Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-20T12:27:39.548Z Has data issue: false hasContentIssue false
  • English
  • Français

Trajectories of cognitive function and their determinants in older people: 12 years of follow-up in the Chinese Longitudinal Healthy Longevity Survey

Published online by Cambridge University Press:  27 April 2020

Lihui Tu ,
Xiaozhen Lv ,
Changzheng Yuan ,
Ming Zhang ,
Zili Fan ,
Xiaolin Xu ,
Yi Zeng ,
Xin Yu  and
Huali Wang Open the ORCID record for Huali Wang [Opens in a new window]
Lihui Tu
Affiliation:
Dementia Care and Research Center, Clinical Research Division, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
Xiaozhen Lv
Affiliation:
Dementia Care and Research Center, Clinical Research Division, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
Changzheng Yuan
Affiliation:
School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Ming Zhang
Affiliation:
Dementia Care and Research Center, Clinical Research Division, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
Zili Fan
Affiliation:
Dementia Care and Research Center, Clinical Research Division, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
Xiaolin Xu
Affiliation:
School of Public Health, Zhejiang University, Hangzhou, Zhejiang, China Center for Longitudinal and Lifecourse Epidemiology, School of Public Health, The University of Queensland, Brisbane, QLD, Australia
Yi Zeng
Affiliation:
Center for the Study of Aging and Human Development, Medical School of Duke University, Durham, NC, USA Center for Healthy Aging and Development Studies, National School of Development, Raissun Institute for Advanced Studies, Peking University, Beijing, China
Xin Yu*
Affiliation:
Dementia Care and Research Center, Clinical Research Division, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
Huali Wang*
Affiliation:
Dementia Care and Research Center, Clinical Research Division, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China Beijing Dementia Key Lab, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
*
*Correspondence should be addressed to: Dr. Huali Wang, Dementia Care and Research Center, Peking University Institute of Mental Health, No. 51 Huayuanbei Road, Haidian District, Beijing100191, China. Phone: +86-10-82801983. Fax: +86-10-62011769. Email: [email protected] or Dr. Xin Yu, Beijing Dementia Key Lab, Peking University Institute of Mental Health, Beijing, China. Phone: +86-10-82801999. Fax: +86-10-62026310. Email: [email protected].
*Correspondence should be addressed to: Dr. Huali Wang, Dementia Care and Research Center, Peking University Institute of Mental Health, No. 51 Huayuanbei Road, Haidian District, Beijing100191, China. Phone: +86-10-82801983. Fax: +86-10-62011769. Email: [email protected] or Dr. Xin Yu, Beijing Dementia Key Lab, Peking University Institute of Mental Health, Beijing, China. Phone: +86-10-82801999. Fax: +86-10-62026310. Email: [email protected].
Get access

Abstract

Background:

Cognitive decline in advanced age is closely related to dementia. The trajectory of cognitive function in older Chinese is yet to be fully investigated. We aimed to investigate the trajectories of cognitive function in a nationally representative sample of older people living in China and to explore the potential determinants of these trajectories.

Methods:

This study included 2,038 cognitively healthy persons aged 65–104 years at their first observation in the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2014. Cognitive function was measured using the Chinese version of the Mini-Mental State Examination (MMSE). Group-based trajectory modeling was used to identify potential heterogeneity of longitudinal changes over the 12 years and to investigate associations between baseline predictors of group membership and these trajectories.

Results:

Three trajectories were identified according to the following types of changes in MMSE scores: slow decline (14.0%), rapid decline (4.5%), and stable function (81.5%). Older age, female gender, having no schooling, a low frequency of leisure activity, and a low baseline MMSE score were associated with the slow decline trajectory. Older age, body mass index (BMI) less than 18.5 kg/m2, and having more than one cardiovascular disease (CVD) were associated with the rapid decline trajectory.

Conclusion:

Three trajectories of cognitive function were identified in the older Chinese population. The identified determinants of these trajectories could be targeted for developing prevention and intervention strategies for dementia.

