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

Rothman-Keller model for risk prediction of motoric cognitive risk syndrome in older Chinese adults: A proof-of-concept study

OBJECTIVE

The risk factors for motoric cognitive risk syndrome (MCR) remains unclear, and a lack of predictive studies on the risk of developing MCR. This proof-of-concept study aims to investigate the risk factors of MCR, and develop and internally validate a prediction system to assess the risk of MCR in older Chinese adults.

METHODS

Through performing a meta-analysis to obtain the risk factors and pooled risk ratio of MCR, the Rothman-Keller model which could be used to predict risk level of MCR was constructed. A total of 5020 participants from the CHARLS were used to validate discrimination and calibration of model. Predictive performance was assessed using AUC-ROC, accuracy, sensitivity, and specificity.

RESULTS

The pooled prevalence of MCR was 12.0 %. The results of the meta-analysis showed that there are eleven significant risk factors of MCR, including age, sex, marital status, diabetes, stroke, depression, falls, physical inactivity, social isolation, fear responses, and hospitalization, with RRi of 3.00, 1.29, 1.21, 1.53, 2.90, 2.13, 2.95, 1.46, 0.79, 1.55, and 1.31, respectively. Rothman-Keller model performed well to predict MCR risk with an AUC-ROC of 0.631 (95 %CI: 0.610-0.653), and the score was well calibrated (chi-square test for goodness-of-fit = 5.981, P = 0.649).

CONCLUSIONS

MCR is highly prevalent in China, caused by the complex interaction of genetics, comorbidities, and lifestyle factors. This study serves as proof-of-concept that Rothman-Keller model performs a good calibration and fair discrimination, which can be used as a simple, time-saving, and cost-effective mean to assess and monitor the risk level of MCR.

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

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.

Prevalence and risk factors associated with circadian syndrome in community-dwelling middle-aged to older adults: Based on health ecology model

OBJECTIVES

To explore the prevalence and risk factors associated with circadian syndrome (CricS) in community-dwelling middle-aged to older adults.

METHOD

We performed a cross-sectional analysis of 13,516 participants from the China Health and Retirement Longitudinal Study (CHARLS). We used logistic regression to compute the odds ratios (OR) and 95 % confidence intervals (Cls), using covariates derived through the health ecology model.

RESULTS

The overall prevalence of CricS was 31.5 % (25.0 % males and 37.1 % females). With controlling all covariates, social isolation (OR 1.164, 95%CI 1.033-1.310), irritable mood (OR 1.689, 95%CI 1.488-1.917), fear responses (OR 1.546, 95%CI 1.262-1.894), chronic disease (OR 1.577, 95%CI 1.392-1.788), and financial debt (OR 0.806, 95%CI 0.657-0.990) were significantly correlated with increased CricS risk in males, whereas CricS syndrome was significantly associated with age (OR 1.285, 95%CI 1.214-1.361), married (OR 1.258, 95%CI 1.089-1.452), current drinkers (OR 0.835, 95%CI 0.716-0.974), social isolation (OR 1.175, 95%CI 1.065-1.296), irritable mood (OR 1.346, 95%CI 1.210-1.497), fear responses (OR 1.202, 95%CI 1.047-1.378), chronic disease (OR 1.363, 95%CI 1.225-1.517), chronic pain (OR 1.177, 95%CI 1.058-1.309), and universal basic income (OR 0.742, 95%CI 0.611-0.900) in females.

CONCLUSION

CricS is common in middle-aged to older adults, and health behavior factors have an important impact on CricS. The potential predictors identified for CricS should be further studied to prevent the occurrence of adverse health events in the presenium stage.

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

BACKGROUND

Dementia 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.

METHODS

First, 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.

RESULTS

In 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.

CONCLUSION

VI, 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.

Association between changes in potentially inappropriate medication use and adverse outcomes during hospitalization in older adults: A retrospective study

PURPOSE

To evaluate the association between the change in the number of PIMs in older adults during hospitalization and adverse outcomes.

METHODS

This retrospective cohort study was conducted in the internal medicine wards of a tertiary teaching hospital between May and December 2017. 3,460 patients (77.5±8.4 years, 60.4% male) were enrolled, and 206 patients died during hospitalization. PIMs were defined using the Beers Criteria as suggested by the American Geriatrics Society. Adverse outcomes studied were functional decline (a loss in 1 or more activities of daily living from admission to discharge), prolonged length of stay (LOS) (≥14 days), and mortality.

RESULTS

2258 patients (65.3%) had increasing PIMs during hospitalization. They tended to be younger (77.0±8.3 versus 78.5±8.5 years, p<0.001) and had lower numbers of PIMs at admission (0.4±0.8 versus 0.8±1.1, p<0.001). Increasing PIM use was strongly associated with greater functional decline (aOR 1.36, 95%CI 1.01-1.67, p=0.005), prolonged LOS (aOR 3.47, 95%CI 2.71-4.44, p<0.001) and higher mortality rate (aOR 2.68, 95%CI 1.75-4.12, p<0.001), even after adjusting for all covariates. We observed a strong association between adverse outcomes and increasing PIMs in older adults during hospitalization (p for trend <0.001).

CONCLUSIONS

Older adults with increasing PIMs during hospitalization were at greater risk for functional decline, prolonged LOS, and mortality, especially in those with three or more PIMs. Further studies are needed to better understand the complex interactions and to evaluate the effectiveness of intervention programs to lower PIM number and improve discharge outcomes for patients who had increasing PIM use during hospitalization.

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

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 individual factors, behaviors/physiology factors and societal factors. Four years later, the incident MCR was evaluated.

RESULTS

After adjusting for individual factors, chronic pain was found to increase the risk of MCR development over time by about 1.5 times (hazard ratio 1.562, 95% confidence interval 1.228-1.986; p < 0.001) and to be linked with incident MCR at baseline (odds ratio 1.397, 95% confidence interval 1.149-1.698; p < 0.001). These associations remained substantial when behaviors/physiology factors and societal factors were taken into account in the analytical models.

CONCLUSIONS

The findings of our study imply that incident MCR may be exacerbated by chronic pain. Further exploration is required to find out whether chronic pain is a modifiable risk factor for MCR.