(2023) 21:81
Shannon et al. BMC Medicine
https://doi.org/10.1186/s12916-023-02772-3

BMC Medicine

RESEARCH ARTICLE

Open Access

Mediterranean diet adherence is associatedwith lower dementia risk, independentof genetic predisposition: findings from the UK
Biobank prospective cohort study
Oliver M. Shannon1†, Janice M. Ranson2†, Sarah Gregory3, Helen Macpherson4, Catherine Milte4,
Marleen Lentjes5, Angela Mulligan6, Claire McEvoy7, Alex Griffiths8, Jamie Matu8, Tom R. Hill1, Ashley Adamson1,
Mario Siervo9, Anne Marie Minihane10,11, Graciela Muniz‑Tererra3,12, Craig Ritchie3, John C. Mathers1*,
David J. Llewellyn2,13† and Emma Stevenson1†

Abstract
Background The identification of effective dementia prevention strategies is a major public health priority, due
to the enormous and growing societal cost of this condition. Consumption of a Mediterranean diet (MedDiet) has
been proposed to reduce dementia risk. However, current evidence is inconclusive and is typically derived fromsmall cohorts with limited dementia cases. Additionally, few studies have explored the interaction between diet andgenetic risk of dementia.
Methods We used Cox proportional hazard regression models to explore the associations between MedDiet adher‑
ence, defined using two different scores (Mediterranean Diet Adherence Screener [MEDAS] continuous and Mediter‑
ranean diet Pyramid [PYRAMID] scores), and incident all-cause dementia risk in 60,298 participants from UK Biobank,followed for an average 9.1 years. The interaction between diet and polygenic risk for dementia was also tested.
Results Higher MedDiet adherence was associated with lower dementia risk (MEDAS continuous: HR = 0.77, 95%
CI = 0.65–0.91; PYRAMID: HR = 0.86, 95% CI = 0.73–1.02 for highest versus lowest tertiles). There was no significant
interaction between MedDiet adherence defined by the MEDAS continuous and PYRAMID scores and polygenic riskfor dementia.
Conclusions Higher adherence to a MedDiet was associated with lower dementia risk, independent of genetic risk,
underlining the importance of diet in dementia prevention interventions.
Keywords Dementia, Alzheimer’s, Mediterranean diet, Genetics, Polygenic risk, Risk factors, UK Biobank†

Oliver M. Shannon and Janice M. Ranson are shared first authors.

†

David J. Llewellyn and Emma Stevenson are shared last authors.

*Correspondence:John C. Mathers
John.Mathers@Newcastle.ac.uk
Full list of author information is available at the end of the article© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
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Shannon et al. BMC Medicine(2023) 21:81

Background
Preventing dementia is a global public health priority due
to the enormous and growing societal cost of this condition [1]. A key strategy to reduce dementia incidence
is the identification of modifiable risk factors that canbe targeted by personalized or public health interventions. These modifiable risk factors, in combination withgenetic risk, play a key role in determining individual
risk of Alzheimer’s disease and other forms of dementia [2–4]. Diet is an important modifiable risk factor for
dementia that could be targeted for disease prevention
and risk reduction [5, 6]. Healthier dietary patterns, especially the Mediterranean diet (MedDiet), have been proposed as a strategy to reduce dementia risk [7, 8]. Recent
systematic [9] and umbrella [10] reviews have suggested
higher adherence to the MedDiet may reduce cognitive
decline, although evidence for a protective role of the
MedDiet against dementia risk is inconsistent [11–16].
As most prior studies have been conducted in relatively
small cohorts (n = 1000–6000) with limited numbers ofdementia cases (n = 20–400), additional investigations
which leverage large population-based cohorts are warranted. There is also currently no gold standard assessment of MedDiet adherence, and some variability instudy findings may therefore be due to different dietaryassessment methods and scoring systems [17]. Therefore,studies comparing different MedDiet scores directly andtheir associations with dementia risk are needed.
A healthy diet might also mitigate individual genetic
risk for dementia. Previous studies exploring gene-dietinteractions are limited, have reported inconsistent
results, and, typically, focus on APOE genotype as thesole measure of genetic risk [13, 18–20]. Polygenic risk
scores combining information from multiple weighted(i.e., according to the strength of their association withdementia) risk alleles predict incident all-cause dementia[21, 22] and are an important advance in facilitating indepth exploration of potential gene-diet interactions.
The purpose of this study was to investigate associations between MedDiet adherence and dementia
incidence in a large prospective cohort study, and to
explore the interaction between diet and genetic risk fordementia.
Methods
Study population and design

The UK Biobank is an ongoing, multi-centre prospective cohort study of over half a million participants, thatprovides a resource for investigating the determinantsof disease in middle and older age [23]. The design andmethods of this study have been described elsewhere[24]. Briefly, between 2006 and 2010, men and women

