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Q. Sun1,2, Y. Yang1, X. Wang1, R. Yang1, X. Li1


1. Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China; 2. School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211100, China

Corresponding Author: X. Li and R. Yang, Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, China, or,

J Prev Alz Dis 2021;
Published online December 20, 2021,



Objective: To explore the association between the intake of sugar-sweetened beverages and cognitive dysfunction in middle-aged and older adults, so as to provide an evidence-based basis for the early prevention of cognitive dysfunction.
Methods: A comprehensive search of relevant literature was conducted in PubMed, EMBase, Cochrane, ScienceDirect, and Web of Science from the inception until January 2021. Odds ratios (OR), hazard ratios (HR) and 95% confidence intervals (CI) were calculated using a random-effects, generic inverse variance method. Meta-analysis of the included studies was performed using Review Manager 5.4.
Results: A total of 10 studies on the association between sugary beverages and cognitive dysfunction in middle-aged and older adults were included, of which 3 were cross-sectional studies and the rest were cohort studies. Eight of the ten studies had results suggestive of a negative association. However, Meta-analysis results showed that the association between the intake of sugar-sweetened beverages and the risk of cognitive impairment was not statistically significant (OR=1.59, 95% CI: 0.93-2.74, P=0.08); but from two studies, the hazard ratios of all-cause dementia in middle-aged and older people consuming sugar-sweetened beverages was 2.77 (95%CI: 2.24-3.43, P<0.00001); the hazard ratios of Alzheimer’s disease in middle-aged and older people consuming sugar-sweetened beverages was 2.63 (95%CI: 1.70-4.05, P<0.0001).
Conclusion: There is insufficient evidence to state conclusively that sugar-sweetened beverages intake causes cognitive dysfunction in middle-aged and older adults.

Key words: Sugar-sweetened beverages, cognitive function, Alzheimer’s disease, middle-aged and older adults, meta-analysis.



Currently, the aging of the population has become one of the challenges worldwide. Advanced age means more health risks. A variety of underlying diseases and years of poor lifestyle habits is associate with cognitive decline, which will further develop into diseases such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and other types of dementia (1). These cognitive disorders not only have a great impact on the lives of middle-aged and elderly people, but also place a high burden on caregivers and put great pressure on society, economy, and public health.
Currently, the prevalence of diseases related to cognitive loss is increasing globally. Alzheimer’s disease is one of the most common causes of dementia (2) and is the fifth leading cause of death among people aged 65 and older worldwide. An estimated 6.2 million Americans age 65 and older are living with Alzheimer’s dementia today (3). Scholars estimate that the number of people suffering from Alzheimer’s disease will be as high as 81.1 million worldwide by 2040 (4). Mild cognitive impairment is a state between normal aging and dementia and is the preclinical stage of Alzheimer’s disease (5, 6). According to statistics, the prevalence of MCI among adults aged 60 and above in China is 15.54% in 2020 (7). The prevalence of these diseases will continue to increase in the future.
Nowadays, with the prevalence of numerous metabolic diseases, the impact of lifestyle, such as diet, on disease is gaining more and more attention. Many studies have proven a greater association between dietary intake and cognitive function, and in particular, healthy dietary patterns play a protective role on cognitive function in middle-aged and older adults (8, 9). Different beverages will have different effects on the risk of developing disease. Some specific beverages, such as tea and coffee, have been studied over the years and an association between the two and cognitive decline has been found (10), while the association between sugar-sweetened beverages (SSBs) and cognitive decline is inconclusive.
The popularity of SSBs has significantly increased the intake of dietary sugar, and currently the main source of added sugar is SSBs (11). Excessive consumption of sugar-sweetened beverages can increase the risk of metabolic diseases such as obesity and diabetes (12), and hyperglycemia and hyperlipidemia are important risk factors for dementia (13). Therefore, further studies are needed to comprehensively assess the association between SSBs and the risk of cognitive impairment.



