Association Between Dietary Flavonoids Intake and Cognitive Function in an Italian Cohort
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Data Collection
2.3. Dietary Assessment
2.4. Dietary Flavonoid Intake Estimation
2.5. Cognitive Evaluation
2.6. Statistical Analysis
3. Results
3.1. Background Characteristics
3.2. Flavonoid Intake
3.3. Association Between Flavonoid Intake and Cognitive Health
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- GBD 2017 Disease and Injury Incidence and Prevalence Collaborators Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018, 392, 1789–1858. [CrossRef] [Green Version]
- Grosso, G. Nutrition and aging: Is there a link to cognitive health? Int. J. Food Sci. Nutr. 2020, 71, 265–266. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Angelino, D.; Godos, J.; Ghelfi, F.; Tieri, M.; Titta, L.; Lafranconi, A.; Marventano, S.; Alonzo, E.; Gambera, A.; Sciacca, S.; et al. Fruit and vegetable consumption and health outcomes: An umbrella review of observational studies. Int. J. Food Sci. Nutr. 2019, 70, 652–667. [Google Scholar] [CrossRef] [PubMed]
- Dinu, M.; Pagliai, G.; Casini, A.; Sofi, F. Mediterranean diet and multiple health outcomes: An umbrella review of meta-analyses of observational studies and randomised trials. Eur. J. Clin. Nutr. 2018, 72, 30–43. [Google Scholar] [CrossRef] [PubMed]
- Yi, M.; Wu, X.; Zhuang, W.; Xia, L.; Chen, Y.; Zhao, R.; Wan, Q.; Du, L.; Zhou, Y. Tea Consumption and Health Outcomes: Umbrella Review of Meta-Analyses of Observational Studies in Humans. Mol. Nutr. Food Res. 2019, 63, e1900389. [Google Scholar] [CrossRef]
- Camfield, D.A.; Stough, C.; Farrimond, J.; Scholey, A.B. Acute effects of tea constituents L-theanine, caffeine, and epigallocatechin gallate on cognitive function and mood: A systematic review and meta-analysis. Nutr. Rev. 2014, 72, 507–522. [Google Scholar] [CrossRef]
- Wu, L.; Sun, D.; He, Y. Coffee intake and the incident risk of cognitive disorders: A dose-response meta-analysis of nine prospective cohort studies. Clin. Nutr. 2017, 36, 730–736. [Google Scholar] [CrossRef]
- Grosso, G.; Micek, A.; Castellano, S.; Pajak, A.; Galvano, F. Coffee, tea, caffeine and risk of depression: A systematic review and dose-response meta-analysis of observational studies. Mol. Nutr. Food Res. 2016, 60, 223–234. [Google Scholar] [CrossRef]
- Grosso, G.; Godos, J.; Lamuela-Raventos, R.; Ray, S.; Micek, A.; Pajak, A.; Sciacca, S.; D’Orazio, N.; Del Rio, D.; Galvano, F. A comprehensive meta-analysis on dietary flavonoid and lignan intake and cancer risk: Level of evidence and limitations. Mol. Nutr. Food Res. 2017, 61. [Google Scholar] [CrossRef]
- Hooper, L.; Kroon, P.A.; Rimm, E.B.; Cohn, J.S.; Harvey, I.; Le Cornu, K.A.; Ryder, J.J.; Hall, W.L.; Cassidy, A. Flavonoids, flavonoid-rich foods, and cardiovascular risk: A meta-analysis of randomized controlled trials. Am. J. Clin. Nutr. 2008, 88, 38–50. [Google Scholar] [CrossRef]
