PDF(Pubmed)
Abstract：
UNASSIGNED: The societal burden of cognitive impairment in China has prompted researchers to develop clinical prediction models aimed at making risk assessments that enable preventative interventions. However, it is unclear what types of risk factors best predict future cognitive impairment, if known risk factors make equally accurate predictions across different socioeconomic groups, and if existing prediction models are equally accurate across different subpopulations.
UNASSIGNED: This paper aimed to identify which domain of health information best predicts future cognitive impairment among Chinese older adults and to examine if discrepancies exist in predictive ability across different population subsets.
UNASSIGNED: Using data from the Chinese Longitudinal Healthy Longevity Survey, we quantified the ability of demographics, instrumental activities of daily living, activities of daily living, cognitive tests, social factors and hobbies, psychological factors, diet, exercise and sleep, chronic diseases, and 3 recently published logistic regression-based prediction models to predict 3-year risk of cognitive impairment in the general Chinese population and among male, female, rural-dwelling, urban-dwelling, educated, and not formally educated older adults. Predictive ability was quantified using the area under the receiver operating characteristic curve (AUC) and sensitivity-specificity curves through 20 repeats of 10-fold cross-validation.
UNASSIGNED: A total of 4047 participants were included in the study, of which 337 (8.3%) developed cognitive impairment 3 years after baseline data collection. The risk factor groups with the best predictive ability in the general population were demographics (AUC 0.78, 95% CI 0.77-0.78), cognitive tests (AUC 0.72, 95% CI 0.72-0.73), and instrumental activities of daily living (AUC 0.71, 95% CI 0.70-0.71). Demographics, cognitive tests, instrumental activities of daily living, and all 3 recreated prediction models had significantly higher AUCs when making predictions among female older adults compared to male older adults and among older adults with no formal education compared to those with some education.
UNASSIGNED: This study suggests that demographics, cognitive tests, and instrumental activities of daily living are the most useful risk factors for predicting future cognitive impairment among Chinese older adults. However, the most predictive risk factors and existing models have lower predictive power among male, urban-dwelling, and educated older adults. More efforts are needed to ensure that equally accurate risk assessments can be conducted across different socioeconomic groups in China.
UNASSIGNED: This paper aimed to identify which domain of health information best predicts future cognitive impairment among Chinese older adults and to examine if discrepancies exist in predictive ability across different population subsets.
UNASSIGNED: Using data from the Chinese Longitudinal Healthy Longevity Survey, we quantified the ability of demographics, instrumental activities of daily living, activities of daily living, cognitive tests, social factors and hobbies, psychological factors, diet, exercise and sleep, chronic diseases, and 3 recently published logistic regression-based prediction models to predict 3-year risk of cognitive impairment in the general Chinese population and among male, female, rural-dwelling, urban-dwelling, educated, and not formally educated older adults. Predictive ability was quantified using the area under the receiver operating characteristic curve (AUC) and sensitivity-specificity curves through 20 repeats of 10-fold cross-validation.
UNASSIGNED: A total of 4047 participants were included in the study, of which 337 (8.3%) developed cognitive impairment 3 years after baseline data collection. The risk factor groups with the best predictive ability in the general population were demographics (AUC 0.78, 95% CI 0.77-0.78), cognitive tests (AUC 0.72, 95% CI 0.72-0.73), and instrumental activities of daily living (AUC 0.71, 95% CI 0.70-0.71). Demographics, cognitive tests, instrumental activities of daily living, and all 3 recreated prediction models had significantly higher AUCs when making predictions among female older adults compared to male older adults and among older adults with no formal education compared to those with some education.
UNASSIGNED: This study suggests that demographics, cognitive tests, and instrumental activities of daily living are the most useful risk factors for predicting future cognitive impairment among Chinese older adults. However, the most predictive risk factors and existing models have lower predictive power among male, urban-dwelling, and educated older adults. More efforts are needed to ensure that equally accurate risk assessments can be conducted across different socioeconomic groups in China.
摘要：
中国认知障碍的社会负担促使研究人员开发临床预测模型，旨在进行风险评估，以实现预防性干预。然而,目前尚不清楚哪种类型的危险因素最能预测未来的认知障碍，如果已知的风险因素在不同的社会经济群体中做出同样准确的预测，以及现有的预测模型在不同的亚群中是否同样准确。
■本文旨在确定哪个健康信息领域最能预测中国老年人未来的认知障碍，并研究不同人群子集的预测能力是否存在差异。
■使用中国纵向健康长寿调查的数据，我们量化了人口统计学的能力，日常生活的工具活动，日常生活活动,认知测试,社会因素和爱好，心理因素,饮食，锻炼和睡眠，慢性疾病,以及最近发表的3种基于逻辑回归的预测模型，用于预测一般中国人群和男性认知功能障碍的3年风险，女性,农村住宅，城市住宅，受过教育，也没有受过正规教育的老年人。通过20次重复的10倍交叉验证,使用接受者工作特征曲线(AUC)和灵敏度-特异性曲线下面积来量化预测能力。
■总共4047名参与者被纳入研究，其中337人(8.3%)在基线数据收集3年后出现认知障碍.一般人群中预测能力最好的危险因素组是人口统计学（AUC0.78，95％CI0.77-0.78），认知测试（AUC0.72，95%CI0.72-0.73），和日常生活的工具性活动(AUC0.71，95%CI0.70-0.71)。人口统计,认知测试,日常生活的工具活动，在女性老年人与男性老年人之间进行预测时,以及在未受过正规教育的老年人与受过一定教育的老年人之间进行预测时,所有3种重新创建的预测模型的AUC均显著较高.
■这项研究表明，人口统计学，认知测试,日常生活和工具性活动是预测中国老年人未来认知障碍的最有用的危险因素。然而,最具预测性的风险因素和现有模型在男性中的预测能力较低，城市住宅，受过教育的老年人。需要做出更多努力，以确保能够在中国不同的社会经济群体中进行同样准确的风险评估。
■本文旨在确定哪个健康信息领域最能预测中国老年人未来的认知障碍，并研究不同人群子集的预测能力是否存在差异。
■使用中国纵向健康长寿调查的数据，我们量化了人口统计学的能力，日常生活的工具活动，日常生活活动,认知测试,社会因素和爱好，心理因素,饮食，锻炼和睡眠，慢性疾病,以及最近发表的3种基于逻辑回归的预测模型，用于预测一般中国人群和男性认知功能障碍的3年风险，女性,农村住宅，城市住宅，受过教育，也没有受过正规教育的老年人。通过20次重复的10倍交叉验证,使用接受者工作特征曲线(AUC)和灵敏度-特异性曲线下面积来量化预测能力。
■总共4047名参与者被纳入研究，其中337人(8.3%)在基线数据收集3年后出现认知障碍.一般人群中预测能力最好的危险因素组是人口统计学（AUC0.78，95％CI0.77-0.78），认知测试（AUC0.72，95%CI0.72-0.73），和日常生活的工具性活动(AUC0.71，95%CI0.70-0.71)。人口统计,认知测试,日常生活的工具活动，在女性老年人与男性老年人之间进行预测时,以及在未受过正规教育的老年人与受过一定教育的老年人之间进行预测时,所有3种重新创建的预测模型的AUC均显著较高.
■这项研究表明，人口统计学，认知测试,日常生活和工具性活动是预测中国老年人未来认知障碍的最有用的危险因素。然而,最具预测性的风险因素和现有模型在男性中的预测能力较低，城市住宅，受过教育的老年人。需要做出更多努力，以确保能够在中国不同的社会经济群体中进行同样准确的风险评估。