Keywords

cognitive functiongroup-based trajectory modellongitudinalChinese Longitudinal Healthy Longevity Surveyrisk factors
Type
Original Research Article
Information
International Psychogeriatrics , Volume 32 , Issue 6: Issue Theme: Interaction of Depression and Cognition in Older Age , June 2020 , pp. 765 - 775
Copyright
© International Psychogeriatric Association 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

#

These authors have contributed equally to this work.

References

Alzheimer’s Association. (2019). 2019 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 15(3), 321–387. https://doi.org/10.1016/j.jalz.2019.01.010CrossRefGoogle Scholar
An, R. and Liu, G. G. (2016). Cognitive impairment and mortality among the oldest-old Chinese. International Journal of Geriatric Psychiatry, 31(12), 1345–1353. https://doi.org/10.1002/gps.4442CrossRefGoogle ScholarPubMed
Arevalo-Rodriguez, I.et al. (2015). Mini-Mental State Examination (MMSE) for the detection of Alzheimer’s disease and other dementias in people with mild cognitive impairment (MCI). The Cochrane Database of Systematic Reviews, 3, CD010783. https://doi.org/10.1002/14651858.CD010783.pub2CrossRefGoogle Scholar
Baumgart, M., Snyder, H. M., Carrillo, M. C., Fazio, S., Kim, H., and Johns, H. (2015). Summary of the evidence on modifiable risk factors for cognitive decline and dementia: a population-based perspective. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 11(6), 718–726. https://doi.org/10.1016/j.jalz.2015.05.016CrossRefGoogle ScholarPubMed
Beydoun, M. A., Beydoun, H. A., Gamaldo, A. A., Teel, A., Zonderman, A. B. and Wang, Y. (2014). Epidemiologic studies of modifiable factors associated with cognition and dementia: systematic review and meta-analysis. BMC Public Health, 14, 643. https://doi.org/10.1186/1471-2458-14-643CrossRefGoogle ScholarPubMed
Blazer, D. G., Yaffe, K., and Liverman, C. T. (2015). Cognitive Aging: Progress in Understanding and Opportunities for Action. Washington, DC: National Academy of Sciences. https://doi.org/10.17226/21693Google Scholar
Breteler, M. M.et al. (1994). Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology, 44(7), 1246–1252. https://doi.org/10.1212/wnl.44.7.1246CrossRefGoogle Scholar
Caracciolo, B., Gatz, M., Xu, W., Marengoni, A., Pedersen, N. L., and Fratiglioni, L. (2013). Relationship of subjective cognitive impairment and cognitive impairment no dementia to chronic disease and multimorbidity in a nation-wide twin study. Journal of Alzheimer’s Disease: JAD, 36(2), 275–284. https://doi.org/10.3233/JAD-122050CrossRefGoogle Scholar
Dahl, A. K., Hassing, L. B., Fransson, E. I., Gatz, M., Reynolds, C. A., and Pedersen, N. L. (2013). Body mass index across midlife and cognitive change in late life. International Journal of Obesity (2005), 37(2), 296–302. https://doi.org/10.1038/ijo.2012.37CrossRefGoogle ScholarPubMed
Doi, T.et al. (2017). Effects of Cognitive Leisure Activity on Cognition in Mild Cognitive Impairment: results of a Randomized Controlled Trial. Journal of the American Medical Directors Association, 18(8), 686–691. https://doi.org/10.1016/j.jamda.2017.02.013CrossRefGoogle ScholarPubMed
Feinkohl, I.et al. (2018). Association of obesity, diabetes and hypertension with cognitive impairment in older age. Clinical Epidemiology, 10, 853–862. https://doi.org/10.2147/CLEP.S164793CrossRefGoogle ScholarPubMed
