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European Journal of Nutrition (2021) 60:1833–1862
https://doi.org/10.1007/s00394-020-02345-7
ORIGINAL CONTRIBUTION
Egg consumption andcardiovascular risk: adose–response
meta‑analysis ofprospective cohort studies
JustynaGodos1· AgnieszkaMicek2· TomaszBrzostek3· EstefaniaToledo4,5,6· LiciaIacoviello7,8· ArneAstrup9·
OscarH.Franco10,11· FabioGalvano12· MiguelA.Martinez‑Gonzalez4,5,6,13· GiuseppeGrosso12
Received: 21 January 2020 / Accepted: 21 July 2020 / Published online: 31 August 2020
© The Author(s) 2020
Abstract
Purpose Cardiovascular disease (CVD) is a leading cause of mortality globally and is strongly influenced by dietary risk
factors. The aim was to assess the association between egg consumption and risk of CVD risk/mortality, including coronary
heart disease (CHD), stroke, and heart failure.
Methods MEDLINE, Embase, and Web of Science databases were searched through April 2020 for prospective studies.
Two independent reviewers screened and extracted the data through standardized methods. Size effects were calculated as
summary relative risks (SRRs) in a dose–response fashion through random-effects meta-analyses.
Results Thirty-nine studies including nearly 2 million individuals and 85,053 CHD, 25,103 stroke, 7536 heart failure,
and 147,124 CVD cases were included. The summary analysis including 17 datasets from 14 studies conducted on CVD
(incidence and/or mortality) showed that intake of up to six eggs per week is inversely associated with CVD events, when
compared to no consumption [for four eggs per week, SRR = 0.95 (95% CI: 0.90; 1.00)]; a decreased risk of CVD incidence
was observed for consumption of up to one egg per day [SRR = 0.94 (95% CI: 0.89; 0.99)]. The summary analysis for CHD
incidence/mortality including 24 datasets from 16 studies showed a decreased risk up to two eggs per week [(SRR = 0.96
(95% CI: 0.91; 1.00)]. No associations were retrieved with risk of stroke. The summary analysis for heart failure risk includ-
ing six datasets from four studies showed that intake of one egg per day was associated with increased risk raising for higher
intakes compared to no consumption [for 1 egg per day, SRR = 1.15 (95% CI:1.02; 1.30)]. After considering GRADE criteria
for strength of the evidence, it was rated low for all outcomes but stroke, for which it was moderate (yet referring to no risk).
Conclusion There is no conclusive evidence on the role of egg in CVD risk, despite the fact that higher quality studies are
warranted to obtain stronger evidence for a possible protection of CVD associated with moderate weekly egg consumption
compared to no intake; equally, future studies may strengthen the evidence for increased heart failure risk associated with
high regular egg consumption.
Keywords Egg· Cardiovascular disease· Stroke· Prospective cohort· Meta-analysis· Dose–response
Introduction
Cardiovascular disease (CVD) represents the leading cause
of mortality globally, responsible for a total of about 18
million deaths in 2017, while increasing from 12.3 million
in 1990 [1]. Nutritional risk factors have been considered
of paramount importance to prevent the global burden of
CVD [2,3]. Among the many factors widely studied over
the last decades, dietary cholesterol has been the focus of
major attention due to the relationship between blood cho-
lesterol and increased risk of CVD firstly observed in the
Framingham Heart Study nearly half century ago and ever
since considered as risk factor [4]. Eggs, as major sources
Miguel A. Martinez-Gonzalez and Giuseppe Grosso have
contributed equally.
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s0039 4-020-02345 -7) contains
supplementary material, which is available to authorized users.
* Giuseppe Grosso
giuseppe.grosso@unict.it
Extended author information available on the last page of the article
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1834 European Journal of Nutrition (2021) 60:1833–1862
1 3
of dietary cholesterol (200–300mg/100g, about 180mg
per medium egg), have been subsequently advised to be
consumed in moderation to lower dietary cholesterol intake
[5]. However, current evidence on the association between
dietary cholesterol and CVD risk is not consistent [6]. In
2000 the American Heart Association advised consumption
of up to one egg per day [7] and nearly 10years later the US
Dietary Guidelines Advisory Committee eliminated choles-
terol restrictions from the latest US dietary guidelines [8].
Nonetheless, the general opinion on egg consumption might
be misled and food advertising and media campaigns spon-
soring and claiming cholesterol-free products as healthier
(sometimes supplemented with added sugars) are common.
As specifically for egg consumption, a comprehensive sum-
mary of evidence reported repeatedly null and contrast-
ing findings, suggesting that meta-analytic studies need to
better investigate potential confounding effects of relevant
variables (i.e., sex, geographical area, adjustment for health
or dietary variables, etc.) [9]. However, more prospective
cohort studies have been published so far: specifically, a later
study involving 6 US cohorts showed that egg consump-
tion was associated with increased risk of CVD and that
the detrimental cardiovascular effect of egg consumption
was mainly driven by dietary cholesterol, once more sug-
gesting the need to limit eggs consumption. In light of such
considerations, the aim of this study was to update current
evidence on the association between egg consumption and
CVD risk while assessing whether confounding factors may
play a role in such relation.
Methods
Study design
The design, analysis, and reporting of this study followed
the meta-analysis of Observational Studies in Epidemiol-
ogy (MOOSE) guidelines (ESM Table1). A systematic
search on PubMed (https ://www.ncbi.nlm.nih.gov/pubme
d/), EMBASE (https ://www.embas e.com/), Web of Science
(www.webof knowl edge.com) databases of studies pub-
lished up to April 2020 was performed with the following
search strategy: “[(egg OR eggs) AND (coronary heart dis-
ease OR myocardial infarction OR ischemic heart disease
OR ischemic heart disease OR coronary artery disease OR
heart disease OR stroke OR cardiovascular disease OR heart
failure)] AND (cohort OR prospective OR longitudinal OR
follow-up)”. Studies were selected if they met the follow-
ing inclusion criteria: (i) they were conducted on general
population of human adults (i.e., no patients recruited in
hospitals); (ii) had a prospective design; (iii) evaluated asso-
ciations between egg intake and risk of CVD (fatal and non-
fatal), cardiovascular-related outcomes (such as coronary
heart disease [CHD] and stroke, fatal and non-fatal), and
heart failure; (iv) assessed and reported hazard ratios (HRs)
or risk ratios (RRs) and their corresponding 95% CI for ≥ 3
exposure categories (egg consumption) or provided HRs
for increased intake of egg (as a continuous variable); and
(v) provided a defined amount of egg consumption per cat-
egory of exposure (i.e., servings of eggs per day or week).
Reference lists of studies of interest were also examined for
any additional study not previously identified. If more than
one study was conducted on the same cohort, only the data-
set including the larger number of individuals, the longest
follow-up, or the most comprehensive data (i.e., number of
cases and person-year for each category of exposure) was
included on a case by case situation, depending on the analy-
sis performed (see below). We did not exclude studies based
on language or publication date. All references were evalu-
ated by two independent reviewers (J.G., G.G.) with a third
reviewer (A.M.) available in case of disagreement.
Data extraction
Data were abstracted by the two independent reviewers from
each identified study using a standardized extraction form.
The following information was collected: (i) first author
name; (ii) year of publication; (iii) study cohort name and
country; (iv) number, sex, and age (mean or range) of par-
ticipants; (v) follow-up period; (vi) endpoints and cases;
(vii) distributions of cases and person-years, HRs and 95%
CIs for all categories of exposure; (viii) covariates used in
adjustments.
Risk ofbias andquality assessment
Risk of bias was assessed using the Cochrane Risk of bias
in Non-randomized Studies of Interventions (ROBINS-I)
tool previously used in comprehensive meta-analyses with
similar outcomes [10, 11]. The tool consists of the follow-
ing seven domains: (1) confounding, (2) selection of par-
ticipants, (3) measurement of the exposure, (4) misclassifi-
cation of exposure during follow-up, (5) missing data, (6)
measurement of outcomes and (7) selective reporting. Two
researchers (J.G. and A. M.) assessed the risk of bias inde-
pendently. Any disagreements were resolved by consensus
or by consultation of a third researcher.
Outcomes
Outcomes evaluated in the analyses included total CVD,
CHD, and stroke (including sub-types hemorrhagic and
ischemic stroke) incidence and mortality. Also risk of heart
failure incidence was assessed.
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1835European Journal of Nutrition (2021) 60:1833–1862
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Statistical analysis
When egg consumption was reported by ranges of intake,
the midpoint of the range was used. When the highest cat-
egory was open-ended, we assumed the width of the cat-
egory to be the same as the adjacent category. When the
lowest category was open-ended, we set the lower bound-
ary to zero. Two-stage random-effects dose–response
meta-analysis was performed to examine linear and
non-linear relationship between egg consumption and
CVD outcomes. In the first stage the method reported
by Greenland and Orsini (generalized least-squares,
GLS) was used to calculate study-specific coefficients
on the basis of results across categories of egg consump-
tion taking into account the correlation within each set
of retrieved HRs [12,13]. Non-linear dose–response
analysis was modeled using restricted cubic splines with
three knots at fixed percentiles (25%, 50%, and 75%)
of the distribution [14]. We combined the coefficients
that had been estimated within each study by performing
random-effects meta-analysis. In linear dose–response
meta-analysis the method of DerSimonian and Laird was
used andin non-linear dose–response meta-analysis the
multivariate extension of the method of moments was
used to estimate summary relative risks (SRRs). We cal-
culated an overall P value by testing that the two regres-
sion coefficients were simultaneously equal to zero. We
then calculated a P value for non-linearity by testing that
the coefficient of the second spline was equal to zero.
