Content uploaded by Alessandro Monaco
Author content
All content in this area was uploaded by Alessandro Monaco on Jun 30, 2021
Content may be subject to copyright.
Available via license: CC BY-NC 3.0
Content may be subject to copyright.
PERSPECTIVE
Perspective: Improving Nutritional Guidelines for
Sustainable Health Policies: Current
Status and Perspectives
Paolo Magni,
1
Dennis M Bier,
3
Sergio Pecorelli,
4
Carlo Agostoni,
2
Arne Astrup,
5
Furio Brighenti,
6
Robert Cook,
7
Emanuela Folco,
8
Luigi Fontana,
9,10
Robert A Gibson,
11
Ranieri Guerra,
12
Gordon H Guyatt,
13
John PA Ioannidis,
14
Ann S Jackson,
4
David M Klurfeld,
15
Maria Makrides,
16
Basil Mathioudakis,
17
Alessandro Monaco,
8
Chirag J Patel,
18
Giorgio Racagni,
1
Holger J Schünemann,
13
Raanan Shamir,
19
Niv Zmora,
20
and Andrea Peracino
8
1
Department of Pharmacological and Biomolecular Sciences, and
2
Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, DISCCO,
Università degli Studi di Milano, Milan, Italy;
3
Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX;
4
Giovanni Lorenzini
Medical Science Foundation, Houston, TX;
5
Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark;
6
Department of Food Sciences, University of Parma, Parma, Italy;
7
Bazian, Economist Intelligence Unit Healthcare, London, United Kingdom;
8
Giovanni Lorenzini Medical Science Foundation, Milan, Italy;
9
Department of Clinical and Experimental Sciences, University of Brescia, Brescia,
Italy;
10
Department of Medicine, Washington University, St. Louis, MO;
11
School of Agriculture, Food and Wine, FOODplus Research Centre,
University of Adelaide, Adelaide, Australia;
12
Department of Preventive Health, Ministry of Health, Rome, Italy;
13
Department of Clinical
Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada;
14
Department of Health Policy and Research, Stanford
University, Stanford, CA;
15
Human Nutrition Program, USDA Agricultural Research Service, Beltsville, MD;
16
Healthy Mothers, Babies and Children,
South Australian Health and Medical Research Institute, Adelaide, Australia;
17
Consulting sprl, Food Legislation and Nutrition, Brussels, Belgium;
18
Department of Biomedical Informatics, Harvard Medical School, Boston, MA;
19
Institute of Gastroenterology, Nutrition and Liver Diseases,
Schneider Children’s Medical Center of Israel, Sackler Faculty of Medicine, University of Tel Aviv, Tel Aviv, Israel; and
20
Department of Immunology,
Weizmann Institute of Science, Rehovot, Israel
ABSTRACT
A large body of evidence supports the notion that incorrect or insufficient nutrition contributes to disease development. A pivotal goal is thus to
understand what exactly is appropriate and what is inappropriate in food ingestion and the consequent nutritional status and health. The
effective application of these concepts requires the translation of scientific information into practical approaches that have a tangible and
measurable impact at both individual and population levels. The agenda for the future is expected to support available methodology in nutrition
research to personalize guideline recommendations, properly grading the quality of the available evidence, promoting adherence to the well-
established evidence hierarchy in nutrition, and enhancing strategies for appropriate vetting and transparent reporting that will solidify the
recommendations for health promotion. The final goal is to build a constructive coalition among scientists, policy makers, and communication
professionals for sustainable health and nutritional policies. Currently, a strong rationale and available data support a personalized dietary
approach according to personal variables, including sex and age, circulating metabolic biomarkers, food quality and intake frequency, lifestyle
variables such as physical activity, and environmental variables including one’s microbiome profile. There is a strong and urgent need to
develop a successful commitment among all the stakeholders to define novel and sustainable approaches toward the management of the
health value of nutrition at individual and population levels. Moving forward requires adherence to well-established principles of evidence
evaluation as well as identification of effective tools to obtain better quality evidence. Much remains to be done in the near future. Adv Nutr
2017;8:532–45.
Keywords: food, genetics, microbiome, nutritional status, personalized nutrition
Introduction
Nutritional guidelines: a historical perspective
The general concept that appropriate nutrition is a very
powerful agent capable of promoting human health is
strongly shared worldwide and has been supported by a
large set of epidemiologic, observational, and experimental
studies and clinical trials over the last century (1–3).
Likewise, a consistent body of evidence supports the thesis
that incorrect or insufficient nutrition contributes to disease
development (4). However, understanding what exactly is
appropriate and what is incorrect or insufficient nutrition
has been a challenge. Moreover, the effective application of
532 ã2017 American Society for Nutrition. Adv Nutr 2017;8:532–45; doi: https://doi.org/10.3945/an.116.014738.
these concepts requires the translation of scientific informa-
tion into practical approaches that have a tangible, measur-
able impact at both individual and population levels.
Over time, translational challenges have brought scien-
tists together to try to provide guidance to people through
the definition of nutritional recommendations and guide-
lines that may be successfully implemented in different geo-
graphic, cultural, ethnic, and socioeconomic contexts.
Numerical recommendations for nutrients or foods are
not independent of each other, and therefore the review pro-
cess in setting guidelines should consider studies that have
used both approaches. Moreover, some coherence between
the different approaches is also expected to be more confi-
dent in the trust that can be placed in a guideline. The ques-
tion about how much of a given nutrient is needed to meet
various biological requirements was initially answered by
setting reference values for energy and nutrients [dietary ref-
erence values (DRVs); RDA], mainly intended to address
malnutrition due to nutrient deficiency. It must be noted
that the early use of terms such as “recommended”in
such guidance documents (e.g., Recommended Dietary In-
takes) generated the idea of an intrinsic benefit in meeting
these levels of nutrients at the individual level. The more ap-
propriate term “reference”is now commonly used as well as
the validity of referring such values mainly to populations.
Examples of DRVs exist at international [e.g., European
Food Safety Authority European Dietary Reference Values
(5)] and national levels. It must be noted that DRVs, gener-
alized to a reference average adult, represent the basis of nu-
trition labeling of foods, with evident limits when used to
provide guidance to individuals. Conversely, with the cur-
rent status of the evidence, where there is often large residual
uncertainty even about big, high-level questions in nutri-
tion arriving at specific numerical recommendations about
an exact desirable threshold for specific nutrients (e.g., no
more than a particular percentage of added sugars) or foods
(e.g., less than a particular amount of red meat weekly) is of-
ten an unreliable exercise with outcomes that are debatable.
In this perspective, it seems meaningless to simply recom-
mend reducing saturated fat intake to <8% energy intake
given the current knowledge that individual FAs behave bi-
ologically very differently and depend on the specific food
matrix. Thus, in this context, recommendations to reduce
dark chocolate (stearic acid) and cheese intakes may con-
ceivably be counterproductive for health.
Nutritional guidelines have been developed over the last
decades to meet different requirements, such as public
health needs, and to promote a healthy lifestyle aimed at re-
ducing the prevalence of some noncommunicable diseases
(NCDs) (6). Currently, nutritional guidelines produced by
national and international institutions and scientific organiza-
tions represent a large body of documents, including, for ex-
ample, the widely used WHO guidelines on nutrition (7), the
Dietary Guidelines for Americans 2015–2020 Eighth Edi-
tion (8, 9), the European dietary reference values for nutrient
intakes, updated by the European Food Safety Authority (5),
and the Nordic Nutrition Recommendations (2012) (10). In
particular, WHO guidelines are intended as global, evidence-
based recommendations directed to a wide audience, includ-
ing policy makers, their expert advisers, and technical and
program staff at organizations involved in the design, imple-
mentation, and scaling-up of nutrition actions for public
health. The Dietary Guidelines for Americans are designed
for professionals to help individuals consume a healthy, nu-
tritionally adequate diet. By US law, the information in these
Dietary Guidelines forms the foundation for developing fed-
eral food, nutrition, and health policies and programs in the
United States. Beyond the mentioned activities, many coun-
tries worldwide refer their food policies to national guideline
approaches. Furthermore, the UN Development Program is
promoting the Sustainable Development Goals, which is a
universal call to action to end poverty, protect the planet,
and ensure that all people enjoy peace and prosperity; it
also includes gender issues (11, 12).