Gow, A. J.et al. (2012a). Neuroprotective lifestyles and the aging brain: activity, atrophy, and white matter integrity. Neurology, 79(17), 1802–1808. https://doi.org/10.1212/WNL.0b013e3182703fd2CrossRefGoogle ScholarPubMed
Gow, A. J., Mortensen, E. L., and Avlund, K. (2012b). Activity participation and cognitive aging from age 50 to 80 in the glostrup 1914 cohort. Journal of the American Geriatrics Society, 60(10), 1831–1838. https://doi.org/10.1111/j.1532-5415.2012.04168.xCrossRefGoogle ScholarPubMed
Hartley, P.et al. (2017). The association between cognitive impairment and functional outcome in hospitalised older patients: a systematic review and meta-analysis. Age and Ageing, 46(4), 559–567. https://doi.org/10.1093/ageing/afx007Google ScholarPubMed
Haviland, A. M., Jones, B. L., and Nagin, D. S. (2011). Group-based Trajectory Modeling Extended to Account for Nonrandom Participant Attrition. Sociological Methods & Research, 40(2), 367–390. https://doi.org/10.1177/0049124111400041CrossRefGoogle Scholar
Hou, C.et al. (2018). Cognitive functioning transitions, health expectancies, and inequalities among elderly people in China: a nationwide longitudinal study. International Journal of Geriatric Psychiatry, 33(12), 1635–1644. https://doi.org/10.1002/gps.4966CrossRefGoogle ScholarPubMed
Ihle, A.et al. (2020). The longitudinal relation between social reserve and smaller subsequent decline in executive functioning in old age is mediated via cognitive reserve. International Psychogeriatrics, in press. https://doi.org/10.1017/S1041610219001789CrossRefGoogle Scholar
Johnson, D. K., Wilkins, C. H., and Morris, J. C. (2006). Accelerated weight loss may precede diagnosis in Alzheimer disease. Archives of Neurology, 63(9), 1312–1317. https://doi.org/10.1001/archneur.63.9.1312CrossRefGoogle ScholarPubMed
Jones, B. L., and Nagin, D. S. (2013). A Note on a Stata Plugin for Estimating Group-based Trajectory Models. Sociological Methods & Research, 42(4), 608–613. https://doi.org/10.1177/0049124113503141CrossRefGoogle Scholar
Kim, G., Choi, S. and Lyu, J. (2019). Body mass index and trajectories of cognitive decline among older Korean adults. Aging & Mental Health, 1–7. https://doi.org/10.1080/13607863.2018.1550628CrossRefGoogle Scholar
Kojima, G. (2018). Quick and simple FRAIL scale predicts incident activities of daily living (ADL) and instrumental ADL (IADL) disabilities: a systematic review and meta-analysis. Journal of the American Medical Directors Association, 19(12), 1063–1068. https://doi.org/10.1016/j.jamda.2018.07.019CrossRefGoogle ScholarPubMed
Laditka, J. N.et al. (2011). Older adults’ concerns about cognitive health: commonalities and differences among six United States ethnic groups. Ageing & Society, 31(7), 1202–1228. https://doi.org/10.1017/S0144686X10001273CrossRefGoogle Scholar
Li, G.et al. (2017a). Cognitive trajectory changes over 20 years before dementia diagnosis: a large cohort study. Journal of the American Geriatrics Society, 65(12), 2627–2633. https://doi.org/10.1111/jgs.15077CrossRefGoogle ScholarPubMed
Li, L. W., Ding, D., Wu, B., and Dong, X. (2017b). Change of cognitive function in U.S. Chinese older adults: a population-based study. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 72(Suppl 1), S5–S10. https://doi.org/10.1093/gerona/glx004CrossRefGoogle ScholarPubMed
Lindbergh, C. A., Dishman, R. K., and Miller, L. S. (2016). Functional disability in mild cognitive impairment: a systematic review and meta-analysis. Neuropsychology Review, 26(2), 129–159. https://doi.org/10.1007/s11065-016-9321-5CrossRefGoogle ScholarPubMed
