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NEUROLOGY 2009;73:186-194
© 2009 American Academy of Neurology

Lifespan influences on mid- to late-life cognitive function in a Chinese birth cohort

Z. X. Zhang, MD, B. L. Plassman, PhD, Q. Xu, PhD, G.E.P. Zahner, PhD, B. Wu, PhD, M. Y. Gai, MD, H. B. Wen, MD, X. Chen, MD, S. Gao, MD, D. Hu, PhD, X. H. Xiao, MD, Y. Shen, MB, A. M. Liu, MD and T. Xu, PhD

From the Department of Neurology (Z.X.Z., H.B.W., X.C., S.G.), Clinical Epidemiology Unit (Z.X.Z.), Obstetrics (M.Y.G.), Diabetes (X.H.X.), Center of Laboratory (Y.S.), and Case Registry Office (A.M.L.), Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China; Department of Psychiatry and Behavioral Sciences at Duke University Medical Center (B.L.P.), Durham, NC; Postgraduate Institute (G.E.P.Z.), Department of Statistics (Q.X.), and National Laboratory of Medical Molecular Biology (T.X.), School of Basic Medicine, Peking Union Medical College, Institute of Basic Medical Science, Chinese Academy of Medical Sciences, Beijing, China; Gerontology Program (B.W.), University of North Carolina at Greensboro; and College of Information Science and Technology (D.H.), Beijing Normal University, Beijing, China.

Address correspondence and reprint requests to Prof. Zhen-Xin Zhang, Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, 1 Shuaifuyuan, Wanfujing, Beijing 100730, China wuzhangzhenxin{at}medmail.com.cn

Objective: To explore factors throughout the lifespan that influence cognition in midlife to late life.

Methods: We conducted a retrospective birth cohort study of 2,062 individuals born during 1921-1954 in Beijing, China. In 2003-2005, birth records were abstracted, and participants then 50-82 years old received standardized examinations for health, cognition, and socio-environmental measures. Using cumulative logit models, we assessed adjusted relative effects of prenatal, early life, and adult factors on mid- to late-life cognition.

Results: Most prenatal factors were associated with mid- to late-life cognition in the unadjusted models. However, when childhood and adult factors were sequentially added to the models, the impact of prenatal factors showed successive attenuation in effect size, and became insignificant. In contrast, early life factors remained significantly associated with mid- to late-life cognition even after full life-course adjustments. Specifically, those whose fathers had laborer vs professional occupations (odds ratio [OR]Laborer 1.74; 95% confidence interval [CI]: 1.25-2.42) had poorer cognitive outcomes, while individuals who drank milk daily in childhood (OR 0.65; 95% CI: 0.54-0.80), had more years of education (OR10-12 years 0.60; 95% CI: 0.45-0.81; OR13+ yrs 0.29; 95% CI: 0.23-0.38), and were taller adults (ORheight ≥ SD 0.65; 95% CI: 0.49-0.86) had better cognition. The high prenatal risk infants had similar patterns with a trend toward a stronger association between cognition and socioenvironmental factors.

Conclusion: Mid- to late-life cognition is influenced by factors over the entire lifespan with the greatest impact coming from early life exposures. Nutrition, education, social, and family environment in early life may have a long-term impact on cognition in developing countries.

Abbreviations: CI = confidence interval; HDL = high-density lipoprotein; LDL = low-density lipoprotein; OR = odds ratio; PUMCH = Peking Union Medical College Hospital; WAIS-R = Wechsler Adult Intelligence Scale-Revised; WISC-R = Wechsler Intelligence Scale for Children-Revised.

Supported by NIH, National Institute on Aging Project 5P01AG17937-03; also funded in part by Chinese National Science and Technology Project 96-096-05-01 and Chinese Medical Board of New York, Inc., New York Grant 99-699.

Disclosure: Author disclosures and a disclaimer are provided at the end of the article.

Received December 16, 2008. Accepted in final form April 13, 2009.






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