Effect of a nutritional intervention based on an energy-reduced Mediterranean diet on environmental impact

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Science of the Total Environment 928 (2024) 172610
Available online 19 April 2024
0048-9697/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Effect of a nutritional intervention based on an energy-reduced
Mediterranean diet on environmental impact
Laura ´
Alvarez-´
Alvarez
a
, María Rubín-García
a
, Facundo Vitelli-Storelli
a
,
*
, Silvia García
b
,
c
,
Cristina Bouzas
b
,
c
, Miguel ´
Angel Martínez-Gonz´
alez
b
,
d
,
e
, Dolores Corella
b
,
f
, Jordi Salas-
Salvad´
o
b
,
g
,
h
, Mireia Malcampo
b
,
i
, J. Alfredo Martínez
b
,
j
,
k
, ´
Angel M. Alonso-G´
omez
b
,
l
,
Julia W¨
arnberg
b
,
m
, Jesús Vioque
n
,
o
, Dora Romaguera
b
,
p
, Jos´
e L´
opez-Miranda
b
,
q
,
Ramon Estruch
b
,
r
, Francisco J. Tinahones
b
,
s
, Jos´
e Lapetra
b
,
t
, Lluís Serra-Majem
b
,
u
,
Aurora Bueno-Cavanillas
n
,
v
,
w
, Camino García Fern´
andez
x
, Xavier Pint´
o
b
,
y
, Miguel Delgado-
Rodríguez
k
,
z
, Pilar Matía-Martín
aa
, Josep Vidal
ab
,
ac
, Clotilde V´
azquez
b
,
ad
, Lidia Daimiel
b
,
ae
,
af
,
Emilio Ros
b
,
ag
, Ana García-Arellano
b
,
d
, María ´
Angeles Martínez
b
,
g
,
h
, Jos´
e V. Sorlí
b
,
f
, María
Dolores Zome˜
no
b
,
i
,
ah
, Antonio García-Rios
b
,
q
, Sandra Gonz´
alez-Palacios
n
,
o
,
Margalida Monserrat-Mesquida
b
,
c
, Itziar Abete
b
,
j
, Antoni Colom Fern´
andez
m
,
p
,
ai
,
Rosa Casas
b
,
r
, Naomi Cano Ib´
a˜
nez
n
,
v
,
w
, Lucía Ugarriza
b
,
c
, M. Rosa Bernal-L´
opez
b
,
aj
, Maira Bes-
Rastrollo
b
,
d
, Indira Paz-Graniel
b
,
g
,
h
, Eva M. Asensio
b
,
f
, Montse Fit´
o
b
,
i
, Antonio P. Arenas
Larriva
b
,
q
, Alejandro Oncina-C´
anovas
n
,
o
, Zenaida V´
azquez
b
,
d
, María Fern´
andez de la
Puente
b
,
g
,
h
, Alejandra P´
erez-Vega
b
,
i
, Josep A. Tur
b
,
c
, Vicente Martín-S´
anchez
a
,
n
a
Group of Investigation in Interactions Gene-Environment and Health (GIIGAS), Institute of Biomedicine (IBIOMED), University of Le´
on, Le´
on, Spain
b
Centro de Investigaci´
on Biom´
edica en Red Fisiopatología de la Obesidad y la Nutrici´
on (CIBEROBN), Institute of Health Carlos III, Madrid, Spain
c
Research Group on Community Nutrition & Oxidative Stress, University of Balearic Islands-IUNICS, Guillem Colom Bldg, Campus, E-07122, Palma de Mallorca, Spain
d
University of Navarra, Department of Preventive Medicine and Public Health, IDISNA, Pamplona, Spain
e
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
f
Department of Preventive Medicine, University of Valencia, Valencia, Spain
g
Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaci`
o, Nutrici´
o, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
h
Institut d’Investigaci´
o Sanit`
aria Pere Virgili (IISPV), Hospital Universitari San Joan de Reus, Reus, Spain
i
Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones M´
edicas Municipal d’Investigaci´
o M´
edica (IMIM), Barcelona, Spain
j
Department of Nutrition, Food Sciences, and Physiology, Center for Nutrition Research, University of Navarra, Pamplona, Spain
k
Precision Nutrition and Cardiometabolic Health Program, IMDEA Food, CEI UAM +CSIC, Madrid, Spain
l
Bioaraba Health Research Institute, Cardiovascular, Respiratory and Metabolic Area, Osakidetza Basque Health Service, Araba University Hospital, University of the
Basque Country UPV/EHU, Vitoria-Gasteiz, Spain
m
Department of Nursing, University of M´
alaga, Institute of Biomedical Research in Malaga (IBIMA), M´
alaga, Spain
n
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
o
Instituto de Investigaci´
on Sanitaria y Biom´
edica de Alicante, Universidad Miguel Hern´
andez (ISABIAL-UMH), Alicante, Spain
p
Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
q
Department of Internal Medicine, Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Reina Soa University Hospital, University of Cordoba, Cordoba,
Spain
r
Department of Internal Medicine, Institut d’Investigacions Biom`
ediques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
s
Virgen de la Victoria Hospital, Department of Endocrinology, Instituto de Investigaci´
on Biom´
edica de M´
alaga (IBIMA), University of M´
alaga, M´
alaga, Spain
t
Department of Family Medicine, Research Unit, Distrito Sanitario Atenci´
on Primaria Sevilla, Sevilla, Spain
u
Research Institute of Biomedical and Health Sciences (IUIBS), University of Las Palmas de Gran Canaria & Centro Hospitalario Universitario Insular Materno Infantil
(CHUIMI), Canarian Health Service, Las Palmas de Gran Canaria, Spain
v
Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
w
Instituto de Investigaci´
on Biosanitaria, IBS-Granada, Spain
Abbreviations: CG, Control group; CO2-eq, Carbon Dioxide equivalents; DS, Diet Score; FFQ, Food frequency questionnaire; GHG, Greenhouse gas; IG, Intervention
group; kJ, Kilojoules; MedDiet, Mediterranean Diet; PO4-eq, Phosphate equivalents; SO2-eq, Sulfur Dioxide equivalents.
