Journal of epidemiology and community health · 2023
Risk assessment and stratification of mild cognitive impairment among the Chinese elderly: attention to modifiable risk factors.
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Wang Qiong, Zhou Shuai, Zhang Jingya, Wang Qing, Hou Fangfang, Han Xiao, Shen Guodong, Zhang Yan
Аннотация
BACKGROUND: The early identification of individuals at risk of mild cognitive impairment (MCI) has major public health implications for Alzheimer's disease prevention.
OBJECTIVE: This study aims to develop and validate a risk assessment tool for MCI with a focus on modifiable factors and a suggested risk stratification strategy.
METHODS: Modifiable risk factors were selected from recent reviews, and risk scores were obtained from the literature or calculated based on the Rothman-Keller model. Simulated data of 10 000 subjects with the exposure rates of the selected factors were generated, and the risk stratifications were determined by the theoretical incidences of MCI. The performance of the tool was verified using cross-sectional and longitudinal datasets from a population-based Chinese elderly cohort.
RESULTS: Nine modifiable risk factors (social isolation, less education, hypertension, hyperlipidaemia, diabetes, smoking, drinking, physical inactivity and depression) were selected for the predictive model. The area under the curve (AUC) was 0.71 in the training set and 0.72 in the validation set for the cross-sectional dataset. The AUCs were 0.70 and 0.64 in the training and validation sets, respectively, for the longitudinal dataset. A combined risk score of 0.95 and 1.86 was used as the threshold to categorise MCI risk as 'low', 'moderate' and 'high'.
CONCLUSION: A risk assessment tool for MCI with appropriate accuracy was developed in this study, and risk stratification thresholds were also suggested. The tool might have significant public health implications for the primary prevention of MCI in elderly individuals in China.
OBJECTIVE: This study aims to develop and validate a risk assessment tool for MCI with a focus on modifiable factors and a suggested risk stratification strategy.
METHODS: Modifiable risk factors were selected from recent reviews, and risk scores were obtained from the literature or calculated based on the Rothman-Keller model. Simulated data of 10 000 subjects with the exposure rates of the selected factors were generated, and the risk stratifications were determined by the theoretical incidences of MCI. The performance of the tool was verified using cross-sectional and longitudinal datasets from a population-based Chinese elderly cohort.
RESULTS: Nine modifiable risk factors (social isolation, less education, hypertension, hyperlipidaemia, diabetes, smoking, drinking, physical inactivity and depression) were selected for the predictive model. The area under the curve (AUC) was 0.71 in the training set and 0.72 in the validation set for the cross-sectional dataset. The AUCs were 0.70 and 0.64 in the training and validation sets, respectively, for the longitudinal dataset. A combined risk score of 0.95 and 1.86 was used as the threshold to categorise MCI risk as 'low', 'moderate' and 'high'.
CONCLUSION: A risk assessment tool for MCI with appropriate accuracy was developed in this study, and risk stratification thresholds were also suggested. The tool might have significant public health implications for the primary prevention of MCI in elderly individuals in China.