Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study

Establishment of a mild cognitive impairment risk model in middle-aged and older adults: a longitudinal study

BACKGROUND

Early identification individuals at high risk of mild cognitive impairment (MCI) is essential for prevention and intervention strategies of dementia, such as Alzheimer's disease. MCI prediction considering the interdependence of predictors in longitudinal data needs to be further explored. We aimed to employ machine learning (ML) to develop and verify a prediction model of MCI.

METHODS

In a longitudinal population-based cohort of China Health and Retirement Longitudinal Study (CHARLS), 8390 non-MCI participants were enrolled. The diagnosis of MCI was based on the aging-associated cognitive decline (AACD), and 13 factors (gender, education, marital status, residence, diabetes, hypertension, depression, hearing impairment, social isolation, physical activity, drinking status, body mass index and expenditure) were finally selected as predictors. We implemented a long short-term memory (LSTM) to predict the MCI risks in middle-aged and older adults within 7 years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model.

RESULTS

Through 7 years of follow-up, 1925 participants developed MCI. The model for all incident MCI achieved an AUC of 0.774, and its deployment to the participants followed 2, 4, and 7 years achieved results of 0.739, 0.747, and 0.750, respectively. The model was well-calibrated with predicted probabilities plotted against the observed proportions of cognitive impairment. Education level, gender, marital status, and depression contributed most to the prediction of MCI.

CONCLUSIONS

This model could be widely applied to medical institutions, even in the community, to identify middle-aged and older adults at high risk of MCI.

Pacing Strategies in Elite Individual-Medley Swimmers: A Decision-Tree Approach

PURPOSE

This study aimed to examine pacing strategies and identify the stroke that has the most significant impact on overall performance in men's and women's 200-m and 400-m individual-medley events from 2000 to 2021.

METHODS

The time in each lap and overall race was retrieved from the World Aquatics website. The standardized time for each stroke in individual medley was calculated by dividing the actual time by a reference time specific to each stroke. The reference time was derived from the respective laps in single-stroke finals in the 2017 World Swimming Championships. The decision-tree method was used for analysis. The dependent variables were qualified or nonqualified in heats and semifinals, and winning medals in finals. The independent variables were the ratio of standardized time in each stroke to the sum of standardized time in all 4 strokes.

RESULTS

Swimmers who spent a higher ratio of standardized time in the butterfly stroke (>0.236-0.245) are associated with a higher likelihood of winning medals or qualifying for the next stage in most men's and women's 200-m and 400-m individual medley. Butterfly exhibited the highest normalized importance that distinguished medalists from nonmedalists in the finals. The front-crawl stroke is the second most important determinant in medalists in men's and women's 200-m individual medley, whereas backstroke and breaststroke were the second most important in men's and women's 400-m individual medley, respectively.

CONCLUSION

Individual-medley swimmers who were excellent in butterfly and conserved energy in butterfly had a higher likelihood of success.

A nomogram for individualized prediction of mild cognitive impairment in patients with subjective cognitive decline during physical examinations: a cross-sectional study

Background and objectives

To develop a nomogram for mild cognitive impairment (MCI) in patients with subjective cognitive decline (SCD) undergoing physical examinations in China.

Methods

We enrolled 370 patients undergoing physical examinations at the Medical Center of the First Hospital of Jilin University, Jilin Province, China, from October 2022 to March 2023. Of the participants, 256 were placed in the SCD group, and 74 were placed in the MCI group. The population was randomly divided into a training set and a validation set at a 7:3 ratio. A least absolute shrinkage and selection operator (LASSO) regression model was applied to optimize feature selection for the model. Multivariable logistic regression analysis was applied to construct a predictive model. The performance and clinical utility of the nomogram were determined using Harrell's concordance index, calibration curves, and decision curve analysis (DCA).

Results

Cognitive reserve (CR), age, and a family history of hypertension were associated with the occurrence of MCI. The predictive nomogram showed satisfactory performance, with a concordance index of 0.755 (95% CI: 0.681-0.830) in internal verification. The Hosmer-Lemeshow test results suggested that the model exhibited good fit (p = 0.824). In addition, DCA demonstrated that the predictive nomogram had a good clinical net benefit.

Discussion

We developed a simple nomogram that could help secondary preventive health care workers to identify elderly individuals with SCD at high risk of MCI during physical examinations to enable early intervention.