* Corresponding author at: Department of Biomedical Sciences, Area of Preventive Medicine and Public Health, Faculty of Health Sciences, University of Leon,
Vegazana Campus, 24071 Le´
on, Spain.
E-mail address: fvits@unileon.es (F. Vitelli-Storelli).
Contents lists available at ScienceDirect
Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv
https://doi.org/10.1016/j.scitotenv.2024.172610
Received 30 October 2023; Received in revised form 15 April 2024; Accepted 17 April 2024

Science of the Total Environment 928 (2024) 172610
2
x
Department of Food Hygiene and Technology, Veterinary Faculty, University of Le´
on, Le´
on, Spain
y
Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge-IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
z
Division of Preventive Medicine, Faculty of Medicine, University of Ja´
en, Ja´
en, Spain
aa
Department of Endocrinology and Nutrition, Instituto de Investigaci´
on Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain
ab
CIBER Diabetes y Enfermedades Metab´
olicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
ac
Department of Endocrinology, Institut d` Investigacions Biom´
ediques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
ad
Department of Endocrinology and Nutrition, Hospital Fundaci´
on Jimenez Díaz, Instituto de Investigaciones Biom´
edicas IISFJD, University Autonoma, Madrid, Spain
ae
Nutritional Control of the Epigenome Group, Precision Nutrition and Obesity Program, IMDEA Food, CEI UAM +CSIC, Madrid, Spain
af
Departamento de Ciencias Farmac´
euticas y de la Salud, Faculty de Farmacia, Universidad San Pablo-CEU, CEU Universities, Boadilla del Monte, Spain
ag
Lipid Clinic, Department of Endocrinology and Nutrition, Institut d’Investigacions Biom`
ediques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
ah
School of Health Sciences, Blanquerna-Ramon Llull University, 08022 Barcelona, Spain
ai
Interdisciplinary Observatory of Mobility, University of the Balearic Islands, 07122 Palma, Spain
aj
Internal Medicine Department, Regional University Hospital of M´
alaga, Instituto de Investigaci´
on Biom´
edica de M´
alaga (IBIMA-Plataforma Bionand), University of
M´
alaga, M´
alaga, Spain
HIGHLIGHTS GRAPHICAL ABSTRACT
•MedDiet adherence and calorie reduc-
tion mediate improved environmental
impact.
•An energy-reduced MedDiet improves
acidication, eutrophication, and land
use.
•Meat has a greater impact on acidica-
tion, eutrophication, land use and
energy.
•In terms of GHGs, the main contributor
in the CG was meat and, in the IG, sh.
ARTICLE INFO
Editor: Jacopo Bacenetti
Keywords:
Climate change
Healthy dietary pattern
Sustainable food
ABSTRACT
Objective: To estimate the environmental impact of a dietary intervention based on an energy-reduced Medi-
terranean diet (MedDiet) after one year of follow-up.
Methods: Baseline and 1-year follow-up data were used for 5800 participants aged 55–75 years with metabolic
syndrome in the PREDIMED-Plus study. Food intake was estimated through a validated semiquantitative food
consumption frequency questionnaire, and adherence to the MedDiet was estimated through the Diet Score.
Using the EAT-Lancet Commission tables we assessed the inuence of dietary intake on environmental impact
(through ve indicators: greenhouse gas emissions (GHG), land use, energy used, acidication and potential
eutrophication). Using multivariable linear regression models, the association between the intervention and
changes in each of the environmental factors was assessed. Mediation analyses were carried out to estimate to
what extent changes in each of 2 components of the intervention, namely adherence to the MedDiet and caloric
reduction, were responsible for the observed reductions in environmental impact.
Results: We observed a signicant reduction in the intervention group compared to the control group in acidi-
cation levels (−13.3 vs. -9.9 g SO2-eq), eutrophication (−5.4 vs. -4.0 g PO4-eq) and land use (−2.7 vs. -1.8 m2).
Adherence to the MedDiet partially mediated the association between intervention and reduction of acidication
by 15 %, eutrophication by 10 % and land use by 10 %. Caloric reduction partially mediated the association with
the same factors by 55 %, 51 % and 38 % respectively. In addition, adherence to the MedDiet fully mediated the
association between intervention and reduction in GHG emissions by 56 % and energy use by 53 %.
Conclusions: A nutritional intervention based on consumption of an energy-reduced MedDiet for one year was
associated with an improvement in different environmental quality parameters.
1. Introduction
Climate change is one of the greatest public health threats of our time
(Costello et al., 2009; Watts et al., 2015). Negative effects range from
rising global temperatures, changes in precipitation patterns, droughts
and more intense heat waves (Roca Villanueva et al., 2019) to patho-
genic diseases and aggravated transmission pathways (dengue, Zika,
malaria or chikungunya among others) (Mora et al., 2022). In addition,
it also conditions agricultural and livestock activities, with climate
change being associated with a reduction in both the quality and
quantity of food produced (Intergovernmental Panel on Climate Change,
2023; Rojas-Downing et al., 2017).
It is estimated that by 2050 the world’s population will have
increased to almost 10 billion people with the consequent increase in the
demand for food that this implies (FAO, 2018). If we take into account
that food systems are responsible for approximately 30 % of global
greenhouse gas (GHG) emissions (Crippa et al., 2021), 78 % of eutro-
phication, 32 % of terrestrial acidication (Poore and Nemecek, 2018),
70 % of freshwater use and 60 % of global biodiversity loss (HLPE,
2017), food production becomes a key point to achieve greater envi-
ronmental sustainability.
According to the latest synthesis report of the Intergovernmental
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Science of the Total Environment 928 (2024) 172610
3
Panel on Climate Change (IPCC) (Intergovernmental Panel on Climate
Change, 2023), one of the measures to mitigate climate change would
focus on food systems and within them, one of the key points would be
diets (Sun et al., 2022). The Food and Agriculture Organization of the
United Nations (FAO) established the denition of sustainable diets as
those “with low environmental impacts which contribute to food and
nutrition security and to healthy life for present and future generations”
with specic features, such as “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” (World Health Organization, 2019).