Lipnicki, D. M.et al. (2019). Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: a COSMIC collaboration cohort study. PLoS Medicine, 16(7), e1002853. https://doi.org/10.1371/journal.pmed.1002853CrossRefGoogle ScholarPubMed
Lv, X.et al. (2019). Cognitive decline and mortality among community-dwelling Chinese older people. BMC Medicine, 17(1), 63. https://doi.org/10.1186/s12916-019-1295-8CrossRefGoogle ScholarPubMed
Lv, Y.-B.et al. (2018). Revisiting the association of blood pressure with mortality in oldest old people in China: community based, longitudinal prospective study. BMJ, 361, k2158. https://doi.org/10.1136/bmj.k2158CrossRefGoogle ScholarPubMed
Marioni, R. E.et al. (2014). Cognitive lifestyle jointly predicts longitudinal cognitive decline and mortality risk. European Journal of Epidemiology, 29(3), 211–219. https://doi.org/10.1007/s10654-014-9881-8CrossRefGoogle ScholarPubMed
Min, J. W. (2018). A longitudinal study of cognitive trajectories and its factors for Koreans aged 60 and over: a latent growth mixture model. International Journal of Geriatric Psychiatry, 33(5), 755–762. https://doi.org/10.1002/gps.4855CrossRefGoogle ScholarPubMed
Nagin, D. (2005). Group-Based Modeling of Development. Cambridge, MA: Harvard University Press.10.4159/9780674041318CrossRefGoogle Scholar
Nagin, D. S. (1999). Analyzing developmental trajectories: a semiparametric, group-based approach. Psychological Methods, 4(2), 139–157. https://doi.org/10.1037/1082-989X.4.2.139CrossRefGoogle Scholar
Nagin, D. S. and Odgers, C. L. (2010). Group-based trajectory modeling in clinical research. Annual Review of Clinical Psychology, 6, 109–138. https://doi.org/10.1146/annurev.clinpsy.121208.131413CrossRefGoogle ScholarPubMed
Olaya, B., Bobak, M., Haro, J. M., and Demakakos, P. (2017). Trajectories of verbal episodic memory in middle-aged and older adults: evidence from the English longitudinal study of ageing. Journal of the American Geriatrics Society, 65(6), 1274–1281. https://doi.org/10.1111/jgs.14789CrossRefGoogle ScholarPubMed
Sabia, S., Kivimaki, M., Shipley, M. J., Marmot, M. G., and Singh-Manoux, A. (2009). Body mass index over the adult life course and cognition in late midlife: the Whitehall II Cohort study. The American Journal of Clinical Nutrition, 89(2), 601–607. https://doi.org/10.3945/ajcn.2008.26482CrossRefGoogle ScholarPubMed
Samieri, C.et al. (2018). Association of cardiovascular health level in older age with cognitive decline and incident dementia. JAMA, 320(7), 657–664. https://doi.org/10.1001/jama.2018.11499CrossRefGoogle ScholarPubMed
Small, B. J., and Bäckman, L. (2007). Longitudinal trajectories of cognitive change in preclinical Alzheimer’s disease: a growth mixture modeling analysis. Cortex, 43(7), 826–834. https://doi.org/10.1016/S0010-9452(08)70682-8CrossRefGoogle ScholarPubMed
Tampubolon, G. (2015). Cognitive ageing in Great Britain in the new century: cohort differences in episodic memory. PloS One, 10(12), e0144907. https://doi.org/10.1371/journal.pone.0144907CrossRefGoogle ScholarPubMed
Taniguchi, Y.et al. (2017). Mini-mental state examination score trajectories and incident disabling dementia among community-dwelling older Japanese adults. Geriatrics & Gerontology International, 17(11), 1928–1935. https://doi.org/10.1111/ggi.12996CrossRefGoogle ScholarPubMed