Over the years, nutritional guidelines have been devel-
oped with the aid of expert panels and systematic reviews
and have been distributed for expert and community com-
ment in an effort to link scholarship and policy (13). Al-
though the evidence basis in nutrition has increased in
volume in recent years, its robustness is still often uncertain,
and the derived nutritional guidelines may not have been
significantly improved. This situation leads not only to lim-
itations of interpretation that are not always clear-cut in the
guidelines themselves but also to criticism of the validity of
the process by which the guidelines were developed. Thus,
there is a need to move forward to improve the quality
and efficacy of nutritional guidelines, following interna-
tional standards (14) and a process that requires valida-
tion with regard to various pivotal elements, such as full
transparency in scientific data collection and analysis,
documented evidence-based justification, grading, and eval-
uation of effectiveness. Interaction with policy makers and
authoritative communication among all stakeholders, in-
cluding citizens, is desirable (15), but one wants to guard
also against biases that various stakeholders may have. Of
particular relevance to the public is the need to understand
the individual- and sex-related features of proposed nutri-
tional recommendations. Real-life studies should also be en-
couraged to overcome the possible bias between population
Perspective articles allow authors to take a position on a topic of current major importance or
controversy in the field of nutrition. As such, these articles could include statements based on
author opinions or point of view. Opinions expressed in Perspective articles are those of the
author and are not attributable to the funder(s) or the sponsor(s) or the publisher, Editor, or
Editorial Board of Advances in Nutrition. Individuals with different positions on the topic of a
Perspective are invited to submit their comments in the form of a Perspectives article or in a
Letter to the Editor. This is a free access article, distributed under terms (http://www.nutrition.
org/publications/guidelines-and-policies/license/) that permit unrestricted noncommercial use,
distribution, and reproduction in any medium, provided the original work is properly cited.
This article emerged from a meeting held in Venice, Italy, on 1 July 2016, with the participation
of a selected panel of experts and was promoted and organized by the Giovanni Lorenzini
Medical Science Foundation (Houston, TX, and Milan, Italy).
Author disclosures: PM, DMB, SP, CA, AA, FB, RC, EF, LF, RAG, RG, GHG, JPAI, ASJ, DMK, MM, BM,
AM, CJP, GR, HJS, RS, NZ, and AP, no conflicts of interest.
Address correspondence to PM (e-mail: paolo.magni@unimi.it) or AP (e-mail: andrea.peracino@
lorenzinifoundation.org).
Abbreviations used: DRV, dietary reference value; GRADE, The Grading of Recommendations Assessment,
Development and Evaluation; NCD, noncommunicable disease; RCT, randomized clinical trial.
Nutritional guidelines for sustainable health policies 533
groups selected in trials and actual population composition
and profile.
Therefore, the agenda for the development of nutritional
guidelines should advance through evaluation of methodol-
ogy in nutrition research, evidence hierarchy in nutrition,
and strategies for appropriate vetting and reporting aimed
at empowering recommendations, including specific impli-
cations for the future such as personalized nutrition in
health promotion (Text Box 1).
Current and Developing Status of Knowledge
Methodology in nutrition research
Historically, nutritional guidelines have been based on all
the evidence available, including not only human clinical
studies but also data available from experimental animal
work and physiological studies. This evidence also includes
information from population-based epidemiologic studies
that have identified food patterns, nutrient intakes, and life-
styles associated with health promotion or with increased
risk or progression of NCDs (4, 16). Moreover, additional
insights have been generated by some randomized clinical
trials (RCTs) and innovative new study designs, such as
Mendelian Randomization and environment-wide associa-
tion studies.
To evaluate the evidence useful for both population
and individual decisions requires that $3 steps be taken
into consideration: 1) what are the uncertainty limits of
the available evidence, 2) how can we improve credibility
by reducing uncertainty and variability, and 3) does the in-
creased evidence credibility lead to improved usefulness
in dietary guidance (17)? Interestingly, although 96% of the
biomedical literature claims significant, positive results,
the validity of these claims is often questionable (18).
The reasons are multiple and generally well known al-
though not widely appreciated or acknowledged. Among
these are the problems of nonrandomized designs, post
hoc data “cherry-picking”and “Phacking”to support de-
sired hypotheses, lack of a priori data analysis plans or
post hoc transparency in data analyses, selective reporting
of results, lack of study registration on public databases,
lack of a replication culture, and limited data sharing (19).
Moreover, in some instances, publication quality in the
field of nutrition shows a lack of consistency, especially
for observational evidence, in which analytical approaches
to newer data suggest that effects of soft outcomes (e.g., sur-
rogate endpoints) may well be overestimated (20). Conclu-
sions drawn from these newer insights support the very
high rate of refutation observed in the most-cited claims
of observational studies that were not validated in RCTs
(21, 22). Nonetheless, among the scientific community,
an inherent resistance to refutation is frequently observed
so that unreliable and contradictory papers often have long
lives as supporting references (23). Interestingly, it has re-
cently been demonstrated that 68.5% of studies reporting
routinely collected data did so for research questions al-
ready addressed by RCTs (24), suggesting that observa-
tional data may not be as informative as often claimed.
Most likely, some inherent obstacles must be overcome
in making sure that expert committees review draft guide-
lines and evidence provided in the format of a consensus
conference, with the participation of all stakeholders.
Moreover, because a substantial part of the evidence in nu-
trition is based on observational data, credibility on the
causal pathway is often questionable (25), which is a prob-
lem compounded by weak conclusions drawn from diverse
subgroups, stratified analyses, and data dredging in the
absence of any preregistration. Conclusions drawn from
nutrition research studies are sometimes based on statis-
tically significant but small or tiny effect sizes (26). Tiny
effects may still be credible, but they are highly susceptible
to even minimal bias. Although larger-scale data and new
measurement platforms offer novel opportunities, they
also provide the potential for even higher error and mis-
leading claims.
RCTs are an important pillar in evidence-based medicine
and require improvement when done in the nutrition field.
There is a need for improved transparency and improved,
quality evidence of nonregulated interventions, especially
compared with the rate of registration and publication of
nondrug trials (27), because a large number of nutritional
trials have never been registered (19).
Additionally, RCT designs in nutrition require attention
to pragmatic issues to reduce the user burden of dietary as-
sessment and long-term compliance, personnel and funding
mechanisms to accommodate large sample sizes, and focus
on important, patient-relevant outcomes (28). Additional
strategies to improve nutritional research include the analy-
sis of subgroups with stratified effects, pooling studies, and
TEXT BOX 1 NUTRITIONAL GUIDELINES: A
HISTORICAL PERSPECTIVE
Appropriate nutrition is a powerful factor prevent-
ing multiple age-related chronic diseases and pro-
moting human health.
Excessive unbalanced—but also insufficient—
nutrition contributes to disease development.
Current nutritional guidelines based on observa-
tional epidemiological studies and some clinical
trials have provided guidance to health profes-
sionals, policy makers, and the public for decades.
Nutritional recommendations and guidelines are
most effective when implemented within appropri-
ate geographic, cultural, ethnic, and socioeconomic
contexts without forgetting age and sex differences.
Nutritional guidelines should evolve through the
incorporation of insights into the methodology of
guideline methods, better evidence, adherence to
grading data within established hierarchy of avail-
able evidence, avoiding conflicts of interest and
aiming at a constructive coalition among all
stakeholders.
534 Magni et al.
the use of biomarkers when available, although the effect
could be diluted in the case of large RCTs (19, 29, 30).
A relevant observation when evaluating the health im-
pact of nutrition is that people actually eat intact foods
and not isolated nutrients. Most generalized nutritional
guidelines are couched in terms of daily nutrient intakes.
Although this is clearly important, it appears obvious that
bioavailability of nutrients incorporated into a food matrix
may be affected by their effects on digestion and absorp-
tion, which are also modulated by the matrix effect or by
the actions of the gut microbiota. Moreover, the composi-
tion of many foods is not completely known, food compo-
sition tables are often incomplete or out of date, and some
compounds are impossible to measure or are unknown.
Not surprisingly, even for the most extensively studied ques-
tions, discrepancies may occur when nutrients or foods are
evaluated (e.g., substitution of saturated fat with polyunsat-
urated fat in substitution studies compared with assessing
the association between saturated fat intake in dairy pro-
ducts and health outcomes). These factors add to the uncer-
tainty of conclusions about nutrients drawn from studies
using foods (Text Box 2).
