Depression and cognitive decline in elderly: causes and consequences

Левин, О С; Васенина, Е. Е.

doi:10.17116/jnevro201911907187

Cited by 12 publications

(11 citation statements)

References 26 publications

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“…For some researchers who used a longitudinal design, they were not sufficient to control the influence of some important covariates, including social engagement, lifestyles (including smoking and drinking), etc., which were reported in previous cross-sectional studies ( 10 , 11 ). Not only is current cognitive performance associated with depressive symptoms, but cognitive decline is also associated with depressive symptoms ( 12 ), and biological evidence has been found in previous studies ( 13 ). However, it remains uncertain whether cognitive decline could lead to depressive symptoms.…”

Section: Introductionmentioning

confidence: 80%

The associations between cognitive function and depressive symptoms among older Chinese population: A cohort study

Yang

Qi-tu

et al. 2023

Front. Psychiatry

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With the rapid development of society, population aging has emerged as a significant global challenge. This study aimed to evaluate the impact of baseline cognitive performance, current cognitive function, and cognitive decline on subsequent depressive symptoms. Data were obtained from participants aged 65 years and older in the Chinese Longitudinal Healthy Longevity Survey (CLHLS), Wave 2014–2018. Of the 7,192 participants in Wave 2014, 1,627 were included in the analysis. Multivariate regressions were conducted to estimate the associations between cognitive measures and depressive symptoms. Our results indicated that baseline cognitive function was not associated with subsequent depressive symptoms, but current cognitive function was. Furthermore, participants who experienced significant cognitive decline were more likely to develop depressive symptoms. Covariates, including marital status, economic status, physical activity, and recreational activity, were also associated with subsequent depressive symptoms. These findings suggest that slowing cognitive decline is an effective strategy for preventing depressive symptoms in older adults, promoting their health and wellbeing.

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Section: Introductionmentioning

confidence: 80%

The associations between cognitive function and depressive symptoms among older Chinese population: A cohort study

Yang

Qi-tu

et al. 2023

Front. Psychiatry

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“…Based on the literature, factors such as age, sex, depressive symptoms, and cognitive function alterations (i.e., FAB score) were found to influence risk-taking behaviors. Similarly, age, depressive symptoms, and cognitive function alterations (i.e., FAB score) were found to influence neuropsychological test scores [ 44 , 45 , 46 , 47 , 48 ]. In order to control for these predictive factors in risk-taking (BART and IGT scores) and neuropsychological assessments, a multiple regression linear analysis model was used.…”

Section: Methodsmentioning

confidence: 99%

Tools for the Assessment of Risk-Taking Behavior in Older Adults with Mild Dementia: A Cross-Sectional Clinical Study

Compagne,

Gabriel,

Ferrero

et al. 2023

Brain Sciences

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Diseases such as Alzheimer’s cause an alteration of cognitive functions, which can lead to increased daily risk-taking in older adults living at home. The assessment of decision-making abilities is primarily based on clinicians’ global analysis. Usual neuropsychological tests such as the MoCA (Montreal Cognitive Assessment) cover most of the cognitive domains and include mental flexibility tasks. Specific behavioral tasks for risk-taking, such as the Balloon Analogue Risk Task (BART) or the Iowa Gambling Task (IGT), have been developed to assess risk-taking behavior, particularly in the field of addictology. Our cross-sectional study aims to determine whether the MoCA global cognitive assessment could be used as a substitute for behavioral tasks in the assessment of risky behavior. In the current study, 24 patients (age: 82.1 ± 5.9) diagnosed with mild dementia completed the cognitive assessment (MoCA and executive function assessment) and two behavioral risk-taking tasks (BART, simplified version of the IGT). Results revealed no relationship between scores obtained in the MoCA and behavioral decision-making tasks. However, the two tasks assessing risk-taking behavior resulted in concordant risk profiles. In addition, patients with a high risk-taking behavior profile on the BART had better Trail Making Test (TMT) scores and thus retained mental flexibility. These findings suggest that MoCA scores are not representative of risk-taking behavioral inclinations. Thus, additional clinical tests should be used to assess risk-taking behavior in geriatric settings. Executive function measures, such as the TMT, and behavioral laboratory measures, such as the BART, are recommended for this purpose.

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“…Advanced age and well-known susceptibility genes, such as the APOE gene encoding apolipoprotein E (ApoE), remain the most significant non-modifiable risk factors for AD ( Al-Hamdan et al, 2010 ; Walker et al, 2017 ; Jarrar et al, 2023 ). Based on numerous epidemiological studies, several modifiable vascular and metabolic factors have been linked to increasing the risk of cognitive impairment and AD, such as midlife hypertension, stroke, midlife diabetes, hyperlipidemia, obesity, and depression, in addition to other lifestyle risk factors including smoking, sleep disturbances, and low levels of education ( Al-Shammari and Al-Subaie, 1999 ; Saeed et al, 2011 ; Bennett and Thomas, 2014 ; Levin and Vasenina, 2019 ; Andreescu and Lee, 2020 ; Kuring et al, 2020 ; Tinnirello et al, 2021 ; Zhao et al, 2023 ). With the continually growing knowledge about the potential role of modifiable risk factors, many researchers focus on modulating the well-known risk factors of AD and exploring new alternative therapeutic approaches.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence approaches for early detection of neurocognitive disorders among older adults

AlHarkan,

Sultana,

Al Mulhim

et al. 2024

Front. Comput. Neurosci.

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IntroductionDementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately.MethodsQuantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient’s cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients’ cognitive function based on gender and developed the predicting models for males and females separately.ResultsFifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time.ConclusionThe results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.

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Depression and cognitive decline in elderly: causes and consequences

Cited by 12 publications

References 26 publications

The associations between cognitive function and depressive symptoms among older Chinese population: A cohort study

The associations between cognitive function and depressive symptoms among older Chinese population: A cohort study

Tools for the Assessment of Risk-Taking Behavior in Older Adults with Mild Dementia: A Cross-Sectional Clinical Study

Artificial intelligence approaches for early detection of neurocognitive disorders among older adults

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