The choice of different dietary patterns is essential when it comes to
making the food system more sustainable since the type of diet that is
followed directly inuences the quality and quantity of what is eaten
and this conditions the individual environmental footprint that is
generated (Hess et al., 2016; Willett et al., 2019). Current studies agree
that eating patterns with fewer animal foods and more plant foods, in
addition to being healthier, have a lower environmental impact (Alek-
sandrowicz et al., 2016; Chai et al., 2019; Nelson et al., 2016; Willett
et al., 2019).
Therefore, the aim of this study was to estimate the reduction of the
environmental impact of an intensive nutritional intervention based on
an energy-reduced Mediterranean Diet (MedDiet) in a cohort of older
Spanish adults with overweight/obesity and Metabolic Syndrome after
one year of follow-up in the framework of the PREDIMED-Plus study.
2. Methods
2.1. Study design
This study used baseline and after one year intervention data from
the PREDIMED-Plus study. This is a multicentre, randomized (non-
blinded) 8-year trial carried out in Spain which objective is to evaluate
the effect of an intensive weight loss intervention based on the con-
sumption of an energy-reduced MedDiet, promotion of physical activity
and behavioural therapy on the prevention of cardiovascular risk. The
study protocol contains all the detailed information (Martínez-Gonz´
alez
et al., 2019; Salas-Salvad´
o et al., 2019) and is available on the project
website http://predimedplus.com. This trial was registered on July 24,
2014, in the International Standard Randomized Controlled Trial
(ISRCT; http://www.isrctn.com/ISRCTN89898870). The Research
Ethics Committees of the 23 recruiting centres approved the study
protocol that complied with the ethical standards of the Helsinki
Declaration (Cantín, 2014). In addition, all participants gave their
written consent to the entry of the program.
2.2. Study population
From September 2013 to November 2016, 23 centres in Spain con-
tacted 9677 people, of which 6874 were included in the program. The
participants selected were men (55–75 years) and women (60–75 years)
with no history of cardiovascular disease, body mass index ≥27 and <
40 kg/m
2
, and at least 3 criteria for metabolic syndrome according to the
denition of the International Diabetes Federation/National Heart,
Lung, and Blood Institute/American Heart Association (Alberti et al.,
2009). Participants were randomly assigned in two distinct groups: the
intervention group (IG) in which an energy-reduced MedDiet was pro-
moted with physical activity and behavioural therapy guidelines; and
the control group (CG) in which general advice about the MedDiet was
given but without promoting weight loss. Both groups received 1 l/
month of extra virgin olive oil and all participants were encouraged to
consume raw nuts.
Our study excluded those participants who had not completed the
Food Frequency Questionnaire (FFQ) in one of the two visits and those
with extreme energy intake (<500 or >3500 kcal/day in women and <
800 or >4000 kcal/day in men)(Willett et al., 1997), including nally a
sample of 5800 participants (Fig. 1).
2.3. Variables and data collection
At the beginning of the program and at one year of intervention,
dietary information was collected through a validated semi-quantitative
143-item (FFQ) for the Spanish population (De La Fuente-Arrillaga et al.,
2010; Fern´
andez-Ballart et al., 2010; Martin-moreno et al., 1993). This
questionnaire collects information about the previous year’s food con-
sumption, with nine possible responses ranging from never or almost
never to more than six times a day and with a specic standard portion
size for each of the items. The total energy and nutrient consumption of
each participant was calculated by multiplying the consumption fre-
quencies by the weight of the standard serving size and the nutritional
information was obtained from the Spanish food composition tables
(Mataix-Verdú et al., 2013; Moreiras et al., 2018).
To calculate adherence to MedDiet we used the index created by
Panagiotakos (Panagiotakos et al., 2007), which uses a score of 0 to 55
points and classies adherence by tertiles, corresponding the rst tertile
to a low adherence and the third to the highest adherence. This index
considers 11 food groups. Each component has a specic scale, with
higher scores for frequent consumption of those foods recommended
within the Mediterranean pattern (fruits, vegetables, pulses, potatoes,
whole grains, sh, and olive oil) and lower scores for those foods whose
consumption should be moderated according to this dietary pattern
(poultry, red meat, dairy products with fat, and alcohol). The total score
is calculated by adding the points obtained in each component.
Information on socio-demographic variables (age, sex, and educa-
tional level) and on lifestyles (dietary habits) was collected at baseline.
Anthropometric variables were determined by trained staff according to
the PREDIMED-Plus protocol.
2.4. Estimating the environmental footprint
Based on the information collected in the EAT-Lancet Commission
tables (Willett et al., 2019) and using the data obtained in the FFQ, we
estimated the greenhouse gas (GHG) emissions (grams of CO2-
equivalents), land (m
2
) and energy use (Kilojoules (kJ)) and potential
acidication (grams of SO2-equivalents) and eutrophication (grams of
PO4-equivalents) of the diet of each of the study participants, as previ-
ously described (´
Alvarez-´
Alvarez et al., 2024). It should be noted that
the database employed uses life cycle analysis as a technique, taking into
account the entire supply chain, from producer to consumer, as well as
waste management.
To obtain this data, the following steps were followed:
1) All foods collected in the FFQ for which information was available in
the EAT-Lancet Commissions tables were included in the analysis (i.
e., 102 items) (Environmental footprint values of each food available
in supplementary material);
All foods collected in the FFQ for which information was available
in the EAT-Lancet Commissions tables were included in the analysis
(i.e., 102 items) (Environmental footprint values of each food
available in supplementary material);
2) In the case of items that referred to elaborate dishes, these were
estimated taking into account the ingredients that compose them
following traditional MedDiet recipes (Flo, 1998; S´
anchez-Tainta
et al., 2015), and in the case of commercialised processed foods, the
nutrition labels of commonly consumed brands were consulted to
check the ingredients;
3) When more than one food appeared in a single FFQ item (e.g. white
sh, formed by anglersh, cod, at sh, sea-bass and turbot), the
intake rate was calculated following data from the Spanish national
survey (MAPA, 2022);
4) Based on the meta-analysis (Clark and Tilman, 2017) published
within the recommendations of the EAT-Lancet Commission, the
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Science of the Total Environment 928 (2024) 172610
4
environmental loads of each food were obtained, and to calculate the
environmental impact of each item we multiplied the value of the
environmental load by the daily consumption of each one;
5) Finally, the total environmental impact of each participant’s diet was
obtained by adding the individual food contributions, based on the
data obtained in the FFQ.