A subgroup analysis was conducted for those studies
providing risk measures by diabetic status. A number of
sensitivity analyses were conducted to test stability of
results, including (i) exclusion of one study at the time,
(ii) exclusion of studies that did not report number of
cases and person-years for each category of exposure,
and (iii) stratifying studies by variables of interest (such
as sex, geographical localization of the cohort, level of
adjustment for body mass index [BMI], diabetic status,
and other dietary factors, and study quality). To facili-
tate interpretation of the results and easy application for
dietary advices for the general population, the analyses
were provided in depth for arbitrarily defined doses, such
as “habitual” (daily) egg consumption corresponding to
one egg per day, and “moderate” (weekly) egg consump-
tion corresponding to four eggs per week. Publication
bias was assessed with Egger’s regression test. Statistical
heterogeneity between studies was assessed using the χ2
test (defined as a P value less than 0.10) and quantified
through the multivariate generalization of the I2 statis-
tic. All analyses were performed with R software version
3.0.3, dosresmeta and mvmeta packages (Development
Core Team, Vienna, Austria).
Grading oftheevidence
The certainty of the evidence was assessed using the Grad-
ing of Recommendations, Assessment, Development, and
Evaluation (GRADE) system [15]. Included observational
studies started at low-certainty of evidence by default and
then were downgraded or upgraded based on pre-specified
criteria. Criteria to downgrade certainty included study limi-
tations (weight of studies showing risk of bias by ROBINS-
I), inconsistency (substantial unexplained inter-study hetero-
geneity, I2 ≥ 50% and Phet < 0.10), indirectness (presence of
factors relating to the population, exposures and outcomes
that limit generalizability), imprecision [95% CIs were wide
or crossed a minimally important difference of 5% (SRR
0.95–1.05) for all CVD outcomes] and publication bias [sig-
nificant evidence of small-study effects). Criteria to upgrade
included a large effect size (SRR > 2 or SRR < 0.5 in the
absence of plausible confounders], a dose–response gradient
and attenuation by plausible confounding effects.
Results
Study characteristics
Out of 291 initial references identified, a total of 39 stud-
ies [16–54] were selected based on 38 cohorts providing
data on CHD (1,831,038 individuals and 85,053 cases),
stroke (761,962 individuals and 25,103 cases), heart failure
(254,588 individuals and 7536 cases), and CVD (1,117,033
individuals and 147,124 cases) outcomes (Fig.1). A detailed
description of the studies included is presented in Table1.
From the 38 individual cohorts, 16 were from North Amer-
ica, 9 from Europe, 9 from Asia and one from Iran, and 3
multinational cohorts. One of the studies from North Amer-
ica included a pooled analysis of 6 US cohorts (pooled data
was used in this meta-analysis). All studies had adequate
follow-up to assess occurrence of the outcomes investigated
(ranging from 3 to 32years of mean follow-up). All studies
scored moderate or serious risk of bias; a detailed descrip-
tion of judgment of potential risk of bias is given in the
online supplementary materials (ESM Table2). All but four
studies [25, 28, 32, 34] provided full data of interest for bet-
ter risk estimation (number of cases and person-years for
each category of exposure), most of studies reported analy-
ses adjusted for potential confounders investigated: among
other dietary factors, besides total energy intake nearly
always considered, also intake of other food groups (fruit/
vegetable, whole grains, meat), macronutrients (trans-fats,
protein) and fiber have been considered. Subgroup analyses
were conducted through sex- and diabetic-specific groups,
including nine studies provided separate risk estimates for
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1836 European Journal of Nutrition (2021) 60:1833–1862
1 3
male and female participants, and eight studies for diabetic
participants.
Egg consumption andcardiovascular outcomes
The dose–response analyses for egg consumption and car-
diovascular outcomes are showed in Fig.2. The summary
analysis including 17 datasets from 14 studies conducted
on CVD (incidence and/or mortality) showed that intake of
up to six eggs per week is inversely associated with CVD
events, when comparing to no consumption [SRR = 0.98
(95% CI: 0.95; 1.00), SRR = 0.96 (95% CI: 0.91; 1.00),
SRR = 0.95 (95% CI: 0.89; 1.00), SRR = 0.95 (95% CI:
0.90; 1.00), SRR = 0.95 (95% CI: 0.91; 1.00), SRR = 0.96
(95% CI: 0.92; 1.00) for 1, 2, 3, 4, 5, and six eggs per week,
respectively; (I2 = 71.94%, Pheter < 0.001)] with no evidence
of publication bias (PEgger = 0.772). The analysis restricted
to CVD mortality showed wide confidence intervals while a
decreased risk of CVD incidence was observed for consump-
tion of up to 1 egg per day (Table2).
The summary analysis for CHD incidence/mortality
including 24 datasets from 16 studies showed a decreased
risk up to two eggs per week [SRR = 0.96 (95% CI: 0.91;
1.00), I2 = 82.25%, Pheter < 0.001] compared to no con-
sumption, while higher intake was associated with no
further reduced risk; no publication bias was detected
(PEgger = 0.173). Distinction between studies on CHD inci-
dence or mortality showed that the associated reduced risk
Fig. 1 Flow chart of study iden-
tification and selection process
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1837European Journal of Nutrition (2021) 60:1833–1862
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Table 1 Characteristics of the prospective cohort studies selected for meta-analysis
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Hu [16] HPFS, 1986 and NHS,
1980 (US)
8 years in men and 14
years in women
37,851 men (40–75 years)
and 80,082 women
(34–59 years)
866 CHD and 258 stroke
events in men and 939
CHD and 563 stroke
events in women
Repeated FFQ Age, BMI, 2-year history
of myocardial infarction,
multivitamin supple-
ment use, vitamin E,
menopausal hormone
use (women), history of
hypertension, physical
activity, and total energy
intake
He [17] HPFS, 1986 (US) 14 years 43,732 (40–75 years) men 725 stroke, 455 ischemic
stroke, 125 hemorrhagic
stroke events
Repeated FFQ BMI, physical activity,
history of hypertension,
smoking status, aspirin
use, multivitamin use,
consumption of alco-
hol, potassium, fiber,
vitamin E, total servings
of fruit and vegetables,
total energy intake, and
hypercholesterolemia at
baseline
Sauvaget [18] LSS, 1979–1981 (Japan) 16 years 15,350 men (mean age
54years) and 24 999
women (mean age
58years)
1462 stroke events FFQ Stratified by sex and birth
cohort, adjusted for city,
radiation dose, self-
reported BMI, smoking
status, alcohol habits,
education level, history of
diabetes, or hypertension
Nakamura [19] NIPPON DATA80, 1980
(Japan)
14 years 5186 women (≥ 30 years)
and 4077 men (≥ 30
years)
112 stroke and 39 CHD
events in men, 107
stroke and 41 IHD
events in women
FFQ Age, serum creatinine, total
cholesterol, blood glu-
cose, BMI, systolic and
diastolic blood pressures,
use of blood pressure–
lowering drugs, cigarette
smoking, and alcohol
intake
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1838 European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Nakamura [20] JPHC, 1990 (Japan) 10.2 years (mean) 19,856 men and 21,408
women, aged 40–59
years in cohort I; 23,463
men and 26,008 women,
aged 40–69 years in
cohort II
462 CHD events FFQ Age, sex, BMI, hyperten-
sion, diabetes, use of
cholesterol-lowering
drugs, smoking, alcohol
drinking, whether or
not intended to avoid
cholesterol-rich diets,
consumption frequencies
of meat, fish, vegetables,
fruits, and cohort effects
Trichopoulou [52] EPIC-Greece, 1994–1999
(Greece)
4.5 years (mean) 1013 men and women
(20–86 years)
46 CVD death events FFQ Gender, age, educational
level, smoking, waist-to-
height, hip circumference,
MET score, treatment
with insulin, treatment
for hypertension at
enrollment, treatment
for hypercholesterolemia
at enrollment, and other
indicated food groups
Qureshi [21] NHANES I, 1982–1992
(US)
20 years 13,586 men and women
(25–74 years)
655 stroke, 1584 MI and
253 CVD death events
FFQ Age, gender, race/ethnicity,
systolic blood pressure,
diabetes mellitus, serum
cholesterol, cigarette
smoking, BMI, and edu-
cational status
Djoussé [22] PHS, 1981 (US) 20 years 21,327 men (40–85 years) 1550 MI, 1342 stroke
events
FFQ Age, BMI, smoking, his-
tory of hypertension,
vitamin intake, alcohol
consumption, vegetable
consumption, breakfast
cereal, physical activ-
ity, treatment arm, atrial
fibrilation, diabetes
