e., includ-
ing FV from mixed dishes).

Assessing the environmental performance of diets
requires a multicriteria environmental perspective, going
beyond climate change impacts alone [59]. In addition, opti-
mal diets remain complex to model due to the many types
of food products consumed, and the diversity of agricultural
production systems, supply chains and local environmental
settings. The majority of LCA databases are not exhaustive
and lack data regarding the diversity of productions [59,
60]. Environmental data on FV production and imports from
Agribalyse are generic estimates as not all crops are assessed
[61, 62], which could impair the robustness of our results.
However, LCA data were used for comparative purposes
here and for the 2-by-2 comparisons, thus reducing the risk
of over-interpretating absolute values that may suffer of
uncertainties.

In addition, our results showed that not all environmental
indicators behave similarly, confirming that it is essential to
adopt a multicriteria assessment approach to better under-
stand the environmental impact of diet.

Regarding the water use indicator, it would be necessary
to approach this indicator more precisely, particularly by
better taking into account spatial and temporal variability in
LCA inventories and impact calculations [63]. Nevertheless,
the results obtained on the overall dietary contribution to
environmental impacts illustrate the importance of focusing
on water use when adopting a more plant-based diet. This
indicator has rarely been addressed, with scientific stud-
ies mainly focusing on GHGE and land use [16]. Linking

the real contribution of adopting a more plant-based diet
to water use is a short-term challenge, as global warming
will make access to water resources more difficult and may
potentially decrease FV consumption and thus disrupt the
human health benefit/planetary health risk balance of FV.
Production modes with irrigation techniques and territorial
management should also be considered in the evaluation of
water use, in order to identify pathways to reduce use of
this resource. In fact, the efficiency of crop water use could
be increased through irrigation strategies based on physical
models of evaporation from partially wetted soil surfaces,
irrigation water redistribution in the soil, and root water
uptake. Micro-sprinkling seems to be the most suitable irri-
gation technique for efficient use of water, as it combines the
advantages of drip irrigation with the capacities of sprinkler
irrigation [64]. Other farm management practices will also
play a key role in efficient water use, such as understand-
ing soil types and structures, the need for water depending
on the season and the development cycle of crops, keep-
ing the soil covered with living or organic mulch to retain
moisture, and selecting drought-tolerant crop species and
varieties [65].

Conclusion

For the vast majority of adults in France, FV consumption
remains insufficient to achieve optimal health. This study
showed that, compared to individuals with low intakes of
fruit and vegetables, those with higher intakes have diets of
better nutritional quality and lower environmental impact
for all the indicators included, except for water use. Given
the benefits of FV for human health and the environment,
increasing their proportion in diets is essential and should
be a national priority in the framework of balanced diets and
nutrition. Regarding their negative impact on water use as
observed in our study, this could be mitigated by working
on the agricultural upstream rather than by reducing their
consumption, such as working on the choice of crop varie-
ties and production methods that better preserve resources
to benefit from the nutritional advantages of FV without
increasing the negative impacts on water use. The desir-
ability of consuming products with the most water-efficient
production systems was illustrated in our study (e.g., micro-
irrigation for tomatoes, etc., or from agricultural areas under
little pressure on water resources). An information and pro-
motion campaign for these production methods could be
considered to facilitate consumer choice. Increasing con-
sumption of these products could thus make a major contri-
bution to a sustainable food system. Additional research is
needed to better take into account production practices that
enable reduced field emissions and water use impacts.
**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s00394-023-03252-3.

**Acknowledgements** We would like to thank Eleonore Loiseau from ITAP, University of Montpellier, INRAE, Institut Agro, Montpellier, France; ELSA, Research Group for Environmental Lifecycle and Sustainability Assessment, Montpellier, France for proofreading and helpful feedback.

**Data availability** Data will be made available upon reasonable request.

## Declarations

**Conflict of interest** This work was supported by APIFEL, a French non-profit organisation promoting research and information on fresh fruit and vegetables. On behalf of all authors, the corresponding author states that there are no conflicts of interest.

**Ethical approval** The INCA3 study was performed in accordance with the guidelines laid down in the Declaration of Helsinki and all procedures involving human participants were approved by the Comité Consultatif sur le Traitement de l'Information en matière de Recherche dans le domaine de la Santé (CCTIRS; Advisory Committee on Information Processing in Health Research).

