(2024) 22:298
Zhang et al. BMC Medicine
https://doi.org/10.1186/s12916-024-03525-6

BMC Medicine

RESEARCH ARTICLE

Open Access

Associations of sugar intake, high-sugar
dietary pattern, and the risk of dementia:
a prospective cohort study of 210,832
participants
Sirui Zhang1,2,3†, Yi Xiao1,2,3†, Yangfan Cheng1,2, Yuanzheng Ma1,2,3, Jiyong Liu1,2,3, Chunyu Li1,2 andHuifang Shang1,2*   

Abstract
Background Limited evidence demonstrated the potential relationship between dietary sugar intake and dementia.
This association demands further clarification in a large-scale population.
Methods A total of 210,832 participants from the UK Biobank cohort were included in this prospective cohort study.
Absolute and relative sugar intake and high-sugar dietary scores were utilized to reflect dietary sugar intake. Absolutesugar intake was identified by the Oxford WebQ in the UK Biobank. Relative sugar intake was calculated by dividing
the absolute sugar intake by total diet energy. High-sugar dietary pattern was identified using the method of reduced
rank regression. Cox proportional hazards regression analyses and restricted cubic splines were performed to examine
the longitudinal associations between dietary sugar intake and all-cause dementia and its main subtype, Alzheimer’s
disease. Explorative mediation analyses were conducted to explore underlying mechanisms.
Results Increased absolute sugar intake (g/day) was significantly associated with a higher risk of all-cause dementia (HR = 1.003, [95%CI: 1.002–1.004], p < 0.001) and Alzheimer’s disease (1.002, [1.001–1.004], 0.005). Relative sugar
intake (%g/kJ/day) also demonstrated significant associations with all-cause dementia (1.317, [1.173–1.480], p < 0.001)
and Alzheimer’s disease (1.249, [1.041–1.500], 0.017), while the high-sugar dietary score was only significantly associated with a higher risk of all-cause dementia (1.090, [1.045–1.136], p < 0.001). In addition, both sugar intake and highsugar dietary score demonstrated significant non-linear relationships with all-cause dementia and Alzheimer’s disease(all p values for non-linearity < 0.05).
Conclusions Our study provided evidence that excessive sugar intake was associated with dementia. Controllingthe excess consumption of dietary sugar may be of great public health implications for preventing dementia.
Keywords Dementia, Alzheimer’s disease, Sugar intake, Dietary pattern†

Sirui Zhang and Yi Xiao contributed equally to this work.

*Correspondence:
Huifang Shanghfshang2002@126.com
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother 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 thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Zhang et al. BMC Medicine(2024) 22:298

Background
Dementia is an important and serious public healthchallenge with a rapidly increasing incidence rate dueto the acceleration of the aging process worldwide [1].
The Global Burden of Disease Study 2019 reported thatdementia patients would increase from 57.4 million
cases globally in 2019 to 152.8 million cases in 2050 [2].
Treatments targeting amyloid-related pathologies at an
early stage have made important advances recently andprovided hope for patients albeit with challenges [3, 4].
However, taking effective measures to prevent the onset
of dementia is still a crucial and cost-effective choice.
Numerous nutritional epidemiological studies haveemphasized the important role of diet intervention in theprevention of dementia [5, 6]. As excess sugar intake wasvalidated to be associated with cardiovascular diseases[7, 8], metabolic disturbances [7, 9], and systemic inflammation [10], which might contribute to increasing therisk for dementia [11–14], we reasonably hypothesizedthat high sugar intake was an important modifiable lifestyle risk factor of dementia. Prior studies predominantly
focused on the effect of some specific sugar sources, suchas sugar-sweetened beverages (SSBs), on the incidence of
dementia [15]. Sugar intake from various other sources indaily diet is also worthy of attention. Nevertheless, only afew studies evaluated the role of dietary sugar intake on
dementia [16, 17].
Accordingly, the current study aimed to examine theassociations between sugar intake, high-sugar dietary
pattern, and the risk of dementia in a large general population and explore the underlying mechanisms by taking
indicators of vascular disorders, metabolic abnormalities,
and systemic inflammation into account in the mediation
analyses.
Methods
Data source

The data analyzed in the current study were obtained
from the UK Biobank database, which is a large-scale
population-based prospective cohort [18]. Written
informed consent forms from all participants wereobtained and ethnic approval was granted by the UK
North West Multi-Centre Research Ethics Committee(no. 21/NW/0157). The detailed introduction of the database was described on the UK Biobank website (http://​www.​ukbio​bank.​ac.​uk/​resou​rces/).
Study populations

Among the initial 502,382 participants, 210,954 individuals who completed at least one dietary questionnaire, based on a 24-h dietary recall of the previous day,were included in the current study. Participants who
were recorded as dementia patients before attending thePage 2 of 13

assessment of the dietary questionnaire were excluded(n = 122). The ascertainment of dementia outcomes in thepresent study will be introduced in the following section.
In total, 210,832 individuals were included in the analysis. The flowchart of the study design and the number ofavailable participants is illustrated in Fig. 1.
Sugar intake measurement

