Midlife stress-related exhaustion and dementia incidence: a longitudinal study over 50 years in women.

BACKGROUNDS: Cognitive problems are common symptoms among individuals with stress-related exhaustion. It is still unknown whether these individuals are at a higher risk of developing dementia later. This study aims to examine the relationship between midlife stress-related exhaustion and dementia incidence. METHODS: A population sample of 777 women (aged 38, 46, 50 and 54 years) without dementia at baseline was followed over 50 years, from 1968 to 2019. Stress-related exhaustion was based on information from the psychiatric examination in 1968/69. Information on dementia incidence between 1968 and 2019 was obtained from neuropsychiatric examinations, key-informant interviews, and hospital registry. Dementia was diagnosed according to the DSM-III-R criteria. A subgroup of non-demented women (n = 284) was examined for cognitive functions by the Gottfries-Bråne-Steen scale 24 years after baseline. RESULTS: Stress-related exhaustion in midlife was associated with higher risk for development of dementia before age 75 (Hazard ratio and 95% confidence interval: 2.95 and 1.35-6.44). The association remained after adjustment for age, major depression, and anxiety disorder. Mean age of dementia onset was younger for women with stress-related exhaustion than women without stress (mean ± SD, 76 ± 9 vs. 82 ± 8 . p = 0.009). Women with stress-related exhaustion in midlife still showed more cognitive impairments 24 years later compared with women without stress (Odds ratio and 95% confidence interval: 2.64 and 1.15-6.06). CONCLUSIONS: We found that women with stress-related exhaustion in midlife were at a higher risk to develop dementia at relatively younger age. These women showed persistently lower cognitive functions over years even without dementia. Present study results need to be interpreted with caution due to small sample size and should be confirmed in future studies with larger sample size. Our study findings may imply the importance of long-term follow-up regarding cognitive function among individuals with stress-related exhaustion.

Agreement between Clinical Frailty Scale-scores based on information from patient interviews and Clinical Frailty Scale-scores based on information from medical records - a cross sectional study.

INTRODUCTION: Frailty is an age-related condition with increased risk for adverse health outcomes. Assessing frailty according to the Clinical Frailty Scale (CFS) based on data from medical records is useful for previously unassessed patients, but the validity of such scores in exclusively geriatric populations and in patients with dementia is relatively unknown. METHODS: Patients admitted for the first time to one of two geriatric wards at Örebro University hospital between January 1st - December 31st, 2021, were included in this study if they had been appointed a CFS-score by anamnestic interview (CFSI) at admission. CFS scores based on medical records (CFSR) were appointed by a single medical student, who was blinded to the CFSI score. Score-agreement was evaluated with quadratic weighted Cohen's kappa (κ). RESULTS: In total, 145 patients between the age of 55-101 were included in the study. The CFSR and CFSI scores agreed perfectly in 102 cases (0.7, 95% CI 0.65-0.77). There was no significant difference regarding age, sex, comorbidity, or number of patients diagnosed with dementia between the patients with complete agreement and the patients whose scores did not agree. Agreement between the scores was substantial, κ = 0.66, 95% CI 0.53-0.80. CONCLUSIONS: CFS scores based on information from medical records can be generated with substantial agreement to CFS scores based on in-person anamnestic interviews. A dementia diagnosis does not influence the agreement between the scores. Therefore, these scores are a useful tool for assessing frailty in geriatric patients who previously lack a frailty assessment, both in clinical practice and future research. The results support previous findings, but larger studies are warranted.

Nutritional status, dietary quality and eating disturbance issues among people with dementia in Vietnam: evidence of a cross-sectional study.