mellitus, hypercholester-
olemia, parental history
of premature myocardial
infarction
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1839European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Djoussé [23] PHS, 1981 (US) 20 years 21,327 men (40–85 years) 1084 heart failure events FFQ Age, BMI, smoking,
alcohol consumption,
physical activity, history
of diabetes mellitus, atrial
fibrillation, hypertension,
valvular heart disease,
and treatment for cho-
lesterol
Nettleton [24] ARIC, 1987–1989 (US) 13.3 years 14,153 men and women
(45–64 years)
1140 heart failure events Repeated FFQ Energy intake, age, sex,
race/center, education
level, physical activity
level, smoking, drink-
ing status, and prevalent
disease status: cardiovas-
cular disease, diabetes,
and hypertension
Bernstein [25] NHS, 1980 (US) 26 years 84,136 women (30–55
years)
2210 CHD and 952 CHD
death events
Repeated FFQ Age, time period, total
energy, cereal fiber,
alcohol, trans fat, BMI,
cigarette smoking, meno-
pausal status, parental his-
tory of early myocardial
infarction, multivitamin
use, vitamin E supple-
ment use, aspirin use
at least once per week,
physical exercise
Scrafford [26] NHANES III, 1988–1994
(US)
12.2 years 6833 men and 8113
women (≥ 17 years)
168 CHD and 74 stroke
events in women and
198 CHD and 63 stroke
events in men
FFQ Age, energy, marital status,
educational status, race/
ethnicity, smoking status,
BMI, WHR, diabetes,
hypertension and dietary
variables
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1840 European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Bernstein [28] HPFS, 1986 and NHS,
1980 (US)
26 years in women and 22
years in men
84,010 women (30–55
years) and 43,150 men
(40–75 years)
2633 stroke events in
women and 1397 stroke
events in men
Repeated FFQ Age, time period BMI,
cigarette smoking,
physical exercise, parental
history of early myocar-
dial infarction, meno-
pausal status in women,
multivitamin use, vitamin
E supplement use, aspirin
use, total energy, cereal
fiber, alcohol, transfat,
fruit and vegetables, and
other protein sources
Houston [49] Health ABC, 1997–1998
(US)
9 years 1941 men and women
(70–79 years)
203 CVD events FFQ Age, gender, race, educa-
tion, field center, smok-
ing, alcohol use, physical
activity, BMI, total energy
intake, protein intake,
fiber intake, multivitamin
use, supplemental vitamin
E use, statin use, aspirin
use, oral estrogen use
(women only), prevalent
hypertension, and satu-
rated fat
Zazpe [27] SUN, 1999 (Spain) 6.1 years 14,185 men and women
(20–90 years)
91 CVD events FFQ Age, sex, total energy
intake, adherence to
the Mediterranean food
pattern, alcohol intake,
baseline BMI, smoking
status, physical activ-
ity during leisure time,
family history of CVD,
self-reported diabetes,
self-reported hyperten-
sion, self-reported hyper-
cholesterolemia
Dilis [29] EPIC-Greece, 1994–1999
(Greece)
10 years 23,929 men and women
(20–86 years)
636 CHD events FFQ Age, BMI, height, physical
activity, years of school-
ing, energy intake,
alcohol consumption,
smoking status and arte-
rial blood pressure, and
nutritional variables
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1841European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Misirli [30] EPIC-Greece, 1994–1999
(Greece)
10.6 years 23,601 men and women
(20–86 years)
395 stroke events FFQ Sex, age, education, smok-
ing status, BMI, level
of physical activity as
measured in metabolic
equivalents, hypertension,
diabetes, and total energy
intake
Yaemsiri [31] WHI-OS, 1994–1998
(US)
7.6 years 87,025 women (50–79
years)
1049 ischemic stroke
events
Repeated FFQ Age, race, education, family
income, years as a regular
smoker, hormone replace-
ment therapy use, total
metabolic equivalent task
hours per week, alcohol
intake, history of coro-
nary heart disease, history
of atrial fibrillation, his-
tory of diabetes, aspirin
use, use of antihyper-
tensive medication, use
of cholesterol-lowering
medication, BMI, systolic
blood pressure, and total
energy intake, dietary
vitamin E, fruits and
vegetable intake, fiber
Goldberg [32] NMS, NR (US) 11 years 1429 men and women
(> 40 years)
719 CVD (266 stroke
events, 226 MI, 452
CVD death events)
FFQ Age, sex, race/ethnicity,
BMI, diabetes, hyperten-
sion, LDL, HDL, TG,
cholesterol-lowering
medication, moderate
alcohol use, moderate-
heavy physical activity,
smoking, high-school
completion, daily kcal,
Mediterranean diet score,
history of stroke, myo-
cardial infarction, daily
consumption of saturated
fat, unsaturated fat, carbo-
hydrates, and protein
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1842 European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Haring [33] ARIC, 1987–1989 (US) 22 years 12,066 men and women
(45–64 years)
1147 CHD events Repeated FFQ Age, sex, race, study center,
total energy intake,
smoking, cigarette years,
education, systolic blood
pressure, use of antihy-
pertensive medication,
high-density lipoprotein
cholesterol, total choles-
terol, use of lipid-low-
ering medication, BMI,
waist-to-hip ratio, alcohol
intake, sports-related
physical activity, leisure-
related physical activity,
carbohydrate intake, fiber
intake, fat intake, and
magnesium intake
Haring [34] ARIC, 1987–1989 (US) 22.7 years 11,601 men and women
(45–64 years)
699 stroke events Repeated FFQ Age, sex, race, study center,
total energy intake,
smoking, cigarette years,
education, systolic blood
pressure, use of antihy-
pertensive medication,
high-density lipoprotein
cholesterol, total choles-
terol, use of lipid-low-
ering medication, BMI,
waist-to-hip ratio, alcohol
intake, sports-related
physical activity, leisure-
related physical activity,
carbohydrate intake, fiber
intake, fat intake, and
magnesium intake
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1843European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Larsson [35] COSM, 1997 and SMC,
1987–1990 (Norway)
13 years 37,766 men (45–79 years)
and 32,805 women
(49–83 years)
1628 HF, 3262 MI, 2039
ischemic strokes, 405
hemorrhagic stroke
events in men and 1207
HF, 1504 MI, 1561
ischemic stroke, and
294 hemorrhagic stroke
events in women
FFQ Age, education, family
history of myocardial
infarction, smoking status
and pack-years of smok-
ing, aspirin use, walking/
bicycling, exercise, BMI,
history of hypertension,
hypercholesterolemia, and
diabetes, intakes of total
energy, alcohol, fruit and
vegetables, and processed
meat
Farvid [38] GCS, 2004 (Iran) 11 years 42,403 men and women
(36–85 years)
1467 CVD, 764 CHD, 507
stroke events
FFQ Sex, age, ethnicity, educa-
tion, marital status,
residency, smoking,
opium use, alcohol, BMI,
systolic blood pressure,
occupational physical
activity, family history
of cancer, wealth score,
medication, and energy
intake
Virtanen [36] KIHD, 1984–1989 (Fin-
land)
20.8 years 1032 men (42–60 years) 230 CHD events 4-d food records Age, examination year, and
energy intake, smoking,
BMI, diabetes, hyperten-
sion, leisure-time physical
activity, coronary artery
disease history in close
relatives, education, and
intakes of alcohol, fruit,
berries, vegetables, fiber,
PUFAs, and SFAs
Díez-Espino [37] PREDIMED, 2003–2009
(Spain)
5.8 years 7216 men and women
(55–80 years)
342 CVD events FFQ Age, sex, BMI, intervention
group, recruitment center,
smoking status, physical
activity during leisure
time, and educational
status, diabetes, hyper-
tension, hypercholester-
olemia, family history of
CVD, Mediterranean food
pattern, alcohol intake,
and total energy intake
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1844 European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Guo [39] CAPS, 1979–1983 and
NDNS, 2008–2009
(UK)
22.8 years 2512 men (45–59 years) 715 CVD (248 stroke, 477
MI, 201 heart failure)
events
7-d food records Age, BMI, total energy
intake, alcohol consump-
tion, smoking status,
energy expenditure, social
class, family history of
myocardial infarction,
diabetes mellitus, sugar
intake, fruit consumption,
red meat consumption and
fiber (cereal and vegetable
sources)
Jang [40] KGES, 2001–2002
(Korea)
7.3 years 9248 men and women
(40–69 years)
570 CVD events FFQ Age, sex, educational level,
residential area, monthly
household income,
alcohol drinking, smoking
in pack-years, physical
activity level, dietary
supplement use, history
of hypertension and dys-
lipidemia, and the intake
levels of total energy, total
vegetables, total fruits,
red meat, fiber, vitamin
E, BMI
Qin [41] CKB, 2004–2008 (China) 8.9 years 461,213 men and women
(30–79 years)
83,977 CVD (30,169
IHD, 7078 hemorrhagic
stroke, and 27,745
ischemic stroke) and
9985 CVD death events
(3374 IHD, 3435 hemor-
rhagic stroke, and 1 003
ischemic stroke deaths)
