Risk Of Mild Cognitive Impairment Research Articles

Trajectories of Occupational Cognitive Demands and Risk of Mild Cognitive Impairment and Dementia in Later Life: The HUNT4 70+ Study.

The cognitive reserve hypothesis posits that cognitively stimulating work delays the onset of mild cognitive impairment (MCI) and dementia. However, the effect of occupational cognitive demands across midlife on the risk of these conditions is unclear. Using a cohort study design, we evaluated the association between registry-based trajectories of occupational cognitive demands from ages 30-65 years and clinically diagnosed MCI and dementia in participants in the HUNT4 70+ Study (2017-19). Group-based trajectory modeling identified trajectories of occupational cognitive demands, measured by the routine task intensity (RTI) index (lower RTI indicates more cognitively demanding occupation) from the Occupational Information Network. Multinomial regression was implemented to estimate the relative risk ratios (RRRs) of MCI and dementia, after adjusting for age, sex, education, income, baseline hypertension, obesity, diabetes, psychiatric impairment, hearing impairment, loneliness, smoking status, and physical inactivity assessed at HUNT1-2 in 1984-1986 and 1995-1997. To handle missing data, we used inverse probability weighting to account for nonparticipation in cognitive testing and multiple imputation. Based on longitudinal RTI scores for 305 unique occupations, 4 RTI trajectory groups were identified (n = 7,003, 49.8% women, age range 69-104 years): low RTI (n = 1,431, 20.4%), intermediate-low RTI (n = 1,578, 22.5%), intermediate-high RTI (n = 2,601, 37.1%), and high RTI (n = 1,393, 19.9%). Participants in the high RTI group had a higher risk of MCI (RRR 1.74, 95% CI 1.41-2.14) and dementia (RRR 1.37, 95% CI 1.01-1.86), after adjusting for age, sex, and education compared with participants in the low RTI group. In a sensitivity analysis, controlling for income and baseline health-related factors, the point estimates were not appreciably changed (RRR 1.66, 95% CI 1.35-2.06 for MCI, and RRR 1.31, 95% CI 0.96-1.78 for dementia). People with a history of cognitively stimulating occupations during their 30s, 40s, 50s, and 60s had a lower risk of MCI and dementia older than 70 years, highlighting the importance of occupational cognitive stimulation during midlife for maintaining cognitive function in old age. Further research is required to pinpoint the specific occupational cognitive demands that are most advantageous for maintaining later-life cognitive function.

Adverse childhood experiences and risk of late-life dementia: a systematic review and meta-analysis.

Adverse childhood experiences (ACEs) refer to distressing events before age 18 that can lead to potential mental and physical health consequences. This systematic review and meta-analysis aimed to examine the association between ACEs and the risk of dementia in elderly adults who experienced ACEs during childhood, addressing the existing inconsistencies and methodological variations. A comprehensive search strategy was employed across key databases (PubMed, Web of Science, Scopus, and Embase) to identify relevant articles. Our primary outcome was ACEs-dementia risk, and our secondary outcome was mild cognitive impairment risk. A quality assessment was conducted using the Newcastle-Ottawa Quality Assessment Scale and GRADE. A random-effects model was utilized to calculate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses were performed to explore potential sources of heterogeneity and assess the reliability of the results. Out of 1,376 screened papers, nine studies were included. The studies consisted of two case-control, one prospective cohort, and six retrospective cohort studies conducted in the UK, France, USA, China, and Spain. Five studies were of good methodological quality according to the NOS. according to the GRADE, all outcomes were classified as very low or low quality of evidence. A significant association was observed between ACEs and dementia risk (OR = 1.35; 95% CI 1.20, 1.52; P = 0.00001) and mild cognitive impairment risk (OR = 1.28; 95% CI 0.63, 2.62; P = 0.49). A meta-analysis by type of adversity revealed significant results for the maltreatment subgroup(OR = 1.30; 95% CI 0.07-1.58; P = 0.007; I² = 0%). Subgroup analysis based on the dementia definition revealed no between-subgroup difference (P = 0.71) between tool-based and register/criteria-based subgroups. No possibility of Publication bias was observed upon inspection of the funnel plot. Adverse childhood experiences may be associated with an increased risk of dementia. However, caution is warranted in interpreting these results due to the limited number of studies. Larger high-quality studies investigating the association between ACEs and dementia risk are needed to confirm the reliability of our results.