Taking advantage of big data. In recent decades, major
improvements in measurement capacity and computerized
data analysis have led to fast high-throughput analyses
at much lower costs. These have allowed different and
heterogeneous sources of data to be integrated in novel
ways that provide reliable new insights. Big data may
be derived from epidemiological cohorts or related
biorepositories with the power to elucidate millions of
genetic variants and thousands of environmental and
nutritional factors in their study participants. Although
this is crucial, it is rather difficult to study and understand
because it is inherently individual, with several variables
based on genome and the individual interaction with the
surrounding environment (starting from parents’
experience and fetal interferences). Electronic medical
records of millions of patients, containing clinical,
pharmacological, and laboratory data, are currently being
repurposed for research and discovery. These research
practices generate new concepts for discovery, which in
turn raise new questions concerning what to measure and
how in health research, whether and how to use and
interpret these big data for discovery, and what roles they
will eventually play in developing guidelines (31). Human
health recommendations may benefit from large-scale data
when noise is minimized, because false alarms due to
confounding variables or other biases are possible even
with very-large-scale studies (32–34).
Enhancement of the validity of guideline precision may
emerge from big data analysis if accompanied by systematic
testing, addressing multiplicity (29, 35–38), and replicating
experiments, as well as considering the vibration of effects
(shifts in the effect-size distribution due to selected adjust-
ments or other analytical choices) in shaping the empirical
distribution of effect sizes due to model choice (20). Further-
more, nutritional exposures and behavior are highly corre-
lated with one another (33, 34, 39, 40), posing challenges in
evaluating possible associations. Therefore, it is an imperative,
along with systematically testing associations with clinical
outcomes, to estimate how large (or small) an association is
with respect to all other possible correlations (33).
There is also a need to assess associations between not
just single nutritional factors and outcomes but an entire
system of correlated nutritional factors and outcomes to ac-
curately capture the complex and correlated dietary behav-
ior of humans. There is the further need to document
analytical approaches and provide both accessible analytical
tools and computer infrastructure to enable reproducible re-
search. There are various aspects of reproducible research,
ranging from the ability to recompute data analytic results
given an observed dataset and knowledge of the pipeline
(41) to reproducibility across different datasets (reproduci-
bility of results) and reproducibility of inferences from the
same datasets and analyses (42) (Text Box 3).
Toward personalized nutrition. When approaching novel
methodologies in nutrition research, it is important to focus
on the associations among individual genotypes and pheno-
types, aiming at personalized nutritional strategies that will
effectively promote the health of individuals. Ideally, the
complex gene-gene and gene-environment interactions and
epigenetic modulation should be taken into consideration
when assessing nutritional and other environmental links
with NCDs such as obesity, dyslipidemia, cardiovascular
diseases, and cancer (43–46).
In the context of the current population epidemics of
metabolic diseases, related to the interaction between the ge-
nome and nutritional changes and environmental factors,
there are well-appreciated differences in how individuals
within the population respond to the same environmental
TEXT BOX 2 METHODOLOGY IN NUTRITION
RESEARCH
Most evidence on nutrition is based on observa-
tional data.
Clinical outcomes with nominally statistically sig-
nificant results are often arguable and of debatable
clinical significance.
Randomized trials can confirm causality but have
inherent design constraints for nutritional inter-
ventions.
Most secondary subgroup analyses and stratified ef-
fects are weak at best.
Large-scale data and new measurement platforms
offer improved opportunities but have the potential
for even higher error rates.
Clinical nutrition research designs and implementa-
tion studies require reforms focused on improved
credibility and utility.
Nutritional guidelines for sustainable health policies 535
stimuli. For example, people have largely different glucose
responses to the same food (47), and recent data suggest
that integrating individual information into a multidimen-
sional algorithm that predicts specific responses to food
may allow definition of personalized diets (48). It has been
proposed that one should individualize the diet according
to personal variables, including sex, age, and microbiome
profile (49). Major determinants of the variability in an in-
dividual’s glucose response to food may include food quality,
intake frequency, and lifestyle, including physical activity,
circulating metabolic biomarkers, and the gut microbiota.
Data based on continuous postprandial glucose measure-
ments have demonstrated that whether a food is nominally
good or bad, regarding its effect on the postprandial glyce-
mic response, is largely dependent on the individual con-
suming the specific food in relation to his or her personalized
variables (48). Thus, individual people can have very differ-
ent responses to the same food (Fig. 1). For instance, in re-
sponse to white bread consumption, some people have the
expected postprandial glucose spikes, whereas others do
not (47, 50) (Fig. 2). Moreover, dietary interventions target-
ing postmeal glucose responses induce consistent changes
in the gut microbiota, with relevant variations according
to the type of diet (high-glucose response compared with low-
glucose response diets) (51). Therefore, diets designed to
maintain normal postprandial blood glucose concentrations
must be personally tailored. If so, population-based
guidelines may have limited generalizability when the
prevalence of specific genetic, lifestyle, and other factors
able to have a large impact in modifying the effect of
the diet consumed is large in the population addressed.
In any case, predictive diets for individuals are quite com-
plex, and population-based clinical trials that test the
value of the intervention of personalized recommenda-
tions on health outcomes, including time to cardiovascu-
lar disease, cancer, and death, must occur. To date, few
observational investigations have shown the utility of
integration of high-dimension information, including
(prevalent) genetic variants, microbiome, and environ-
mental exposures. These studies, already partially ongo-
ing, will hopefully demonstrate feasibility for large-scale
clinical trials for personalized interventions. Therefore,
at this stage such predictors can assist in devising a dietary
plan but cannot replace the general nutrition recommenda-
tions (Text Box 4).
The implementation of such novel approaches (e.g., big-
data analysis, personalized nutrition algorithms) needs to be
evaluated against conclusions based on traditional methods.
Moreover, although the inclusion of these methods into
new guidelines will surely improve the knowledge base,
TEXT BOX 3 TAKING ADVANTAGE OF BIG DATA
Big data analysis may provide answers based on a multitude of new ways to interrogate datasets and uncover insights
into generating improved guidelines.
Big data may be derived from large epidemiological cohorts and/or related biorepositories and have the potential
power to elucidate relations among millions of genetic variants and thousands of environmental and nutritional
factors, but their utility is still to be proven.
The huge number of analytic scenarios can multiply the analytical challenges and magnify potential biases.
To enhance the validity of conclusions from big data there is a need for:
·systematic testing procedures to address multiple hypotheses testing and results replication to enhance the validity
of the results
·consideration of the dense correlative nature of both clinical outcomes and nutritional factors
·modeling scenarios that are fully detailed and explicitly transparent
·increased education for literacy in understanding and interpreting information at the big-data level
Human health could benefit from large-scale data only if large-scale bias is likewise minimized.
FIGURE 1 PPGRs to identical
standardized meals can be highly variable
among different people. (A) Population
responses to standardized meals. Kernel
density estimation histogram of PPGRs of
healthy individuals (n= 800) to 4 selected
meals. (B) Four individual responses to bread,
showing the high interpersonal variability in
PPGRs to bread across participants. iAUC,
incremental AUC; PPGR, postprandial glucose
response. Reprinted from reference 48 with
permission from Elsevier.
536 Magni et al.
it remains to be shown whether the problems these methods
create in more complex interpretations will lead to de-
monstrable improvements in better health and disease
outcome in the long-term and in various sociocultural and
economic conditions.
Evidence hierarchy in science with a focus on nutrition
The evidence hierarchy, built on the principles of the scien-
tific method, is a construct widely shared among all sciences.
Nutrition, as a science, must comply with and be judged by
the same scientific principles as far as the grading the quality
of its evidence is concerned. In practice, difficulties associ-
ated with designing and conducting human studies using
real foods may limit compliance with these principles at
the highest levels of the evidence hierarchy. Nonetheless,
limitations of this kind do not serve as reasons to elevate
the level of evidence obtained but rather to limit the cer-
tainty of conclusions drawn from the evidence available.
Moreover, within this context, properly grading the caliber
of available evidence is pivotal because trustworthy guide-
lines must systematically weigh both the amount of evidence
and its quality. The Grading of Recommendations Assess-
ment, Development and Evaluation (GRADE) approach,
adopted by >100 organizations worldwide, has become the
standard for rating the quality of evidence (52). The GRADE
Working Group (53) has provided tools that indicate the
reasons for a recommendation (direction, strength, and cer-
tainty) and allow adoption, adaptation, and new develop-
ment of recommendations globally. Key criteria include
the following: how big is the problem locally; how direct
is the evidence; how does it impact on resources, equity, ac-
ceptability, and feasibility (54, 55).