BACKGROUND: Due to cognitive impairments, people with dementia (PWD) often have difficulties in eating and drinking. This study aimed to assess the nutritional status, dietary quality and eating disturbance issues among PWD in Vietnam. METHODS: We conducted a cross-sectional study at the Vietnamese National Geriatric Hospital from April to December 2022. We used Mini-Mental State Exam (MMSE) to classify the severity levels of dementia. Mini Nutritional Assessment (MNA), 24-hour recall, eating disturbance questionnaires, and anthropometric indicators were used to evaluate the nutritional status, dietary quality, and eating disorders of study subjects. RESULTS: Overall, among 63 study participants, 74.6 per cent of PWD were at risk of or having malnutrition. By dementia classification according to MMSE scale, people with moderate and severe dementia accounted for 53.3 per cent of those who met the recommended energy levels, compared to 42.4 per cent of people with mild dementia and normal people. In the above two groups, around three per cent of participants reached the recommended amount of fibre. Calcium (50-70%), vitamin A (80-90%), and D (90%) were found to be the most severe deficiency forms of minerals and vitamins in both male and female participants. The majority of participants (90.5%) had at least one form of eating disorders with the most frequent issue being appetite changes (76.2%) and swallowing issues (50.8%). CONCLUSIONS: PWD in our sample frequently experienced malnutrition, a lack of essential nutrients, difficulties swallowing, changes in eating habits and appetite. It is neccesary to early screen and assess nutritional status and swallowing disturbance in PWD, and instruct their caregivers to prepare nutritious meals for them.

Self-Explainable Graph Neural Network for Alzheimer Disease and Related Dementias Risk Prediction: Algorithm Development and Validation Study.

BACKGROUND: Alzheimer disease and related dementias (ADRD) rank as the sixth leading cause of death in the United States, underlining the importance of accurate ADRD risk prediction. While recent advancements in ADRD risk prediction have primarily relied on imaging analysis, not all patients undergo medical imaging before an ADRD diagnosis. Merging machine learning with claims data can reveal additional risk factors and uncover interconnections among diverse medical codes. OBJECTIVE: The study aims to use graph neural networks (GNNs) with claim data for ADRD risk prediction. Addressing the lack of human-interpretable reasons behind these predictions, we introduce an innovative, self-explainable method to evaluate relationship importance and its influence on ADRD risk prediction. METHODS: We used a variationally regularized encoder-decoder GNN (variational GNN [VGNN]) integrated with our proposed relation importance method for estimating ADRD likelihood. This self-explainable method can provide a feature-important explanation in the context of ADRD risk prediction, leveraging relational information within a graph. Three scenarios with 1-year, 2-year, and 3-year prediction windows were created to assess the model's efficiency, respectively. Random forest (RF) and light gradient boost machine (LGBM) were used as baselines. By using this method, we further clarify the key relationships for ADRD risk prediction. RESULTS: In scenario 1, the VGNN model showed area under the receiver operating characteristic (AUROC) scores of 0.7272 and 0.7480 for the small subset and the matched cohort data set. It outperforms RF and LGBM by 10.6% and 9.1%, respectively, on average. In scenario 2, it achieved AUROC scores of 0.7125 and 0.7281, surpassing the other models by 10.5% and 8.9%, respectively. Similarly, in scenario 3, AUROC scores of 0.7001 and 0.7187 were obtained, exceeding 10.1% and 8.5% than the baseline models, respectively. These results clearly demonstrate the significant superiority of the graph-based approach over the tree-based models (RF and LGBM) in predicting ADRD. Furthermore, the integration of the VGNN model and our relation importance interpretation could provide valuable insight into paired factors that may contribute to or delay ADRD progression. CONCLUSIONS: Using our innovative self-explainable method with claims data enhances ADRD risk prediction and provides insights into the impact of interconnected medical code relationships. This methodology not only enables ADRD risk modeling but also shows potential for other image analysis predictions using claims data.

Exploring the impacts of risk factors on mortality patterns of global Alzheimer's disease and related dementias from 1990 to 2021.

Alzheimer's Disease and Related Dementias (ADRD) affect millions of people worldwide, with mortality rates influenced by several risk factors and exhibiting significant heterogeneity across geographical regions. This study aimed to investigate the impact of risk factors on global ADRD mortality patterns from 1990 to 2021, utilizing clustering and modeling techniques. Data on ADRD mortality rates, cardiovascular disease, and diabetes prevalence were obtained for 204 countries from the GBD platform. Additional variables such as HDI, life expectancy, alcohol consumption, and tobacco use prevalence were sourced from the UNDP and WHO. All the data were extracted for men, women, and the overall population. Longitudinal k-means clustering and generalized estimating equations were applied for data analysis. The findings revealed that cardiovascular disease had significant positive effects of 1.84, 3.94, and 4.70 on men, women, and the overall ADRD mortality rates, respectively. Tobacco showed positive effects of 0.92, 0.13, and 0.39, while alcohol consumption had negative effects of - 0.59, - 9.92, and - 2.32, on men, women, and the overall ADRD mortality rates, respectively. The countries were classified into five distinct subgroups. Overall, cardiovascular disease and tobacco use were associated with increased ADRD mortality rates, while moderate alcohol consumption exhibited a protective effect. Notably, tobacco use showed a protective effect in cluster A, as did alcohol consumption in cluster B. The effects of risk factors on ADRD mortality rates varied among the clusters, highlighting the need for further investigation into the underlying causal factors.