Characterizing the post-traumatic growth trajectory in gastric cancer survivors: a population-based longitudinal study

OBJECTIVES

Post-traumatic growth can improve the quality of life of cancer survivors. The objective of this study was to investigate post-traumatic growth heterogeneity trajectory in perioperative gastric cancer survivors, and to identify characteristics that predict membership for each trajectory.

METHODS

Gastric cancer survivors (n = 403) were recruited before surgery, their baseline assessment (including post-traumatic growth and related characteristics) was completed, and post-traumatic growth levels were followed up on the day they left the intensive care unit, at discharge, and 1 month after discharge. Latent growth mixture mode was used to identify the heterogeneous trajectory of post-traumatic growth, and the core predictors of trajectory subtypes were explored using a decision tree model.

RESULTS

Three post-traumatic growth development trajectories were identified among gastric cancer survivors: stable high of PTG group (20.6%), fluctuation of PTG group (44.4%), persistent low of PTG group (35.0%). The decision tree model showed anxiety, coping style, and psychological resilience-which was the primary predictor-might be used to predict the PTG trajectory subtypes of gastric cancer survivors.

CONCLUSIONS

There was considerable variability in the experience of post-traumatic growth among gastric cancer survivors. Recognition of high-risk gastric cancer survivors who fall into the fluctuation or persistent low of PTG group and provision of psychological resilience-centered support might allow medical professionals to improve patients' post-traumatic growth and mitigate the impact of negative outcomes.

Digital exclusion and cognitive impairment in older people: findings from five longitudinal studies

OBJECTIVES

Older people are more likely to have digital exclusion, which is associated with poor health. This study investigated the relationship between digital exclusion and cognitive impairment in older adults from 23 countries across five longitudinal surveys.

DESIGN AND MEASUREMENTS

Digital exclusion is defined as self-reported non-use of the Internet. We assessed cognitive impairment on three dimensions: orientation, memory, and executive function. We used generalized estimation equations fitting binary logistic regression with exchangeable correlations to study the relationship between digital exclusion and cognitive impairment, and apply the minimum sufficiently adjusted set of causally directed acyclic graphs as the adjusted variable.

SETTING AND PARTICIPANTS

We pooled a nationally representative sample of older adults from five longitudinal studies, including the China Health and Retirement Longitudinal study (CHARLS), the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Study (HRS), the Mexican Health and Ageing Study (MHAS) and the Survey of Health, Ageing and Retirement in European (SHARE).

RESULTS

We included 62,413 participants from five longitudinal studies. Digital exclusion varied by country, ranging from 21.69% (SHARE) in Denmark to 97.15% (CHARLS) in China. In the original model, digital exclusion was significantly associated with cognitive impairment in all five studies. In the adjusted model, these associations remained statistically significant: CHARLS (Odds ratio [OR] = 2.81, 95% confidence interval [CI] 1.84-4.28, ELSA (1.92 [1.70-2.18]), HRS(2.48[2.28-2.71), MHAS (1.92 [1.74-2.12]), and SHARE (2.60 [2.34-2.88]).

CONCLUSION

Our research shows that a significant proportion of older people suffer from digital exclusion, especially in China. Digital exclusion was positively correlated with cognitive impairment. These findings suggest that digital inclusion could be an important strategy to improve cognitive function and reduce the risk of cognitive impairment in older adults.

Lifestyle Influence on Mild Cognitive Impairment Progression: A Decision Tree Prediction Model Study

Purpose

This study assessed the influences of different lifestyle on mild cognitive impairment (MCI) progression and established a decision tree prediction model to analyse their predictive significance on MCI progression incidence.

Patients and Methods

From October 2015 to February 2020,330 patients with MCI were recruited, and demographic and lifestyle information collected. They were followed up for 19.04 ± 10.227 months. Cognitive function was assessed using the Mini-Mental State Examination Scale every 6 months, and they were divided into MCI stable group and MCI progression group.

Results

The Kaplan Meier survival analysis showed an overall cohort survival rate of 33.2%; the annual conversion rate of MCI progression was 20%. Physical exercise, social engagement, high-fat diet, age, napping, and tea drinking were decision tree prediction model nodes. Hobbies were the most important factor for predicting MCI progression. The MCI progression probability rates were: with hobbies 26.829% (44 cases), without hobbies 57.831% (96 cases); for those withot hobbies, with physical exercise 43.077% (28 cases) without physical exercise 72.340% (68 cases); for those without hobbies with physical exercise and social engagement 20.000% (4 cases), without social engagement 53.333% (24 cases); for those without hobbies, physical exercises and social engagement and with nap habits 48.485% (16 cases), without nap habits 66.667% (8 cases). The decision tree prediction model AUC for predicting the MCI progression receiver operating characteristic curve was 0.737 (95% confidence interval: 0.685-0.785) (75.71% sensitivity, 71.75% specificity, P < 0.001.