In the GRADE system, randomized trials are initially
graded as high-quality evidence, but their grade can be rated
down to moderate or low/very low based on limitations in 5
categories: risk of bias, inconsistency, indirectness, impreci-
sion, and publication bias (54, 56). On the other hand, ob-
servational studies are initially graded as low-quality
evidence but can be rated up to a higher grade, primarily
on the basis of large effect sizes. GRADE also provides guid-
ance for grading recommendations as strong or weak. A
panel makes strong recommendations when the net benefits
clearly favor one option. A panel makes weak recommenda-
tions in the face of uncertainty, either because the evidence
is of low or very-low quality or because the desirable and
undesirable consequences (54, 57) are closely balanced. In
making decisions regarding direction and strength of recom-
mendations, guideline panels should always consider the
magnitude of the desirable and undesirable consequences,
the certainty of the evidence regarding those consequences,
TEXT BOX 4 TOWARD PERSONALIZED NUTRITION
People have highly variable postmeal glucose responses to identical meals.
Following current dietary guidelines may result in high glycemic responses in some subjects, accelerating metabolic
disease development, which the guidelines were intended to prevent.
An individual’s microbiome is a driver of interpersonal variability in postmeal responses.
Integrating personal parameters and microbiome features into an algorithm may allow more accurate predictions of
personalized postmeal glucose response to defined meals.
Personalized diets normalize postmeal glucose responses and increase compliance.
A personalized nutritional approach based on validated algorithms may be relevant for effectively promoting indi-
vidual health.
FIGURE 2 PPGRs to real-life meals can
be highly variable among different
people. (A) IQRs (10th–90th percentiles)
of the PPGRs of healthy individuals
(n= 800) to different meals along with
the amounts of carbohydrates consumed
(green; means 6SDs). (B) An example of
inverse PPGRs to a set of 2 isocaloric real-
life meals. iAUC, incremental AUC; PPGR,
postprandial glucose response. Reprinted
from reference 48 with permission from
Elsevier.
Nutritional guidelines for sustainable health policies 537
and the values and preferences of the population to
whom the recommendation applies, the last being crucial
in ensuring compliance. Panels may also consider re-
source use, acceptability, feasibility, and equity in making
their recommendations. If guidelines are not adapted to
real life, it is unlikely they will be used.
Evidence in nutrition: strategies for appropriate
vetting and reporting, aimed at empowering
recommendations
To produce trustworthy and optimal guidelines mandates a
well-constructed panel of discussants, including scientific
experts in the specific nutritional areas, methodologists in-
cluding statisticians, practicing clinicians and patients, and
policy makers, needs to become involved when necessary
if medical and clinical care guidelines are under consider-
ation. Expert translators are also of paramount importance
when considering the wide practical use of these guidelines
and the subsequent impact on clinical practice as well as on
the population.
Standards for trustworthy guidelines are well established
(e.g., Institute of Medicine recommendations) (58). Several
authoritative international organizations (WHO, Institute
of Medicine, the Guideline International Network, and the
GRADE Working Group) agree on the key principles for
the development of high-quality guidelines (59). Interna-
tional standards exist that will also ensure trustworthiness
for nutritional guidelines based on progression to higher
levels as bias in the quality of evidence declines (60).
Recommendations should be based on an explicit and trans-
parent process that maximizes the use of the highest-quality
graded evidence; minimizes distortions, biases, and conflicts
of interest; provides a clear explanation of the logical relations
between alternative care options and health outcomes; and pro-
vides ratings of both the quality of evidence and the strength of
recommendations (61). More realistically, to provide high-
quality systematic reviews of today’s expansive literature will re-
quire more than the voluntary spare time of already-pressed
scientists. Governments should be obliged to appropriate
the funds necessary for producing timely, high-quality, and
evidence-based dietary reference intakes (62).
Because foods are so intimately related to lifestyles and
food cultures in humans, instruments to assess the quality
of life in relation to nutrition and nutrition-related lifestyle
changes are also needed (63). Moreover, there is a need to
assess sustainability, (e.g., environmental impact or eco-
nomic impact) with regard to future recommendations. As
it is obviously appropriate, trustworthy guidelines should
be reconsidered and revised when important, new evidence
warrants modifications of recommendations.
The presence of conflicts of interest can lead to biased
and potentially incorrect recommendations (64). Interna-
tional principles for disclosure of interests and management
of conflicts in guidelines have been developed to address this
issue. However, declaration of conflict alone seems a poor
strategy overall. More acceptable options for managing con-
flicts are to exclude altogether those with major conflicts or
to allow input by conflicted individuals to participate in the
discussion but excluding them from the decision-making
process. Several tools for the development of trustworthy
guidelines are available. In particular, a comprehensive check-
list of items and related resources can help guideline de-
velopers in their enterprise (14) (Fig. 3). Additional tools
include the Essential Reporting Items for Practice Guidelines
in Healthcare (65) statement, which helps those producing
guidelines report them properly and in a certain format
for the lay audience (Text Box 5).
Implications for the future
Based on the concepts developed above, one might envision
a series of implications for the future aimed at improving
nutritional guidelines and effectively applying them to peo-
ple worldwide. These could also consider personalized nu-
trition, ethnic and geographic preferences, more effective
translation of nutrition guidelines for the public, and pro-
motion of sustainability and cooperation among all nutrit-
ion stakeholders.
Among them, the food industry plays a central role when
food industry interventions in industrial food production
are taken into consideration. Very rarely it is possible to ac-
cess foods that have not been treated industrially or have not
undergone a treatment (i.e., pesticide treatment or genetic
manipulation) at any level of the production chain. How
is it possible to manage this artificial input into the food
chain? What is the impact on individuals?
Ethnic and geographic issues. Lessons learned from em-
ploying the experimental principles discussed immediately
above might also be extended to individualizing guidelines
based on ethnic and national food preferences. The selection
of specific local foods included in a diet represents a critical
issue in the translation of guidelines as well as likely health
promotion outcomes, because dietary compliance is inti-
mately related to local and ethnic food preferences. It is now
also well appreciated that nutrient-based recommendations
should be focused on foods as the source of nutrients.
Moreover, recommendations should not be based on indirect
evidence, such as a prediction from nutrient composition
listed in the label, but on solid scientific evidence, accumu-
lated from actual subject responses to the particular foods
themselves (48). These refinements can lead to improvement
in dietary approaches based on traditional or regional habits
that have already been validated and translated into
recommendations for health promotion, e.g., starting with
the Mediterranean Diet (66) and translating it into
corresponding regional geographic variants, including the
recently developed New Nordic Diet in Denmark (67, 68).
Effectively translating nutritional guidelines for the
public. A particularly relevant issue in effective guideline de-
velopment is how to properly communicate the information
to the general public in the current era of widespread, largely
uncontrolled dissemination of information via an almost
limitless variety of media outlets. The revolution in online
538 Magni et al.
media has drastically altered the pressure on journalists to
reach readers, changing the ways that complicated stories,
such as nutritional topics, are written and presented. Indeed,
nutritional issues, which are often intrinsically complex,
are difficult to report comprehensively and, even when truly
balanced, frequently fail online. Because ambiguity does not
sell, there is pressure to oversimplify.
The traditional fact-checking stringency of legitimate
print media outlets has largely been bypassed by many of
the newer electronic “information”sites online. The result
has been an abundance of often-conflicting information
that both generates public confusion and produces issues
of credibility (69, 70). Problems often begin with the reli-
ability of the media translation of the original research
reports. Recently, 18 kinds of media spin were identified,
and $1 spin was found in 88% of media research reports:
25% failed to report adverse events mentioned in the scien-
tific article, 49% claimed a causal effect despite a non-
randomized study design, and 21% extrapolated a
beneficial effect from an animal study to humans (71). For
many people, the media are the main provider of the infor-
mation that individuals use to make decisions about their
health. Thus inaccurate, incomplete, or imprecise reporting
of the research reports themselves is a major impediment in
conveying solid nutrition evidence from scientists to citi-
zens. However, the scientists themselves are not blameless
in this context. Lazarus et al. (72) reported finding $1 exam-
ple of spin in 84% of scientific reports studied, most
TEXT BOX 5 EVIDENCE IN NUTRITION: STRATEGIES FOR APPROPRIATE VETTING AND
REPORTING, AIMED AT EMPOWERING RECOMMENDATIONS
Trustworthy guidelines should:
·be based on a systematic review of the existing evidence
·be developed by a knowledgeable, multidisciplinary panel of experts and representatives from key affected groups
·consider important patient subgroups and patient preferences as appropriate
·be based on an explicit and transparent process that minimizes distortions, biases, and conflicts of interest
·provide a clear explanation of the logical relations between alternative care options and health outcomes
·provide ratings of the quality of the evidence and strength of the recommendations
·be reconsidered and revised as appropriate when important new evidence arises
FIGURE 3 Diagram of the guideline development process. The steps and involvement of various members of the guideline
development group are interrelated and not necessarily sequential. The guideline panel and supporting groups work collaboratively,
informed through consumer and stakeholder involvement, and report to an oversight committee or board overseeing the process.