Repeated FFQ Age at recruitment, sex,
education level, house-
hold income, marital
status, alcohol consump-
tion, tobacco smoking,
physical activity in
MET-hours/day, BMI,
waist-to-hip ratio, preva-
lent hypertension, use of
aspirin, family history of
CVD, intake of multivita-
min supplementation and
dietary pattern
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1845European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Xu [43] GBCS, 2003–2008
(China)
9.8 years 28,024 men and women
(> 50 years)
873 CVD, 388 IHD and
341 stroke death events
FFQ Sex, age, education, occu-
pation, family income,
smoking status, physical
activity, alcohol drinking,
self-rated health and
chronic disease history
(diabetes, hypertension
and dyslipidemia), dietary
variables (daily dietary
energy and vegetable,
fruit, milk and nut intake
were included in this
model with additional
adjustment for total
energy, vegetable, fruit,
milk and nut intake; only
in 18,707 participants)
Zamora‐Ros [44] EPIC-Spain, 1992–1996
(Spain)
18 years 40,621 men and women
(29–69 years)
761 CVD death and 184
stroke events
FFQ center, age at recruitment
in 5year categories, sex,
smoking intensity, BMI,
lifetime alcohol intake,
education level, physical
activity, energy intake,
and adherence to Mediter-
ranean diet
Abdollahi [42] KIHD, 1984–1989 (Fin-
land)
21.2 years 1950 men (42–60 years) 217 stroke (166 ischemic
and 55 hemorrhagic)
events
4-d food records Age, year of examination,
energy intake, BMI, pack-
years of smoking, leisure-
time physical activity,
hypertension medication,
intakes of alcohol, fruit,
berries, and vegetables
Djoussé [47] MVP, 2011 (US) 3.24 years (mean) 188,267 men and women
(64.4 years mean)
10,160 MI events FFQ Age, sex race, education,
BMI, exercise, smok-
ing, alcohol intake, and
dietary approach to stop
hypertension score
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1846 European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Key [50] EPIC, 1992–2000
(Europe)
12.6 years (mean) 409,885 men and women
(~ 55 years)
7198 CHD events FFQ Age, smoking status and
number of cigarettes per
day, history of diabetes
mellitus, previous hyper-
tension, prior hyper-
lipidemia, Cambridge
physical activity index,
employment status, level
of education completed,
BMI, current alcohol con-
sumption, and observed
intakes of energy, fruit
and vegetables combined,
sugars, fiber from cereals,
and stratified by sex and
EPIC center
van den Brandt [53] NLCS, 1986, (The Neth-
erlands)
~ 9 years 3202 subcohort men and
women (55–69 years)
2985 CVD death events FFQ Age at baseline, sex,
cigarette smoking status,
number of cigarettes
smoked per day, and
years of smoking, history
of physician-diagnosed
hypertension and diabe-
tes, body height, BMI,
non-occupational physical
activity, highest level of
education, intake of alco-
hol, vegetables and fruit,
energy, use of nutritional
supplements, and, in
women, postmenopausal
HRT
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1847European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Zhong [45]Pooled cohorts (from US)a17.7 years 29,615 men and women
(mean age 51.6 years at
baseline)
5400 CVD events Harmonized assessment Age, sex, race/ ethnicity,
education, total energy,
smoking status, smok-
ing pack- years, cohort-
specific physical activity
z score, alcohol intake,
use of hormone therapy,
BMI, diabetes status,
systolic blood pressure,
use of antihypertensive
medications, high-density
lipoprotein (HDL)
cholesterol, non-HDL
cholesterol, and use of
lipid-lowering medica-
tions, dietary cholesterol
consumption
Dehghan [46] PURE, 2003, (multina-
tional); ONTARGET/
TRANSCEND, 2001–
2004 (multinational)
9.5 years PURE; 56
months ONTARGET/
TRANSCEND
PURE: 114,615 men and
women (~ 50 years);
ONTARGET/ TRAN-
SCEND 31,410 men
and women (≥ 55 years)
PURE: 3410 CVD death
events, 8477 CVD
events, 3664 MI, 3916
stroke, 939 heart failure;
ONTARGET/ TRAN-
SCEND: 2264 CVD
death events, 5181 CVD
events, 1554 MI, 1394
stroke, 1337 heart failure
FFQ PURE: age, sex, smoking,
location, education, physi-
cal activity, history of
diabetes, daily intakes of
fruits, vegetables, dairy,
red meat, poultry, and
fish; percentage energy
from carbohydrate; total
daily energy; and center
as a random effect
ONTARGET/TRAN-
SCEND: age, sex,
smoking, location, BMI,
education, physical activ-
ity, history of diabetes,
history of myocardial
infarction; history of
stroke; medication; trial
allocation; daily intakes
of fruit, vegetables, red
meat, poultry, fish, and
dairy; and regions as a
random effect
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1848 European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Drouin-Chartier [48] HPFS, 1986, NHS, 1980,
NHS II, 1991 (US)
32 years (up to) HPFS: 42,055 men
(40–75 years); NHS:
83,349 women (30–55
years); NHS II: 90,214
(25–44 years)
HPFS: 6170 CVD, 4461
CHD, 1740 stroke
events; NHS: 7411
CVD, 3896 CHD, 3587
stroke events; NHS II:
1225 CVD, 653 CHD,
576 stroke events
FFQ Age, race, family history
of myocardial infarc-
tion, baseline hypercho-
lesterolemia, baseline
hypertension, smoking
status, BMI, physical
activity, oral contracep-
tive use (in NHS II only),
postmenopausal hormone
use (in NHS and NHS
II only), alcohol intake,
and multivitamin use,
hypercholesterolemia and
hypertension, cumulative
average of daily intake
of total calories, full fat
milk, bacon, unprocessed
red meat, other processed
meats, refined grains,
fruits, vegetables, pota-
toes, coffee, fruit juices,
and sugar-sweetened
beverages
Tong [51] EPIC, 1992–2000
(Europe)
12.7 years (mean) 418,329 men and women
(~ 55 years)
7378 stroke events (4281
ischemic and 1430 hem-
orrhagic)
FFQ Age, smoking status and
number of cigarettes per
day, history of diabetes,
prior hypertension, prior
hyperlipidemia, Cam-
bridge physical activity
index, employment status,
level of education com-
pleted, current alcohol
consumption, BMI, and
observed intake of energy,
and stratified by sex and
EPIC center
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1849European Journal of Nutrition (2021) 60:1833–1862
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Table 1 (continued)
References Cohort name, years of
study (country)
Follow-up Sample, sex, age Outcomes, no. of cases Diet assessment Covariate adjustment
Xia [54] China-MUCA, 1998;
InterAISA, 200–2001
(China); CIMIC,
2007–2008 (China)
15 years China-MUCA
(median); 13 years Inte-
rAISA (median); 6 years
CIMIC (median)
China-MUCA: 10,410
men and women (35–59
years); InterAISA:
12,660 men and women
(35–74 years); CIMIC:
79,066 men and women
(≥ 18 years)
Overall 4848 CVD, 1273
CHD, 2919 stroke (1832
ischemic, 862 hemor-
rhagic) events
FFQ Age, gender, urban or rural
resident, per-capita house-
hold income, education
attainment, tobacco smok-
ing, alcohol consumption,
family history of CVD,
physical activity, BMI
and dietary factors (red
meat intake, fresh fruit
and vegetable intake)
ARIC Atherosclerosis Risk in Communities, CAPS Caerphilly Prospective Cohort Study, CKB China Kadoorie Biobank, COSM Cohort of Swedish Men, EPIC European Prospective into
Cancer and Nutrition, GBCS Guangzhou Biobank Cohort Study, GCS Golestan Cohort Study, Health ABC Health, Aging and Body Composition, HPFS Health Professionals Follow-up Study,
JPHC Japan Public Health Center-based prospective study, KGES Korean Genome and Epidemiology Study, KIHD Kuopio Ischaemic Heart Disease Risk Factor Study, LSS Life Span Study,
MVP Million Veteran Program, NDNS National Diet and Nutritional Survey, NHANES National Health and Nutrition Examination Survey, NHS Nurses’ Health Study, NIPPON DATA80 Non-
communicable Disease and Its Trends in the Aged, 1980, NMS Northern Manhattan Study, NR not reported, ONTARGET Ongoing Telmisartan Alone and in Combination with Ramipril Global
End Point Trial, PHS Physicians’ Health Study, PREDIMED PREvencion con DIeta MEDiterranea, PURE Prospective Urban Rural Epidemiology, SMC Swedish Mammography Cohort, SUN
Seguimiento Universidad de Navarra, TRANSCEND Telmisartan Randomized Assessment Study in ACEI Intolerant Subjects with Cardiovascular Disease, WHI-OS Women’s Health Initiative
Observational Study
a Cohorts included were Atherosclerosis Risk in Communities (ARIC) Study, Coronary Artery Risk Development in Young Adults (CARDIA) Study, Framingham Heart Study (FHS), Framing-
ham Offspring Study (FOS), Jackson Heart Study (JHS), and the Multi-Ethnic Study of Atherosclerosis (MESA)
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1850 European Journal of Nutrition (2021) 60:1833–1862
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was referring to the former, yet with evidence of heterogene-
ity (Table2).