To carry out these calculations we took into account the following
considerations: white sh included anglersh, hake, seabass, sole and
turbot; blue sh included mackerel, salmon, trout, and tuna; burgers and
meatballs was considered derived from beef and pork 50 % each of
them; liver from chicken, beef, and pork 33 % each one; sausages, pˆ
at´
e
and other meat products derived from pork.
2.5. Statistical analysis
Independent mean comparison analyses were performed for baseline
and 1-year situations and Kruskal-Wallis tests were used to assess
Fig. 1. Flowchart of participants from the PREDIMED-Plus trial.
Fig. 2. Conventional mediation model for the association between intervention group and different environmental impact indicators with caloric intake and
adherence to the MedDiet as mediators. MedDiet indicates Mediterranean Diet; DS, Dietary Score. c =the total effect of X on Y (c =c’ ab); c’ =the direct effect of X
on Y after controlling for mediators; ab =indirect effect of X on Y.
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Science of the Total Environment 928 (2024) 172610
5
differences between baseline and follow-up data (paired data) between
CG and IG.
To assess whether Mediterranean diet and energy intake were
correlated with each other at baseline and in differences at 1 year for GI
and CG, Pearson pairwise correlations were performed.
Linear regression models adjusted for sex, age, level of education and
baseline caloric intake were used to analyse the association between
intervention and reduction of the different environmental pressures
analysed. A mediation analysis was conducted using structural equation
modelling (Mehmetoglu, 2018). This approach is based on the model
proposed by Baron and Kenny (Baron and Kenny, 1986), modied by
Iacobucci et al. (Iacobucci et al., 2007) and with an alternative approach
proposed by Zhao et al. (Zhao et al., 2010) and was used to determine to
what extent MedDiet, caloric reduction and intervention were respon-
sible for reducing the environmental impact assessed through ve in-
dicators (Fig. 2). The following steps were carried out:
a) A linear regression that analysed the association between the inter-
vention (independent variable) and the difference in environmental
impact (dependent variable), without taking into account the me-
diators (caloric intake and adherence to the MedDiet) (path c ➔ total
effect);
b) A linear regression that analysed the association between the inter-
vention and changes in caloric intake and adherence to the MedDiet
(path a);
c) A linear regression that analysed the association between changes in
caloric intake and adherence to the MedDiet with the difference in
environmental impact (path b);
d) The existence of mediation was determined by analysing the asso-
ciation between the intervention and the difference in environmental
impact, while the mediator remains constant (route c’ ➔ direct ef-
fect), and the indirect effect (path a x path b).
e) Finally, the proportion mediated by caloric intake and MedDiet
adherence was estimated by dividing the indirect effect by the total
effect.
Statistical signicance was set at p <0,05. Stata software version
15.1 (StataCorp LP Statistics/Data Analysis, n.d.) was used for the sta-
tistical analysis, and R software version 4.1.1 (R Core Team, 2016) was
used for the determination of the environmental impact of each
individual.
3. Results
The data obtained on the reduction of the different environmental
impact factors analysed in the two groups of the program can be seen in
Table 1. It shows how IG reduces the impact on the 5 factors analysed,
being the signicant difference (IG vs. CG) in the case of acidication
(−13.3 vs. -9.9 g SO2-eq), eutrophication (−5.4 vs. -4.0 g PO4-eq), and
land use (−2.7 vs. -1.8 m
2
). In addition, signicant differences were
found in the reduction of calories intakes (−178.4 vs. -73.3 kcal) and in
the increase in adherence to MedDiet (1.2 vs. 0.5 points).
Mediterranean diet and energy intake were not correlated with each
other, neither at baseline (r = − 0.1154) nor the differences at 1 year for
IG (r =0.0057) and CG (r = − 0.0650).
The main contributor, at the year of participation in the study, in
both groups (IG vs. CG) was meat with respect to acidication (72.9 vs.
74.8 %), eutrophication (69.6 vs. 72.2 %), energy (50.9 vs. 53.5 %) and
land use (75.3 vs. 76.4 %); the main contributor to GHG emissions for
CG was meat (33.5 %) and in IG were sh and seafood (32.1 %) (Fig. 3).
In addition, Fig. 4 shows the changes that occur in the percentage of
contribution of the different food groups in the different factors analysed
after one year of inclusion in the program. The IG increases the %
contribution against the CG (IG vs. CG) in dairy products, fruits, vege-
tables, and eggs in the ve factors analysed; in addition, it increases the
% of sh and shellsh in the case of GHG emissions (5.6 vs. 2.7 %) and
alcohol in the case of land use (1.7 % vs. 1.3 %). On the other hand, the
IG decreases the % of contribution against the CG in meat, juices, ce-
reals, and pastries in the ve environmental indicators.
Regarding the mediation analysis (Fig. 5), there was a signicant
association between the IG and caloric reduction and the IG and
adherence to the MedDiet (β: −104.7 and 0.68 respectively, path a) and
between each of these mediators and the change in environmental in-
dicators (path b): GHG (β: 1.39 and −25.79, respectively), acidication
(β: 0.02 and −0.91, respectively), eutrophication (β: 0.01 and −0.27,
respectively), land use (β: 0.003 and −0.13, respectively) and energy
use (β: 2.7 and −103.11, respectively).
The direct and indirect effects of the intervention on changes in
different indicators of environmental sustainability with adherence to
the MedDiet and caloric reduction as mediators are shown in Table 2.