Considerations for organization, planning, and training encompass the entire guideline development project and steps, such as
documenting the methodology used, the decisions made, and considering conflicts of interest, occur throughout the process. PICO,
patient/problem, intervention, comparison, outcome. Reprinted from reference 14 with permission from Access Copyright.
Nutritional guidelines for sustainable health policies 539
commonly the improper implication of causality and a high
degree of overselling the research findings in approximately
half of the publication abstracts. Furthermore, although peer
reviewers identified an example of spin in about half of the
research manuscripts they reviewed, resulting in author re-
moval of two-thirds of these items, the peer reviewers failed
to identify spin in three-quarters of the abstracts of the man-
uscripts reviewed (73). Surprisingly, for 15% of the reviewed
articles, the referees themselves suggested adding some spin,
and in 9% of the reviewed articles the authors themselves
added additional spin (73).
Promoting sustainability and cooperation among all
nutrition stakeholders. For guidelines to be maximally ef-
fective there is a need for cooperation among all nutrition
stakeholders (individuals, citizens of any age and sex, scien-
tists, clinicians, policy makers, the food industry, the com-
munications industry, etc.).
Furthermore, reshaping food systems around sustainable
diets is one of the world’s biggest challenges for the 21st cen-
tury. Sustainability is a complex concept, and sustainable de-
velopment was first introduced in Europe in the 1980s. In
the ensuing years, there has been a growing concern for sus-
tainability, including the food and nutrition field, which has
gained the attention of researchers, academics, and practi-
tioners and has become a focus for governments, private or-
ganizations, and other stakeholders (74). Countries vary in
their conceptual understanding of sustainability and in its
practical implementation determined by their own health
agencies in the complex local policy environment. Neverthe-
less, the nature of global interconnectivity today poses
sustainability problems that must be solved at the interna-
tional level. Different approaches (evidence briefs, policy
dialogues, and benchmarking) mandate international infor-
mation and debate on policymaking.
Conclusions
In this article, the most important issues relevant to improv-
ing nutritional guidelines are discussed and the proposed
concepts and actions are the result of the merged efforts
of a qualified panel of experts in the related areas. The fol-
lowing conclusions of such joint work are proposed.
Nutritional guidelines: a historical perspective
There is a need to move forward to improve the quality and
efficacy of nutritional guidelines, starting from an unbiased
assessment of the currently consolidated information. The
future agenda should advance through evaluation of newly
available methodology in nutrition research to personalize
guideline recommendations, properly grade the evidence
quality, adhere to evidence hierarchy in nutrition, and en-
hance strategies for appropriate vetting and transparent
reporting to solidify the recommendations for health pro-
motion. The final goal is to build a constructive coalition
among scientists, policy makers, and communications pro-
fessionals to develop and implement sustainable health and
nutritional policies. Constructive integration that facilitates
harmonization among institutions is necessary for the for-
mulation of nutritional recommendations, guidelines, and
policies, because they must be implemented in different geo-
graphical, cultural, ethnic, and socioeconomic contexts to
produce a relevant public health impact.
Methodology in nutrition research
Nutritional trials require an improvement in the design, col-
lection, analysis, transparency, and quality of evidence at all
levels of research. To improve nutritional research, it is im-
portant to increase study registration in public databases and
to include predeclaration of endpoints and analytical ap-
proaches and open access for data. Nutritional guidelines
need to be periodically reexamined and revised accordingly
as new data become available. Moreover, there is a need to
ensure that dietary essential nutrient and food recommen-
dations apply to all subjects present in the society. Inno-
vative scientific research generates new concepts for
discovery, raising new questions concerning what and how
to use the novel findings. The pervasive expansion of big
data in the health research field has opened new horizons
for their use for discovery or to develop guidelines (31), gen-
erating many challenges, especially in the context of causal
pathway interpretation. Human health could benefit from
large-scale data analysis, if large-scale noise is minimized
and confounding variables or other biases are evaluated
(32–34). Proper use of big data may help in designing nutri-
tional guidelines for individual intervention and improve
their effectiveness and relevance over the limitations of the
generalized approach available today (48).
Evidence hierarchy in science, with a focus on
nutrition
The principles of the scientific method apply to nutrition as
they do to all disciplines classified as scientific. Trustworthy
guidelines should be based on systematic summaries of the
best available, properly graded evidence addressing each rec-
ommendation that is part of the guidelines. In making deci-
sions regarding direction and strength of recommendations,
guideline panels should consider the totality of evidence and
the magnitude of the desirable and undesirable health
effects, the domains of evidence certainty or uncertainty
both with respect to the desired goals and potential undesir-
able effects. To support sustainability, guideline panels
should also consider all desirable and undesirable conse-
quences, including resource use, environmental and ecolog-
ical consequences, acceptability, feasibility, and equity, in
making their recommendations (54–57, 75, 76).
Evidence in nutrition: strategies for appropriate
vetting and reporting, aimed at empowering
recommendations
To produce trustworthy and optimal guidelines, it is manda-
tory to have a well-constructed, well-balanced panel of discus-
sants, including experts in specific areas, methodologists,
and practicing clinicians and patients if medical and clini-
cal care guidelines are under consideration (77). Guidelines
540 Magni et al.
TEXT BOX 6 COMMON ACCEPTABLE DEFINITIONS
Biomarkers
·A biomarker is a natural molecule, gene, or functional characteristic by which a specific physiological or patho-
logical process can be identified. They are commonly used to diagnose conditions and to assess how advanced an
individual’s illness is.
Conflict of interest
·An interest that may affect an individual’s ability to impartially assess the evidence or provide a perspective on a
particular topic. Conflicts can be financial, where the person is in direct or indirect receipt of financial support, or
intellectual, where the person may have a reputation built on a particular stance on an issue.
Diet
·Diet is the sum of food and drink consumed by an individual and often implies its quality, composition, and ef-
fects on health.
Dietary guidelines
·Dietary guidelines translate nutritional guidelines into food intake recommendations by using nontechnical lan-
guage, enabling individual consumers to compose their daily diet in a way that provides the appropriate nutrition.
Feasibility/implementation
·Feasibility and implementation consider how health policy will be implemented, including assessing and mitigat-
ing any individual, social, cultural, economic, and practical barriers to implementation; for example, not recom-
mending food sources of nutrition that the majority of the population may not be able to access because of
financial constraints or availability.
Food
·Food consists of essential body nutrients, such as carbohydrates, fats, proteins, vitamins, or minerals, which are
ingested and assimilated by an individual to produce energy, stimulate growth, and maintain life.
Guidelines
·Guidelines are a series of recommendations on a particular topic (e.g., health condition or aspect of health, such
as nutrition), developed by a multidisciplinary panel based on an independent systematic review of the best avail-
able evidence. Guideline panels can include health professionals and academics specializing in that area, as well as
representatives of other groups such as the general public, the policy makers, and the industry.
Nutrition
·Nutrition interprets the interaction of nutrients and other substances in food in relation to the linked metabolic
effects within the body. It includes food intake, absorption, assimilation, metabolism, and excretion.
Nutritional guidelines
·Nutritional guidelines focus on the quantities of individual nutrients and quality and quantity of whole foods that
people should consume to achieve a healthy nutritional state. Nutritional guidelines may include estimates such as
DRVs, reference intake, and daily intake. These guidelines usually apply to the entire healthy population by using
broad groups, such as different age ranges, but can also be tailored to more focused population groups. The gen-
eral public often come into contact with these when examining food packaging, which may have DRVs on the
front, etc.
Nutritional status
·Nutritional status includes the condition of the body, influenced by the actions and interactions generated from
the food intake through metabolism and absorption in the gut (exercised by microbiome, genetic, and food com-
ponent interactions), and the consequent metabolism and handling within the body (due to genetic and organ—
not only liver and kidney—functions) toward to the nutritional status differences on health effects.
Policy makers
·Policy makers are professionals working within local and national government who are responsible for translating
research findings into actionable health policy to promote health in their population, for example, creating food-
based guidelines based on nutritional guidelines, the best available evidence, and stakeholder input.
RCT
·An RCT is a clinical study with a specific design aimed to reduce bias when testing a new treatment. Subjects par-
ticipating in the trial are randomly allocated to either the group receiving the treatment under investigation or to a
group receiving standard treatment (or placebo treatment) as the control.