- Grosso, G.; Micek, A.; Godos, J.; Pajak, A.; Sciacca, S.; Galvano, F.; Giovannucci, E.L. Dietary Flavonoid and Lignan Intake and Mortality in Prospective Cohort Studies: Systematic Review and Dose-Response Meta-Analysis. Am. J. Epidemiol. 2017, 185, 1304–1316. [Google Scholar] [CrossRef] [PubMed]
- Godos, J.; Currenti, W.; Angelino, D.; Mena, P.; Castellano, S.; Caraci, F.; Galvano, F.; Del Rio, D.; Ferri, R.; Grosso, G. Diet and mental health: Review of the recent updates on molecular mechanisms. Antioxidants 2020, 9, 346. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Grosso, G.; Marventano, S.; D’Urso, M.; Mistretta, A.; Galvano, F. The Mediterranean healthy eating, ageing, and lifestyle (MEAL) study: Rationale and study design. Int. J. Food Sci. Nutr. 2017, 68, 577–586. [Google Scholar] [CrossRef] [PubMed]
- Craig, C.L.; Marshall, A.L.; Sjöström, M.; Bauman, A.E.; Booth, M.L.; Ainsworth, B.E.; Pratt, M.; Ekelund, U.; Yngve, A.; Sallis, J.F.; et al. International physical activity questionnaire: 12-country reliability and validity. Med. Sci. Sports Exerc. 2003, 35, 1381–1395. [Google Scholar] [CrossRef] [Green Version]
- Mistretta, A.; Marventano, S.; Platania, A.; Godos, J.; Galvano, F.; Grosso, G. Metabolic profile of the Mediterranean healthy Eating, Lifestyle and Aging (MEAL) study cohort. Med. J. Nutr. Metab. 2017, 10, 131–140. [Google Scholar] [CrossRef]
- Buscemi, S.; Rosafio, G.; Vasto, S.; Massenti, F.M.; Grosso, G.; Galvano, F.; Rini, N.; Barile, A.M.; Maniaci, V.; Cosentino, L.; et al. Validation of a food frequency questionnaire for use in Italian adults living in Sicily. Int. J. Food Sci. Nutr. 2015, 66, 426–438. [Google Scholar] [CrossRef]
- Marventano, S.; Mistretta, A.; Platania, A.; Galvano, F.; Grosso, G. Reliability and relative validity of a food frequency questionnaire for Italian adults living in Sicily, Southern Italy. Int. J. Food Sci. Nutr. 2016, 67, 857–864. [Google Scholar] [CrossRef]
- Italian Research Center for Foods and Nutrition. Available online: www.crea.gov.it/-/tabella-di-composizione-degli-alimenti (accessed on 17 July 2020).
- Godos, J.; Marventano, S.; Mistretta, A.; Galvano, F.; Grosso, G. Dietary sources of polyphenols in the Mediterranean healthy Eating, Aging and Lifestyle (MEAL) study cohort. Int. J. Food Sci. Nutr. 2017, 68, 750–756. [Google Scholar] [CrossRef]
- Phenol-Explorer. Available online: www.phenol-explorer.eu (accessed on 17 July 2020).
- Godos, J.; Rapisarda, G.; Marventano, S.; Galvano, F.; Mistretta, A.; Grosso, G. Association between polyphenol intake and adherence to the Mediterranean diet in Sicily, southern Italy. NFS J. 2017, 8, 1–7. [Google Scholar] [CrossRef]
- Pfeiffer, E. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J. Am. Geriatr. Soc. 1975, 23, 433–441. [Google Scholar] [CrossRef]