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study.

The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non-shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

Estimating Gender Differences in the Association between Cognitive Resilience and MCI Incidence.

Recent evidence suggests that the influence of verbal intelligence and education on the onset of subjective cognitive decline may be modulated by gender, where education contributes less to cognitive resilience in women than in men. This study aims to examine gender differences in the association between cognitive resilience (CR) and mild cognitive impairment (MCI) incidence in an Australian population-based cohort. We included 1806 participants who had completed at least the first two waves and up to four waves of assessments in the Personality and Total Health (PATH) through life study (Baseline: 49% Female, Mage=62.5, SD=1.5), age range=60-66). CR proxies included measures of educational attainment, occupation skill, verbal intelligence, and leisure activity. Discrete-time survival analyses were conducted to examine gender differences in the association between CR proxies and MCI risk, adjusting for age and Apolipoprotein E4 status. Gender differences were only found in the association between occupation and MCI risk, where lower occupation skill was more strongly associated with higher risk in men than in women (OR = 1.30, 95% CI[1.07, 1.57]). In both genders, after adjusting for education and occupation, one SD increase in leisure activity was associated with lower MCI risk by 24% (OR = 0.76, 95% CI[0.65, 0.89]). Higher scores in verbal intelligence assessment were associated with reduced risk of MCI by 22% (OR = 0.78, 95% CI[0.69, 0.89]). Occupational experience may contribute to cognitive resilience differently between genders. Life-course cognitive engagement and verbal intelligence may be more protective against MCI than education and occupation for both men and women.

Interplay of age, gender, education, and heart rate in dementia among older adults in Wakiso, Uganda: a cross sectional study

Background In this cross-sectional study conducted in Wakiso, Uganda, from May to July 2023, we investigated the interactions among age, sex, education, and heart rate in relation to dementia and Mild Cognitive Impairment (MCI) among individuals aged 65 years and older. Methods We purposively sampled 106 participants, focusing on those with Alzheimer’s disease and related dementias, leveraging collaborations with local health teams. Data collection involved comprehensive questionnaires covering sociodemographic details and health parameters, and employed the Montreal Cognitive Assessment Tool for dementia screening. Results Our findings highlight a nuanced landscape of risk factors; each additional year of age was associated with a 1.19- and 1.22-times increased risk of MCI and dementia, respectively. Gender analysis revealed a protective effect against MCI in males, but no significant impact on dementia risk. Education emerged as a protective factor, with each additional year associated with a 28% reduction in MCI risk, although its effect on dementia risk remains ambiguous. Significantly, an elevated heart rate was strongly linked to an increased risk of both MCI and dementia, underscoring the potential cardiovascular dimension in cognitive health. Conclusions This study contributes to the understanding of the complex interplay of risk factors for dementia, emphasizing the need for further research to elucidate the underlying mechanisms and interventions for healthy cognitive aging in the older adult population.

Development of Malaysian-MIND diet scores for prediction of mild cognitive impairment among older adults in Malaysia.