Caloric reduction signicantly mediated the association between inter-
vention and reduction of acidication, eutrophication, and land use,
explaining 55 %, 51 % and 38 % of the overall association respectively.
It also signicantly mediated the association between the intervention
and increased GHG and energy use, but as the direction of direct effect
and indirect effect were opposite the proportion of mediation may not be
interpretable (Valeri and VanderWeele, 2013).
On the other hand, adherence to the MedDiet signicantly mediated
the association between the intervention and reduction of acidication,
eutrophication, and land use, explaining 15 %, 10 % and 10 % of the
overall association respectively. In addition, adherence to MedDiet fully
mediated the association between intervention and reduction of GHG
emissions by 56 % and energy use by 53 %.
Path a indicates the regression coefcient for the association
Table 1
Caloric intake, adherence to the MedDiet and environmental impact for the different study groups.
Baseline 1 year intervention Differences
CG IG CG IG CG IG
Mean (SD) Mean (SD) p-
value
Mean (SD) Mean (SD) p-value Mean (SD) Mean (SD) p-value
Caloric intake (Kcal/day) 2374.5 (553.2) 2361.5 (545.7) 0.368 2300.8 (490.3) 2183.1 (452.2) <0.001 −73.7 (525.6) −178.4 (543.0) <0.001
Dietary Score (points) 33.4 (4.0) 33.5 (3.9) 0.196 33.9 (3.8) 34.7 (3.7) <0.001 0.5 (3.5) 1.2 (3.7) <0.001
GHG (g/CO2-eq) 5058.9
(1529.8)
4998.1
(1492.7) 0.126 4713.8
(1324.6)
4620.4
(1258.4) 0.006 −345.1
(1460.0)
−377.7
(1509.4) 0.403
Acidication (g SO2-eq) 61.7 (27.6) 64.4 (26.3) 0.053 55.8 (23.2) 51.1 (21.2) <0.001 −9.9 (26.5) −13.3 (27.1) <0.001
Eutrophication (g PO4-
eq) 24.9 (11.7) 24.3 (11.1) 0.047 20.9 (9.9) 18.9 (8.9) <0.001 −4.0 (11.2) −5.4 (11.5) <0.001
Land use (m
2
) 9.9 (5.2) 9.8 (5.2) 0.338 8.2 (4.3) 7.1 (3.9) <0.001 −1.8 (4.9) −2.7 (5.1) <0.001
Energy use (kJ) 9307.2 (2745) 9247.2
(2700.3) 0.402 8519.3
(2362.9) 8347 (2268.7) 0.005 −787.9
(2647.2)
−899.7
(2798.8) 0.119
Notes: Mean and SD for different factors at baseline and one year of intervention for both study groups. CG indicates control group; IG, intervention group; SD, standard
deviation; GHG, greenhouse gas emissions. The results highlighted in bold are those statistically signicant (p <0.05).
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between intervention and caloric intake and adherence to the MedDiet.
Path b indicates the regression coefcient for the association between
caloric intake and adherence to the MedDiet with the different in-
dicators of environmental sustainability. Path c’ indicates the direct
effect of the intervention on environmental sustainability indicators
after adjustment for caloric intake or adherence to the MedDiet. Path c
indicates the simple total effect of the intervention on environmental
sustainability indicators without adjustment for caloric intake and
adherence to the MedDiet.
4. Discussion
This work shows how a nutritional intervention based on a one-year
energy-reduced MedDiet improves environmental impact data, doing so
signicantly in the case of acidication, eutrophication, and land use. In
addition, it shows how this improvement in environmental sustain-
ability is mediated by adherence to MedDiet and caloric reduction.
To our knowledge, the present study is the rst to evaluate the role of
caloric reduction and adherence to the MedDiet in the relationship be-
tween intensive nutritional intervention and environmental impact
reduction by using a mediation analysis. In our work, the reduction in
caloric intake acted as a mediator between nutritional intervention and
the reduction in acidication, eutrophication, and land use (with a
mediated proportion of 55 %, 51 % and 38 % respectively). In the same
way, but to a lesser extent, greater adherence to the MedDiet acted as a
partial mediator of these associations (with a mediated proportion of 15
%, 10 % and 10 % respectively).
The food group that had the most environmental impact on both
Fig. 3. Contribution of food groups to the different environmental factors analysed at one year of intervention.
*CG indicates control group; IG, intervention group; Eutrop, eutrophication; GHG, Greenhouse Gas emissions; and Land, land use.
Fig. 4. Change in percentage of contribution of food groups to the different environmental factors analysed at one year of intervention.
*CG indicates control group; IG, intervention group; GHG, Greenhouse Gas emissions; and Land, land use.
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groups (CG and IG) in the 5 indicators analysed were meat products,
with the greatest impact always on the CG, except only the IG in which
the largest contributor to the GHG emission was sh. This is in line with
different published works that establish that animal products, and more
specically meat, are responsible for the emission of a greater amount of
GHG and a greater use of energy and land (Hedenus et al., 2014; Hjorth
et al., 2020; Tepper et al., 2022; Tilman and Clark, 2014; van de Kamp
et al., 2018). This could be explained by the fact that about 70 % of
global agricultural land is used by livestock, which translates into the
main cause of deforestation and, in turn, leads to further land degra-
dation (Friel et al., 2009; Stehfest et al., 2009).
In the case of the IG, the largest contributor to GHG emissions was
sh, increasing its consumption after a year of intervention. This may be
the reason why although the IG reduces GHG emissions more than the
CG, it does not do so signicantly. Although within the MedDiet pattern
the consumption of 2 to 3 servings per week of sh is recommended for
its indisputable health benets (Chen et al., 2022; Jurek et al., 2022;
Mohan et al., 2021), sh may contribute to exposure to certain
pollutants such as heavy metals (Casta˜
no et al., 2015) and, in addition,
has GHG values similar to meat, so this recommendation may not be as
sustainable (Lofstedt et al., 2021).