- Chang, S.-C.; Cassidy, A.; Willett, W.C.; Rimm, E.B.; O’Reilly, E.J.; Okereke, O.I. Dietary flavonoid intake and risk of incident depression in midlife and older women. Am. J. Clin. Nutr. 2016, 104, 704–714. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Godos, J.; Castellano, S.; Ray, S.; Grosso, G.; Galvano, F. Dietary Polyphenol Intake and Depression: Results from the Mediterranean Healthy Eating, Lifestyle and Aging (MEAL) Study. Molecules 2018, 23, 999. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Godos, J.; Ferri, R.; Castellano, S.; Angelino, D.; Mena, P.; Del Rio, D.; Caraci, F.; Galvano, F.; Grosso, G. Specific Dietary (Poly)phenols Are Associated with Sleep Quality in a Cohort of Italian Adults. Nutrients 2020, 12, 1226. [Google Scholar] [CrossRef] [PubMed]
- Devore, E.E.; Kang, J.H.; Breteler, M.M.B.; Grodstein, F. Dietary intakes of berries and flavonoids in relation to cognitive decline. Ann. Neurol. 2012, 72, 135–143. [Google Scholar] [CrossRef]
- Letenneur, L.; Proust-Lima, C.; Le Gouge, A.; Dartigues, J.F.; Barberger-Gateau, P. Flavonoid intake and cognitive decline over a 10-year period. Am. J. Epidemiol. 2007, 165, 1364–1371. [Google Scholar] [CrossRef]
- Kesse-Guyot, E.; Fezeu, L.; Andreeva, V.A.; Touvier, M.; Scalbert, A.; Hercberg, S.; Galan, P. Total and specific polyphenol intakes in midlife are associated with cognitive function measured 13 years later. J. Nutr. 2012, 142, 76–83. [Google Scholar] [CrossRef]
- Root, M.; Ravine, E.; Harper, A. Flavonol Intake and Cognitive Decline in Middle-Aged Adults. J. Med. Food 2015, 18, 1327–1332. [Google Scholar] [CrossRef] [Green Version]
- Shishtar, E.; Rogers, G.T.; Blumberg, J.B.; Au, R.; Jacques, P.F. Long-term dietary flavonoid intake and change in cognitive function in the Framingham Offspring cohort. Public Health Nutr. 2020, 23, 1576–1588. [Google Scholar] [CrossRef]
- Valls-Pedret, C.; Lamuela-Raventós, R.M.; Medina-Remón, A.; Quintana, M.; Corella, D.; Pintó, X.; Martínez-González, M.Á.; Estruch, R.; Ros, E. Polyphenol-rich foods in the Mediterranean diet are associated with better cognitive function in elderly subjects at high cardiovascular risk. J. Alzheimers Dis. 2012, 29, 773–782. [Google Scholar] [CrossRef] [Green Version]
- Bensalem, J.; Dudonné, S.; Etchamendy, N.; Pellay, H.; Amadieu, C.; Gaudout, D.; Dubreuil, S.; Paradis, M.-E.; Pomerleau, S.; Capuron, L.; et al. Polyphenols from Grape and Blueberry Improve Episodic Memory in Healthy Elderly with Lower Level of Memory Performance: A Bicentric Double-Blind, Randomized, Placebo-Controlled Clinical Study. J. Gerontol. A Biol. Sci. Med. Sci. 2019, 74, 996–1007. [Google Scholar] [CrossRef]
- Mastroiacovo, D.; Kwik-Uribe, C.; Grassi, D.; Necozione, S.; Raffaele, A.; Pistacchio, L.; Righetti, R.; Bocale, R.; Lechiara, M.C.; Marini, C.; et al. Cocoa flavanol consumption improves cognitive function, blood pressure control, and metabolic profile in elderly subjects: The Cocoa, Cognition, and Aging (CoCoA) Study--a randomized controlled trial. Am. J. Clin. Nutr. 2015, 101, 538–548. [Google Scholar] [CrossRef] [PubMed]
