轻度认知障碍老年人不同潜在类别的增长混合模型研究

Study on growth mixture model of different latent classes of elderly with mild cognitive impairment

目的探讨增长混合模型在识别轻度认知障碍的老年人群中存在的潜在类别及识别不同类别的群体认知功能的发展轨迹的应用。方法利用65岁以上轻度认知障碍老年人的随访数据构建增长混合模型(growth mixed model,GMM)。利用贝叶斯信息标准(Bayesian information criterion,BIC)进行潜在类别的确定并用后验概率进行模型评价。结果轻度认知障碍的老年人呈现出了3种不同的认知轨迹:类别1的人群初始认知功能低且短时间内快速下降中间又有反弹,最后下降至一定程度后趋于平缓,称之为"痴呆高危人群",占全部人群的4.46%。类别2的人群具有较低的认知功能且随着年龄增长认知能力急剧下降,这部分人群称之为"痴呆低危人群",占全部人群的33.28%。类别3的人群具有较高的认知功能,随着年龄增长认知功能缓慢下降,称之为"正常老化人群",占全部人群的62.26%。结论研究揭示了轻度认知障碍的老年人群中认知发展轨迹的异质性,有助于健康促进人员针对高危人群及早制订干预措施从而减少老年痴呆的发生。

Objective To explore the application of the growth mixed model of identifying the latent classes of the elderly people with mild cognitive impairment and identifying the cognitive trajectory of different classes. Methods The growth mixed model （GMM） was constructed by using the follow-up daia of the elderly with mild cognitive impairment over the age of 65. Bayesian information criterion（BIC） and the posterior probability were used to determine the number of la- tent classes and to conduct model evaluation, respectively. Results The elderly with mild cognitive impairment presented three different cognitive trajectories. The initial eognitive function of class 1 was low and decreased rapidly in the short time, and then rebounded in the middle, finally descended to a certain degree and tended to be slow, which was called the ＂high risk population of dementia＂ , accounted for 4. 46% of the total population. Class 2 bad a lower cognitive function and a sharp decline in cognitive ability with age, which was called ＂low risk population of dementia＂, accounted for 33.28% of the population. Class 3 had higher cognitive function, and the cognitive function decreased slowly with age, which was called ＂normal aging population＂, accounted for 62. 26% of the total population. Conclusions The study reveals the het- erogeneity of the cognitive development trajectory in the elderly population with mild cognitive impairment, which helps health promotion personnel develop interventions for high-risk groups early to reduce the incidence of Alzheimer＇ s disease.