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Objective:To analyze the lifestyle for brain health related factors and demographic characteristics through machine learning to achieve the assessing effect of mild cognitive impairement prevalence risk among rural elderly people in Guizhou.Methods:From July to August 2019, a multi-stage cluster random sampling method was used to select 1 235 rural elderly people aged 60 years and above in Guizhou Province as the subjects, and the investigation was performed with questionnaire and physical examination.The Mini-Mental State Examination (MMSE) was used to assess cognitive function, and the important features and optimal number of features based on 12 LIBRA factors and 4 demographic characteristics were selected.Logistic regression and random forest algorithm were used to establish a evaluation model for the risk of mild cognitive impairment in the elderly.The evaluation efficacy of the model was also assessed using a combination of precision, accuracy, sensitivity, specificity, F1 score and area under curve (AUC) of receiver operating characteristic curve, and the Delong method was used to check the difference of AUC values between the two models.Results:A total of 291 subjects were diagnosed with mild cognitive impairment, with a detection rate of 23.56% (291/1 235). The AUC values of logistic regression and random forest models evaluating the risk of mild cognitive impairment in the rural elderly were 0.758 and 0.820, respectively, and the differences were statistically significant(both P<0.05). The random forest model had better evaluations with an accuracy of 0.823, precision of 0.805, sensitivity of 0.874, specificity of 0.767 and F1 score of 0.838, all of which were better than those of the logistic regression model.And the random forest model was also more stable after 10-fold cross-validation. Conclusion:The lifestyle for brain health related factors combined with demographic characteristics can more accurately evaluate the risk of mild cognitive impairment among rural elderly people in Guizhou.The random forest model is better than the logistic regression model.
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Cognitive health is key for older adults to live independently, and exercise intervention can improve cognitive health.Exercise improves cognitive health through a variety of mechanisms, including improvement of cerebral blood perfusion, enhancement of brain capacity and connectivity, promotion of neurogenesis, and release of neurotrophic factors, miRNA and myokines.The exercise mode and dose can affect the effect of exercise intervention on cognitive health.Individualized exercise intervention with a duration of more than 12 weeks and a multi-mode combination is more conducive to improving the cognitive health of older adults.
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Objective:To study on performance comparison between clinic digital memory assessment and previously used assessments in dementia risk screening.To compare the performance comparison between Beijing Aging Brain Rejuvenation Initiative(BABRI)Brain Health System's Clinic Digital Memory Detection as study and Alzheimer Disease-8(AD8)and the Brief Community Screening Instrument for Dementia(BCSID)as controls, We calculated and evaluated the accuracy, sensitivity and specificity of screening Mild cognitive impairment(MCI)among these tests.Furthermore, BABRI Brain Health System was used to conduct a large sample brain health examination and early dementia screening to test the validity, adaptability and stability of the evaluation results by BABRI Brain Health System'Clinic Digital Memory Detection.Methods:Dataset 1 contained 669 elderly subjects from five communities in Beijing were recruited according to inclusion and exclusion standard.The diagnosis of MCI was based on the full set of neuropsychological scale and Petersen standard.Dataset 1 was used to compare the discriminant effect of BABRI Brain Health System'Clinic Digital Memory Detection as study versus AD8 and BCSID as controls.The sensitivity, specificity, positive predictive value, negative predictive value and Youden index of each measurement tool were calculated.Then, the receiver operator characteristic(ROC)curve was prepared to compare the discrimination ability of MCI between each measurement tool.While the area under the curve(AUC)of different tools was compared by Wald χ2 test.Dataset 2 contained 284 103 subjects from 16 communities in Beijing, which were used to test the applicability of large sample screening in BABRI Brain Health System. Results:77 patients with MCI were found among 666 people, and incidence rate was 11.56% using the full set of neuropsychological scales in dataset 1.Compared with the results of other tests, the sensitivity of BABRI Brain Health System to correctly distinguish MCI was 0.753, which was close to BCSID, and better than AD8.In addition, BABRI Brain Health System's Youden's index was 0.741 and AUC was 0.905, which suggested that the specificity, positive predictive value, negative predictive value and cognitive domain coverage of MCI screening were generally better in BABRI Brain Health System than in AD8 and BCSID.Finally, the Brain Health Examination results of 284, 000 people in dataset 2 showed that the high-risk detection rate of MCI(8.65%)of the tool for people over 50 years old under a large sample was quite close to the results of dataset 1(8.67%), indicating that the BABRI Brain Health System had high stability.Conclusions:BABRI Brain Health System has not only high sensitivity and specificity, but also wide cognitive field coverage and high stability.BABRI Brain Health System is suitable for large-scale brain health examination and dementia risk screening in grass-roots communities, and is worthy of popularization.
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@#The combined effort of the neuroscience and psychology cluster at the Universiti Sains Malaysia (USM)—fundamental, applied and clinical—has moved the institution to the number two position in the country, behind Universiti Malaya. The strategy to join the Global Brain Consortium (GBC) and put Malaysia on the map to address the GBC mission, vision, focus areas and outcomes began recently, in May 2019.
