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    標題: Risk of Alzheimer's disease with metal concentrations in whole blood and urine: A case-control study using propensity score matching
    作者: Yang, Yu-Wan
    Liou, Saou-Hsing
    Hsueh, Yu-Mei
    Lyu, Wun-Sin
    Liu, Chiu-Shong
    Liu, Huei-Ju
    Chung, Mu-Chi
    Hung, Peir-Haur
    Chung, Chi-Jung
    貢獻者: China Med Univ & Hosp, Dept Neurol
    China Med Univ & Hosp, Coll Med, Sch Med
    Natl Hlth Res Inst, Div Environm Hlth & Occupat Med
    Taipei Med Univ, Shuang Ho Hosp, Dept Family Med
    China Med Univ, Dept Hlth Risk Management, Coll Publ Hlth
    China Med Univ Hosp, Dept Family Med
    Taichung Vet Gen Hosp, Dept Med, Div Nephrol
    Ditmanson Med Fdn Chiayi Christian Hosp, Dept Internal Med
    Chia Nan Univ Pharm & Sci, Dept Appl Life Sci & Hlth
    China Med Univ Hosp, Dept Med Res
    關鍵字: Arsenic methylation capacity
    Alzheimer's diseases
    Heavy metals
    Propensity score matching
    日期: 2018-10-01
    上傳時間: 2019-11-15 15:42:56 (UTC+8)
    出版者: ACADEMIC PRESS INC ELSEVIER SCIENCE
    摘要: Environmental exposure to heavy metals is suspected to result in neuropathology damage and cognitive impairment. We aimed to explore the association of Alzheimer's disease (AD) risk with the internal dose of heavy metals by constructing a hospital-based case-control study and using propensity-score-matching methods. We investigated 170 patients with AD and 264 controls from the Department of Neurology and Family Medicine, China Medical University Hospital in Taiwan. All patients with AD received clinical neuropsychological examination and cognitive-function assessments, including the mini-mental status examination and clinical dementia rating scale. We also constructed a propensity-score-matched population of 82 patients with AD and 82 controls by matching age, gender, education, and AD-related comorbidity. Blood levels with cadmium, lead, mercury, selenium, and urinary arsenic profile were measured. Logistic regression models and 95% confidence intervals (CIs) were applied to estimate AD risk. After stratification by respective quartile cutoffs of heavy metals, the AD risk of study participants with high urinary inorganic arsenic (InAs%) or low dimethylarsinic acid (DMA%) significantly increased (p < 0.05), as similarly found in the propensity-score-matched population. In addition, people with a low median level of selenium and high median level of InAs%, or/and a low median level of DMA% had approximately two- to threefold significant AD risk. Urinary arsenic profiles may be associated with increased AD risk. Repeat measurements of heavy metals with large sample size and the surveying of potential exposure sources are recommended in future studies.
    link: http://dx.doi.org/10.1016/j.taap.2018.07.015
    關聯: Regulatory Toxicology and Pharmacology, v.356, pp.8-14
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