Mild Cognitive impairment (MCI) is a pre-demented state in the elderly populace. The Mediterranean & Dietary Approaches to Stop Hypertension (DASH) Intervention for Neurodegenerative Delay (MIND) diet has shown promise in reducing the risk of MCI and Alzheimer's disease in older people. Notably, the existing MIND diet is not adapted to the specific needs of older adults in Malaysia, considering distinct food cultures and availability. Consequently, this study aimed to develop the Malaysian version of the MIND diet (MY-MINDD) scores and investigate their association with MCI in the older adult populace of Malaysia. A comprehensive pooled data analysis was conducted on combined data from 810 participants sourced from the longitudinal Long-Term Research Grant Scheme-Towards Useful Aging (LRGS-TUA) and Fundamental Research Grant Scheme (FRGS) studies. The MY-MINDD scores were developed by incorporating existing MIND diet food groups, their corresponding scoring mechanisms, and consideration of common Malaysian foods which are proven to be beneficial and detrimental to cognitive function. To substantiate the MY-MINDD scoring system, its association with MCI was evaluated using a series of validated neuropsychological test batteries. MY-MINDD consists of seven food groups promote brain health and four food groups exert negative cognitive outcomes. The study participants had an average age of 67.9 ± 4.7 years. The collective MY-MINDD score for all participants was 6.4 ± 0.1 (out of a maximum 11 points), revealing a lower score in individuals with MCI at 6.0 ± 1.7 compared to those without MCI at 6.6 ± 1.6 (p < 0.001). According to hierarchical multivariate binary logistic regression analysis, being in the highest tertile of MY-MINDD score was linked to reduced odds of MCI (odds ratio (OR) = 0.43, 95% confidence interval (CI): 0.26-0.72, p < 0.001) in the fully adjusted model in comparison to the lowest tertile. The development of the MY-MINDD scores for Malaysian older population revealed that a stronger adherence to this diet is linked to a reduced risk of MCI. Further substantiation of the MY-MINDD scores using more objective measures, such as neuroimaging approaches and other neuropsychological batteries, is necessary.

The effect of the apolipoprotein E ε4 allele and olfactory function on odor identification networks.

The combination of apolipoprotein E ε4 (ApoE ε4) status, odor identification, and odor familiarity predicts conversion to mild cognitive impairment (MCI) and Alzheimer's disease (AD). To further understand olfactory disturbances and AD risk, ApoE ε4 carrier (mean age 76.38±5.21) and ε4 non-carrier (mean age 76.8±3.35) adults were given odor familiarity and identification tests and performed an odor identification task during fMRI scanning. Five task-related functional networks were detected using independent components analysis. Main and interaction effects of mean odor familiarity ratings, odor identification scores, and ε4 status on network activation and task-modulation of network functional connectivity (FC) during correct and incorrect odor identification (hits and misses), controlling for age and sex, were explored using multiple linear regression. Findings suggested that sensory-olfactory network activation was positively associated with odor identification scores in ε4 carriers with intact odor familiarity. The FC of sensory-olfactory, multisensory-semantic integration, and occipitoparietal networks was altered in ε4 carriers with poorer odor familiarity and identification. In ε4 carriers with poorer familiarity, connectivity between superior frontal areas and the sensory-olfactory network was negatively associated with odor identification scores. The results contribute to the clarification of the neurocognitive structure of odor identification processing and suggest that poorer odor familiarity and identification in ε4 carriers may signal multi-network dysfunction. Odor familiarity and identification assessment in ε4 carriers may contribute to the predictive value of risk for MCI and AD due to the breakdown of sensory-cognitive network integration. Additional research on olfactory processing in those at risk for AD is warranted.

Glycemic Control, Cognitive Aging, and Impairment Among Diverse Hispanics/Latinos: Study of Latinos-Investigation of Neurocognitive Aging (Hispanic Community Health Study/Study of Latinos).

