Association of polypharmacy and motoric cognitive risk syndrome in older adults: A 4-year longitudinal study in China

Liang, Haixu; Fang, Ya

doi:10.1016/j.archger.2022.104896

Cited by 6 publications

(10 citation statements)

References 30 publications

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“…It asked: “How would you rate your memory at the present time?” The questions asked respondents to rate their responses on a scale of “excellent”, “very good”, “good”, “fair” and “poor”. Subjective cognitive concerns were identified for those who responded “fair” or “poor” [20, 21]. Approximately 4 m of open area were used for the gait speed test, and a 2.5‐m line was set up as the walking path [20, 21].…”

Section: Methodsmentioning

confidence: 99%

“…The diagnosis of MCR in CHARLS has been described in previous studies [20,21], which included subjective cognitive concerns and slow gait speed without dementia or impaired mobility [1]. The diagnosis of MCR was made based on the appearance of slow gait and subjective cognitive concerns that met the established cut-points [22].…”

Section: Diagnosis Of Mcr Syndromementioning

confidence: 99%

“…Subjective cognitive concerns were identified for those who responded "fair" or "poor" [20,21]. Approximately 4 m of open area were used for the gait speed test, and a 2.5-m line was set up as the walking path [20,21]. The distance (in meters) was divided by the time (in seconds).…”

Section: Diagnosis Of Mcr Syndromementioning

confidence: 99%

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Chronic pain increases the risk of motoric cognitive risk syndrome at 4 years of follow‐up: evidence from the China Health and Retirement Longitudinal Study

Liang

Fang

2023

Euro J of Neurology

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Background and purpose: Slower gait speed and subjective cognitive concerns are characteristics of the motoric cognitive risk (MCR) syndrome. This study aimed to examine if changes in pain may be hallmarks of early MCR, through investigating the magnitude of the association of chronic pain and the risk of MCR at 4 years follow-up. Methods:In total, 3711 participants without dementia or any mobility disability aged ≥60 years were studied, including 1413 with chronic pain, enrolled in the China Health and Retirement Longitudinal Study, a prospective cohort study. MCR assessed at wave 1 (2011) and wave 3 (2015) was used as the exposure. Cox regression analysis was used to examine the longitudinal association between chronic pain and MCR after adjusting for

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Section: Methodsmentioning

confidence: 99%

Section: Diagnosis Of Mcr Syndromementioning

confidence: 99%

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Chronic pain increases the risk of motoric cognitive risk syndrome at 4 years of follow‐up: evidence from the China Health and Retirement Longitudinal Study

Liang

Fang

2023

Euro J of Neurology

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“…Health behavior and clinical risk covariates included smoking, drinking, and healthy aging score (HAS) (low, high levels), following previous study methodology. [3][4][5]32 Further details for each variable are available on the CHARLS Website (http://charls.pku.edu. cn/).…”

Section: Covariatesmentioning

confidence: 99%

“…Motoric cognitive risk syndrome (MCR) is the intermediate state of the trajectory from normal cognition to dementia, which is a pre-dementia syndrome characterized by subjective cognitive complaints and slow gait speed without dementia or reduced mobility. [1][2][3][4][5] The burden of MCR will rise quickly as the global population aging, which estimated the global prevalence of MCR was 2%-27%. 6 The conversion rate of dementia in MCR patients is as high as 12.81, 2 which has also been proven to be closely related to adverse health outcomes such as disability, 7,8 falls, 3,9 and mortality.…”

Section: Introductionmentioning

confidence: 99%

Associations of visual, hearing, and dual sensory impairment with motoric cognitive risk syndrome: Observational and Mendelian randomization analyses

Liang,

Zheng

et al. 2024

Int J Geriat Psychiatry

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BackgroundDementia is associated with individual vision impairment (VI) and hearing impairment (HI). However, little is known about their associations with motoric cognitive risk syndrome (MCR), a pre‐dementia stage. We investigated the association of VI, HI, and dual sensory impairment (DSI) with MCR and to further evaluate causal relationships using Mendelian randomization (MR) approach.MethodsFirst, an observational study was conducted in the China Health and Retirement Longitudinal Study (CHARLS). Evaluate the cross‐sectional and longitudinal associations of VI, HI, and DSI with MCR using the logistic regression models and Cox proportional hazard models, respectively. Second, evaluate the causal association between VI and HI with MCR using MR analysis. The GWAS data was used for genetic instruments, including 88,250 of European ancestry (43,877 cases and 44,373 controls) and 504,307 with “white British” ancestry (100,234 cases and 404,073 controls), respectively; MCR information was obtained from the GWAS with 22,593 individuals. Inverse variance weighted was the primary method and sensitivity analysis was used to evaluate the robustness of MR methods.ResultsIn the observational study, VI (HR: 1.767, 95%CI: 1.331–2.346; p < 0.001), HI (HR: 1.461, 95%CI: 1.196–1.783; p < 0.001), and DSI (HR: 1.507, 95%CI: 1.245–1.823; p < 0.001) were significantly associated with increased risk of MCR. For the MR, no causal relationship between VI (OR: 0.902, 95% CI: 0.593–1.372; p = 0.631) and HI (OR: 1.016, 95% CI: 0.989–1.043; p = 0.248) with MCR risk, which is consistent with the sensitivity analysis.ConclusionVI, HI, and DSI were significantly associated with MCR, but MR analysis failed to provide evidence of their causal relationship. Emphasized the importance of sensory impairment screening in identifying high‐risk populations for dementia.

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Development and validation of a risk prediction model for motoric cognitive risk syndrome in older adults

Li,

Huang,

Wei

et al. 2024

Aging Clin Exp Res

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Objective The objective of this study was to develop a risk prediction model for motoric cognitive risk syndrome (MCR) in older adults. Methods Participants were selected from the 2015 China Health and Retirement Longitudinal Study database and randomly assigned to the training group and the validation group, with proportions of 70% and 30%, respectively. LASSO regression analysis was used to screen the predictors. Then, identified predictors were included in multivariate logistic regression analysis and used to construct model nomogram. The performance of the model was evaluated by area under the receiver operating characteristic (ROC) curve (AUC), calibration curves and decision curve analysis (DCA). Results 528 out of 3962 participants (13.3%) developed MCR. Multivariate logistic regression analysis showed that weakness, chronic pain, limb dysfunction score, visual acuity score and Five-Times-Sit-To-Stand test were predictors of MCR in older adults. Using these factors, a nomogram model was constructed. The AUC values for the training and validation sets of the predictive model were 0.735 (95% CI = 0.708–0.763) and 0.745 (95% CI = 0.705–0.785), respectively. Conclusion The nomogram constructed in this study is a useful tool for assessing the risk of MCR in older adults, which can help clinicians identify individuals at high risk.

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Association of polypharmacy and motoric cognitive risk syndrome in older adults: A 4-year longitudinal study in China

Cited by 6 publications

References 30 publications

Chronic pain increases the risk of motoric cognitive risk syndrome at 4 years of follow‐up: evidence from the China Health and Retirement Longitudinal Study

Chronic pain increases the risk of motoric cognitive risk syndrome at 4 years of follow‐up: evidence from the China Health and Retirement Longitudinal Study

Associations of visual, hearing, and dual sensory impairment with motoric cognitive risk syndrome: Observational and Mendelian randomization analyses

Development and validation of a risk prediction model for motoric cognitive risk syndrome in older adults

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