Innovation in Aging最新文献

Background and objectives: Indicators of midlife health decline are needed to determine people's ability to engage in meaningful activities as they age and to implement early interventions to improve long-term health trajectories. Existing measures of physiological aging are unidimensional, expensive, difficult to collect, or focused on advanced disability, making it challenging to identify exposures that contribute to accelerate aging beginning in midlife.

Research design and methods: Using the Health and Retirement Study (HRS), we developed the Index of Aging in Midlife and Beyond (IAM+), a 10-item scale that accounts for a range of abilities and domains of health using survey items including multimorbidity, functional capacity, and self-reported cognitive, mental, physical, and sensory health. We evaluated overall reliability and variability. Then, we tested the association between physically demanding jobs in ages 51-56 with trajectories of IAM+ scores in midlife and old age. Finally, we considered predictive validity by examining associations between midlife IAM+ scores and later life activity and health outcomes.

Results: The IAM+ had acceptable reliability (alpha = 0.739-0.773). Distributions showed substantial variability. Physically demanding jobs were associated with higher IAM+ scores and accelerated increases in scores in midlife; differences in level, but not slopes, were sustained after retirement age. Higher IAM+ scores in midlife predicted reduced engagement in activities 10 years later, including early labor force exits, and predicted allostatic load, frailty, and mortality 20 years later.

Discussion and implications: The IAM+ is an acceptable and accessible new measure for evaluating health in midlife, with many applications for promoting active and productive engagement through later life.

The rapid aging of the global population presents complex challenges for health systems, families, and societies. Artificial intelligence (AI) technologies-from predictive analytics and conversational agents to robotic caregivers and remote monitoring-offer scalable solutions to support older adults throughout their life courses. This article examines the evolving landscape of AI-enabled care for aging populations, structured around the geriatric 4Ms: what Matters, Medication, Mentation, and Mobility. We synthesize current evidence on the application of AI in personalized medicine, cognitive support, fall detection, and chronic disease management while exploring the cultural, economic, and policy contexts that influence technology adoption. The market for age-related technology is expanding; however, disparities in access, digital literacy, and algorithmic bias risk exacerbating inequities. We identify persistent gaps in implementation, including the underrepresentation of diverse older adults in training data sets, limited longitudinal studies, and a lack of integration across diagnostic and therapeutic systems. We propose a future research agenda centered on five priorities: (1) establishing life-course AI research agendas, (2) promoting inclusive and participatory development processes, (3) advancing gerontological design principles, (4) expanding AI literacy across the aging services workforce, and (5) developing robust ethical and regulatory infrastructures. The article calls for interdisciplinary collaboration among gerontologists, engineers, policymakers, and ethicists to ensure that AI innovations are safe, equitable, and responsive to the lived experiences of older adults. Ultimately, we argue that AI must be implemented not as isolated tools but as components of comprehensive care ecosystems that support aging in place, reduce caregiver burden, and preserve human dignity.

Background and objectives: Elder abuse (EA) conceptualizations are evolving from conventional binary understandings toward a severity lens that more accurately captures the spectrum of victim experiences and complexity of EA intervention. Although momentum behind a focus on severity has grown, our understanding of EA severity risk factors is methodologically limited by studies using clinical convenience samples and/or cross-sectional designs. Informed by the Contextual Theory of Elder Abuse, this article sought to advance the state of science surrounding EA severity risk factors using data from a longitudinal, population-based design and examining factors from several levels of ecological influence.

Research design and methods: Using the Canadian Longitudinal Study on Aging, this study analyzed a sample of EA victims (n = 2,364) reporting past-year emotional/psychological, physical, and/or financial abuse, who completed baseline and follow-up waves of data collection. EA victimization was assessed using validated tools and behaviorally defined items describing specific mistreatment behaviors. Calculation of EA severity for each subtype combined dimensions of behavioral multiplicity (number of mistreatment behaviors) and frequency. Independent change variables were used to confirm the direction of change underlying potential risk factors prior to EA victimization. Multinomial logistic regression was used to identify factors associated with increased levels of EA severity.

Results: Across subtypes, the most consistent risk factors for heightened EA severity were perpetrator cohabitation and the older adult's experience of child maltreatment. Other risk factors were identified across physical, psycho-emotional, social, and sociocultural domains. Risk profiles varied across mistreatment subtypes.

Discussion and implications: This study represents the most methodologically rigorous examination of EA severity risk conducted to date. Findings will enhance our capacity to identify EA victims in particularly harmful scenarios and inform mechanistically driven interventions designed to reduce the magnitude of the problem, as well as practice decisions related to case prioritization, triaging, and risk assessment.

