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Association of Dietary Quality with Cognitive Function in Chinese Adults Aged 55 Years and Above: A Longitudinal Study

  • Original Research
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The journal of nutrition, health & aging

Abstract

Objectives

Diet is an important modifiable factor for brain health and aging. Present study aimed to explore association of dietary quality with cognitive function and poor cognition in middle-aged and older adults participating in the China Health and Nutrition Survey (CHNS).

Design

A longitudinal study with a twenty-year follow-up.

Setting and Participants

Data were drawn from the CHNS 1997, 2000, 2004, 2006, 2015 and 2018. Subjects aged 55 years and more who participated in at least two waves and had completed data on socio-demographics, lifestyle, disease history, anthropometrics, dietary measure and cognitive assessment were eligible in present study.

Methods

Baseline diet were assessed by 3-day 24-hour dietary recalls and used to evaluate diet quality via China Elderly Dietary Guidelines Index 2022 (CDGI 2022-E). Cognitive function was examined using part items of the Telephone Interview for Cognitive Status-modified. Three-level linear mixed effects models and three-level mixed effects logistic regression models were performed to estimate the association between diet quality and cognitive function and odds of poor cognition, respectively.

Results

At baseline, 4173 subjects with median age of 63.7 years were recruited. Median of CDGI 2022-E total score was 44.7. Median score of global cognition was 16.0, and the proportion of people with poor cognitive function was 13.9%. Difference in global cognitive score was observed by tertiles of CDGI 2022-E (p<0.05). Significant associations of high diet quality with increment in global cognitive score [β (95%CI): 0.704 (0.394∼1.015)], composite cognitive z score [0.086 (0.045∼0.128)] and standardized verbal memory score [0.221 (0.122∼0.320)] were observed in total subjects. Consistent associations were also found in those below 65 years at baseline. The likelihood of poor cognition in the highest tertile of CDGI 2022-E decreased by 18% (95%CI: 0.698∼0.965) relative to the lowest tertile group in total population.

Conclusions

High diet quality may be beneficial for improving cognitive function and delaying cognitive decline in Chinese middle-aged and older population.

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References

  1. Jia L, Du Y, Chu L, Zhang Z, Li F, Lyu D, 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. doi: https://doi.org/10.1016/S2468-2667(20)30185-7.

    PubMed  Google Scholar 

  2. Zhang Q, Wu Y, Han T, Liu E. Changes in Cognitive Function and Risk Factors for Cognitive Impairment of the Elderly in China: 2005–2014. Int J Environ Res Public Health 2019;16(16):2847. doi: https://doi.org/10.3390/ijerph16162847.

    PubMed  PubMed Central  Google Scholar 

  3. Kuchibhatla M, Hunter JC, Plassman BL, Lutz MW, Casanova R, Saldana S, et al. The association between neighborhood socioeconomic status, cardiovascular and cerebrovascular risk factors, and cognitive decline in the Health and Retirement Study (HRS). Aging Ment Health 2019;24(9):1479–1486. doi: https://doi.org/10.1080/13607863.2019.1594169.

    PubMed  PubMed Central  Google Scholar 

  4. Jia J, Zhao T, Liu Z, Liang Y, Li F, Li Y, et al. Association between healthy lifestyle and memory decline in older adults: 10 year, population based, prospective cohort study. BMJ 2023;380:e072691. doi: https://doi.org/10.1136/bmj-2022-072691.

    PubMed  PubMed Central  Google Scholar 

  5. Shi Z, Li M, Wang Y, Liu J, El-Obeid T. High iron intake is associated with poor cognition among Chinese old adults and varied by weight status-a 15-y longitudinal study in 4852 adults. Am J Clin Nutr 2019;109(1):109–116. doi: https://doi.org/10.1093/ajcn/nqy254.

    PubMed  PubMed Central  Google Scholar 

  6. Li S, Sun W, Zhang D. Association of Zinc, Iron, Copper, and Selenium Intakes with Low Cognitive Performance in Older Adults: A Cross-Sectional Study from National Health and Nutrition Examination Survey (NHANES). J Alzheimers Dis 2019;72(4):1145–1157.doi: https://doi.org/10.3233/JAD-190263.