The summary analysis for stroke including 22 datasets
from 16 studies showed no related risks associated with
any dose of egg consumption compared to no consumption,
with lower SRRs for stroke mortality, though with large
CIs (Table2). Also, the analyses conducted on sub-types
of stroke, despite investigated in a lower number of studies
(eight studies on hemorrhagic and nine studies on ischemic
stroke), showed null associations with egg consumption, yet
with evidence of heterogeneity (Table2).
The summary analysis for heart failure risk including
six datasets from four studies showed that intake of one
egg per day was associated with increased risk raising for
higher intakes compared to no consumption [SRR = 1.15
(95% CI:1.02; 1.30), SRR = 1.19 (95% CI: 1.04; 1.36),
SRR = 1.23 (95% CI: 1.06; 1.44) for 7, 8, and nine eggs
per week, respectively], with no evidence of heterogeneity
(I2 = 37%) and no publication bias (PEgger = 0.630).
In the sensitivity analyses by excluding one study at
the time, results were substantially unchanged (data not
shown). Also in the sensitivity analyses excluding stud-
ies with no complete data on number of individuals and
cases risk estimates associated to egg consumption were
unchanged for CVD and heart failure, while no associa-
tions with CHD and stroke were detected (ESM Table3);
moreover, both ischemic and hemorrhagic stroke risk was
Fig. 2 Graphical representation of dose–response association between egg intake and CVD, CHD, stroke and heart failure risk in prospective
cohort studies
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1851European Journal of Nutrition (2021) 60:1833–1862
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Table 2 Dose–response meta-analysis of the association between egg consumption and cardiovascular outcomes in prospective cohort studies
Outcome Datasets
(studies)
Eggs/week, RR (95% CI) I2Phet Pnonlinearity PEgger
0123456789
CVD
incidence/
mortality
17 (14) 1 (ref.) 0.98 (0.95;
1)
0.96 (0.91;
1.00)
0.95 (0.89;
1.00)
0.95 (0.9;
1.00)
0.95 (0.91;
1.00)
0.96 (0.92;
1.00)
0.96 (0.92;
1.01)
0.97
(0.91;
1.02)
0.97 (0.91;
1.04)
71 < 0.001 0.167 0.772
CVD inci-
dence
12 (9) 1 (ref.) 0.97 (0.94;
1)
0.94 (0.89;
1)
0.93 (0.87;
0.99)
0.93 (0.87;
0.99)
0.93 (0.88;
0.98)
0.94 (0.89;
0.99)
0.94 (0.89;
0.99)
0.95
(0.89;
1.01)
0.95 (0.89;
1.03)
75 < 0.001 0.13 0.955
CVD mor-
tality
9 (8) 1 (ref.) 0.98 (0.94;
1.03)
0.97 (0.9;
1.05)
0.96 (0.89;
1.05)
0.96 (0.89;
1.04)
0.96 (0.89;
1.03)
0.95 (0.88;
1.03)
0.95 (0.88;
1.03)
0.95
(0.87;
1.04)
0.95 (0.86;
1.04)
57 0.002 0.667 0.415
CHD
incidence/
mortality
24 (16) 1 (ref.) 0.98 (0.95;
1)
0.96 (0.91;
1)
0.95 (0.89;
1.01)
0.95 (0.88;
1.02)
0.96 (0.89;
1.03)
0.97 (0.9;
1.05)
0.98 (0.91;
1.07)
1 (0.91;
1.1)
1.01 (0.91;
1.13)
82 < 0.001 0.042 0.173
CHD inci-
dence
17 (12) 1 (ref.) 0.97 (0.94;
1)
0.94 (0.89;
0.99)
0.92 (0.86;
1)
0.93 (0.85;
1.01)
0.94 (0.86;
1.02)
0.96 (0.88;
1.05)
0.98 (0.89;
1.08)
1 (0.9;
1.11)
1.02 (0.9;
1.15)
85 < 0.001 0.011 0.222
CHD mor-
tality
8 (6) 1 (ref.) 1.01 (0.97;
1.06)
1.02 (0.94;
1.11)
1.02 (0.91;
1.14)
1.01 (0.88;
1.15)
0.99 (0.85;
1.15)
0.97 (0.81;
1.16)
0.95 (0.76;
1.18)
0.93
(0.72;
1.2)
0.91 (0.68;
1.23)
1 0.435 0.304 0.542
Stroke
incidence/
mortality
22 (16) 1 (ref.) 1 (0.97;
1.02)
0.99 (0.95;
1.04)
0.98 (0.93;
1.04)
0.98 (0.93;
1.02)
0.97 (0.93;
1.01)
0.96 (0.91;
1.01)
0.95 (0.88;
1.01)
0.94
(0.85;
1.03)
0.93 (0.82;
1.05)
46 < 0.001 0.842 0.936
Stroke inci-
dence
14 (10) 1 (ref.) 0.99 (0.96;
1.02)
0.97 (0.92;
1.03)
0.96 (0.9;
1.03)
0.96 (0.91;
1.02)
0.97 (0.92;
1.01)
0.97 (0.93;
1.02)
0.98 (0.91;
1.04)
0.98
(0.9;
1.07)
0.99 (0.88;
1.11)
42 0.011 0.503 0.127
Stroke mor-
tality
8 (6) 1 (ref.) 1.03 (0.98;
1.08)
1.05 (0.96;
1.14)
1.04 (0.95;
1.14)
1 (0.93;
1.07)
0.95 (0.86;
1.04)
0.9 (0.77;
1.05)
0.86 (0.69;
1.06)
0.81
(0.62;
1.08)
0.77 (0.55;
1.1)
38 0.063 0.174 0.727
Stroke,
ischemic
incidence
11 (9) 1 (ref.) 0.99 (0.96;
1.02)
0.98 (0.93;
1.04)
0.97 (0.91;
1.05)
0.97 (0.91;
1.04)
0.97 (0.92;
1.04)
0.98 (0.93;
1.03)
0.98 (0.93;
1.03)
0.98
(0.93;
1.04)
0.99 (0.93;
1.05)
69 < 0.001 0.584 0.855
Stroke,
hemor-
rhagic
incidence
10 (8) 1 (ref.) 0.97 (0.93;
1.02)
0.95 (0.88;
1.03)
0.94 (0.84;
1.04)
0.94 (0.84;
1.05)
0.95 (0.84;
1.07)
0.96 (0.83;
1.12)
0.98 (0.8;
1.19)
0.99
(0.78;
1.27)
1.01 (0.75;
1.36)
88 < 0.001 0.347 0.919
Heart
failure
6 (4) 1 (ref.) 1.01 (0.96;
1.05)
1.01 (0.93;
1.1)
1.02 (0.91;
1.15)
1.04 (0.92;
1.19)
1.07 (0.95;
1.21)
1.11 (0.99;
1.25)
1.15 (1.02;
1.30)
1.19
(1.04;
1.36)
1.23 (1.06;
1.44)
37 0.103 0.409 0.630
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1852 European Journal of Nutrition (2021) 60:1833–1862
1 3
reduced with up to one egg per day compared to no con-
sumption (ESM Table3).
Subgroup analyses
The subgroup analysis including results on cohort restricted
to diabetic individuals showed that the direction of the risk
associated with egg consumption was substantially inverted
for all outcomes (Table3); among all of them, the risk of
CVD incidence/mortality peaked up to one egg per day
[SRR = 1.22 (95% CI: 1.08; 1.39), I2 = 63%)] compared to
no consumption.
The subgroup analysis by sex revealed a different relation
with risk of CVD, CHD, and heart failure in women than
in men. Among women a decreased risk of all outcomes for
consumption of 4 eggs per week [SRR = 0.89 (95% CI: 0.82;
0.96), SRR = 0.89 (95% CI: 0.82; 0.98), and 0.84 (95% CI:
0.71; 1.00), respectively] with no evidence of heterogeneity
between studies was observed (Table3). When consider-
ing consumption of one egg per day, only CVD risk was
decreased in women [SRR = 0.90 (95% CI: 0.81; 1.00)], with
no evidence of heterogeneity (I2 = 0%) (Table3). No sig-
nificant associations were observed among men (Table3).
Stratified analyses
Several stratified analyses have been performed to test the
stability of results taking into consideration the geographical
localization of the cohorts as well as the level of adjustment
models and the quality of the studies included. The analyses
have been considered for a moderate consumption (four eggs
per week) and a habitual consumption (one egg per day).