Conclusion

Hobbies, physical exercise, social engagement, napping, and drinking tea can help prevent MCI progression, while a high-fat diet may exacerbate MCI progression. In this study the rule with the lowest MCI progress probability for those who had hobbies, high-fat diet, and social engagement. And the decision tree model had good prediction efficiency.

Physical activity, sleep disorders, and type of work in the prevention of cognitive function decline in patients with hypertension

BACKGROUND

Hypertensive patients are likelier to have cognitive function decline (CFD). This study aimed to explore physical activity level, sleep disorders, and type of work that influenced intervention effects on cognitive function decline in hypertensive patients and to establish a decision tree model to analyze their predictive significance on the incidence of CFD in hypertensive patients.

METHODS

This cross-sectional study recruited patients with essential hypertension from several hospitals in Shandong Province from May 2022 to December 2022. Subject exclusion criteria included individuals diagnosed with congestive heart failure, valvular heart disease, cardiac surgery, hepatic and renal dysfunction, and malignancy. Recruitment is through multiple channels such as hospital medical and surgical outpatient clinics, wards, and health examination centers. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Moreover, we obtained information on the patients' type of work through a questionnaire and their level of physical activity through the International Physical Activity Questionnaire (IPAQ).

RESULTS

The logistic regression analysis results indicate that sleep disorder is a significant risk factor for CFD in hypertension patients(OR:1.85, 95%CI:[1.16,2.94]), mental workers(OR:0.12, 95%CI: [0.04,0.37]) and those who perform both manual and mental workers(OR: 0.5, 95%CI: [0.29,0.86]) exhibit protective effects against CFD. Compared to low-intensity, moderate physical activity(OR: 0.53, 95%CI: [0.32,0.87]) and high-intensity physical activity(OR: 0.26, 95%CI: [0.12,0.58]) protects against CFD in hypertension patients. The importance of predictors in the decision tree model was ranked as follows: physical activity level (54%), type of work (27%), and sleep disorders (19%). The area under the ROC curves the decision tree model predicted was 0.72 [95% CI: 0.68 to 0.76].

CONCLUSION

Moderate and high-intensity physical activity may reduce the risk of developing CFD in hypertensive patients. Sleep disorders is a risk factor for CFD in hypertensive patients. Hypertensive patients who engage in mental work and high-intensity physical activity effectively mitigate the onset of CFD in hypertensive patients.

Sociodemographic Factors Predict Incident Mild Cognitive Impairment: A Brief Review and Empirical Study

OBJECTIVES

Mild cognitive impairment (MCI) is a transitional stage between normal cognitive aging and dementia that increases the risk of progressive cognitive decline. Early prediction of MCI could be beneficial for identifying vulnerable individuals in the community and planning primary and secondary prevention to reduce the incidence of MCI.

DESIGN

A narrative review and cohort study.

SETTING AND PARTICIPANTS

We review the MCI prediction based on the assessment of sociodemographic factors. We included participants from 3 surveys: 8915 from wave 2011/2012 of the China Health and Retirement Longitudinal Study (CHARLS), 9765 from the 2011 Chinese Longitudinal Healthy Longevity Survey (CLHLS), and 1823 from the 2014 Rugao Longevity and Ageing Study (RuLAS).

METHODS

We searched in PubMed, Embase, and Web of Science Core Collection between January 1, 2019, and December 30, 2022. To construct the composite risk score, a multivariate Cox proportional hazards regression model was used. The performance of the score was assessed using receiver operating characteristic (ROC) curves. Furthermore, the composite risk score was validated in 2 longitudinal cohorts, CLHLS and RuLAS.

RESULTS

We concluded on 20 articles from 892 available. The results suggested that the previous models suffered from several defects, including overreliance on cross-sectional data, low predictive utility, inconvenient measurement, and inapplicability to developing countries. Our empirical work suggested that the area under the curve for a 5-year MCI prediction was 0.861 in CHARLS, 0.797 in CLHLS, and 0.823 in RuLAS. We designed a publicly available online tool for this composite risk score.

CONCLUSIONS AND IMPLICATIONS

Attention to these sociodemographic factors related to the incidence of MCI can be beneficially incorporated into the current work, which will set the stage for better early prediction of MCI before its incidence and for reducing the burden of the disease.