Page 2 of 13

aged 40–69 years were recruited from across England,
Scotland and Wales using National Health Service (NHS)
patient registers. Participants attended one of 22 assessment centres where they completed a touchscreen questionnaire, verbal interview, and provided measures ofphysical function alongside biological samples. Subsequently, participants were invited to complete additional
measures, including enhanced dietary assessments, imaging, and assessment of multiple health-related outcomes.
UK Biobank also includes linkage to electronic healthcare records (death, cancer, inpatient and primary carerecords) for disease ascertainment. Ethical approval for
the UK Biobank study was provided by the North West–
Haydock Research Ethics Committee (REC reference:
16/NW/0274), and all participants provided electronic
signed consent. The current study included participants
who self-reported a racial/ ethnic background of white
British, Irish or other white, were aged ≥ 60 years at
recruitment with genetic data, appropriate dietary data
(self-reported atypical dietary reports were excluded)
and were not missing data for any of the included covariates (Additional file 1, Fig. S1).
Dietary assessment and calculation of Mediterranean dietscoresThe Oxford WebQ is a web-based, self-administered 24-h
dietary assessment tool, validated for use in large-scaleobservational studies [25, 26]. This tool collects information about the consumption of 206 types of foods and32 types of drinks during the previous 24-h period, withparticipants selecting the number of standard portions
for each item that they consumed. Participants recruited
between April 2009 and September 2010 completed theOxford WebQ as part of their baseline assessment centre visits. In addition, between February 2011 and June
2012, participants were invited to complete the Oxford
WebQ assessment via their home computer every three
to four months, up to a total of five assessments (including the baseline assessment). Consistent with previous
investigations [17, 27], we energy-adjusted the dietarydata (2000 kcal/d) for each time point via the residuals
method to allow evaluation of diet quality independentof diet quantity [28]. Data were then averaged across all
available time points (minimum 1, maximum 5) for eachparticipant prior to calculation of MedDiet scores.
We quantified MedDiet adherence using two separate scores: the MedDiet Adherence Screener (MEDAS)
score, and the MedDiet PYRAMID score. These scores
define MedDiet adherence in different ways (e.g., using
different dietary targets and food components) andtherefore may differ in terms of their association withdementia.

Shannon et al. BMC Medicine(2023) 21:81

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MEDAS score

PYRAMID score

The MEDAS is a 14-point score developed as part of
the Prevención con Dieta Mediterránea (PREDIMED)
trial [29] that has been used widely in trials and observational studies [8, 30]. The MEDAS has been validated for use in the UK (the UK-validated version of
the MEDAS was used to develop our MEDAS scoresin this study) [31] and endorsed for use as a rapid dietassessment screening tool in clinical practice by theAmerican Heart Association [32]. The MEDAS is conventionally calculated with a binary evaluation for eachof the 14 food components, with one point awarded
if the participant’s consumption meets a pre-defined
cut-off (e.g., intake of a specific amount of vegetables),and zero points if they do not. The total possible score
ranges from 0–14 points. We have shown previouslythat using the same dietary targets but implementing
an alternative continuous scoring system using linear
equation principles (y = ax + b, in which y is the number of points scored between 0 and 1, a is the slope
and b is the intercept), in which points are awarded
between zero and one depending upon proximity to the
dietary targets, increases the sensitivity of this score in
detecting differences in diet quality [17]. Therefore, thisscore, referred to here as the MEDAS continuous score,
was used for the primary analyses in the present study.
As a hypothetical example to illustrate the difference
between the MEDAS and MEDAS continuous scores,
an individual with a daily vegetable intake of 295 gor ~ 1.5 * 200 g servings of vegetables would be awarded
0 points for this specific MedDiet component for the
MEDAS score, as they have not achieved the dietary
target of 2 servings (i.e., 400 g) vegetable intake per day.
By contrast, according to the MEDAS continuous score,
this individual would be awarded ~ 0.74 points (y = 0.5* 1.475 + 0 = 0.7375 points), based around how close
they are to the specific dietary target (i.e., ~ 3/4 of theway towards achieving the dietary target). We repeatedthe analysis using the conventionally-scored MEDAS asa sensitivity analysis.
Both the MEDAS and MEDAS continuous scores
award points for use of olive oil as the main culinary fat
and, separately, for consumption of a target amount (4or more tablespoons per day) of olive oil. Although wewere able to determine use of olive oil as a culinary fat
and to award points for consumption (1 point) or nonconsumption (0 points) accordingly, it was not possible
to determine the amount of olive oil consumed fromthe available dietary data, limiting the maximum possible scores for the MEDAS and MEDAS continuous to
13 points in this study.