Substitution effect
·When advised to eat less of one nutrient (e.g., carbohydrate) or individual food, the public will substitute that item with
another. Substitution advice should be provided to ensure healthy substitutions that do not have unintended harms.
continued
Nutritional guidelines for sustainable health policies 541
should be based on an explicit and transparent process
that minimizes distortions, biases, and conflicts of interest;
provides a clear explanation of the logical relations between
alternative care options and health outcomes; and provides
ratings of the quality of the evidence and the strength of
the recommendations (61). The GRADE recommendation
classifies systematic reviews of RCTs with an initial score
of high and classifies systematic reviews of cohort studies
with a score of low. As the studies are evaluated, the indi-
vidual RCTs can be rated lower and the individual cohort
studies can be rated higher depending on prespecified lim-
itations of the former and the effect sizes of the latter. To
complement this methodologic gap, improved measures
and tools that also take into account nutrition research–
specific re quirements (e.g., d ietar y assessment methods
and their validation or funding bias) for assessing the meta-
evidence (quality of the evidence of the meta-analyses) need
to be developed. Recently, an attempt to adapt the GRADE
approach to specifically address peculiarities of nutrition re-
search has been proposed [NutriGRADE from Schwingshackl
et al. (78)]. For optimal implementation, this approach is best
conducted with interaction with the GRADE working group,
which we encourage and welcome strongly.
Implications for the future
Novel approaches may lead to the development of nutri-
tional, exercise, and pharmacological interventions targeting
the metabolic and molecular causes of human ageing and
health promotion, inhibiting pro-aging pathways that con-
trol the accumulation of molecular damage in multiple tis-
sues or minimizing the risks of diseases that contribute to
or accelerate those pathways (48, 79). Accurate predictions
of the individual metabolic response integrating different
approaches may lead to personalized nutrition able to com-
bine health promotion and the possible use of locally avail-
able foods (48). The transfer of this information to novel
nutritional guidelines to improve the effectiveness of current
generalized guidelines, however, still appears complex.
Although most guidelines have historically focused on
the essential nutrient components of foods, future nu-
tritional recommendations must evaluate evidence derived
from ingestion of whole foods or diets.
A crucial issue is the communication of the fundamental
nutritional information in the current electronic media
environment, where traditional factual evidence verification
is often lacking. Improved communications and effectiveness
require cooperation among all nutrition stakeholders (the lay
public, basic scientists, practicing clinicians, policy makers, in-
dustry, education, communication, etc.). The specificissueof
sustainability requires the additional communication among
governments, nations, and international regulatory agencies.
In conclusion, there is a strong and urgent need to
develop a successful commitment among all the stakeholders
to define novel approaches to the management of the health
value of nutrition at the individual and population levels.
Moving forward requires adherence to well-established prin-
ciples of evidence evaluation and the identification of effective
tools to obtain better-quality evidence. Much remains to be
done in the near future. A starting step is to identify common
acceptable definitions (Text Box 6).
Acknowledgments
Panel of experts invited to the meeting in Venice, Italy—
Carlo Agostoni: Pediatric Medium Intensity Care Unit, De-
partment of Clinical Sciences and Community Health, Uni-
versità degli Studi di Milano, Fondazione IRCCS Ca’Granda
Ospedale Maggiore Policlinico, Milan, Italy; Arne Astrup:
Department of Nutrition, Exercise and Sports, University
of Copenhagen, Denmark; Dennis M Bier: Children’sNu-
trition Research Center, Baylor College of Medicine, Houston,
TX; Furio Brighenti: Department of Food Sciences, University
of Parma, Italy; Paolo Cavallo Perin: Department of Medical
Sciences, University of Turin, Italy; Elena Colombo: Giovanni
Lorenzini Medical Science Foundation, Milan, Italy; Rob
Cook: Bazian, Economist Intelligence Unit Healthcare,
London, United Kingdom; Lorenzo Maria Donini: Food Sci-
ence and Human Nutrition Research Unit, Sapienza Univer-
sity, Rome, Italy; Christopher Emsden: Policy Sonar, Rome,
Italy; Emanuela Folco: Giovanni Lorenzini Medical Science
Foundation, Milan, Italy, and Houston, TX; Luigi Fontana:
Department of Clinical and Experimental Sciences, University
of Brescia, Italy, and Department of Medicine, Washington
University, St. Louis, MO; Robert A. Gibson: School of
Agriculture, Food and Wine, FOODplus Research Centre,
University of Adelaide, Australia; Maria Giovanna Graziani:
Gastroenterology and Digestive Endoscopy Unit, San
Giovanni Addolorata Hospital, Rome, Italy; Ranieri Guerra,
Department of Preventive Health, Ministry of Health,
continued from previous page
Surrogate disease biomarker
·In some research areas, it may be challenging to conduct studies that are sufficiently long term to wait for disease
outcomes (such as heart attack) or answers that may be required in the meantime. In such cases, biomarkers of
that disease (e.g., blood pressure) can be measured to predict the likely risk of later developing the disease. How-
ever, these results indicate a possible risk rather than providing direct causal proof.
Weak/qualified/conditional recommendations
·Where evidence is limited in terms of its quality or quantity, this affects the level of certainty in any conclusions
based on that evidence. Describing recommendations as weak, qualified, or conditional communicates this level
of uncertainty.
542 Magni et al.
Rome, Italy; Gordon H Guyatt: Department of Clinical
Epidemiology and Biostatistics, McMaster University,
Hamilton, ON, Canada; John PA Ioannidis: C.F. Rehnborg
Chair in Disease Prevention, Department of Health Policy
and Research, Stanford University, Stanford, CA; Ann
S. Jackson: Giovanni Lorenzini Medical Foundation, Houston,
TX;DavidM.Klurfeld:HumanNutritionProgram,USDA
Agricultural Research Service, Beltsville, MD; Paolo Magni:
Department of Pharmacological and Biomolecular Sciences,
Università degli Studi di Milano, Milan, Italy; Carlos Daniel
Magnoni: Department of Nutrition and Nutritional Therapy,
HCor Heart Hospital (SP), Department of Clinical Nutrition,
Dante Pazzanese Cardiovascular Institute, Sao Paulo, Brazil;
Maria Makrides: Healthy Mothers, Babies and Children,
South Australian Health and Medical Research Institute,
Adelaide, Australia; Basil Mathioudakis: Consulting sprl,
Food Legislation and Nutrition, Brussels, Belgium; Alessandro
Monaco: Giovanni Lorenzini Medical Science Foundation,
Milan, Italy; Elvira Naselli: La Repubblica, Rome, Italy;
Elly O’Brien: Bazian, Economist Intelligence Unit, London,
United Kingdom; Chirag J. Patel: Department of Biomed-
ical Informatics, Harvard Medical School, Boston, MA;
Sergio Pecorelli: Giovanni Lorenzini Medical Foundation,
Houston, TX; Andrea Peracino: Giovanni Lorenzini Med-
ical Science Foundation, Milan, Italy; Giorgio Racagni:
Department of Pharmacology and Biomolecular Sciences,
Faculty of Pharmaceutical Sciences, Università di Milano,
Milan, Italy; Holger J Schünemann: Department of Clin-
ical Epidemiology and Biostatistics, McMaster University,
Hamilton, ON, Canada; Raanan Shamir: Institute Gas-
troenterology, Nutrition and Liver Diseases, Schneider
Children’s Medical Center of Israel - Sackler Faculty
of Medicine, University of Tel Aviv, Israel; Katherine L
Tucker: Department of Clinical Laboratory and Nutri-
tional Sciences, University of Massachusetts, Lowell,
MA; Peter Whoriskey: The Washington Post, Washington,
DC; Niv Zmora: Department of Immunology, Weizmann
Institute of Science, Rehovot, Israel. All authors read and
approved the final version of the paper.
References
1. Watts ML, Hager MH, Toner CD, Weber JA. The art of translating
nutritional science into dietary guidance: history and evolution of the
Dietary Guidelines for Americans. Nutr Rev 2011;69:404–12.
2. Fontana L, Partridge L. Promoting health and longevity through diet:
from model organisms to humans. Cell 2015;161:106–18.
3. Murphy SP, Yates AA, Atkinson SA, Barr SI, Dwyer J. History of nu-
trition: the long road leading to the dietary reference intakes for the
United States and Canada. Adv Nutr 2016;7:157–68.
4. Onvani S, Haghighatdoost F, Surkan PJ, Larijani B, Azadbakht L. Ad-
herence to the healthy eating index and alternative healthy eating index
dietary patterns and mortality from all causes, cardiovascular disease
and cancer: a meta-analysis of observational studies. J Hum Nutr Diet
2017;30:216–26.
5. European Food Safety Authority. Dietary reference values and dietary
guidelines [Internet]. c2017 [cited 2017 Mar 20]. Available from: https://
www.efsa.europa.eu/en/topics/topic/drv.
