Association of Education With Dementia Incidence Stratified by Ethnicity and Nativity in a Cohort of Older Asian American Individuals

Associations of modifiable dementia risk factors with dementia and cognitive decline: evidence from three prospective cohorts

Objective

This study aims to assess the relationship between modifiable dementia risk factors and both dementia and cognitive decline.

Methods

Data were obtained from the Health and Retirement Study (HRS) [2008-2020], the China Health and Retirement Longitudinal Study (CHARLS) [2011-2020], and the English Longitudinal Study of Ageing (ELSA) [2010-2020]. After adjusting for confounding factors, multivariable logistic regression was utilized to analyze the relationship between modifiable dementia risk factors and dementia, while multivariable linear regression was employed to examine the relationship between these risk factors and cognitive decline. Additionally, the Cox proportional hazards model was used to assess the relationship between the number of risk factor events, clusters, and dementia risk.

Results

A total of 30,113 participants from HRS, CHARLS, and ELSA were included (44.6% male, mean age 66.04 years), with an average follow-up period of 7.29 years. A low education level was significantly associated with an increased risk of dementia and accelerated cognitive decline (Overall, OR = 2.93, 95% CI: 2.70-3.18; Overall, β = -0.25, 95% CI: -0.60 to-0.55). The presence of multiple dementia risk factors correlated with a higher dementia risk; Specifically, compared with more than 5 risk factor events, both having no dementia risk factors and having only one dementia risk factor were associated with a significantly lower risk of dementia (Overall, HR = 0.15, 95% CI: 0.11-0.22, HR = 0.22, 95% CI: 0.18-0.25). Compared to the group with no coexistence of risk factors, the clusters of excessive alcohol, diabetes, vision loss, and hearing loss (HR = 4.11; 95% CI = 3.42-4.95; p < 0.001); excessive alcohol, vision loss, smoking, and hearing loss (HR = 5.18; 95% CI = 4.30-6.23; p < 0.001); and excessive alcohol, obesity, diabetes, and smoking (HR = 5.96; 95% CI = 5.11-6.95; p < 0.001) were most strongly associated with dementia risk.

Conclusion

Among the 11 risk factors, educational attainment has the greatest impact on dementia risk and cognitive decline. A dose-response relationship exists between the number of modifiable risk factor events and dementia risk. The coexistence of multiple risk factors is associated with dementia risk, and these associations vary by risk factor cluster.

Impact of Anticholinergic Burden and Clinical-Demographic Characteristics on Incident Dementia in Parkinson Disease

PURPOSE

Anticholinergic medication use measured via the Anticholinergic Cognitive Burden (ACB) scale has been associated with an increased dementia incidence in older adults but has not been explored specifically for Parkinson disease dementia (PDD). We used adjusted Cox models to estimate the risk of incident PDD associated with demographic factors, clinical characteristics, and time-varying total ACB in a longitudinal, deeply-phenotyped prospective PD cohort.

MAJOR FINDINGS

56.5% of study participants were taking ACB-scale drugs at enrollment. Increasing age, motor symptom burden and psychosis were associated with PDD risk. Female sex and educational achievement were protective against PDD. ACB categories were not associated with PDD overall, but depression and impulse control disorder were strongly associated with PDD in a subsample with high baseline ACB.

CONCLUSIONS

Patient and clinical factors modify PDD risk. PD drug safety and drug-disease interaction studies may require considering multiple mechanisms and including dose-based, prospectively acquired medication exposure measures.

Brain health equity and the influence of social determinants across the life cycle

Social determinants of health are social, economic and environmental factors known to influence health and development of infants, children and adults. Advancing equity in brain health relies upon interdisciplinary collaboration and recognition of the impact of social determinants on brain health through the lifespan and across generations. Critical periods of fetal, infant and early childhood development encompass intrinsic genetic and extrinsic environmental influences with complex gene-environment interactions. This review discusses the influence of social determinants on the continuum of brain health from preconception and pregnancy health, through fetal, infant and childhood neurodevelopment into adulthood. Opportunities for intervention to address the social determinants of brain health across the life cycle are highlighted.

Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions

Background

Social determinants of health (SDoH), such as socioeconomics and neighborhoods, strongly influence health outcomes. However, the current state of standardized SDoH data in electronic health records (EHRs) is lacking, a significant barrier to research and care quality.

Methods

We conducted a PubMed search using "SDOH" and "EHR" Medical Subject Headings terms, analyzing included articles across five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

Of 685 articles identified, 324 underwent full review. Key findings include implementation of tailored screening instruments, census and claims data linkage for contextual SDoH profiles, NLP systems extracting SDoH from notes, associations between SDoH and healthcare utilization and chronic disease control, and integrated care management programs. However, variability across data sources, tools, and outcomes underscores the need for standardization.

Discussion

Despite progress in identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical for SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately, widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Assessing Risk Factors for Cognitive Decline Using Electronic Health Record Data: A Scoping Review

Background

The data and information contained within electronic health records (EHR) provide a rich, diverse, longitudinal view of real-world patient histories, offering valuable opportunities to study antecedent risk factors for cognitive decline. However, the extent to which such records' data have been utilized to elucidate the risk factors of cognitive decline remains unclear.

Methods

A scoping review was conducted following the PRISMA guideline, examining articles published between January 2010 and April 2023, from PubMed, Web of Science, and CINAHL. Inclusion criteria focused on studies using EHR to investigate risk factors for cognitive decline. Each article was screened by at least two reviewers. Data elements were manually extracted based on a predefined schema. The studied risk factors were classified into categories, and a research gap was identified.

Results

From 1,593 articles identified, 80 were selected. The majority (87.5%) were retrospective cohort studies, with 66.3% using datasets of over 10,000 patients, predominantly from the US or UK. Analysis showed that 48.8% of studies addressed medical conditions, 31.3% focused on medical interventions, and 17.5% on lifestyle, socioeconomic status, and environmental factors. Most studies on medical conditions were linked to an increased risk of cognitive decline, whereas medical interventions addressing these conditions often reduced the risk.

Conclusions

EHR data significantly enhanced our understanding of medical conditions, interventions, lifestyle, socioeconomic status, and environmental factors related to the risk of cognitive decline.

Shared whole environmental etiology between Alzheimer's disease and age-related macular degeneration

The comorbidity of Alzheimer's disease (AD) and age-related macular degeneration (AMD) has been established in clinical and genetic studies. There is growing interest in determining the shared environmental factors associated with both conditions. Recent advancements in record linkage techniques enable us to identify the contributing factors to AD and AMD from a wide range of variables. As such, we first constructed a knowledge graph based on the literature, which included all statistically significant risk factors for AD and AMD. An environment-wide association study (EWAS) was conducted to assess the contribution of various environmental factors to the comorbidity of AD and AMD based on the UK biobank. Based on the conditional Q-Q plots and Bayesian algorithm, several shared environmental factors were identified, which could be categorized into the domains of health condition, biological sample parameters, body index, and attendance availability. Finally, we generated a shared etiology landscape for AD and AMD by combining existing knowledge with our novel findings.

A systematic review/meta-analysis of prevalence and incidence rates illustrates systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research

We investigate Alzheimer's disease and related dementia (ADRD) prevalence, incidence rate, and risk factors in individuals racialized as Asian and/or Asian-American and assess sample representation. Prevalence, incidence rate, risk factors, and heterogeneity of samples were assessed. Random-effects meta-analysis was conducted, generating pooled estimates. Of 920 records across 14 databases, 45 studies were included. Individuals racialized as Asian and/or Asian-American were mainly from Eastern and Southern Asia, had higher education, and constituted a smaller sample relative to non-Hispanic white cohorts. The average prevalence was 10.9%, ranging from 0.4% to 46%. The average incidence rate was 20.03 (12.01-33.8) per 1000 person-years with a range of 75.19-13.59 (12.89-14.33). Risk factors included physiological, genetic, psychological, behavioral, and social factors. This review underscores the systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research and the need for inclusive approaches accounting for culture, language, and immigration status. HIGHLIGHTS: There is considerable heterogeneity in the prevalence of ADRD among studies of Asian-Americans. There is limited data on group-specific risk factors for ADRD among Asian-Americans. The average prevalence of (ADRD) among Asian-Americans was found to be 7.4%, with a wide range from 0.5% to 46%.

Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development

INTRODUCTION

The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention.

METHODS

This study included 2,288 participants with normal cognitive function from the Ma'anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level.

RESULTS

The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773-0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults.

CONCLUSION

The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings.

Deriving life-course residential histories in brain bank cohorts: A feasibility study

INTRODUCTION

The exposome is theorized to interact with biological mechanisms to influence risk for Alzheimer's disease but is not well-integrated into existing Alzheimer's Disease Research Center (ADRC) brain bank data collection.

METHODS

We apply public data tracing, an iterative, dual abstraction and validation process rooted in rigorous historic archival methods, to develop life-course residential histories for 1254 ADRC decedents.

RESULTS

The median percentage of the life course with an address is 78.1% (IQR 24.9); 56.5% of the sample has an address for at least 75% of their life course. Archivists had 89.7% agreement at the address level. This method matched current residential survey methodology 97.4% on average.

DISCUSSION

This novel method demonstrates feasibility, reproducibility, and rigor for historic data collection. To our knowledge, this is the first study to show that public data tracing methods for brain bank decedent residential history development can be used to better integrate the social exposome with biobank specimens.

HIGHLIGHTS

Public data tracing compares favorably to survey-based residential history. Public data tracing is feasible and reproducible between archivists. Archivists achieved 89.7% agreement at the address level. This method identifies residences for nearly 80% of life-years, on average. This novel method enables brain banks to add social characterizations.

Neighborhood disadvantage reduces cognitive reserve independent of neuropathologic change

INTRODUCTION

Individuals in socioeconomically disadvantaged neighborhoods exhibit increased risk for impaired cognitive function. Whether this association relates to the major dementia-related neuropathologies is unknown.

METHODS

This cross-sectional study included 469 autopsy cases from 2011 to 2023. The relationships between neighborhood disadvantage measured by Area Deprivation Index (ADI) percentiles categorized into tertiles, cognition evaluated by the last Mini-Mental State Examination (MMSE) scores before death, and 10 dementia-associated proteinopathies and cerebrovascular disease were assessed using regression analyses.

RESULTS

Higher ADI was significantly associated with lower MMSE score. This was mitigated by increasing years of education. ADI was not associated with an increase in dementia-associated neuropathologic change. Moreover, the significant association between ADI and cognition remained even after controlling for changes in major dementia-associated proteinopathies or cerebrovascular disease.

DISCUSSION

Neighborhood disadvantage appears to be associated with decreased cognitive reserve. This association is modified by education but is independent of the major dementia-associated neuropathologies.

Disparities in neighbourhood characteristics and 10-year dementia risk by nativity status

AIMS

Prior research indicates that neighbourhood disadvantage increases dementia risk. There is, however, inconclusive evidence on the relationship between nativity and cognitive impairment. To our knowledge, our study is the first to analyse how nativity and neighbourhood interact to influence dementia risk.

METHODS

Ten years of prospective cohort data (2011-2020) were retrieved from the National Health and Aging Trends Study, a nationally representative sample of 5,362 U.S. older adults aged 65+. Cox regression analysed time to dementia diagnosis using nativity status (foreign- or native-born) and composite scores for neighbourhood physical disorder (litter, graffiti and vacancies) and social cohesion (know, help and trust each other), after applying sampling weights and imputing missing data.

RESULTS

In a weighted sample representing 26.9 million older adults, about 9.5% (n = 2.5 million) identified as foreign-born and 24.4% (n = 6.5 million) had an incident dementia diagnosis. Average baseline neighbourhood physical disorder was 0.19 (range 0-9), and baseline social cohesion was 4.28 (range 0-6). Baseline neighbourhood physical disorder was significantly higher among foreign-born (mean = 0.28) compared to native-born (mean = 0.18) older adults (t = -2.4, p = .02). Baseline neighbourhood social cohesion was significantly lower for foreign-born (mean = 3.57) compared to native-born (mean = 4.33) older adults (t = 5.5, p < .001). After adjusting for sociodemographic, health and neighbourhood variables, foreign-born older adults had a 51% significantly higher dementia risk (adjusted hazard ratio = 1.51, 95% CI = 1.19-1.90, p < .01). There were no significant interactions for nativity with neighbourhood physical disorder or social cohesion.

