National Estimates of Incremental Work Absenteeism Costs Associated With Adult Children of Parents With Alzheimer's Disease and Related Dementias

OBJECTIVE

More than half of primary caregivers for ADRD patients are adult children, yet there is little empirical evidence on how caring for parents with ADRD affects their employment. Using a nationally representative dataset, this study aimed to estimate incremental work absenteeism costs for adult children of parents with ADRD.

DESIGN, SETTING, AND PARTICIPANTS

The study used the data from the 2015-2021 Medical Expenditure Panel Survey (MEPS). Multivariate regressions and two-part models were employed to estimate the incremental work absenteeism costs among adult children aged 40 to 64 who had at least one parent diagnosed with ADRD, compared with those who did not have ADRD parents.

MEASUREMENTS

The incremental work absenteeism costs due to caregiving for adult children with ADRD parents was a cumulated estimation of labor productivity cost at three stages: (1) the likelihood of not working due to unemployment, (2) the likelihood of missing any workdays for caregiving, and (3) the number of workdays missed due to caregiving.

RESULTS

Adult children with ADRD parents were more likely to be unemployed (OR = 1.80, p = 0.024) and 2.95 times more likely to miss work for caregiving (p = 0.002) than those with non-ADRD parents. The difference in the number of workdays missed for caregiving between children with and without ADRD parents was not significant. The incremental effects of having ADRD parents were estimated to be $4,510.29 ($1,702.09-$6,723.69) per person per year.

CONCLUSIONS

Having ADRD parents significantly increases the chances of unemployment and missing any workdays for caregiving, leading to higher lost labor productivity costs for adult children with ADRD parents.

Retention of American Indian and Alaska Native participants in the National Alzheimer's Coordinating Center Uniform Data Set

INTRODUCTION

The number of American Indian and Alaska Native (AI/AN) elders is expected to double by 2060. Thus it is imperative to retain AI/AN participants in longitudinal research studies to identify novel risk factors and potential targets for intervention for Alzheimer's disease and related dementias in these communities.

METHODS

The National Alzheimer's Coordinating Center houses uniformly collected longitudinal data from the network of National Institute on Aging (NIA)-funded Alzheimer's Disease Research Centers (ADRCs). We used logistic regression to quantify participant retention at 43 ADRCs, comparing self-identified AI/AN participants to non-Hispanic White (NHW) participants, adjusting for potential confounding factors including baseline diagnosis, age, sex, education, and smoking.

RESULTS

The odds of AI/AN participant retention at the first follow-up visit were significantly lower than those for NHW participants (adjusted odds ratio [aOR]: 0.599; 95%: 0.46-0.78; p < 0.001).

DISCUSSION

These results suggest the need for improved strategies to retain AI/AN participants, perhaps including improved researcher-community relationships and community engagement and education.

HIGHLIGHTS

American Indian and Alaska Native (AI/AN) research participants were retained to the first follow-up appointment at lower rates than non-Hispanic White (NHW) participants. AI/AN participants are retained at lower rates than NHW participants for long-term follow-up. The majority of AI/AN participants were not retained to the second follow-up visit.

Examining the role of race and quality of home health agencies in delayed initiation of home health services for individuals with Alzheimer's disease and related dementias (ADRD)

INTRODUCTION

We examined differences in the timeliness of the initiation of home health care by race and the quality of home health agencies (HHA) among patients with Alzheimer's disease and related dementias (ADRD).

METHODS

Medicare claims and home health assessment data were used for the study cohort: individuals aged ≥65 years with ADRD, and discharged from the hospital. Home health latency was defined as patients receiving home health care after 2 days following hospital discharge.

RESULTS

Of 251,887 patients with ADRD, 57% received home health within 2 days following hospital discharge. Black patients were significantly more likely to experience home health latency (odds ratio [OR] = 1.15, 95% confidence interval [CI] = 1.11-1.19) compared to White patients. Home health latency was significantly higher for Black patients in low-rating HHA (OR = 1.29, 95% CI = 1.22-1.37) compared to White patients in high-rating HHA.

DISCUSSION

Black patients are more likely to experience a delay in home health care initiation than White patients.

Early prediction of Alzheimer's disease and related dementias using real-world electronic health records

INTRODUCTION

This study aims to explore machine learning (ML) methods for early prediction of Alzheimer's disease (AD) and related dementias (ADRD) using the real-world electronic health records (EHRs).

METHODS

A total of 23,835 ADRD and 1,038,643 control patients were identified from the OneFlorida+ Research Consortium. Two ML methods were used to develop the prediction models. Both knowledge-driven and data-driven approaches were explored. Four computable phenotyping algorithms were tested.

RESULTS

The gradient boosting tree (GBT) models trained with the data-driven approach achieved the best area under the curve (AUC) scores of 0.939, 0.906, 0.884, and 0.854 for early prediction of ADRD 0, 1, 3, or 5 years before diagnosis, respectively. A number of important clinical and sociodemographic factors were identified.

DISCUSSION

We tested various settings and showed the predictive ability of using ML approaches for early prediction of ADRD with EHRs. The models can help identify high-risk individuals for early informed preventive or prognostic clinical decisions.

Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study

Background and Objective: Within-person variability in cognitive performance has emerged as a promising indicator of cognitive health with potential to distinguish normative and pathological cognitive aging. We use a smartphone-based digital health approach with ecological momentary assessments (EMA) to examine differences in variability in performance among older adults with mild cognitive impairment (MCI) and those who were cognitively unimpaired (CU). Method: A sample of 311 systematically recruited, community-dwelling older adults from the Einstein Aging Study (Mean age = 77.46 years, SD = 4.86, Range = 70-90; 67% Female; 45% Non-Hispanic White, 40% Non-Hispanic Black) completed neuropsychological testing, neurological assessments, and self-reported questionnaires. One hundred individuals met Jak/Bondi criteria for MCI. All participants performed mobile cognitive tests of processing speed, visual short-term memory binding, and spatial working memory on a smartphone device up to six times daily for 16 days, yielding up to 96 assessments per person. We employed heterogeneous variance multilevel models using log-linear prediction of residual variance to simultaneously assess cognitive status differences in mean performance, within-day variability, and day-to-day variability. We further tested whether these differences were robust to the influence of environmental contexts under which assessments were performed. Results: Individuals with MCI exhibited greater within-day variability than those who were CU on ambulatory assessments that measure processing speed (p < 0.001) and visual short-term memory binding (p < 0.001) performance but not spatial working memory. Cognitive status differences in day-to-day variability were present only for the measure of processing speed. Associations between cognitive status and within-day variability in performance were robust to adjustment for sociodemographic and contextual variables. Conclusion: Our smartphone-based digital health approach facilitates the ambulatory assessment of cognitive performance in older adults and the capacity to differentiate individuals with MCI from those who were CU. Results suggest variability in mobile cognitive performance is sensitive to MCI and exhibits dissociative patterns by timescale and cognitive domain. Variability in processing speed and visual short-term memory binding performance may provide specific detection of MCI. The 16-day smartphone-based EMA measurement burst offers novel opportunity to leverage digital technology to measure performance variability across frequent assessments for studying cognitive health and identifying early clinical manifestations of cognitive impairment.

Lysosome dysfunction as a cause of neurodegenerative diseases: Lessons from frontotemporal dementia and amyotrophic lateral sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are fatal neurodegenerative disorders that are thought to exist on a clinical and pathological spectrum. FTD and ALS are linked by shared genetic causes (e.g. C9orf72 hexanucleotide repeat expansions) and neuropathology, such as inclusions of ubiquitinated, misfolded proteins (e.g. TAR DNA-binding protein 43; TDP-43) in the CNS. Furthermore, some genes that cause FTD or ALS when mutated encode proteins that localize to the lysosome or modulate endosome-lysosome function, including lysosomal fusion, cargo trafficking, lysosomal acidification, autophagy, or TFEB activity. In this review, we summarize evidence that lysosomal dysfunction, caused by genetic mutations (e.g. C9orf72, GRN, MAPT, TMEM106B) or toxic-gain of function (e.g. aggregation of TDP-43 or tau), is an important pathogenic disease mechanism in FTD and ALS. Further studies into the normal function of many of these proteins are required and will help uncover the mechanisms that cause lysosomal dysfunction in FTD and ALS. Mutations or polymorphisms in genes that encode proteins important for endosome-lysosome function also occur in other age-dependent neurodegenerative diseases, including Alzheimer's (e.g. APOE, PSEN1, APP) and Parkinson's (e.g. GBA, LRRK2, ATP13A2) disease. A more complete understanding of the common and unique features of lysosome dysfunction across the spectrum of neurodegeneration will help guide the development of therapies for these devastating diseases.

Dietary fatty acids and risk of Alzheimer's disease and related dementias: Observations from the Washington Heights-Hamilton Heights-Inwood Columbia Aging Project (WHICAP)

Introduction:

High dietary intake of long chain, polyunsaturated fatty acids is associated with lower Alzheimer’s disease (AD) risk.

Methods:

Washington Heights-Hamilton Heights-Inwood Columbia Aging Project is a multiethnic, prospective observational study of aging and dementia among elderly (≥ 65 years). Dietary intake was measured using a food frequency questionnaire. Dietary short-, medium-, and long-chain fatty acid intakes were categorized by number of carbons and double bonds. Consensus AD diagnoses were made. Associations between AD risk and dietary fatty acid and cholesterol intakes were estimated using multivariable Cox proportional hazards regression models.

Results:

Of 2612 multiethnic women (67%) and men (baseline age 76.3 [6.4] years), 380 developed AD over an average 4.5 years follow-up. Lower risk of AD was associated with increasing intakes of docosahexaenoic acid (DHA; hazard ratio [HR] = 0.73, 95% confidence interval [CI]: 0.57 to 0.95, P = 0.018) and eicosapentaenoic acid (EPA; HR = 0.74, 95% CI: 0.57 to 0.95, P = 0.021), and longer AD-free survival (P < 0.05).

Discussion:

Higher intake of DHA and EPA are protective for AD.