6. Mozaffarian D. Dietary and policy priorities for cardiovascular disease,
diabetes, and obesity: a comprehensive review. Circulation 2016;133:
187–225.
7. WHO. WHO guidelines on nutrition[Internet]. c2017 [cited 2017 Mar 20].
Available from: http://www.who.int/publications/guidelines/nutrition/en/.
8. Office of Disease Prevention and Health Promotion. Dietary guidelines
for Americans 2015–2020 [Internet]. c2017 [cited 2017 Mar 20].
Available from: https://health.gov/dietaryguidelines/2015/guidelines/.
9. Millen BE, Abrams S, Adams-Campbell L, Anderson CA, Brenna JT,
Campbell WW, Clinton S, Hu F, Nelson M, Neuhouser ML, et al. The
2015 Dietary Guidelines Advisory Committee Scientific Report: de-
velopment and major conclusions. Adv Nutr 2016;7:438–44.
10. Nordic co-operation. Nordic nutrition recommendations 2012 [Inter-
net]. c2017 [cited 2017 Mar 20]. Available from: https://www.norden.
org/en/theme/nordic-nutrition-recommendation.
11. Sustainable Development. Sustainable Development Goals [Internet].
c2017 [cited 2017 Mar 20]. Available from: https://sustainabledevelopment.
un.org/sdgs.
12. Taukobong HF, Kincaid MM, Levy JK, Bloom SS, Platt JL, Henry SK,
Darmstadt GL. Does addressing gender inequalities and empowering
women and girls improve health and development programme out-
comes? Health Policy Plan 2016;31:1492–514.
13. Morgan PJ. Back to the future: the changing frontiers of nutrition
research and its relationship to policy. Proc Nutr Soc 2012;71:190–
7.
14. Schünemann HJ, Wiercioch W, Etxeandia I, Falavigna M, Santesso N,
Mustafa R, Ventresca M, Brignardello-Petersen R, Laisaar KT, Kowalski S,
et al. Guidelines 2.0: systematic development of a comprehensive
checklist for a successful guideline enterprise. CMAJ 2014;186:E123–
42.
15. Brownell KD, Roberto CA. Strategic science with policy impact. Lancet
2015;385:2445–6.
16. LaRocca TJ, Martens CR, Seals DR. Nutrition and other lifestyle in-
fluences on arterial aging. Ageing Res Rev 2016 Sep 28 (Epub ahead of
print; DOI: 10.1016/j.arr.2016.09.002).
17. Ohlhorst SD, Russell R, Bier D, Klurfeld DM, Li Z, Mein JR, Milner J,
Ross AC, Stover P, Konopka E. Nutrition research to affect food and a
healthy life span. Am J Clin Nutr 2013;98:620–5.
18. Chavalarias D, Wallach JD, Li AH, Ioannidis JP. Evolution of reporting
P values in the biomedical literature, 1990–2015. JAMA 2016;315:
1141–8.
19. Ioannidis JP. We need more randomized trials in nutrition-preferably
large, long-term, and with negative results. Am J Clin Nutr 2016;103:
1385–6.
20. Patel CJ, Burford B, Ioannidis JP. Assessment of vibration of effects due
to model specification can demonstrate the instability of observational
associations. J Clin Epidemiol 2015;68:1046–58.
21. Ioannidis JP. Contradicted and initially stronger effects in highly cited
clinical research. JAMA 2005;294:218–28.
22. Young SS, Karr A. Deming, data and observational studies. Significance
2011;8:116–20.
23. Brown AW, Ioannidis JP, Cope MB, Bier DM, Allison DB. Unscientific
beliefs about scientific topics in nutrition. Adv Nutr 2014;5:563–5.
24. Hemkens LG, Contopoulos-Ioannidis DG, Ioannidis JP. Routinely
collected data and comparative effectiveness evidence: promises and
limitations. CMAJ 2016;188:E158–64.
25. Ioannidis JP. Implausible results in human nutrition research. BMJ
2013;347:f6698.
26. Siontis GC, Ioannidis JP. Risk factors and interventions with statistically
significant tiny effects. Int J Epidemiol 2011;40:1292–307.
27. Dal-Ré R, Bracken MB, Ioannidis JP. Call to improve transparency of
trials of non-regulated interventions. BMJ 2015;350:h1323.
28. Hébert JR, Frongillo EA, Adams SA, Turner-McGrievy GM, Hurley TG,
Miller DR, Ockene IS. Perspective: randomized controlled trials
are not a panacea for diet-related research. Adv Nutr 2016;7:
423–32.
29.TzoulakiI,PatelCJ,OkamuraT,ChanQ,BrownIJ,MiuraK,
UeshimaH,ZhaoL,VanHornL,DaviglusML,etal.Anutrient-
wide association study on blood pressure. Circulation 2012;126:
2456–64.
Nutritional guidelines for sustainable health policies 543
30. Del Gobbo LC, Imamura F, Aslibekyan S, Marklund M, Virtanen JK,
Wennberg M, Yakoob MY, Chiuve SE, Dela Cruz L, Frazier-Wood AC,
et al.; Cohorts for Heart and Aging Research in Genomic Epidemiology
(CHARGE) Fatty Acids and Outcomes Research Consortium(FORCe).
Omega-3 polyunsaturated fatty acid biomarkers and coronary heart
disease: pooling project of 19 cohort studies. JAMA Intern Med
2016;176:1155–66.
31. Khoury MJ, Ioannidis JP. Medicine. Big data meets public health.
Science 2014;346:1054–5.
32. Patel CJ, Chen R, Kodama K, Ioannidis JP, Butte AJ. Systematic identi-
fication of interaction effects between genome- and environment-wide
associations in type 2 diabetes mellitus. Hum Genet 2013;132:495–508.
33. Patel CJ, Ioannidis JP. Placing epidemiological results in the context of
multiplicity and typical correlations of exposures. J Epidemiol Com-
munity Health 2014;68:1096–100.
34. Patel CJ, Ioannidis JP. Studying the elusive environment in large scale.
JAMA 2014;311:2173–4.
35. Patel CJ, Cullen MR, Ioannidis JP, Butte AJ. Systematic evaluation of
environmental factors: persistent pollutants and nutrients correlated
with serum lipid levels. Int J Epidemiol 2012;41:828–43.
36. Patel CJ, Rehkopf DH, Leppert JT, Bortz WM, Cullen MR,
Chertow GM, Ioannidis JP. Systematic evaluation of environmental and
behavioural factors associated with all-cause mortality in the United
States National Health and Nutrition Examination Survey. Int J Epide-
miol 2013;42:1795–810.
37. Merritt MA, Tzoulaki I, Tworoger SS, De Vivo I, Hankinson SE,
Fernandes J, Tsilidis KK, Weiderpass E, Tjønneland A, Petersen KE, et al.
Investigation of dietary factors and endometrial cancer risk using a
nutrient-wide association study approach in the EPIC and Nurses’Health
Study (NHS) and NHSII. Cancer Epidemiol Biomarkers Prev 2015;24:
466–71.
38. Merritt MA, Tzoulaki I, van den Brandt PA, Schouten LJ, Tsilidis KK,
Weiderpass E, Patel CJ, Tjønneland A, Hansen L, Overvad K, et al.
Nutrient-wide association study of 57 foods/nutrients and epithelial
ovarian cancer in the European Prospective Investigation into Cancer
and Nutrition study and the Netherlands Cohort Study. Am J Clin
Nutr 2016;103:161–7.
39. Ioannidis JP. Exposure-wide epidemiology: revisiting Bradford Hill.
Stat Med 2016;35:1749–62.
40. Ioannidis JP, Loy EY, Poulton R, Chia KS. Researching genetic versus
nongenetic determinants of disease: a comparison and proposed uni-
fication. Sci Transl Med 2009;1:7ps8.
41. Leek JT, Peng RD. Opinion: reproducible research can still be wrong:
adopting a prevention approach. Proc Natl Acad Sci USA 2015;112:
1645–6.
42. Goodman SN, Fanelli D, Ioannidis JP. What does research reproduci-
bility mean? Sci Transl Med 2016;1:341ps12.
43. Parnell LD, Lee YC, Lai CQ. Adaptive genetic variation and heart dis-
ease risk. Curr Opin Lipidol 2010;21:116–22.
44. Bennett BJ, Hall KD, Hu FB, McCartney AL, Roberto C. Nutrition and
the science of disease prevention: a systems approach to support
metabolic health. Ann N Y Acad Sci 2015;1352:1–12.