The PYRAMID score is a 15-point MedDiet score usedwidely in epidemiological studies [9, 17, 27]. Each of the
15 individual components are coded on a continuous
basis with scores ranging from zero to one (26). Further details of the calculation of each MedDiet score isprovided in Additional file 1, Tables S1 and S2. For both
MedDiet scores, higher values reflect greater adherence
to the MedDiet.
Polygenic risk score

To estimate genetic risk of dementia, we used the polygenic risk score developed by Lourida and colleagues,
who demonstrated that higher values of this score areassociated with higher all-cause dementia risk in the UK
Biobank cohort [22]. The score was based on a genomewide association study of individuals of European ancestry [33]. Therefore, the current analysis was restricted
to individuals who self-reported a racial/ ethnic background of white British, Irish or other white (who constitute > 90% of the UK Biobank cohort). For the primary
analyses, the polygenic risk score was divided into quintiles, and participants were categorised into low (quintile 1), medium (quintiles 2–4) and high (quintile 5) risk
groups. A total of 249,273 independent genetic variants were used to create the polygenic risk score. Further details of the polygenic risk score creation and thisapproach can be found elsewhere [22].
Dementia outcome ascertainment

All-cause incident dementia cases were ascertained using
data linkage to hospital inpatient records and death registries. Diagnoses were recorded using the International
Classification of Diseases (ICD) coding system [34].
Participants with a primary or secondary diagnosis ofdementia were identified from hospital records or underlying/contributory cause of death from death registries
using relevant ICD-9 and ICD-10 codes (Additional
file 1, Table S3.). We used the censoring dates recommended by UK Biobank for death data and hospital
inpatient data. These are the dates up to which the data
is estimated to be over 90% complete in England, Scotland and Wales separately. At the time of analysis, therecommended censoring dates were ­31st March, 2021 forEngland and Scotland, and 2­ 8th February, 2018 for Wales.
The mean (SD) and median (interquartile range) follow
up was 9.1 (1.7) and 9.3 (8.8–9.7) years, respectively. Follow up time was calculated from the most recent eligible
dietary report used for MedDiet score creation and either
the date of first dementia diagnosis, death, loss to followup, or censoring date, whichever was the earliest.

Shannon et al. BMC Medicine(2023) 21:81

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All analyses were conducted in SPSS version 27. Baseline characteristics of the analytic sample, stratified bydementia status, were summarised as mean ± SD for continuous variables and as percentages for categorical variables. Cox proportional hazard regression models wereused to examine the association between MedDiet adherence and time to incident all-cause dementia, with theduration of follow-up in years used as the timescale. We
also explored the association between the polygenic risk
score and dementia incidence, to confirm the previously
reported associations between these variables in thiscohort [22]. The possible interaction between MedDiet
adherence and polygenic risk for dementia was investigated by including an interaction term, with both variables expressed continuously.
Analyses were adjusted simultaneously for: age, sex,socioeconomic status (Townsend Index categorised as
low [quintile 1], moderate [quintiles 2–4], high [quintile
5] deprivation), education (higher [college/university/
other professional qualification], vocational [NVQ/HND/
HNC], upper secondary [A-levels], lower secondary[O-levels/GCSEs /CSEs] or none), smoking status (never,past, current), typical sleep duration (< 7, 7–8, > 8 h),physical activity (international physical activity questionnaire [IPAQ] group, categorised as low, medium, high),
energy intake (kcal/d), third-degree relatedness of individuals in the sample, and the first 20 principal components of ancestry. Models which included the polygenic
risk score were additionally adjusted for the number ofalleles included in the score, to account for SNP-levelvariation [22]diagnosed prior to dementia diagnosis or end of followup for those who remained dementia-free), self-reported
depressive symptoms (yes/no for reporting feeling down/
depressed/hopeless on ‘several days’, ‘more than half thedays’ or ‘nearly every day’), and body mass index (BMI)
category (< 25, 25–29.9, > 30 kg/m2). Seventh, as an alternative method of exploring whether associations between
MedDiet adherence and dementia risk were influenced
by polygenic risk score, we conducted stratified analyses
exploring associations between MedDiet adherence anddementia risk in low, medium and high genetic risk categories. Eighth, we investigated the interaction between
MedDiet adherence and genetic risk, with genetic risk
defined by Apolipoprotein E (APOE) genotype only
(a more common but less comprehensive measure ofgenetic risk, which may be easier to apply in clinicalpractice). APOE ε4 carriers were defined as higher risk,
whilst non-carriers were defined as lower risk. Nineth, toevaluate the influence of missing data, we repeated analyses following imputation of missing dietary and covariate data using multiple imputations by chained Eqs. (70imputations, 20 iterations) [36]. We included all analytic
variables (covariates and outcome data) as predictors in
the model. In addition, we created abbreviated MedDiet
scores using dietary data from the UK Biobank touchscreen questionnaire (data available for all participants)
which were used as auxiliary variables in the imputation
model. Tenth, we carried out separate analyses for fatal
and non-fatal cases of dementia. Eleventh, we conductedstratified analyses in individuals with higher (college/
university/other professional qualification) and lower(vocational, upper secondary, lower secondary, and none)
education levels.