Concerning the intake of 4 eggs/week, the decreased risk
of CVD was confirmed when restricting the analyses to the
majority of better quality studies, such as those adjusting for
BMI, other dietary factors, longer follow-up, larger sample
size, including heart failure in the definition of CVD, and
scoring moderate risk of bias (Table4); other strata associ-
ated with a decreased risk of CVD where studies conducted
in US cohorts. Similar associations were retrieved for risk
of CHD, with a direction toward reduction when restricting
the analysis to studies adjusting for other dietary factors,
longer follow-up and low risk of bias (Table4). No associa-
tion between moderate egg consumption and risk of stroke
nor heart failure was found (Table4).
Concerning the intake of 1 egg/day, the analysis resulted
in a decreased risk of CVD when involving studies con-
ducted in Asia and adjusting for other dietary factors
(Table4); curiously, a decreased risk was also observed in
studies not adjusting for diabetic status, which on the con-
trary was reported to potentially act as effect modifier toward
the opposite direction. No associations were retrieved for
CHD risk, while also the risk of stroke was reduced only
when considering Asian cohorts and studies including more
than 10,000 individuals (Table4). Also risk of heart fail-
ure differed between strata, resulting higher in the analysis
restricted to US cohorts with large sample size, adjusted for
BMI but not for other dietary factors; no study with low risk
of bias was available (Table4).
Evaluation oftheevidence
Table5 provides an overview of the GRADE assessment
for the association between consumption of eggs and each
cardiovascular outcome. The level of evidence was rated
generally low for all outcomes but stroke, for which was
moderate.
Discussion
The present meta-analysis provided an updated overview
on the association between egg consumption and CVD risk
and mortality: compared to previous meta-analyses, we
included the highest number of cohorts reviewed to date,
several dose–response analyses for the investigated out-
comes, a detailed investigation for potential confounding
factors by studying subgroups and stratifying the analyses,
and we attempted an evaluation of the overall evidence. Pre-
vious meta-analyses reported rather mixed results, with no
association with stroke risk [55], decreased risk of stroke
and no association with CHD [56, 57], decreased risk of
CHD [58], no association with CVD risk [59], increased
risk of heart failure [60, 61],compared to these studies, our
analysis is more complete and provides a general more in
depth analysis of level of evidence. We generally found no
strong association with either increased or decreased risk of
cardiovascular outcomes following the habitual consumption
of eggs (i.e., one egg per day compared to no intake), with
exception of risk of heart failure, which resulted higher espe-
cially in men from US cohorts. In contrast, there are more
consistent results regarding the association between mod-
erate egg consumption (i.e., four eggs per week compared
to no intake) and lower risk of CVD, especially in spite of
the stratified analyses involving higher quality studies, for
which there was lower heterogeneity across results. Also
when considering the findings from the stratified analyses,
heterogeneity of the results between studies remained sig-
nificant and rather unexplained. We can hypothesize that
egg consumption between men and women or across differ-
ent geographical areas may be associated with unmeasured
lifestyle choices or in the context of different quality of the
overall diet to motivate the differences observed in these
strata, another hypothesis is that these strata may also reflect
genetic unmeasured factors motivating the inter-individual
variations. After the GRADE assessment, we could not
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1853European Journal of Nutrition (2021) 60:1833–1862
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Table 3 Subgroup analyses for the association between 4 eggs/week and 1 egg/day consumption and CVD, CHD, stroke, and heart failure
CVD CHD Stroke Heart failure
Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) ph et Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet
4 eggs/week
Sex
Men 2 (2) 1.04
(0.92;
1.17)
0 0.398 7 (7) 1.03
(0.96;
1.1)
2 0.426 7 (7) 0.99
(0.91;
1.08)
57 0.006 3 (3) 1.05
(0.94;
1.18)
0 0.449
Women 2 (1) 0.89
(0.82;
0.96)
0 0.772 5 (4) 0.89
(0.82;
0.98)
0 0.884 5 (4) 1.05
(0.86;
1.3)
33 0.153 1 (1) 0.84
(0.71;
1)
0NA
Diabetic indi-
viduals
6 (6) 1.22
(0.88;
1.71)
63 0.002 4 (4) 1.19
(0.82;
1.74)
80 < 0.001 5 (5) 1.22
(0.84;
1.77)
57 0.016 1 (1) 1.43
(0.92;
2.22)
0NA
1 egg/day
Sex
Men 2 (2) 1.09
(0.89;
1.34)
0 0.398 7 (7) 0.99
(0.89;
1.09)
2.07 0.426 7 (7) 0.94
(0.75;
1.18)
57 0.006 3 (3) 1.21
(1.01;
1.45)
0 0.449
Women 2 (1) 0.9 (0.81;
1.00)
0 0.772 5 (4) 0.92
(0.81;
1.04)
0.00 0.884 5 (4) 1.04
(0.83;
1.32)
33 0.153 1 (1) 0.94
(0.75;
1.18)
0NA
Diabetic indi-
viduals
6 (6) 1.22
(1.08;
1.39)
63 0.002 4 (4) 1.25
(0.89;
1.75)
80 < 0.001 5 (5) 1.33
(0.87;
2.05)
57 0.016 1 (1) 1.35
(0.85;
2.13)
0NA
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1854 European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 4 Stratified analyses for the association between 4 eggs/week and 1 egg/day consumption and CVD, CHD, stroke, and heart failure
CVD CHD Stroke Heart failure
Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet
4 eggs/week
Location
USA 5 (3) 0.94
(0.89;
0.99)
20 0.264 10 (6) 0.98
(0.89;
1.09)
70 < 0.001 9 (6) 0.98
(0.91;
1.04)
56 0.002 1 (1) 1.05
(0.88;
1.26)
0NA
Europe 5 (5) 1.07
(0.94;
1.22)
0 0.883 5 (4) 0.98
(0.92;
1.03)
0 0.756 5 (4) 1.01 (0.9;
1.14)
27 0.204 3 (2) 0.99
(0.81;
1.21)
29 0.225
Asia 5 (5) 0.93
(0.84;
1.04)
90 < 0.001 7 (5) 0.92
(0.77;
1.09)
90 < 0.001 6 (5) 0.93
(0.81;
1.07)
63 0.002 – – – –
Adjusted for BMI
No 2 (2) 0.97
(0.76;
1.24)
78 0.010 2 (2) 0.95
(0.56;
1.6)
89 < 0.001 2 (2) 0.99
(0.89;
1.09)
13 0.313 1 (1) 1.05
(0.82;
1.35)
0NA
Yes 15 (13) 0.94
(0.89;
0.99)
72 < 0.001 22 (15) 0.95
(0.89;
1.02)
82 < 0.001 20 (15) 0.98
(0.92;
1.03)
48 0.001 5 (4) 1.04 (0.9;
1.22)
39 0.104
Adjusted for diabetic
status
No 8 (6) 0.91
(0.86;
0.96)
80 < 0.001 7 (5) 0.93
(0.81;
1.06)
93 < 0.001 7 (5) 0.91
(0.82;
1.01)
18 0.259 – – – –
Yes 9 (8) 0.98 (0.9;
1.07)
48 0.014 17 (12) 0.96
(0.89;
1.04)
50 < 0.001 15 (11) 1.01
(0.96;
1.06)
49 0.002 6 (4) 1.04
(0.92;
1.19)
37 0.103
Adjusted for other
dietary factors
No 3 (3) 0.98
(0.86;
1.11)
63 0.028 6 (5) 1.06
(0.95;
1.19)
42 0.065 7 (6) 0.99
(0.91;
1.08)
30 0.142 1 (1) 1.05
(0.88;
1.26)
0NA
Yes 14 (11) 0.94
(0.88; 1)
72 < 0.001 18 (13) 0.92
(0.85;
0.99)
84 < 0.001 15 (10) 0.96
(0.91;
1.02)
51 0.001 5 (3) 1.05
(0.88;
1.24)
35 0.137
Follow-up, years
< 10 7 (6) 0.99
(0.89;
1.09)
62 0.002 5 (4) 0.94
(0.77;
1.16)
94 < 0.001 3 (2) 1.03
(0.91;
1.17)
29 0.228 2 (1) 1.17
(0.94;
1.46)
2 0.359
> = 10 10 (8) 0.93
(0.87; 1)
43 0.024 19 (13) 0.94
(0.89;
0.99)
62 < 0.001 19 (14) 0.96
(0.92;
1.02)
47 0.001 4 (3) 0.99
(0.86;
1.15)
35 0.159
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1855European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 4 (continued)
CVD CHD Stroke Heart failure
Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet
Sample size
< 10,000 4 (4) 1.06 (0.9;
1.25)
0 0.418 7 (5) 1.08
(0.86;
1.34)
0 0.790 7 (5) 1.16
(0.91;
1.47)
69 < 0.001 1 (1) 1.38
(0.81;
2.34)
0NA
> = 10,000 13 (10) 0.94
(0.89; 1)
74 < 0.001 17 (12) 0.94
(0.87;
1.01)
87 < 0.001 15 (11) 0.98