45. Pigeyre M, Yazdi FT, Kaur Y, Meyre D. Recent progress in genetics,
epigenetics and metagenomics unveils the pathophysiology of human
obesity. Clin Sci (Lond) 2016;130:943–86.
46. Reddon H, Gueant JL, Meyre D. The importance of gene-environment
interactions in human obesity. Clin Sci (Lond) 2016;130:1571–97.
47. Vega-López S, Ausman LM, Griffith JL, Lichtenstein AH. Interindi-
vidual variability and intra-individual reproducibility of glycemic index
values for commercial white bread. Diabetes Care 2007;30:1412–7.
48. Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A,
Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, et al. Person-
alized nutrition by prediction of glycemic responses. Cell 2015;163:
1079–94.
49. Zmora N, Zeevi D, Korem T, Segal E, Elinav E. Taking it personally:
personalized utilization of the human microbiome in health and dis-
ease. Cell Host Microbe 2016;19:12–20.
50. Vrolix R, Mensink RP. Variability of the glycemic response to single
food products in healthy subjects. Contemp Clin Trials 2010;31:5–11.
51. Thaiss CA, Zmora N, Levy M, Elinav E. The microbiome and innate
immunity. Nature 2016;535:65–74.
52. GRADE Working Group. The GRADE working group [Internet]. c2017
[cited 2017 Mar 20]. Available from: http://www.gradeworkinggroup.org/.
53. GRADEpro GDT. GRADE’s software for summary of findings tables,
health technology assessment and guidelines [Internet]. c2017 [cited
2017 Mar 20]. Available from: www.GRADEpro.org.
54. Alonso-Coello P, Schunemann HJ, Moberg J, Brignardello-
Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Rada G,
Rosenbaum S, et al.; GRADE Working Group. GRADE Evidence to
Decision (EtD) frameworks: a systematic and transparent approach
to making well informed healthcare choices. 1: introduction. BMJ
2016;353:i2016.
55. Schünemann HJ, Mustafa R, Brozek J, Santesso N, Alonso-Coello P,
Guyatt G, Scholten R, Langendam M, Leeflang MM, Akl EA, et al.;
GRADE Working Group. GRADE Guidelines: 16. GRADE evidence to
decision frameworks for tests in clinical practice and public health.
J Clin Epidemiol 2016;76:89–98.
56. Guyatt GH, Alonso-Coello P, Schunemann HJ, Djulbegovic B,
Nothacker M, Lange S, Murad MH, Akl EA. Guideline panels should
seldom make good practice statements: guidance from the GRADE
Working Group. J Clin Epidemiol 2016;80:3–7.
57. Alonso-Coello P, Oxman AD, Moberg J, Brignardello-Petersen R,
Akl EA, Davoli M, Treweek S, Mustafa RA, Vandvik PO, Meerpohl J,
et al.; the GRADE Working Group. GRADE Evidence to Decision (EtD)
frameworks: a systematic and transparent approach to making well
informed healthcare choices. 2: clinical practice guidelines. BMJ 2016;
353:i2089.
58. The National Academies of Sciences, Engineering, and Medicine.
Health and medicine division [Internet]. c2017 [cited 2017 Mar 20].
Available from: https://www.nationalacademies.org/hmd.
59. Schünemann HJ, Fretheim A, Oxman AD. Improving the use of re-
search evidence in guideline development: 9. Grading evidence and
recommendations. Health Res Policy Syst 2006;4:21.
60. Schünemann HJ, Fretheim A, Oxman AD; WHO Advisory Committee
on Health Research. Improving the use of research evidence in
guideline development: 1. Guidelines for guidelines. Health Res Policy
Syst 2006;4:13.
61. Fretheim A, Schunemann HJ, Oxman AD. Improving the use of re-
search evidence in guideline development: 3. Group composition and
consultation process. Health Res Policy Syst 2006;4:15.
62. Bier DM, Willett WC. Dietary Reference Intakes: resuscitate or let die?
Am J Clin Nutr 2016;104:1195–6.
63. Schünemann HJ, Sperati F, Barba M, Santesso N, Melegari C, Akl EA,
Guyatt G, Muti P. An instrument to assess quality of life in relation to
nutrition: item generation, item reduction and initial validation. Health
Qual Life Outcomes 2010;8:26.
64. Schünemann HJ, Al-Ansary LA, Forland F, Kersten S, Komulainen J,
Kopp IB, Macbeth F, Phillips SM, Robbins C, van der Wees P, et al.;
Board of Trustees of the Guidelines International Network. Guidelines
International Network: principles for disclosure of interests and
management of conflicts in guidelines. Ann Intern Med 2015;163:
548–53.
65. The RIGHT Working Group. A proposal of essential reporting items
for practice guidelines in health systems (RIGHT) [Internet]. c2017
[cited 2017 Mar 20]. Available from: http://www.equator-network.org/
wp-content/uploads/2009/02/RIGHT-Guideline.pdf.
66. Medina-Remón A, Casas R, Tresserra-Rimbau A, Ros E, Martínez-
González MA, Fitó M, Corella D, Salas-Salvadó J, Lamuela-Raventos RM,
Estruch R.; PREDIMED Study InvestigatorsPolyphenol intake from
a Mediterranean diet decreases inflammatory biomarkers related to
atherosclerosis: A sub-study of The PREDIMED trial. Br J Clin Phar-
macol 2017;83:114–28.
67. Mithril C, Dragsted LO, Meyer C, Blauert E, Holt MK, Astrup A.
Guidelines for the New Nordic diet. Public Health Nutr 2012;15:
1941–7.
544 Magni et al.
68. Mithril C, Dragsted LO, Meyer C, Tetens I, Biltoft-Jensen A, Astrup A.
Dietary composition and nutrient content of the New Nordic Diet.
Public Health Nutr 2013;16:777–85.
69. Yavchitz A, Boutron I, Bafeta A, Marroun I, Charles P, Mantz J,
Ravaud P. Misrepresentation of randomized controlled trials in
press releases and news coverage: a cohort study. PLoS Med 2012;9:
e1001308.
70. Vinkers CH, Tijdink JK, Otte WM. Use of positive and negative words
in scientific PubMed abstracts between 1974 and 2014: retrospective
analysis. BMJ 2015;351:h6467.
71. Haneef R, Lazarus C, Ravaud P, Yavchitz A, Boutron I. Interpretation of
results of studies evaluating an intervention highlighted in Google
health news: a cross-sectional study of news. PLoS One 2015;10:
e0140889.
72. Lazarus C, Haneef R, Ravaud P, Boutron I. Classification and preva-
lence of spin in abstracts of non-randomized studies evaluating an in-
tervention. BMC Med Res Methodol 2015;15:85.
73. Lazarus C, Haneef R, Ravaud P, Hopewell S, Altman DG, Boutron I.
Peer reviewers identified spin in manuscripts of nonrandomized
studies assessing therapeutic interventions, but their impact on spin in
abstract conclusions was limited. J Clin Epidemiol 2016;77:44–51.
74. Johnston JL, Fanzo JC, Cogill B. Understanding sustainable diets: a
descriptive analysis of the determinants and processes that influence
diets and their impact on health, food security, and environmental
sustainability. Adv Nutr 2014;5:418–29.
75. Balshem H, Helfand M, Schunemann HJ, Oxman AD, Kunz R, Brozek J,
Vist GE, Falck-Ytter Y, Meerpohl J, Norris S, et al. GRADE guidelines: 3.
Rating the quality of evidence. J Clin Epidemiol 2011;64:401–6.
76. Andrews JC, Schunemann HJ, Oxman AD, Pottie K, Meerpohl JJ,
Coello PA, Rind D, Montori VM, Brito JP, Norris S, et al. GRADE
guidelines: 15. Going from evidence to recommendation-determinants
of a recommendation’s direction and strength. J Clin Epidemiol 2013;
66:726–35.
77. Schünemann HJ, Fretheim A, Oxman AD. Improving the use of re-
search evidence in guideline development: 10. Integrating values and
consumer involvement. Health Res Policy Syst 2006;4:22.
78. Schwingshackl L, Knüppel S, Schwedhelm C, Hoffmann G, Missbach B,
Stelmach-Mardas M, Dietrich S, Eichelmann F, Kontopanteils E,
Iqbal K, et al. Perspective: nutriGrade: a scoring system to assess and
judge the meta-evidence of randomized controlled trials and cohort
studies in nutrition research. Adv Nutr 2016;7:994–1004.
79. Fontana L, Kennedy BK, Longo VD, Seals D, Melov S. Medical research:
treat ageing. Nature 2014;511:405–7.
Nutritional guidelines for sustainable health policies 545