Sensitivity analyses

Results

Sensitivity analyses were performed to test the robustnessof associations between MedDiet adherence and dementia incidence. First, we used the conventional binary
MEDAS score. Secondly, we included participants witha minimum of two, 24-h diet recalls to provide a more
stringent measure of habitual dietary intake [26]. Thirdly,
we excluded participants with 24-h recalls with extreme
energy intakes (defined as < 800 or > 4200 kcal/d for malesand < 600 or > 3500 kcal/d for females) [35]. Fourth, toassess whether any individual components of the MedDiet drove the observed associations, we repeated theanalyses after sequentially removing each MedDiet component from the total score. Fifth, in consideration of
the potential for reverse causality, we repeated the primary analyses after excluding participants with less than2- and less than 5-years of follow-up, respectively. Sixth,
we repeated the analyses including potential mediators
individually; stroke history (yes/no for any type of stroke

Cohort characteristics

Statistical analysis

A total of 502,536 participants underwent baseline
assessment as part of the UK Biobank study, of whom
60,298 participants were included in this analysis (SeeAdditional file 1, Fig. S1 for the study inclusion flow
diagram). Baseline characteristics of the participants,
stratified by level of MedDiet adherence (low, medium,and high MEDAS continuous scores), are provided inTable 1. During a mean (SD) follow up of 9.1 (1.7) years
and a total of 549,999 person years, there were 882 casesof incident all-cause dementia. Participants with a higher
MedDiet adherence according to the MEDAS continuousscore were more likely to be female, have a BMI within
the healthy range (< 25 kg/m2), have a higher educational
level, and be more physically active than those with lower
MedDiet adherence. The mean MEDAS continuousand PYRAMID scores in this cohort were 6.1 ± 1.7 and
7.5 ± 1.8, respectively.

Shannon et al. BMC Medicine(2023) 21:81

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Table 1 Participant characteristics of the analytic sample of UK Biobank, stratified by level of MedDiet adherence according to the
MEDAS continuous score

Age (mean ± SD), years
Sex

Total
(n = 60,298)

MEDAS continuous
low (0–5.3)(n = 19,393, 32.2%)

MEDAS continuous
medium (> 5.3–6.8)(n = 20,120, 33.4%)

MEDAS continuousHigh (> 6.8)
(n = 20,785, 34.5%)

63.8 ± 2.7

63.9 ± 2.8

63.9 ± 2.8

63.8 ± 2.7

Male

31,066 (51.5%)

11,252 (58%)

10,252 (51.0%)9562 (46.0%)

Female29,232 (48.5%)8141 (42.0%)9868 (49.0%)

11,223 (54.0%)

BMIa (kg/m2)  < 2525–29.9  > 3020,780 (34.5%)5526 (28.5%)6826 (33.9%)8428 (40.5%)

27,154 (45.1%)8835 (45.6%)

9259 (46.0%)9060 (43.6%)

12,229 (20.3%)4984 (25.7%)3994 (19.9%)3251 (15.6%)

Education
Higher

33,291 (55.2%)

8799 (45.4%)

11,162 (55.5%)

13,330 (64.1%)

Vocational

6143 (10.2%)

2391 (12.3%)2036 (10.1%)

1716 (8.3%)

Upper secondary

3377 (5.6%)1015 (5.2%)

1132 (5.6%)

1230 (5.9%)

Lower secondary

9270 (15.4%)

3387 (17.5%)

3161 (15.7%)

2722 (13.1%)

Other8217 (13.6%)

3801 (19.6%)

2629 (13.1%)

1787 (8.6%)

14,375 (23.8%)4279 (22.6%)

4987 (24.8%)5009 (24.1%)

Socioeconomic ­statusb
1 (least deprived)
2–4

38,142 (63.3%)

12,370 (63.8%)

12,774 (63.5%)

12,998 (62.5%)5 (most deprived)

7781 (12.9%)2644 (13.6%)2359 (11.7%)

2778 (13.4%)

Smoking status
Never

30,686 (50.9%)9645 (49.7%)

10,400 (51.7%)

10,641 (51.2%)

Previous

26,157 (43.4%)

8197 (42.3%)

8725 (43.4%)9235 (44.4%)

Current

3455 (5.7%)

1551 (8.0%)995 (4.9%)

909 (4.4%)

Typical sleep duration  < 7/hours

12,402 (20.6%)4252 (21.9%)4088 (20.3%)4062 (19.5%)

7–8 h42,813 (71%)

13,287 (68.5%)

14,346 (71.3%)

15,180 (72.0%)  > 8 h5083 (8.4%)

1854 (9.6%)

1686 (8.4%)

1543 (7.4%)

Physical activity ­levelsc
Low (least active)

9921 (16.5%)

3786 (19.5%)

3372 (16.8%)2763 (13.3%)

Moderate

26,021 (43.2%)

8339 (43.0%)8727 (43.4%)8955 (43.1%)

High (most active)

24,356 (40.4%)7268 (37.5%)8021 (39.9%)9067 (43.6%)

Genetic risk ­categorydLow

12,703 (21.1%)

4044 (20.9%)4104 (20.4%)4555 (21.9%)

Medium36,085 (59.8%)

11,594 (59.8%)

12,051 (59.9%)

12,440 (59.9%)High

11,510 (19.1%)

3755 (19.4%)3965 (19.7%)

3790 (18.2%)

Dementia incidenceabIncident dementia

882 (1.5%)

336 (1.7%)

301 (1.5%)245 (1.2%)

No incident dementia

59,416 (98.5%)

19,057 (98.3%)

19,819 (98.5%)

20,540 (98.8%)

BMI data available in n = 60,163 participants (incident dementia n = 876, no incidence dementia n = 59,287)