(0.92;
1.03)
24 0.116 5 (3) 1.02 (0.9;
1.16)
40 0.094
Study quality
Moderate risk of bias 12 (10) 0.95
(0.91;
0.99)
27 0.115 16 (11) 0.95
(0.88;
1.02)
82 < 0.001 13 (9) 0.98
(0.93;
1.03)
38 0.03 4 (3) 0.99
(0.86;
1.15)
35 0.159
Serious risk of bias 5 (4) 0.95
(0.82;
1.09)
79 < 0.001 8 (6) 0.92
(0.75;
1.12)
66 < 0.001 9 (7) 0.97
(0.87;
1.07)
59 0.001 2 (1) 1.17
(0.94;
1.46)
2 0.359
Inclusion of HF in
CVD outcome
No 7 (7) 1.01
(0.94;
1.09)
5 0.399 – – – – – – – – – – – –
Yes 7 (7) 0.89
(0.84;
0.94)
84 < 0.001 ––––––––––––
1 egg/day
Location
USA 5 (3) 0.97 (0.9;
1.05)
20 0.264 10 (6) 1.05
(0.98;
1.13)
70 < 0.001 9 (6) 0.96
(0.79;
1.16)
56 0.002 1 (1) 1.32
(1.11;
1.58)
0NA
Europe 5 (5) 1.17
(0.95;
1.43)
0 0.883 5 (4) 0.97
(0.86;
1.09)
0 0.756 5 (4) 1.04
(0.82;
1.33)
27 0.204 3 (2) 1.08
(0.88;
1.32)
29 0.225
Asia 5 (5) 0.92
(0.87;
0.98)
90 < 0.001 7 (5) 0.95
(0.74;
1.21)
90 < 0.001 6 (5) 0.86
(0.79;
0.93)
63 0.002 – – – –
Adjusted for BMI
No 2 (2) 0.97
(0.82;
1.14)
78 0.010 2 (2) 0.98
(0.66;
1.46)
89 < 0.001 2 (2) 0.9 (0.73;
1.11)
13 0.313 1 (1) 1.02
(0.81;
1.29)
0NA
Yes 15 (13) 0.96
(0.91;
1.01)
72 < 0.001 22 (15) 0.98
(0.90;
1.07)
82 < 0.001 20 (15) 0.96
(0.89;
1.03)
48 0.001 5 (4) 1.19
(1.03;
1.38)
39 0.104
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1856 European Journal of Nutrition (2021) 60:1833–1862
1 3
Table 4 (continued)
CVD CHD Stroke Heart failure
Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet Datasets
(studies)
RR (95%
CI)
I2 (%) phet
Adjusted for diabetic
status
No 8 (6) 0.9 (0.88;
0.92)
80 < 0.001 7 (5) 0.98
(0.82;
1.17)
93 < 0.001 7 (5) 0.97
(0.85;
1.1)
18 0.259 – – – –
Yes 9 (8) 1 (0.93;
1.07)
48 0.014 17 (12) 0.97
(0.92;
1.02)
50 < 0.001 15 (11) 0.98
(0.86;
1.1)
49 0.002 6 (4) 1.15
(1.02;
1.3)
37 0.103
Adjusted for other
dietary factors
No 3 (3) 1.01
(0.93;
1.09)
63 0.028 6 (5) 1.04
(0.92;
1.18)
42 0.065 7 (6) 0.93
(0.85;
1.03)
30 0.142 1 (1) 1.32
(1.11;
1.58)
0NA
Yes 14 (11) 0.95 (0.9;
1)
72 < 0.001 18 (13) 0.97
(0.88;
1.07)
84 < 0.001 15 (10) 0.95
(0.87;
1.04)
51 0.001 5 (3) 1.11
(0.96;
1.28)
35 0.137
Follow-up, years
< 10 7 (6) 0.96 (0.9;
1.02)
62 0.002 5 (4) 0.98
(0.79;
1.21)
94 < 0.001 3 (2) 0.97
(0.86;
1.08)
29 0.228 2 (1) 1.16
(0.86;
1.57)
2 0.359
> = 10 10 (8) 0.97 (0.92;
1.03)
43 0.024 19 (13) 0.97 (0.92;
1.03)
62 < 0.001 19 (14) 0.95 (0.88;
1.03)
47 0.001 4 (3) 1.14 (0.98;
1.34)
35 0.159
Sample size
< 10,000 4 (4) 1.16
(0.82;
1.64)
0 0.418 7 (5) 1.04
(0.79;
1.36)
0 0.790 7 (5) 1.21
(0.63;
2.32)
69 < 0.001 1 (1) 1.14
(0.61;
2.12)
0NA
> = 10,000 13 (10) 0.96
(0.91;
1.01)
74 < 0.001 17 (12) 0.98 (0.9;
1.07)
87 < 0.001 15 (11) 0.96
(0.91; 1)
24 0.116 5 (3) 1.15 (1;
1.31)
40 0.094
Study quality
Moderate risk of bias 12 (10) 0.97
(0.91;
1.05)
27 0.115 16 (11) 0.96
(0.88;
1.05)
82 < 0.001 13 (9) 0.99
(0.89;
1.1)
38 0.03 4 (3) 1.14
(0.98;
1.34)
35 0.159
Serious risk of bias 5 (4) 0.97
(0.88;
1.06)
79 < 0.001 8 (6) 1.04
(0.84;
1.28)
66 < 0.001 9 (7) 0.9 (0.81;
0.99)
59 0.001 2 (1) 1.16
(0.86;
1.57)
2 0.359
Inclusion of HF in
CVD outcome
No 7 (7) 1.03
(0.97;
1.1)
5 0.399 – – – – – – – – – – – –
Yes 7 (7) 0.9 (0.88;
0.92)
84 < 0.001 ––––––––––––
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1857European Journal of Nutrition (2021) 60:1833–1862
1 3
conclude that exist strong evidence of association between
egg consumption and CVD outcomes, but higher quality
studies showed a decreased risk of CVD for moderate intake
of eggs (four per week), while higher risk of heart failure
was found for higher intake of egg (one per day). Interpre-
tation of these findings is not easy: consuming up to four
eggs per week may decrease the risk of CVD but increasing
the intake to one egg per day or more may not be beneficial
anymore. Nonetheless, we cannot exclude that the pattern
of the diet and way of cooking might differ depending on
the frequency of consumption (i.e., individuals with moder-
ate egg consumption may include eggs into specific recipes
varying the way of cooking while habitual consumers may
have fried eggs for breakfast together with bacon or other
unhealthy dietary features). Such hypothesis could explain
the different risks associated with egg consumption in West-
ern and Eastern Asian countries. This is a common issue
for nearly all food groups when investigating the relation of
one single dietary element with health. However, we cannot
ignore that an association can be observed and, in that case,
needs further attention.
There is a biological rationale to explain how moderate
egg consumption might be associated to decreased risk of
CVD. Eggs have been historically considered a controver-
sial food for nutritional experts and health agencies due to
its content in cholesterol. However, researchers argue that
the focus of common dietary guidelines on specific nutri-
ents (i.e., saturated fats) do not take into account that health
effects varies depending on the specific food source [62].
Furthermore, the major attention paid to egg consump-
tion has been based on the assumption that higher dietary
cholesterol intake would lead to rise in blood cholesterol,
despite current evidence suggests otherwise [63, 64]. Recent
meta-analyses showed rise of both LDL and HDL follow-
ing egg consumption in healthy individuals, with minimum
rise of LDL:HDL ratio (marker of CVD risk) finally lead-
ing to no substantial increased risk profile [63, 64]. Thus,
the concomitant rise of HDL cholesterol might counteract
the elevation of LDL, while other components of egg might
exert potential beneficial effects [65]. Eggs are a highly
nutritious food providing quality proteins and supplying
micronutrients, antioxidants, antimicrobials, accompanied
with great culinary versatility, which may have potential
benefits to overall health. Some egg proteins, such as phosvi-
tin, ovotransferrin and ovalbumin can inhibit lipid oxidation
by binding to metal or scavenging free radical [66]. In addi-
tion to protein, eggs also contain a large number of active
lipid components, such as unsaturated fatty acids, phospho-
lipids, choline, and carotenoids. Eggs are considered a valu-
able source of omega-3 polyunsaturated fatty acids, which
have been considered to exert a number of health benefits,
including CVD protection [67]. Eggs are a major source
of choline, an essential nutrient with critical roles in sev-
eral biological processes including neuronal development,
cell signaling, and lipid transport and metabolism [68]. Part
of the choline may undergo conversion to trimethylamine
by gut microbiota, which in turn is oxidized in the liver to
trimethylamine-N-oxide (TMAO), agent associated with
increased atherosclerosis in the coronary vasculature [69].
Double blinded clinical trial investigating the effect of 0 to 6
egg yolks ingested for the breakfast demonstrated that con-
sumption of ≥ 2 eggs results in an increased formation of
TMAO yet not accompanied by a rise in hsCRP and oxidized
LDL levels [70]. Phospholipids contained in eggs, including
phosphatidylcholine, phosphatidylethanolamine, lysophos-
phatidylcholine, sphingomyelin, and some neutral lipids in
minor quantities, may have, among others, broad effects on
cholesterol metabolism, HDL functions, and inflammation
[71]. Egg yolks are also a dietary source of bioavailable
xanthophyll carotenoids, such as lutein and zeaxanthin, that
have been shown to exert potential benefits against inflam-
mation and oxidation during early development, childhood,
and may have lifetime consequences in determining health
or onset of major diseases in the adult life [72].