The term “sugar” refers to monosaccharides and disaccharides, including fructose, glucose, sucrose, maltose,galactose, and lactose according to its chemical classification [19]. UK Biobank applied an automated web-based
24-h dietary questionnaire named the Oxford WebQ
to collect information about participants’ consumption of food and beverages during the last 24 h [20]. The
quantity for each consumed food or beverage item wasdetermined by multiplying its assigned portion size by
the consumed amount, and then the built-in algorithmsof the system would evaluate the food composition data
for each participant and calculate the intakes of specificnutrients (such as total sugars), as described detailed in
the previous literature [21, 22]. The web-based Oxford
WebQ has been validated against an interviewer-administered 24-h dietary recall [20] and also performed wellacross key nutrients including protein, potassium, sugar
intake, and total energy when using objective biomarkers as the standard [23]. Absolute total sugar (unit: g/day)and its subtypes (fructose, glucose, sucrose, maltose, lactose, and other sugars) data were collected from the UK
Biobank and analyzed in the current study. Relative sugar
intake (unit: %g/kJ/day) was defined as absolute sugar
intake divided by total energy intake (unit: kJ) in the present study. We also calculated the quartile of the daily
intake of the different types of sugars and categorized theparticipants into four groups: Q1(lowest intake), Q2, Q3,
and Q4 (highest intake). The first dietary assessment was
performed at the assessment center from April 2009 to
September 2010. Four additional questionnaire rounds
were conducted online, with invitations being emailed toparticipants at 3–4 monthly intervals between April 2009
and June 2012. The mean values of the exposures fromthe available data were calculated in the case that participants attended more than one assessment to reflect along-term exposed state.
Identification of high‑sugar dietary pattern

Reduced rank regression (RRR) is a widely used method
to identify the specific dietary pattern in the studyof nutritional epidemiology and the principle of thismethod has been introduced in previous literature [24].
In the present study, RRR was utilized to derive a highsugar dietary pattern that could explain the maximum
variation in sugar intake (response variables) accordingZhang et al. BMC Medicine(2024) 22:298

Page 3 of 13

Fig. 1 Flowchart of the study design and the number of available participants

to the consumption of different food groups (exposure
variables). Relative fructose, glucose, sucrose, maltose,
lactose, and other sugar intake were set as response variables. Fifty-one food groups based on food intake datafrom the Oxford WebQ questionnaire were set as exposure variables, as presented in Additional file 1: Table S1.
Faction loading for each food group was calculated basedon the linear function to reflect the estimate of the association between food group consumption and specificnutrient consumption. High-sugar dietary pattern scorefor each participant was calculated by multiplying thestandardized intake of each food group by its factor loading, representing the extent to which the participant’s
dietary pattern reflected the high-sugar dietary patternrelative to that of other participants. Individuals who
consumed more food groups with a positive factor loading would obtain higher scores. The dietary pattern that
explained the maximum variation in the sugar intake wasretained for the subsequent analyses, in consistency withprevious reports [25, 26]. RRR contributes to overcoming

the limitation of only focusing on the role of one single type of nutrient, as the interactions of different foodgroup combinations were considered in the analysis, but
not merely the intake of specific nutrients.
Dementia ascertainment

The primary outcome of the current study was all-cause
dementia. We also investigated its major subtype, Alzheimer’s disease (AD), as the secondary outcome. The
dementia incidents were ascertained through both algorithmically defined dementia outcomes and first occurrences data in the UK Biobank. Algorithmically defined
dementia outcomes were derived from the algorithmic
combinations of UK Biobank’s linked data from hospital
admissions and death registries, along with self-reported
medical conditions at baseline. First occurrences data
additionally recorded the primary care data to supplement the algorithmically defined dementia outcomes.
Since we excluded those participants diagnosed with allcause dementia before baseline assessment, self-reported

Zhang et al. BMC Medicine(2024) 22:298

dementia patients were not included in the analysis toincrease the accuracy of dementia outcomes ascertainment. The detailed description of the algorithmicallydefined outcomes and first occurrence of health outcomes in the UK Biobank can be found on the website(biobank.ndph.ox.ac.uk/ukb/ukb/docs/alg_outcome_main.pdf, and biobank.ndph.ox.ac.uk/ukb/ukb/docs/
first_occurrences_outcomes.pdf ). The International
Classification of Diseases (ICD)-9 and ICD-10 coding
systems were used to record the diagnoses of dementia in
the UK Biobank, as shown in Additional file 1: Table S2.
Previous studies have reported a positive predictive valueof 82.5% regarding the all-cause dementia events using
the UK routinely collected healthcare datasets whencombining the data source of primary care, hospital
admissions, and death registries, validating the accuracyof dementia diagnoses in the UK Biobank [27]. Followup started when the dietary questionnaire was completed
for the first time and ended at the time of the earliest
dementia incident (all-cause dementia and AD), death,loss to follow-up, or latest data update (February 2022),
whichever occurred first.
Covariates

The covariates were selected based on the identified risk
factors for dementia in previous reports [28–30], including sex, age at baseline, ethnicity, body mass index (BMI),
education level, Townsend Deprivation Index (TDI),
smoking status, drinking status, metabolic equivalent oftasks (MET), diabetes, hypertension, and apolipoprotein
E (APOE) ε4 status. Ethnicity was categorized as whiteand non-white. BMI was categorized as less than 18.5,
18.5–24.9, 25.0–29.9, and ≥ 30 (unit: kg/m2) according to
the World Health Organization’s criteria. Education level
was categorized as higher education (college degree/
university degree/other professional qualification) andlower education. TDI reflected an area-based socioeconomic status and was divided into quartiles in the analyses. Smoking and drinking status were classified into
three groups: never, previous, and current. MET was anindicator of total physical activity (unit: minutes/week)
and was divided into quartiles. The number of APOE
ε4 alleles was calculated based on two single-nucleotide
polymorphisms (rs7412 and rs429358) and was classified
into three groups in the current study according to thenumber of carriers: 0, 1, and 2. All the variables used in
the current study are listed in Additional file 1: Table S3.
Statistical analysis