Socioeconomic status includes categories derived from Townsend deprivation index, with quintiles 1 = low (least deprived), 2–4 = medium, 5 = high (most deprived)cSelf-reported physical activity levels according to the International Physical Activity Questionnaire (IPAQ)

dGenetic risk category, with quintiles 1 = low, 2–4 = medium, 5 = highMediterranean diet adherence and risk of incident
dementia

Higher adherence to the MedDiet was associatedwith 4.2–6.9% lower risk for dementia for the MEDAS

continuous (HR per one point increase in MedDiet score:
0.931; 95% CI: 0.895–0.969; p < 0.001) and PYRAMID(HR per one point increase in MedDiet score: 0.958; 95%
CI: 0.922–0.996; p = 0.031) scores. When divided into

Shannon et al. BMC Medicine(2023) 21:81

tertiles, relative to low MedDiet, high but not moderate adherence was associated with lower dementia risk
(Fig. 1).
The absolute risk of dementia in the low, medium andhigh MedDiet adherence groups defined by the MEDAS
continuous score was 1.73%, 1.50% and 1.18%, respectively. Moderate and high MedDiet adherence groups
had 0.23% (95% CI: -0.01–0.49%) and 0.55% (95% CI:
0.32–0.79%) lower absolute risk of dementia than thosein the low MedDiet adherence group. Meanwhile, theabsolute risk of dementia in the low, medium and high
MedDiet adherence groups defined by the PYRAMID
score was 1.67%, 1.53%, and 1.21%, respectively. Moderate and high MedDiet adherence groups had 0.14% (95%
CI: -0.1–0.39%) and 0.46% (95% CI: 0.23–0.69%) lower
absolute risk of dementia than those in the low MedDiet
adherence group.
Mediterranean diet adherence, genetic risk and dementia
incidence

A higher polygenic risk score was associated with greaterrisk for dementia (HR: 1.224, 95% CI: 1.102–1.360;
p < 0.001). There was no significant interaction between
polygenic risk for dementia and MedDiet adherence
defined by the MEDAS continuous (HR: 1.036, 95% CI:

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0.977–1.076; p = 0.070) or PYRAMID (HR: 1.011; 95%
CI: 0.974–1.049; p = 0.572) scores.
Sensitivity analyses

The associations between high MedDiet adherence andlower dementia risk were robust to a range of sensitivity
analyses. When we used the conventional (i.e., in which
points for each MedDiet component are awarded on abinary basis) rather than continuous (i.e., in which points
for each MedDiet component are awarded between 0
and 1 based on proximity to the dietary targets) MEDAS
score, there was a similar, albeit slightly attenuated,association between MedDiet adherence and dementia risk. Specifically, each one-point increase in MEDAS
score was associated with 4.5% lower risk of dementia(HR: 0.955; 95% CI: 0.918–0.993; p = 0.021) and, whensplit into tertiles, high (HR: 0.783, 95% CI: 0.651–0.943,
p = 0.001) but not moderate (HR: 1.023, 95% CI: 0.873–
1.199, p = 0.775) MedDiet adherence was associatedwith lower dementia risk versus low MedDiet adherence(Fig. 2). Results were similar when we repeated analyses for participants with a minimum of 2 dietary reports(Fig. 2 and Additional file 1, Table S4) and after excluding participants with extreme energy intakes (Fig. 2 andAdditional file 1, Table S5). In analyses where MedDiet

Fig. 1 Association between MedDiet adherence and risk of dementia (n = 60,298, including 882 dementia cases). MedDiet adherence level was
split into tertiles, with the dashed line reflecting the low MedDiet adherence reference group for each MedDiet score

Shannon et al. BMC Medicine(2023) 21:81

scores were derived after sequential removal of individual
dietary components, the associations remained reasonably stable (Fig. 3 and Additional file 1, Table S6 and S7).
Higher MedDiet adherence was associated with lower
dementia risk when we repeated analyses after removing participants with less than two and less than five
years of follow up to minimise risk of reverse causality(Fig. 2 and Additional file 1, Table S8), and when adjusting for potential mediators (BMI, history of depression,or stroke; Fig. 2 and Additional file 1, Table S9).
When we repeated the analyses exploring the interaction between the MedDiet adherence and polygenic
risk for dementia using the conventional MEDAS score
we found a significant interaction (HR: 1.042, 95% CI:
1.003–1.082; p = 0.035). When analyses were stratified
by polygenic risk category, higher MedDiet adherence
according to the MEDAS continuous scores was associated with lower dementia incidence in individuals in thelower genetic risk category only (Fig. 2 and Additional
file 1, Table S10). When we repeated the analysis using
the conventional MEDAS score coded on a binary basis,
similar results were observed. In addition, in individuals in the higher genetic risk category, moderate MedDiet adherence according to the conventional MEDAS
score was associated with higher risk for dementia (Fig. 2
and Additional file 1, Table S10). When we explored theinteraction between MedDiet adherence and genetic
risk defined by APOE genotype, no diet-gene interactions were observed (MEDAS continuous HR: 1.035; 95%
CI: 0.958–1.118; p = 0.386; MEDAS (binary coding) HR:
0.985; 95% CI: 0.913–1.064; p = 0.706; PYRAMID HR:
1.054; 95% CI: 0.978–1.136; p = 0.167). Likewise, whenanalyses were stratified by APOE genotype, there was asimilar pattern of response (i.e., higher MedDiet adherence was associated with lower HRs) in APOE ε4 carriers/non-carriers (Fig. 2 and Additional file 1, Table S11).
Similar associations were observed when we imputed
missing data (Fig. 2 and Additional file 1, Table S12), forfatal and non-fatal dementia cases (Fig. 2 and Additional
file 1, Table S13), and when analyses were stratified byeducation status (Fig. 2 and Additional file 1, Table S14).