Despite the evidence reported, nearly all analyses showed
substantial heterogeneity of results between studies, lead-
ing to a weakening of the evidence. We hypothesize that
the certain inconsistency of the results may depend on
the variability of response to dietary cholesterol between
individuals and the overall dietary and lifestyle framework
within populations and individuals. Despite the majority of
population experience moderate to no difference in blood
cholesterol following the intake of dietary cholesterol (con-
sequently described as “normal responders”), about a third
Table 5 Certainty of evidence by GRADE criteria
a Despite better quality studies provided less heterogeneity across
results
b The analyses showed no evidence for non-linearity of associations
CVD CHD Stroke Heart failure
No. of studies 17 (14) 24 (16) 22 (16) 6 (4)
Downgrade quality of
evidence
Risk of bias No No No No
Inconsistency Yes Ye s No No
Indirectness No No No Yes
Imprecision No No No No
Publication Bias No No No No
Upgrade quality of
evidence
Large effect No No No No
Plausible confounding NoaNoaNo No
Dose–response Yes bNo YesbYe s b
Overall quality of evi-
dence
Low Low Moderate Low
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1858 European Journal of Nutrition (2021) 60:1833–1862
1 3
of individuals suffer of an abnormal rise in circulating LDL
cholesterol (thus described as “hyper responders”) as a result
of an increase fractional absorption and/or endogenous cho-
lesterol synthesis in response to dietary cholesterol intake
[73]. An abnormal response to dietary cholesterol has been
hypothesized to depend on altered cholesterol transport
due to decreased levels of apolipoprotein E and increased
of apolipoprotein C-III [74, 75]. Some genes responsible
for intestinal absorption and biliary secretion of cholesterol
and phytosterols, such as expression of ATP-binding cassette
(ABC) transporters G5 (ABCG5) and G8 (ABCG8) [76],
have been proposed as candidates for better understanding
of potential genetic influences on egg metabolism. These
genetic variants might provide the rationale, at least in part,
for the geographical and sex differences observed in this
study: however, further studies are warranted to identify
other genetic markers that may explain the observed vari-
ability in cholesterol absorption/production among the gen-
eral population.
The results of this meta-analysis on heart failure seems
to provide indication of potential increased risk for habit-
ual consumption (one egg per day) despite this evidence
was affected by some limitations, including the role of sex:
while sex seems to act as confounding factor for CVD,
the observed variation in the direction for risk heart fail-
ure (increased in men and decreased in women) may lead
to consider sex as an effect modifier. The reasons for such
finding is not clear. The role of cholesterol abnormalities
and risk or worsening of heart failure is unknown; data on
worsening heart failure and lipid moieties are now beginning
to emerge but conclusions are far to be made [77]. The fact
that heart failure was the only outcome potentially at higher
risk following consumption of eggs suggests that alternative
mechanisms could be responsible for the observed associa-
tion. Interpretation of these differences between sexes makes
even harder to provide a rationale for this result: as suggested
in the individual studies included in the meta-analysis, it
may be possible that the observed difference between sexes
may depend on the fact that men might be more sensitive
to high consumption of eggs (or cholesterol) than women,
or it could be mediated by uncontrolled risk factors asso-
ciated with egg consumption (i.e., bacon) occurring more
in men than women. Another hypothesis is that individuals
more sensible to dietary cholesterol presenting blood lipids
abnormalities may be regular users of statins, which in turn
are known to increase the risk of atherosclerosis and heart
failure by promoting arteries calcification and inhibiting the
biosynthesis of selenium containing proteins, respectively
[78]: this might explain the mixed results for CHD risk and
increased risk of heart failure.
Another concern regard the different risk estimates
observed in diabetic individuals showing an increased risk
of CVD associated with consumption of one egg per day,
notably in the different direction than for the general popu-
lation. The increased risk of developing CVD among indi-
viduals with type 2 diabetes may be mainly attributed to the
impaired cholesterol absorption and synthesis. Studies on
type 2 diabetic patients with uncontrolled hyperglycemia
showed higher cholesterol synthesis and plasma lipid con-
centrations [79], including total cholesterol and triglycer-
ide, suggesting unfavorable effects of egg consumption on
lipid profiles and, consequently, CVD risk. The mechanism
might be explained, at least partially, by a reduced plasma
level of campesterol, a marker of cholesterol absorption, and
increased plasma levels of lathosterol, a marker of choles-
terol synthesis among diabetic people [80]. Moreover, apoli-
poprotein E polymorphism has been associated with higher
risk of diabetes, and thus diabetic individuals tend to have
lower serum levels of apolipoptorein E and impaired lipid
transport [81].
The findings reported in this study should be considered
in light of some limitations. First, some analyses showed
substantial heterogeneity: several reasons for such discrep-
ancy of results across studies have been aforementioned,
but no firm explanation can be drafted at this moment due
to lack of data. Second, we stratified the analyses testing the
role of controlling for potential confounding factors known
to be related to cardiovascular outcomes in the original stud-
ies and revealed the importance of conducting higher qual-
ity studies to observe a decreased risk of CVD associated
with moderate egg consumption; however, we cannot rule
out the possibility that residual or unmeasured confounding
may persist. Third, time-related variables, including poten-
tial reverse causation (i.e., change in dietary intake due to
diagnosed medical condition or disease), period of evalu-
ation (i.e., baseline assessment or repeated over time), or
duration of egg intake have been not investigated. Finally,
the GRADE system may not be the best suit for assessing
evidence in nutritional epidemiology, as by definition it
tends to underestimate the strength of the evidence due to
the observational nature of the studies. However, it helps
to have a clearer idea of which can be the strengths and
weaknesses of the studies evaluated (i.e., results from better
quality studies are less heterogeneous and tend to show a
decreased risk of CVD for moderate egg consumption) and
a guide for future investigations.
Conclusion
Given the inconsistency of current findings on egg consump-
tion and risk of CVD, future studies should improve the
characterization of the population investigated, aiming to
identify and remove genetic bias, such as the determinants
of normal/hyper-response to dietary cholesterol. However,
current evidence is not sufficient to address egg consumption
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1859European Journal of Nutrition (2021) 60:1833–1862
1 3
as unhealthy nor to generalize potential detrimental effects
to the whole population. While waiting for better designed
and more complete studies overcoming the aforementioned
limitations and lack of information on genetic profile, there
may be no need to discourage egg consumption at the popu-
lation level.
Author contributions Conceptualization: JG, GG; methodology: JG,
GG; formal analysis and investigation: AM, GG; writing—original
draft preparation: JG, GG; writing—review and editing: TB, ET, LI,
AA, OHF, FG, MAMG, GG; supervision: MAMG, GG.
Funding This study was partially supported by a fund from the Italian
Ministry of Health “Ricerca Corrente” (RC no. 2751594) (Dr. Godos).
Open access funding provided by Università degli Studi di Catania
within the CRUI-CARE Agreement.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Ethical approval The manuscript does not contain clinical studies or
patient data.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
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Aliations
JustynaGodos1· AgnieszkaMicek2· TomaszBrzostek3· EstefaniaToledo4,5,6· LiciaIacoviello7,8· ArneAstrup9·
OscarH.Franco10,11· FabioGalvano12· MiguelA.Martinez‑Gonzalez4,5,6,13· GiuseppeGrosso12
1 Oasi Research Institute, IRCCS, Troina, Italy
2 Department ofNursing Management andEpidemiology
Nursing, Faculty ofHealth Sciences, Jagiellonian University
Medical College, Kraków, Poland
3 Department ofInternal Medicine andCommunity Nursing,
Faculty ofHealth Sciences, Jagiellonian University Medical
College, Kraków, Poland
4 Department ofPreventive Medicine andPublic Health,
School ofMedicine, University ofNavarra, Pamplona,
Navarre, Spain
5 CIBER Physiopathology ofObesity andNutrition
(CIBEROBN), Carlos III Institute ofHealth, Madrid, Spain
6 Navarra Institute forHealth Research, IdiSNA, Pamplona,
Navarre, Spain
7 Department ofEpidemiology andPrevention, IRCCS
NEUROMED, Pozzilli, IS, Italy
8 Department ofMedicine andSurgery, Research Centre
inEpidemiology andPreventive Medicine (EPIMED),
University ofInsubria, Varese, Italy
9 Department ofNutrition, Exercise, andSports, Faculty
ofScience, University ofCopenhagen, Nørre Campus,
Copenhagen, Denmark
10 Department ofEpidemiology, Erasmus MC, University
Medical Center Rotterdam, Rotterdam, Netherlands
11 Institute ofSocial andPreventive Medicine, University
ofBern, Bern, Switzerland
12 Department ofBiomedical andBiotechnological Sciences,
University ofCatania, Via S. Sofia 97, 95123Catania, Italy
13 Department ofNutrition, Harvard T.H. Chan School
ofPublic Health, Boston, MA, USA
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