Databases and Search terms

This study was reported using the Meta-analysis of Observational Studies in Epidemiology (MOOSE) statement (14). The literature on the association between SSBs and cognitive function in middle-aged and older adults was searched in five databases, PubMed (MEDLINE), EMBase, Cochrane, ScienceDirect, and Web of Science, between the establishment of the databases and January 2021. Combinations of the following search terms were used: ‘cognitive’, ‘cognition’, ‘Alzheimer’s disease’, ‘dementia’, ‘sugar-sweetened beverages’, ‘soft drinks’, ‘beverages’, ‘Carbonated beverages’ and ‘soda’. The details of the search strategy are shown in supplementary materials.
The components of PICOS were as follows: P: adult population; I: SSBs; C: highest intakes versus lowest intakes; O: Cognitive function, MCI, AD, Dementia.
After eliminating duplicates from the retrieved literature, references from relevant reviews were retraced to find research-based literature that met the criteria. Two researchers read the title, abstract, and full text for screening based on inclusion and exclusion criteria.

Selection and Extraction criteria of articles

The literature inclusion and exclusion were carried out simultaneously by two researchers. If disagreement arose during the literature screening process, a third party was consulted to assist in the judgment.
Literature inclusion criteria: (1) Study population: adults aged 30 years or older. (2) Study type: all study types. (3) Interference measures or exposure factors of the study: SSBs. (4) Outcome of the study: Cognitive functional status, mild cognitive impairment, prevalence of dementia and Alzheimer’s disease.
Literature exclusion criteria: (1) The language of the literature is not English or Chinese. (2) Non-clinical studies. (3) Literature for which data extraction was not possible. (4) Study subjects with serious health problems and severe psychiatric system disorders. (5) The study design was problematic and incomprehensive.

Data extraction

The following information needs to be extracted: (1) Study characteristics information: first author, time of publication, study type, study duration, study region, intervention/exposure factors and measures, outcome and measures. (2) Study population information: number of people, mean age. (3) Study data information: frequency or sugar content of sugary beverages consumed by the population, study hazard ratios (HR), odds ratios (OR), 95% confidence interval (CI), and P value. Two researchers independently extracted data from the included literature. If disagreements arose during the process, they discussed them with a third party until agreement was reached. The extracted information is managed in Excel and finally presented in a table.

Risk of bias assessment

The method of literature quality evaluation was chosen according to the type of included studies. For cohort studies, the Newcastle-Ottawa Quality Rating Scale (Newcastle-Ottawa, NOS) (15) was used for quality evaluation, which was developed based on three aspects: cohort selection, intercohort comparability, and outcome evaluation, with multiple entries refined under each aspect, with ‘’ indicating compliance. Cohort selection accounted for 4 points, intercohort comparability accounted for 2 points, and outcome evaluation accounted for 3 points, for a total score of 9. The final score of 0-5 was classified as low-quality literature, and literature with a score higher than 6 was of good quality. For cross-sectional studies, the JBI scale (16) was used for quality evaluation, which contains 10 questions, and each question was given a score of 0, 1, and 2 based on three criteria: non-conformity, cursory mention, and detailed and comprehensive description, with a total score of 20, and a final score higher than 14 was considered high quality literature. For randomized controlled trials (RCTs), the Cochrane risk bias tool was used for quality evaluation.

Statistical analyses

Given the high likelihood of between-study variance, a random effects model was applied to derive summary odds ratios (OR), hazard ratios (HR) and 95% confidence intervals (CI), investigating the associations between the categories of highest versus lowest intake, and risk of impaired cognitive function and incidence of AD, dementia. The data was combined by the generic inverse variance method (17).
Statistical heterogeneity among studies was assessed using the I2 index (18). The I2 index depicts the percentage of total variation due to inter-study variation (19). A value of I2 of 0% to 25% represents insignificant heterogeneity, 26% to 50% low heterogeneity, 51% to 75% moderate heterogeneity and >75% high heterogeneity (20). All statistical analyses were performed using Review Manager 5.4. The P value less than 0.05 was considered significant.



Literature search

According to the literature search strategy, a total of 1032 relevant literatures were retrieved, and 773 literatures were obtained after removing duplicates using Endnote. The initial screening work was performed by cursory reading of titles and abstracts, and a total of 732 papers that did not meet the inclusion criteria were removed. After combining references back to relevant reviews and Meta-analyses, a total of 56 papers needed to be read in full for judgment. Ten papers were finally included (21-30), of which seven were cohort studies (three prospective cohort studies) and three were cross-sectional studies. A flowchart showing the selection process is presented in Figure 1.