Despite the fact that there is increasing evidence of the relationship
between dietary habits and the impact on the environment (Stehfest
et al., 2009; Tilman and Clark, 2014; Tukker and Jansen, 2006), one of
the problems that we nd when comparing our results is that there are
few published papers analysing the real change in environmental impact
through dietary interventions. Nevertheless, our results are in line with
those published by Rosi et al. (Rosi et al., 2022), whose study showed a
certain improvement in environmental sustainability promoting adher-
ence to the MedDiet. In addition, they are in line with other papers
already published in which authors observed a reduction in GHG
emissions and in the use of land and energy with a high adherence to the
MedDiet (Baudry et al., 2023; Fres´
an et al., 2018; García et al., 2023;
Germani et al., 2014; Grosso et al., 2020; Tepper et al., 2022).
Most of the studies are based on hypothetical changes in the con-
sumption of certain populations, but agree that the consumption of diets
Fig. 5. Conventional mediation scheme for the association between the intervention and the different indicators of environmental sustainability with caloric intake
and adherence to MedDiet as mediators. Mediation model adjusted for sex, age, education level and baseline caloric intake.
* p <0.05; ** p <0.001.
Table 2
Direct and indirect effects of the intervention on different indicators of environmental sustainability with caloric intake and adherence to the MedDiet as mediators.
Independent variable Mediator Outcome variable Indirect effect Direct effect Proportion Mediated
β Coefcient (95 % CI) β Coefcient (95 % CI) %
Intervention group Energy intake
GHG −145.6 (−184.7 to −106.5)* 114.4 (47.5 to 181.3)* non interpretable
Acidication −2.3 (−2.9 to −1.7)* −1.8 (−2.8 to −0.9)* 55 % partial
Eutrophication −0.9 (−1.1 to −0.6)* −0.9 (−1.3 to −0.5)* 51 % partial
Land use −0.3 (−0.4 to −0.3)* −0.6 (−0.8 to −0.3)* 38 % partial
Energy use −242.7 (−308.3 to −177.1)* 128.8 (4.7 to 253.0)* non interpretable
Intervention group Mediterranean Diet
GHG −17.0 (−25.6 to −8.5)* −13.5 (−90.0 to 63.0) 56 % complete
Acidication −0.6 (−0.8 to −0.4)* −3.6 (−4.7 to −2.6)* 15 % partial
Eutrophication −0.2 (−0.2 to −0.1)* −1.6 (−2.0 to −1.2)* 10 % partial
Land use −0.1 (−0.1 to −0.06)* −0.8 (−1.1 to −0.6)* 10 % partial
Energy use −70.3 (−93.2 to −47.5)* −63.2 (−195.1 to 68.6) 53 % complete
Mediation model adjusted for sex, age, education level and starting point of caloric intake. Notes: GHG indicates greenhouse gas emissions; CI, condence interval.
*
Indicates p <0.05.
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Science of the Total Environment 928 (2024) 172610
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rich in plant products and with a lower contribution of animal products
would have a clear benet on environmental sustainability (Aleksan-
drowicz et al., 2016; Belgacem et al., 2021; Serra-Majem et al., 2018).
For example, the review published by Fres´
an et al. (Fres´
an and Sabat´
e,
2019) exposed that the shift from omnivorous diets to vegan and ovo-
lactovegetarian options is associated with the use of fewer natural re-
sources and lower GHG emissions and therefore with greater
environmental sustainability, and the review published by Berardy et al.
(Berardy et al., 2022) linked the use of vegetable drinks with a more
sustainable diet. However, it should be mentioned that vegetarian diets,
if not properly planned, can lead to deciencies in certain micro-
nutrients such as vitamin D, vitamin B12, calcium or iron (Casta˜
n´
e and
Ant´
on, 2017; Key et al., 2006).
Compared to the large number of studies analysing the relationship
between diet and health, there is very little literature (although it is
increasing considerably in recent years) that addresses the relationship
between dietary patterns and environmental sustainability. It is well
known that dietary choices affect people’s health, and also that those
dietary choices, along with the food system, affect the environment.
Therefore, in recent years the use of the term “trilemma diet-environ-
ment-health” has spread.
In this context, the MedDiet, characterised by moderation and
frugality, is postulated as a reference dietary standard since, in addition
to its known benets on cardiovascular health, the prevention of chronic
diseases and certain types of cancer (´
Alvarez-´
Alvarez et al., 2019;
´
Alvarez-´
alvarez et al., 2021; Guasch-Ferr´
e and Willett, 2021; Martinez-
Gonzalez and Bes-Rastrollo, 2014; Rosato et al., 2019; Salas-Salvado
et al., 2011; Schwingshackl et al., 2017), it is a dietary model that
promotes biodiversity and reduces environmental impact (Germani
et al., 2014; Serra-Majem and Ortiz-Andrellucchi, 2018).
5. Strengths and limitations
One of the main limitations of our work is that there is not a single
database that gathers the environmental impact generated by food, but
rather there are numerous databases collecting information, so the re-
sults obtained may not be quantitatively comparable. In addition, we
understand that there are products that could be produced locally and
therefore have a different environmental impact than the one used for
our calculations. It should also be taken into account that the environ-
mental impact may vary depending on the geographical location,
especially in the cultivation of agricultural products, so we always talk
about estimates.
Another of the limitations is that the database on which we rely to
perform the calculations does not include all the items of the FFQ, so
they were outside the analysis food with great presence in the MedDiet
as some types of legumes and nuts. Also, recall bias cannot be excluded
when food intake data are obtained from an indirect reporting method
such as the FFQ. However, this FFQ has been validated in the Spanish
population and shows a good level of reproducibility and validity (De La
Fuente-Arrillaga et al., 2010). In addition, the population on which the
study was based was adults aged 55–75 years with metabolic syndrome,
which may limit the extrapolation of the results to general populations.
Finally, although a dietary intervention is not carried out on the CG
or an energy-reduced diet is applied, it is given MedDiet guidelines that
may have prevented seeing more differences between both groups since
both decrease caloric intake and improve adherence to the MedDiet after
one year of permanence in the study.