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Discussion
Using data from over 60,000 participants, we demonstrated that higher adherence to the MedDiet is associated with lower risk of incident all-cause dementia.
Specifically, participants with the highest MedDiet
adherence had 23% lower risk of developing dementia incomparison with those with the lowest level of adherence(highest vs. lowest MEDAS continuous tertiles), which
was equivalent to an absolute risk difference (reduction)of 0.55%. We found no significant interaction between
MedDiet adherence, defined by both the MEDAS continuous and PYRAMID scores, and polygenic risk fordementia. In addition, we found that a continuous
MEDAS score was a more sensitive predictor of dementia
risk when compared with a binary MEDAS or PYRAMID
scores.
Previous studies exploring associations between MedDiet adherence and dementia risk have produced inconsistent findings. Indeed, a systematic review by Limongi
and colleagues [9] reported lower risk of Alzheimer’s disease and all-cause dementia in four out of seven and zeroout of five studies (with the other studies reporting null
findings), respectively. A more recent cohort study analysis found lower risk of all-cause and non-Alzheimer’s,
but not Alzheimer’s, dementia among those with higher
MedDiet adherence [16]. Previous investigations haveused different approaches for collecting dietary intake
data (e.g., food frequency questionnaires and 24-h recall
methods), and have employed various MedDiet scoring
systems, each of which define adherence to this dietary
pattern in distinctly different ways. Such heterogeneity could hinder efforts to interpret and compare resultsfrom different studies [9]. Indeed, although we observed
broadly consistent findings across the different MedDiet scores in this study, the strength of association withdementia risk differed. Whilst diet may be an important
tractable risk factor for dementia, it is not emphasised inall dementia prevention guidelines (e.g., [2]), which may
reflect the lack of consistent evidence about the dietary
patterns that are associated with lower dementia risk. A
better understanding of the best ways to operationalize(See figure on next page.)
Fig. 2 Association between MedDiet adherence and risk of dementia in sub-group and sensitivity analyses. MedDiet adherence level was split into
tertiles, with the dashed line reflecting the low MedDiet adherence reference group for each MedDiet score. Analyses include: A) Primary analyses
for the MEDAS, MEDAS continuous and PYRAMID scores (n = 60,298, including 882 dementia cases); B) Including participants with a minimum of 2
dietary reports (n = 38,794, including 479 dementia cases); C) After excluding participants with extreme energy intakes (n = 59,627, including 867
dementia cases); D) Excluding participants with less than 2 years (n = 59,594, including 843 dementia cases) and 5 years (n = 58,196, including 698
dementia cases) follow up; E) Adjusting for potential mediators, including BMI (n = 60,163, including 876 dementia cases), history of depression(n = 58,837, including 851 dementia cases), or stroke (n = 60,298, including 882 dementia cases); F) Stratified into low (n = 21,009, including 261
dementia cases), medium (n = 20,000, including 313 dementia cases) and high (n = 19,273, including 308 dementia cases) genetic risk categories;G) Stratified into APOE4 carriers (n = 16,644, including 467 dementia cases) and non-carriers (n = 43,651, including 415 dementia cases); H) With
imputed missing data (n = 196,335, including 5001 dementia cases); I) Restricted to fatal (n = 59,627, including 260 dementia cases) and non-fatal(n = 60,038, including 622 dementia cases) dementia cases; and J) Stratified into higher (n = 33,281, including 430 dementia cases) and lower(n = 27,007, including 452 dementia cases) education status groupsShannon et al. BMC Medicine(2023) 21:81

Fig. 2 (See legend on previous page.)

Page 8 of 13

Shannon et al. BMC Medicine(2023) 21:81

Page 9 of 13

Fig. 3 Association between MedDiet adherence defined by the MEDAS (A), MEDAS continuous (B) and PYRAMID (C) scores and risk of dementia(n = 60,298, including 882 dementia cases) after sequentially removing each MedDiet component from the total score. Hazard ratios and 95% CIs
were estimated per point increased in MedDiet score