Figure 1. Flow chart of literature screening


Study characteristics

A total of ten studies were included in this study, including retrospective cohort studies, prospective cohort studies, and cross-sectional studies, with sample sizes ranging from 333 to 16948. The follow-up period of cohort studies ranged from 4 to 32 years. And mean ages indicating that the study population was mostly elderly with a relatively balanced male to female ratio. The studies mostly used the Food Frequency Questionnaire (FFQ) and other health questionnaires to collect the SSBs intake habits and preferences of the study population. Methods for assessing cognitive function include the Wechsler Memory Scale (WAIS), the Mini-Mental State Examination (MMSE), and other assessments. The methods of diet assessment and outcome ascertainment differed across studies, as described in Table 1. All the included studies generally exhibited a low risk of bias. Details regarding the quality of included studies are provided in Table 2-3.

Table 1. Characteristics of the included article

*FFQ=Food Frequency Questionnaire; MMSE=Mini-Mental State Examination; BMI=Body Mass Index; WAIS=Wechsler Memory Scale; SM-MMSE=Singapore-Modified Mini-Mental State Examination; CRP=C-reactive protein;DSM-4=the Diagnostic and Statistical Manual of Mental Disorders, 4th edition; NINCDS-ADRDA=the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association; MSLS=Maine–Syracuse Longitudinal Study; DHQ=dietary history questionnaire; RAVLT=Rey’s auditory verbal learning test; MoCA=Montreal Cognitive Assessment; VR=visual-reproduction test.; STICS-m= the Spanish version of the modifified Telephone Interview of Cognitive Status


Table 2. Risk of bias assessment for cohort studies

Table 3. Risk of bias assessment for cross-sectional studies


Sugar-sweetened beverages and Cognitive function decline

Eight papers reported the association between SSBs intake and cognitive function decline or risk of cognitive impairment, contained five cohort studies (21-25) and three cross-sectional studies (28-30), looking at populations in five regions, Puerto Rico, Spanish, Singapore, New York and Malaysia.
The results of four cohort studies showed that the intake of SSBs in the middle-aged and elderly population had a negative effect on cognitive function. Ye et al. found that greater intakes of total sugars, added sugars and SSBs, were significantly associated with lower MMSE score (21). Mariana I. Muñoz-García et al. found that the consumption of SSBs was significantly associated with a decline in cognitive function after 6 years (β=-0.43, 95%CI: -0.85, -0.02, P=0.04) (22). And Feng et al. reported that soft/sugared drinks increased the incident MCI (P< 0.001) (23). Crichton et al. found that carbonated beverage intake was inversely associated with cognitive scores (β=-0.038, SE=0.017, P=0.024) and that people with higher cognitive scores tended to drink less carbonated beverages (25). Only one cohort study showed no significant association between SSBs intake habits and cognitive impairment (P=0.306) (24).
After excluding the data of Zhang et al. (24), our meta-analysis based on a random-effects model showed no significant association between SSBs intake habits and cognitive impairment in middle-aged and older adults (OR=1.59, 95% CI: 0.93-2.74, P=0.08). (Figure 2)

Figure 2. Forest plot of the association between SSBs intake and the risk of cognitive impairment in middle-aged and older adults


In the cross-sectional study, on the other hand, Crichton et al. found a significant linear relationship between regular intake of sugary beverages and cognitive function scores (P<0.05). They were negatively correlated with each other. In this study, the reduction in cognitive scores was greater in diabetic patients who consumed sugary beverages (28). Chong et al. comparing the highest intake group with the lowest intake group, grouped by quartiles of sugar intake, found that free sugar intake was significantly and inversely associated with MMSE scores, and that free sugar was mainly derived from SSBs (OR=3.69, 95% CI: 2.39-5.71, P<0.001) (29). Pase et al. found that higher intake of SSBs (>2 times/day) was associated with low brain volume (β=-0.68, SE=0.18, P<0.0001) and also with reduced logical memory (immediate: β=-0.67, SE=0.16, P<0.0001; delayed: β=-0.69, SE=0.16, P<0.0001), while it was not significantly associated with hippocampal volume (P=0.06) (30).