    PubMed  Google Scholar 

  7. Qin B, Plassman BL, Edwards LJ, Popkin BM, Adair LS, Mendez MA. Fish intake is associated with slower cognitive decline in Chinese older adults. J Nutr 2014;144(10):1579–1585. doi: https://doi.org/10.3945/jn.114.193854.

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Nooyens ACJ, van Gelder BM, Bueno-de-Mesquita HB, van Boxtel MPJ, Verschuren WMM. Fish consumption, intake of fats and cognitive decline at middle and older age: the Doetinchem Cohort Study. Eur J Nutr 2018;57(4):1667–1675. doi: https://doi.org/10.1007/s00394-017-1453-8.

    CAS  PubMed  Google Scholar 

  9. Allés B, Samieri C, Féart C, Jutand MA, Laurin D, Barberger-Gateau P. Dietary patterns: a novel approach to examine the link between nutrition and cognitive function in older individuals. Nutr Res Rev 2012;25(2):207–222. doi: https://doi.org/10.1017/S0954422412000133.

    PubMed  Google Scholar 

  10. Samieri C, Okereke OI, E ED, Grodstein F. Long-term adherence to the Mediterranean diet is associated with overall cognitive status, but not cognitive decline, in women. J Nutr 2013;143(4):493–499. doi: https://doi.org/10.3945/jn.112.169896.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Wengreen H, Munger RG, Cutler A, Quach A, Bowles A, Corcoran C, et al. Prospective study of Dietary Approaches to Stop Hypertension- and Mediterranean-style dietary patterns and age-related cognitive change: the Cache County Study on Memory, Health and Aging. Am J Clin Nutr 2013;98(5):1263–1271. doi: https://doi.org/10.3945/ajcn.112.051276.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Kheirouri S, Alizadeh M. MIND diet and cognitive performance in older adults: a systematic review. Crit Rev Food Sci Nutr 2022;62(29):8059–8077. doi: https://doi.org/10.1080/10408398.2021.1925220.

    PubMed  Google Scholar 

  13. Milte CM, Ball K, Crawford D, McNaughton SA. Diet quality and cognitive function in mid-aged and older men and women. BMC Geriatr 2019;19(1):361. doi: https://doi.org/10.1186/s12877-019-1326-5.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Tangney CC, Kwasny MJ, Li H, Wilson RS, Evans DA, Morris MC. Adherence to a Mediterranean-type dietary pattern and cognitive decline in a community population. Am J Clin Nutr 2011;93(3):601–607. doi: https://doi.org/10.3945/ajcn.110.007369.

    CAS  PubMed  Google Scholar 

  15. Shatenstein B, Ferland G, Belleville S, Gray-Donald K, Kergoat MJ, Morais J, et al. Diet quality and cognition among older adults from the NuAge study. Exp Gerontol 2012;47(5):353–360. doi: https://doi.org/10.1016/j.exger.2012.02.002.

    PubMed  Google Scholar 

  16. Kim E, Choi BY, Kim MK, Yang YJ. Association of diet quality score with the risk of mild cognitive impairment in the elderly. Nutr Res Pract 2022;16(5):673–684. doi: https://doi.org/10.4162/nrp.2022.16.5.673.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Qin B, Adair LS, Plassman BL, Batis C, Edwards LJ, Popkin BM, et al. Dietary Patterns and Cognitive Decline Among Chinese Older Adults. Epidemiology 2015;26(5):758–768. doi: https://doi.org/10.1097/EDE.0000000000000338.

    PubMed  PubMed Central  Google Scholar 

  18. Huang X, Aihemaitijiang S, Ye C, Halimulati M, Wang R, Zhang Z. Development of the cMIND Diet and Its Association with Cognitive Impairment in Older Chinese People. J Nutr Health Aging 2022;26(8):760–770. doi: https://doi.org/10.1007/s12603-022-1829-1.

    CAS  PubMed  Google Scholar 

  19. Nagel G, Wabitsch M, Galm C, Berg S, Brandstetter S, Fritz M, et al. Secular changes of anthropometric measures for the past 30 years in South-West Germany. Eur J Clin Nutr 2009;63(12):1440–1443. doi: https://doi.org/10.1038/ejcn.2009.86.