- Gorelick, P.B. Role of inflammation in cognitive impairment: Results of observational epidemiological studies and clinical trials. Ann. N. Y. Acad. Sci. 2010, 1207, 155–162. [Google Scholar] [CrossRef] [PubMed]
- Ceppa, F.; Mancini, A.; Tuohy, K. Current evidence linking diet to gut microbiota and brain development and function. Int. J. Food Sci. Nutr. 2019, 70, 1–19. [Google Scholar] [CrossRef] [PubMed]
- Salvucci, E. The human-microbiome superorganism and its modulation to restore health. Int. J. Food Sci. Nutr. 2019, 70, 781–795. [Google Scholar] [CrossRef]
- Tangestani Fard, M.; Stough, C. A review and hypothesized model of the mechanisms that underpin the relationship between inflammation and cognition in the elderly. Front. Aging Neurosci. 2019, 11, 56. [Google Scholar] [CrossRef] [Green Version]
- Walker, K.A.; Gottesman, R.F.; Wu, A.; Knopman, D.S.; Gross, A.L.; Mosley, T.H.; Selvin, E.; Windham, B.G. Systemic inflammation during midlife and cognitive change over 20 years: The ARIC Study. Neurology 2019, 92, e1256–e1267. [Google Scholar] [CrossRef] [PubMed]
- Hajjar, I.; Hayek, S.S.; Goldstein, F.C.; Martin, G.; Jones, D.P.; Quyyumi, A. Oxidative stress predicts cognitive decline with aging in healthy adults: An observational study. J. Neuroinflamm. 2018, 15, 17. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Youdim, K.A.; Dobbie, M.S.; Kuhnle, G.; Proteggente, A.R.; Abbott, N.J.; Rice-Evans, C. Interaction between flavonoids and the blood-brain barrier: In Vitro studies. J. Neurochem. 2003, 85, 180–192. [Google Scholar] [CrossRef]
- Kalt, W.; Blumberg, J.B.; McDonald, J.E.; Vinqvist-Tymchuk, M.R.; Fillmore, S.A.E.; Graf, B.A.; O’Leary, J.M.; Milbury, P.E. Identification of anthocyanins in the liver, eye, and brain of blueberry-fed pigs. J. Agric. Food Chem. 2008, 56, 705–712. [Google Scholar] [CrossRef]
- Mao, T.K.; Van De Water, J.; Keen, C.L.; Schmitz, H.H.; Gershwin, M.E. Cocoa flavonols and procyanidins promote transforming growth factor-beta1 homeostasis in peripheral blood mononuclear cells. Exp. Biol. Med. (Maywood) 2003, 228, 93–99. [Google Scholar] [CrossRef]
- Matias, I.; Morgado, J.; Gomes, F.C.A. Astrocyte heterogeneity: Impact to brain aging and disease. Front. Aging Neurosci. 2019, 11, 59. [Google Scholar] [CrossRef] [Green Version]
- Caraci, F.; Spampinato, S.F.; Morgese, M.G.; Tascedda, F.; Salluzzo, M.G.; Giambirtone, M.C.; Caruso, G.; Munafò, A.; Torrisi, S.A.; Leggio, G.M.; et al. Neurobiological links between depression and AD: The role of TGF-β1 signaling as a new pharmacological target. Pharmacol. Res. 2018, 130, 374–384. [Google Scholar] [CrossRef]