Sugar-sweetened beverages and Dementia

Two papers were prospective cohort studies (26, 27) that examined different follow-up time points of the large epidemiological study, the Framingham Heart Study (FHS), in the United States. In the FHS, the Harvard semi-quantitative FFQ was used to investigate the frequency of intake of various dietary items in the population, and both papers divided the population into three groups according to the frequency of intake of SSBs per week, with the lowest intake group consuming almost none and the highest intake group consuming more than seven times a week. The diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-4) were used to identify whether the population had dementia.
Meta-analysis of data from two studies revealed that the frequency of SSBs intake was associated with the risk of developing all-cause dementia, and the higher the intake of SSBs in the population, the higher the risk of developing all-cause dementia (HR=2.77, 95% CI: 2.24-3.43, P<0.00001). (Figure 3)

Figure 3. Forest plot of the association between SSBs and the risk of all-cause dementia in middle-aged and older adults


Sugar-sweetened beverages and AD

The two aforementioned papers (26, 27) also examined the relationship between the frequency of SSBs intake and the risk of developing AD in older adults. A combined meta-analysis of the data from the two papers suggested that the frequency of SSBs intake in middle-aged and older adults is positively associated with the risk of developing Alzheimer’s disease (HR=2.63, 95% CI: 1.70-4.05, P<0.0001). (Figure 4)

Figure 4. Forest plot of the association between SSBs and the risk of AD in middle-aged and older adults



The present study used different epidemiological studies from 7 regions to analyze the relationship between SSBs intake and cognitive impairment-related disorders in middle-aged and older adults, but based on the results of the above Meta-analysis, it was found that the association between SSBs intake habits and the risk of cognitive impairment in middle-aged and older adults was not statistically significant, but was associated with the risk of developing all-cause dementia and Alzheimer’s disease. But the current the ten included papers were not sufficient to confirm an association between SSBs intake and the risk of cognitive impairment-related disorders in middle-aged and older adults.
In all the included studies, there are cohort studies and cross-sectional studies with statistical models such as linear regression and logistic regression. We chose the cohort studies using logistic regression with HR or OR as the outcome for the meta-analysis. Compared with other cohort studies, Zhang et al. had the smallest maximum grouping of all studies (>2/week) (24), others were one or more SSB per day. To make the results more reliable, we removed Zhang et al. data.
The reason for the insignificant results of the analysis may stem from the excessive heterogeneity among the included literature: first, the dietary patterns of the study populations differed. These papers contained epidemiological research projects from 7 different regions, there were significant differences in the dietary habits of the residents of different countries. According to the basic characteristics of the study population in each study, more than half of the residents in Asian countries did not consume SSBs, which greatly reduced the effective sample size of the study. Second, the definitions of SSBs differed. For example, sugary beverages generally do not include fruit and vegetable juices, while a few studies have included them in sugary beverages. Third, the means of investigating the intake of sugary beverages in the population differed. Among the studies included so far, the four main methods for measuring the intake habits of sugary beverages in the population include FFQ, corrected semi-quantitative FFQ, DHQ, and self-reported nutrition and health questionnaire. Different studies used different instruments and different measurements for subgroup division, which made it difficult to achieve uniformity among studies and greatly reduced the comparability of study results. Fourth, the means of assessment of outcomes differed. For the assessment of cognitive function, scales such as MMSE and WAIS were mainly used, and other tests were added in different studies to assess cognitive function status in various aspects. Finally, the adjusted confounders differed. In one study, adjusting for different confounding factors yielded significantly different results, even with negative and positive results. However, we’re unable to deal with these confounders because of the paucity of data published on this issue. We ultimately selected data adjusted for all confounders for comparison.
Although there was no significant difference in the association between SSBs intake and the risk of cognitive impairment in middle-aged and older adults, eight of the ten papers reported that increased SSBs intake was associated with an increased risk of cognitive decline in middle-aged and older adults, and all combined results in the Meta-analysis were greater than 1, suggesting that SSBs might be a risk factor.
SSBs have now become a major source of dietary added sugars. According to statistics, about 80% of the added sugars in sugary beverages originate from high fructose corn syrup (HFCS), and the fructose content of the now preferred sweetener HFCS is 55% (31-34). Many animal studies have shown that excessive intake of fructose is associated with decreased cognitive function. Ross et al. found a significant decrease in memory function in male rats after consuming a high fructose diet for a certain period of time. In addition to fructose, sucrose intake was also associated with altered cognitive function (35). Jurdak et al. found that rats given sucrose solution had poorer memory compared to rats on a normal diet, while rats on a high-fat diet showed no alteration in memory function (36). Another study also showed that rats given sucrose solution had poorer spatial memory (37).
Our study found a positive association between consumption of SSBs and cognitive impairment, although the results were not statistically significant. We recommended that middle-aged and older adults avoid excessive intake of sugar-sweetened beverages.
However, there were some limitations. Firstly, the small number of included studies is not sufficient to draw definite conclusions. Secondly, studies differed in their assessment of exposure factors and outcomes, as well as in their grouping strategies for SSBs intake, resulting in great heterogeneity among studies. Further studies could develop and select more objective instruments to collect more detailed information on the risk of SSBs intake and cognitive decline in middle-aged and elderly populations.