    CAS  PubMed  Google Scholar 

  20. Verly-Jr E, Oliveira DC, Fisberg RM, Marchioni DM. Performance of statistical methods to correct food intake distribution: comparison between observed and estimated usual intake. Br J Nutr 2016;116(5):897–903. doi: https://doi.org/10.1017/S0007114516002725.

    CAS  PubMed  Google Scholar 

  21. Yuan YQ, Li F, Dong RH, Chen JS, He GS, Li SG, et al. The Development of a Chinese Healthy Eating Index and Its Application in the General Population. Nutrients 2017;9(9):977. doi: https://doi.org/10.3390/nu9090977.

    PubMed  PubMed Central  Google Scholar 

  22. Wang Z, Siega-Riz AM, Gordon-Larsen P, Cai J, Adair LS, Zhang B, et al. Diet quality and its association with type 2 diabetes and major cardiometabolic risk factors among adults in China. Nutr Metab Cardiovasc Dis 2018;28(10):987–1001. doi: https://doi.org/10.1016/j.numecd.2018.06.012.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Soedamah-Muthu SS, Verberne LD, Ding EL, Engberink MF, Geleijnse JM. Dairy consumption and incidence of hypertension: a dose-response meta-analysis of prospective cohort studies. Hypertension 2012;60(5):1131–1137. doi: https://doi.org/10.1161/HYPERTENSIONAHA.112.195206.

    CAS  PubMed  Google Scholar 

  24. Zhu S, He M, Su D, Zou Y, Liu J, Deng Y, et al. Association between the diet balance index-based dietary quality and cognitive function among Zhejiang population aged 40 years and older. Wei Sheng Yan Jiu 2022;51(3):374–380. doi: https://doi.org/10.19813/j.cnki.weishengyanjiu.2022.03.005.

    PubMed  Google Scholar 

  25. Ding K, Zhou H, Gao T, Xu R, Chen L, Cai J, et al. Dietary patterns and cognitive function in older adults residing in rural China. Asia Pac J Clin Nutr 2021;30(2):253–262. doi: https://doi.org/10.6133/apjcn.202106_30(2).0010.

    CAS  PubMed  Google Scholar 

  26. Zhang X, Wang Y, Liu W, Wang T, Wang L, Hao L, et al. Diet quality, gut microbiota, and microRNAs associated with mild cognitive impairment in middle-aged and elderly Chinese population. Am J Clin Nutr 2021;114(2):429–440. doi: https://doi.org/10.1093/ajcn/nqab078.

    PubMed  Google Scholar 

  27. Zhang B, Zhai FY, Du SF, Popkin BM. The China Health and Nutrition Survey, 1989–2011. Obes Rev 2014;15 Suppl 1:2–7. doi: https://doi.org/10.1111/obr.12119.

    PubMed  Google Scholar 

  28. Popkin BM, Du S, Zhai F, Zhang B. Cohort Profile: The China Health and Nutrition Survey—monitoring and understanding socio-economic and health change in China, 1989–2011. Int J Epidemiol 2010;39(6):1435–1440. doi: https://doi.org/10.1093/ije/dyp322.

    PubMed  Google Scholar 

  29. Wang L, Zhang B, Wang H, Du W, Zhang J, Wang Z. Establishment and application of China Elderly Dietary Guideline Index 2018 in the elderly of 15 provinces. Wei Sheng Yan Jiu 2019;48(1):41–48.doi:https://doi.org/10.19813/j.cnki.weishengyanjiu.2019.01.005.

    CAS  PubMed  Google Scholar 

  30. Wang Y, Howard AG, Adair LS, Wang H, Avery CL, Gordon-Larsen P. Waist Circumference Change is Associated with Blood Pressure Change Independent of BMI Change. Obesity (Silver Spring) 2020;28(1):146–153. doi: https://doi.org/10.1002/oby.22638.

    PubMed  Google Scholar 

  31. Yang Y, Wang G, Pan X (2009) China Food Composition Table 2nd ed. Peking University Medical Press, Beijing, China.

    Google Scholar 

  32. Chinese Nutrition Society (2022) Dietary guidelines for Chinese (2022). People’s Medical Publishing House, Beijing, China.