- Caraci, F.; Gulisano, W.; Guida, C.A.; Impellizzeri, A.A.R.; Drago, F.; Puzzo, D.; Palmeri, A. A key role for TGF-β1 in hippocampal synaptic plasticity and memory. Sci. Rep. 2015, 5, 11252. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Molaei, A.; Hatami, H.; Dehghan, G.; Sadeghian, R.; Khajehnasiri, N. Synergistic effects of quercetin and regular exercise on the recovery of spatial memory and reduction of parameters of oxidative stress in animal model of Alzheimer’s disease. EXCLI J. 2020, 19, 596–612. [Google Scholar] [CrossRef] [PubMed]
- Yu, X.; Li, Y.; Mu, X. Effect of Quercetin on PC12 Alzheimer’s Disease Cell Model Induced by Aβ25-35 and Its Mechanism Based on Sirtuin1/Nrf2/HO-1 Pathway. Biomed. Res. Int. 2020, 2020, 8210578. [Google Scholar] [CrossRef]
- Lee, B.; Yeom, M.; Shim, I.; Lee, H.; Hahm, D.-H. Protective Effects of Quercetin on Anxiety-Like Symptoms and Neuroinflammation Induced by Lipopolysaccharide in Rats. Evid. Based Complement. Alternat. Med. 2020, 2020, 4892415. [Google Scholar] [CrossRef] [PubMed]
- Rahvar, M.; Owji, A.A.; Mashayekhi, F.J. Effect of quercetin on the brain-derived neurotrophic factor gene expression in the rat brain. Bratisl. Lek. Listy 2018, 119, 28–31. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nakajima, K.; Niisato, N.; Marunaka, Y. Quercetin stimulates NGF-induced neurite outgrowth in PC12 cells via activation of Na(+)/K(+)/2Cl(-) cotransporter. Cell. Physiol. Biochem. 2011, 28, 147–156. [Google Scholar] [CrossRef]
- Gundimeda, U.; McNeill, T.H.; Fan, T.K.; Deng, R.; Rayudu, D.; Chen, Z.; Cadenas, E.; Gopalakrishna, R. Green tea catechins potentiate the neuritogenic action of brain-derived neurotrophic factor: Role of 67-kDa laminin receptor and hydrogen peroxide. Biochem. Biophys. Res. Commun. 2014, 445, 218–224. [Google Scholar] [CrossRef]
- Fang, J.-L.; Luo, Y.; Jin, S.-H.; Yuan, K.; Guo, Y. Ameliorative effect of anthocyanin on depression mice by increasing monoamine neurotransmitter and up-regulating BDNF expression. J. Funct. Foods 2020, 66, 103757. [Google Scholar] [CrossRef]
- Neshatdoust, S.; Saunders, C.; Castle, S.M.; Vauzour, D.; Williams, C.; Butler, L.; Lovegrove, J.A.; Spencer, J.P.E. High-flavonoid intake induces cognitive improvements linked to changes in serum brain-derived neurotrophic factor: Two randomised, controlled trials. Nutr. Healthy Aging 2016, 4, 81–93. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Total Polyphenol Intake | P | ||||
---|---|---|---|---|---|
Q1 (n = 184) | Q2 (n = 237) | Q3 (n = 253) | Q4 (n = 209) | ||
Age (years), mean (SD) | 67.3 (11.1) | 65.2 (9.2) | 63.9 (8.9) | 63.5 (8.6) | <0.001 a |
Men, n (%) | 124 (67.4) | 124 (52.3) | 146 (57.7) | 107 (51.2) | 0.004 b |
BMI, mean (SD) | 26.5 (4.4) | 26.7 (4.3) | 27.04 (4.4) | 27.2 (3.9) | 0.414 a |
Smoking status, n (%) | 0.665 b | ||||
Current | 43 (23.4) | 56 (23.6) | 53 (20.9) | 47 (22.5) | |
Former | 30 (16.3) | 52 (21.9) | 56 (22.1) | 49 (23.4) | |
Never | 111 (60.3) | 129 (54.4) | 144 (56.9) | 113 (54.1) | |