The effect of childhood social isolation on behavioral cognition in Chinese middle-aged and older adults: The moderating effect of family support

INTRODUCTION

This study aimed to analyze the association of childhood social isolation and behavioral cognition, and moderating effect of family support in middle-aged and older adults.

METHODS

The study samples were from the China Health and Retirement Longitudinal Study (CHARLS) of 2014 and 2018. The dependent variable was behavioral cognitive ability, measured by episodic memory and mental state; The independent variable was childhood social isolation, and the moderating variable was family support. The baseline OLS regression model was used to explore the correlation among independent variables, dependent variables and moderating variables, the least square regression model was used to analyze the moderating effect of family support, and the replacement model and the method of replacing characteristic variables were used for the robustness test. Hierarchical regression heterogeneity analysis was performed to further verify the results of the moderating effect.

RESULTS

In this study, 3459 samples were selected for analysis. OLS baseline regression results showed that the deepening of childhood social isolation was significantly correlated with the decline of behavioral cognitive ability in middle-aged and elderly people (β=-0.9664, t = 0.0893). After adding all covariates, we found that childhood social isolation was significantly negatively correlated with behavioral cognitive ability in middle-aged and elderly people (β=-0.4118, t = 0.0785). Among the moderating variables of family support, we found that there is a moderating effect on female guardians' efforts of caring in early parental support (β=0.0948, t = 0.0320) and the frequency of children's visits in late children support (β=0.0073, t = 0.0036). Finally, through the heterogeneity test, we found that there were differences in the relationship between childhood social isolation and behavioral cognitive ability among middle-aged and elderly people of different ages, genders and places of residence. Moreover, there are significant differences in the moderating effect of female guardian's effort of caring and the frequency of children's visits in heterogeneous groups.

CONCLUSIONS

The greater the degree of childhood social isolation experienced by middle-aged and elderly people, the worse their behavioral cognitive ability. Female guardian's effort of caring and the frequency of children's visits have a moderating effect to suppress this negative effect.

Analysis of Factors Associated with Subjective Mild Cognitive Impairment (MCI) among Older Adults Resident in the Community

This study explored the associated factors of mild cognitive impairment (MCI) in older adults, focusing on personal characteristics and health promotion activities. The research design of this study was a non-experimental, cross-sectional design. This study used secondary data from the 2019 community health survey conducted by the Korea Disease Control and Prevention Agency (KDCA). In this study, 20,041 older adults with subjective MCI and 52,587 healthy older adults-a total of 72,628 subjects-were analyzed as the final subjects in this study. The data were analyzed by using descriptive statistics, a chi-square test, an independent t-test, and logistic regression. The results indicate that the probability of experiencing subjective MCI significantly decreased with an increase in monthly income (odds ratio (OR) = 1.71, 95% confidence interval (CI) = 1.19-2.46); increased with an increase in depressive symptoms (odds ratio (OR) = 1.09, 95% confidence interval (CI) = 1.04-1.15); and decreased with an increase in the quality of life level (OR = 0.90, 95% CI = 0.82-0.99). Through the results of this study, several factors related to MCI in older adults were identified. If these related factors are properly managed, the possibility of MCI in older adults may be reduced. Therefore, MCI in older adults should be addressed as a preventable disease rather than a natural aging process.

Using machine learning algorithms for predicting cognitive impairment and identifying modifiable factors among Chinese elderly people

Objectives: This study firstly aimed to explore predicting cognitive impairment at an early stage using a large population-based longitudinal survey of elderly Chinese people. The second aim was to identify reversible factors which may help slow the rate of decline in cognitive function over 3 years in the community. Methods: We included 12,280 elderly people from four waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), followed from 2002 to 2014. The Chinese version of the Mini-Mental State Examination (MMSE) was used to examine cognitive function. Six machine learning algorithms (including a neural network model) and an ensemble method were trained on data split 2/3 for training and 1/3 testing. Parameters were explored in training data using 3-fold cross-validation and models were evaluated in test data. The model performance was measured by area-under-curve (AUC), sensitivity, and specificity. In addition, due to its better interpretability, logistic regression (LR) was used to assess the association of life behavior and its change with cognitive impairment after 3 years. Results: Support vector machine and multi-layer perceptron were found to be the best performing algorithms with AUC of 0.8267 and 0.8256, respectively. Fusing the results of all six single models further improves the AUC to 0.8269. Playing more Mahjong or cards (OR = 0.49,95% CI: 0.38-0.64), doing more garden works (OR = 0.54,95% CI: 0.43-0.68), watching TV or listening to the radio more (OR = 0.67,95% CI: 0.59-0.77) were associated with decreased risk of cognitive impairment after 3 years. Conclusions: Machine learning algorithms especially the SVM, and the ensemble model can be leveraged to identify the elderly at risk of cognitive impairment. Doing more leisure activities, doing more gardening work, and engaging in more activities combined were associated with decreased risk of cognitive impairment.

