P1‐395: Progression and Predictors of Mild Cognitive Impairment in Chinese Elderly: A Prospective Follow‐Up in The Shanghai Aging Study

Ding, Ding; Zhao, Qianhua; Guo, Qiahao; Hong, Zhen

doi:10.1016/j.jalz.2016.06.1147

Cited by 11 publications

(13 citation statements)

References 15 publications

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“…For example, a recent epidemiological study showed that the prevalence of mild cognitive impairment (MCI) in China was 20.1% among older adults aged 60 or above [2]. In addition, it is estimated that around 6% of the older adults with MCI progress to dementia annually [3]. Such increase in cognitive impairment in aging populations have major societal and human implications [4].…”

Section: Introductionmentioning

confidence: 99%

The impact of residential status on cognitive decline among older adults in China: Results from a longitudinal study

Dupre

et al. 2017

BMC Geriatr

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BackgroundResidential status has been linked to numerous determinants of health and well-being. However, the influence of residential status on cognitive decline remains unclear. The purpose of this research was to assess the changes of cognitive function among older adults with different residential status (urban residents, rural-to-urban residents, rural residents, and urban-to-rural residents), over a 12-year period.MethodsWe used five waves of data (2002, 2005, 2008/2009, 2011/2012, and 2014) from the Chinese Longitudinal Healthy Longevity Survey with 17,333 older adults age 65 and over who were interviewed up to five times. Cognitive function was measured by the Mini Mental State Examination (MMSE). Multilevel models were used regarding the effects of residential status after adjusting for demographic characteristics, socioeconomic factors, family support, health behaviors, and health status.ResultsAfter controlling for covariates, significant differences in cognitive function were found across the four groups: rural-to-urban and rural residents had a higher level of cognition than urban residents at baseline. On average, cognitive function decreased over the course of the study period. Rural-to-urban and rural residents demonstrated a faster decline in cognitive function than urban residents.ConclusionsThis study suggests that residential status has an impact on the rate of changes in cognition among older adults in China. Results from this study provide directions for future research that addresses health disparities, particularly in countries that are undergoing significant socioeconomic transitions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12877-017-0501-9) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

The impact of residential status on cognitive decline among older adults in China: Results from a longitudinal study

Dupre

et al. 2017

BMC Geriatr

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“…Recently, the communitybased Shanghai aging Study investigated the progression of cognitive decline in Chinese elderly 31 . they found that the conversion rate to dementia was 6.0 per 100 personyears, while the reversion rate to cognitive normality was 7.8 per 100 person-years.…”

Section: Discussionmentioning

confidence: 99%

“…In that study, age was considered the main risk factor for developing dementia. evidence from autopsy, epidemiological, and cohort studies show that advanced age is the strongest risk factor for the development of alzheimer's disease related to pathophysiological abnormalities and the ultimate development of symptomatic alzheimer's disease 31 . even so, there is a significant heterogeneity between individuals in the age-specific prevalence of alzheimer's-related pathology: some individuals appear relatively spared from developing the pathognomonic alzheimer's brain lesions even in old age 32 .…”

Section: Discussionmentioning

confidence: 99%

Clinical and Demographic Predictors of Conversion to Dementia in Mexican Elderly with Mild Cognitive Impairment

Aguilar-Navarro

Mimenza-Alvarado

Ávila-Fuñes

et al. 2017

RIC

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“…10 The CR construct has been formalized by considering two latent variables: level of education (including proxies such as years of formal schooling, occupational attainment, reading habits, and vocabulary knowledge) and lifestyle (including participation in social and cultural activities). 13 Diagnostic transitions in MCI and eventual conversion to dementia have been studied by survival analysis, 14 polynomial regression analysis, 15 multinomial logistic regression (LR) analysis, 16 and Markov models. 13 Diagnostic transitions in MCI and eventual conversion to dementia have been studied by survival analysis, 14 polynomial regression analysis, 15 multinomial logistic regression (LR) analysis, 16 and Markov models.…”

Section: Introductionmentioning

confidence: 99%

Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia

Facal

Valladares-Rodríguez

Lojo‐Seoane

et al. 2019

Int J Geriat Psychiatry

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Objectives The overall aim of the present study was to explore the role of cognitive reserve (CR) in the conversion from mild cognitive impairment (MCI) to dementia. We used traditional and machine learning (ML) techniques to compare converter and nonconverter participants. We also discuss the predictive value of CR proxies in relation to the ML model performance. Methods In total, 169 participants completed the longitudinal study. Participants were divided into a control group and three MCI subgroups, according to the Petersen criteria for diagnosis. Information about the participants was compared using nine ML classification techniques. Seven relevant performance metrics were computed in order to evaluate the accuracy of prediction regarding converter and nonconverter participants. Results ML algorithms applied to socio‐demographic, basic health, and CR proxy data enabled prediction of conversion to dementia. The best performing models were the gradient boosting classifier (accuracy (ACC) = 0.93; F1 = 0.86, and Cohen κ = 0.82) and random forest classifier (ACC = 0.92; F1 = 0.79, and Cohen κ = 0.71). Use of ML techniques corroborated the protective role of CR as a mediator of conversion to dementia, whereby participants with more years of education and higher vocabulary scores survived longer without developing dementia. Conclusions We used ML approaches to explore the role of CR in conversion from MCI to dementia. The findings indicate the potential value of ML algorithms for detecting risk of conversion to dementia in cognitive aging and CR studies. Further research is required to develop an ML‐based procedure that can be used to make robust predictions.

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P1‐395: Progression and Predictors of Mild Cognitive Impairment in Chinese Elderly: A Prospective Follow‐Up in The Shanghai Aging Study

Cited by 11 publications

References 15 publications

The impact of residential status on cognitive decline among older adults in China: Results from a longitudinal study

The impact of residential status on cognitive decline among older adults in China: Results from a longitudinal study

Clinical and Demographic Predictors of Conversion to Dementia in Mexican Elderly with Mild Cognitive Impairment

Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia

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