**Consent to participate and for publication** Verbal informed consent was obtained from all participants by the French Agency for Food, Environmental and Occupational Health & Safety (ANSES). Verbal consent was witnessed and formally recorded.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

## References

1. Burlingame BA, Dernini S, Food and Agriculture Organization of the United Nations, Biodiversity International (2012) Sustainable diets and biodiversity: directions and solutions for policy, research and action. FAO, Rome

2. Masset G, Vieux F, Verger EO et al (2014) Reducing energy intake and energy density for a sustainable diet: a study based on self-selected diets in French adults. Am J Clin Nutr 99:1460-1469. https://doi.org/10.3945/ajcn.113.077958

3. Notarnicola B, Tassielli G, Renzulli PA et al (2017) Environmental impacts of food consumption in Europe. J Clean Prod 140:753-765. https://doi.org/10.1016/j.jclepro.2016.06.080

4. Rosi A, Mena P, Pellegrini N et al (2017) Environmental impact of omnivorous, ovo-lacto-vegetarian, and vegan diet. Sci Rep 7:6105. https://doi.org/10.1038/s41598-017-06466-8

5. Esteve-Llorens X, Darriba C, Moreira MT et al (2019) Towards an environmentally sustainable and healthy Atlantic dietary pattern: life cycle carbon footprint and nutritional quality. Sci Total

Environ 646:704-715. https://doi.org/10.1016/j.scitotenv.2018.07.264

6. Aune D, Giovannucci E, Boffetta P et al (2017) Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality—a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol 46:1029-1056. https://doi.org/10.1093/ije/dyw319

7. WCRF (2018) Diet, nutrition, physical activity and cancer: a global perspective : a summary of the Third expert report. World Cancer Research Fund International, London

8. Afshin A, Sur PJ, Fay KA et al (2019) Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet 393:1958-1972. https://doi.org/10.1016/S0140-6736(19)30041-8

9. WHO (2020) Healthy diet. In: World Health Organization. https://www.who.int/news-room/fact-sheets/detail/healthy-diet

10. EUROSTAT (2019) Daily consumption of fruit and vegetables by sex, age and educational attainment level. In: EUROSTAT. https://ec.europa.eu/eurostat/datab browser/bookmark/572ad9a7-8390-4e26-bd04-92a7a3a76fad?lang=en&page= time:2019

11. MangerBouger Augmenter les fruits et légumes. In: Manger Bouger. https://www.mangerbouger.fr/l-essentiel/les-recommandations-sur-l-alimentation-l-activite-physique-et-la-sedentarite/augmenter/augmenter-les-fruits-et-legumes

12. Gomes F, Reynolds A (2021) Effects of fruits and vegetables intakes on direct and indirect health outcomes. FAO and PAHO

13. Gibbs J, Cappuccio FP (2022) Plant-based dietary patterns for human and planetary health. Nutrients 14:1614. https://doi.org/10.3390/nu14081614

14. Willett W, Rockström J, Loken B et al (2019) Food in the anthropocene: the EAT–lancet commission on healthy diets from sustainable food systems. The Lancet 393:447–492. https://doi.org/10.1016/S0140-6736(18)31788-4

15. Fresán U, Martínez-Gonzalez M-A, Sabaté J, Bes-Rastrollo M (2018) The Mediterranean diet, an environmentally friendly option: evidence from the Seguimiento Universidad de Navarra (SUN) cohort. Public Health Nutr 21:1573-1582. https://doi.org/10.1017/S1368980017003986

16. Grosso G, Fresán U, Bes-Rastrollo M et al (2020) Environmental impact of dietary choices: role of the mediterranean and other dietary patterns in an italian cohort. IJERPH 17:1468. https://doi.org/10.3390/ijerph17051468

17. Cambeses-Franco C, González-García S, Feijoo G, Moreira MT (2021) Encompassing health and nutrition with the adherence to the environmentally sustainable New Nordic Diet in Southern Europe. J Clean Prod 327:129470. https://doi.org/10.1016/j.jclepro.2021.129470

18. Vieux F, Soler L-G, Touazi D, Darmon N (2013) High nutritional quality is not associated with low greenhouse gas emissions in self-selected diets of French adults. Am J Clin Nutr 97:569-583. https://doi.org/10.3945/ajcn.112.035105

19. French Agency for Food Environmental and Occupational Health & Safety (ANSES) (2017) Individual and national study on food consumption 3 (INCA3) [Étude individuelle nationale des consommations alimentaires 3 (INCA 3)]. Maisons-Alfort, France

20. ILO (2012) International standard classification of occupations 2008 (ISCO-08): structure, group definitions and correspondence tables

21. Golubic R, May AM, Benjaminsen Borch K et al (2014) Validity of electronically administered recent physical activity questionnaire (RPAQ) in ten European countries. PLoS ONE 9:e92829. https://doi.org/10.1371/journal.pone.0092829

22. WHO Consultation on Obesity (2003) Obésité: prévention et prise en charge de l'épidémie mondiale ; rapport d'une consultation de l'OMS ; [Consultation OMS sur l'Obésité, Genève, 3 - 5 juin 1997], Genève: Organisation Mondiale de la Santé
23. ANSES (2017) Ciqual : Table de composition nutritionnelle des aliments

24. Louie JCY, Mostaghian H, Boylan S et al (2015) A systematic methodology to estimate added sugar content of foods. Eur J Clin Nutr 69:154–161. https://doi.org/10.1038/ejcn.2014.256

25. French Agency for Ecological Transition (ADEME) (2020) Agribalyse V3

26. Asselin-Balençon A, Broekema R, Telon H, et al (2020) Agribalyse 3.1. The French agricultural and food lci database. Methodology for food products.