Association Between Internet Use, Cognitive Function, and Globus Pallidus Volumes: A Study Among the Elderly in Chinese Communities

Background

Previous studies have linked internet use with several beneficial outcomes for brain health, but there is little data on this among older Chinese.

Objective

The goal of this study was to explore the association between internet use and cognitive impairment and to explore the possible mechanisms by which internet use prevents cognitive decline.

Methods

The current study consisted of two cohorts: one from the China Longitudinal Aging Study (CLAS), which included 610 older adults with mild cognitive impairment (MCI), 192 with dementia, and 2,218 healthy older adults; the second cohort included 39 healthy adults from the Shanghai brain health foundation (SHBHF2016001), who underwent T1 cranial magnetic resonance imaging at baseline, from which their volumes of the hippocampus, amygdala, and globus pallidus were calculated. Moreover, they were also followed up for 1 year. Through standardized questionnaires, detailed general demographic information and internet use information was obtained. The cognitive diagnosis of each participant was made by attending psychiatrists at baseline, and their overall cognitive function was assessed by the mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA).

Results

In cohort 1, after controlling age, gender, smoker, tea drinker, take exercise, diabetes, and hypertension, we found that internet use was associated with MCI (P = 0.015, OR = 0.478, 95% CI: 0.264~0.867), but not for dementia (P = 0.205, OR = 0.393, 95% CI: 0.093~1.665). In cohort 2, we found that the globus pallidus volume of internet users was significantly larger than that of non-users, and the MMSE change score was lower (P < 0.05). The results of partial correlation analysis (controlled for sex, age and education) showed that the change of MMSE value was positively correlated with the volume of left globus pallidus (r = 0.547, P = 0.004).

Conclusions

Internet use might be a protective factor for mild cognitive impairment among the Chinese elderly, and it may prevent a decline in cognitive decline by affecting the volume of the globus pallidus.

The Prevalence of Amnestic and Non-Amnestic Mild Cognitive Impairment and Its Association with Different Lifestyle Factors in a South Italian Elderly Population

Mild Cognitive Impairment (MCI) is a transition stage between normal aging and dementia and can be useful to monitor the cognitive status of people at risk of dementias. Our aims were to investigate the prevalence of amnestic and non-amnestic MCI in a South Italian elderly population, and to identify socio-demographic, clinical and lifestyle factors associated with MCI. A cross-sectional retrospective population study on 839 community-dwelling participants over 60 years of age was carried out. Elderly people were administered a brief neuropsychological screening to identify their cognitive and functional status, and a questionnaire to investigate several socio-demographic, clinical, and lifestyle factors. Prevalence estimate for MCI was 12.0% (95% CI: 10.0-14.5%), for amnestic MCI was 7.4% (95% CI: 5.8-9.4%), and for non-amnestic MCI was 4.6% (95% CI: 3.4-6.4%), for people older than 60 years of age. Logistic regression models, corrected for age, sex, and education, revealed a significant association of MCI with the following factors: age, education, intellectual activities, and topographical disorientation. On the other hand, education, clinical factors (e.g., depression level and perceived physical pain), lifestyle factors (e.g., smoking, alcohol, and leisure/productive activities), dietary habits, quality of life, and self-reported topographical disorientation were non-significantly associated with MCI. Prevalence estimates and the association of MCI and its subtypes with risk and protective factors were discussed in comparison with the most recent systematic reviews and meta-analyses.

Prevalence, Influencing Factors, and Clinical Characteristics of Cognitive Impairment in Elderly Patients With Schizophrenia

AIMS

The purpose of this study was to investigate the prevalence, influencing factors, and clinical characteristics of cognitive impairment in elderly patients with chronic schizophrenia.