Hispanics/Latinos in the United States have the highest prevalence of undiagnosed and untreated diabetes and are at increased risk for cognitive impairment. In this study, we examine glycemic control in relation to cognitive aging and impairment in a large prospective cohort of middle-aged and older Hispanics/Latinos of diverse heritages. Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) is a Hispanic Community Health Study/Study of Latinos (HCHS/SOL) ancillary study. HCHS/SOL is a multisite (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA), probability sampled prospective cohort study. SOL-INCA enrolled 6,377 diverse Hispanics/Latinos age 50 years and older (2016-2018). The primary outcomes were cognitive function, 7-year cognitive decline and mild cognitive impairment (MCI). The primary glycemia exposure variables were measured from fasting blood samples collected at HCHS/SOL visit 1 (2008-2011). Visit 1 mean age was 56.5 years ± 8.2 SD, and the average glycosylated hemoglobin A1C (HbA1c) was 6.12% (43.5 ± 14.6 mmol/mol). After covariates adjustment, higher HbA1c was associated with accelerated 7-year global (b = -0.045; 95% CI = -0.070; -0.021; in z-score units) and executive cognitive decline, and a higher prevalence of MCI (odds ratio = 1.20; 95% CI = 1.11;1.29). Elevated HbA1c levels were associated with 7-year executive cognitive decline and increased MCI risk among diverse middle-aged and older Hispanics/Latinos. Our findings indicate that poor glycemic control in midlife may pose significant risks for cognitive decline and MCI later in life among Hispanics/Latinos of diverse heritages.

A non-linear relationship between blood pressure and mild cognitive impairment in elderly individuals: A cohort study based on the Chinese longitudinal healthy longevity survey (CLHLS).

Hypertension is an established risk factor for mild cognitive impairment (MCI) in elderly individuals. Nevertheless, the impact of different levels of blood pressure on the progression of MCI remains uncertain. This study aims to investigate the non-linear relationship between blood pressure and MCI in the elderly and detect the critical blood pressure threshold, thus, improving blood pressure management for individuals at high risk of MCI. Data was obtained from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) cohort. We chose normal cognitive elderly individuals who entered the cohort in 2014 for a 5-year follow-up to observe the progression of MCI. Subsequently, we utilized the Cox regression model to identify risk factors for MCI and conducted a Cox-based restricted cubic spline regression (RCS) model to examine the non-linear relationship between systolic blood pressure (SBP) and diastolic blood pressure (DBP) with MCI, determining the critical blood pressure threshold for MCI progression. In the elderly population, female (HR = 1.489, 95% CI: 1.017-2.180), lacking of exercise in the past (HR = 1.714, 95% CI: 1.108-2.653), preferring animal fats (HR = 2.340, 95% CI: 1.348-4.061), increased age (HR = 1.061, 95% CI: 1.038-1.084), increased SBP (HR = 1.036, 95% CI: 1.024-1.048), and increased DBP (HR = 1.056, 95% CI: 1.031-1.081) were associated with MCI progression. After adjusting factors such as gender, exercise, preferred types of fats, and age, both SBP (P non-linear < 0.001) and DBP (P non-linear < 0.001) in elderly individuals exhibited a non-linear association with MCI. The risk of MCI rose when SBP exceeded 135mmHg and DBP was in the range of 80-88mmHg. However, when DBP exceeded 88mmHg, there was a declining trend in MCI progression, although the HR remained above 1. The identified critical blood pressure management threshold for MCI was 135/80mmHg. In this study, we discovered that risk factors affecting the progression of MCI in elderly individuals comprise gender (female), preferring to use animal fat, lack of exercise in the past, increased age, increased SBP, and increased DBP. Additionally, a non-linear relationship between blood pressure levels and MCI progression was confirmed, with the critical blood pressure management threshold for MCI onset falling within the prehypertensive range.

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

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. 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 7years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model. Through 7years 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 7years 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. 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.