To summarize the baseline characteristics of the populations according to total sugar intake, continuous variables were described as mean (standard deviation, SD)

Page 4 of 13

and categorical variables were described in the form of
frequency (percentage).
Cox proportional hazard regression models wereused to investigate the longitudinal association between
sugar exposures (absolute sugar intake, relative sugar
intake, and high-sugar dietary score) and dementia incidents (all-cause dementia and AD). Continuous variables were transformed into categorical variables by theirquartile distributions from low to high (Q1 to Q4) andthe Q1 group was set as the reference group for analyses. Model 1 was unadjusted. Model 2 was adjusted forbaseline demographic information and socio-economic
factors including sex, age at baseline, ethnicity, education level, BMI, and TDI. Model 3 was further adjusted
for important lifestyle factors, comorbidities, and genotype factor including smoking status, drinking status,
metabolic equivalent of tasks (MET), diabetes, hypertension, and apolipoprotein E (APOE) ε4 status. Participants with missing covariates information were excluded
from the corresponding analyses. The complete information regarding missing covariants is listed in Additional
file 1: Table S4. The proportional hazards assumptions
were tested using the method of Schoenfeld residuals andwe observed no violation of the assumption. The potential non-linear associations between sugar intake anddementia incidents were also tested in Model 3 using themethod of restricted cubic spline (RCS), with the reference value set at the median, and four knots set at the
25th, 50th, 75th, and 95th centiles. Hazard ratios (HRs)and 95% confidence intervals (CIs) were calculated. pvalues for the trend were calculated using the median ofeach quartile group as a quasi-continuous variable in themodel.
We then examined the potential interaction effects ofage, sex, BMI, APOE ε4 status, diabetes, and hypertension with sugar intake on the risk of dementia by adding
multiplicative interaction terms in the Cox proportional
hazard model and performed subgroup analyses further. Regarding sensitivity analyses, we first excluded
participants who developed dementia within 3 years offollow-up to minimize the effect of reverse causation.
Additionally, we repeated previously mentioned analyses
among participants who completed at least two, three,and four times of dietary assessments which might reflecta more long-term and stable dietary preference.
Cardiovascular factors, systemic inflammation, andmetabolic disturbance might contribute to the effect ofsugar intake on the risk of dementia incidents. In the
exploratory mediation analyses, we evaluated the mediation effects of inflammatory markers including neutrophil–lymphocyte ratio and C-reactive protein (CRP),
metabolic markers including BMI and HbA1c, and vascular markers including systolic blood pressure (SBP)Zhang et al. BMC Medicine(2024) 22:298

and diastolic blood pressure (DBP) on the association
between total sugars intake and dementia cross-sectionally. The “Lavaan” package in R software was applied toperform mediation analyses with a nonparametric Bootstrapping test with 1000 iterations.
We used STATA software (version: 17.0) to perform
RRR ­analysis24 and R software (version: 4.2.0) for all otheranalyses. A two-sided p value of < 0.05 was accepted asstatistically significant.

Results
Population characteristics

The population characteristics were summarized according to the quartile distribution of absolute daily sugar
intake, as presented in Table 1. A total of 210,832 participants without all-cause dementia at the baseline visit
were enrolled in the current study. The mean age of the
included populations was 56.08 ± 7.99 years old, and116,153 (55.09%) were females. Participants with highintake of total sugars appeared to be older (Table 1).
The mean age of the participants with the lowest quartile of total sugar intake was 55.35 ± 7.93 years, whilethat of the participants with the highest quartile was56.45 ± 8.08 years. Additionally, males, current smokers and drinkers, and participants with vascular diseases
were more likely to consume more sugar. Finally, 1877
cases of all-cause dementia and 781 cases of AD occurred
during the mean follow-up period of 11.80 ± 1.66 years.
Identification of high‑sugar dietary pattern

We identified the high-sugar dietary pattern that
explained the maximum variation in the response variables. The high-sugar dietary pattern explained 28.2%of the variations in the six subtypes of sugar intake on
average. This dietary pattern was characterized by highconsumption of fresh fruit, sugar-sweetened beverages
and other sugary drinks, fruit juice, dried and stewed
fruit, table sugars and preserves, milk-based and powdered drinks, chocolate, and confectionery, as illustrated
in Fig. 2. The mean absolute sugar intake increased
from 102.976 g/day among individuals in quantile 1(Q1) of high-sugar dietary scores to 162.243 g/day in
Q4. Detailed information on factor loadings of different
food groups and all types of sugar intake according to
the quartile of high-sugar dietary scores is listed in Additional file 1: Table S5 and S6.
Sugar intake and dementia

In the crude model 1, higher absolute and relative total
sugar intake and high-sugar dietary scores demonstrated
significant positive associations with the increased risk of
all-cause dementia and AD. In the fully adjusted model
3, absolute and relative total sugar intake and high-sugar