Background and objectives: Alzheimer's disease (AD) and AD-related dementias (ADRD) are expected to affect over 100 million people by 2050, placing a significant strain on public health systems. Social determinants of health (SDoH), which include factors such as socioeconomic conditions and environment, play a crucial role in AD risk. Despite growing evidence, the understanding of SDoH's impact on AD remains limited.

Research design and methods: This study leverages large language models and knowledge graphs (KGs) to extract AD-related SDoH knowledge from literature and electronic health records (EHR). We integrate this knowledge into biological research on AD through KG construction and graph deep learning, performing KG-link predictions validated by multimodal biological data from single-cell RNA-seq and proteomics.

Results: We generated an SDoH knowledge graph with around 92k triplets, integrating literature and EHR data. In various link prediction experiments, we observed higher accuracy when integrating SDoH into knowledge graphs. Additionally, exploratory predictions uncovered potential SDoH-gene interactions, many of which were validated through differential expression analysis using proteomics and RNA-seq data.

Discussion and implications: This novel KG-based analysis enhances link prediction in AD-related biomedical networks by integrating SDoH and biological knowledge. Our findings highlight the potential interaction between social determinants and biological factors in AD, offering insights into more personalized and socially aware healthcare interventions.

Background and objectives: While research on transgender older adults and health is growing, gaps remain about transgender older adults of color, immigrants, and other groups experiencing multiple forms of marginalization who are shaped by concurring experiences of oppression across the life course. This article aims to address these gaps by examining health challenges and supports among transgender older adults-many of whom are racially minoritized and immigrants-through an Equitable Aging in Health framework.

Research design and methods: This community-driven study incorporates qualitative data from 37 transgender older adults from a larger study of 23 focus groups with 208 lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQIA+) older adults in California to examine challenges, thriving and surviving strategies, and recommendations regarding health, housing, social services, and caregiving. Data foreground experiences of transgender older adults who are racially underrepresented, immigrants, and have low incomes.

Results: Transgender older adults identified challenges related to healthcare access, housing, employment, economics, and violence that often intersected with disability and aging. Transgender older Latina immigrants experienced elevated challenges related to language barriers, immigration status, and discrimination. Supports included community connections, financial and legal assistance, educational workshops, and homesharing programs. Healthcare access, health experiences, and overall well-being were intricately tied to challenges and supports in housing, social services, healthcare systems, and employment that existed at micro, mezzo, and macro levels.

Discussion and implications: The Equitable Aging in Health framework helps illuminate how challenges and supports described by transgender older adults, including immigrants and older adults who are racially minoritized, can shape health-related experiences for transgender older adults. Policies, services, and programs targeting transgender older adults, thus, would benefit from a multi-level, multi-systems approach.

Background and objectives: Chewing disability may contribute to depressive symptoms in older adults, but causal pathways, accounting for time-varying confounding factors, remain unexplored. Previous research shows an association between chewing disability, loneliness, and depression. This study examines the causal relationship between chewing disability and clinically significant depressive symptoms (CSDS) and whether loneliness mediates this association among older adults.

Research design and methods: In total, 1,277 participants aged ≥60 years, without CSDS at baseline, were selected from a nationally representative study of older adults in Singapore (2009-2015, three waves). Marginal structural models were utilized to estimate total and indirect effects of chewing disability and CSDS over time, where loneliness was treated as a mediator.

Results: Across the study period, 10.3% developed CSDS, 40.7% experienced loneliness, and 33.6% had chewing disability. Individuals with chewing disability had a 48% higher risk of CSDS (RR: 1.48, 95% CI: 1.15-1.82), and the indirect effect through loneliness was 26% (RR: 1.26, 95% CI: 0.99-1.53; 17.3% of the total effect). Nonetheless, the estimates varied by the operationalization of chewing disability and loneliness. A broader definition of chewing disability showed stronger total effects (RR: 1.57, 95% CI: 1.24-1.91), while a stricter loneliness threshold had a greater indirect effect (RR: 1.70, 95% CI: 1.30-2.09; 21.8% of the total effect).

Discussion and implications: Chewing disability increases the risk of CSDS among older adults, with partial mediation by loneliness. Further research on oral rehabilitative interventions that improve chewing function and mitigate depressive symptoms in older adults is needed.

Background and objectives: Perceived stress is associated with poor health outcomes, including accelerated cognitive decline and increased risk for dementia. Prior research suggests that emotion regulation may determine the extent to which stress impairs cognition with age. This study extends this work by examining the moderating role of two emotion regulation strategies (cognitive reappraisal; expressive suppression) on the relationship between perceived stress and cognitive decline over 10 years in a sample of older adults.

Research design and methods: The sample was drawn from the Midlife in the United States Study (MIDUS; N = 468; Mean age at baseline = 60.24), providing measures of perceived stress, emotion regulation, and cognition at baseline and follow-up (episodic memory; executive functioning). Moderation analyses with 5,000 bootstrapped samples were conducted in the PROCESS Macro and statistically adjusted for age, sex, education, household income, medications, and baseline cognition.