Based on available evidence, we conducted a Meta-analysis of the association between sugary beverage intake and the risk of cognitive impairment, Alzheimer’s disease, all-cause dementia in middle-aged and older adults. We found that there was no statistical difference between the intake of SSBs and the risk of cognitive impairment in middle-aged and elderly people. There was a positive association between the intake of SSBs and the risk of all-cause dementia and Alzheimer’s disease in middle-aged and elderly people. However, the study evidence is insufficient to draw a firm conclusion.


Conflict of interest: The authors declare no competing financial interest.

Funding: This work was supported by Special Research project of Clinical Toxicology of Chinese Society of Toxicology (CST2020CT104).

Acknowledgements: We are grateful to Yifan Zheng for figure editing in this manuscript. All authors approved the final version of the manuscript for publication.

Ethical standard: None.





1. Cheng XJ, Hu GQ. Progress in research of burden of disease attributed to population ageing. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(11):1915-1920.
2. Kukull WA, Bowen JD. Dementia epidemiology. Med Clin North Am. 2002;86:573–590.
3. 2021 Alzheimer’s disease facts and figures. Alzheimers Dement. 2021;17(3):327-406.
4. Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W, Ferri CP. The global prevalence of dementia: a systematic review and meta analysis. Alzheimers Dement. 2013;9(1):63-75.e2.
5. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999;56(3):303-8.
6. Garcia-Ptacek S, Eriksdotter M, Jelic V, Porta-Etessam J, Palomo SM, et al. Subjective cognitive impairment: Towards early identification of Alzheimer disease. Neurologia. 2013; 31(8).
7. Jia L, Du Y, Chu L, et al. Prevalence, risk factors, and management of dementia and mild cognitive impairment in adults aged 60 years or older in China: a cross-sectional study. Lancet Public Health. 2020;5(12):e661-e671.
8. Van D, Brouwer-Brolsma EM, Berendsen A, et al. The Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) Diets Are Associated with Less Cognitive Decline and a Lower Risk of Alzheimer’s Disease-A Review. Adv Nutr. 2019;10(6):1040-1065.
9. Reichelt AC, Stoeckel LE, Reagan LP, et al. Dietary influences on cognition. Physiol Behav. 2018;192:118-126.
10. Ran LS, Liu WH, Fang YY, et al. Alcohol, coffee and tea intake and the risk of cognitive deficits: a dose–response meta-analysis. Epidemiol Psychiatr Sci. 2021;30:e13.
11. Yang Q, Zhang Z, Gregg EW, et al. Added sugar intake and cardiovascular diseases mortality among US adults. JAMA Intern Med. 2014;174(4):516-524.
12. Cozma AI, HaV, Jayalath VH, et al. Sweeteners and Diabetes. 2014. Springer, New York.
13. Barnes D, Yaffe K. The Projected impact of risk factor reduction on Alzheimer’s disease prevalence. Alzheimers Dement. 2011;7(4):S511-S511.
14. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283(15): 2008-2012.
15. Wells G. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analyses. Syst Rev. 2014.
16. Gu Y, Zhang HW, Zhou YF, et al. JBI evidence based health center’s quality assessment tool for different types of research-The quality evaluation of diagnostic and economic evaluation. Journal of Nurses Training. 2018;33(008):701-703.
17. Dersimonian R, Nan L. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177.
18. Xiao K, Liu F, Liu J, et al. The effect of metformin on lung cancer risk and survival in patients with type 2 diabetes mellitus: A meta-analysis. J Clin Pharm Ther. 2020;45(4):783-792.
19. Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions. Wiley-Blackwell. 2008.
20. Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analysis. BMJ. 2003;327.
21. Ye X, Gao X, Scott T, et al. Habitual sugar intake and cognitive function among middle-aged and older Puerto Ricans without diabetes. Br Journal Nutr. 2011;106(09):1423-1432.