Page 5 of 13

dietary scores remained statistically significant associations with all-cause dementia incidents. The corresponding HRs and 95%CI were 1.003 [1.002–1.004], 1.317[1.173–1.480], and 1.090 [1.045–1.136], respectively.
After transforming continuous variables into categoricalvariables according to their quartiles, the highest quartile
group (Q4) of absolute and relative total sugar intake andhigh-sugar dietary scores demonstrated significant associations with17.1%, 32.3%, and 25.5% increased risk of allcause dementia, compared to the lowest quartile group(all p for trend < 0.05). Regarding AD, both absolute andrelative sugar intake were significantly associated with alinearly increased risk of AD, but not high-sugar dietaryscores (p = 0.056). The longitudinal associations between
absolute sugar intake, relative sugar intake, and highsugar dietary scores and dementia are listed in Table 2.
The comprehensive results of the analyses based on thethree models are listed in Additional file 1: Table S7 andS8.
We further performed the analyses to validate the roleof different types of sugar on the risk of dementia. The
results showed that sucrose was most robustly associatedwith all-cause dementia and AD. As the different rolesof sugar subtypes were not the main concern of the current research, we did not conduct further analyses. The
detailed results of analyses between various subtypes ofsugar and incidents of dementia are summarized in Additional file 1: Table S9 and S10.
We additionally performed RCS analyses to explore thepotential non-linear associations between sugar intake
and dementia. We observed significant non-linear associations between absolute and relative total sugar intake
and high-sugar dietary scores and all-cause dementia and
AD. They presented a similar pattern in which consumption of more than the median amount of sugar increased
the risk of dementia more evidently, as shown in Fig. 3.
The inflection points where HR = 1 are listed in Additional file 1: Table S11.
Interaction effects and subgroup analyses

The results of interaction effects analyses are summarized comprehensively in Additional file 1: Table S12 andS13. Further, in the age-specific analyses, we found thatthe effect of sugar intake and high-sugar dietary patternon all-cause dementia and AD only remained significant among middle-aged populations (56–65 years old),but not among young or aged people. In the sex-specificanalyses, generally, the effect of sugar intake on dementia appeared to be more prominent among females. In
males, absolute and relative sugar intake and high-sugar
dietary scores did not correlate with the increased risk ofAD significantly. In the APOE ε4 status-specific analyses,
generally, the effect of sugar intake on all-cause dementia

Zhang et al. BMC Medicine(2024) 22:298

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Table 1 Baseline characteristics of study participants by the quartile of absolute total sugar intake
Characteristics

NumberAbsolute total sugar intake
Total

Q1

Q2

Q3

Q4

210,832

52,69452,72652,70552,707Sex
Female116,153 (55.09)

32,741 (62.13)

30,890 (58.59)

28,391 (53.87)

24,131 (45.78)

Male

94,679 (44.91)

19,953 (37.87)

21,836 (41.41)

24,314 (46.13)

28,576 (54.22)

Age at baseline, years

56.08 (7.99)

55.35 (7.93)

56.14 (7.85)

56.38 (7.89)

56.45 (8.08)

EthnicityWhite

198,110 (95.46)

49,442 (95.35)

49,549 (95.54)

49,581 (95.51)

49,538 (95.47)

Non-white

9413 (4.54)

2413 (4.65)2314 (4.46)

2333 (4.49)

2353 (4.53)

Smoking status
Current

21,7225435 (10.48)

5399 (10.42)5375 (10.37)

5513 (10.63)

Never

113,71228,524 (54.84)

28,403 (54.83)

28,544 (55.04)

28,241 (54.46)

Previous

71,934

17,885 (34.69)

18,004 (34.75)

17,938 (34.59)

18,107 (34.91)

Alcohol consumption
Current

191,300 (92.00)

47,771 (91.93)

47,798 (91.96)

47,873 (92.05)

47,858 (92.05)

Never9185 (4.42)2256 (4.34)

2332 (4.49)

2305 (4.43)

2292 (4.41)

Previous

7453 (3.58)

1936 (3.73)

1846 (3.55)

1829 (3.52)

1842 (3.54)

Higher education
Yes

117,155 (55.59)

27,577 (52.36)

30,007 (56.93)

30,577 (58.04)

28,994 (55.03)

No

93,593 (44.41)

25,096 (47.64)

22,701 (43.07)

22,106 (41.96)

23,690 (44.97)

Townsend deprivation index− 1.30 (3.09)− 1.28 (3.11)− 1.30 (3.09)− 1.31 (3.08)

23,691

Townsend deprivation index quartile
Q1 (least deprived)

52,302 (25.16)

13,019 (25.05)

13,096 (25.21)

13,086 (25.17)

13,101 (25.20)

Q251,737 (24.88)

12,995 (25.01)

12,921 (24.87)

12,950 (24.90)

12,871 (24.75)

Q351,938 (24.99)

12,807 (24.64)

13,010 (25.05)

13,025 (25.05)

13,116 (25.23)

Q4 (most deprived)

51,911 (24.97)

13,148 (25.30)

12,919 (24.87)

12,938 (24.88)

12,906 (24.82)

Diabetes
No

201,794 (95.73)

49,443 (93.86)

50,397 (95.60)

50,925 (96.64)

51,029 (96.83)

Yes8994 (4.27)

3237 (6.14)2320 (4.40)

1768 (3.36)

1669 (3.17)

Vascular diseases
No

154,773 (73.53)

38,203 (72.62)

38,920 (73.93)

39,043 (74.20)

38,607 (73.38)

Yes

55,710 (26.47)

14,403 (27.38)

13,725 (26.07)

13,579 (25.80)

14,003 (26.62)

BMI, kg/m2

26.96 (4.66)

27.36 (4.90)

26.87 (4.60)

26.70 (4.50)

26.90 (4.60)

BMI groups   < 18.5

1095 (0.53)

253 (0.49)

277 (0.54)

262 (0.51)

303 (0.59)   ≥ 18·5 to < 25·067,278 (32.49)