Analysis of eligibility criteria in Alzheimer's and related dementias clinical trials.

Overly restrictive clinical trial eligibility criteria can reduce generalizability, slow enrollment, and disproportionately exclude historically underrepresented populations. The eligibility criteria for 196 Alzheimer's Disease and Related Dementias (AD/ADRD) trials funded by the National Institute on Aging were analyzed to identify common criteria and their potential to disproportionately exclude participants by race/ethnicity. The trials were categorized by type (48 Phase I/II pharmacological, 7 Phase III/IV pharmacological, 128 non-pharmacological, 7 diagnostic, and 6 neuropsychiatric) and target population (51 AD/ADRD, 58 Mild Cognitive Impairment, 25 at-risk, and 62 cognitively normal). Eligibility criteria were coded into the following categories: Medical, Neurologic, Psychiatric, and Procedural. A literature search was conducted to describe the prevalence of disparities for eligibility criteria for African Americans/Black (AA/B), Hispanic/Latino (H/L), American Indian/Alaska Native (AI/AN) and Native Hawaiian/Pacific Islander (NH/PI) populations. The trials had a median of 15 criteria. The most frequent criterion were age cutoffs (87% of trials), specified neurologic (65%), and psychiatric disorders (61%). Underrepresented groups could be disproportionately excluded by 16 eligibility categories; 42% of trials specified English-speakers only in their criteria. Most trials (82%) contain poorly operationalized criteria (i.e., criteria not well defined that can have multiple interpretations/means of implementation) and criteria that may reduce racial/ethnic enrollment diversity.

Benzodiazepine use in relation to long-term dementia risk and imaging markers of neurodegeneration: a population-based study.

BACKGROUND: Benzodiazepine use is common, particularly in older adults. Benzodiazepines have well-established acute adverse effects on cognition, but long-term effects on neurodegeneration and dementia risk remain uncertain. METHODS: We included 5443 cognitively healthy (MMSE ≥ 26) participants from the population-based Rotterdam Study (57.4% women, mean age 70.6 years). Benzodiazepine use from 1991 until baseline (2005-2008) was derived from pharmacy dispensing records, from which we determined drug type and cumulative dose. Benzodiazepine use was defined as prescription of anxiolytics (ATC-code: N05BA) or sedative-hypnotics (ATC-code: N05CD) between inception of pharmacy records and study baseline. Cumulative dose was calculated as the sum of the defined daily doses for all prescriptions. We determined the association with dementia risk until 2020 using Cox regression. Among 4836 participants with repeated brain MRI, we further determined the association of benzodiazepine use with changes in neuroimaging markers using linear mixed models. RESULTS: Of all 5443 participants, 2697 (49.5%) had used benzodiazepines at any time in the 15 years preceding baseline, of whom 1263 (46.8%) used anxiolytics, 530 (19.7%) sedative-hypnotics, and 904 (33.5%) used both; 345 (12.8%) participants were still using at baseline assessment. During a mean follow-up of 11.2 years, 726 participants (13.3%) developed dementia. Overall, use of benzodiazepines was not associated with dementia risk compared to never use (HR [95% CI]: 1.06 [0.90-1.25]), irrespective of cumulative dose. Risk estimates were somewhat higher for any use of anxiolytics than for sedative-hypnotics (HR 1.17 [0.96-1.41] vs 0.92 [0.70-1.21]), with strongest associations for high cumulative dose of anxiolytics (HR [95% CI] 1.33 [1.04-1.71]). In imaging analyses, current use of benzodiazepine was associated cross-sectionally with lower brain volumes of the hippocampus, amygdala, and thalamus and longitudinally with accelerated volume loss of the hippocampus and to a lesser extent amygdala. However, imaging findings did not differ by type of benzodiazepines or cumulative dose. CONCLUSIONS: In this population-based sample of cognitively healthy adults, overall use of benzodiazepines was not associated with increased dementia risk, but potential class-dependent adverse effects and associations with subclinical markers of neurodegeneration may warrant further investigation.