Resistance training's impact on blood biomarkers and cognitive function in older adults with low and high risk of mild cognitive impairment: a randomized controlled trial

BackgroundThe aging brain exhibits a neuroinflammatory state, driven partly by peripheral pro-inflammatory stimuli, that accelerates cognitive deterioration. A growing body of evidence clearly indicates that physical exercise partly alleviates neuroinflammation and positively affects the aging process and cognition. In this randomized controlled trial, we aimed to observe the effect of 12 weeks of resistance training (RT) on peripheral biomarker levels, cognitive function changes and their interrelationship, and explore differences in those exercise-induced changes in older adults with high risk of mild cognitive impairment (MCI) compared to older adults with low risk of MCI.MethodsFifty-two participants (aged 60–85 years old, 28 female) were randomly allocated to a 12 week lower limb RT program consisting of two training sessions per week or waiting list control group. The Montreal Cognitive Assessment (MoCA) was used to stratify participants screened as high (< 26/30) or low risk (≥ 26/30) of MCI. We assessed serum Interleukin 6 (IL-6), Insulin-like Growth Factor-1 (IGF-1), and Kynurenine (KYN) levels. Cognitive measurement consisted of and four subtests of Automated Neuropsychological Assessment Metrics (ANAM), the two-choice reaction time, go/no-go, mathematical processing, and memory search test.ResultsTwelve weeks of RT improved Go/No-go test results in older adults with high MCI risk. RT did not significantly affect blood biomarkers. However, IGF-1 level increases were associated with improvements in response time on the mathematical processing test in the exercise group, and IL-6 level increases were associated with improvements in response time on the memory search test in the total group of participants. Finally, KYN levels significantly differed between older adults with low and high MCI risk but no significant associations with performance were found.ConclusionOur study results suggest a different effect of RT on inhibitory control between older adults with low compared to high MCI risk. IGF-1 may play a role in the mechanism behind the cognitive benefit of RT and KYN may be a surrogate biomarker for neurodegeneration and cognitive decline.

Association Between Long-Term Exposure to Ambient Air Pollution and the Risk of Mild Cognitive Impairment in a Chinese Urban Area: A Case-Control Study.

As a prodromal stage of dementia, significant emphasis has been placed on the identification of modifiable risks of mild cognitive impairment (MCI). Research has indicated a correlation between exposure to air pollution and cognitive function in older adults. However, few studies have examined such an association among the MCI population inChina. We aimed to explore the association between air pollution exposure and MCI risk from the Hubei Memory and Aging Cohort Study. We measured four pollutants from 2015 to 2018, 3 years before the cognitive assessment of the participants. Logistic regression models were employed to calculate odds ratios (ORs) to assess the relationship between air pollutants and MCI risk. Among 4,205 older participants, the adjusted ORs of MCI risk for the highest quartile of PM2.5, PM10, O3, and SO2 were 1.90 (1.39, 2.62), 1.77 (1.28, 2.47), 0.56 (0.42, 0.75), and 1.18 (0.87, 1.61) respectively, compared with the lowest quartile. Stratified analyses indicated that such associations were found in both males and females, but were more significant in older participants. Our findings are consistent with the growing evidence suggesting that air pollution increases the risk of mild cognitive decline, which has considerable guiding significance for early intervention of dementia in the older population. Further studies in other populations and broader geographical areas are warranted to validate these findings.

A household survey of the prevalence of subjective cognitive decline and mild cognitive impairment among urban community-dwelling adults aged 30 to 65

While it is possible to detect cognitive decline before the age of 60, and there is a report indicating that certain cognitive abilities peak in one's 30s, the evidence regarding cognitive problems in populations younger than 65 years is scarce. This study aims to (1) determine the proportion of community-dwelling adults with different cognitive status, and (2) determine the prevalence of neuropsychiatric behaviors. A population-based survey was conducted in Chiang Mai, Thailand. Individuals aged 30 to 65 were recruited and assessed for demographic data, memory complaints, cognitive performance, and neuropsychiatric symptoms using self-reported questionnaires. In a total of 539 participants, 33.95% had mild cognitive impairment (MCI), 7.05% had subjective cognitive decline (SCD), and 52.50% had neuropsychiatric symptoms. The risk of MCI increased with age, and neuropsychiatric symptoms were significantly higher in those with MCI or SCD than in those without (p < 0.001). The most common complaints were sleep problems, anxiety, and irritability. Screening for MCI in adults aged < 65 years might be useful. However, further investigation on the appropriate age to screen and the program’s cost-effectiveness is suggested.