16,709 (32.29)

16,730 (32.33)

16,887 (32.61)

16,952 (32.73)   ≥ 25·0 to < 30·088,224 (42.61)

22,083 (42.67)

22,007 (42.53)

22,083 (42.64)

22,051 (42.58)   ≥ 30·050,465 (24.37)

12,703 (24.55)

12,726 (24.60)

12,554 (24.24)

12,482 (24.10)

2647.67 (2705.92)

2644.57 (2700.75)

2648.76 (2719.54)

2655.88 (2703.30)

2641.44 (2700.1)

MET min/week
MET quartile
1

42,065 (24.94)

10,489 (24.88)

10,572 (25.07)

10,566 (25.00)

10,438 (24.81)

242,268 (25.06)

10,630 (25.22)

10,574 (25.07)

10,502 (24.85)

10,562 (25.10)

342,235 (25.04)

10,507 (24.93)

10,483 (24.86)

10,550 (24.96)

10,695 (25.42)

442,015 (24.96)

10,525 (24.97)

10,544 (25.00)

10,652 (25.20)

10,384 (24.68)

APOE ε40

143,338 (71.94)

36,035 (72.58)

35,872 (71.97)

35,908 (72.05)

35,523 (71.13)

151,419 (25.81)

12,536 (25.25)

12,866 (25.81)

12,785 (25.65)

13,232 (2.65)

24501 (2.26)

1075 (2.17)1105 (2.22)

1142 (2.29)

1179 (2.36)

Data is presented as mean (SD) for continuous variables and as frequency (percentage) for categorical variables
BMI body mass index, MET metabolic equivalent of tasks, APOE ε4 apolipoprotein E4

Zhang et al. BMC Medicine(2024) 22:298

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Fig. 2 Factor loadings for high-sugar dietary pattern. Note: Only the top 15 food groups with negative factor loadings are preserved in the figure
and the comprehensive information is listed in Supplementary Table 4

Table 2 Associations between sugar intake, high-sugar dietary score, and dementia

Absolute total sugar intake (g/day)All-cause dementia

AD

Number of events = 1391

Number of events = 570

HR

95% CI

p-valueHR

95% CI

p-value

1.003

1.002–1.004< 0.001*

1.002

1.001–1.004

0.005*

0.483

Absolute total sugar intake, quartile
Q1 (74.134)

Reference

Q2 (105.784))

0.849

0.724–0.995

0.043*

0.914

0.712–1.174

Q3 (133.527)

0.898

0.769–1.049

0.175

0.993

0.779–1.267

0.958

Q4 (177.590)

1.171

1.013–1.355

0.033*

1.191

0.944–1.503

0.140

1.173–1.480< 0.001*

1.041–1.500

0.017*

0.892

p for trend

0.003*

Relative total sugar intake (%g/kJ/day)

1.317

Reference

0.058
1.249

Relative total sugar intake, quartile
Q1 (0.980)

Reference

Q2 (1.300)

0.964

0.822–1.132

0.658

0.983

0.764–1.265

Q3 (1.563)

0.945

0.805–1.109

0.489

0.938

0.729–1.207

0.619

Q4 (1.957)

1.323

1.140–1.535< 0.001*

1.283

1.014–1.624

0.038*

1.045–1.136*< 0.001

0.998–1.140

0.056

0.290

p for trend
High-sugar dietary score

Reference< 0.001*
1.09

0.021*
1.067

High-sugar dietary score, quartile
Q1 (− 1.369)

Reference

Q2 (− 0.370)

0.914

0.778–1.074

0.274

0.871

0.674–1.125

Q3 (0.348)

0.964

0.822–1.132

0.657

0.97

0.756–1.246

0.813

Q4 (1.364)

1.255

1.078–1.462

0.003*

1.196

0.942–1.520

0.142

p for trend

Reference< 0.001*

Results of Cox-proportional hazards analyses in fully adjusted model 3
AD Alzheimer’s disease, HR hazard ratio, 95% CI 95% confidence interval*

Statistically significant difference was found among the groups (p < 0.05)

0.053

Zhang et al. BMC Medicine(2024) 22:298

Page 8 of 13

Fig. 3 Restricted cubic spline models of the association between absolute sugar intake, relative sugar intake, and high-sugar dietary score
and incident dementia. Note: The analyses were performed in fully adjusted model 3. The solid lines show hazard ratios (HRs) and the shaded areas
show 95% confidential intervals (CIs). a-c Absolute sugar intake (g/day), relative sugar intake(%g/kJ/day), and high-sugar dietary score and the riskof all-cause dementia. d-f Absolute sugar intake (g/day), relative sugar intake(%g/kJ/day), and high-sugar dietary score and the risk of Alzheimer’s
diseaseFig. 4 Associations between exposures and dementia in the age-specific, sex-specific, and APOE-specific subgroups. Note: For the clarity
of presentation, a 20 g/day increment of absolute total sugar was considered as one unit of absolute total sugar in Fig. 4. The boxes show hazard
ratios (HRs) and the lines show 95% confidential intervals (CIs). The analyses were performed in fully adjusted model 3

Zhang et al. BMC Medicine(2024) 22:298

and AD was likely to be more prominent among participants with one APOE ε4 allele. Comprehensive information on the subgroup analyses is summarized in Fig. 4
and Additional file 1: Table S14-S18.
Mediation analyses