Results: Results revealed that perceived stress interacted with expressive suppression to predict later episodic memory performance. As stress levels increased, only individuals endorsing regular use of expressive suppression exhibited significant memory decline. By contrast, cognitive reappraisal did not significantly moderate relationships between stress and later cognition.

Discussion and implications: Findings highlight that habitual suppression of emotional expression may amplify the consequences of perceived stress on memory decline in late life. Promotion of adaptive emotion regulation may play a role in mitigating the effects of stress on cognitive outcomes among older adults.

Background and objectives: The evidence-based Adult Day Services (ADS) Plus program, delivered by ADS staff to caregivers, offers dementia education, support, and strategies to manage care challenges and has been shown in randomized trials to decrease caregiver depressive symptoms and increase ADS utilization. This study examines costs, cost savings, and caregiver willingness to pay (WTP) and ability to pay (ATP) for this evidence-based program.

Research design and methods: In a 34-site cluster-randomized trial (16 ADS Plus sites; 18 ADS-only usual care sites) involving 203 caregivers, we surveyed program delivery costs, payer-perspective costs (healthcare utilization, formal care/social services utilization), and societal-perspective costs (caregiver time + payer costs) at baseline and 12-months. Enrollees were caregivers who reported on their outcomes and those of the person living with dementia. Costs were calculated using unit costs or appropriate wage rates. We assessed mean per-dyad costs and the between-group difference in mean change in payer and societal costs from baseline to 12-months. Multilevel mixed models considered clustering, and caregivers' WTP and ATP were evaluated.

Results: ADS Plus delivery costs were $433/dyad over 12-months. From the payer perspective, ADS Plus resulted in nonstatistically significant but policy-significant cost savings of $1,501 (95% CI: -$2,771 to $4,804). From a societal perspective, ADS Plus led to cost savings of $1,185 (95% CI: -$11,187 to $7,036). ADS Plus caregivers' median per-session WTP was $90 at baseline and $100 at 12-months, compared to $50 and $100 for usual care. ADS Plus caregivers' median ATP was $31.50 at baseline and $50 at 12-months, versus $25 at both timepoints for usual care.

Discussion and implications: Adult Day Services Plus yielded meaningful cost savings, though statistical significance was not achieved. Caregivers were WTP and ATP toward ADS Plus sessions, which could offset program costs. This study elucidates the financial implications of incorporating caregiver support into community-based dementia care programs.

Background and objectives: Population aging affects health and social care needs. Although its effects on healthcare needs have been widely discussed, less has been said about its implications on social care needs, even though the consequences of living with chronic conditions are related to functional decline, disability, dependency, and mobility limitation. This study aims to identify trajectories of healthcare and social care needs after the onset of chronic conditions, as well as to explore through cross-country comparisons how demographic, socioeconomic, living arrangements, and health-related dimensions explain individuals' trajectories.

Research design and methods: Using data from the Survey of Health, Ageing and Retirement in Europe, we analyzed trajectories of 16,718 individuals aged 50 and above from 10 European countries through sequence analysis. Multinomial regression models were fitted to understand the factors that explained these trajectories.

Results: This study identified four trajectories after the onset of chronic conditions: (a) "Persistent multimorbidity and social care needs," (b) "Persistent multimorbidity without social care needs," (c) "One chronic condition and social care needs," and (d) "One chronic condition without social care needs and some recoveries." The models present divergences in individuals' characteristics, including demographic and socioeconomic aspects, as well as differences by country, related to each trajectory.

Discussion and implications: By acknowledging trajectories within health and social care needs, we showed the challenges posed by aging processes, which require tailored-made and person-centered services oriented towards preventing and postponing the onset of chronic conditions as well as dealing with their consequences on individuals' daily lives.

Background and objectives: Despite the rapid growth of older Asian American populations, little is known about their retention and its associated factors in longitudinal aging studies, partially due to the limited longitudinal studies among this population. This study addresses this critical gap by examining key predictors of attrition in this understudied population.

Research design and methods: Using data from the Population Study of Chinese Elderly in Chicago (PINE), a large longitudinal epidemiological study of older Chinese immigrants in the United States (US), we analyzed the effect of sociodemographic, immigration, health, and psychosocial characteristics on attrition status and various attrition patterns.

Results: High levels of acculturation and longer length of stay in the US were associated with a higher likelihood of attrition. Also, participants with higher levels of educational attainment and loneliness were more likely to drop out of the study earlier. In addition, participants with lower income were more likely to remain in the study.

Discussion and implications: These results show unique attrition dynamics in older Asian immigrants, where acculturation and education paradoxically increase attrition risk. These findings highlight the need for tailored retention strategies to enhance continued participation in longitudinal aging studies among older Asian American immigrants.