59 Mild cognitive impairment among older adults with diabetes: A pilot study in San Juan, Puerto Rico

OBJECTIVES/GOALS: Research on mild cognitive impairment (MCI) risk factors in type 2 diabetes mellitus (T2DM) is scarce; however, MCI is a concern in T2DM as it can adversely impact self-care behaviors. This study aims to estimate the proportion of MCI and describe its sociodemographic, clinical, psychosocial, and lifestyle characteristics in older adults with T2DM. METHODS/STUDY POPULATION: Cross-sectional pilot study of 60 adults (aged ≥50yrs) with a diagnosis of T2DM will be recruited at a diabetes center located in San Juan, Puerto Rico. Data on sociodemographic, clinical, psychosocial (depressive symptoms and social support), and lifestyle characteristics related to diabetes self-management (diabetes self-care activities and activities of daily living) will be collected through face-to-face interviews using validated questionnaires. Our primary outcome will be MCI assessed via the Spanish-language version of the Montreal Cognitive Assessment (MoCA-S). The proportion of adults with MCI (MoCA-S score&lt;26) will be estimated, and the sociodemographic, lifestyle, psychosocial, and clinical characteristics of older adults will be compared across MCI status using bivariate analysis. RESULTS/ANTICIPATED RESULTS: Expected results include an estimate of the proportion of MCI among older adults with T2DM, which we hypothesize will be higher in our study than in Puerto Rico’s older adult population (previously reported as 17%). Additionally, we will describe the sociodemographic, clinical, psychosocial, and lifestyle characteristics that significantly differ by MCI status in older adults with T2DM. We expect that those with MCI will be more likely to be females, have lower education and annual income, longer time with a diabetes diagnosis, worse psychosocial profiles (higher levels of depressive symptoms and lower levels of social support), and worse lifestyle profiles (poorer glycemic control and lower activities of daily living score) than those without MCI. DISCUSSION/SIGNIFICANCE: This pilot study is a first step to understanding MCI among older adults with T2DM in Puerto Rico, a Hispanic population with a higher prevalence of T2DM than their US non-Hispanic White counterparts. Its findings can guide the design and implementation of a larger epidemiological study aimed at understanding MCI risk factors among adults with T2DM.

Prediction model for mild cognitive impairment in patients with type 2 diabetes using the autonomic function test.

Type 2 diabetes mellitus (T2DM) is a risk factor for cognitive impairment, and reduced heart rate variability (HRV) has been correlated with cognitive impairment in elderly individuals. This study investigated risk factors and validated a predictive model for mild cognitive impairment (MCI) in patients with T2DM using an autonomic function test. Patients with T2DM, 50-85years of age, who attended the diabetes clinic at Gyeongsang National University Hospital between March 2018 and December 2019, were included. A total of 201 patients had been screened; we enrolled 124 patients according to the inclusion and exclusion criteria in this study. Cognitive function was assessed using the Montreal Cognitive Assessment-Korean version (MOCA-K); MCI was defined as a total MOCA-K score ≤ 23. Risk factors for MCI in patients with T2DM, including demographic- and diabetes-related factors, and autonomic function test results, were analyzed. Based on multivariate logistic regression, a nomogram was developed as a prediction model for MCI. Thirty-nine of 124 patients were diagnosed with MCI. Age, education, and decreased cardiovagal function were associated with a high risk for MCI, with cardiovagal function exerting the greatest influence. However, diabetes-related factors, such as glycemic control, duration of diabetes, or medications, were not associated with the risk for MCI. The nomogram demonstrated excellent discrimination (area under the curve, 0.832) and was well calibrated. Approximately one-third of patients had MCI; as such, carefully evaluating cognitive function in elderly T2DM patients with reduced HRV is important to prevent progression to dementia.

Resistance exercise effects on hippocampus subfield volumes and biomarkers of neuroplasticity and neuroinflammation in older adults with low and high risk of mild cognitive impairment: a randomized controlled trial.