As far as we know, there is no published study examining the rela-
tionship between an intensive nutritional intervention based on an
energy-reduced MedDiet and the reduction of environmental impact
using mediation analysis. Therefore, we believe that this work can ll
this gap in literature.
Another of the strengths of this work is that it performs an analysis of
the real change in the environmental impact by nutritional intervention
while most of the published studies are based on hypothetical scenarios
of change in dietary patterns.
In addition, although normally this type of studies focuses on GHG
emissions, this work has taken into account four other indicators to
assess the environmental impact of the MedDiet: acidication, eutro-
phication and land and energy use.
Finally, it is also necessary to mention the size of the sample used to
carry out the analysis that is relatively large and that the database
employed uses life cycle analysis as a technique.
6. Conclusions
After a year of intensive nutritional intervention with promotion of
energy-reduced MedDiet, IG participants reduced to a greater extent
than CG the ve environmental impact indicators analysed, making it
signicantly in acidication, eutrophication, and land use.
Although in almost all cases, meat products were the ones that
contributed the most to the environmental impact in all the indicators
analysed, the IG always had a lower consumption, which strengthens the
idea that diets with less contribution of these products will have a lower
environmental impact.
In addition, this study shows how this improvement in environ-
mental impact was mediated in part by the increase in adherence to
MedDiet and the caloric reduction in the diet of the participants.
Therefore, an intensive nutritional intervention based on the con-
sumption of an energy-reduced MedDiet is associated with the
improvement of different environmental quality parameters which
translates into a more sustainable diet.
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.scitotenv.2024.172610.
Ethics approval and consent to participate
The study protocol was approved by the Research Ethics Committees
of all recruiting centres. In addition, all participants signed an informed
consent form upon entry into the study.
Consent for publication
Informed consent was obtained from all subjects involved in the
study.
Funding
This work was supported by the ofcial Spanish Institutions for
funding scientifc biomedical research, CIBER Fisiopatología de la Obe-
sidad y Nutrici´
on (CIBEROBN) and Instituto de Salud Carlos III (ISCIII),
through the Fondo de Investigaci´
on para la Salud (FIS), which is co-
funded by the European Regional Development Fund (six coordinated
FIS projects leaded by JS-S and JVi, including the following projects:
PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462,
PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056,
PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206,
PI14/01919, PI14/00853, PI14/01374, PI14/00972, PI14/00728,
PI14/01471, PI16/00473, PI16/00662, PI16/01873, PI16/01094,
PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522,
PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347,
PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441,
PI17/00508, PI17/01732, PI17/00926, PI19/00957, PI19/00386,
PI19/00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226,
PI19/00781, PI19/01560, PI19/01332, PI20/01802, PI20/00138,
PI20/01532, PI20/00456, PI20/00339, PI20/00557, PI20/00886,
PI20/01158); the Especial Action Project entitled: Implementaci´
on y
evaluaci´
on de una intervenci´
on intensiva sobre la actividad física
Cohorte PREDIMED-Plus grant to JS-S; the European Research Council
(Advanced Research Grant 2014–2019; agreement #340918) granted to
M´
AM-G.; the Recercaixa (number 2013ACUP00194) grant to JS-S;
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Science of the Total Environment 928 (2024) 172610
9
grants from the Consejería de Salud de la Junta de Andalucía (PI0458/
2013, PS0358/2016, PI0137/2018; PI-0067-2022); the PROMETEO/
2017/017 and PROMETEO/2021/021 grant from the Consellería
Innovaci´
on, Ciencia y Sociedad Digital, Generalitat Valenciana; the
SEMERGEN grant. J.S-S is partially supported by ICREA under the
ICREA Academia programme. AC is cofounded by Margarita Salas
fellowship part of the Recovery, Transformation and Resilience Plan -
Funded by the European Union - NextGenerationEU (Ministry of Uni-
versities). None of the funding sources took part in the design, collec-
tion, analysis, interpretation of the data, or writing the report, or in the
decision to submit the manuscript for publication.
CRediT authorship contribution statement
Laura ´
Alvarez-´
Alvarez: Writing – original draft, Methodology,
Investigation, Formal analysis, Data curation, Conceptualization. María
Rubín-García: Writing – review & editing, Methodology, Investigation,
Formal analysis, Data curation, Conceptualization. Facundo Vitelli-
Storelli: Writing – review & editing, Methodology, Investigation,
Formal analysis, Data curation, Conceptualization. Silvia García:
Writing – review & editing, Investigation, Data curation, Conceptuali-
zation. Cristina Bouzas: Writing – review & editing, Investigation, Data
curation, Conceptualization. Miguel ´
Angel Martínez-Gonz´
alez:
Writing – review & editing, Investigation, Data curation, Conceptuali-
zation. Dolores Corella: Writing – review & editing, Investigation, Data
curation, Conceptualization. Jordi Salas-Salvad´
o: Writing – review &
editing, Investigation, Data curation, Conceptualization. Mireia Mal-
campo: Writing – review & editing, Investigation, Data curation,
Conceptualization. J. Alfredo Martínez: Writing – review & editing,
Investigation, Data curation, Conceptualization. ´
Angel M. Alonso-
G´
omez: Writing – review & editing, Investigation, Data curation,
Conceptualization. Julia W¨
arnberg: Writing – review & editing,
Investigation, Data curation, Conceptualization. Jesús Vioque: Writing
– review & editing, Investigation, Data curation, Conceptualization.
Dora Romaguera: Writing – review & editing, Investigation, Data
curation, Conceptualization. Ramon Estruch: Writing – review &
editing, Investigation, Data curation, Conceptualization. Francisco J.
Tinahones: Writing – review & editing, Investigation, Data curation,
Conceptualization. Jos´
e Lapetra: Writing – review & editing, Investi-
gation, Data curation, Conceptualization. Lluís Serra-Majem: Writing –
review & editing, Investigation, Data curation, Conceptualization.
Aurora Bueno-Cavanillas: Writing – review & editing, Investigation,
Data curation, Conceptualization. Camino García Fern´
andez: Writing
– review & editing, Investigation, Data curation, Conceptualization.