MATERIALS AND METHODS

A total of 264 elderly patients with chronic schizophrenia and 156 normal controls were enrolled in the current study. The Mini-mental State Examination (MMSE) was used to assess their overall cognitive function, the Positive And Negative Syndrome Scale (PANSS) was used to assess their psychotic symptoms, the Geriatric Depression Scale (GDS) was used to assess their depressive symptoms, while Activity of Daily Living Scale (ADL) was used to assess their daily living ability.

RESULTS

The prevalence of cognitive impairment was 77.7% (205/264) in elderly patients with chronic schizophrenia, which was much higher than that [16.7% (26/156)] in normal controls. By using stepwise binary regression analysis, we found that hobbies (p < 0.001, OR = 0.224, 95% CI: 0.114-0.441) might be a protective factor for cognitive impairment, and this relationship remained statistically significant after adjusting for total scores of GDS, ADL and PANSS (model ^b ) (p = 0.016, OR = 0.406, 95% CI: 0.195-0.847). Compared with individuals without cognitive impairment, individuals with cognitive impairment tend to have more depression and psychiatric symptoms as well as worse activities of daily living (p < 0.05). Through linear regression analysis of the mediating model, we found that hobbies may improve cognitive function by improving psychiatric symptoms, and play a partial mediating role (B = -4.789, p < 0.001).

CONCLUSION

Cognitive impairment is a very prominent problem in elderly patients with chronic schizophrenia. Elderly schizophrenia patients with cognitive impairment tended to have more depressive mood, more psychotic symptoms and worse activities of daily living. Hobbies will help prevent cognitive impairment in elderly patients with schizophrenia and may improve their cognitive function by influencing psychiatric symptoms. Therefore, we should encourage elderly patients with chronic schizophrenia to develop their own hobbies. However, the above conclusion still need to be further verified, as we cannot exclude the effects of age and education.

Body Mass Index and Mild Cognitive Impairment Among Middle-Aged and Older Adults from Low- and Middle-Income Countries

BACKGROUND

The effect of weight modification on future dementia risk is currently a subject of debate and may be modified by age.

OBJECTIVE

The aim of the present study was to investigate the association between body mass index (BMI) status with mild cognitive impairment (MCI) (a preclinical stage of dementia) in middle-aged and older adults residing in six low- and middle-income countries using nationally representative data.

METHODS

Cross-sectional data from the Study on Global Ageing and Adult Health (SAGE) were analyzed. MCI was defined using the National Institute on Aging-Alzheimer's Association criteria. BMI (kg/m2) was based on measured weight and height and categorized as: underweight (<18.5), normal (18.5-24.9), overweight (25.0-29.9), and obese (≥30.0). Multivariable logistic regression analysis and meta-analysis were conducted to assess associations.

RESULTS

Data on 32,715 individuals aged ≥50 years with preservation in functional abilities were analyzed [mean (SD) age 62.1 (15.6) years; 51.7% females]. Among those aged 50-64 years, compared to normal weight, underweight (OR = 1.44; 95% CI = 1.14-1.81), overweight (OR = 1.17; 95% CI = 1.002-1.37), and obesity (OR = 1.46; 95% CI = 1.09-1.94) were all significantly associated with higher odds for MCI. In those aged ≥65 years, underweight (OR = 0.71; 95% CI = 0.54-0.95) and overweight (OR = 0.72; 95% CI = 0.55-0.94) were associated with significantly lower odds for MCI, while obesity was not significantly associated with MCI.

CONCLUSION

The results of the study suggest that the association between BMI and MCI is likely moderated by age. Future longitudinal studies are required to confirm or refute the present findings before recommendations for policy and practice can be made.

Impacts of stroke and cognitive impairment on activities of daily living in the Taiwan longitudinal study on aging

Stroke and cognitive impairment are common in older population. They often occur together and their combined effects significantly increase disability in both basic (BADLs) and instrumental (IADLs) activities of daily living. We investigated the individual and combined impacts of stroke and cognitive impairment on BADLs and IADLs. A total of 3331 community-dwelling older adults were enrolled from the Taiwan longitudinal study on aging in 2011. Both BADLs and IADLs were analyzed. Combination of stroke and cognitive impairment increased severity of ADL disabilities, but similar prevalence, similar numbers of summed BADL and IADL tasks with disability, and similar levels of difficulty for each BADL and IADL task were found between the stroke group and cognitive impairment group. The former had more difficult in dressing while the latter had more difficult in using the telephone, transport, and managing finances. A hierarchy of ADLs was also observed in all groups. ADL skill training supplemented with cognitive and physical interventions should focus on secondary prevention of dementia and improve motor functional capacity to reduce loss of ADLs.