Physical exercise is suggested to promote hippocampal neuroplasticity by increasing circulating neurotrophic and anti-inflammatory factors. Our aim was to explore the interplay between the effect of progressive resistance exercise on blood biomarker levels, hippocampal neurometabolite levels and hippocampal volume in older adults with a low compared to a high risk of mild cognitive impairment (MCI). Seventy apparently healthy male/female older adults (aged 60-85years old) were randomly allocated to a 12week lower limb progressive resistance or no intervention, stratified for low (< 26/30) or high (≥ 26/30) Montreal Cognitive Assessment (MoCA) score, indicating MCI risk. Outcome measures were blood levels of insulin-like growth factor-1 (IGF-1), interleukin-6 (IL-6) or kynurenine (KYN); hippocampal total and subfield volumes of the cornu ammonis 1 (CA1) and 4 (CA4), subiculum, presubiculum, and dentate gyrus measured with magnetic resonance imaging (MRI); and hippocampus neurometabolites including total N-acetylaspartate (NAA), myo-inositol (mIns), and total creatine (Cr) measured with proton magnetic resonance spectroscopy (1H-MRS). We evaluated the intervention effect, cognitive status effect, their interaction and the bivariate relationship between exercise-induced changes between the outcome measures. Higher kynurenine levels (p = 0.015) and lower subiculum volumes (p = 0.043) were found in older adults with high MCI risk compared to older adults with low MCI risk. Exercise-induced CA1 volume changes were negatively correlated with hippocampal tNAA/mIns level changes (r = -0.605, p = 0.006). This study provides valuable insight in the multifactorial processes related to resistance training in older adults with low or high MCI risk.

Chronic Non-cancer Pain and Associated Risks of Incident Mild Cognitive Impairment and Alzheimer's Disease and Related Dementias in Middle-Aged and Older Adults.

The goal of this study is to investigate the association between chronic non-cancer pain (CNCP) and mild cognitive impairment (MCI)/Alzheimer's disease and related dementias (ADRDs) development among adults aged ≥50 using administrative claims data from a national commercial health insurance company during 2007-2017. To reduce selection bias, propensity-score matching was applied to select comparable CNCP and non-CNCP patients. Time-dependent Cox proportional-hazards regressions were conducted to estimate the hazard ratios (HRs) of incident MCI/ADRDs. Of 170,900 patients with/without CNCP, 0.61% developed MCI and 2.33% had been diagnosed with ADRDs during the follow-up period. Controlling for potential confounders, CNCP patients had a 123% increase in MCI risk (HR = 2.23; 95% CI = 1.92-2.58) and a 44% increase in ADRDs risk (HR = 1.44; 95% CI = 1.34-1.54) relative to non-CNCP patients. CNCP is a risk factor for MCI/ADRDs. Promoting awareness and improving early CNCP diagnosis in middle-aged and older adults should be incorporated into cognitive impairment and dementia prevention.

Machine Learning Predicts Conversion from Normal Aging to Mild Cognitive Impairment Using Medical History, APOE Genotype, and Neuropsychological Assessment.

Identifying individuals at risk for mild cognitive impairment (MCI) is of urgent clinical need. This study aimed to determine whether machine learning approaches could harness longitudinal neuropsychology measures, medical data, and APOEɛ4 genotype to identify individuals at risk of MCI 1 to 2 years prior to diagnosis. Data from 676 individuals who participated in the 'APOE in the Predisposition to, Protection from and Prevention of Alzheimer's Disease' longitudinal study (N = 66 who converted to MCI) were utilized in supervised machine learning algorithms to predict conversion to MCI. A random forest algorithm predicted conversion 1-2 years prior to diagnosis with 97% accuracy (p = 0.0026). The global minima (each individual's lowest score) of memory measures from the 'Rey Auditory Verbal Learning Test' and the 'Selective Reminding Test' were the strongest predictors. This study demonstrates the feasibility of using machine learning to identify individuals likely to convert from normal cognition to MCI.