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0bjective To explore the effect of brain health education on therapeutic adherence of hypertensive patients with subjective memory complaints based on health belief model. Methods A randomized controlled trial was designed in this study. eligible patients were selected from a community health service center in Chongqing were randomly assigned to intervention group (56 cases) and control group (60 cases). The control group received routine community health services and the intervention group received brain health education on the basis of the control group. statistical analysis was performed on the patients' dementia risk control belief, therapeutic adherence, and blood pressure control rate at baseline, after the group intervention, and after the individualized telephone intervention. Results There was a significant group× time interaction(F 交互=12.353, 22.376, P<0.05) on dementia risk control belief and therapeutic adherence (P<0.05),. The dementia risk control belief score, the therapeutic adherence and the blood pressure control rate in the intervention group was (98.74±13.62), (119.26±4.93) points and 70.0% , the control group was (85.00 ± 12.80), (106.48 ± 10.33) points and 50.0% after the intervention; the intervention group was higher than the control group (t=5.194, t=7.899, χ2=4.167, P<0.05). The subjects were rated at 4 points and above for each item of satisfaction with the project after the intervention. Conclusions Brain health education based on health belief model in hypertensive patients with subjective memory complaints, can effectively improve the dementia risk control belief and therapeutic adherence, and promote the self-management of blood pressure control.
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RESUMEN Introducción: La Diabetes Mellitus es la enfermedad metabólica más frecuente. Su efecto deletéreo sobre la cognición es poco reconocido. La demencia es la enfermedad neurodegenerativa más común y la población diabética está en mayor riesgo de desarrollarla a futuro. Objetivo: Comparar la función cognitiva de los individuos diabéticos de mediana edad, con un grupo control no diabético, y así determinar población en riesgo de desarrollar deterioro cognitivo. Metodología: Se realizó un estudio observacional, poblacional, de corte transversal en Guayaquil. Se han estudiado 309 individuos -142 diabéticos y 167 no diabéticos- entre 55 y 65 años de edad a quienes se les practicaron pruebas neuropsicológicas para determinar su funcionamiento cognitivo en atención, velocidad de procesamiento, memoria y función ejecutiva. Resultados: Las comparaciones entre ambos grupos demostraron diferencias significativas en cuanto a hipertensión arterial sistólica (p< .001), hiperlipidemia (p< .001) e índice de riesgo cardiovascular (p< .001). El rendimiento cognitivo fue menor en los pacientes diabéticos luego de considerar la diferencia en años de escolaridad (pruebas de memoria con valores p entre .000 y .002; pruebas de atención con valores p entre .000 y .019; función ejecutiva con valores p entre .000 y .001). No hubo correlación significativa entre los años de evolución de la enfermedad y deterioro cognitivo (memoria -.055; atención -.040; función ejecutiva .0169). La relación entre los niveles de hemoglobina glicosilada y deterioro cognitivo sí fueron significativos para todas las funciones cognitivas evaluadas (memoria -.219; atención -.186; función ejecutiva -.269). Conclusión: La población diabética de mediana edad tiene un rendimiento cognitivo inferior a la no diabética. La identificación temprana de población en riesgo de desarrollar demencia en la adultez mayor permitirá diseñar estrategias de intervención que permitan retardar la aparición clínica de la demencia en individuos vulnerables.
ABSTRACT Introduction: Diabetes mellitus is a frequent and systemic illness. Deleterious effects on cognition are one of its lesser known consequences. Diabetic individuals are at an increased risk for development of dementia in the future. Objective: To compare cognitive function in middle aged diabetic population with non-diabetic control group, in order to determine high risk population for developing cognitive decline or dementia in the future. Methodology: This is a cross-sectional, observational study conducted in Guayaquil. We studied 309 individuals between the ages of 55 and 65 years, of which 142 were diabetics and 167 were non-diabetic controls. A neuropsychological evaluation was performed to assess memory, attention, executive functioning and processing speed. Results: Group comparisons revealed significant differences between diabetics and non-diabetics in systolic blood pressure (p<.001), hyperlipidemia (p<.001) and cardiovascular risk (p < .001). Cognitive performance, after considering differences in scholarship, was lower in diabetic people (memory p values between .000 and .002; attention p values between .000 and .019; executive function p values between .000 and .001). Correlation between years of disease and cognitive decline was not significant (memory -.055; attention -.040; executive function .0169). Correlation between glycated hemoglobin and cognitive performance was significant for all evaluated functions (memory -.219; attention -.186; executive function -.269). Conclusion: Middle aged diabetic population has lower cognitive performance compared with non diabetics. The identification of individuals at risk for cognitive decline will contribute to the development and implementation of intervention strategies that will allow the slowing of cognitive decline in vulnerable individuals.
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Exercise can promote brain health in all the ages, directly or indirectly. In early childhood and adolescence, exercise can increase cardiorespiratory fitness to optimize the neuronal environment to benefit cerebral maturation and cognitive de-velopment. In mid-life, exercise may maintain cognitive function by increasing cerebral gray volume and cardiovascular fitness, and preventing a lot of neurobiological events which result in cognitive decline later in life. Finally, regular exer-cise in late life is very important for integrity of brain white matter, cardiorespiratory fitness, and prevention of future de-cline.