    Google Scholar 

  33. Shi Z, El-Obeid T, Li M, Xu X, Liu J. Iron-related dietary pattern increases the risk of poor cognition. Nutr J 2019;18(1):48. doi: https://doi.org/10.1186/s12937-019-0476-9.

    PubMed  PubMed Central  Google Scholar 

  34. Jones-Smith JC, Popkin BM. Understanding community context and adult health changes in China: development of an urbanicity scale. Soc Sci Med 2010;71(8):1436–1446. doi: https://doi.org/10.1016/j.socscimed.2010.07.027.

    PubMed  PubMed Central  Google Scholar 

  35. Zhang X, Huang F, Zhang J, Wei Y, Bai J, Wang H, et al. Association between Micronutrient-Related Dietary Pattern and Cognitive Function among Persons 55 Years and Older in China: A Longitudinal Study. Nutrients 2023;15(3):481. doi: https://doi.org/10.3390/nu15030481.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 1995;854:1–452.

  37. Berding K, Vlckova K, Marx W, Schellekens H, Stanton C, Clarke G, et al. Diet and the Microbiota-Gut-Brain Axis: Sowing the Seeds of Good Mental Health. Adv Nutr 2021;12(4):1239–1285. doi: https://doi.org/10.1093/advances/nmaa181.

    PubMed  PubMed Central  Google Scholar 

  38. Moore K, Hughes CF, Ward M, Hoey L, McNulty H. Diet, nutrition and the ageing brain: current evidence and new directions. Proc Nutr Soc 2018;77(2):152–163. doi: https://doi.org/10.1017/S0029665117004177.

    PubMed  Google Scholar 

  39. Huang F, Wang Z, Wang L, Wang H, Zhang J, Du W, et al. Evaluating adherence to recommended diets in adults 1991–2015: revised China dietary guidelines index. Nutr J 2019;18(1):70. doi: https://doi.org/10.1186/s12937-019-0498-3.

    PubMed  PubMed Central  Google Scholar 

  40. Wu L, Sun D. Adherence to Mediterranean diet and risk of developing cognitive disorders: An updated systematic review and meta-analysis of prospective cohort studies. Sci Rep 2017;7:41317. doi: https://doi.org/10.1038/srep41317.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Bloom I, Edwards M, Jameson KA, Syddall HE, Dennison E, Gale CR, et al. Influences on diet quality in older age: the importance of social factors. Age Ageing 2017;46(2):277–283. doi: https://doi.org/10.1093/ageing/afw180.

    PubMed  Google Scholar 

  42. Zabetian-Targhi F, Srikanth VK, Beare R, Moran C, Wang W, Breslin M, et al. Adherence to the Australian Dietary Guidelines Is Not Associated with Brain Structure or Cognitive Function in Older Adults. J Nutr 2020;150(6):1529–1534. doi: https://doi.org/10.1093/jn/nxaa052.

    PubMed  Google Scholar 

  43. Puri S, Shaheen M, Grover B. Nutrition and cognitive health: A life course approach. Front Public Health 2023;11:1023907. doi: https://doi.org/10.3389/fpubh.2023.1023907.

    PubMed  PubMed Central  Google Scholar 

  44. Krivanek TJ, Gale SA, McFeeley BM, Nicastri CM, Daffner KR. Promoting Successful Cognitive Aging: A Ten-Year Update. J Alzheimers Dis 2021;81(3):871–920. doi: https://doi.org/10.3233/JAD-201462.

    PubMed  PubMed Central  Google Scholar 

  45. Sun K, Hu H, Yang C, Wang L, Ai Y, Dong X, et al. Dietary Intake is Positively Associated with Cognitive Function of a Chinese Older Adults Sample. J Nutr Health Aging 2018;22(7):805–810. doi: https://doi.org/10.1007/s12603-018-1048-y.

    CAS  PubMed  Google Scholar 

  46. Cahoon D, Shertukde SP, Avendano EE, Tanprasertsuk J, Scott TM, Johnson EJ, et al. Walnut intake, cognitive outcomes and risk factors: a systematic review and meta-analysis. Ann Med 2021;53(1):971–997. doi: https://doi.org/10.1080/07853890.2021.1925955.