Considering total sugar intake presented a robust significant correlation with dementia in the previous analyses,
explorative mediation analyses were conducted to elucidate whether the association between sugar intake anddementia was partly mediated by vascular, inflammatory, and metabolic factors. As shown in Additional file 1:
Table S19 and S20, we found that 2.8% and 4.1% of theassociations between absolute total sugar intake and allcause dementia and AD were mediated by SBP, respectively, and 0.7% and 0.4% of the associations between
absolute total sugar intake and all-cause dementia and
AD were mediated by neutrophil–lymphocyte ratio. In
terms of metabolic factors, we did not detect any evidence that metabolic disturbances exerted potential
mediation effects in our populations.
Sensitivity analyses

In the sensitivity analysis excluding participants who
had an all-cause dementia event within 3 years of completing their first dietary assessment, the absolute andrelative sugar intake and high-sugar dietary scores demonstrated robust significant associations with the risk of
all-cause dementia and AD (Additional file 1: Table S21).
In the sensitivity analysis which restricted the number offollow-up visits, we first derived three new high-sugar
dietary patterns based on populations who completed atleast two, three, and four times of dietary assessments,
respectively (Additional file 1: Table S22-S24). Most of
the subsequent analyses validated the stable significant
association between total sugar intake and high-sugar
dietary pattern and all-cause dementia, conforming toour primary analyses. However, the statistically significant association between total sugar intake and highsugar dietary scores and AD incidents only survived
when the analytic samples were restricted to participants
who completed at least two times of dietary assessments
and three times of dietary assessments, respectively.
The comprehensive results of sensitivity analyses that
restricted the number of follow-up visits are listed in
Additional file 1: Table S25-S27.

Discussion
In the current study, based on a large population-based
cohort from UK Biobank, we provided evidence of thelongitudinal relationship between sugar intake and highsugar dietary pattern and dementia. We detected thatthe increase in daily sugar intake in both absolute andPage 9 of 13

relative forms was significantly associated with the risk of
all kinds of dementia, while the high-sugar dietary score
was significantly associated with all-cause dementia, but
not with AD. The explorative mediation analyses revealed
that hypertension, especially high SBP, and systemic
inflammation, reflected by neutrophil–lymphocyte ratio,
might partly mediate the aforementioned associations toa small degree, providing hints for further mechanisms
studies.
To the best of our knowledge, this is the first study toinvestigate the relationship between high-sugar dietary
pattern and dementia in a large-scale and general population. Previous literature regarding high-sugar dietary
pattern and dementia is relatively limited, only one study
focused on the effect of high-sugar dietary pattern on
AD among elderly women in the USA by Liu et al. [17].
They reported that both absolute total sugar intake anda high-sugar diet were associated with the risk of AD
significantly. Nonetheless, considering the study population was restricted to elderly women, the generalizabilityof their conclusion is limited. In the current study, wereconfirmed the significant associations between total
sugar intake and high-sugar dietary scores and AD within
the female participants. In a general population, we further detected the significant non-linear relationshipbetween sugar intake and AD, whereby higher consumption of more than the median amount of sugar increased
the risk of dementia more prominently. Several otherstudies also investigated the effect of sugar intake on therisk of dementia without consideration of the interactionof different nutrients contained in different food groups
in a specific dietary pattern as a whole [16, 31]. Most
recently, Schaefer et al. reported that two sugar subtypes(free and intrinsic sugars) from different sources wereassociated with the risk of dementia [16]. Chong et al.
performed the analysis on 1209 participants aged ≥ 60
and found that higher intake of total sugars, free sugar,
sucrose, and lactose were significantly associated withlower MMSE scores [31]. Indeed, recent studies focusedmore on the effect of sugars from sugar-sweetened beverages, an important source of dietary sugar intake, on therisk of dementia [32, 33]. All these investigations together
validated the robustness of the finding that sugar intake istightly correlated with dementia.
The high-sugar dietary pattern established in the present study is characterized by a high-level consumptionof fresh and dried fruit, sugar-sweetened beverages, etc.
Many fresh fruits are repositories of various bioactive
compounds that were reported to play a neuroprotective role [34] and potentially mitigate the adverse impactsof sugar, potentially leading to the underestimation of
the association between sugar and AD. As expected,
this high-sugar dietary pattern provided us with moreZhang et al. BMC Medicine(2024) 22:298

comprehensive information, emphasizing the synergistic effects of various foods rather than isolated nutrients. To further clarify, RRR is a data-driven approachto delineate dietary pattern, reflecting combinations offoods consumed by participants with high sugar intake
in a large-scale population and could not explain all thevariations in the sugar intake. Consequently, not all foods
conventionally considered as sugar-rich were positively
associated with high-sugar dietary pattern score andthere are variances in high-sugar dietary patterns identified by different studies. This requires to be distinguishedfrom hypothesis-driven dietary pattern, such as the Mediterranean diet [35].
Although the p values for interactive effects were notstably significant regarding three different exposures andtwo different outcomes (all-cause dementia and AD), we
still conducted subgroup analyses according to age, sex,and APOE status exploratively. Therefore, the resultsfrom the subgroup analyses should be integrated cautiously, especially considering the obvious disparities in
the number of participants in each group as well as in thestatistical power. In the age- and sex-specific analyses,
the association between sugar and dementia appeared
to be statically significant only in middle-aged females,
although the trends were similar in the other subgroups.
The exact mechanism is unclear. One possible explanation is that middle-aged females are more vulnerable tosystemic inflammation [36] and vascular disorders [37]resulting from excessive sugar intake. In the APOE-specific analyses, the most possible reason for the negative
finding in the subgroup with two APOE-ε4 alleles liesin the small sample sizes (less than 100 participants inthe analysis of AD). The effect of excessive sugar intake
on all-cause dementia and AD was more prominent in
APOE-ε4 alleles carriers, potentially partly owing to thecomplex interplay between sugar intake and metabolism
disturbances. Previous studies reported that APOE-ε4
carriers were more likely to develop insulin resistanceand exhibited a stronger tendency to develop diabetes[38]. Furthermore, high midlife glycemia was associatedwith more severe AD neuropathology among APOE-ε4
carriers [39].
In the current study, while the emphasis was placed on
the impact of one specific type of carbohydrate, namely
sugars, it should be noted that different classes of carbohydrates may share common physiological properties andhealth effects. Other carbohydrates may also exert significant detrimental effects on dementia. Glycemic load
is an important and widely discussed indicator whichreflects blood glucose response to a specific ingredient,food, or portion of a meal [19]. A high glycemic load
diet always reflects an elevated intake of refined carbohydrates, such as starches and sugars. Gentreau et al.