27. ANSES (2016) AVIS et RAPPORTS de l'Anses relatifs à l'Actualisation des repères du PNNS : élaboration des références nutritionnelles. In: Anses—Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail. https://www.anses.fr/fr/content/avis-et-rapports-de-lanses-relatifs-%C3%A0-lactualisation-des-rep%C3%A8res-du-pnns-%C3%A9laboration-des. Accessed 16 Mar 2023

28. ANSES (2021) Les références nutritionnelles en vitamines et minéraux. In: Anses—Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail. https://www.anses.fr/fr/content/les-r%C3%A9f%C3%A9rences-nutritionnelles-en-vitamines-et-min%C3%A9raux. Accessed 16 Mar 2023

29. ANSES (2011) Actualisation des Apports Nutritionnels Conseillés pour les acides gras—Version intégrant les modifications apportées par l'erratum du 28 juillet 2011. In: Anses—Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail. https://www.anses.fr/fr/content/actualisation-des-apports-nutritionnels-conseill%C3%A9s-pourles-acides-gras-version-int%C3%A9grant-0. Accessed 16 Mar 2023

30. Ledikwe JH, Blanck HM, Khan LK et al (2006) Low-energy-density diets are associated with high diet quality in adults in the United States. J Am Diet Assoc 106:1172–1180. https://doi.org/10.1016/j.jada.2006.05.013

31. Anses (2021) Les lipides. https://www.anses.fr/fr/content/les-lipides#:~:text=Recommandations en lipides totaux&text=La part recommandée des lipides, compte la prévention des pathologies. Accessed 16 May 2022

32. ANSES-Rapport d'expertise collective (2016) Actualisation des repères du PNNS : élaboration des références nutritionnelles

33. World Health Organization (2015) WHO Guideline: Sugars intake for adults and children. World Health Organization, Geneva

34. Chaltiel D, Adjibade M, Deschamps V, et al (2019) Programme National Nutrition Santé—guidelines score 2 (PNNS-GS2): development and validation of a diet quality score reflecting the 2017 French dietary guidelines. British Journal of Nutrition 1–12. https://doi.org/10.1017/S00071145190001181

35. Sala S, Cerutti AK, Pant R (2018) Development of a weighting approach for the environmental footprint. Publications Office of the European Union, Luxembourg

36. European Commission. Joint Research Centre. (2018) Supporting information to the characterisation factors of recommended EF Life Cycle Impact Assessment methods: version 2, from ILCD to EF 3.0. Publications Office, LU

37. GIS REVALIM (2022) Note méthodologique : méthode EF 3.1 interim for AGRIBALYSE

38. World Health Organization (2015) Guideline: sugars intake for adults and children. World Health Organization, Geneva

39. Darmon N, Vieux F, Soler L-G, Touazi D (2013) Impact carbone et qualité nutritionnelle de l'alimentation en France. Notes et études socio-économiques 185–197. https://hal.inrae.fr/hal-02809922

40. GOV.UK (2020) NDNS: results from years 9 to 11 (combined)—statistical summary. In: GOV.UK. https://www.gov.uk/government/statistics/ndns-resul

ts-from-years-9-to-11-2016-to-2017-and-2018-to-2019/ndns-resul ts-from-years-9-to-11-combined-statistical-summary. Accessed 6 Apr 2023

41. EUROSTAT (2022) How much fruit and vegetables do you eat daily? In: Eurostat. https://ec.europa.eu/eurostat/web/products-eurostat-news/-/ddn-20220104-1. Accessed 6 Apr 2023

42. Slavin JL, Lloyd B (2012) Health benefits of fruits and vegetables. Adv Nutr 3:506–516. https://doi.org/10.3945/an.112.002154

43. Stephen AM, Champ MM-J, Cloran SJ et al (2017) Dietary fibre in Europe: current state of knowledge on definitions, sources, recommendations, intakes and relationships to health. Nutr Res Rev 30:149–190. https://doi.org/10.1017/S095442241700004X