Educational level, n (%) | 0.003 b | ||||
Low | 105 (57.1) | 120 (50.6) | 114 (45.1) | 112 (53.6) | |
Medium | 58 (31.5) | 71 (30.0) | 103 (40.7) | 53 (25.4) | |
High | 21 (11.4) | 46 (19.4) | 36 (14.2) | 44 (21.1) | |
Occupational level, n (%) | 0.086 b | ||||
Unemployed | 47 (30.3) | 45 (21.6) | 54 (23.8) | 57 (31.1) | |
Low | 31 (20.0) | 43 (20.7) | 35 (15.4) | 26 (14.2) | |
Medium | 33 (21.3) | 69 (33.2) | 79 (34.8) | 53 (29.0) | |
High | 44 (28.4) | 51 (24.5) | 59 (26.0) | 47 (25.7) | |
Physical activity level, n (%) | 0.169 b | ||||
Low | 52 (33.8) | 55 (27.0) | 46 (21.7) | 43 (24.0) | |
Medium | 63 (40.9) | 100 (49.0) | 116 (54.7) | 91 (50.8) | |
High | 39 (25.3) | 49 (24.0) | 50 (23.6) | 45 (25.1) | |
Alcohol consumption, n (%) | <0.001 b | ||||
None | 58 (31.5) | 62 (26.2) | 41 (16.2) | 29 (13.9) | |
Moderate (0.1–12 g/d) | 121 (65.8) | 152 (64.1) | 151 (59.7) | 91 (43.5) | |
Regular (>12 g/d) | 5 (2.7) | 23 (9.7) | 61 (24.1) | 89 (42.6) | |
Health status, n (%) | |||||
Hypertension | 145 (78.8) | 185 (78.1) | 184 (72.7) | 146 (69.9) | 0.103 b |
Diabetes | 21 (11.4) | 50 (21.1) | 41 (16.2) | 32 (15.3) | 0.061 b |
Dyslipidaemias | 59 (32.1) | 89 (37.6) | 90 (35.6) | 64 (30.6) | 0.398 b |
Cardiovascular disease | 37 (20.6) | 32 (13.9) | 37 (15.2) | 30 (15.1) | 0.285 b |
Cancer | 17 (9.2) | 17 (7.2) | 18 (7.1) | 22 (10.5) | 0.492 b |
Menopausal status (women only), n (%) | 11 (8.6) | 13 (10.2) | 18 (11.8) | 6 (5.3) | 0.320 b |
Total energy intake (kcal/d), mean (SD) | 1768.3 (534.1) | 1900.1 (512.1) | 2026.9 (559.1) | 2486.1 (765.9) | <0.001 a |
Cognitive Status | |||
---|---|---|---|
Normal (n = 801) | Impaired (n = 82) | P-Value a | |
Mean (SD) | |||
Total flavonoids, mg/d | 250.2 (170.1) | 219.6 (238.2) | 0.137 |
Flavan-3-ols, mg/d | 86.10 (90.61) | 76.13 (170.87) | 0.394 |
Catechins, mg/d | 51.82 (60.24) | 49.69 (132.35) | 0.793 |
Flavonols, mg/d | 56.06 (40.33) | 54.52 (61.39) | 0.756 |
Quercetin, mg/d | 0.77 (1.01) | 0.70 (1.32) | 0.543 |
Kaempferol, mg/d | 0.25 (0.23) | 0.20 (0.18) | 0.053 |
Flavanones, mg/d | 37.92 (40.12) | 33.57 (51.39) | 0.365 |
Hesperetin, mg/d | 27.30 (28.94) | 24.01 (36.11) | 0.339 |
Naringenin, mg/d | 6.43 (7.16) | 4.82 (6.02) | 0.051 |
Flavones, mg/d | 7.86 (6.88) | 8.77(10.66) | 0.284 |
Apigenin, mg/d | 0.008 (0.004) | 0.009 (0.008) | 0.362 |
Luteolin, mg/d | 3.98 (3.72) | 4.38 (4.26) | 0.360 |
Anthocyanins, mg/d | 57.03 (54.79) | 42.14 (44.18) | 0.017 |
Flavonoid Quartiles, OR (95% CI) | ||||
---|---|---|---|---|
Q1 (n = 187) | Q2 (n = 243) | Q3 (n = 255) | Q4 (n = 198) | |
Total flavonoids | ||||
Energy-adjusted a | 1 | 0.35 (0.19, 0.65) | 0.15 (0.07, 0.34) | 0.48 (0.24, 0.94) |
Multivariate b | 1 | 0.37 (0.17, 0.79) | 0.13 (0.05, 0.35) | 0.39 (0.15, 1.00) |
Flavan-3-ols | ||||
Energy-adjusted a | 1 | 1.71 (0.75, 3.88) | 1.25 (0.42, 3.73) | 1.29 (0.28, 5.85) |
