Lin Chun-Hung Richard, Tsai Jui-Hsiu, Wu Shihn-Sheng, Chang Yang-Pei, Wen Yen-Hsia, Liu Jain-Shing, Lung For-Wey
Department of Computer Science and Engineering, National Sun Yat-sen University Program in Environmental and Occupation Medicine, National Health Research Institutes (Taiwan) and Kaohsiung Medical University Calo Psychiatric Center, Pingtung School of Pharmacy, College of Pharmacy Department of Neurology, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University, Kaohsiung Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan.
Medicine (Baltimore). 2018 Apr;97(15):e0298. doi: 10.1097/MD.0000000000010298.
Dementia is one of the most burdensome illnesses in elderly populations worldwide. However, the literature about multiple risk factors for dementia is scant.To develop a simple, rapid, and appropriate predictive tool for the clinical quantitative assessment of multiple risk factors for dementia.A population-based cohort study.Based on the Taiwan National Health Insurance Research Database, participants first diagnosed with dementia from 2000 to 2009 and aged ≥65 years in 2000 were included.A logistic regression model with Bayesian supervised learning inference was implemented to evaluate the quantitative effects of 1- to 6-comorbidity risk factors for dementia in the elderly Taiwanese population: depression, vascular disease, severe head injury, hearing loss, diabetes mellitus (DM), and senile cataract, identified from a nationwide longitudinal population-based database.This study enrolled 4749 (9.5%) patients first diagnosed as having dementia. Aged, female, urban residence, and low income were found as independent sociodemographic risk factors for dementia. Among all odds ratios (ORs) of 2-comorbidity risk factors for dementia, comorbid depression and vascular disease had the highest adjusted OR of 6.726. The 5-comorbidity risk factors, namely depression, vascular disease, severe head injury, hearing loss, and DM, exhibited the highest OR of 8.767. Overall, the quantitative effects of 2 to 6 comorbidities and age difference on dementia gradually increased; hence, their ORs were less than additive. These results indicate that depression is a key comorbidity risk factor for dementia.The present findings suggest that physicians should pay more attention to the role of depression in dementia development. Depression is a key cormorbidity risk factor for dementia. It is the urgency of evaluating the nature of the link between depression and dementia; and further testing what extent controlling depression could effectively lead to the prevention of dementia.
痴呆症是全球老年人群中最具负担的疾病之一。然而,关于痴呆症多种风险因素的文献却很少。旨在开发一种简单、快速且合适的预测工具,用于临床定量评估痴呆症的多种风险因素。一项基于人群的队列研究。基于台湾国民健康保险研究数据库,纳入2000年首次被诊断为痴呆症且在2000年年龄≥65岁的参与者。采用具有贝叶斯监督学习推理的逻辑回归模型,评估从全国纵向人群数据库中确定的台湾老年人群中1至6种合并症风险因素对痴呆症的定量影响:抑郁症、血管疾病、重度头部损伤、听力损失、糖尿病(DM)和老年性白内障。本研究纳入了4749名(9.5%)首次被诊断患有痴呆症的患者。年龄、女性、城市居住和低收入被发现是痴呆症独立的社会人口学风险因素。在所有痴呆症2种合并症风险因素的优势比(OR)中,合并抑郁症和血管疾病的调整后OR最高,为6.726。5种合并症风险因素,即抑郁症、血管疾病、重度头部损伤、听力损失和DM,表现出最高的OR为8.767。总体而言,2至6种合并症和年龄差异对痴呆症的定量影响逐渐增加;因此,它们的OR小于相加效应。这些结果表明抑郁症是痴呆症的关键合并症风险因素。目前的研究结果表明,医生应更加关注抑郁症在痴呆症发展中的作用。抑郁症是痴呆症的关键合并症风险因素。评估抑郁症与痴呆症之间联系的性质以及进一步测试控制抑郁症在多大程度上能有效预防痴呆症是当务之急。