44. Uthayakumar T (2017) Vers une alimentation bas carbone, saine et abordable

45. FranceAgriMer (2023) Fruits frais- Fiche filière. In: FranceAgriMer. https://www.franceagrimer.fr/fam/content/download/70365/document/FICHE_FILIERE_FRUITS_2023.pdf

46. FranceAgriMer (2023) Légumes frais- Fiche filière. In: FranceAgriMer. https://www.franceagrimer.fr/fam/content/download/70367/document/FICHE_FILIERE_LEGUMES_2023.pdf

47. Jalava M, Kummu M, Porkka M et al (2014) Diet change—a solution to reduce water use? Environ Res Lett 9:074016. https://doi.org/10.1088/1748-9326/9/7/074016

48. Hallström E, Davis J, Håkansson N et al (2022) Dietary environmental impacts relative to planetary boundaries for six environmental indicators—a population-based study. J Clean Prod 373:133949. https://doi.org/10.1016/j.jclepro.2022.133949

49. Tepper S, Kissinger M, Avital K, Shahar DR (2022) The environmental footprint associated with the Mediterranean diet, EATlancet diet, and the sustainable healthy diet index: a population-based study. Front Nutr 9:870883. https://doi.org/10.3389/fnut.2022.870883

50. European Food Safety Authority (2014) Guidance on the EU Menu methodology. EFS2 12:. https://doi.org/10.2903/j.efsa.2014.3944

51. Anses (2017) Étude individuelle nationale des consommations alimentaires 3 (INCA 3) (2014–2015). Rapport d'expertise collective.

52. Clemente-Suárez VJ, Ramos-Campo DJ, Mielgo-Ayuso J et al (2021) Nutrition in the actual COVID-19 pandemic. A narrative. Rev Nutr 13:1924. https://doi.org/10.3390/nu13061924

53. Di Renzo L, Gualtieri P, Pivari F et al (2020) Eating habits and lifestyle changes during COVID-19 lockdown: an Italian survey. J Transl Med 18:229. https://doi.org/10.1186/s12967-020-02399-5

54. González-Monroy C, Gómez-Gómez I, Olarte-Sánchez CM, Motrico E (2021) Eating behaviour changes during the COVID-19 pandemic: a systematic review of longitudinal studies. Int J Environ Res Public Health 18:11130. https://doi.org/10.3390/ijerp h182111130

55. Mekanna AN, Panchal SK, Li L (2022) Beyond lockdowns: a systematic review of the impacts of COVID-19 lockdowns on dietary pattern, physical activity, body weight, and food security. Nutr Rev nuac088. https://doi.org/10.1093/nutrit/nuac088

56. Maugeri A, Barchitta M, Perticone V, Agodi A (2023) How COVID-19 pandemic has influenced public interest in foods: a google trends analysis of Italian Data. IJERPH 20:1976. https://doi.org/10.3390/ijerph20031976

57. Rubio-Tomás T, Skouroliakou M, Ntountaniotis D (2022) Lockdown due to COVID-19 and its consequences on diet, physical activity, lifestyle, and other aspects of daily life worldwide: a narrative review. IJERPH 19:6832. https://doi.org/10.3390/ijerp h19116832

58. Sarda B, Delamaire C, Serry A-J, Ducrot P (2022) Changes in home cooking and culinary practices among the French population during the COVID-19 lockdown. Appetite 168:105743. https://doi.org/10.1016/j.appet.2021.105743
59. Hélias A, van der Werf HMG, Soler L-G et al (2022) Implementing environmental labelling of food products in France. *Int J Life Cycle Assess* 27:926–931. https://doi.org/10.1007/s11367-022-02071-8

60. Ridoutt BG, Hendrie GA, Noakes M (2017) Dietary strategies to reduce environmental impact: a critical review of the evidence base. *Adv Nutr* 8:933–946. https://doi.org/10.3945/an.117.016691

61. Hallström E, Carlsson-Kanyama A, Börjesson P (2015) Environmental impact of dietary change: a systematic review. *J Clean Prod* 91:1–11. https://doi.org/10.1016/j.jclepro.2014.12.008

62. Basset-Mens C, Vannière H, Grasselly D et al (2016) Environmental impacts of imported and locally grown fruits for the French market: a cradle-to-farm-gate LCA study. *Fruits* 71:93–104. https://doi.org/10.1051/fruits/2015050

63. Boulay A-M, Bare J, Benini L et al (2018) The WULCA consensus characterization model for water scarcity footprints: assessing impacts of water consumption based on available water remaining (AWARE). *Int J Life Cycle Assess* 23:368–378. https://doi.org/10.1007/s11367-017-1333-8

64. Koumanov K (2002) Towards improving of water management in fruit-tree plantations under micro-irrigation

65. FAO, CIRAD (2021) Fruit and vegetables. FAO, CIRAD