Multivariate b | 1 | 0.57 (0.26, 1.25) | 0.30 (0.11, 0.76) | 0.66 (0.29, 1.48) |
Catechins | ||||
Energy-adjusted a | 1 | 0.68 (0.38, 1.21) | 0.53 (0.29, 0.99) | 0.28 (0.11, 0.65) |
Multivariate b | 1 | 0.56 (0.27, 1.18) | 0.45 (0.20, 1.04) | 0.24 (0.08, 0.72) |
Flavonols | ||||
Energy-adjusted a | 1 | 0.90 (0.50, 1.59) | 0.36 (0.17, 0.75) | 0.75 (0.38, 1.47) |
Multivariate b | 1 | 0.57 (0.26, 1.25) | 0.30 (0.11, 0.76) | 0.66 (0.29, 1.48) |
Quercetin | ||||
Energy-adjusteda | 1 | 1.49 (0.80, 2.79) | 1.30 (0.70, 2.42) | 0.63 (0.29, 1.36) |
Multivariateb | 1 | 0.81 (0.33, 2.00) | 1.29 (0.57, 2.90) | 0.30 (0.10, 0.91) |
Kaempferol | ||||
Energy-adjusted a | 1 | 0.90 (0.47, 1.69) | 0.53 (0.27, 1.05) | 0.80 (0.41, 1.57) |
Multivariate b | 1 | 0.56 (0.25, 1.24) | 0.45 (0.20, 1.04) | 0.46 (0.16, 1.34) |
Flavanones | ||||
Energy-adjusted a | 1 | 0.77 (0.42, 1.43) | 0.73 (0.39, 1.37) | 0.56 (0.27, 1.15) |
Multivariate b | 1 | 0.92 (0.41, 2.08) | 0.88 (0.39, 1.97) | 1.05 (0.43, 2.55) |
Hesperetin | ||||
Energy-adjusted a | 1 | 0.80 (0.43, 1.47) | 0.75 (0.40, 1.40) | 0.57 (0.27, 1.16) |
Multivariate b | 1 | 1.08 (0.48, 2.40) | 0.92 (0.41, 2.05) | 1.20 (0.49, 2.92) |
Naringenin | ||||
Energy-adjusted a | 1 | 0.76 (0.41, 1.42) | 0.62 (0.31, 1.22) | 0.58 (0.28, 1.20) |
Multivariate b | 1 | 0.69 (0.31, 1.56) | 0.56 (0.24, 1.33) | 1.00 (0.41, 2.39) |
Flavones | ||||
Energy-adjusted a | 1 | 0.90 (0.47, 1.74) | 1.04 (0.54, 1.99) | 1.27 (0.66, 2.45) |
Multivariate b | 1 | 0.76 (0.34, 1.71) | 1.09 (0.49, 2.44) | 0.73 (0.31, 1.69) |
Apigenin | ||||
Energy-adjusted a | 1 | 0.69 (0.35, 1.37) | 0.60 (0.30, 1.18) | 0.89 (0.48, 1.63) |
Multivariate b | 1 | 1.02 (0.45, 2.35) | 0.41 (0.17, 1.02) | 0.92 (0.40, 2.12) |
Luteolin | ||||
Energy-adjusted a | 1 | 0.56 (0.27, 1.16) | 1.04 (0.55, 1.99) | 1.41 (0.74, 2.69) |
Multivariate b | 1 | 0.28 (0.10, 0.75) | 0.93 (0.43, 2.01) | 0.90 (0.40, 2.00) |
Anthocyanins | ||||
Energy-adjusted a | 1 | 0.80 (0.44, 1,46) | 0.54 (0.28, 1.04) | 0.65 (0.32, 1.31) |
Multivariate b | 1 | 0.88 (0.40, 1.93) | 0.49 (0.21, 1.15) | 0.38 (0.14, 1.00) |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Godos, J.; Caraci, F.; Castellano, S.; Currenti, W.; Galvano, F.; Ferri, R.; Grosso, G. Association Between Dietary Flavonoids Intake and Cognitive Function in an Italian Cohort. Biomolecules 2020, 10, 1300. https://doi.org/10.3390/biom10091300
Godos J, Caraci F, Castellano S, Currenti W, Galvano F, Ferri R, Grosso G. Association Between Dietary Flavonoids Intake and Cognitive Function in an Italian Cohort. Biomolecules. 2020; 10(9):1300. https://doi.org/10.3390/biom10091300
Chicago/Turabian StyleGodos, Justyna, Filippo Caraci, Sabrina Castellano, Walter Currenti, Fabio Galvano, Raffaele Ferri, and Giuseppe Grosso. 2020. "Association Between Dietary Flavonoids Intake and Cognitive Function in an Italian Cohort" Biomolecules 10, no. 9: 1300. https://doi.org/10.3390/biom10091300