Subjective cognitive concerns, APOE ε4, PTSD symptoms, and risk for dementia among older veterans.

BACKGROUND: Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups. METHODS: Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older. RESULTS: PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18). CONCLUSIONS: The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.

Exposure to source-specific air pollution in residential areas and its association with dementia incidence: a cohort study in Northern Sweden.

The aim of this study was to investigate the relationship between source-specific ambient particulate air pollution concentrations and the incidence of dementia. The study encompassed 70,057 participants from the Västerbotten intervention program cohort in Northern Sweden with a median age of 40 years at baseline. High-resolution dispersion models were employed to estimate source-specific particulate matter (PM) concentrations, such as PM10 and PM2.5 from traffic, exhaust, and biomass (mainly wood) burning, at the residential addresses of each participant. Cox regression models, adjusted for potential confounding factors, were used for the assessment. Over 884,847 person-years of follow-up, 409 incident dementia cases, identified through national registers, were observed. The study population's average exposure to annual mean total PM10 and PM2.5 lag 1-5 years was 9.50 µg/m3 and 5.61 µg/m3, respectively. Increased risks were identified for PM10-Traffic (35% [95% CI 0-82%]) and PM2.5-Exhaust (33% [95% CI - 2 to 79%]) in the second exposure tertile for lag 1-5 years, although no such risks were observed in the third tertile. Interestingly, a negative association was observed between PM2.5-Wood burning and the risk of dementia. In summary, this register-based study did not conclusively establish a strong association between air pollution exposure and the incidence of dementia. While some evidence indicated elevated risks for PM10-Traffic and PM2.5-Exhaust, and conversely, a negative association for PM2.5-Wood burning, no clear exposure-response relationships were evident.

Association between depression and incident dementia: Longitudinal findings from the share study.

BACKGROUND: The association between depression and dementia is still unclear, particularly regarding depression as a potential risk factor preceding dementia. Therefore, we aimed to verify if the presence of depression at baseline may increase the risk of dementia and cognitive impairment during 15 years of follow-up in the SHARE (Survey of Health, Aging and Retirement in Europe) study. METHODS: Depressive symptoms were defined using the EURO-D, with a score ≥4 indicative of depression. Incident dementia was ascertained using self-reported data and caregivers' information, cognitive impairment using objective cognitive tests. Cox regression analysis, adjusted for 10 baseline confounders, was run and hazard ratios (HRs), with their 95% confidence intervals, were estimated. RESULTS: In total 22,789 participants were included in the present analysis (mean age 64.2 years) and were predominantly female. The prevalence of depression at baseline was 24.9%. Over 15 years of follow-up, the onset of dementia occurred a median 2 years earlier in people with depression compared to those without. Depression at the baseline significantly increased the risk of dementia in the overall sample (HR = 1.74; 95% CI: 1.54-1.95) and the risk of cognitive impairment (HR = 1.15; 95% CI: 1.06-1.25). For dementia, the association was stronger in people less than 60 years (HR = 2.07; 95% CI: 1.42-3.02) than in participants aged ≥80 years (HR = 1.47; 95% CI: 1.14-1.91). A similar trend was observed for cognitive impairment. Among the single items of the EURO-D, loss of concentration was the strongest individual variable predicting the onset of dementia. CONCLUSIONS: Depression increased the risk of dementia and cognitive impairment, particularly in younger adults, whereas loss of concentration was the strongest individual predicting variable of dementia. These findings demonstrate the need for early detection of depression for preventing future cognitive worsening.

Dementia, comorbidity and multimorbidity.

Many people living with dementia will also have multimorbidity comprising several other intercurrent, long-term and comorbid conditions. This article examines the relationship between such conditions in the context of dementia, giving an overview of the literature, including prevalence and some of the common conditions that can coexist with dementia. The theory and evidence-base will be tied together using a case study approach, to illustrate the complexity of managing comorbid conditions and multimorbidity alongside dementia, and explore some of the approaches that can be used by community nurses to support the overall health of people living with dementia that they work with.