TY - JOUR
T1 - Lifespan influences on mid- To late-life cognitive function in a Chinese birth cohort
AU - Zhang, Z. X.
AU - Plassman, B. L.
AU - Xu, Q.
AU - Zahner, G. E.P.
AU - Wu, B.
AU - Gai, M. Y.
AU - Wen, H. B.
AU - Chen, X.
AU - Gao, S.
AU - Hu, D.
AU - Xiao, X. H.
AU - Shen, Y.
AU - Liu, A. M.
AU - Xu, T.
N1 - Funding Information:
Dr. Zhang reports no disclosures. Dr. Plassman receives research support from the NIH [U01 AG09740 (Site PI), R01 AG027010 (Co-investigator), R21 DE-016970 (Co-investigator), and R21 DE019518-01(Co-investigator)], the Veterans Administration, and the Alzheimer's Association [IIRG 0891522 (PI)], and her spouse has received royalty payments from Abbott Laboratories for pulmonary/respiratory instruments. Dr. Xu reports no disclosures. Dr. Zahner has received honoraria from Pfizer China for 2 lectures on writing research grants applications. Dr. Wu serves on the Editorial Boards of Ageing International and the Journal of Applied Gerontology ; receives research support from National Institutes of Health (NIH)/National Institute for Dental and Craniofacial Research [1 R21 DE019518-01 (PI) and 5R21DE016970 (PI)], NIH/Fogarty International Center, Chinese Dementia Care Research Center [Infrastructure, Training And Pilot Studies (Co-investigator)], and Centers for Disease Control and Prevention [Prevention Research to Promote and Protect Brain Health (Consultant)]. Dr. Gai reports no disclosures. Dr. Wen reports no disclosures. Dr. Chen reports no disclosures. Dr. Gao reports no disclosures. Dr. Hu reports no disclosures. Dr. Xiao reports no disclosures. Dr. Shen reports no disclosures. Dr. Liu reports no disclosures. Dr. Xu reports no disclosures.
PY - 2009/7/21
Y1 - 2009/7/21
N2 - 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 socioenvironmental 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 [Cl]: 1.25-2.42) had poorer cognitive outcomes, while individuals who drank milk daily in childhood (OR 0.65; 95% Cl: 0.54-0.80), had more years of education (OR10.12 years 0.60; 95% Cl: 0.45-0.81; OR13-yrs 0.29; 95% Cl: 0.23-0.38), and were taller adults (ORheight ≥ SD 0.65; 95% Cl: 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.
AB - 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 socioenvironmental 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 [Cl]: 1.25-2.42) had poorer cognitive outcomes, while individuals who drank milk daily in childhood (OR 0.65; 95% Cl: 0.54-0.80), had more years of education (OR10.12 years 0.60; 95% Cl: 0.45-0.81; OR13-yrs 0.29; 95% Cl: 0.23-0.38), and were taller adults (ORheight ≥ SD 0.65; 95% Cl: 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=68949175288&partnerID=8YFLogxK
U2 - 10.1212/WNL.0b013e3181ae7c90
DO - 10.1212/WNL.0b013e3181ae7c90
M3 - Article
C2 - 19620606
AN - SCOPUS:68949175288
SN - 0028-3878
VL - 73
SP - 186
EP - 194
JO - Neurology
JF - Neurology
IS - 3
ER -