Xavier Pint´
o: Writing – review & editing, Investigation, Data curation,
Conceptualization. Miguel Delgado-Rodríguez: Writing – review &
editing, Investigation, Data curation, Conceptualization. Pilar Matía-
Martín: Writing – review & editing, Investigation, Data curation,
Conceptualization. Josep Vidal: Writing – review & editing, Investi-
gation, Data curation, Conceptualization. Clotilde V´
azquez: Writing –
review & editing, Investigation, Data curation, Conceptualization. Lidia
Daimiel: Writing – review & editing, Investigation, Data curation,
Conceptualization. Emilio Ros: Writing – review & editing, Investiga-
tion, Data curation, Conceptualization. Ana García-Arellano: Writing –
review & editing, Investigation, Data curation, Conceptualization.
María ´
Angeles Martínez: Writing – review & editing, Investigation,
Data curation, Conceptualization. Jos´
e V. Sorlí: Writing – review &
editing, Investigation, Data curation, Conceptualization. María Dolores
Zome˜
no: Writing – review & editing, Investigation, Data curation,
Conceptualization. Antonio García-Rios: Writing – review & editing,
Investigation, Data curation, Conceptualization. Sandra Gonz´
alez-
Palacios: Writing – review & editing, Investigation, Data curation,
Conceptualization. Margalida Monserrat-Mesquida: Writing – review
& editing, Investigation, Data curation, Conceptualization. Itziar Abete:
Writing – review & editing, Investigation, Data curation, Conceptuali-
zation. Antoni Colom Fern´
andez: Writing – review & editing,
Investigation, Data curation, Conceptualization. Rosa Casas: Writing –
review & editing, Investigation, Data curation, Conceptualization.
Naomi Cano Iba˜
nez: Writing – review & editing, Investigation, Data
curation, Conceptualization. Lucía Ugarriza: Writing – review & edit-
ing, Investigation, Data curation, Conceptualization. M. Rosa Bernal-
L´
opez: Writing – review & editing, Investigation, Data curation,
Conceptualization. Maira Bes-Rastrollo: Writing – review & editing,
Investigation, Data curation, Conceptualization. Indira Paz-Graniel:
Writing – review & editing, Investigation, Data curation, Conceptuali-
zation. Eva M. Asensio: Writing – review & editing, Investigation, Data
curation, Conceptualization. Montse Fit´
o: Writing – review & editing,
Investigation, Data curation, Conceptualization. Antonio P. Arenas
Larriva: Writing – review & editing, Investigation, Data curation,
Conceptualization. Alejandro Oncina-C´
anovas: Writing – review &
editing, Investigation, Data curation, Conceptualization. Zenaida
V´
azquez: Writing – review & editing, Investigation, Data curation,
Conceptualization. María Fern´
andez de la Puente: Writing – review &
editing, Investigation, Data curation, Conceptualization. Alejandra
P´
erez-Vega: Writing – review & editing, Investigation, Data curation,
Conceptualization. Josep A. Tur: Writing – review & editing, Investi-
gation, Data curation, Conceptualization. Vicente Martín-S´
anchez:
Writing – review & editing, Methodology, Investigation, Formal anal-
ysis, Data curation, Conceptualization.
Declaration of competing interest
J.S.-S. reported receiving research support from the Instituto de
Salud Carlos III, Ministerio de Educaci´
on y Ciencia, the European
Commission, the USA National Institutes of Health; receiving consulting
fees or travel expenses from Eroski Foundation and Instituto Danone,
receiving nonnancial support from Hojiblanca, Patrimonio Comunal
Olivarero, the California Almond Board of California, Pistachio Growers
and Borges S.A; serving on the board of and receiving grant support
through his institution from the International Nut and Dried Foundation
and the Eroski Foundation; and personal fees from Instituto Danone
Spain; Serving in the Board of Danone Institute International. D⋅C. re-
ported receiving grants from Instituto de Salud Carlos III. R.E. reported
receiving grants from Instituto de Salud Carlos III, Fundaci´
on Dieta
Meditarr´
anea and Cerveza y Salud and olive oil for the trial from
Fundaci´
on Patrimonio Comunal Olivarero and personal fees from
Brewers of Europe, Fundaci´
on Cerveza y Salud, Interprofesional del
Aceite de Oliva, Instituto Cervantes in Albuquerque, Milano and Tokyo,
Pernod Ricard, Fundaci´
on Dieta Mediterr´
anea (Spain), Wine and Culi-
nary International Forum and Lilly Laboratories; nonnancial support
from Sociedad Espa˜
nola de Nutrici´
on and Fundaci´
on Bosch y Gimpera;
and grants from Uriach Laboratories. The rest of the authors have
declared that no competing interests exist. The funders had no role in the
design of the study; in the collection, analysis, or interpretation of data;
in the writing of the manuscript, or in the decision to publish the results.
Data availability
Data described in the manuscript, code book, and analytic code will
be made available upon request pending application and approval of the
PREDIMED-Plus Steering Committee. There are restrictions on the
availability of data for the PREDIMED-Plus trial, due to the signed
consent agreements around data sharing, which only allow access to
external researchers for studies following the project purposes. Re-
questors wishing to access the PREDIMED-Plus trial data used in this
study can make a request to the PREDIMED-Plus trial Steering Com-
mittee chair: jordi.salas@urv.cat. The request will then be passed to
members of the PREDIMED-Plus Steering Committee for deliberation.
Acknowledgments
The authors especially thank the PREDIMED-Plus participants for the
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Science of the Total Environment 928 (2024) 172610
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enthusiastic collaboration, the PREDIMED-Plus personnel for
outstanding support, and the personnel of all associated primary care
centers for the exceptional effort. CIBEROBN, CIBERESP, and CIBER-
DEM are initiatives of Instituto de Salud Carlos III (ISCIII), Madrid,
Spain. The authors also thank the PREDIMED-Plus Biobank Network as a
part of the National Biobank Platform of the ISCIII for storing and
managing the PREDIMED-Plus biological samples.
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