Shannon et al. BMC Medicine(2023) 21:81

a healthy dietary pattern (including the MedDiet) will bevaluable for future research studies and for the formulation of dietary guidelines to minimise dementia risk.
There is limited and inconclusive evidence about theinteraction between diet (defined by MedDiet adherenceor another dietary index) and genetic risk on dementia incidence [13, 18–20]. For example, higher MedDiet adherence was associated with lower dementia riskin APOE ε4 carriers but not non-carriers in one study[13]. In contrast, other studies have reported that higher
adherence to both the MIND diet (a hybrid between
the MedDiet and Dietary Approach to Stop Hypertension) [18] and a ‘healthy’ diet [19] are more protective
against dementia in APOE ε4 non-carriers. In the present study, we found no significant interaction between
polygenic risk for dementia and MedDiet adherence
defined by the MEDAS continuous or PYRAMID scoresin our primary analyses. Likewise, when we explored theinteraction between MedDiet adherence and genetic risk
defined by APOE genotype, there was a similar pattern of
response for both APOE ε4 carriers/non-carriers. Thus,
our findings suggest similar associations between MedDiet adherence and dementia risk irrespective of genetic
risk for this condition. Nevertheless, we acknowledge adegree of uncertainty in this conclusion, given that findings were not consistent across all sensitivity analyses.
Further research into the interaction between diet andgenetics on dementia risk is therefore warranted.
This study has several strengths. The majority of previous studies exploring associations between MedDiet
adherence and dementia risk have involved relatively
small numbers of participants (n = 1000–6000) with limited dementia cases (n = 20–400) and may have lacked
statistical power [9]. In contrast, our study involved amuch larger cohort (n =  ~ 60,000) with more dementia
cases (n = 882) than most previous investigations. We
defined genetic risk for dementia using a comprehensive
polygenic risk score whereas most previous studies have
explored gene-diet interactions for individual genetic
variants (e.g., APOE genotype) [13, 18–20]. A further
strength of this study is that we carried out a wide rangeof sensitivity analyses which demonstrate the robustness of our findings. Several limitations should also be
considered. Firstly, the observational design of this study
precludes drawing causal inferences. Nevertheless, ourfindings are supported by the results from randomised
controlled trials. This includes data from the Navarra[37] and Barcelona [38] cohorts of the PREDIMED trial,
which demonstrated clinically meaningful benefits of a
MedDiet intervention on cognitive function. A further
limitation is the potential risk of reverse causality, given
lower MedDiet adherence could be a consequence rather
than a cause of dementia [39]. Although we did not findPage 10 of 13

any evidence of reverse causality in sensitivity analyses
where we excluded participants who developed dementia
in the first two or five years of follow up, this does not
eliminate the possibility that diet quality declined earlier in individuals who developed dementia, given thelong pre-clinical phase of this condition [40, 41]. The
measurement of dietary intake is a major challenge in
research, and there are specific limitations related to theassessment of dietary intake in this study which should
be considered when interpreting our results. We useddietary data from the Oxford WebQ, a self-administered
24-h recall method which provides results broadly comparable to those achieved via interviewer-administered
24-h recalls [25], to derive our MedDiet scores. Since
multiple 24-h recalls are required to provide a ‘true’ representation of habitual diet [42], and many participantsin UK Biobank completed only one or two recalls, it ispossible that calculated MedDiet scores are not fully
representative of the participants usual dietary intake.
However, 20,348 participants repeated the touchscreen
questionnaire at median 4.4 years after the initial dietaryassessment. Analyses of the resulting data showed that
there was moderate to substantial agreement between
the responses to the dietary touchscreen questions atbaseline and at the repeat visit [43]. Based on this evidence, we conclude that the estimates of dietary intake
available in UK Biobank represent habitual intake andthat this limits the likelihood of participant misclassification. In addition, we were unable to determine theamount of olive oil consumed from the available dietarydata, which increases the risk of misclassification, as individuals who consume large amounts of olive oil may havebeen awarded lower scores than if we had been able toaccurately quantify their intake of this MedDiet component. Nevertheless, findings from our previous researchsuggest that few individuals in a UK setting consume therequisite amount of olive oil to be awarded a full point
for this MedDiet component [17], suggesting that this is
likely to have had a limited impact on our MedDiet scores
overall. Similarly, it was difficult to quantify accurately
intake of sofrito, a sauce containing typically tomatoes,
onions, and garlic cooked with olive oil which is popularin Mediterranean cuisine and is one of the componentsof the MEDAS/MEDAS continuous scores. We used selfreported intake of tomato-based sauces as the closest
proxy for sofrito intake, which may have resulted in somemisclassification depending upon the ingredients andpreparation method. A further limitation of our work isthat dementia cases were ascertained via linkage to hospital inpatient records and death registry only, which may
miss some cases [44, 45]. However, previous studies havesuggested good agreement with dementia ascertainment
through primary care records [45]. Finally, UK Biobank

Shannon et al. BMC Medicine(2023) 21:81

participants are generally healthier and of higher socioeconomic status than the wider UK population [46] but thisis unlikely to jeopardise valid assessment of exposuredisease relationships that are widely generalizable [46].
Nevertheless, since we restricted our sample to individuals of European ancestry aged ≥ 60 years at recruitment,
our findings require substantiation in other populations(e.g., different ethnicities).