    PubMed  PubMed Central  Google Scholar 

  47. Cuesta-Triana F, Verdejo-Bravo C, Fernandez-Perez C, Martin-Sanchez FJ. Effect of Milk and Other Dairy Products on the Risk of Frailty, Sarcopenia, and Cognitive Performance Decline in the Elderly: A Systematic Review. Adv Nutr 2019;10(suppl_2):S105–S119. doi: https://doi.org/10.1093/advances/nmy105.

    PubMed  PubMed Central  Google Scholar 

  48. Ding B, Xiao R, Ma W, Zhao L, Bi Y, Zhang Y. The association between macronutrient intake and cognition in individuals aged under 65 in China: a cross-sectional study. BMJ open 2018;8(1):e018573. doi: https://doi.org/10.1136/bmjopen-2017-018573.

    PubMed  PubMed Central  Google Scholar 

  49. He FJ, Tan M, Ma Y, MacGregor GA. Salt Reduction to Prevent Hypertension and Cardiovascular Disease: JACC State-of-the-Art Review. J Am Coll Cardiol 2020;75(6):632–647. doi: https://doi.org/10.1016/j.jacc.2019.11.055.

    CAS  PubMed  Google Scholar 

  50. Lourenco J, Serrano A, Santos-Silva A, Gomes M, Afonso C, Freitas P, et al. Cardiovascular Risk Factors Are Correlated with Low Cognitive Function among Older Adults Across Europe Based on The SHARE Database. Aging Dis 2018;9(1):90–101. doi: https://doi.org/10.14336/AD.2017.0128.

    PubMed  PubMed Central  Google Scholar 

  51. Mohan D, Yap KH, Reidpath D, Soh YC, McGrattan A, Stephan BCM, et al. Link Between Dietary Sodium Intake, Cognitive Function, and Dementia Risk in Middle-Aged and Older Adults: A Systematic Review. J Alzheimers Dis. 2020;76(4):1347–1373. doi: https://doi.org/10.3233/JAD-191339.

    PubMed  PubMed Central  Google Scholar 

  52. Rush TM, Kritz-Silverstein D, Laughlin GA, Fung TT, Barrett-Connor E, McEvoy LK. Association between Dietary Sodium Intake and Cognitive Function in Older Adults. J Nutr Health Aging 2017;21(3):276–283. doi: https://doi.org/10.1007/s12603-016-0766-2.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Tan SY, Georgousopoulou EN, Cardoso BR, Daly RM, George ES. Associations between nut intake, cognitive function and non-alcoholic fatty liver disease (NAFLD) in older adults in the United States: NHANES 2011–14. BMC Geriatr 2021;21(1):313. doi: https://doi.org/10.1186/s12877-021-02239-1.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Yin Z, Chen J, Zhang J, Ren Z, Dong K, Kraus VB, et al. Dietary Patterns Associated with Cognitive Function among the Older People in Underdeveloped Regions: Finding from the NCDFaC Study. Nutrients 2018;10(4):464. doi: https://doi.org/10.3390/nu10040464.

    PubMed  PubMed Central  Google Scholar 

  55. Zhu N, Jacobs DR, Meyer KA, He K, Launer L, Reis JP, et al. Cognitive function in a middle aged cohort is related to higher quality dietary pattern 5 and 25 years earlier: the CARDIA study. J Nutr Health Aging 2015;19(1):33–38. doi: https://doi.org/10.1007/s12603-014-0491-7.

    CAS  PubMed  PubMed Central  Google Scholar 

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Funding

This work was funded by the Abbott Research Fund for Food Nutrition and Safety from Chinese Institute of Food Science and Technology (2019–27). The CHNS has been funded by the National Institutes of Health (NIH), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01 HD30880), the National Institute on Aging (R01 AG065357), the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK104371 and R01HL108427) and the NIH Fogarty International Center grant (D43 TW009077).

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Correspondence to Huijun Wang.

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The CHNS was approved by the Ethics Committee of National Institute for Nutrition and Health (No. 201524). All subjects gave their informed consent for inclusion before participation.

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Jia, X., Su, C., Du, W. et al. Association of Dietary Quality with Cognitive Function in Chinese Adults Aged 55 Years and Above: A Longitudinal Study. J Nutr Health Aging 27, 514–523 (2023). https://doi.org/10.1007/s12603-023-1941-x

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  • DOI: https://doi.org/10.1007/s12603-023-1941-x

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