CONCLUSIONS

Our findings suggest that foreign-born older adults have higher neighbourhood physical disorder and lower social cohesion compared to native-born older adults. Despite the higher dementia risk, we observed for foreign-born older adults, and this relationship was not moderated by either neighbourhood physical disorder or social cohesion. Further research is needed to understand what factors are contributing to elevated dementia risk among foreign-born older adults.

Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions

Background

Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality.

Methods

We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes.

Discussion

Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Sarcopenia using muscle mass prediction model and cognitive impairment: A longitudinal analysis from the English longitudinal study on ageing

BACKGROUND

Literature on the association between sarcopenia and cognitive impairment is largely unclear and mainly limited to non-European populations. Therefore, the aim of this study is to explore if the presence of sarcopenia at the baseline could increase the risk of cognitive impairment in a large cohort of older people participating to the English Longitudinal Study of Ageing (ELSA), over ten years of follow-up.

METHODS

Sarcopenia was diagnosed as having low handgrip strength and low skeletal muscle mass index at the baseline, using a muscle mass prediction model; cognitive function was evaluated in the ELSA through several tests. The results are reported in the whole sample adjusted for potential baseline confounders and after matching sarcopenic and non-sarcopenic participants with a propensity score.

RESULTS

2738 people (mean age: 68.7 years, 54.4% males) were included. During the ten years of follow-up, sarcopenia was associated with significantly lower scores in memory (p < 0.001), verbal fluency (p < 0.001), immediate word recall (p <0.001), delayed word recall (p = 0.018), and in recall summary score (p < 0.001). After adjusting for eight potential confounders, the presence of sarcopenia was significantly associated with poor verbal fluency (odds ratio, OR= 1.417, 95% confidence intervals, CI= 1.181-1.700) and in propensity-score matched analyses (OR=1.272, 95%CI= 1.071- 1.511).

CONCLUSIONS AND IMPLICATIONS

Sarcopenia was found to be associated with a significantly higher incidence of poor cognitive status in a large population of elderly people followed up for 10 years, suggesting it may be an important potential risk factor for dementia.

Socioeconomic Status Disparities in Cognitive and Physical Functional Impairment among Older Adults: Comparison of Asians with other Major Racial/Ethnic Groups

This study investigated to what extent socioeconomic status (SES) disparity associates with cognitive and physical impairment within older Asian Americans in comparison with other races/ethnicities. Data were from the National Health and Nutrition Examination Survey 2011-2018 that included 3,297 White, 1,755 Black, 1,708 Hispanic, and 730 Asian Americans aged ≥ 60. Physical functioning was measured by activities of daily living (ADL) or instrumental activities of daily living (IADL). Memory and language fluency were evaluated using the Alzheimer's Disease Word List Memory Task and Animal Fluency Tests, respectively. Multivariate logistic regressions were conducted to investigate the association between SES and physical and cognitive impairment within racial/ethnic groups, and seemingly unrelated regressions compared coefficients across subgroups. Asians with ≤ high school education had the highest prevalence of age- and sex-adjusted memory impairment among all races/ethnicities, while no difference was observed for those with > high school education. ADL/IADL disability odds did not differ between Asians and Whites, but Asians were more likely to exhibit impaired verbal fluency. Education disparity for ADL disability (OR, 3.40; 95% CI, 2.20-5.25) and memory impairment (OR, 11.57; 95% CI, 6.59-20.31) were largest among Asians compared to Whites, Blacks, and Hispanics. Income disparity for function impairment showed no significant difference across racial/ethnic groups (all P > 0.05). Asians experienced the highest burden of physical functioning and memory impairment due to education disparity. Efforts should focus on strengthening research infrastructure and creating targeted programs and services to improve cognitive and physical health for racially/ethnically underrepresented older adults with lower education attainment.