Page 10 of 13

delineated consistent and robust findings that a highglycemic load diet is associated with cognitive decline[40] and an increased risk of dementia [41]. The 2015
Scientific Advisory Committee on Nutrition argued thatthe cause–effect relationships for outcomes based on
variation in diet glycemic load should be integrated withcaution, considering the intricate relationship between
carbohydrates and glucose [19]. Therefore, we establisheda high-sugar dietary pattern based on daily sugar intake
and food consumption data directly and validated theassociation between sugar intake and dementia incidents.
This body of evidence together suggested that excessive carbohydrate intake (sugars as well as other refinedcarbohydrates) might have adverse effects on cognitive
health, which was of great public health significance.
The underlying mechanisms of such association havenot been elucidated clearly so far. Excessive sugar intake
might directly cause hyperglycemia and insulin resistancein the brain, disturbing normal brain function and leading to neurodegeneration consequently through a variety
of mechanisms, such as glucose neurotoxicity, abnormalenergy metabolism, vascular injury, neuroinflammation,and oxidative stress reactions [42–44]. Additionally, it is
known that brain-derived neurotrophic factor (BDNF)
plays a crucial role in regulating the normal survival andmaintenance of neurons and is vital to the process oflearning and memory [45]. Previous studies found that arefined sugar diet could reduce the level of hippocampal
BDNF, and the function of neuronal plasticity and learning in mouse models [46]. Regarding AD, several studies
revealed the interaction between insulin resistance andAβ accumulation [42, 47], suggesting the role of excessive sugar intake in the neuropathology of AD. Crosstalk
between the gut and brain is another alternative hypothesis to link dietary sugar intake with the risk of AD. Highsugar diets have been associated with the disruption ofgut microbiota [48], which can contribute to the pathophysiological hallmarks of AD, including oxidative stress,
metabolic disturbances, and neuroinflammation throughthe microbiota–gut–brain axis [49]. Consistent withthese proposed potential mechanisms, it might be speculated from our explorative mediation analyses that SBP
and neutrophil–lymphocyte ratio, reflecting vascular disorders and systemic inflammation, partly mediated theassociation between sugar intake and dementia, although
the effects were rather moderate (less than 5.0% of theassociation explained by SBP and less than 1.0% of theassociation explained by neutrophil–lymphocyte ratio).
This indicates that other unmeasured mechanisms ofsugar consumption on the risk of dementia are worth further exploration and validation. In the present study, we
did not observe any mediating role of BMI and HbA1C,
which may be caused by potential reverse causality bias

Zhang et al. BMC Medicine(2024) 22:298

considering the cross-sectional study design of the mediated analyses. That is, participants with diabetes may
limit their consumption of sugars and hence demonstrated a negative association between sugar intake andthe risk of diabetes, interfering with the interpretation of
our findings.
The present study had several other limitations [1].
The food consumption data were collected through a
web-based self-reported dietary questionnaire, whichmight be affected by potential recall bias, resulting in theinaccurate estimation of the consumption of sugar andits subtypes, especially among those participants withprodromal dementia in the current cohort. In addition,
diet exposure assessed at baseline might not reflect along-term habitual dietary pattern and could not capturechanges in food preference over time. To be more specific, individuals’ dietary preferences may exhibit variations between weekends and weekdays, as well as acrossdifferent seasons. However, we performed the sensitivity
analyses using diet data from participants who completed
at least two, three, and four repeated assessments to better capture the characteristics of their habitual diet [2].
As usually happens with the RRR approach, the identified high-sugar dietary pattern did not explain all variability in the sugar intake, and the remaining variability
may result in the underestimation of the effect of sugar
intake on dementia [3]. The existence of a “health volunteer” selection bias in the UK Biobank population [50]may contribute to the underestimation of the strengthof the positive association. People who actively participate in the UK biobank cohort tend to be healthier than
nonparticipants [4]. Most participants in the UK Biobank
were white British, which may limit the generalization of
our findings [5]. The current study focused on all-cause
dementia and its main subtype, Alzheimer’s disease.
Future studies are still warranted to clarify the general
associations between sugar intake and other types ofcognitive decline such as mild cognitive impairment andvascular dementia. The strengths of the study include thelarge sample size, the prospective study design, and thelong-term follow-up. Additionally, the application of RRR
to derive the high-sugar dietary pattern has the advantage of addressing the potential interaction of multiple
food categories collectively.
One previous report based on the 2009–10 National
Health and Nutrition Examination Survey (NHANES)
showed that 8.0% and 6.9% of daily energy intake amongchildren/adolescents and adults were from sugar-sweetened beverages in the US [51]. The excess intake of
dietary sugar is still a health-threatening issue in bothdeveloped and developing countries [7]. Our study confirmed the tight correlation between sugar intake andthe risk of dementia, and we first provided evidence that

Page 11 of 13

high adherence to the high-sugar dietary pattern was
an important modifiable risk factor for dementia, especially all-cause dementia, in a general population. Futurestudies are warranted to elucidate the underlying mechanisms and provide strong evidence for the causal association between sugar intake and dementia. From a publichealth perspective, our findings support that controllingthe consumption of sugar may be of great significance inpreventing the future occurrence of dementia.