Taylor, C. A. (2018). Subjective cognitive decline among adults aged ≥45 years — United States, 2015–2016. MMWR. Morbidity and Mortality Weekly Report, 67. https://doi.org/10.15585/mmwr.mm6727a1CrossRefGoogle Scholar
Wang, F., Zhen, Q., Li, K., and Wen, X. (2018). Association of socioeconomic status and health-related behavior with elderly health in China. PloS One, 13(9), e0204237. https://doi.org/10.1371/journal.pone.0204237CrossRefGoogle ScholarPubMed
Warren, J. R., Luo, L., Halpern-Manners, A., Raymo, J. M., and Palloni, A. (2015). Do different methods for modeling age-graded trajectories yield consistent and valid results? AJS; American Journal of Sociology, 120(6), 1809–1856. https://doi.org/10.1086/681962CrossRefGoogle ScholarPubMed
WHO | Ageing and health. (2018). Retrieved September 7, 2019, from https://www.who.int/news-room/fact-sheets/detail/ageing-and-healthGoogle Scholar
WHO | Risk reduction of cognitive decline and dementia. (2019). WHO. Retrieved September 3, 2019, from http://www.who.int/mental_health/neurology/dementia/guidelines_risk_reduction/en/Google Scholar
Yohannes, A. M., Chen, W., Moga, A. M., Leroi, I., and Connolly, M. J. (2017). Cognitive impairment in chronic obstructive pulmonary disease and chronic heart failure: a systematic review and meta-analysis of observational studies. Journal of the American Medical Directors Association, 18(5), 451.e1–451.e11. https://doi.org/10.1016/j.jamda.2017.01.014CrossRefGoogle ScholarPubMed
Zaninotto, P., Batty, G. D., Allerhand, M., and Deary, I. J. (2018). Cognitive function trajectories and their determinants in older people: 8 years of follow-up in the English longitudinal study of ageing. Journal of Epidemiology and Community Health, 72(8), 685–694. https://doi.org/10.1136/jech-2017-210116CrossRefGoogle ScholarPubMed
Zeng, Y. (2012). Towards Deeper Research and Better Policy for Healthy Aging --Using the Unique Data of Chinese Longitudinal Healthy Longevity Survey. China Economic Journal, 5(2–3), 131–149. https://doi.org/10.1080/17538963.2013.764677CrossRefGoogle ScholarPubMed
Zeng, Y., Feng, Q., Hesketh, T., Christensen, K., and Vaupel, J. W. (2017). Survival, disabilities in activities of daily living, and physical and cognitive functioning among the oldest-old in China: a cohort study. Lancet (London, England), 389(10079), 1619–1629. https://doi.org/10.1016/S0140-6736(17)30548-2CrossRefGoogle ScholarPubMed
Zhang, J., Lyu, Y. B., Yin, Z. X., Luo, J. S., Shi, W. H., and Shi, X. M. (2017). [Follow-up study of body mass index and risk of cognitive impairment among elderly adults aged ≥65 years old from longevity areas of China]. Zhonghua Yu Fang Yi Xue Za Zhi [Chinese Journal of Preventive Medicine], 51(11), 1019–1023. https://doi.org/10.3760/cma.j.issn.0253-9624.2017.11.012Google Scholar
Zhang, Y.et al. (2019). Effect of sociodemographic and physical activity on cognitive function in older adults: a nationwide cross-sectional survey. International Journal of Geriatric Psychiatry, 34(2), 243–248. https://doi.org/10.1002/gps.4932CrossRefGoogle ScholarPubMed
Zheng, W.et al. (2011). Association between body-mass index and risk of death in more than 1 million Asians. The New England Journal of Medicine, 364(8), 719–729. https://doi.org/10.1056/NEJMoa1010679CrossRefGoogle ScholarPubMed
Zhou, M.et al. (2019). Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(19)30427-1CrossRefGoogle Scholar
Supplementary material: File

Tu et al. supplementary material

Tu et al. supplementary material

Download Tu et al. supplementary material(File)
File 581.5 KB