22. Muñoz-García MI, Martínez-González MA, Martín-Moreno JM, et al. Sugar-sweetened and artificially-sweetened beverages and changes in cognitive function in the SUN project. Nutr Neurosci. 2020 Dec;23(12):946-954.
23. Feng TD, Feng ZY, Jiang LL, et al. Associations of health behaviors, food preferences, and obesity patterns with the incidence of mild cognitive impairment in the middle-aged and elderly population: An 18-year cohort study. J Affect Disord. 2020;275:180-186.
24. Zhang YG, Wu J, Feng L, Yuan JM, Koh EP, Pan A. Sugar-sweetened beverages consumption in midlife and risk of late-life cognitive impairment in Chinese adults. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(1):55-61.
25. Crichton GE, Elias MF, Davey A, et al. Higher Cognitive Performance Is Prospectively Associated with Healthy Dietary Choices: The Maine Syracuse Longitudinal Study. J Prev Alzheimers Dis. 2015;2(1):24–32.
26. Pase MP, Himali JJ, Beiser AS, et al. Sugar- and Artificially Sweetened Beverages and the Risks of Incident Stroke and Dementia: A Prospective Cohort Study. Stroke. 2017;48(5):1139–1146.
27. Miao H, Chen K, Yan X, et al. Sugar in Beverage and the Risk of Incident Dementia, Alzheimer’s disease and Stroke: A Prospective Cohort Study. J Prev Alzheimers Dis. 2021;8(2):188–193.
28. Crichton GE, Elias MF, Torres RV. Sugar-sweetened soft drinks are associated with poorer cognitive function in individuals with type 2 diabetes: the Maine–Syracuse Longitudinal Study. Br J Nutr. 2016;115(08):1397-1405.
29. Chong CP, Shahar S, Haron H, et al. Habitual sugar intake and cognitive impairment among multi-ethnic Malaysian older adults. Clin Interv Aging. 2019;14:1331-1342.
30. Pase MP, Himali JJ, Jacques PF, et al. Sugary beverage intake and preclinical Alzheimer’s disease in the community. Alzheimers dement. 2017;13(9):955–964.
31. Gross LS, Li L, Ford ES, Liu S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment. Am J Clin Nutr. 2004;79(5):774-9.
32. Bray GA, Nielsen SJ, Popkin BM. Consumption of high-fructose corn syrup in beverages may play a role in the epidemic of obesity. Am J Clin Nutr. 2004;79(4):537-543.
33. Marriott BP, Olsho L, Hadden L, et al. Intake of added sugars and selected nutrients in the United States, National Health and Nutrition Examination Survey (NHANES) 2003-2006. Crit Rev Food Sci Nutr. 2010;50(3):228–258.
34. Hanover LM, White JS. Manufacturing, composition, and applications of fructose. Am J Clin Nutr. 1993;58(5 Suppl):724S-732S.
35. Ross AP, Bartness TJ, Mielke JG, Parent MB. A high fructose diet impairs spatial memory in male rats. Neurobiol Learn Mem. 2009;92(3):410-416.
36. Jurdak N, Kanarek RB. Sucrose-induced obesity impairs novel object recognition learning in young rats. Physiol Behav. 2009;96(1):1-5.
37. D’Hooge R, De Deyn PP. Applications of the Morris water maze in the study of learning and memory. Brain Res Brain Res Rev. 2001;36(1):60–90.
38. Malik VS, Willett WC, Hu FB. Global obesity: Trends, risk factors and policy implications. Nature reviews. Nat Rev Endocrinol. 2013;9:13-27.
39. Kenny PJ, Voren G, Johnson PM. Dopamine D2 receptors and striatopallidal transmission in addiction and obesity. Curr Opin Neurobiol. 2013;23(4):535-538.
40. Nettleton JA, Lutsey PL, Wang Y, et al. Diet Soda Intake and Risk of Incident Metabolic Syndrome and Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care. 2009;32(4):688-694.
41. Singh-Manoux A, Czernichow S, Elbaz A, et al. Obesity phenotypes in midlife and cognition in early old age: The Whitehall II cohort study. Neurology. 2012; 79(8):755-762.
42. Strachan MW. RD Lawrence Lecture 2010. The brain as a target organ in Type 2 diabetes: exploring the links with cognitive impairment and dementia. Diabet Med. 2011;28(2):141-147.