Conclusions
In this large population-based prospective cohort study,
higher adherence to a MedDiet was associated with
reduced dementia risk. A continuous MEDAS score was
the most sensitive predictor of dementia risk when compared with a binary MEDAS or PYRAMID score andcould therefore be prioritised as a tool for defining MedDiet adherence in future observational studies. There wasno clear evidence for an interaction with genetic risk.
These results underline the importance of dietary interventions in future dementia prevention strategies regardless of genetic predisposition.
Abbreviations
BMI	Body mass index
ICD	International classification of diseases
IPAQ	International physical activity questionnaire
MEDAS	Mediterranean diet adherence screener
MedDiet	Mediterranean diet
NHS	National Health Service
PREDIMED	Prevención con Dieta Mediterránea
PYRAMID	Mediterranean diet Pyramid score
SNP	Single nucleotide polymorphism

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​023-​02772-3.
Additional file 1: Text S1. Dietary assessment and creation of the Med‑
Diet scores. Table S1. Components and scoring of the MEDAS and MEDASContinuous Mediterranean diet scores. Table S2. Components andscoring of the PYRAMID Mediterranean diet adherence score. Table S3.
ICD-9 and ICD-10 codes for dementia diagnosis. Figure S1. Participant
flowchart. Table S4. Risk of incident dementia according to Mediter‑
ranean diet adherence, with analyses restricted to individuals with aminimum of 2 dietary reports. Table S5. Risk of incident dementia accord‑
ing to Mediterranean diet adherence excluding participants with extreme
energy intakes. Table S6. Influence of each component of the MEDAS
and MEDAS Continuous scores on dementia risk. Table S7. Influenceof each component of the PYRAMID score on dementia risk. Table S8.
Risk of incident dementia according to Mediterranean diet adherence,
excluding participants with less than 2 years and 5 years of follow up.
Table S9. Sensitivity analyses adjusting for potential effect mediators(BMI, Depression and stroke). Table S10. Association between MedDiet
adherence and risk of dementia in analyses stratified by polygenic risk
score tertiles. Table S11. Associations between MedDiet adherence anddementia incidence in APOE ε4 non-carriers and carriers. Table S12.
Associations between MedDiet adherence and dementia incidence inanalyses where missing data were imputed. Table S13. Risk of incident
dementia according to Mediterranean diet adherence restricted to fatal
and non-fatal dementia cases. Table S14. Risk of incident dementia

Page 11 of 13

according to Mediterranean diet adherence for individuals with higher
and lower education levels.
Acknowledgements
None.
Authors’ contributions
OMS, JMR, TRH, AA, MS, AMM, G M-T, CR, JCM, DJL and ES conceived anddesigned the study. OMS, HM, CM, ML, AM, CM, AG, JM, MS, JCM and ES
derived the MedDiet scores. OMS conducted the statistical analysis, withsupport from JMR, SG, ML, MS, GM-T, JCM, DJL, and ES. JMR and DJL facilitateddata access, carried out data processing, and derived key variables used in
the analysis. JMR updated the dementia data. OMS, JMR, JCM, DJL and ES
wrote the initial draft of the manuscript, with OMS taking a lead role. TRH, AA,
AMM, GMT, CR, and ES obtained funding to support the analysis. All authors
participated in the interpretation of the results and critical revision of themanuscript. All authors read and approved the final manuscript.
Funding
This research was conducted as part of the NuBrain consortium, which isfunded by the UK Nutrition Research Partnership (UK NRP), an initiative sup‑ported by the Medical Research Council (MRC), Biotechnology and Biological
Sciences Research Council (BBSRC) and the National Institute for HealthResearch (NIHR) (MR/T001852/1).
Availability of data and materials
Data are available from UK Biobank for all bona fide researchers for healthrelated research in the public interest.

Declarations
Ethics approval and consent to participate
Ethical approval for the UK Biobank study was provided by the North West–
Haydock Research Ethics Committee (REC reference: 16/NW/0274), and allparticipants provided electronic signed consent. The study was performed inaccordance with the tenets of the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Human Nutrition & Exercise Research Centre, Centre for Healthier Lives,
Population Health Sciences Institute, Newcastle University, Newcastle Upon
Tyne, UK. 2 College of Medicine and Health, University of Exeter, Exeter, UK.
3
Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Universityof Edinburgh, Edinburgh, UK. 4 Institute for Physical Activity and Nutrition,
School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC,
Australia. 5 School of Medical Sciences, Örebro University, Örebro, Sweden.
6
Nutrition Measurement Platform, MRC Epidemiology Unit, University of Cam‑bridge, Cambridge, UK. 7 Centre for Public Health, The Institute for Global
Food Security, Queen’s University Belfast, Belfast, UK. 8 School of Health, Leeds
Beckett University, Leeds, UK. 9 School of Life Sciences, Queen’s Medical Centre,
The University of Nottingham Medical School, Nottingham, UK. 10 Nutrition
and Preventive Medicine, Norwich Medical School, University of East Anglia,
Norwich, UK. 11 Norwich Institute of Health Ageing (NIHA), Norwich, UK.
12
Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, USA.
13
Alan Turing Institute, London, UK.
Received: 27 June 2022 Accepted: 7 February 2023

Shannon et al. BMC Medicine(2023) 21:81

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