Conclusions
Our study provided evidence that dietary sugar intake
was associated with the risk of dementia. Controlling theexcess consumption of dietary sugar may be of great public health implications for preventing dementia.
Abbreviations
AD	Alzheimer’s disease
BMI	Body mass index
CRP	C-reactive protein
DBP	Diastolic blood pressure
MET	Metabolic equivalent of tasks
RCS	Restricted cubic spline
RRR​	Reduced rank regression
SBP	Systolic blood pressure
SSBs	Sugar-sweetened beverages
TDI	Townsend Deprivation Index

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​024-​03525-6.
Additional file 1: Table S1-Food groups and their contents. Table S2-UK
Biobank codes for dementia diagnosis and classification. Table S3-The variates used in the present study from the UK Biobank. Table S4-Informationof missing covariates in model 3. Table S5-Factor loadings for high-sugar
dietary pattern among participants completing one dietary assessment.
Table S6-Mean sugars intake by quartile of high-sugar dietary patternscore. Table S7-Associations between sugar intake, high-sugar dietaryscore and all-cause dementia in three models. Table S8-Associations
between sugar intake, high-sugar dietary score and Alzheimer’s diseasein three models. Table S9-Associations between subtypes of sugars andall-cause dementia in three models. Table S10-Associations between subtypes of sugars and Alzheimer’s disease in three models. Table S11-Inflection points where HR = 1 in the RCS analyses. Table S12-P values on theinteraction between exposures and stratification variables with all-cause
dementia incidents. Table S13-P values on the interaction between
exposures and stratification variables with Alzheimer’s disease incidents.
Table S14-Age-specific subgroup analyses of associations between sugar
intake, high-sugar dietary score and all-cause dementia. Table S15-Sexspecific subgroup analyses of associations between sugar intake,high-sugar dietary score and all-cause dementia. Table S16-APOE-specificsubgroup analyses of associations between sugar intake, high-sugar
dietary score and all-cause dementia. Table S17-Age-specific subgroup
analyses of associations between sugar intake, high-sugar dietary scoreand Alzheimer’s disease. Table S18-Sex-specific subgroup analyses of associations between sugar intake, high-sugar dietary score and Alzheimer’s
disease. Table S19-Mediation analyses of absolute total sugar intake anddementia. Table S20-Mediation analyses of relative total sugar intake anddementia. Table S21-Sensitivity analysis excluding participants developing
all-cause dementia within 3 years. Table S22-Factor loadings for high-sugar
dietary pattern among participants who completed at least two dietaryassessments. Table S23-Factor loadings for high-sugar dietary pattern

Zhang et al. BMC Medicine(2024) 22:298

among participants who completed at least three dietary assessments.
Table S24-Factor loadings for high-sugar dietary pattern among participants who completed at least four dietary assessments. Table S25-Sensitivity analysis among participants who completed at least two dietaryassessments. Table S26-Sensitivity analysis among participants whocompleted at least three dietary assessments. Table S27-Sensitivity analysis
among participants who completed at least four dietary assessments.
Acknowledgements
This study was conducted using the UK Biobank resource under application
number 98992. We are sincerely grateful to all associated researchers of the
UK Biobank.
Author’s contributions
ZSR and XY designed the study, analyzed the data, and drafted the article. CYF,
MYZ, and LJY also participated in the conception of the study, analyzed thedata, and contributed to the article draft. LCY and SHF contributed substantially to the conception of the study and the interpretation of data and revised
the manuscript critically. All authors read and approved the final manuscript.
Funding
This study was funded by the National Key Research and Development Plan
(Grant No. 2021YFC2501203), the Sichuan Science and Technology Program(Grant No. 2022ZDZX0023), and the Sichuan Province Cadre Health Research
Project (2022–115). The funders were not involved in the study design, analysis, and interpretation of the data or the writing of the manuscript.
Availability of data and materials
The UK Biobank resource is available to researchers who wish to access thedata by completing the registration form in the Access Management System(AMS- https://​bbams.​ndph.​ox.​ac.​uk/​ams/).

Page 12 of 13

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Declarations
Ethics approval and consent to participate
Ethnic approval was granted by the UK North West Multi-Centre Research Ethics Committee (no. 21/NW/0157). All participants provided written informed
consent before enrollment in the study.
Consent for publication
All authors approve the publication of the final manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Author details
1
Department of Neurology, Laboratory of Neurodegenerative Disorders, Rare
Disease Center, West China Hospital, Sichuan University, Chengdu 610041,
China. 2 Laboratory of Neurodegenerative Disorders, National Clinical ResearchCenter for Geriatric, West China Hospital, Sichuan University, Chengdu 610041,
China. 3 School of Medicine, West China Hospital, Sichuan University,
Chengdu 610041, China.
Received: 14 December 2023 Accepted: 9 July 2024

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