Predictive model for identifying mild cognitive impairment in patients with type 2 diabetes mellitus: A CHAID decision tree analysis.

As the population ages, mild cognitive impairment (MCI) and type 2 diabetes mellitus (T2DM) become common conditions that often coexist. Evidence has shown that MCI could lead to reduced treatment compliance, medication management, and self-care ability in T2DM patients. Therefore, early identification of those with increased risk of MCI is crucial from a preventive perspective. Given the growing utilization of decision trees in prediction of health-related outcomes, this study aimed to identify MCI in T2DM patients using the decision tree approach. This hospital-based case-control study was performed in the Endocrinology Department of Xiangya Hospital affiliated to Central South University between March 2021 and December 2022. MCI was defined based on the Petersen criteria. Demographic characteristics, lifestyle factors, and T2DM-related information were collected. The study sample was randomly divided into the training and validation sets in a 7:3 ratio. Univariate and multivariate analyses were performed, and a decision tree model was established using the chi-square automatic interaction detection (CHAID) algorithm to identify key predictor variables associated with MCI. The area under the curve (AUC) value was used to evaluate the performance of the established decision tree model, and the performance of multivariate regression model was also evaluated for comparison. A total of 1001 participants (705 in the training set and 296 in the validation set) were included in this study. The mean age of participants in the training and validation sets was 60.2 ± 10.3 and 60.4 ± 9.5 years, respectively. There were no significant differences in the characteristics between the training and validation sets (p>.05). The CHAID decision tree analysis identified six key predictor variables associated with MCI, including age, educational level, household income, regular physical activity, diabetic nephropathy, and diabetic retinopathy. The established decision tree model had 15 nodes composed of 4 layers, and age is the most significant predictor variable. It performed well (AUC=.75 [95% confidence interval (CI): .71-.78] and .67 [95% CI: .61-.74] in the training and validation sets, respectively), was internally validated, and had comparable predictive value compared to the multivariate logistic regression model (AUC=.76 [95% CI: .72-.80] and .69 [95% CI: .62-.75] in the training and validation sets, respectively). The established decision tree model based on age, educational level, household income, regular physical activity, diabetic nephropathy, and diabetic retinopathy performed well with comparable predictive value compared to the multivariate logistic regression model and was internally validated. Due to its superior classification accuracy and simple presentation as well as interpretation of collected data, the decision tree model is more recommended for the prediction of MCI in T2DM patients in clinical practice.

Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool.

Numerous evidence suggests that diabetes increases the risk of cognitive impairment. This study aimed to develop and validate a multivariable risk score model to identify mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). This cross-sectional study included 1256 inpatients (age: 57.5 ± 11.2 years) with T2DM in a tertiary care hospital in China. MCI was diagnosed according to the criteria recommended by the National Institute on Aging-Alzheimer's Association Workgroup, and a MoCA score of 19-25 indicated MCI. Participants were randomly allocated into the derivation and validation sets at 7:3 ratio. Logistic regression models were used to identify predictors for MCI in the derivation set. A scoring system based on the predictors' beta coefficient was developed. Predictive ability of the risk score was tested by discrimination and calibration methods. Totally 880 (285 with MCI, 32.4%) and 376 (167 with MCI, 33.8%) patients were allocated in the derivation and validation set, respectively. Age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease were identified as predictors for MCI and constituted the risk score. The AUCs (95% CI) of the risk score were 0.751 (0.717, 0.784) in derivation set and 0.776 (0.727, 0.824) in validation set. The risk score showed good apparent calibration of observed and predicted MCI probabilities and was capable of stratifying individuals into 3 risk categories by two cut-off points (low risk: ≤ 3, medium risk: 4-13, and high risk ≥ 14). The risk score based on age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease can effectively assess MCI risk in adults with T2DM at different age. It can serve as a practical prescreening tool for early detection of MCI in daily diabetes care.